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17 pages, 2619 KB

Open AccessProceeding Paper

Unsupervised Categorization of Hysteresis Loops: A Comparative Study of Expert-Driven Feature Engineering vs. Deep 1D-Convolutional Autoencoders

by Ivelin Karageorgiev, Sevil Ahmed-Shieva, Nikola Shakev and Ivaylo Minev

Eng. Proc. 2026, 150(1), 1; https://doi.org/10.3390/engproc2026150001 - 14 Jul 2026

Viewed by 239

Abstract

Hysteresis defines a system’s state as a function of its historical trajectory, manifesting as path-dependent loops where variables diverge based on the direction of change. Intrinsic to both information storage and irreversible thermodynamic dissipation, this phenomenon serves as a critical fingerprint for characterizing [...] Read more.

Hysteresis defines a system’s state as a function of its historical trajectory, manifesting as path-dependent loops where variables diverge based on the direction of change. Intrinsic to both information storage and irreversible thermodynamic dissipation, this phenomenon serves as a critical fingerprint for characterizing complex behaviors and dynamic system responses. The automated classification and labeling of dense hysteresis signals is essential for systems engineering, electronics, bio-signal processing, and meteorology. This study presents a comprehensive comparison between two unsupervised learning pipelines, to which a main objective is to discover the capabilities for phenotype discovery between automated feature extraction and expert-driven feature engineering. These methodologies are examined by clustering 7736 respiratory cycles from critical care patients who have undergone invasive mechanical ventilation. Methodology I utilizes the extraction of 17 geometric and spectral features, reduced via Principal Component Analysis (PCA) to ease the choice of high variance parameters for subsequent clustering. Methodology II proposes a Deep Learning (DL) framework utilizing a 1D-convolutional autoencoder (CAE) for automated feature discovery. Both methods utilize UMAP and HDBSCAN for the final clustering stage. After evaluation both models performed with high trustworthiness (0.9974; 0.9853) and Silhouette Scores of 0.6441 and 0.6415. Here, both methodologies obtained a surprisingly low noise ratio (1.5% and 0.74%) by the aformentioned HDBSCAN. The strategy of narrowing discrete features allows for better model interpretability, and the resulting similarity measures reasoned trough a Davies–Bouldin Index are higher. However, a peculiar difference was observed in favor to the automated extraction (CAE), where the method assessed a better quality of clustering when compared for dispersion between clusters and the dispersion of reference clusters. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 15672 KB

Open AccessProceeding Paper

Assessment of Non-Destructive Testing Techniques for Detecting Fatigue Cracks in Railway Suspension Pivot Pins

by Ivanka Delova, Raycho Raychev, Margarit Lozev, Yordan Mirchev, Tsvetomir Borisov and Stefan Manov

Eng. Proc. 2026, 150(1), 2; https://doi.org/10.3390/engproc2026150002 - 14 Jul 2026

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Abstract

This study investigates the capabilities of modern ultrasonic non-destructive testing (NDT) methods for the detection and sizing of fatigue cracks in hinge bolts used in railway transport. Experimental investigations were conducted using immersion ultrasonic testing combined with advanced signal processing techniques, including PAUT, [...] Read more.

This study investigates the capabilities of modern ultrasonic non-destructive testing (NDT) methods for the detection and sizing of fatigue cracks in hinge bolts used in railway transport. Experimental investigations were conducted using immersion ultrasonic testing combined with advanced signal processing techniques, including PAUT, FMC/TFM, and FMC/PCI. Artificially introduced erosion notches ranging in size from 0.025 mm to 23 mm were used to simulate fatigue defects. The probability of defect detection was evaluated through Hit/Miss analysis and determination of the a90/95 parameter. The results indicate that the FMC/TFM method provides the highest sensitivity for the detection of small defects, while the PAUT technique demonstrates the highest accuracy in defect sizing. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 1092 KB

Open AccessProceeding Paper

Deep Learning Estimation of Mechanical Power in Pressure-Controlled Ventilation Using a 1D CNN–Bidirectional LSTM Model

by Ralitsa Petrova, Sevil Ahmed-Shieva, Nikola Shakev and Ivaylo Minev

Eng. Proc. 2026, 150(1), 3; https://doi.org/10.3390/engproc2026150003 - 15 Jul 2026

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Abstract

Mechanical Power (MP) is a critical determinant of Ventilator-Induced Lung Injury (VILI), yet its real-time calculation in pressure-controlled ventilation (PCV) remains a challenge due to the complexity of existing analytical formulas and the inconsistent availability of ICU sensor data. This study proposes a [...] Read more.

Mechanical Power (MP) is a critical determinant of Ventilator-Induced Lung Injury (VILI), yet its real-time calculation in pressure-controlled ventilation (PCV) remains a challenge due to the complexity of existing analytical formulas and the inconsistent availability of ICU sensor data. This study proposes a hybrid deep learning architecture, combining a One-Dimensional Convolutional Neural Network (1D CNN) with Bidirectional Long Short-Term Memory (BiLSTM) layers, to estimate MP from 11 standard respiratory parameters. Utilizing research sources from the high-fidelity database VitalDB, the model was trained and validated against four established MP equations. To ensure clinical robustness, a feature-masking augmentation strategy was implemented to simulate signal inconsistencies and sensor failures. The results demonstrate exceptional predictive accuracy, achieving a peak

R^{2}

of 0.9994 and a symmetric Mean Absolute Percentage Error (sMAPE) between 3.80% and 4.87% across all target equations. This “sensor-fusion” approach effectively captures both spatial features and temporal dynamics, providing a reliable, real-time decision-support tool for personalized, lung-protective ventilation strategies. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 1130 KB

Open AccessProceeding Paper

A Governance-Aware, Privacy-Preserving, Event-Driven Conceptual Model for Supply Chain Traceability

by Aleksandar Panayotov, Ivan Lambov and Mariana Atanasova

Eng. Proc. 2026, 150(1), 4; https://doi.org/10.3390/engproc2026150004 - 15 Jul 2026

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Abstract

Supply chain traceability often fails in practice because relevant records are scattered across production, warehouse, transport, laboratory, and document systems. When a recall or audit is needed, firms must manually collect and reconcile evidence from many sources. Existing standards and blockchain platforms address [...] Read more.

Supply chain traceability often fails in practice because relevant records are scattered across production, warehouse, transport, laboratory, and document systems. When a recall or audit is needed, firms must manually collect and reconcile evidence from many sources. Existing standards and blockchain platforms address parts of this problem, but prior work still reports recurring weaknesses in governance, confidentiality management, interoperability, and performance measurement. This paper presents a governance-aware, privacy-preserving, event-driven conceptual model for supply chain traceability. The model uses five event types—Create, Transform, Transfer, Verify, and Recall—linked through explicit lineage. It stores compact signed event headers on-ledger and anchors detailed off-ledger payloads and governance policy text through hashes. It also links data-sharing choices to consortium governance, defines validation invariants, embeds key performance indicators, and produces two regulator-ready outputs: a product passport and an audit pack. The contribution is a standards-informed conceptual artifact that integrates event semantics, provenance reconstruction, selective disclosure, governance, validation, performance measurement, and regulator-ready outputs in one cross-sector traceability model. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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21 pages, 2420 KB

Open AccessProceeding Paper

Design and Implementation of a FIWARE-Based Education Smart Data Model for University Campus Management

by Galia Nedeltcheva, Tsvetelin Stefanov, Denis Chikurtev and Eugenia Kovatcheva

Eng. Proc. 2026, 150(1), 5; https://doi.org/10.3390/engproc2026150005 - 15 Jul 2026

Viewed by 403

Abstract

Smart campus development is increasingly associated with the combined use of IoT technologies, artificial intelligence, cloud infrastructures, and large-scale data analytics in higher education. Despite this progress, many existing data models are not well-suited to the educational domain, particularly when interoperability and real-time [...] Read more.

Smart campus development is increasingly associated with the combined use of IoT technologies, artificial intelligence, cloud infrastructures, and large-scale data analytics in higher education. Despite this progress, many existing data models are not well-suited to the educational domain, particularly when interoperability and real-time analytical capabilities are required. To address this limitation, the study proposes a Smart Campus Education Data Model (SCEDM), which can be integrated into any FIWARE-based platform. The model is organized as a layered architecture that includes data acquisition, processing, and storage; analytics and decision support; application presentation; and security. The proposed model is not presented only at a conceptual level; it is also validated in a containerized FIWARE environment built around the Orion-ld Context Broker and NGSI-ld specifications. The SCEDM model is validated in a system that supports real-time state management across multiple campus domains. The model’s practical operation is validated across several experimental scenarios, including a simulation of a lecture process, classroom occupancy monitoring, and automated notifications to external platforms. In addition, the study compares five international case studies from different contexts. The comparison shows that, despite differences across local settings, similar benefits can be observed in campus operations and learning conditions. The study also recognizes several continuing challenges in the development of smart campuses, including interoperability, long-term scalability, data governance, privacy protection, stakeholder engagement, and financial sustainability. In response to these issues, the authors propose practical design guidelines alongside strategic recommendations for adoption at the institutional level. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 259 KB

Open AccessProceeding Paper

Blockchain for EUPHEMIA Market Transparency

by Tsvetomir Gospodinov, Mariana Atanasova and Eliza Stefanova

Eng. Proc. 2026, 150(1), 6; https://doi.org/10.3390/engproc2026150006 - 16 Jul 2026

Viewed by 203

Abstract

EUPHEMIA, the Pan-European day-ahead electricity market-coupling algorithm, operates in a centralized manner that restricts independent auditability and has been characterized as pseudo-transparent. We propose a blockchain-based architecture that improves the transparency and verifiability of the market-coupling process while preserving participant confidentiality. It combines [...] Read more.

EUPHEMIA, the Pan-European day-ahead electricity market-coupling algorithm, operates in a centralized manner that restricts independent auditability and has been characterized as pseudo-transparent. We propose a blockchain-based architecture that improves the transparency and verifiability of the market-coupling process while preserving participant confidentiality. It combines off-chain computation with selective on-chain publication and treats the three principal data categories of the EUPHEMIA pipeline separately: order books, network constraints, and clearing outputs. Zero-knowledge proofs utilizing zk-STARKs are employed to verify the integrity of the order book aggregation process and specific network-constraint sub-processes, whereas Merkle commitments ensure tamper-evident anchoring of publicly disclosed data. zk-STARKs are selected over CRS-based alternatives to eliminate the trusted-setup governance overhead associated with EUPHEMIA’s multi-jurisdictional structure. The estimated AIR trace size reaches approximately 2,225,000 rows in the worst-case NEMO (EPEX SPOT) scenario. A correction proof generated by the Regional Coordination Centre (RCC) requires an AIR of 641 trace rows when a binding network constraint exceeds its threshold during the review of Transmission System Operator (TSO) submissions. This trace size corresponds to an estimated proving time of 1 to 30 s based on reported STARK prover throughput. End-to-end verification of welfare maximization remains infeasible due to the lack of a complete public algorithm specification. Preliminary calibrated estimates are provided, and full empirical benchmarking remains as future work. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 2412 KB

Open AccessProceeding Paper

An Innovative Approach to the Management of Industrial Equipment Subject to Maintenance

by Rocco Ricci, Enrico Marsilio, Vito Santarcangelo, Gianfranco Piscopo and Massimiliano Giacalone

Eng. Proc. 2026, 150(1), 7; https://doi.org/10.3390/engproc2026150007 - 16 Jul 2026

Viewed by 230

Abstract

This paper presents an innovative method and information system developed by Tre Esse Srl for the integrated management of industrial equipment. The proposed solution supports asset management, operator training, maintenance recording, and the assessment of plant reliability. Its core component is the “SSS” [...] Read more.

This paper presents an innovative method and information system developed by Tre Esse Srl for the integrated management of industrial equipment. The proposed solution supports asset management, operator training, maintenance recording, and the assessment of plant reliability. Its core component is the “SSS” marker, which combines QR Code, Data Matrix, and PDF417 technologies through a dedicated encoding and decoding logic. The combined marker expands storage capacity and enables information to be distributed across different barcode types according to integrity and confidentiality requirements. The approach is particularly relevant in ATEX environments, where network connectivity may be unavailable or restricted and maintenance information must remain accessible offline. Encryption and spatially distributed encoding are used to protect confidential industrial information and support compliance with data-protection and industrial-secrecy requirements. The system integrates the markers with a cloud platform for equipment records, maintenance operations, and reliability monitoring, providing a practical bridge between offline identification and Industry 4.0 asset-management processes. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 3109 KB

Open AccessProceeding Paper

Investigation of the Influence of the k-Factor Parameter on the Quality of Printed Parts Using Ingeo Biopolymer 4043D

by Blagovest Bankov, Zdravko Kuzmanov, Tasin Tasinov and Todor T. Todorov

Eng. Proc. 2026, 150(1), 8; https://doi.org/10.3390/engproc2026150008 - 16 Jul 2026

Viewed by 348

Abstract

This study examines the influence of the dynamic pressure control parameter in the nozzle during melt deposition onto the build platform (k-Factor), also known as Linear Advance or Pressure Advance in different firmware implementations, on the quality of parts produced using the Fused [...] Read more.

This study examines the influence of the dynamic pressure control parameter in the nozzle during melt deposition onto the build platform (k-Factor), also known as Linear Advance or Pressure Advance in different firmware implementations, on the quality of parts produced using the Fused Deposition Modeling (FDM) technology. The investigation was conducted based on printed test specimens made from Ingeo Biopolymer 4043D, with k-Factor values varied in the range of 0.01 to 0.20 under comparable process conditions. Dimensional measurements were performed along the X and Y axes, and visual analysis was carried out to identify defects in the specimens. The results from statistical analysis and visual inspection reveal a clear correlation between the k-Factor value and part quality. An optimal balance between dimensional and geometric stability was achieved at k-Factor = 0.04, identifying it as a suitable value for the material and process conditions used. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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7 pages, 352 KB

Open AccessProceeding Paper

Evaluating Compliance Approaches in Data Analysis Between Teams and Artificial Intelligence

by Saverio Gianluca Crisafulli, Angelo Riccardi, Gianfranco Piscopo and Maria Longobardi

Eng. Proc. 2026, 150(1), 9; https://doi.org/10.3390/engproc2026150009 - 16 Jul 2026

Viewed by 197

Abstract

The purpose of this paper is to present and evaluate some compliance-oriented approaches designed and patented by the company Elabordati of Matera, which operates in the business services sector with particular reference to administrative, accounting and tax services, together with a comparison with [...] Read more.

The purpose of this paper is to present and evaluate some compliance-oriented approaches designed and patented by the company Elabordati of Matera, which operates in the business services sector with particular reference to administrative, accounting and tax services, together with a comparison with approaches generated by the generative artificial intelligence ChatGPT, with the aim of making a comparison and providing insights to the academic world in terms of data analysis. The two approaches highlighted concern the assessment of the mandatory nature of a DPO, presented in the first part of the paper, and the assessment of enterprise value, presented in the same way in the second part of this paper. Finally, for each approach presented, a subjective comparison is made by the generative artificial intelligence itself. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 13095 KB

Open AccessProceeding Paper

A Hybrid Synthetic Dataset Generation for Robust Document Recognition Using Image Rendering and Domain Randomization

by Plamen Nakov, Petar Petrov, Georgi Kotov, Milena Lazarova and Ognyan Nakov

Eng. Proc. 2026, 150(1), 10; https://doi.org/10.3390/engproc2026150010 - 16 Jul 2026

Viewed by 294

Abstract

Automated recognition of identity documents is a critical component in digital identity verification systems. The development of robust recognition models is often constrained by the limited availability of large, diverse, high-quality, and publicly accessible ID card datasets. Collecting and annotating real-world ID card [...] Read more.

Automated recognition of identity documents is a critical component in digital identity verification systems. The development of robust recognition models is often constrained by the limited availability of large, diverse, high-quality, and publicly accessible ID card datasets. Collecting and annotating real-world ID card images is time-consuming, and often restricted due to privacy, legal, and security concerns. The paper proposes a novel approach for generating a large-scale synthetic dataset for ID card recognition by merging real ID card images with a texture dataset through a structured data fusion pipeline that introduces realistic visual variations as illumination effects, geometric distortions, and noise patterns while preserving the semantic integrity of the original ID card content. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 1981 KB

Open AccessProceeding Paper

Architecture and Performance Evaluation of Real-Time Facial Recognition for Access Control

by Fatima Sapundzhi, Ramazan Ertuğrul Aydoğan, Slavi Georgiev and Nikita Nikitov

Eng. Proc. 2026, 150(1), 11; https://doi.org/10.3390/engproc2026150011 - 17 Jul 2026

Viewed by 208

Abstract

The current study presents the design, implementation, and evaluation of a real-time face recognition system for automated access control. The system uses Python libraries to build an accurate and secure identification platform that incorporates dedicated stages for facial data processing and recognition. During [...] Read more.

The current study presents the design, implementation, and evaluation of a real-time face recognition system for automated access control. The system uses Python libraries to build an accurate and secure identification platform that incorporates dedicated stages for facial data processing and recognition. During data preparation, 128-dimensional facial embedding vectors are generated for authorized users through a command-line interface and protected using authenticated encryption. In real-time operation, the system captures video frames, detects faces, and verifies identities by matching them against the encrypted database. Experimental results demonstrate high recognition accuracy, real-time throughput, and robust performance, highlighting the system’s suitability for GDPR-oriented deployment in small institutional environments. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 4706 KB

Open AccessProceeding Paper

Simulation and Experimental Investigation of an SRM Drive in Motoring Mode

by Tsvetana Grigorova, Georgi Bodurov and Dimitar Yankov

Eng. Proc. 2026, 150(1), 12; https://doi.org/10.3390/engproc2026150012 - 17 Jul 2026

Viewed by 198

Abstract

The paper presents a simulation and experimental study of a three-phase 12/8 Switched Reluctance Motor (SRM) operating in motoring mode. The operation of the asymmetric bridge converter is analyzed, and the mathematical equations describing the phase-current change under various commutation states in soft-switching [...] Read more.

The paper presents a simulation and experimental study of a three-phase 12/8 Switched Reluctance Motor (SRM) operating in motoring mode. The operation of the asymmetric bridge converter is analyzed, and the mathematical equations describing the phase-current change under various commutation states in soft-switching mode (modulation of the upper transistors) are derived. An analytical model is used to examine the energy exchange between the battery, the power switches, and the phase inductance. For the purposes of the study, a simulation model was developed in the MATLAB/Simulink R2025b environment, including models of the battery, the power converter, and the SRM. Simulation studies were conducted under various load conditions and phase current values, yielding time-domain waveforms of the phase currents and voltages, as well as the electromagnetic torque. Experimental waveforms of the phase current and voltage, measured under conditions corresponding to those in the simulation studies, are presented. A comparative analysis was performed between the simulation and experimental results, with tabular and graphical dependencies presented, and the relative error between them determined. The results obtained show good agreement between the simulation model and the actual system, which confirms the applicability of the developed approach for the analysis and optimization of SRM drives. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 5521 KB

Open AccessProceeding Paper

Investigation of the Mechanical Properties and Electromagnetic Damping of Polymer Composites Reinforced with Carbon Particles and Cenospheres

by Boyan Dochev, Desislava Dimova, Yavor Boychev, Kamen Vasilev, Filip Ublekov and Nikola Tomanov

Eng. Proc. 2026, 150(1), 13; https://doi.org/10.3390/engproc2026150013 - 17 Jul 2026

Viewed by 236

Abstract

In this work, composites based on thermosetting polymers (epoxy, polyester and vinylester resins) are presented, in which carbon particles and cenospheres are embedded. The influence of combinations of multi-walled carbon nanotubes (MWCNTs) and cenospheres, as well as amorphous carbon and cenospheres, on the [...] Read more.

In this work, composites based on thermosetting polymers (epoxy, polyester and vinylester resins) are presented, in which carbon particles and cenospheres are embedded. The influence of combinations of multi-walled carbon nanotubes (MWCNTs) and cenospheres, as well as amorphous carbon and cenospheres, on the mechanical properties and electromagnetic attenuation in (part of) the X-band range (812 GHz) of the developed composites has been studied. It has been established that the used combinations of carbon particles and cenospheres have the greatest positive effect on the mechanical properties of the composites based on vinylester resin. The developed materials demonstrate effectiveness for electromagnetic protection in the X-band range. The combination of a polymer matrix and appropriate fillers leads to significant attenuation of the radio frequency signal. The presented composites are suitable materials for integration into various defense systems—from coatings to structural elements with functional purposes. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 8019 KB

Open AccessProceeding Paper

Emissions and Dynamics: The Role of Software in Similar Automotive Platforms

by Hristo Konakchiev, Iliyan Damyanov and Rosen Miletiev

Eng. Proc. 2026, 150(1), 14; https://doi.org/10.3390/engproc2026150014 - 17 Jul 2026

Viewed by 253

Abstract

The development of internal combustion engines aims to maximize the combustion process energy, achieve the highest possible efficiency, and reduce harmful emissions released into the environment, while also improving power output. In this regard, here we have presented two pairs of vehicles which [...] Read more.

