Engineering Proceedings

2889 KiB

Open AccessProceeding Paper

Comparative Analysis of Machine Learning Algorithms for Flow Rate Prediction in Optimizing Pipeline Maintenance Strategies

by Adamu Abubakar Sani, Mohamed Mubarak Abdul Wahab and Nasir Shafiq

Eng. Proc. 2025, 87(1), 37; https://doi.org/10.3390/engproc2025087037 - 3 Apr 2025

Abstract

Using machine learning to predict maintenance schedules for crude oil pipelines is crucial for enhancing efficiency and minimizing disruptions in the oil and gas sector. Our research explores the effectiveness of machine learning algorithms in this context, with a specific focus on using [...] Read more.

Using machine learning to predict maintenance schedules for crude oil pipelines is crucial for enhancing efficiency and minimizing disruptions in the oil and gas sector. Our research explores the effectiveness of machine learning algorithms in this context, with a specific focus on using oil flow rate as a primary predictor. When trained with a variety of inspection data, machine learning models can accurately predict flow rates, thus improving maintenance planning. Several pipeline scenarios were analyzed, and the Python library was used for dataset augmentation. The study shows a correlation between variations in the buildup deposits and the oil flow rate in the pipeline, indicating that the oil flow rate gives an indication for determining the need for maintenance. The flow rate was categorized into three efficiency levels: High Efficiency (flow rate > 90% of the allowable rate), Moderate Efficiency (flow rate between 70% and 90%), and Low Efficiency (flow rate < 70%). Each efficiency level was linked to specific maintenance intervals: Specifically, a higher flow rate allowed longer intervals between maintenance activities, while a lower flow rate could indicate there is an accumulation of deposits that necessitates urgent intervention. Several machine learning models were trained, and variations in performance were observed. Gradient Boosting and XGBoost Regressor show the best performers with lower values for MSE, RMSE, and MAE and higher R² scores compared to the Support Vector Regressor. The result shows Gradient Boosting has an MSE of 0.000005, RMSE of 0.002259, MAE of 0.000968, and an R² of 0.997259, followed by XGBoost Regressor with MSE of 0.000005, an RMSE of 0.002269, an MAE of 0.000922, and an R² of 0.997234. Support Vector Regressor indicates the least performance, with an MSE of 0.002868, RMSE of 0.053554, MAE of 0.046311, and an R² of −0.540765. The findings of the study emphasize the necessity of choosing machine learning algorithms that are appropriately suited to the features of the dataset and the task. The findings highlight the importance of selecting machine learning algorithms that are more suitable to the features of the dataset and the task. Full article

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9 pages, 204 KiB

Open AccessProceeding Paper

Computational Drug-Likeness Studies of Selected Thiosemicarbazones: A Sustainable Approach for Drug Designing

by Ekhlakh Veg, Kulsum Hashmi, Satya, Seema Joshi and Tahmeena Khan

Eng. Proc. 2025, 87(1), 35; https://doi.org/10.3390/engproc2025087035 - 2 Apr 2025

Abstract

Drug intake, its absorption in the body, removal, and various side effects are factors considered when designing the drugs. Here, the in silico tools act as virtual shortcuts, assisting in the prediction of several important physicochemical properties like polar surface area (PSA), molecular [...] Read more.

Drug intake, its absorption in the body, removal, and various side effects are factors considered when designing the drugs. Here, the in silico tools act as virtual shortcuts, assisting in the prediction of several important physicochemical properties like polar surface area (PSA), molecular weight, and molecular flexibility, etc., to evaluate probable drug leads as potential drug candidates. These tools also play a vital role in the prediction of the bioactivity score of probable drug leads against various human receptors. This paper presents a virtual combinatorial library of selected thiosemicarbazones (TSCs) and their metal complexes. Different properties like bioactivity score, physicochemical, distribution, absorption, excretion, metabolism, and toxicity (ADMET) parameters were assessed. By using ChemDraw Ultra 12.0, the structures of ligands and complexes were drawn and downloaded in PDB format. Physicochemical parameters were calculated using online softwares viz. Molinspiration and SwissADME, and ADMET properties were calculated using admetSAR (2.0). Molecular docking was performed using PyRx Python Prescription 0.8. with Janus Kinase and Transforming Growth Factor Beta (Tgf-β). Janus Kinase and Tgf-β are some cytokines involved in cell development, proliferation, and cell death. Three important TSCs, i.e., salicyldehyde thiosemicarbazone, acenaphthenequinone thiosemicarbazone, 2-chloronicotinic thiosemicarbazone, and their virtually designed complexes exhibited appreciable in silico results. Most ligands and complexes had good bioactivity values against all the biological targets. Full article

7 pages, 5282 KiB

Open AccessProceeding Paper

Tuning the Electrical Resistivity of Molecular Liquid Crystals for Electro-Optical Devices

by Michael Gammon, Iyanna Trevino, Michael Burnes, Noah Lee, Abdul Saeed and Yuriy Garbovskiy

Eng. Proc. 2025, 87(1), 34; https://doi.org/10.3390/engproc2025087034 - 2 Apr 2025

Abstract

Modern applications of molecular liquid crystals span from high-resolution displays for augmented and virtual reality to miniature tunable lasers, reconfigurable microwave devices for space exploration and communication, and tunable electro-optical elements, including spatial light modulators, waveguides, lenses, light shutters, filters, and waveplates, to [...] Read more.