The development of internal combustion engines aims to maximize the combustion process energy, achieve the highest possible efficiency, and reduce harmful emissions released into the environment, while also improving power output. In this regard, here we have presented two pairs of vehicles which have mechanically similar internal combustion engines but either different environmental or dynamic performance characteristics. The first example is of upgrading an internal combustion engine from Euro 4 to Euro 5. The second example demonstrates a 23% increase in power while maintaining the same emission parameters. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 372 KB

Open AccessProceeding Paper

AutoSignal: A Dart-Based Programming Paradigm for Automatic Component Connection via a Signal–Slot Architecture

by George Pashev and Silvia Gaftandzhieva

Eng. Proc. 2026, 150(1), 15; https://doi.org/10.3390/engproc2026150015 - 17 Jul 2026

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Abstract

Managing event-driven communication in large reactive codebases remains a persistent challenge: developers routinely write repetitive wiring code that becomes difficult to trace and maintain. We present AutoSignal, a programming paradigm for the Dart ecosystem that automates component interconnection through a signal–slot architecture based [...] Read more.

Managing event-driven communication in large reactive codebases remains a persistent challenge: developers routinely write repetitive wiring code that becomes difficult to trace and maintain. We present AutoSignal, a programming paradigm for the Dart ecosystem that automates component interconnection through a signal–slot architecture based on name and data-type matching. To improve scalability and limit unintended side effects in large applications, the framework implements hierarchical namespace isolation and deterministic reactivity through topological sorting of dependency graphs. In a reference contact-management application, AutoSignal reduced connection-specific code by 47%, unintended signal propagation by 32%, and average propagation latency by 28% relative to manual wiring. The framework also integrates with Flutter through reactive UI primitives such as specialized hooks and builders. These results indicate that AutoSignal is a practical, type-aware option for building maintainable event-driven applications in the Dart/Flutter ecosystem. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 582 KB

Open AccessProceeding Paper

The Invisible Guardian: Big Data, Behavioral Biometrics, and the Era of Continuous Authentication

by Hadi Fares, Teodora Bakardjieva and Antonina Ivanova

Eng. Proc. 2026, 150(1), 16; https://doi.org/10.3390/engproc2026150016 - 17 Jul 2026

Viewed by 252

Abstract

Traditional authentication systems rely mainly on static login checkpoints such as passwords or one-time verification. However, the expansion of cloud services, mobile devices, and distributed digital platforms has exposed significant limitations in these approaches. Modern cyberattacks increasingly exploit credential theft, phishing, and session [...] Read more.

Traditional authentication systems rely mainly on static login checkpoints such as passwords or one-time verification. However, the expansion of cloud services, mobile devices, and distributed digital platforms has exposed significant limitations in these approaches. Modern cyberattacks increasingly exploit credential theft, phishing, and session hijacking in order to bypass login-based security mechanisms. This study examines the use of behavioral biometrics and data-driven analytics in continuous authentication systems that verify user identity throughout an active session. Behavioral interaction signals such as keystroke dynamics, cursor movement patterns, touchscreen gestures, and device usage characteristics can form distinctive behavioral profiles for individual users. Machine-learning models can analyze these signals to detect deviations from established behavioral patterns that may indicate unauthorized access. The paper develops a conceptual framework for continuous behavioral authentication that integrates behavioral monitoring, anomaly detection, and scalable data-processing infrastructures. The analysis highlights both the cybersecurity benefits of behavioral authentication and the challenges related to large-scale behavioral data collection, including privacy protection and responsible data governance. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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13 pages, 1186 KB

Open AccessProceeding Paper

Automated Assessment of Cognitive Levels in Bloom’s Taxonomy Through RAG-Based Architecture with LLMs

by Anastasia Vangelova and Veska Gancheva

Eng. Proc. 2026, 150(1), 17; https://doi.org/10.3390/engproc2026150017 - 17 Jul 2026

Viewed by 275

Abstract

This paper presents a RAG-based architecture with a large language model for automated assessment of student responses, in which Bloom’s Taxonomy is used to structure an analytical rubric and to form a cognitive profile of the performance. The approach integrates Moodle, n8n, a [...] Read more.

This paper presents a RAG-based architecture with a large language model for automated assessment of student responses, in which Bloom’s Taxonomy is used to structure an analytical rubric and to form a cognitive profile of the performance. The approach integrates Moodle, n8n, a vector database for semantic retrieval of relevant context, and a GPT model for criterion-based assessment. The model’s output is formed based on the student response, the RAG-extracted learning context, and a predefined rubric. The system is implemented in a real exam environment in Bulgarian and English. The results of data analysis show differentiated behavior across Bloom’s cognitive levels, with higher sensitivity in tasks related to remembering, understanding, and applying, and more conservative behavior in tasks related to evaluating and critical thinking. Expert evaluation of the automatically generated feedback confirms its clarity, usefulness, and correctness. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 1283 KB

Open AccessProceeding Paper

Driver Visibility and Pedestrian Detection Distance in Nighttime Traffic Accident Reconstruction

by Milena Savova-Mratsenkova, Borislav Vasilovski and Danail Hlebarski

Eng. Proc. 2026, 150(1), 18; https://doi.org/10.3390/engproc2026150018 - 17 Jul 2026

Viewed by 209

Abstract

Traffic accidents involving pedestrians during the hours of darkness pose a serious threat to road safety due to reduced visibility and drivers’ delayed perception of the traffic situation. Accurate estimation of the detection distance for pedestrians is essential in the reconstruction of traffic [...] Read more.

Traffic accidents involving pedestrians during the hours of darkness pose a serious threat to road safety due to reduced visibility and drivers’ delayed perception of the traffic situation. Accurate estimation of the detection distance for pedestrians is essential in the reconstruction of traffic accidents. This study analyzes the relationship between driver visibility, environmental conditions, and the ability to detect pedestrians in a timely manner during nighttime driving. The study examines the main factors influencing the driver’s “perception–reaction” process, including the illumination provided by the vehicle’s headlights, the illumination of the road environment, the contrast and reflective properties of the pedestrian’s clothing, as well as the driver’s level of attention. Using a graph-analytical method, the detection distances for pedestrians under nighttime conditions are estimated. A real-life accident scenario was reconstructed to determine whether the driver had sufficient time and distance to perceive the danger and take action to avoid a collision. The results show that pedestrian visibility depends on lighting conditions, which directly affect the driver’s reaction time. These findings contribute to the refinement of the methodological approach to reconstructing traffic accidents and can assist experts in conducting automotive technical examinations. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 2361 KB

Open AccessProceeding Paper

Diffusion Field Reconstruction by Image Processing Technique

by Valentin Mateev, Martin Ralchev and Iliana Marinova

Eng. Proc. 2026, 150(1), 19; https://doi.org/10.3390/engproc2026150019 - 17 Jul 2026

Viewed by 184

Abstract

In this work, an image reconstruction technique applied for 2D field problem reconstruction is presented. Diffusion concentration plots, represented as images, are used for inverse field reconstruction in the empty part of the image, inside the problem domain. The image reconstruction technique is [...] Read more.

In this work, an image reconstruction technique applied for 2D field problem reconstruction is presented. Diffusion concentration plots, represented as images, are used for inverse field reconstruction in the empty part of the image, inside the problem domain. The image reconstruction technique is based on Green’s function linear system minimization for one- and three-layered data structures, visualized as color images. The reconstruction process is implemented as an iterative numerical procedure for field energy and error minimization. Results on low-resolution image reconstruction for 2D diffusion concentration are calculated and presented. The convergence of the method depending on the feedback correction is considered. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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21 pages, 2118 KB

Open AccessProceeding Paper

A Fractal-Inspired Supervisory Layer for Robust PI Control of DC–DC Buck Converters

by Plamen Stanchev, Nikolay Hinov and Reni Kabakchieva

Eng. Proc. 2026, 150(1), 20; https://doi.org/10.3390/engproc2026150020 - 17 Jul 2026

Viewed by 216

Abstract

This paper presents a fractal–multiscale supervisory control strategy for a digitally controlled DC–DC buck converter. A conventional PI controller is augmented with a supervisory layer that adaptively modulates the effective control gains based on multiscale error dynamics and oscillation indicators derived from the [...] Read more.

This paper presents a fractal–multiscale supervisory control strategy for a digitally controlled DC–DC buck converter. A conventional PI controller is augmented with a supervisory layer that adaptively modulates the effective control gains based on multiscale error dynamics and oscillation indicators derived from the error and its time derivative. In addition, automatic PI shaping using notch and lead compensators is performed through FFT-based identification of dominant oscillatory modes. The proposed approach is evaluated under load, input voltage, and combined disturbances, as well as robustness and stress-test scenarios. The simulation results indicate comparable nominal regulation, reduced oscillatory behavior, and improved robustness-oriented transient response compared to baseline PI control, particularly under non-ideal and stress-test conditions. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 1443 KB

Open AccessProceeding Paper

Map Matching Location Data from Utility Vehicles

by Alexander Petkov

Eng. Proc. 2026, 150(1), 21; https://doi.org/10.3390/engproc2026150021 - 17 Jul 2026

Viewed by 148

Abstract

Equipping municipal service vehicles with GPS and activity sensors and displaying this data on an interactive map is the first step towards creating a “smart city” infrastructure to improve planning and provide proof of service. Without a proper link between the data and [...] Read more.

Equipping municipal service vehicles with GPS and activity sensors and displaying this data on an interactive map is the first step towards creating a “smart city” infrastructure to improve planning and provide proof of service. Without a proper link between the data and the map, a human operator must evaluate whether the vehicles are performing their designated tasks by estimating their actual routes. In this paper, we develop a map-matching algorithm that maps the location data from the GPS sensors on such vehicles to the respective street segments in a GIS setting, removing the need for human operator evaluation. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 4520 KB

Open AccessProceeding Paper

Proactive System for Cyber Attack Detection Based on Big Data Analytics Using Machine Learning

by Plamen Spahiev and Desislava Ivanova

Eng. Proc. 2026, 150(1), 22; https://doi.org/10.3390/engproc2026150022 - 17 Jul 2026

Viewed by 225

Abstract

This paper presents the conceptual foundation and software architecture of a proactive system for real-time cyber-attack detection. The system is based on a nested approach of building two-level chains of machine learning models. It is composed of two components—one for learning and one [...] Read more.

This paper presents the conceptual foundation and software architecture of a proactive system for real-time cyber-attack detection. The system is based on a nested approach of building two-level chains of machine learning models. It is composed of two components—one for learning and one for evaluating real-time data. Both components are written in the Python programming language. The data has been processed and manipulated using PySpark. The initial experiments showed a combined increase of up to 25% in accuracy, compared to using non-combined ML models and unbalanced data. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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14 pages, 1586 KB

Open AccessProceeding Paper

Analytical Study of Methods and Diagnostic Tools for Evaluating Automotive Brake Fluid Quality Under Operational Conditions

by Georgi Mladenov, Kalin Dimitrov and Lyubomir Laskov

Eng. Proc. 2026, 150(1), 23; https://doi.org/10.3390/engproc2026150023 - 20 Jul 2026

Viewed by 181

Abstract

This work presents an analysis of the methods and means for determining the technical condition of brake fluid in the conditions of technical operation of vehicles. The study is motivated by the fact that hygroscopic glycol ether brake fluids degrade over time due [...] Read more.

This work presents an analysis of the methods and means for determining the technical condition of brake fluid in the conditions of technical operation of vehicles. The study is motivated by the fact that hygroscopic glycol ether brake fluids degrade over time due to moisture absorption, which leads to a decrease in the boiling point, an increase in electrical conductivity, and a change in their chemical properties. Within the experimental part, measurements of three diagnostic parameters were carried out: boiling point, electrical current/conductivity, and moisture tester readings at different controlled water contents in several types of brake fluids. The results obtained show a clear relationship between moisture content and a decrease in the boiling point, as well as a nonlinear increase in electrical conductivity with increasing water percentage. It was found that a moisture tester provides a quick but limited and inaccurate assessment. Based on the comparative analysis, conclusions have been formulated regarding the reliability, applicability, and limitations of different diagnostic methods in service and operational conditions. The results support the optimization of technical control procedures and increase the reliability of brake systems in real operation. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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13 pages, 538 KB

Open AccessProceeding Paper

Anomaly Detection in ADS-B Air Traffic Data Using Distributed Machine Learning

by Maria Babanova, Radoslav Furnadzhiev and Mitko Shopov

Eng. Proc. 2026, 150(1), 24; https://doi.org/10.3390/engproc2026150024 - 20 Jul 2026

Viewed by 218

Abstract

This paper presents a comparative study of two unsupervised machine learning methods, Isolation Forest (IF) and Gaussian Mixture Model (GMM), for anomaly detection in Automatic Dependent Surveillance–Broadcast (ADS-B) data. While ADS-B provides critical flight telemetry, its high volume and inherent noise pose significant [...] Read more.

This paper presents a comparative study of two unsupervised machine learning methods, Isolation Forest (IF) and Gaussian Mixture Model (GMM), for anomaly detection in Automatic Dependent Surveillance–Broadcast (ADS-B) data. While ADS-B provides critical flight telemetry, its high volume and inherent noise pose significant challenges for automated surveillance. To address this, we developed a distributed Extract Transform Load (ETL) pipeline using Apache Spark to analyze a dataset of 4.82 billion records. The results show a low Pearson correlation between the two models, suggesting that they capture complementary types of anomalies: IF identifies structural outliers through recursive partitioning, while GMM detects statistical deviations from learned probability densities. This study demonstrates that an ensemble of lightweight methods can effectively scale to billion-record datasets, with IF offering superior computational efficiency (∼1.7 h) compared to GMM (∼4.8 h). These results provide a robust baseline for developing scalable, real-time aviation monitoring systems to enhance global air traffic safety. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 1194 KB

Open AccessProceeding Paper

Technology for Managing and Grouping Datasets Regarding Protected Natural Areas and Species

by Delyana Dimova

Eng. Proc. 2026, 150(1), 25; https://doi.org/10.3390/engproc2026150025 - 20 Jul 2026

Viewed by 132

Abstract

This article presents a technology for managing and grouping datasets regarding protected natural areas and species in Bulgaria for the period 2010–2024. The studied indicators include the area in hectares and number of the following objects: protected areas, natural landmarks, reserves and maintained [...] Read more.

This article presents a technology for managing and grouping datasets regarding protected natural areas and species in Bulgaria for the period 2010–2024. The studied indicators include the area in hectares and number of the following objects: protected areas, natural landmarks, reserves and maintained reserves, national and natural parks. The other groups of considered elements are the number of protected plant and animal species, as well as protected venerable trees. This information is extracted from a created relational database and subsequently it is processed. The use of certain rules and the calculation of a given set of variables leads to the generation of the relevant solutions concerning the studied objects. Linear regression analysis is used to evaluate the examined data related to the protected natural areas in the considered period. This work also applies hierarchical cluster analysis to the mentioned data. The number of protected plant and animal species does not change in the whole examined time interval. During 2024 compared to the first year of the interval (2010), the number of protected venerable trees decreases by about 17.31%. The presented technology can also be applied when studying other economic indicators. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 1716 KB

Open AccessProceeding Paper

Investigation of the Power Characteristics of a Photovoltaic Power Plant in Relation to Daylight Duration

by Stanimir Stefanov

Eng. Proc. 2026, 150(1), 26; https://doi.org/10.3390/engproc2026150026 - 20 Jul 2026

Viewed by 100

Abstract

This study examines the electrical energy performance of a photovoltaic (PV) power plant with respect to the duration of the daylight period. The evaluated indicators are normalized to the initially installed capacity of the PV plant. During the operational period, a portion of [...] Read more.

This study examines the electrical energy performance of a photovoltaic (PV) power plant with respect to the duration of the daylight period. The evaluated indicators are normalized to the initially installed capacity of the PV plant. During the operational period, a portion of the photovoltaic panels ceased operation. However, for the subsequent analysis periods, the calculations of the energy and power performance indicators were carried out with reference to the originally installed capacity in order to maintain consistency and comparability of the results. The energy yield and power output of the PV plant were evaluated on both a monthly and a daily basis for the total installed capacity and referred to unit inverter capacity. Tabulated datasets and graphical representations were used to provide both quantitative and visual comparisons of the PV system performance over the investigated period. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 1980 KB

Open AccessProceeding Paper

Enhancing Agricultural Efficiency: Integrating YOLOv5 and SORT Tracker for Precise Weed and Cabbage Detection

by Ivan Ivanov, Vladimir Kotev, Miroslava Ivanova and Kiril Petkov

Eng. Proc. 2026, 150(1), 27; https://doi.org/10.3390/engproc2026150027 - 20 Jul 2026

Viewed by 136

Abstract

This paper presents an innovative approach to agricultural management by integrating YOLOv5 for real-time detection and a modified SORT tracker for tracking two critical classes in agriculture: cabbage and weed. By deploying YOLOv5 on each video frame and updating the SORT tracker with [...] Read more.

This paper presents an innovative approach to agricultural management by integrating YOLOv5 for real-time detection and a modified SORT tracker for tracking two critical classes in agriculture: cabbage and weed. By deploying YOLOv5 on each video frame and updating the SORT tracker with current detections, we uniquely identify every cabbage and weed plant, allowing for precise monitoring and analysis. This method not only enables the collection of detailed data on the area covered by cabbage and weeds but also facilitates the calculation of free area, providing invaluable insights for optimizing crop management and reducing weed-related losses. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 4938 KB

Open AccessProceeding Paper

Monitoring Piglet Growth via Instance Segmentation with YOLOv8

by Ivan Ivanov, Vladimir Kotev, Georgi Komitov and Ivelina Zapryanova

Eng. Proc. 2026, 150(1), 28; https://doi.org/10.3390/engproc2026150028 - 20 Jul 2026

Viewed by 142

Abstract

In this paper, we present a method for monitoring piglet growth over time using instance segmentation with the YOLOv8 model. Our goal is to estimate the average weight gain of piglets by measuring changes in their visible body area in images. We fine-tuned [...] Read more.

In this paper, we present a method for monitoring piglet growth over time using instance segmentation with the YOLOv8 model. Our goal is to estimate the average weight gain of piglets by measuring changes in their visible body area in images. We fine-tuned the yolov8x-seg.pt model on a custom dataset of 471 annotated images, using polygonal masks created in Roboflow. The dataset captures piglets from multiple angles and developmental stages. After training, the model achieved accurate segmentation results, effectively distinguishing individual piglets in varied conditions. By computing the mean segmented area across images over time, we derive a reliable proxy for monitoring weight gain, offering a non-invasive, camera-based alternative to manual weighing. Our findings demonstrate that YOLOv8 instance segmentation can be a valuable tool for automated livestock monitoring and precision farming. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 666 KB

Open AccessProceeding Paper

Conceptual Model and Software Architecture for Bioinformatics Data Analysis and Diagnosis in Support of Precision Medicine

by Boris Nenchovski and Desislava Ivanova

Eng. Proc. 2026, 150(1), 29; https://doi.org/10.3390/engproc2026150029 - 20 Jul 2026

Viewed by 142

Abstract

This paper proposes a novel three-layered software architecture for processing and analyzing sequences, medical images, and patient-reported outcomes (PROs). The aim is to provide a comprehensive end-to-end solution for patient diagnosis by integrating all major types of bioinformatics data. This approach leverages advanced [...] Read more.

This paper proposes a novel three-layered software architecture for processing and analyzing sequences, medical images, and patient-reported outcomes (PROs). The aim is to provide a comprehensive end-to-end solution for patient diagnosis by integrating all major types of bioinformatics data. This approach leverages advanced machine learning algorithms, including decision trees, support vector machines, neural networks, and quantum neural networks, to enhance the efficiency and effectiveness of precision medicine. A graphical user interface was constructed to validate the suggested approach and present the experimental results. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 219 KB

Open AccessProceeding Paper

Trajectory Planning for Infinitely Smooth Motion Using Non-Polynomial Functions

by Hristo Genev and Miroslava Ivanova

Eng. Proc. 2026, 150(1), 30; https://doi.org/10.3390/engproc2026150030 - 20 Jul 2026

Viewed by 102

Abstract

Although the polynomial approach is effective in many respects, it cannot provide fully smooth transitions between motion phases due to limited continuity at phase boundaries. This limitation motivated the search for an alternative class of trajectory functions that could ensure higher regularity and [...] Read more.