Modern applications of molecular liquid crystals span from high-resolution displays for augmented and virtual reality to miniature tunable lasers, reconfigurable microwave devices for space exploration and communication, and tunable electro-optical elements, including spatial light modulators, waveguides, lenses, light shutters, filters, and waveplates, to name a few. The tunability of these devices is achieved through electric-field-induced reorientation of liquid crystals. Because the reorientation of the liquid crystals can be altered by ions normally present in mesogenic materials in minute quantities, resulting in their electrical resistivity having finite values, the development of new ways to control the concentration of the ions in liquid crystals is very important. A promising way to enhance the electrical resistivity of molecular liquid crystals is the addition of nano-dopants to low-resistivity liquid crystals. When nanoparticles capture certain ions, they immobilize them and increase their resistivity. If properly implemented, this method can convert low-resistivity liquid crystals into high-resistivity liquid crystals. However, uncontrolled ionic contamination of the nanoparticles can significantly alter this process. In this paper, building on our previous work, we explore how physical parameters such as the size of the nanoparticles, their concentration, and their level of ionic contamination can affect the process of both enhancing and lowering the resistivity of the molecular liquid crystals. Additionally, we analyze the use of two types of nano-dopants to achieve better control over the electrical resistivity of molecular liquid crystals. Full article

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6 pages, 209 KiB

Open AccessProceeding Paper

Influence of Dispersant and Surfactant on nZVI Characterization by Dynamic Light Scattering

by Filipe Fernandes, Ana Isabel Oliveira, Cristina Delerue-Matos and Clara Grosso

Eng. Proc. 2025, 87(1), 33; https://doi.org/10.3390/engproc2025087033 - 2 Apr 2025

Abstract

The agrifood industries generate tremendous amounts of waste, with the valorization of these wastes being of the utmost importance. The aim of this work was to synthesize green zero-valent iron nanoparticles (nZVI) using hydromethanolic extracts of spent coffee grounds (SCGs) and post-distillation residues [...] Read more.

The agrifood industries generate tremendous amounts of waste, with the valorization of these wastes being of the utmost importance. The aim of this work was to synthesize green zero-valent iron nanoparticles (nZVI) using hydromethanolic extracts of spent coffee grounds (SCGs) and post-distillation residues of Cistus ladanifer L. leaves (CLL). The synthesized nZVI were then analyzed by dynamic light scattering (DLS), and their size, polydispersity index (PDI), and zeta potential (ZP) were determined. Different dispersants (water and methanol) and the impact of a surfactant (Tween^® 20) were tested for DLS analysis. nZVI dispersed in water and added with Tween^® 20 displayed lower agglomeration, particle size, and PDI, but higher ZP than nZVI without the addition of surfactant and methanolic suspension. These results provide further insight into the applicability of surfactants in nZVI characterization. Full article

8 pages, 2080 KiB

Open AccessProceeding Paper

Video Surveillance and Augmented Reality in Maritime Safety

by Igor Vujović, Mario Miličević and Joško Šoda

Eng. Proc. 2025, 87(1), 32; https://doi.org/10.3390/engproc2025087032 (registering DOI) - 2 Apr 2025

Abstract

Recently, augmented reality and machine learning have become integral parts of many developed systems. In the maritime domain, it is particularly interesting to develop a concept that combines augmented reality with the visualization of collision risks, using machine learning for motion prediction as [...] Read more.

Recently, augmented reality and machine learning have become integral parts of many developed systems. In the maritime domain, it is particularly interesting to develop a concept that combines augmented reality with the visualization of collision risks, using machine learning for motion prediction as its foundation. Hence, this research aims to propose a system that visualizes the risk in an augmented reality application. The paper presents a distance estimation method that mainly uses a single stationary camera placed at the harbor entrance. The machine learning component involves training the YOLO algorithm on the Split Port Ship Classification Dataset. This distance estimation is an input for the speed estimation algorithm. Speed is a key parameter for the prediction of collision risk. Preliminary experiments were conducted to provide proof of concept for further research, and the description of a case study is included in this paper. Full article

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9 pages, 3571 KiB

Open AccessProceeding Paper

Putting the Synthetic Global Navigation Satellite System Meta-Signal Paradigm into Practice: Application to Automotive Market Devices

by Domenico Di Grazia, Fabio Pisoni, Giovanni Gogliettino, Ciro Gioia and Daniele Borio

Eng. Proc. 2025, 88(1), 30; https://doi.org/10.3390/engproc2025088030 - 2 Apr 2025

Abstract

The synthetic meta-signal reconstruction approach enables the generation of wideband Global Navigation Satellite System (GNSS) measurements from side-band observations. This approach is of particular interest for automotive market devices where, for instance, hardware constraints do not allow full-band Galileo Alternative Binary Offset Carrier [...] Read more.