Although the polynomial approach is effective in many respects, it cannot provide fully smooth transitions between motion phases due to limited continuity at phase boundaries. This limitation motivated the search for an alternative class of trajectory functions that could ensure higher regularity and improved dynamic behavior. This paper addresses the trajectory planning of longitudinal horizontal motion incorporating a uniform motion segment, with a focus on achieving infinitely smooth transitions between the acceleration, uniform motion, and deceleration phases. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

9 pages, 6289 KB

Open AccessProceeding Paper

Effect of Plastic Deformation on the Corrosion Behavior of EN AW-2024 Aluminum Alloy in Acidic Environment in the Presence of Eco-Friendly Inhibitors

by Desislava Dimova, Boyan Dochev, Kalina Kamarska and Teodor Solakov

Eng. Proc. 2026, 150(1), 31; https://doi.org/10.3390/engproc2026150031 - 21 Jul 2026

Viewed by 138

Abstract

The present study examines the influence of plastic deformation on the corrosion behavior of aluminum alloy EN AW-2024 (AlCu₄Mg) in an acidic medium (0.5 M H₂SO₄). Specimens without deformation and with a degree of plastic deformation of [...] Read more.

The present study examines the influence of plastic deformation on the corrosion behavior of aluminum alloy EN AW-2024 (AlCu₄Mg) in an acidic medium (0.5 M H₂SO₄). Specimens without deformation and with a degree of plastic deformation of 25%, 33% and 50% were studied. Corrosion tests were carried out using the gravimetric method for a period of 72 h. The inhibitory effect of environmental inhibitors—ascorbic acid (vitamin C) and citric acid—was also evaluated. The results show that the degree of plastic deformation has a significant influence on the corrosion rate of the studied alloy. The lowest corrosion rate is observed at 25% deformation, while at higher degrees, the resistance decreases. It was found that citric acid exhibits the highest inhibitory effect at 33% deformation (77.27%), while vitamin C shows a better effect at 50% deformation. The results obtained show that the optimal degree of deformation in combination with a suitable inhibitor can significantly improve the corrosion resistance of EN AW-2024 alloy in acidic environments. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 1826 KB

Open AccessProceeding Paper

Supporting the Design of Electronic Circuits by Predicting Links in a Graph Structure

by Malinka Ivanova and Mariana Durcheva

Eng. Proc. 2026, 150(1), 32; https://doi.org/10.3390/engproc2026150032 - 21 Jul 2026

Viewed by 160

Abstract

Graph structures can be used to represent and explain data about connections and interactions between certain objects that form network systems. Graphs are applied in various scientific areas, and this paper explores their potential to support the design process of electronic circuits. Experimentations [...] Read more.

Graph structures can be used to represent and explain data about connections and interactions between certain objects that form network systems. Graphs are applied in various scientific areas, and this paper explores their potential to support the design process of electronic circuits. Experimentations for predicting links in a heterogeneous graph structure are performed, which are built on the basis of schematic variants of electronic circuits and their elements. A graph neural network approach and the PyG library are used. The predictive model is evaluated, and the obtained results are promising. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 787 KB

Open AccessProceeding Paper

Influence of a Confuser–Diffuser Channel on the Energy Efficiency of an Idealized Theoretical Model of a Wind Turbine

by Hristo Nedev and Chavdar Pashinski

Eng. Proc. 2026, 150(1), 33; https://doi.org/10.3390/engproc2026150033 - 21 Jul 2026

Viewed by 160

Abstract

The Betz limit defines the maximum theoretical efficiency of a wind turbine operating in an unconstrained flow. In practice, however, turbines may operate in confuser–diffuser or Venturi-type channels, where the flow is geometrically constrained. In this study, a theoretical model of a wind [...] Read more.

The Betz limit defines the maximum theoretical efficiency of a wind turbine operating in an unconstrained flow. In practice, however, turbines may operate in confuser–diffuser or Venturi-type channels, where the flow is geometrically constrained. In this study, a theoretical model of a wind turbine integrated into a profiled channel is analyzed. Based on energy and momentum balance, a relationship between efficiency and a dimensionless geometric parameter n is derived. The results show that efficiency depends on the channel geometry and reaches a maximum at n = 1.299. This finding provides an analytical reference for the design and analysis of ducted wind turbine systems. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 2153 KB

Open AccessProceeding Paper

An Experimental Setup for Collecting Physiological Data from Vehicle Drivers

by Hristo Radev and Galidiya Petrova

Eng. Proc. 2026, 150(1), 34; https://doi.org/10.3390/engproc2026150034 - 21 Jul 2026

Viewed by 172

Abstract

This paper presents an experimental framework for synchronizing multi-modal physiological data in a real-world driving environment. Research-grade sensors (CardioBAN, respiBAN) were integrated with consumer wearables (Huawei Watch D2, Oura, and Xmart smart rings) to monitor driver heart rate (HR) and respiration rate (RR). [...] Read more.

This paper presents an experimental framework for synchronizing multi-modal physiological data in a real-world driving environment. Research-grade sensors (CardioBAN, respiBAN) were integrated with consumer wearables (Huawei Watch D2, Oura, and Xmart smart rings) to monitor driver heart rate (HR) and respiration rate (RR). A custom MATLAB (version R2024a, 24.1.0)-based workflow was developed to align disparate data streams, using a nearest-neighbor principle to ensure temporal accuracy. The setup was validated through 60 min driving sessions, successfully correlating physiological responses with video feeds. Our results demonstrate that, with proper synchronization, consumer wearables can be compared with precise research-grade equipment for continuous driver state monitoring. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 18555 KB

Open AccessProceeding Paper

Instrumentation Used for VHF Solar Burst Observations at the Bulgarian Antarctic Base During Solar Cycle 25

by Ivaylo Nachev, Ilia Iliev, Yuliyan Velchev, Boncho Bonev and Peter Z. Petkov

Eng. Proc. 2026, 150(1), 35; https://doi.org/10.3390/engproc2026150035 - 21 Jul 2026

Viewed by 149

Abstract

This article presents a high-performance system for classifying types of solar bursts. The proposed system was installed on Livingston Island, Antarctica. Results from early 2026 are presented—the period of maximum solar activity in the 11-year solar cycle. The results obtained are verified by [...] Read more.

This article presents a high-performance system for classifying types of solar bursts. The proposed system was installed on Livingston Island, Antarctica. Results from early 2026 are presented—the period of maximum solar activity in the 11-year solar cycle. The results obtained are verified by correlation with satellite X-ray data. Unlike satellite data, the ground system-obtained data shows how an RF frequency (50–820 MHz band) is useful to classify radio bursts of types I, II, III, and IV. Capturing these radio signals simplifies solar burst classification and improves the reliability of space weather research. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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17 pages, 1058 KB

Open AccessProceeding Paper

Modern Stochastic Techniques for Multifaceted Sensitivity Analysis

by Venelin Todorov and Miroslav Stoenchev

Eng. Proc. 2026, 150(1), 36; https://doi.org/10.3390/engproc2026150036 - 21 Jul 2026

Viewed by 186

Abstract

This paper introduces a sophisticated stochastic methodology grounded in a lattice rule featuring an optimized generating vector, which has been rigorously developed and comprehensively analyzed. At the heart of this investigation lies the Unified Danish Eulerian Model (UNI-DEM), an extensive large-scale mathematical framework [...] Read more.

This paper introduces a sophisticated stochastic methodology grounded in a lattice rule featuring an optimized generating vector, which has been rigorously developed and comprehensively analyzed. At the heart of this investigation lies the Unified Danish Eulerian Model (UNI-DEM), an extensive large-scale mathematical framework designed to accurately capture the complex physical and chemical processes occurring within the atmosphere. The proposed lattice-based approach is systematically compared against state-of-the-art techniques, including the modified Sobol sequence and the Fibonacci lattice rule. The comparative analysis demonstrates the superiority of the proposed method in the estimation of high-dimensional integrals, highlighting its enhanced robustness and computational efficiency. These characteristics render it particularly well-suited for the computation of sensitivity indices, which are crucial for ensuring the reliability of scientific models. Furthermore, the study employs variance-based sensitivity analysis methods, notably the Sobol technique, to quantify the influence of input parameters on model outputs rigorously. A comprehensive experimental evaluation is undertaken, integrating advanced Monte Carlo algorithms in conjunction with stochastic scrambling strategies to further enhance computational performance. In addition, the research examines the effects of varying emission levels on key atmospheric pollutants such as ammonia, ozone, ammonium sulfate, and ammonium nitrate, with particular emphasis on major European urban centers exhibiting diverse geographical and environmental conditions. These results underscore the critical importance of sensitivity analysis in validating model accuracy and elucidating the intricate relationships between input parameters and environmental outcomes. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 1873 KB

Open AccessProceeding Paper

Configurable Collaborative VR Exhibitions Using Artefacts from Multiple Public and Private Collections

by Dimo Chotrov, Aleksandar Valov, Doroteya Todorova and Antoniya Tasheva

Eng. Proc. 2026, 150(1), 37; https://doi.org/10.3390/engproc2026150037 - 21 Jul 2026

Viewed by 168

Abstract

We present a system that allows cultural organizations to configure their own exhibitions using artefacts from multiple collections. Those might include their own private collections, public collections, for example indexed in Europeana, or private collections of other organizations they collaborate with. The system [...] Read more.

We present a system that allows cultural organizations to configure their own exhibitions using artefacts from multiple collections. Those might include their own private collections, public collections, for example indexed in Europeana, or private collections of other organizations they collaborate with. The system includes several modules and applications that facilitate the communication with public/private collections via APIs, the configuration of an exhibition and the experiencing of the configured exhibition in VR. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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7 pages, 564 KB

Open AccessProceeding Paper

Fine-Tuning a Denoiser for Low-Dose CT Image Reconstruction

by Tim Selig, Thomas März, Martin Storath and Andreas Weinmann

Eng. Proc. 2026, 150(1), 38; https://doi.org/10.3390/engproc2026150038 - 21 Jul 2026

Viewed by 186

Abstract

A commonly employed imaging modality that relies on ionizing radiation is Computed Tomography (CT). While lowering the radiation dose is beneficial for patient health, it can result in reduced image quality. Therefore, improving low-dose CT (LDCT) reconstruction is a significant area of research. [...] Read more.

A commonly employed imaging modality that relies on ionizing radiation is Computed Tomography (CT). While lowering the radiation dose is beneficial for patient health, it can result in reduced image quality. Therefore, improving low-dose CT (LDCT) reconstruction is a significant area of research. The LoDoPaB-CT benchmark evaluates LDCT reconstruction methods, where many top methods use UNet-type architectures. We explore a two-stage approach for LDCT reconstruction: the first stage employs traditional filtered backprojection (FBP), while the second stage performs CT image enhancement. Our training strategy involves pretraining a neural network to denoise natural grayscale images, which are corrupted by Gaussian noise, followed by fine-tuning the network for CT image enhancement using LDCT and normal-dose CT (NDCT) pairs. Experiments on various small subsets of the LoDoPaB-CT dataset demonstrate the effectiveness of our method, showing that less task-specific data are required for training. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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13 pages, 1109 KB

Open AccessProceeding Paper

Quantum Machine Learning for Enhanced Cardiovascular Disease Risk Prediction

by Veska Gancheva and Valentin Tsvetkov

Eng. Proc. 2026, 150(1), 39; https://doi.org/10.3390/engproc2026150039 - 21 Jul 2026

Viewed by 207

Abstract

Quantum computing has emerged as a powerful tool for solving complex problems in various fields. Personalized medicine, tailoring medical treatment to patients based on their genetic and health data, is one area where predictive analytics can be useful. This work explores the application [...] Read more.

Quantum computing has emerged as a powerful tool for solving complex problems in various fields. Personalized medicine, tailoring medical treatment to patients based on their genetic and health data, is one area where predictive analytics can be useful. This work explores the application of quantum algorithms for predictive analytics, specifically in the context of predicting outcomes of cardiovascular disease based on patient data. This research is focused on the quantum-based predictive models for the case study of cardiovascular disease. The models are based on Quantum Support Vector Machines, Quantum Neural Networks, and Variational Quantum Eigensolver algorithms. The software implementation is based on the Python programming language, including an integrated quantum algorithm. A dataset of cardiovascular disease from an online platform is used to train and evaluate the models. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 4954 KB

Open AccessProceeding Paper

Tensile Testing at Elevated Temperatures of PolyJet Digital ABS Plus Material

by Miglena Paneva, Peter Panev and Nikola Kuzmanov

Eng. Proc. 2026, 150(1), 40; https://doi.org/10.3390/engproc2026150040 - 21 Jul 2026

Viewed by 157

Abstract

This publication focuses on the additive technology PolyJet and more specifically the photopolymer Digital ABS Plus. After a thorough analysis, it was concluded that this technology is suitable for both rapid prototyping of parts and rapid small-scale production of various products. The resulting [...] Read more.

This publication focuses on the additive technology PolyJet and more specifically the photopolymer Digital ABS Plus. After a thorough analysis, it was concluded that this technology is suitable for both rapid prototyping of parts and rapid small-scale production of various products. The resulting parts can be implemented in a production process with different operating conditions. That is why it is interesting to investigate the Digital ABS Plus material at elevated temperatures. The temperatures at which the tests were performed are consistent with the values for heat deflection temperature (HDT) of the Digital ABS Plus material, described in the manufacturer’s technical data sheet, as well as with the results of high-temperature tests of parts obtained using Fused Deposition Modeling (FDM) technology. The investigated test pieces are subjected to annealing in order to increase their tensile strength and temperature resistance. The process is carried out in an oven with digital temperature control with a thermal profile according to a procedure approved by the manufacturer Stratasys. The obtained data from the mechanical properties before and after annealing of the Digital ABS Plus material are compared and depicted in a diagram. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 429 KB

Open AccessProceeding Paper

A Model for BIM Adoption in the Government Sector of Bulgaria

by Alexander Petkov

Eng. Proc. 2026, 150(1), 41; https://doi.org/10.3390/engproc2026150041 - 21 Jul 2026

Viewed by 138

Abstract

Building Information Modelling (BIM) is a key component of the digital transformation of the construction industry. The government of Bulgaria has accepted a National Strategy for The Digital Transformation of the Construction Industry which defines a set of goals and measures to achieve [...] Read more.

Building Information Modelling (BIM) is a key component of the digital transformation of the construction industry. The government of Bulgaria has accepted a National Strategy for The Digital Transformation of the Construction Industry which defines a set of goals and measures to achieve these goals. In this paper, we examine the goals and measures of the strategy related to adoption of BIM in the government sector and purpose a model for the adoption, emphasizing the use of existing standards and open-source solutions. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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16 pages, 3260 KB

Open AccessProceeding Paper

Minimizing the Grid Energy Component When Charging Electric Vehicles

by Krasimira Stoilova and Todor Stoilov

Eng. Proc. 2026, 150(1), 42; https://doi.org/10.3390/engproc2026150042 - 21 Jul 2026

Viewed by 179

Abstract

This paper considers an optimal energy management problem for a real electric vehicle charging system with photovoltaic power generation, stationary battery energy storage, and an electrical grid. A linear optimization model is formulated with the objective of minimizing the cost of electricity purchased [...] Read more.

This paper considers an optimal energy management problem for a real electric vehicle charging system with photovoltaic power generation, stationary battery energy storage, and an electrical grid. A linear optimization model is formulated with the objective of minimizing the cost of electricity purchased from the grid while satisfying the technical constraints of system components and the energy requirements of electric vehicles. Various parameters of the system are evaluated when changing the main variables. From the analysis and comparison of the results, a conclusion is drawn about resource savings with appropriate management of energy capacities. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 587 KB

Open AccessProceeding Paper

Generalized Trajectory Planning Using Polynomial Functions of Arbitrary Odd Degree

by Miroslava Ivanova and Hristo Genev

Eng. Proc. 2026, 150(1), 43; https://doi.org/10.3390/engproc2026150043 - 20 Jul 2026

Viewed by 109

Abstract

In this paper, we explore the synthesis of a trajectory with preassigned maximum velocity and acceleration for planning longitudinal horizontal motion. The trajectory includes polynomials of arbitrary odd degree for the acceleration and deceleration phases, and an intermediate segment of uniform motion. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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20 pages, 922 KB

Open AccessProceeding Paper

HVAC Duct Contamination and Its Impact on Energy Efficiency and Indoor Air Quality: Evaluation and Ranking of Inspection Methods Using Multi-Criteria Analysis

by Kristina Mashonova, Tanya Titova and Rosen Kosturkov

Eng. Proc. 2026, 150(1), 44; https://doi.org/10.3390/engproc2026150044 - 21 Jul 2026

Viewed by 244

Abstract

Air duct contamination in HVAC systems degrades indoor air quality and reduces energy efficiency by increasing aerodynamic resistance, pressure drop, and electricity consumption. This study systematically analyzes contamination causes and their effects on indoor health, system performance, and energy use. It examines physical, [...] Read more.

Air duct contamination in HVAC systems degrades indoor air quality and reduces energy efficiency by increasing aerodynamic resistance, pressure drop, and electricity consumption. This study systematically analyzes contamination causes and their effects on indoor health, system performance, and energy use. It examines physical, biological, and chemical pollutants and their accumulation mechanisms. Emphasis is placed on inspection and diagnostic methods to guide effective monitoring strategies. Ten methods were evaluated using five criteria: reliability, applicability, speed, cost efficiency, and diagnostic value. Optical camera inspection with image processing and pressure drop measurement ranked highest, highlighting the importance of continuous monitoring for preventive maintenance and energy optimization. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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7 pages, 1261 KB

Open AccessProceeding Paper

Research on the Time Mutability Method for Stochastic Objects Drift Velocity Measurement—A Review

by Boryana Pachedjieva, Petya Pavlova, Dobrinka Petrova and Ivailo Atanasov

Eng. Proc. 2026, 150(1), 45; https://doi.org/10.3390/engproc2026150045 - 21 Jul 2026

Viewed by 127

Abstract

The paper presents a review of research on the time mutability method for stochastic objects drift velocity measurement. The method models one-dimensional signals describing the movement of cloud structures with different types of statistical heterogeneity, without considering their evolution in the measurement interval. [...] Read more.

The paper presents a review of research on the time mutability method for stochastic objects drift velocity measurement. The method models one-dimensional signals describing the movement of cloud structures with different types of statistical heterogeneity, without considering their evolution in the measurement interval. The main study shows the dependence of the accuracy of the measured speed

\vec{V}

results on the number of recorded images, the type of statistical heterogeneity of the fields examined, and the measurement conditions. The obtained results are graphically illustrated. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 4106 KB

Open AccessProceeding Paper

Integrating Automated Notifications and Geospatial Navigation into a Mobile Learning Management Platform to Support Higher Education

by Mariya Zhekova, Todor Peychinov and Adeliya Karaivanova

Eng. Proc. 2026, 150(1), 46; https://doi.org/10.3390/engproc2026150046 - 21 Jul 2026

Viewed by 181

Abstract

This article describes the process of designing and developing an Android application to support students in a university environment by automating study schedule management, facilitating access to study materials, providing navigation to educational buildings, and sending notifications about upcoming classes. The main problem [...] Read more.

This article describes the process of designing and developing an Android application to support students in a university environment by automating study schedule management, facilitating access to study materials, providing navigation to educational buildings, and sending notifications about upcoming classes. The main problem that current development addresses is the lack of a centralized system for timely notifications and difficulties in navigating university campuses and obtaining summaries of study material files. Using two multilingual machine learning (ML) models, the solution integrates an automated notification system using Firebase Cloud Messaging (FCM), which operates in real time and provides geospatial navigation to educational buildings. Two ML models for natural language processing are used to automatically generate short and meaningful text summaries, and they accept long articles or documents in different languages and create abstract summaries, which makes them suitable for easy absorption of academic/educational materials. The technology stack includes the Django REST Framework 3.10 for the server part, PostgreSQL 18 for database management, and Java SE 21 for the mobile application, with security guaranteed through JWT (JSON Web Token) authentication and TLS encryption 1.2. The result is a comprehensive application that provides students with personalized access to weekly schedules, information about classes and assigned classroom numbers, and access to learning materials that are trained with a model optimized to create short, informative summaries. This contributes to better organization, reducing absences and increasing the efficiency of the educational process. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 1760 KB

Open AccessProceeding Paper

Feedback Control of the Inverted Pendulum

by Kamen Perev

Eng. Proc. 2026, 150(1), 47; https://doi.org/10.3390/engproc2026150047 - 21 Jul 2026

Viewed by 171

Abstract

This paper considers the control problem for the cart–pendulum system. The equations of system dynamics are derived and its parameters are estimated by applying simple identification procedures. The design goals include stabilization of the pendulum in upper equilibrium position and disturbance rejection for [...] Read more.

This paper considers the control problem for the cart–pendulum system. The equations of system dynamics are derived and its parameters are estimated by applying simple identification procedures. The design goals include stabilization of the pendulum in upper equilibrium position and disturbance rejection for plant input disturbances. For satisfying the design goals, the conditional feedback control structure is introduced and its properties are discussed. The first objective is to stabilize the unstable pendulum in an upright position. Since the pendulum cannot be stabilized by a simple gain, a state feedback is designed in the local feedback contour. Based on the conditional feedback, the design problem for the forward controller is solved by using desired closed-loop system complementary sensitivity function and achieving low sensitivity with respect to disturbances at the plant input. The performance of the obtained designs are tested by a numerical example. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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14 pages, 2207 KB

Open AccessProceeding Paper

Frequency Domain Modal Characterization and Multi-Injection Resonance Assessment of a Zeta DC–DC Converter

by Plamen Stanchev, Nikolay Hinov and Reni Kabakchieva

Eng. Proc. 2026, 150(1), 48; https://doi.org/10.3390/engproc2026150048 - 21 Jul 2026

Viewed by 200

Abstract

This paper presents a frequency domain harmonic and modal analysis of a four-bus Zeta DC–DC converter, targeting the identification of resonance phenomena up to 200 MHz. The method is based on nodal admittance modeling and eigenvalue decomposition of the impedance matrix, enabling extraction [...] Read more.

This paper presents a frequency domain harmonic and modal analysis of a four-bus Zeta DC–DC converter, targeting the identification of resonance phenomena up to 200 MHz. The method is based on nodal admittance modeling and eigenvalue decomposition of the impedance matrix, enabling extraction of modal impedance and dominant resonance modes. Participation factors and sequential current injection at each bus are employed to evaluate spatial sensitivity and voltage amplification under different excitation scenarios. A two-stage frequency sweep, combining a coarse global scan with fine local refinement around detected peaks, ensures efficient and accurate resonance characterization. Simulation results demonstrate strong dependence of resonance severity on the injection location and highlight the dominant contribution of specific modes and reactive elements. The proposed framework provides physical insight and supports resonance-aware design of power electronic converters. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 744 KB

Open AccessProceeding Paper

Analytical Recommendation for the Battery Capacity of a Photovoltaic System

by Todor Stoilov and Krasimira Stoilova

Eng. Proc. 2026, 150(1), 49; https://doi.org/10.3390/engproc2026150049 - 21 Jul 2026

Viewed by 138

Abstract

This paper aims to provide a numerical estimate of the capacity of a battery in a photovoltaic system. The battery’s capacity is calculated numerically based on the current operating state of the load in the grid. This evaluation can help designers to use [...] Read more.

This paper aims to provide a numerical estimate of the capacity of a battery in a photovoltaic system. The battery’s capacity is calculated numerically based on the current operating state of the load in the grid. This evaluation can help designers to use the appropriate battery capacity. In the case of a large capacity, part of the battery will not be used, which reduces the efficiency of the photovoltaic design and operations. A low battery capacity will limit the operational use of the photovoltaic system. An analytical assessment and recommendations for the battery condition are provided using real data from the operation of the photovoltaic system. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 1207 KB

Open AccessProceeding Paper

Inverse Copula Sampling for Multi-Dimensional Data Synthesis

by Angel Marchev, Jr., Dimitar Lyubchev and Vasil Marchev

Eng. Proc. 2026, 150(1), 50; https://doi.org/10.3390/engproc2026150050 - 22 Jul 2026

Viewed by 172

Abstract

In the era of big data, the demand for vast quantities of diverse and representative datasets has surged across various domains, from healthcare and finance to artificial intelligence and machine learning. Synthetic data generation offers a promising solution by enabling the creation of [...] Read more.

In the era of big data, the demand for vast quantities of diverse and representative datasets has surged across various domains, from healthcare and finance to artificial intelligence and machine learning. Synthetic data generation offers a promising solution by enabling the creation of data with specific properties that closely mimic real-world data while avoiding privacy concerns and regulatory limitations. However, generating high-quality synthetic data that accurately preserves complex dependencies remains a significant challenge. This paper addresses this gap by exploring a novel approach: Inverse Copula Sampling for Multi-Dimensional Data Synthesis. Utilizing copulas, which are powerful tools for modeling dependencies between variables, our method generates synthetic data that maintains intricate interdependencies. We demonstrate the effectiveness of this approach through various experiments and case studies, showing high fidelity in preserving dependencies and minor discrepancies in marginal distributions. The method’s robustness was validated through comparative analysis and statistical checks, including the Kolmogorov–Smirnov test. Our research contributes to the field by introducing a flexible and efficient method for synthetic data generation that is applicable to a wide range of data distributions and practical applications. Future work will explore the application of other copula types and the further refinement of the method to enhance its versatility. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 4634 KB

Open AccessProceeding Paper

Time Series Analysis of the Behavior of Wild Animals Using Camera Traps

by Petar Matov, Milena Lazarova and Simona Filipova-Petrakieva

Eng. Proc. 2026, 150(1), 51; https://doi.org/10.3390/engproc2026150051 - 21 Jul 2026

Viewed by 154

Abstract

During the last 50 years, average wild animal populations have decreased by 73%. The present article is part of a scientific project aimed at tracking wild animal habitats in the Bulgarian mountains. Based on the PlantNet base model, a model based on the [...] Read more.

During the last 50 years, average wild animal populations have decreased by 73%. The present article is part of a scientific project aimed at tracking wild animal habitats in the Bulgarian mountains. Based on the PlantNet base model, a model based on the YOLOv8n architecture has been created through transfer learning on local data to recognize animal species specific to Bulgarian geographical latitudes. In this paper, a system for assessing population dynamics and animal movement through the analysis of time series of images is proposed. The effectiveness of the proposed methodology is illustrated using a database of images from Ukraine, as it provides a sufficient number of images needed to train and test the model, thereby monitoring changes in the behavior of wild animals over time. This will enable the detection of migration patterns, preferred habitats, and potential threats to these populations. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 5709 KB

Open AccessProceeding Paper

Adversarial Robustness and Explainability in AI-Generated Face Detection

by Georgi Kotov, Plamen Nakov and Ognyan Nakov

Eng. Proc. 2026, 150(1), 52; https://doi.org/10.3390/engproc2026150052 - 22 Jul 2026

Viewed by 240

Abstract

This paper investigates adversarial robustness and explainability in AI-generated face detection through the Robust and Explainable Detection (RED) framework. RED unifies CNN and Vision Transformer (ViT) backbones with FGSM/PGD adversarial training and Grad-CAM-based interpretability in one reproducible pipeline. Experiments on the Kaggle real/fake [...] Read more.

This paper investigates adversarial robustness and explainability in AI-generated face detection through the Robust and Explainable Detection (RED) framework. RED unifies CNN and Vision Transformer (ViT) backbones with FGSM/PGD adversarial training and Grad-CAM-based interpretability in one reproducible pipeline. Experiments on the Kaggle real/fake face dataset with stratified 70/15/15 splits report accuracy, F1, AUC-ROC, Adversarial Robustness Index (ARI), and Explainability Fidelity (EF). Xception and ResNet-50 reach 97.53% and 96.64% validation accuracy, respectively, while ViT-B/16 attains 69.08%. RED supports forensic and legal applications requiring both detection accuracy and transparent model behavior. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 1033 KB

Open AccessProceeding Paper

Constructive Approach to the Design of Data Protection Systems: Models and Transformation

by Ivan Gaidarski and Anastas Madzharov

Eng. Proc. 2026, 150(1), 53; https://doi.org/10.3390/engproc2026150053 - 22 Jul 2026

Viewed by 200

Abstract

In this article, we present a constructive method for designing an information security system (ISS). The method is based on the IEEE 1471 and IEEE 42010 standards. They provide an architectural framework for describing the system through conceptual modeling from different perspectives. The [...] Read more.

In this article, we present a constructive method for designing an information security system (ISS). The method is based on the IEEE 1471 and IEEE 42010 standards. They provide an architectural framework for describing the system through conceptual modeling from different perspectives. The perspectives reflect the requirements of stakeholders—regulatory, normative, technological or budgetary. As result of analysis of the problem area, conceptual models are constructed. The resulting models are combined into a generalized multilayer model. The transformation of the conceptual model into a technology-independent object-oriented (OO) design model follows. The next stage is selection of an appropriate technological platform and subsequent transformation of the design model into an implementation model. An essential part of the method is the creation of an agent-based simulation model. It allows the simulation of the ISS in different environments, changing the input conditions. The method ensures technological independence of the ISS, due to the fact that the resulting conceptual model reflects the requirements of the system and the methods for implementing the tasks of the ISS without using a specific technological solution. The method also ensures universal communication between the individual stakeholders and unification of the used terminology. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 6424 KB

Open AccessProceeding Paper

A Combined Approach for Design Concept Variants Assessment of a Hydropower System

by Konstantin Kamberov, Maria Ivanova and Martina Stipchekova

Eng. Proc. 2026, 150(1), 54; https://doi.org/10.3390/engproc2026150054 - 22 Jul 2026

Viewed by 190

Abstract

The study aims to demonstrate the role and significance of product evaluation at the concept stage of its development. It is particularly dedicated to a contemporary product—a hydropower generation system—that is directly related to green renewable energy sources. The assessment of each of [...] Read more.

The study aims to demonstrate the role and significance of product evaluation at the concept stage of its development. It is particularly dedicated to a contemporary product—a hydropower generation system—that is directly related to green renewable energy sources. The assessment of each of the six developed design variants combines the output of the virtual prototyping system (generated power) and an analysis of capital expenditure, both used to assess the return on investment period. The project’s financial aspects highly influence final design variant selection, and this is a good example of the possibility of including financial specifics at the early project stage. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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14 pages, 866 KB

Open AccessProceeding Paper

Aging Behavior and Wear Metal Evolution of Low-Viscosity SAE 0W20 Engine Oil During the First Service Interval

by Atanasi Tashev, Yordan Stoyanov and Penko Mitev

Eng. Proc. 2026, 150(1), 55; https://doi.org/10.3390/engproc2026150055 - 22 Jul 2026

Viewed by 211

Abstract

The present study investigates the physicochemical degradation and wear metal evolution of low-viscosity SAE 0W-20 engine oil during the first service interval of a modern gasoline internal combustion engine. Two oil samples were analyzed: fresh lubricant and used oil collected after approximately 13,000 [...] Read more.

The present study investigates the physicochemical degradation and wear metal evolution of low-viscosity SAE 0W-20 engine oil during the first service interval of a modern gasoline internal combustion engine. Two oil samples were analyzed: fresh lubricant and used oil collected after approximately 13,000 km of vehicle operation. The analysis included determination of kinematic viscosity at 100 °C (ASTM D445), total base number (ASTM D2896), FT-IR spectroscopic indicators of chemical degradation (ASTM E2412), and elemental analysis of wear and additive metals using ICP-OES (ASTM D5185). The results show a viscosity reduction from 8.5 to 7.01 mm²/s and a decrease in the alkalinity reserve to 3.7 mgKOH/g, indicating progressive lubricant aging. FT-IR analysis revealed moderate oxidation, nitration, and sulfation processes, while elemental analysis identified Cu, Fe, and Al as the dominant wear metals. The observed changes correspond primarily to normal oil aging and engine running-in processes. The results demonstrate the effectiveness of combined oil analysis techniques for monitoring lubricant degradation and early engine wear. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 4346 KB

Open AccessProceeding Paper

Enhancing the Load Capacity of Flat Wagons: Theoretical Justification and Dynamic Simulation of a Prototype Three-Axle Bogie

by Stancho Ivanov, Svetoslav Slavchev, Petko Sinapov and Vladislav Maznichki

Eng. Proc. 2026, 150(1), 56; https://doi.org/10.3390/engproc2026150056 - 22 Jul 2026

Viewed by 197

Abstract

This study presents a theoretical justification and simulation analysis of a flat wagon with increased load capacity for the needs of intermodal transport. A modification is proposed by replacing the middle two-axle bogie with a prototype three-axle bogie. Preliminary calculations using mechanics of [...] Read more.

This study presents a theoretical justification and simulation analysis of a flat wagon with increased load capacity for the needs of intermodal transport. A modification is proposed by replacing the middle two-axle bogie with a prototype three-axle bogie. Preliminary calculations using mechanics of materials demonstrate the possibility of increasing the payload by 14 tonnes per wagon, thereby improving economic efficiency and reducing the carbon footprint. To assess the safety against derailment and the running behavior, a computational multibody model was developed in the Universal Mechanism software (Version 10.0.7). The simulation results are evaluated in accordance with the requirements of the European standard EN 14363, confirming the operational reliability of the proposed innovative design. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 714 KB

Open AccessProceeding Paper

Heuristic Algorithm for Conceptual Learning

by Dimitar Minkov, Roumen Trifonov and Dilyana Budakova

Eng. Proc. 2026, 150(1), 57; https://doi.org/10.3390/engproc2026150057 - 22 Jul 2026

Viewed by 142

Abstract

This article presents a new heuristic algorithm for conceptual learning. The process of constructing a decision tree through the minimization of a logical function is explained. This heuristic approach eliminates the need to expand the inverse property space into a full logical expression, [...] Read more.

This article presents a new heuristic algorithm for conceptual learning. The process of constructing a decision tree through the minimization of a logical function is explained. This heuristic approach eliminates the need to expand the inverse property space into a full logical expression, which could be computationally expensive for large expressions. Tests were conducted using various sets of standardized machine learning benchmarks. They show that the algorithm operates with high precision and accuracy on noise-free data as well as on datasets that include noise through the presence of mislabeled examples. The algorithm’s ability to capture non-linear patterns was experimentally evaluated, where the target class is defined by the equality of two specified attributes. The application of the proposed algorithm for the creation of hybrid neuro-symbolic architectures is discussed, with the aim of achieving logically grounded and interpretable machine learning and machine reasoning. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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13 pages, 2559 KB

Open AccessProceeding Paper

Forecasting Customer Complaints in the Mobile Telecommunication Sector Using Supervised Machine Learning

by Hussein Ibrahim

Eng. Proc. 2026, 150(1), 58; https://doi.org/10.3390/engproc2026150058 - 22 Jul 2026

Viewed by 189

Abstract

The telecommunications sector continues to experience exponential growth in demand, accompanied by a corresponding increase in customer complaints regarding service quality. To effectively address these challenges, many telecom companies rely on customer feedback to assess and improve their network and services. This case [...] Read more.

The telecommunications sector continues to experience exponential growth in demand, accompanied by a corresponding increase in customer complaints regarding service quality. To effectively address these challenges, many telecom companies rely on customer feedback to assess and improve their network and services. This case study focused on a Lebanese telecom company, investigating the application of machine learning algorithms, particularly Artificial Neural Networks. The analysis performed compares the effectiveness of various optimizers and activation functions to identify the most suitable approach for our specific context. Utilizing a sample database comprising 10,000 mobile market subscribers, this study incorporates variables such as gender, age, device manufacturer, service quality, and complaint status. The results of this case study emphasize that, across various metrics, and despite its complexity, Artificial Neural Networks outperform other algorithms in terms of prediction performance. Additionally, we propose a segmented prediction model based on time intervals and customer groups to enhance prediction accuracy and practical utility. The segmentation will involve examining customer groups based on their characteristics. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 629 KB

Open AccessProceeding Paper

Integrating the Approach of Adjustable Reliability into the System Development Life Cycle

by Edita Djambazova

Eng. Proc. 2026, 150(1), 59; https://doi.org/10.3390/engproc2026150059 - 22 Jul 2026

Viewed by 178

Abstract

Fault-tolerant distributed systems are implemented in safety-critical applications where a system failure could cause severe damage and threaten human lives. To guarantee their flawless operation, their dependability attributes must be embedded early and continuously throughout system design, rather than treating them as an [...] Read more.

Fault-tolerant distributed systems are implemented in safety-critical applications where a system failure could cause severe damage and threaten human lives. To guarantee their flawless operation, their dependability attributes must be embedded early and continuously throughout system design, rather than treating them as an afterthought. This paper presents a conceptual framework for integrating the approach of adjustable reliability into the System Development Life Cycle (SDLC). The approach of adjustable reliability provides a way to distribute structural hardware redundancy and achieve the system reliability required by the application. The proposed framework shifts reliability from a design add-on to a core architectural decision variable in the design of dependable distributed systems. Opportunities and challenges involved are discussed, and some future research directions are outlined. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 2065 KB

Open AccessProceeding Paper

Microcontroller Firmware for Embedded Systems in Industrial Applications

by Svetozar Ilchev

Eng. Proc. 2026, 150(1), 60; https://doi.org/10.3390/engproc2026150060 - 22 Jul 2026

Viewed by 258

Abstract

This paper discusses the creation of a microcontroller firmware that focuses on the control of lighting, temperature, and external devices, and enables sensor data acquisition and transmission to remote systems in industrial applications. Relevant economic and technological aspects are outlined, a suitable firmware [...] Read more.

This paper discusses the creation of a microcontroller firmware that focuses on the control of lighting, temperature, and external devices, and enables sensor data acquisition and transmission to remote systems in industrial applications. Relevant economic and technological aspects are outlined, a suitable firmware architecture is proposed, related implementation details are presented, and experimental results are summarized after gathering practical experience with three microcontroller boards developed for real-world application. The proposed firmware achieves a good balance between development cost, usability, and reliability, and provides enough room for future integration in new application scenarios and configuration adjustments requested by clients. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 1741 KB

Open AccessProceeding Paper

Assessment of Flutter Stability Constraints and the Impact on the Helicopter Rotor Aeroelastic Characteristics

by Gabriel Georgiev

Eng. Proc. 2026, 150(1), 61; https://doi.org/10.3390/engproc2026150061 - 22 Jul 2026

Viewed by 198

Abstract

This study represents the evaluation of the aeroelastic flutter stability characteristics of a helicopter rotor, expressed as correlations between the flutter frequency ratio and the relative center of gravity coordinate, considering the varying distance from the ground surface and the location of the [...] Read more.

This study represents the evaluation of the aeroelastic flutter stability characteristics of a helicopter rotor, expressed as correlations between the flutter frequency ratio and the relative center of gravity coordinate, considering the varying distance from the ground surface and the location of the aerodynamic center for a fixed flapping frequency. For every constant aerodynamic center’s coordinate, a decrease in the relative distance from the ground surface produces a reduction in the flutter stability zone for the given helicopter rotor. Conversely, moving the center of gravity coordinates in the backward direction from

{ξ_{A}}_{1} = 0.1

to

{ξ_{A}}_{3} = 0.8

leads to a rise in the flutter stability zone and then improves the stability characteristics. A nonlinear representation of the lift force coefficient variations with the angle of attack, when the reduced frequency changes from

k_{1} = 0

to

k_{6} = 10

, is conducted with the incorporation of Theodorsen’s function. Eventually, an increase in the reduced frequency magnitude leads to a rise in the produced nonlinearities in the lift force coefficients when the angle of attack changes. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 734 KB

Open AccessProceeding Paper

Use of DCC Additional Information for the Expression of Calibration Results in Metrological Practice and Education

by Gregor Starinský, Martin Halaj, Jan Rybář and Peter Onderčo

Eng. Proc. 2026, 150(1), 62; https://doi.org/10.3390/engproc2026150062 - 22 Jul 2026

Viewed by 231

Abstract

Technological progress in metrology provides new opportunities for enhancing the quality and transparency of metrological services, with the Digital Calibration Certificate (DCC) playing a significant role in this development. In contrast to traditional calibration certificates, the DCC enables the transfer of extended machine-readable [...] Read more.

Technological progress in metrology provides new opportunities for enhancing the quality and transparency of metrological services, with the Digital Calibration Certificate (DCC) playing a significant role in this development. In contrast to traditional calibration certificates, the DCC enables the transfer of extended machine-readable data and can bring additional technical and metrological information describing the calibration process. This paper focuses on the use of DCC additional information for enhanced expression of calibration results in metrological practice and education. Using the example of pressure transducer calibration, the implementation of extended datasets within the DCC structure and their application in result evaluation are demonstrated, including analytical determination of measurement uncertainty and the application of the Monte Carlo method. The results confirm the contribution of DCC to more transparent interpretation of calibration results and to the support of professional education in metrology. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 2194 KB

Open AccessProceeding Paper

Customer Behavior Analysis and Service Enhancement in Telecom Company Using Machine Learning Methods

by Hussein Ibrahim and Vladimir Dimitrov

Eng. Proc. 2026, 150(1), 63; https://doi.org/10.3390/engproc2026150063 - 23 Jul 2026

Viewed by 179

Abstract

Customer complaints are considered one of the key indicators of customer discontentment with a service. In organizations, such as telecommunications companies, not all customers raise their complaints, which raises concerns about their potential churn or retention. As firms usually rely on the complaints [...] Read more.

Customer complaints are considered one of the key indicators of customer discontentment with a service. In organizations, such as telecommunications companies, not all customers raise their complaints, which raises concerns about their potential churn or retention. As firms usually rely on the complaints raised to customer services, there exists an important portion of customers who claim their complaints through other platforms, such as social media, even though another portion does not complain at all. This places the company’s image in jeopardy and might affect its productivity and profits. To address this challenge, it is important to address possible customer problems before they turn into effective complaints. To do so, the current study aims to predict the complaints of customers in a telecommunication company and their potential churn through the usage of supervised machine learning models to test the correlation between churn and complaints. Through a thorough data analysis, it becomes evident that a good portion of clients who encounter service issues decide not to present any complaints to the company. In addition, among complainers, some do not complain directly to the company, while others who contact the company have their problems postponed. Among those, there is a proportion, considered as having unresolved concerns, turned into churn. Using a dataset of 1000 clients, recruited over a period of six months, the results showed that a considerable portion of customers using the services during the day were non-churners and continued using it over the overall period of 6 months. Whereas, day churn and evening churn both showed much lower frequencies compared to non-churn customers, with fewer calls across all durations. Additionally, the findings showed that there exists a correlation between customer complaints and customer churn, where churn events frequently coincide with complaints, indicating that customers without churn are generally content with their service, while those having complaints are more likely to quit. This study presents important insights into telecommunications companies to improve their service offerings, enhance customer satisfaction, and reduce churn rates, leading to a more stable and profitable customer base. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 2899 KB

Open AccessProceeding Paper

A Monte Carlo Method for the Modeling of Flow in a Network Channel

by Khristo Tarnev and Rositsa Andreeva

Eng. Proc. 2026, 150(1), 64; https://doi.org/10.3390/engproc2026150064 - 23 Jul 2026

Viewed by 145

Abstract

A Monte Carlo method for the modeling of traffic in a network is developed. The main advantage of the method is the possibility of using arbitrary probability functions for the transfer of an element of the flow to the next node. The model [...] Read more.

A Monte Carlo method for the modeling of traffic in a network is developed. The main advantage of the method is the possibility of using arbitrary probability functions for the transfer of an element of the flow to the next node. The model is validated by comparison with results known from the literature. Possible applications of the method for modeling in nonlinear and delay systems are discussed. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 534 KB

Open AccessProceeding Paper

Modeling the Law of Motion of a Robotic Manipulator Using Polynomial Functions

by Miroslava Ivanova and Hristo Genev

Eng. Proc. 2026, 150(1), 65; https://doi.org/10.3390/engproc2026150065 - 23 Jul 2026

Viewed by 141

Abstract

The increasing use of robotic manipulators in construction requires precise trajectory planning to reduce oscillations, dynamic loads, and positioning errors. Trajectory planning, understood as determining the manipulator’s motion from an initial to a final configuration while satisfying specified kinematic and dynamic constraints, is [...] Read more.

The increasing use of robotic manipulators in construction requires precise trajectory planning to reduce oscillations, dynamic loads, and positioning errors. Trajectory planning, understood as determining the manipulator’s motion from an initial to a final configuration while satisfying specified kinematic and dynamic constraints, is a fundamental part of motion planning. Polynomial trajectories are widely applied because they ensure smoothness and allow specifying boundary conditions on velocity and acceleration. However, higher-degree polynomials introduce computational complexity. This study develops the analytical framework for seventh-degree polynomial trajectory generation for horizontal motion with smooth acceleration and deceleration, achieving prescribed maximum velocity and acceleration and identifying the conditions for including a uniform-motion segment. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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14 pages, 4440 KB

Open AccessProceeding Paper

Applications of Twin Counter-Rotating Common-Axis Rotor Systems in Modern Rotorcraft and UAVs

by Gabriel Georgiev and Vladimir Serbezov

Eng. Proc. 2026, 150(1), 66; https://doi.org/10.3390/engproc2026150066 - 23 Jul 2026

Viewed by 211

Abstract

This study represents a comprehensive analysis of the implementation of twin counter-rotating common-axis (coaxial) rotor systems in the design process and technical application of rotorcraft and Unmanned Aerial Vehicles (UAVs). In detail, the conducted literature review clearly illustrates the already usable vehicles and [...] Read more.

This study represents a comprehensive analysis of the implementation of twin counter-rotating common-axis (coaxial) rotor systems in the design process and technical application of rotorcraft and Unmanned Aerial Vehicles (UAVs). In detail, the conducted literature review clearly illustrates the already usable vehicles and the existing experimental models. The application of a system of two coaxial rotors, one above the other, rotating in opposite directions, eliminates the need for a tail rotor for the provision of directional stability and leads to several additional advantages such as the reduction in the rotorcraft’s weight and enhancement of the directional stability qualities in comparison with the single main rotor configurations. However, the inclusion of two rotors, one above the other, affects lift generation, reducing its magnitude on the lower rotor, while the lift and the thrust of the upper rotor remain relatively unchanged. The implementation of two-rotor systems requires complex algorithms with respect to cyclic and collective pitch control. Ultimately, the analyzed cases indicate the existing gap in the research into coaxial systems concerning the influence of the distance between the two rotors and the collective pitch on the generated thrust and the interferences in cross-flow conditions. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 3242 KB

Open AccessProceeding Paper

Virtual Prototyping and Evaluation of Hydro Plant System with Crossflow Turbine

by Konstantin Kamberov, Georgi Todorov and Blagovest Zlatev

Eng. Proc. 2026, 150(1), 67; https://doi.org/10.3390/engproc2026150067 - 22 Jul 2026

Viewed by 135

Abstract

The study presents an application of virtual prototyping and numerical analysis in engineering practice for an in-stream hydropower system. The performed analyses aimed to compare different design configurations of the crossflow turbine. All simulations use virtual prototypes and computational fluid dynamics to review [...] Read more.

The study presents an application of virtual prototyping and numerical analysis in engineering practice for an in-stream hydropower system. The performed analyses aimed to compare different design configurations of the crossflow turbine. All simulations use virtual prototypes and computational fluid dynamics to review design performance in detail under various environmental conditions. Specifics of mixed fluid flows are outlined. The major focus is on virtual prototype testing, aiming to demonstrate its ability to deliver fast results for complex, expensive structures. This work is a good example of the practical application of numerical analysis and virtual prototyping and demonstrates a specific, complex field, such as computational fluid dynamics. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 7283 KB

Open AccessProceeding Paper

Manufacturing Technologies Comparison for Nozzles

by Svetlana Boshnakova

Eng. Proc. 2026, 150(1), 68; https://doi.org/10.3390/engproc2026150068 - 23 Jul 2026

Viewed by 151

Abstract

During operation, several parts of the thermal reactor burners sustain heavy damage and need to be replaced. Different solutions for parts manufacturing are investigated: thermal spraying, Selective Laser Melting (SLM), and hardfacing by Directed Energy Deposition plasma arc (DED-arc). Based on the comparison [...] Read more.

During operation, several parts of the thermal reactor burners sustain heavy damage and need to be replaced. Different solutions for parts manufacturing are investigated: thermal spraying, Selective Laser Melting (SLM), and hardfacing by Directed Energy Deposition plasma arc (DED-arc). Based on the comparison to original material and the duration of usage, application of those three methods for replacement is studied in order to determine the most suitable one, with Additive Manufacturing (AM) being proposed for targeting the problem. Thermal-sprayed items have a zirconium-oxide-based outer layer. SLM produces a monolithic item, while with the help of DED-arc, a composite structure with a sound metallurgical bond between the base and the added material is produced. The microstructures with the interface zones are observed. Samples are machined and ground, and their friction characteristics are taken with the help of acoustic emission (AE) and Electrical Contact Resistances (ECR) sensors during scratching. As a result, overlaying of the base stainless steel by DED-arc is proposed due to the better metallurgical stability of the added mixture in a hot environment above 800 °C and its hardness characteristics. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 8294 KB

Open AccessProceeding Paper

Design and Development of a Microcontroller Board for Environmental Control and Device Management

by Svetozar Ilchev

Eng. Proc. 2026, 150(1), 69; https://doi.org/10.3390/engproc2026150069 - 23 Jul 2026

Viewed by 155

Abstract

The paper discusses some important microcontroller board features in the application context of laser projection systems, which include measuring temperature and humidity by analog and digital sensors, controlling internal and external devices according to sensor values and time schedules, as well as communicating [...] Read more.

The paper discusses some important microcontroller board features in the application context of laser projection systems, which include measuring temperature and humidity by analog and digital sensors, controlling internal and external devices according to sensor values and time schedules, as well as communicating the system state to remote computers. Accordingly, the hardware architecture of the microcontroller board is designed, specific implementation details are illustrated, and experimental results are discussed showcasing a custom desktop application for monitoring and control. Future development will build on the flexibility and extensibility of the board to include additional digital sensors and connectivity options. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 527 KB

Open AccessProceeding Paper

Compensations for Horizontal Inertial Components of INS/GNSS with Flight Altitude

by Anastas Madzharov, Stefan Hristozov and Ivan Gaidarski

Eng. Proc. 2026, 150(1), 70; https://doi.org/10.3390/engproc2026150070 - 24 Jul 2026

Viewed by 214

Abstract

This research examines the fundamental autonomous inertial navigation formulas for aircraft. The study aims to identify analytical errors arising from the use of approximate gravity field models and proposes corrections for horizontal inertial components relative to changes in flight altitude. GPS measurements of [...] Read more.

This research examines the fundamental autonomous inertial navigation formulas for aircraft. The study aims to identify analytical errors arising from the use of approximate gravity field models and proposes corrections for horizontal inertial components relative to changes in flight altitude. GPS measurements of ground speed and its total and relative derivatives are transformed into compensations for Coriolis and centrifugal accelerations, with flight altitude taken into account. This type of compensation corresponds to a precisely defined gravitational field model, assumed to be accurate to the second degree of eccentricity. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 8453 KB

Open AccessProceeding Paper

Mechanical Characterization of PETG/TPU Multi-Material 3D-Printed Samples and Fabrication of a Test Part

by Mihail Zagorski, Radoslav Miltchev, Todor Gavrilov and Martina Nikolova

Eng. Proc. 2026, 150(1), 71; https://doi.org/10.3390/engproc2026150071 - 24 Jul 2026

Viewed by 259

Abstract

The present article aims to explore the feasibility of manufacturing multi-material components from PETG and TPU using FFF/FDM 3D printing. The mechanical characterization includes Shore hardness measurements of the individual materials and Izod impact strength testing of samples produced with different structural configurations. [...] Read more.

The present article aims to explore the feasibility of manufacturing multi-material components from PETG and TPU using FFF/FDM 3D printing. The mechanical characterization includes Shore hardness measurements of the individual materials and Izod impact strength testing of samples produced with different structural configurations. Furthermore, a test part based on a rover wheel is fabricated using a PETG/TPU multi-material structure to validate the practical applicability of the proposed multi-material concept. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 800 KB

Open AccessProceeding Paper

Statistical Modelling in User Experience Design of Detergent Packages

by Alexander Radoslavov, Lyubomir Dimitrov and Alexander Nikov

Eng. Proc. 2026, 150(1), 72; https://doi.org/10.3390/engproc2026150072 - 24 Jul 2026

Viewed by 143

Abstract

A method for user experience design of detergent packages is proposed. Using a checklist, user experience with detergent packages is assessed. Through a statistical model, the most important package design elements, which provide positive emotional user experience, are determined. User experience design recommendations [...] Read more.

A method for user experience design of detergent packages is proposed. Using a checklist, user experience with detergent packages is assessed. Through a statistical model, the most important package design elements, which provide positive emotional user experience, are determined. User experience design recommendations for good and bad design of detergent packages are defined. Within a case study, the method was experimentally used for design of detergent packages. Further research in this new and very promising area is discussed. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 1098 KB

Open AccessProceeding Paper

Electric Power Consumption Forecasting in Bulgaria

by Petko Ivanov Stoev, Kiril Yavorov Hristov, Hristo Veselinov Grigorov and Maya Angelova Stoeva

Eng. Proc. 2026, 150(1), 73; https://doi.org/10.3390/engproc2026150073 - 24 Jul 2026

Viewed by 129

Abstract

The primary goal of this paper is to develop a robust model for forecasting electric power consumption in Bulgaria. Leveraging historical forecast data from Open-Meteo for weather-related features and ENTSOE data, our objective is to create an accurate prediction tool that can assist [...] Read more.

The primary goal of this paper is to develop a robust model for forecasting electric power consumption in Bulgaria. Leveraging historical forecast data from Open-Meteo for weather-related features and ENTSOE data, our objective is to create an accurate prediction tool that can assist in optimizing energy management within the country. By achieving this goal, we aim to improve energy reliability, support data-driven decision making in energy policy, and promote sustainable energy practices in Bulgaria. This predictive model will empower us to proactively address fluctuations in energy demand, particularly during extreme weather conditions, and will contribute to the efficient allocation of electrical resources. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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19 pages, 6784 KB

Open AccessProceeding Paper

Exploring the Relationships Between Material and Image in the Exquisite Graphics of Letterpress Printing

by Mihaela Gadzheva-Nedelcheva and Ivelina Daulova

Eng. Proc. 2026, 150(1), 74; https://doi.org/10.3390/engproc2026150074 - 24 Jul 2026

Viewed by 188

Abstract

This current scientific article deals with the study of the relationships between material and iconic image in fine graphics. In this specific case, these relationships relate only to letterpress printing. Of interest are non-standard materials, which, depending on their physical and chemical indicators, [...] Read more.

This current scientific article deals with the study of the relationships between material and iconic image in fine graphics. In this specific case, these relationships relate only to letterpress printing. Of interest are non-standard materials, which, depending on their physical and chemical indicators, lead to different results in the final artistic image. The aim of the article is to establish the dependencies: material–manipulation–result–effect/defect. Specific “effects” are sought in the final version of the image, in which the work of fine art-graphics is of high artistic value. For this purpose, experiments were conducted with the same images, but on different material carriers, with different inks and types of paper, which practically establish the physical and technological indicators and results. From these conditions it is established what artistic effect or defect is realized. The parameters presented in the comparative tables are intended to orient the user as to what base, ink and paper to choose for a specific creative manifestation. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 2533 KB

Open AccessProceeding Paper

Predictive Maintenance via Remaining Useful Life Estimation in Jet Engine Systems: A Comparative Analysis of Machine Learning Approaches Using the NASA CMAPSS Dataset

by Mustafa Kemal Tezcan and Hilmi Kuscu

Eng. Proc. 2026, 150(1), 75; https://doi.org/10.3390/engproc2026150075 - 24 Jul 2026

Viewed by 207

Abstract

Anticipating component degradation before failure occurs has become a cornerstone of intelligent condition monitoring in safety-critical engineering environments. This paper benchmarks three supervised learning algorithms—Linear Regression (LR), Random Forest (RF), and Gradient Boosting (GB)—against each other for the task of Remaining Useful Life [...] Read more.

Anticipating component degradation before failure occurs has become a cornerstone of intelligent condition monitoring in safety-critical engineering environments. This paper benchmarks three supervised learning algorithms—Linear Regression (LR), Random Forest (RF), and Gradient Boosting (GB)—against each other for the task of Remaining Useful Life (RUL) forecasting on turbofan engines, using the NASA CMAPSS FD001 simulation dataset as the evaluation testbed. The benchmark encompasses 100 run-to-failure training trajectories and 100 test sequences, each characterised by 21 on-board sensor channels recorded over successive flight cycles. Following a systematic preparation stage—which involved discarding uninformative constant-variance channels and applying a piecewise linear degradation labelling scheme capped at 125 cycles—all three algorithms were trained and scored on normalised feature vectors. Among the three candidates, Random Forest delivered the strongest results (RMSE = 17.09, MAE = 12.10, R² = 0.818), ahead of Gradient Boosting (RMSE = 17.42, R² = 0.811) and the linear baseline (RMSE = 20.60, R² = 0.736). These outcomes confirm that bagging-based ensemble regressors provide a compelling accuracy–deployability trade-off for degradation forecasting, with direct relevance to autonomous scheduling and condition surveillance in industrial automation contexts. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 1737 KB

Open AccessProceeding Paper

Transient Numerical Simulation of Reheating Furnace Behavior for Continuous Casting Rail Steel Blooms Prior to Rolling

by Jan Rybář, Sohaibullah Zarghoon, Sardar Maroofi, Sayed Yousuf Sayed, Stanislav Ďuriš, Ibrahim Shaikh and Peter Onderčo

Eng. Proc. 2026, 150(1), 76; https://doi.org/10.3390/engproc2026150076 - 24 Jul 2026

Viewed by 144

Abstract

In this study a transient finite element model was developed to examine the temperature evolution of continuous casting blooms during reheating prior to rail rolling. The simulation was carried out using COMSOL Multiphysics 5.6, incorporating convective and radiative heat transfer mechanisms under a [...] Read more.

In this study a transient finite element model was developed to examine the temperature evolution of continuous casting blooms during reheating prior to rail rolling. The simulation was carried out using COMSOL Multiphysics 5.6, incorporating convective and radiative heat transfer mechanisms under a three-zone furnace (preheating, heating and soaking) temperature schedule. The temperature distribution and soaking uniformity were evaluated over a 7200 s heating cycle. The results indicate that proper adjustment of furnace setpoints enables the bloom center to reach approximately 1220 °C while maintaining acceptable temperature uniformity

∆ T \leq 50 ℃

. This study shows how numerical modeling can be used to improve thermal homogeneity prior to hot rolling and optimize reheating furnace performance. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 8037 KB

Open AccessProceeding Paper

Research on Impact Resistance Using Free-Falling Dart Drop Testing of 3D-Printed Parts Made of ABS and PETG According to ASTM D1709

by Konstantin Chukalov, Sabi Sabev, Valeri Bakardzhiev, Agop Izmirliyan and Plamen Kasabov

Eng. Proc. 2026, 150(1), 77; https://doi.org/10.3390/engproc2026150077 - 24 Jul 2026

Viewed by 182

Abstract

The paper investigates impact resistance of 3D-printed ABS and PETG specimens with a falling dart drop. Twenty-five specimens of each material were manufactured in accordance with the ASTM D1709 standard, as well as twenty-five specimens of notched ABS. The test data is processed [...] Read more.

The paper investigates impact resistance of 3D-printed ABS and PETG specimens with a falling dart drop. Twenty-five specimens of each material were manufactured in accordance with the ASTM D1709 standard, as well as twenty-five specimens of notched ABS. The test data is processed when 10 cracked and 10 uncracked specimens are available. Dart drop tests are typical for specimens that are manufactured in the shape of films. The purpose of the test is to perform an impact from a certain height with a controlled velocity of the falling dart drop. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 1372 KB

Open AccessProceeding Paper

Implementation and Evaluation of the Shortest-Path Algorithm for GIS Network Routing

by Ventsislav Stanchev, Antonina Ivanova, Fatima Sapundzhi and Slavi Georgiev

Eng. Proc. 2026, 150(1), 78; https://doi.org/10.3390/engproc2026150078 - 27 Jul 2026

Viewed by 151

Abstract

This work examines the implementation and evaluation of shortest-path algorithm in a Geographic Information System environment integrating QGIS with a PostgreSQL/PostGIS spatial database. Spatial edge and junction layers stored in the PostgreSQL/PostGIS define a directed weighted network in which edge costs are derived [...] Read more.

This work examines the implementation and evaluation of shortest-path algorithm in a Geographic Information System environment integrating QGIS with a PostgreSQL/PostGIS spatial database. Spatial edge and junction layers stored in the PostgreSQL/PostGIS define a directed weighted network in which edge costs are derived from spatial distance and modified through a gradient-based cost function. The routing algorithm is implemented in Python using the PyQGIS library and a binary heap priority queue. Network data are loaded from the geodatabase and processed in memory to compute the optimal route between selected nodes. The resulting path is reconstructed as a dissolved polyline feature stored in the geodatabase and visualized within the GIS environment. The study also includes a theoretical comparison of several classical shortest-path algorithms—Dijkstra,

A^{*}

, Bellman–Ford, and Floyd–Warshall—with respect to their applicability to sparse spatial graphs typical of transportation networks. The analysis confirms the suitability of Dijkstra’s algorithm for such networks and demonstrates that routing outcomes depend directly on the definition of the edge cost function. The proposed workflow relies exclusively on open-source GISs and database technologies. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 12824 KB

Open AccessProceeding Paper

Experimental Determination of Mechanical Characteristics: Hardness and Roughness of PolyJet Test Bodies for Digital ABS Plus Material

by Miglena Paneva, Peter Panev and Stanislav Gyoshev

Eng. Proc. 2026, 150(1), 79; https://doi.org/10.3390/engproc2026150079 - 27 Jul 2026

Viewed by 112

Abstract

The present work is based on an experimental determination of the mechanical properties of test bodies made using PolyJet technology from the two-component material Digital ABS Plus. The parameters of the 3D printing of the test bodies and their dimensions are presented. The [...] Read more.

The present work is based on an experimental determination of the mechanical properties of test bodies made using PolyJet technology from the two-component material Digital ABS Plus. The parameters of the 3D printing of the test bodies and their dimensions are presented. The testing methods and equipment for the studied parameters of hardness and roughness are selected. Roughness studies were conducted according to different test body positions and orientations. Hardness studies were carried out according to the Shore D and Rockwell M scales for three types of test bodies: after 3D printing of their surface; inside the test body; and after applying thermal treatment to the test bodies. These indicators are extremely important in the evaluation of details and the possibility of their implementation in the production process. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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7 pages, 4323 KB

Open AccessProceeding Paper

Internal Strain Modeling for Liquid Micro Droplet Formation

by Valentin Mateev, Teodor Grakov, Martin Ralchev and Iliana Marinova

Eng. Proc. 2026, 150(1), 80; https://doi.org/10.3390/engproc2026150080 - 27 Jul 2026

Viewed by 132

Abstract

In this paper, the formation of viscous liquid droplets in a micro 3D printing process is presented. Differences in the behavior of liquid flows under specific microsystem conditions are numerically modeled. Two working fluids, water and acrylic resin, are numerically tested. The relationship [...] Read more.

In this paper, the formation of viscous liquid droplets in a micro 3D printing process is presented. Differences in the behavior of liquid flows under specific microsystem conditions are numerically modeled. Two working fluids, water and acrylic resin, are numerically tested. The relationship between the internal forces acting within the fluid volume during droplet formation, such as viscosity, surface tension, and capillary forces, is estimated. Results can be used for micro 3D printing process optimization. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 8157 KB

Open AccessProceeding Paper

Fluid Flow Modeling for Hollow Microchannel Cantilever for Micro 3D Printing

by Valentin Mateev, Teodor Grakov, Martin Ralchev and Iliana Marinova

Eng. Proc. 2026, 150(1), 81; https://doi.org/10.3390/engproc2026150081 - 27 Jul 2026

Viewed by 130

Abstract

Here a CFD model for a hollow microchannel cantilever is presented. Considered case is a part of a micromanipulator system for droplet pattern formation on a solid plane in microscale for 3D printing. Internal pressure distribution in the cantilever channel and tip are [...] Read more.

Here a CFD model for a hollow microchannel cantilever is presented. Considered case is a part of a micromanipulator system for droplet pattern formation on a solid plane in microscale for 3D printing. Internal pressure distribution in the cantilever channel and tip are calculated for precise process control. Four fluids are used in the CFD modeling as water, ethanol, ethylene glycol, cyclopentano-cycloheptene. Results on the fluid flow parameters according to used fluid type are calculated and presented. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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11 pages, 12204 KB

Open AccessProceeding Paper

The Influence of Infill Direction on the Tensile Strength of High-Speed FDM 3D-Printed ABS

by Tsvetomir Gechev, Veselin Tsonev, Nikola Kuzmanov, Velichka Ruykova and Krasimir Nedelchev

Eng. Proc. 2026, 150(1), 82; https://doi.org/10.3390/engproc2026150082 - 27 Jul 2026

Viewed by 156

Abstract

The paper presents an experimental evaluation of the influence of infill direction (raster angle) on the tensile strength of 3D-printed ABS (Acrylonitrile Butadiene Styrene) samples produced at high speed (200 mm/s infill), flat orientation, and 100% infill density via FDM (Fused Deposition Modeling). [...] Read more.

The paper presents an experimental evaluation of the influence of infill direction (raster angle) on the tensile strength of 3D-printed ABS (Acrylonitrile Butadiene Styrene) samples produced at high speed (200 mm/s infill), flat orientation, and 100% infill density via FDM (Fused Deposition Modeling). The printing material was dried before printing and then stored in a low-humidity environment with desiccant in order to minimize moisture absorption during the experiments. The testing and conditioning of the samples were performed in accordance with the EN ISO 527 standard. The results revealed that the highest mean tensile strength of 39.28 MPa is obtained with the aligned rectilinear pattern at 0° infill direction, while the lowest, 34.56 MPa, is obtained with the same pattern at 90° infill direction relative to the load direction. The tested material demonstrated moderate tensile strength anisotropy in the direction of the load based on the change in infill direction. Moreover, productivity when printing ABS can be significantly increased when the correct conditions are available, as the resulting mean tensile strength is comparable to or higher than that reported by the filament’s producer, which recommends printing at low to moderate speeds for optimal layer adhesion and structural integrity. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 3011 KB

Open AccessProceeding Paper

Investigation of Optimal Temperature Parameters in ABS Additive Printing

by Kliment Georgiev and Iva Naydenova

Eng. Proc. 2026, 150(1), 83; https://doi.org/10.3390/engproc2026150083 - 27 Jul 2026

Viewed by 161

Abstract

This article presents an experimental study aimed at determining the optimal printing temperatures for the nozzle and the build plate when printing ABS by evaluating the geometric accuracy of the parts. The recommended printing temperatures were analyzed, and various operating temperature regimes were [...] Read more.

This article presents an experimental study aimed at determining the optimal printing temperatures for the nozzle and the build plate when printing ABS by evaluating the geometric accuracy of the parts. The recommended printing temperatures were analyzed, and various operating temperature regimes were selected for the nozzle and the build plate. The experimental part is based on single-factor and two-factor experiments. An analysis of the manufacturing process was also performed. Despite the experimental determination of the optimal temperatures, the manufactured parts do not meet the specified tolerances. Further research is needed to determine the shrinkage coefficient and to make corrections to the initial model. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 1049 KB

Open AccessProceeding Paper

Impact of SMOTE Oversampling on Machine Learning Classifiers for Preeclampsia Prediction Under Severe Class Imbalance: Evidence from a Bulgarian Screening Cohort

by Vasil Derimanov, Boris Stoilov and Mitko Shopov

Eng. Proc. 2026, 150(1), 84; https://doi.org/10.3390/engproc2026150084 - 27 Jul 2026

Viewed by 151

Abstract

This paper evaluates machine learning (ML) classifiers for predicting preeclampsia (PE) and pregnancy-induced hypertension (PIH) using first-trimester screening data from 1383 pregnant women in Plovdiv, Bulgaria (2018–2020). Three classifiers—Logistic Regression (LR), Extra Trees Classifier (ETC), and Voting Classifier (VC)—are compared across multiple prediction [...] Read more.

This paper evaluates machine learning (ML) classifiers for predicting preeclampsia (PE) and pregnancy-induced hypertension (PIH) using first-trimester screening data from 1383 pregnant women in Plovdiv, Bulgaria (2018–2020). Three classifiers—Logistic Regression (LR), Extra Trees Classifier (ETC), and Voting Classifier (VC)—are compared across multiple prediction targets and feature configurations. The impact of SMOTE oversampling strategies on model performance in the context of a severe class imbalance (2.46% PE prevalence) is assessed. Logistic Regression achieves the highest AUC of 0.853 for preterm PE prediction without oversampling, while SMOTE significantly improves tree-based models (ETC: +0.058 AUC). A non-screened control cohort of 533 patients is evaluated separately using maternal characteristics alone (AUC 0.751). The ML model showed promising discrimination for preterm PE in this local cohort and warrants direct comparison with FMF-based risk stratification in future studies. These results support further validation of ML-based tools as potential components of future clinical decision support systems to extend systematic PE screening in resource-constrained settings. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 3412 KB

Open AccessProceeding Paper

Low-Cost Automation System for Sorting Parts of Type “Connector”

by Ivo Malakov and Velizar Zaharinov

Eng. Proc. 2026, 150(1), 85; https://doi.org/10.3390/engproc2026150085 - 28 Jul 2026

Viewed by 149

Abstract

The application of low-cost automation is a permanent trend in modern production. It is especially promising in control and sorting operations, characterized by labor-intensiveness and low productivity. The paper presents methods and approaches for implementing a system for sorting parts of the type [...] Read more.

The application of low-cost automation is a permanent trend in modern production. It is especially promising in control and sorting operations, characterized by labor-intensiveness and low productivity. The paper presents methods and approaches for implementing a system for sorting parts of the type “Connector” by size. The suitability of the parts for automated sorting is assessed, a method for control and sorting is selected, an original passive contact system for automatic orienting is described, and the main functional parameters of the system are determined. By unifying the transporting, control and sorting device, a simplified structure, increased reliability and low system cost are achieved. The main technical characteristics of the proposed system are indicated. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 7360 KB

Open AccessProceeding Paper

Modeling and Simulation of Planar Transformer for Flyback Converter

by Hristo Ibrishimov, Dimitar Arnaudov and Milko Yovchev

Eng. Proc. 2026, 150(1), 86; https://doi.org/10.3390/engproc2026150086 - 30 Jul 2026

Viewed by 185

Abstract

In this paper, the design of a planar transformer for a flyback converter and modeling using the finite element method are presented. Results are obtained for primary and secondary winding inductance, transformer leakage inductance, winding parasitic capacitances, winding current density, magnetic flux density, [...] Read more.

In this paper, the design of a planar transformer for a flyback converter and modeling using the finite element method are presented. Results are obtained for primary and secondary winding inductance, transformer leakage inductance, winding parasitic capacitances, winding current density, magnetic flux density, and distribution of magnetic field lines. A simulation of the operation of the converter in the continuous current mode and in border mode was made to validate the obtained electrical parameters. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 1472 KB

Open AccessProceeding Paper

Analysis of Natural Frequencies of a MacPherson Suspension Using Different Bushings’ Elastic Characteristics

by Stiliyana Taneva, Krasimir Ambarev and Valyo Nikolov

Eng. Proc. 2026, 150(1), 87; https://doi.org/10.3390/engproc2026150087 - 30 Jul 2026

Viewed by 91

Abstract

The first natural frequency is the most important vibration parameter during the design of suspensions. It has a major impact on vehicle ride comfort and handling. This paper presents the results of the effects of different bushings’ elastic characteristics of the natural frequencies [...] Read more.

The first natural frequency is the most important vibration parameter during the design of suspensions. It has a major impact on vehicle ride comfort and handling. This paper presents the results of the effects of different bushings’ elastic characteristics of the natural frequencies of a front-independent quarter MacPherson suspension system. The natural frequencies and mode shapes were obtained using Finite Element Analysis (FEA). A simulation study was conducted, taking into account the elastic characteristics of bushings and an analysis with two rubber bushings within the mounting of the arm (Case I), and a rubber bushing and a polyurethane bushing (Case II). The natural frequencies were also determined by Frequency Response Function (FRF) analysis. FRF analysis was performed using experimentally obtained acceleration and time data of the body. The experiment was conducted using a suspension tester and a measuring system. FEA was performed using SolidWorks 2023. The results were compared and analyzed. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 988 KB

Open AccessProceeding Paper

Identification of the Natural Frequencies of a MacPherson Suspension Using FFT, FRF, and Spectral Analysis

by Krasimir Ambarev, Stiliyana Taneva and Valyo Nikolov

Eng. Proc. 2026, 150(1), 88; https://doi.org/10.3390/engproc2026150088 - 30 Jul 2026

Viewed by 120

Abstract

This paper presents the results of identification of the natural frequencies of a MacPherson suspension using fast Fourier transform (FFT) analysis, frequency response function (FRF) analysis, and spectral analysis. Experimental investigations are conducted to determine the accelerations of a quarter-car MacPherson suspension system [...] Read more.

This paper presents the results of identification of the natural frequencies of a MacPherson suspension using fast Fourier transform (FFT) analysis, frequency response function (FRF) analysis, and spectral analysis. Experimental investigations are conducted to determine the accelerations of a quarter-car MacPherson suspension system of an Audi A3 passenger car at a tire inflation pressure of 0.22 MPa. The investigated suspension control arm was equipped with one original equipment manufacturer (OEM) bushing and one polyurethane bushing. The paper also presents the results obtained using a set of MATLAB scripts developed for processing the vibration measurement data acquired from the components of the vehicle’s quarter-car suspension system, with each script corresponding to a specific analysis approach. The developed scripts implement several methods for analyzing the recorded acceleration signals, including FFT, FRF, and spectral analysis. The results obtained by applying these three methods to the experimental data are compared and discussed. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 1367 KB

Open AccessProceeding Paper

Statistical Distribution of Electrical Properties of Wire Arc Additively Manufactured ER4043 Aluminum Alloy Components

by Valentin Mateev, Georgi Kotlarski, Iliana Marinova, Stefan Valkov, Maria Ormanova and Daniela Stoeva

Eng. Proc. 2026, 150(1), 89; https://doi.org/10.3390/engproc2026150089 - 30 Jul 2026

Viewed by 149

Abstract

This paper is dedicated to the determination of the electrical properties of a wire arc additively manufactured (WAAM) aluminum alloy component. Statistical processing of the electrical properties and hollow micro-interlayer zones of the WAAM sample made of ER4043 aluminum alloy is performed. The [...] Read more.

This paper is dedicated to the determination of the electrical properties of a wire arc additively manufactured (WAAM) aluminum alloy component. Statistical processing of the electrical properties and hollow micro-interlayer zones of the WAAM sample made of ER4043 aluminum alloy is performed. The eddy current electrical conductivity measurement method is employed for WAAM 3D-printed sample surface properties mapping. Measured data on electrical conductivity are estimated depending on the 3D printing axis directions and the lift-off distance from the sample surface. The 3D standard deviation is calculated for property anisotropy correlation. These data can be used for improved additive manufacturing control for enhanced electrical conductivity of aluminum WAAM samples as well as for numerical modeling of the properties of such samples. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 2569 KB

Open AccessProceeding Paper

Data-Driven Electricity Forecasting for Small Grid-Tied Photovoltaic Power Plants in the Transition from Centralized to Distributed Generation

by Rumen Mihailov and Vladimir Valkanov

Eng. Proc. 2026, 150(1), 90; https://doi.org/10.3390/engproc2026150090 - 30 Jul 2026

Viewed by 119

Abstract

The rapid expansion of renewable weather-dependent electricity generators has created a challenge in the way grid operators manage electricity dispatch. This article explores the core challenges of managing the instantaneous balance between generation and consumption needed to maintain healthy grid operation. The magnitude [...] Read more.

The rapid expansion of renewable weather-dependent electricity generators has created a challenge in the way grid operators manage electricity dispatch. This article explores the core challenges of managing the instantaneous balance between generation and consumption needed to maintain healthy grid operation. The magnitude of the challenge is depicted clearly by the 2025 Iberian Peninsula blackout, listing as a main contributing factor the large penetration of renewable energy in the grid. The article proposes a model to better forecast photovoltaic production and limit grid entropy. It also outlines how the implementation of such a model would lead to increased feed-in prices for producers and offset renewable cannibalization as well as a lower end-user electricity bill. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 834 KB

Open AccessProceeding Paper

A Parametric CNC Approach for Buttress Thread Machining

by Plamen Kasabov, Konstantin Chukalov, Sabi Sabev, Valeri Bakardzhiev and Agop Izmirliyan

Eng. Proc. 2026, 150(1), 91; https://doi.org/10.3390/engproc2026150091 - 31 Jul 2026

Viewed by 112

Abstract

The threaded connections used in drilling machines operate under high axial loads and torques. These elements ensure both the reliable fastening of the drill heads and their centering relative to the other components of the structure. For fastening drill heads, threads with specific [...] Read more.

The threaded connections used in drilling machines operate under high axial loads and torques. These elements ensure both the reliable fastening of the drill heads and their centering relative to the other components of the structure. For fastening drill heads, threads with specific profiles are used, such as trapezoidal profiles with asymmetric flanks. A profile tool is typically used for manufacturing such profiles. This, in turn, limits the flexibility of the process and increases costs in small-batch and repair production conditions. This study proposes a methodology for machining a buttress thread, with trapezoid side angles of 5° and 45°, using a standard grooving insert. The profile geometry is described analytically through the height of each pass of the threading cycle and the inclination angles of the trapezoid flanks, and the implementation is carried out using a macro program based on synchronized G92 cycles. The final profile is formed by the superposition of helical surfaces with a constant pitch. The approach enables the realization of non-standard trapezoidal profiles without the need for a specially profiled tool. The proposed model serves as a foundation for subsequent research into the geometric accuracy and strength characteristics of the thread profile obtained by this method. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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7 pages, 302 KB

Open AccessProceeding Paper

Noise Estimation in Zero-Shot Plug-and-Play Reconstruction for 3D MPI Data

by Vladyslav Gapyak, Thomas März and Andreas Weinmann

Eng. Proc. 2026, 150(1), 92; https://doi.org/10.3390/engproc2026150092 - 31 Jul 2026

Viewed by 118

Abstract

In Magnetic Particle Imaging (MPI), the scans of delta concentrations can be collected in a system matrix and a target distribution of particles injected in a specimen can be retrieved by regularized inversion of the associated linear system, using the scan of the [...] Read more.

In Magnetic Particle Imaging (MPI), the scans of delta concentrations can be collected in a system matrix and a target distribution of particles injected in a specimen can be retrieved by regularized inversion of the associated linear system, using the scan of the specimen as data. Recent publications show that ill-posed inverse problems can be solved with Plug-and-Play (PnP) algorithms, which split at each iteration the general regularized inversion into a simpler Tikhonov-type problem and a Gaussian denoising problem. By substituting the Gaussian denoising step with machine learning-based denoisers, it is possible to leverage the performance of Neural Networks in the denoising task. In particular, it has been shown that it is possible to employ publicly available and general-purpose denoisers into the MPI reconstruction task in a Zero-Shot fashion (no ad hoc training necessary). In the specific algorithm considered, each denoising step takes as input the noise level of the Tikhonov subproblem and works in particular with a very coarse estimation of the noise level as variance of the iterate. In this work we explore the benefit of using a better estimation of the noise level using convolution with the Laplacian. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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20 pages, 2624 KB

Open AccessProceeding Paper

Quantum Image Encoding Fidelity Metric (QIEF) for Performance Evaluation of Quantum Devices

by Alexander Geng and Ali Moghiseh

Eng. Proc. 2026, 150(1), 93; https://doi.org/10.3390/engproc2026150093 - 1 Aug 2026

Viewed by 145

Abstract

The rapid advancement of quantum technologies has led to a growing and diverse landscape of quantum computing devices, each with varying architectures and capabilities. Most of them are evaluated using hardware-centric benchmarks such as gate fidelity, quantum volume, or coherence time. However, these [...] Read more.

The rapid advancement of quantum technologies has led to a growing and diverse landscape of quantum computing devices, each with varying architectures and capabilities. Most of them are evaluated using hardware-centric benchmarks such as gate fidelity, quantum volume, or coherence time. However, these metrics often fail to capture performance in problem-specific contexts, particularly in applications involving quantum image processing. In this work, we address this gap by introducing the Quantum Image Encoding Fidelity (QIEF) metric, a novel task-specific benchmark designed to evaluate how accurately quantum devices can encode classical image data into quantum representations. By focusing on image-specific criteria rather than device-agnostic parameters, QIEF offers a more application-relevant assessment of device capability, enabling a direct comparison of quantum hardware based on their effectiveness in real-world image-related tasks. We present the theoretical formulation of the QIEF, validate its relevance through quantum simulators and experiments on real quantum devices, and discuss its implications for guiding future hardware development tailored to quantum image processing applications. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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15 pages, 2361 KB

Open AccessProceeding Paper

A Quantum Fourier Transform Approach for Image Alignment

by Alexander Geng and Ali Moghiseh

Eng. Proc. 2026, 150(1), 94; https://doi.org/10.3390/engproc2026150094 - 1 Aug 2026

Viewed by 131

Abstract

This work explores the practical application of the Quantum Fourier Transform (QFT) for image alignment, focusing on the estimation of rotation angles in grayscale images containing structured line patterns and text. Motivated by the need to demonstrate quantum computing’s potential in addressing real-world [...] Read more.

This work explores the practical application of the Quantum Fourier Transform (QFT) for image alignment, focusing on the estimation of rotation angles in grayscale images containing structured line patterns and text. Motivated by the need to demonstrate quantum computing’s potential in addressing real-world image processing tasks, we develop a hybrid approach that combines classical pre-processing with quantum computation. We demonstrate that QFT can be applied to a concrete image processing task, illustrating the practical utility of quantum computing beyond theoretical examples. A classical baseline using the Fast Fourier Transform (FFT) is implemented via the ToolIP framework, achieving fast and accurate angle estimation. In parallel, a quantum version replaces the FFT with a simulated QFT on IBM’s Qiskit platform, using the Quantum Image Encoding Probability scheme to reduce qubit requirements. The classical method delivers results in milliseconds, while the quantum implementation, constrained by simulation and encoding overhead, demands significantly greater computational effort. Nonetheless, our findings show that QFT-based angle estimation is feasible and can yield results comparable to classical techniques. This study demonstrates the applicability of quantum algorithms to real-world image processing and underscores both the theoretical promise of QFT and the practical limitations faced in the current Noisy Intermediate-Scale Quantum (NISQ) era. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 20236 KB

Open AccessProceeding Paper

Application of 3D-Printed Patterns in Sand Casting

by Mihail Zagorski, Krum Petrov, Antonio Nikolov and Rayna Dimitrova

Eng. Proc. 2026, 150(1), 95; https://doi.org/10.3390/engproc2026150095 - 1 Aug 2026

Viewed by 120

Abstract

The present article considers the feasibility of using 3D-printed patterns for sand casting applications. The patterns have been produced by FDM/FFF technology, and the casting process has been simulated in the specialized CAE software product ProCAST. A prototype series of castings has been [...] Read more.

The present article considers the feasibility of using 3D-printed patterns for sand casting applications. The patterns have been produced by FDM/FFF technology, and the casting process has been simulated in the specialized CAE software product ProCAST. A prototype series of castings has been produced for the purpose of experimentally validating the applicability of 3D-printed patterns in the sand casting process. The results obtained demonstrate the significant potential of 3D-printed patterns to streamline the technological process in the manufacture of foundry tooling equipment. The use of additive-manufactured patterns reduces the time required for their design and production and increases flexibility in the manufacture of prototypes or small series products. The result is more efficient production planning and a reduction in the overall time required to produce sand castings. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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17 pages, 2545 KB

Open AccessProceeding Paper

Hybrid Quantum–Classical AI for Industrial Defect Classification in Welding Images

by Akshaya Srinivasan, Xiaoyin Cheng, Jianming Yi, Alexander Geng, Desislava Ivanova, Andreas Weinmann and Ali Moghiseh

Eng. Proc. 2026, 150(1), 96; https://doi.org/10.3390/engproc2026150096 - 1 Aug 2026

Viewed by 157

Abstract

Hybrid quantum–classical machine learning offers a promising direction for advancing automated quality control in industrial settings. In this study, we investigate two hybrid quantum–classical approaches for classifying defects in aluminum TIG welding images and benchmarking their performance against a conventional deep learning model. [...] Read more.

Hybrid quantum–classical machine learning offers a promising direction for advancing automated quality control in industrial settings. In this study, we investigate two hybrid quantum–classical approaches for classifying defects in aluminum TIG welding images and benchmarking their performance against a conventional deep learning model. A convolutional neural network is used to extract compact and informative feature vectors from weld images, effectively reducing the higher-dimensional pixel space to a lower-dimensional feature space. Our first quantum approach encodes these features into quantum states using a parameterized quantum feature map composed of rotation and entangling gates. We compute a quantum kernel matrix from the inner products of these states, defining a linear system in a higher-dimensional Hilbert space corresponding to the support vector machine (SVM) optimization problem and solving it using a Variational Quantum Linear Solver (VQLS). We also examine the effect of the quantum kernel condition number on classification performance. In our second method, we apply angle encoding to the extracted features in a variational quantum circuit and use a classical optimizer for model training. Both quantum models are tested on binary and multiclass classification tasks, and the performance is compared with the classical CNN model. Our results show that while the CNN model demonstrates robust performance, hybrid quantum–classical models perform competitively. This highlights the potential of hybrid quantum–classical approaches for near-term real-world applications in industrial defect detection and quality assurance. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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13 pages, 2098 KB

Open AccessProceeding Paper

Overview of the Application of Innovation Management Tools and Methods in the Industry

by Tzvetelin Gueorguiev, Kristian Tsvetkov and Kiril Lengerov

Eng. Proc. 2026, 150(1), 97; https://doi.org/10.3390/engproc2026150097 - 1 Aug 2026

Viewed by 148

Abstract

This paper presents a comprehensive review of innovation management tools and methods. It is based on the analysis of a specific segment of available specialized and research bibliographies, i.e., current international standards for innovation management systems that have been published as the ISO [...] Read more.

This paper presents a comprehensive review of innovation management tools and methods. It is based on the analysis of a specific segment of available specialized and research bibliographies, i.e., current international standards for innovation management systems that have been published as the ISO 56000 series since 2019. The innovation management tools and methods presented in this paper are related to innovation partnerships, intellectual property management, strategic intelligence management, managing innovation opportunities and ideas, and innovation operation measurements. The innovation management tools and methods are aligned with the clauses of ISO 56001. The findings present opportunities for industrial organizations to implement specific tools and methods and to realize value from innovation processes, activities, and initiatives. The conclusions summarize the results of the analysis and highlight directions for further development and improvement of existing innovation management systems in the industry. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 250 KB

Open AccessProceeding Paper

Degradation of Stylometric Attribution Accuracy for AI-Generated Text

by Kalin Kopanov and Tatiana Atanasova

Eng. Proc. 2026, 150(1), 98; https://doi.org/10.3390/engproc2026150098 - 3 Aug 2026

Viewed by 130

Abstract

The growing use of large language models (LLMs) makes it essential to identify which system produced a given text. Existing stylometric detectors perform well on raw outputs; however, users routinely translate, paraphrase, or edit content before release. These transformations can erase the lexical [...] Read more.

The growing use of large language models (LLMs) makes it essential to identify which system produced a given text. Existing stylometric detectors perform well on raw outputs; however, users routinely translate, paraphrase, or edit content before release. These transformations can erase the lexical and syntactic cues that support attribution. This study measures the resulting performance drop on a purpose-built benchmark of synthetic responses from two instruction-tuned models, Qwen 2.5 (32B) and Gemma 3 (27B). Each passage is subjected to common editing workflows ranging from machine translation to paraphrasing and grammar-focused rewriting. The edited variants are evaluated using a custom machine-learning classifier. Overall, attribution remains robust, but obfuscation leads to degradation that often renders the text unusable for professional purposes. Although the analysis is limited to data from two LLMs, the controlled setting shows how specific post-editing actions alter stylometric signals. Recognising this sensitivity is essential for academic integrity checks, platform-moderation tools, and the ongoing debate between watermarking and stylometry. The results provide practical guidance on developing attribution methods that remain reliable after routine text updates. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

13 pages, 4326 KB

Open AccessProceeding Paper

Prediction of Cutting Tool Wear in Turning

by Svetlana Koleva

Eng. Proc. 2026, 150(1), 99; https://doi.org/10.3390/engproc2026150099 - 30 Jul 2026

Viewed by 54

Abstract

The paper examines the possibility of compensating one of the significant systematic factors in turning that affects the quality of machined surfaces—namely, the dimensional wear of cutting inserts during finish turning. Predictive wear models are developed in which the process is approximated using [...] Read more.

The paper examines the possibility of compensating one of the significant systematic factors in turning that affects the quality of machined surfaces—namely, the dimensional wear of cutting inserts during finish turning. Predictive wear models are developed in which the process is approximated using either a linear or an exponential function. The wear prediction error is determined. Based on data from the authors’ experimental studies and other published sources, the duration and intensity of the initial and steady-state wear stages are established. A corrected predictive function is presented, consisting of a nonlinear initial segment and a linear steady-state segment. A design variant of a measuring probe for monitoring the current wear of the insert cutting edge, applicable under production conditions, is also proposed. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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13 pages, 5678 KB

Open AccessProceeding Paper

A Study and Small-Signal Modeling of a Two-Switch Buck–Boost Converter Considering Parasitic Elements

by Ivan Ivanov Genov and Tsvetana Grigorova

Eng. Proc. 2026, 150(1), 100; https://doi.org/10.3390/engproc2026150100 - 3 Aug 2026

Viewed by 119

Abstract

The paper presents an analytical study and small-signal modeling of a non-inverting two-switch buck–boost converter based on the LM5118 controller, accounting for parasitic elements. The converter dynamics were analyzed using simulations in the PLECS^® 5.0.2 environment. Furthermore, the steady-state and dynamic characteristics [...] Read more.

The paper presents an analytical study and small-signal modeling of a non-inverting two-switch buck–boost converter based on the LM5118 controller, accounting for parasitic elements. The converter dynamics were analyzed using simulations in the PLECS^® 5.0.2 environment. Furthermore, the steady-state and dynamic characteristics of the LM5118-based two-switch buck–boost converter were examined using the PSpice for TI^® simulator for different input voltages and load conditions. The obtained simulation results show close correspondence with the analytical analysis, confirming the validity of the proposed approach. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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21 pages, 3220 KB

Open AccessProceeding Paper

Transforming Educational Attendance Systems Through Advanced Facial Recognition and Machine Learning

by Issa Kamar and Galina Momcheva

Eng. Proc. 2026, 150(1), 101; https://doi.org/10.3390/engproc2026150101 - 3 Aug 2026

Viewed by 218

Abstract

These days, learning management systems have been instrumental in changing the face of online education. Nonetheless, a significant shortcoming in distance education is the attendance reports. This paper addresses the need to streamline attendance control and administration in institutions, particularly the education sector, [...] Read more.

These days, learning management systems have been instrumental in changing the face of online education. Nonetheless, a significant shortcoming in distance education is the attendance reports. This paper addresses the need to streamline attendance control and administration in institutions, particularly the education sector, by introducing a novel real-time facial recognition-based tracking system. The facial recognition mechanism at the heart of the system is a state-of-the-art technology that enhances attendance tracking. The system can use sophisticated algorithms and machine learning approaches to achieve accurate identification and detection. Together with important features like dynamic charts and real-time insights, the system also includes a dashboard that is used to centralize real-time records for better tracking and managing attendance. This enhanced data visibility enables the administrator to make well-informed decisions. Additionally, because the dashboard can be dynamically altered to suit the requirements of administrators and institutions, admininistrators can quickly become accustomed to the system thanks to dashboard modification. Thus, a significant advancement in attendance management has been made with the PHP 8.3 and Python 3.12 based facial recognition attendance system. Because of its user-friendly interface and instantaneous insights, it can be an invaluable tool for educational institutions looking to improve the effectiveness of their daily operations and optimize attendance monitoring procedures. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 2696 KB

Open AccessProceeding Paper

Wind Tunnel Experiment and Analysis of Aerodynamic Characteristics of eVTOL Aircraft

by Martin Zikyamov, Hristian Panayotov and Stanimir Penchev

Eng. Proc. 2026, 150(1), 102; https://doi.org/10.3390/engproc2026150102 - 30 Jul 2026

Viewed by 49

Abstract

This report presents an experimental study focused on parametric optimization of an electric vertical take-off and landing (eVTOL) wing–propeller lifting system. The experiments were conducted in a wind tunnel equipped with a Particle Image Velocimetry (PIV) system, and a wing–propeller thrust and power [...] Read more.

This report presents an experimental study focused on parametric optimization of an electric vertical take-off and landing (eVTOL) wing–propeller lifting system. The experiments were conducted in a wind tunnel equipped with a Particle Image Velocimetry (PIV) system, and a wing–propeller thrust and power measurement test stand was used. The total mission flight energy was evaluated and compared for three different propeller-to-wing gross area ratios and three mission profiles. Two principal configurations of the wing–propeller lifting system were considered, corresponding to the hovering and cruising stages of flight. In these configurations, both the propellers and the tilting wing sections were oriented according to the requirements of hover and cruise operation. The total flight energy was adopted as the figure of merit and was calculated for all design points. The figure of merit was then analyzed as a function of the propeller-to-wing gross area ratio. The results allowed the determination of optimal configurations for different hover times. Finally, the total flight energy obtained from the experiments was calculated and compared with the corresponding simulation results. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 5921 KB

Open AccessProceeding Paper

Web-Based Financial Diary: Architecture, Functionalities and Application for Personal Finance Management

by Stanislav Dakov and Megi Dakova

Eng. Proc. 2026, 150(1), 103; https://doi.org/10.3390/engproc2026150103 - 4 Aug 2026

Viewed by 89

Abstract

This article offers a conceptual overview and functional analysis of the author’s web-based application LolyDash, a tool for managing personal finances through structured dashboards for expenses, income, notes, and group fundraising. The main features of the system, its advantages over traditional financial tracking [...] Read more.

This article offers a conceptual overview and functional analysis of the author’s web-based application LolyDash, a tool for managing personal finances through structured dashboards for expenses, income, notes, and group fundraising. The main features of the system, its advantages over traditional financial tracking solutions, visual analytical tools, and categorization and planning mechanisms, and its integration capabilities via webhook are described. This article argues for the need for modern digital tools for financial literacy in the context of the growing complexity of personal financial management. This article examines the concept of a web-based financial diary that integrates functionalities for managing expenses, income, financial notes, and group payments within a single information system. The main components of the system, its advantages over traditional financial management methods, and the potential for future development through the integration of artificial intelligence are analyzed. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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7 pages, 2033 KB

Open AccessProceeding Paper

Multimodal Machine Learning Models Using Zero-Shot Learning to Control Robots

by Vladimir Kotev, Ivan Ivanov, Kosuke Kakikoshi, Stanislav Georgiev and Ken’ichi Yano

Eng. Proc. 2026, 150(1), 104; https://doi.org/10.3390/engproc2026150104 - 4 Aug 2026

Viewed by 96

Abstract

Substantial growth has been observed in large language models (LLMs), which are increasingly applied across various fields. The integration of vision–language models trained on Internet-scale data into end-to-end robotic control systems to enhance generalization and enable emergent semantic reasoning is studied. A small-size [...] Read more.

Substantial growth has been observed in large language models (LLMs), which are increasingly applied across various fields. The integration of vision–language models trained on Internet-scale data into end-to-end robotic control systems to enhance generalization and enable emergent semantic reasoning is studied. A small-size mobile robot with a 6 DoF arm is designed and developed in order to study and test a control approach utilizing vision–language models trained on Internet-scale data. The current work studies whether an LLM (GPT-4) can directly predict sequences of commands for mobile robot control to execute given tasks. An algorithm for measuring distance among objects is developed because the robot has only one camera and there are no other sensors for distance measurement. The performance of a single task-agnostic prompt, devoid of in-context examples, motion primitives, or external trajectory optimizers, in executing various tasks is evaluated. Furthermore, a framework that leverages multimodal GPT-4 to enhance task planning by integrating natural language instructions with robot visual perceptions is proposed. Indoor experiments show that the robot could execute different tasks such as moving to various objects that surround us in rooms and offices. Users write/input commands on the PC and the robot executes them. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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25 pages, 773 KB

Open AccessProceeding Paper

Research on Traffic Delays Caused by Pedestrians Crossing at a Light-Regulated Intersection: Case Study of City of Sofia

by Durhan Saliev, Tsvetan Valkovski, Lyubomir Laskov and Milen Markov

Eng. Proc. 2026, 150(1), 105; https://doi.org/10.3390/engproc2026150105 - 4 Aug 2026

Viewed by 121

Abstract

The safe crossing of pedestrians at traffic light-regulated intersections is ensured by the permissive and prohibitive signals provided for them and by certain priority rules that drivers in traffic flows conflicting with pedestrians must comply with. This in turn leads to the occurrence [...] Read more.

The safe crossing of pedestrians at traffic light-regulated intersections is ensured by the permissive and prohibitive signals provided for them and by certain priority rules that drivers in traffic flows conflicting with pedestrians must comply with. This in turn leads to the occurrence of traffic delays, which are inevitable under certain traffic conditions. The present study focuses on determining the length of traffic delays when pedestrians cross at a traffic light-regulated intersection in the city of Sofia, Republic of Bulgaria. The intersection was selected due to the high intensity of pedestrian flows established in preliminary random observations, which is provoked by its location. The study includes determining the traffic delays over a period of 12 h with full readings of these indicators for each cycle of the traffic light system during the morning and evening peak periods and with partial readings for 15 min for each cycle in the remaining hours of the study period. The results show the lack of a relationship between the waiting time of vehicles and the number of pedestrians crossing. Such an influence can be sought in the behavior and types of pedestrians and the intervals at which they enter the crosswalk. This study can assist researchers in this field in developing pedestrian crossing models and determining additional measures to increase their safety when crossing light-regulated intersections. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 1511 KB

Open AccessProceeding Paper

Cyber Response Automation with Dedicated AI Agents

by Stanimir Kabaivanov and Veneta Markovska

Eng. Proc. 2026, 150(1), 106; https://doi.org/10.3390/engproc2026150106 - 3 Aug 2026

Viewed by 92

Abstract

Proactive cyber security has moved from being an innovative approach to an essential requirement for business success, especially considering the large number of new tools and technologies that organizations need to learn and use. In this paper, we discuss and demonstrate the possibility [...] Read more.

Proactive cyber security has moved from being an innovative approach to an essential requirement for business success, especially considering the large number of new tools and technologies that organizations need to learn and use. In this paper, we discuss and demonstrate the possibility of automating important cyber security and immediate response steps with the use of dedicated artificial intelligence agents. We focus on local-first solutions that are able to keep sensitive data private and at the same time fit well with existing data protection policies and infrastructure. Using a minimalist AI agent addressing a local large language model, we experiment with skills aimed at running cyber security tools and processing their output in support of cyber incident response. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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13 pages, 2403 KB

Open AccessProceeding Paper

Design and Technology Development of an Innovative Biodegradable Single-Use Cup

by Konstantin Kamberov, Georgi Chernev, Maria Ivanova and Martina Stipchekova

Eng. Proc. 2026, 150(1), 107; https://doi.org/10.3390/engproc2026150107 - 4 Aug 2026

Viewed by 93

Abstract

The presented study is dedicated to a “green” solution for hot beverage packaging—a biodegradable single-use cup. Product development follows a specifically elaborated methodology that involves initial material characterization, followed by adjusted product design. The research and design activities continue toward mold design development [...] Read more.

The presented study is dedicated to a “green” solution for hot beverage packaging—a biodegradable single-use cup. Product development follows a specifically elaborated methodology that involves initial material characterization, followed by adjusted product design. The research and design activities continue toward mold design development and testing. The study concludes with a cost analysis, in which an alternative material composition is also examined. The finalized product is ready for industrialization, reaching TRL 5, with assessed financial aspects. This study is a good demonstration of the application of modern technologies and tools for the development of an innovative product. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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14 pages, 9733 KB

Open AccessProceeding Paper

Optimizing Computer Mouse Shell Design Based on Vietnamese Student Anthropometry

by Thi Ngoc Anh La and Thanh Thuy Hoang

Eng. Proc. 2026, 150(1), 108; https://doi.org/10.3390/engproc2026150108 - 4 Aug 2026

Viewed by 67

Abstract

This study proposes a comprehensive design framework for computer mice tailored to Vietnamese users, based on anthropometric data collected from 610 university students using a cross-sectional survey. Three important parameters—hand length, finger length, and palm width—were used to specify five optimal size groups [...] Read more.

This study proposes a comprehensive design framework for computer mice tailored to Vietnamese users, based on anthropometric data collected from 610 university students using a cross-sectional survey. Three important parameters—hand length, finger length, and palm width—were used to specify five optimal size groups with an overall satisfaction rate of 81.7%. The average hand length of 186 mm places Vietnamese users within the 20th–30th percentile of the U.S. population (ANSUR), suggesting that devices designed as medium-sized in Western markets may be oversized in Vietnam. Parametric modeling combined with Fitts’ Law and ISO 9241 produced geometrically precise designs that reduce discomfort at inclination angles of 25–30%, while also enabling the development of a user-friendly tool for selecting the most appropriate mouse size for consumers. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 1912 KB

Open AccessProceeding Paper

Rheological Properties of Bitumen Modified with Crumb Rubber and Devulcanized Rubber

by Akkenzhe Bussurmanova, Anar Akkenzheyeva and Uzilkhan Yensegenova

Eng. Proc. 2026, 150(1), 109; https://doi.org/10.3390/engproc2026150109 - 4 Aug 2026

Viewed by 90

Abstract

The modification of bitumen with recycled rubber materials has gained significant attention due to its potential to enhance pavement performance and support sustainable waste management. In this study, the rheological properties of bitumen modified with crumb rubber (CR) and devulcanized crumb rubber (DCR) [...] Read more.

The modification of bitumen with recycled rubber materials has gained significant attention due to its potential to enhance pavement performance and support sustainable waste management. In this study, the rheological properties of bitumen modified with crumb rubber (CR) and devulcanized crumb rubber (DCR) were investigated. Rubber modifiers were added at concentrations of 5–25% by weight, and the rheological behavior was evaluated using a Dynamic Shear Rheometer at 1.59 Hz over a temperature range of 46–96 °C. Key parameters, including storage modulus (G′), loss modulus (G″), and complex viscosity (η*), were analyzed. The results indicate that increasing rubber content significantly enhances stiffness and viscosity, improving resistance to deformation at elevated temperatures. Moreover, DCR-modified binders exhibit higher rheological performance compared to CR systems, indicating better compatibility with the bitumen matrix. Overall, devulcanized rubber demonstrates superior efficiency as a modifier and shows strong potential for improving the durability and high-temperature performance of asphalt binders. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 2238 KB

Open AccessProceeding Paper

Determination of UV Intensity and Radiation Dose from an LED for Active Air Purification for Personal Protective Equipment

by Konstantin Kamberov, Blagovest Zlatev, Yavor Sofronov, Denitsa Ivanova-Mutafchieva, Mario Semkov and Todor Todorov

Eng. Proc. 2026, 150(1), 110; https://doi.org/10.3390/engproc2026150110 (registering DOI) - 5 Aug 2026

Viewed by 75

Abstract

The study concerns the simulation of an active personal protective mask that performs air purification of incoming and outgoing air to and from the user using ultraviolet germicidal irradiation (UVGI). The specific method for determining the radiation dose is done using a CFD [...] Read more.

The study concerns the simulation of an active personal protective mask that performs air purification of incoming and outgoing air to and from the user using ultraviolet germicidal irradiation (UVGI). The specific method for determining the radiation dose is done using a CFD simulation of the process of breathing to determine the duration of the irradiation of the air. Additionally, an optical simulation is performed in order to determine the average irradiance in the illuminated zone. For the purposes of the UVGI, a radiation dose of 20–40 J/m² is sufficient to achieve LD90 when applied to most Flu and Corona viruses. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 1253 KB

Open AccessProceeding Paper

Optimizing Industrial Workflows: A Synergistic Approach with AIoT and Large Language Models

by Victor K. Danev and Viktorya V. Muchanova

Eng. Proc. 2026, 150(1), 111; https://doi.org/10.3390/engproc2026150111 - 5 Aug 2026

Viewed by 126

Abstract

The article explores the transformative impact of integrating the Internet of Things (IoT) and Artificial Intelligence (AI) on optimizing industrial workflows. The synergy between IoT and AI (AIoT) enables real-time data-driven decision-making and automation. This leads to increased operational efficiency, predictive maintenance, improved [...] Read more.

The article explores the transformative impact of integrating the Internet of Things (IoT) and Artificial Intelligence (AI) on optimizing industrial workflows. The synergy between IoT and AI (AIoT) enables real-time data-driven decision-making and automation. This leads to increased operational efficiency, predictive maintenance, improved decision-making, optimized energy consumption, enhanced quality control, reduced costs, and improved safety. The mechanics of this optimization involve collecting data from IoT devices and performing intelligent analysis with AI. Edge computing reduces latency in data processing. Implementation challenges are addressed, focusing on data security, the complexities of integrating new technologies with legacy systems, and the critical need for skilled personnel proficient in IoT, AI, data analytics, and cybersecurity. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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12 pages, 4314 KB

Open AccessProceeding Paper

Multi-Parameter Optimization of Process Modes in Injection Molding of Plastic Product

by Todor T. Todorov, Georgi Todorov and Yavor Sofronov

Eng. Proc. 2026, 150(1), 112; https://doi.org/10.3390/engproc2026150112 - 3 Aug 2026

Viewed by 31

Abstract

The work presented demonstrate a methodology for multi-parameter optimization of process parameters in plastic injection molding, with a focus on established techniques such as DOE (Design of Experiment) Taguchi, root cause diagram, and rapid prediction methods. The aim of the study is to [...] Read more.

The work presented demonstrate a methodology for multi-parameter optimization of process parameters in plastic injection molding, with a focus on established techniques such as DOE (Design of Experiment) Taguchi, root cause diagram, and rapid prediction methods. The aim of the study is to improve the efficiency and accuracy of the production process by reducing the iterations for searching the optimal parameters to satisfy specific requirements and constraints. Through the implementation of these methods, it strives to achieve more stable and predictable process conditions, which ultimately leads to a reduction in crucial defects and improvement in the quality of the manufactured products. Exploring the possibilities of multi-parameter optimization offers an innovative approach to solving complex problems in engineering practice by providing a systematic method to analyze and manage various factors affecting the final result. This approach not only improves production processes, but also contributes to a wider understanding and optimization of the operation of the system as a whole. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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6 pages, 229 KB

Open AccessProceeding Paper

Green’s Function for Non-Homogeneous Magneto-Electro-Elastic Half-Plane

by Yonko Stoynov

Eng. Proc. 2026, 150(1), 113; https://doi.org/10.3390/engproc2026150113 (registering DOI) - 5 Aug 2026

Viewed by 49

Abstract

An exponentially graded magneto-electro-elastic (MEE) half-plane subjected to anti-plane mechanical and in-plane electric and magnetic time-harmonic external load is considered. Green’s function in the MEE half-plane is analytically derived using the fundamental solution in the MEE plane and the integral representation of the [...] Read more.

An exponentially graded magneto-electro-elastic (MEE) half-plane subjected to anti-plane mechanical and in-plane electric and magnetic time-harmonic external load is considered. Green’s function in the MEE half-plane is analytically derived using the fundamental solution in the MEE plane and the integral representation of the Hankel functions. The solutions presented here can be further used in computational schemes based on the boundary elements method (BEM) to obtain numerical results in a cracked homogeneous and non-homogeneous half-plane. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

8 pages, 248 KB

Open AccessProceeding Paper

Fracture Problems in Graded Magneto-Electro-Elastic Half-Plane by Boundary Integral Equations

by Yonko Stoynov

Eng. Proc. 2026, 150(1), 114; https://doi.org/10.3390/engproc2026150114 (registering DOI) - 5 Aug 2026

Viewed by 39

Abstract

A boundary integral equations method (BIEM) for a graded magneto-electro-elastic (MEE) half-plane with cracks under an incident time-harmonic SH wave is presented. The method is based on an analytically derived Green’s function and a free-field wave motion solution for the half-plane. Quadratic and [...] Read more.

A boundary integral equations method (BIEM) for a graded magneto-electro-elastic (MEE) half-plane with cracks under an incident time-harmonic SH wave is presented. The method is based on an analytically derived Green’s function and a free-field wave motion solution for the half-plane. Quadratic and exponential inhomogeneity functions are considered. The Green’s function is derived for different values of the frequency of the incident time-harmonic load by using an integral representation of the Henkel functions and the natural logarithm. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

8 pages, 247 KB

Open AccessProceeding Paper

A Priori Reliability of Electrical Machines and Its Verification by Testing

by Atanas Nachev, Nikolay Gueorguiev, Gergana Chalakova and Tereza Trencheva

Eng. Proc. 2026, 150(1), 115; https://doi.org/10.3390/engproc2026150115 (registering DOI) - 5 Aug 2026

Viewed by 33

Abstract

A method is proposed for determining the reliability of electrical machines of the most widely used types during their design stage and for verifying this reliability through testing of the components intended for them. The method is invariant with respect to the type [...] Read more.

A method is proposed for determining the reliability of electrical machines of the most widely used types during their design stage and for verifying this reliability through testing of the components intended for them. The method is invariant with respect to the type of machine and its operating mode. Particular attention is given to its practical application in real engineering practice. The method is applicable to both direct current and alternating current machines, with or without a commutator, operating in either generator or motor mode. It is based on the evaluation of the probability of failure-free operation over a specified time interval, determined on the basis of the reliability characteristics of their windings, bearings, and commutation system. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

14 pages, 1939 KB

Open AccessProceeding Paper

Investigation of Overall Light Transmittance of PETG Material

by Kliment Georgiev, Misho Matsankov, Mario Dechev, Atanas Radulov and Teodor Demirev

Eng. Proc. 2026, 150(1), 116; https://doi.org/10.3390/engproc2026150116 (registering DOI) - 5 Aug 2026

Viewed by 37

Abstract

The article presents a study of the overall brightness of semi-transparent materials used in additive manufacturing. Components with varying thicknesses and diverse types of finished surfaces were manufactured and evaluated under various lighting conditions. The test components were fabricated from a transparent PETG [...] Read more.

The article presents a study of the overall brightness of semi-transparent materials used in additive manufacturing. Components with varying thicknesses and diverse types of finished surfaces were manufactured and evaluated under various lighting conditions. The test components were fabricated from a transparent PETG (polyethylene terephthalate) material. The printing parameters were selected based on a series of experiments conducted on this type of material. The measurements were conducted on a specially designed and manufactured stand for measuring overall light transmittance. The classical method for evaluating the results according to the normal distribution law was applied. The findings of the studies demonstrate that transmittance is predominantly contingent on the thickness of the component, as opposed to the illuminance or the nature of the surface. The discrepancy in transmittance between thicknesses of 1 and 1.5 mm for all illuminance levels is approximately 12%. As the thickness increases, the discrepancy in transmittance decreases, reaching approximately 1.5% for samples with thicknesses ranging from 2 to 3.5 mm. The light intensity exhibited a negligible effect on transmittance, with an approximate measurement of 1.5%. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 5059 KB

Open AccessProceeding Paper

A Portable IoT-Enabled System for Georeferenced Soil Nutrient Screening in Agricultural Fields

by Omar Flores-Cortez, Bayron Cordero, Fernando Arévalo, Carlos Pocasangre and Werner Melendez

Eng. Proc. 2026, 150(1), 117; https://doi.org/10.3390/engproc2026150117 (registering DOI) - 6 Aug 2026

Viewed by 68

Abstract

This paper presents the design and preliminary field validation of a portable, low-cost Internet of Things (IoT) station for georeferenced soil nutrient profiling in agricultural environments. The proposed system integrates a digital RS-485 NPK soil sensor, an ESP32 microcontroller, and a SIM7000G GSM/GPS [...] Read more.

This paper presents the design and preliminary field validation of a portable, low-cost Internet of Things (IoT) station for georeferenced soil nutrient profiling in agricultural environments. The proposed system integrates a digital RS-485 NPK soil sensor, an ESP32 microcontroller, and a SIM7000G GSM/GPS module to enable on-site acquisition and real-time transmission of nitrogen (N), phosphorus (P), and potassium (K) measurements using the MQTT protocol. Data are serialized in JSON format and transmitted to a ThingsBoard cloud platform for remote storage and visualization. The portable architecture supports manual spatial sampling across multiple locations without reliance on fixed infrastructure, making it suitable for small- and medium-scale agricultural contexts with limited connectivity. Preliminary testing in a controlled lemon plantation demonstrated stable GSM connectivity, successful geotagging, and consistent cloud-based visualization, with an average acquisition–transmission cycle of 30–45 s per measurement. Spatial heat maps generated from collected data illustrate the system’s capability for indicative nutrient mapping. Although laboratory-grade validation is ongoing, the results confirm the technical feasibility of integrating low-cost sensing, cellular communication, and georeferenced data acquisition into a compact IoT unit. The system establishes a foundation for future calibration, large-scale field validation, and decision-support applications in precision agriculture. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 4483 KB

Open AccessProceeding Paper

Experimental Assessment of Formaldehyde Gas Emissions from Laminate and Solid Parquet Under Simulated Fire Conditions

by Rositsa Velichkova, Iskra Simova and Aleksandra Mihaylova

Eng. Proc. 2026, 150(1), 118; https://doi.org/10.3390/engproc2026150118 - 6 Aug 2026

Viewed by 57

Abstract

This paper presents an experimental study on the amount of formaldehyde released during a fire in apartments, focusing on the flooring most commonly used in Bulgaria. Formaldehyde is a potentially hazardous chemical known to be carcinogenic in large amounts. It often causes respiratory [...] Read more.

This paper presents an experimental study on the amount of formaldehyde released during a fire in apartments, focusing on the flooring most commonly used in Bulgaria. Formaldehyde is a potentially hazardous chemical known to be carcinogenic in large amounts. It often causes respiratory problems and skin irritation. People prone to allergies are especially sensitive to formaldehyde. These health risks depend on the duration and level of exposure. The experiment tested seven types of laminate samples and six types of natural parquet samples at three different combustion temperatures in a room. Each sample was placed in a muffle furnace, heated to the specified temperatures of 150, 250, and 400 °C, respectively. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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7 pages, 219 KB

Open AccessProceeding Paper

Expediency Assessment of an Information System Based on the Reliability Characteristics of Its Elements

by Atanas Nachev, Nikolay Gueorguiev, Gergana Chalakova and Tereza Trencheva

Eng. Proc. 2026, 150(1), 119; https://doi.org/10.3390/engproc2026150119 - 6 Aug 2026

Viewed by 33

Abstract

An invariant method is proposed for determining the expediency of implementing the structure and organization of an information system (IS). The method is based on determining time losses occurring during the execution of information processes and on assessing the functional reliability of the [...] Read more.

An invariant method is proposed for determining the expediency of implementing the structure and organization of an information system (IS). The method is based on determining time losses occurring during the execution of information processes and on assessing the functional reliability of the system with respect to the performed tasks, taking into account the reliability characteristics of the corresponding IS components. This study addresses the importance of the problem from both theoretical and applied perspectives, as well as the need for its solution under conditions of a limited number of methods described in the literature for assessing the influence of hardware and software reliability of information system elements. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

17 pages, 2527 KB

Open AccessProceeding Paper

Machine Learning Approaches to Detect Application Layer DDoS Attacks

by Ali Sabra, Nehmeh Rmeiti and Zlatogor Minchev

Eng. Proc. 2026, 150(1), 120; https://doi.org/10.3390/engproc2026150120 - 6 Aug 2026

Viewed by 173

Abstract

This study proposes a machine learning and deep learning framework to detect application layer DDoS attacks using web server access logs. A realistic dataset was generated using eight DDoS tools, along with benign traffic. Multiple ML models, including Random Forest, SVM, and KNN, [...] Read more.

This study proposes a machine learning and deep learning framework to detect application layer DDoS attacks using web server access logs. A realistic dataset was generated using eight DDoS tools, along with benign traffic. Multiple ML models, including Random Forest, SVM, and KNN, as well as DL models such as ANN and LSTM, were evaluated. The results show high detection performance, with the LSTM achieving up to 99% accuracy and outperforming other models. Additional validation on non-DDoS attacks revealed that ML models performed poorly, while LSTM maintained strong performance (92.89%). The findings highlight the effectiveness of log-based datasets and the superiority of LSTM for handling sequential and mixed-feature data in cybersecurity detection tasks. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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8 pages, 1715 KB

Open AccessProceeding Paper

Detecting Information Operations Using Machine Learning Algorithms

by Velizar Varbanov and Tatiana Atanasova

Eng. Proc. 2026, 150(1), 121; https://doi.org/10.3390/engproc2026150121 - 4 Aug 2026

Viewed by 28

Abstract

The proliferation of fake news poses a significant threat to democratic institutions, public trust, and crisis management, particularly as it becomes a central tactic in coordinated information operations. This paper explores the application of machine learning (ML) algorithms in detecting and classifying disinformation [...] Read more.

The proliferation of fake news poses a significant threat to democratic institutions, public trust, and crisis management, particularly as it becomes a central tactic in coordinated information operations. This paper explores the application of machine learning (ML) algorithms in detecting and classifying disinformation as a means of supporting experts engaged in combating influence campaigns. We utilize a labelled English dataset, and a custom collected Bulgarian news dataset gathered using version 1 of the NewsData.io API, as indicated by the /api/1/ endpoint. After translating the Bulgarian content and generating synthetic fake news from real articles, we construct a multilingual training set. We evaluate the performance of three ML models demonstrating that advanced ML approaches can significantly enhance the identification of disinformation. These findings highlight the potential for machine learning to assist intelligence analysts, cybersecurity professionals, and policy makers in detecting and countering modern information operations at scale. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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5 pages, 2558 KB

Open AccessProceeding Paper

Influence of Chemical Composition on Microstructure and Hardness of High-Chromium Cast Irons

by Gergana Buchkova, Boryana Ivanova and George Lutov

Eng. Proc. 2026, 150(1), 124; https://doi.org/10.3390/engproc2026150124 - 10 Aug 2026

Abstract

High-chromium white cast irons represent an important group of wear-resistant engineering materials widely used in mining, mineral processing and cement industries due to their excellent abrasion resistance and high hardness. The present study investigates the influence of chemical composition and magnesium modification on [...] Read more.

High-chromium white cast irons represent an important group of wear-resistant engineering materials widely used in mining, mineral processing and cement industries due to their excellent abrasion resistance and high hardness. The present study investigates the influence of chemical composition and magnesium modification on the microstructure and hardness of two high-chromium cast irons. Two alloys were examined: a 28 mass% Cr cast iron without magnesium addition and a modified alloy containing 14 mass% Cr and 0.88 mass% Mg. Optical metallographic analysis revealed significant differences in carbide morphology between the investigated alloys. The alloy without magnesium exhibited coarse primary M7C3 chromium carbides embedded in the metallic matrix, whereas the Mg-modified alloy showed a significantly refined eutectic structure with fine carbide distribution. Hardness measurements revealed values of approximately 475 HV for the non-modified alloy and 750 HV for the Mg-modified alloy. The obtained results demonstrate the strong relationship between chemical composition, microstructure and hardness of high-chromium cast irons. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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9 pages, 2960 KB

Open AccessProceeding Paper

Integrating AI-Generated 3D Models into Education—A Methodological and Practical Approach

by Plamen Petrov and Tatiana Atanasova

Eng. Proc. 2026, 150(1), 125; https://doi.org/10.3390/engproc2026150125 - 10 Aug 2026

Abstract

As education embraces digital transformation, integrating AI into pedagogy is increasingly important. One promising innovation is AI-generated 3D models, which help visualize complex concepts, enhance spatial reasoning, and foster creativity. Unlike traditional 3D modeling, which requires advanced skills and time, AI tools make [...] Read more.

As education embraces digital transformation, integrating AI into pedagogy is increasingly important. One promising innovation is AI-generated 3D models, which help visualize complex concepts, enhance spatial reasoning, and foster creativity. Unlike traditional 3D modeling, which requires advanced skills and time, AI tools make content creation more accessible to educators and students. This study develops and validates a structured methodology for using AI-generated 3D models in education. It supports personalized, rapid, and intuitive content development, particularly in STEM. The framework includes guidelines for effective text-to-3D prompts, validation of educational impact, and a roadmap toward immersive technologies like VR, AR, and digital twins, enabling scalable, student-centered learning experiences. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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10 pages, 376 KB

Open AccessProceeding Paper

Assessing MQTT, CoAP, and HTTP Performance in Real-Life Scenarios on ESP32-Based IoT Nodes

by Aleksandar Kirilov, Denis Chikurtev, Galia Nedeltcheva and Peter So

Eng. Proc. 2026, 150(1), 126; https://doi.org/10.3390/engproc2026150126 (registering DOI) - 10 Aug 2026

Abstract

The goal of the study is to compare the most popular protocols available in IoT (Internet of Things) nodes and how they perform across multiple samples in controlled conditions. The focus is on local telemetry transmission, in which the ESP32-C6 and ESP32-S3 boards [...] Read more.

The goal of the study is to compare the most popular protocols available in IoT (Internet of Things) nodes and how they perform across multiple samples in controlled conditions. The focus is on local telemetry transmission, in which the ESP32-C6 and ESP32-S3 boards communicate with two other devices—a router and a laptop—over the 2.4 GHz band. For the experiment, three standard nominal transmission sizes of 16, 64, and 256 bytes were pre-set. Each size was trialed for 30 samples for each protocol. All transmissions achieved a 100% success rate and were received by the end device. Both latency and success rate were used as the main performance indicators. The end results were that CoAP had the lowest mean latency of 47.0 ms, followed by MQTT with 63.0 ms and HTTP with a mean overall latency of 1419.0 ms. A comparative test with the ESP32-S3 revealed that while the overall protocol ranking remained identical, the gap eventually narrowed. The more powerful ESP32-S3 processed HTTP significantly faster (mean latency of 449.0 ms) but yielded slower latencies for the lightweight CoAP and MQTT protocols compared to the C6. The results indicate an order of magnitude faster performance of CoAP and MQTT than HTTP in the test setup. The study offers a simple and reproducible setup and benchmarking, allowing it to serve as a practical reference point when selecting the right protocol for a given use case. Full article

(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2025—Engineering, Technology and Systems)

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