The synthetic meta-signal reconstruction approach enables the generation of wideband Global Navigation Satellite System (GNSS) measurements from side-band observations. This approach is of particular interest for automotive market devices where, for instance, hardware constraints do not allow full-band Galileo Alternative Binary Offset Carrier (Alt-BOC) processing. In this paper, the applicability of the synthetic GNSS meta-signal paradigm is extended by introducing a half-cycle ambiguity detector for the reconstructed carrier phases and a jump detector for the pseudoranges. These accessories make the reconstruction approach more robust and suitable for mass market devices. Tests conducted using the STMicroelectronics TeseoV receiver demonstrate the validity and potential of this approach. Full article

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16 pages, 2011 KiB

Open AccessProceeding Paper

Sustainable Pharmaceutical Development Utilizing Vigna mungo Polymer Microbeads

by Krishnaveni Manubolu and Raveesha Peeriga

Eng. Proc. 2024, 81(1), 14; https://doi.org/10.3390/engproc2024081014 - 2 Apr 2025

Abstract

This study explores the potential of Vigna mungo gum as a sustainable and innovative natural polymer for developing microbeads for the controlled delivery of vildagliptin, a widely used antidiabetic agent. Unlike conventional natural polymers, Vigna mungo gum offers unique biocompatibility, biodegradability, and an [...] Read more.

This study explores the potential of Vigna mungo gum as a sustainable and innovative natural polymer for developing microbeads for the controlled delivery of vildagliptin, a widely used antidiabetic agent. Unlike conventional natural polymers, Vigna mungo gum offers unique biocompatibility, biodegradability, and an eco-friendly production process, distinguishing it as a superior candidate for drug delivery systems. Microbeads were prepared by combining Vigna mungo gum with sodium alginate and inducing gelation using calcium carbonate. Scanning electron microscopy (SEM) revealed a rough, porous microbead surface, advantageous for drug encapsulation and controlled release. Drug release studies demonstrated sustained release kinetics, highlighting the effectiveness of this formulation. These findings underscore the novelty of Vigna mungo gum as a promising platform for antidiabetic drug delivery, providing a sustainable alternative to existing polymer systems. Full article

(This article belongs to the Proceedings of The 1st International Online Conference on Bioengineering)

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11 pages, 2526 KiB

Open AccessProceeding Paper

Practical Evaluation and Performance Analysis for Deepfake Detection Using Advanced AI Models

by Bikash Ranjan Barik, Ankush Nayak, Adyasha Biswal and Neelamadhab Padhy

Eng. Proc. 2025, 87(1), 36; https://doi.org/10.3390/engproc2025087036 - 1 Apr 2025

Abstract

In the 21st century of digital technology, deepfakes are increasingly becoming a serious issue across the globe. We have many machine learning and deep learning algorithms that are meant to serve humanity, but nowadays, these algorithms are the main cause of deepfake media, [...] Read more.

In the 21st century of digital technology, deepfakes are increasingly becoming a serious issue across the globe. We have many machine learning and deep learning algorithms that are meant to serve humanity, but nowadays, these algorithms are the main cause of deepfake media, which can affect human life. This study aimed to create a model for recognizing deepfake media or manipulated media using deep learning and machine learning algorithms. The dataset we required for training the model was collected from online sources, and we created some GAN-generated images. Then, we created a model by using the MTCNN, InceptionResNetV1, and FaceNet_PyTorch. All the algorithms gave an excellent result, with an accuracy of 95% by the MTCNN, 98% by InceptionResNetV1, and 98% by Facenet_pytorch. Full article

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7 pages, 1602 KiB

Open AccessProceeding Paper

A Prediction of Drug Transport, Distribution, and Absorption Through a Multicompartmental Physiologically Based Pharmacokinetic Model

by Simone Chiorboli, Antonio D’Ambrosio, Leone Mazzeo, Francesca Santori, Luca Bacco, Federico D’Antoni, Giovanni Palombo, Mario Merone and Vincenzo Piemonte

Eng. Proc. 2024, 81(1), 13; https://doi.org/10.3390/engproc2024081013 (registering DOI) - 1 Apr 2025

Abstract

The objective of this study was to develop a multicompartmental physiologically based pharmacokinetic (PBPK) model that allows for the reproduction of the function of the gastrointestinal system in silico. Based on the typical tools of chemical engineering, transport phenomena, and human physiological and [...] Read more.

The objective of this study was to develop a multicompartmental physiologically based pharmacokinetic (PBPK) model that allows for the reproduction of the function of the gastrointestinal system in silico. Based on the typical tools of chemical engineering, transport phenomena, and human physiological and anatomical knowledge, the developed model is not limited to representing the transport of drugs and their interactions with ingested foods but also describes several physiological aspects that quantitatively regulate the distribution, absorption, and elimination of drugs. Nevertheless, the model only contains a limited number of parameters: the permeability constants of jejunum, ileum, and colon membranes and the drug removal rates in both the blood and cellular compartments. Therefore, it can be used for a preliminary drug bioavailability assessment in the early stages of drug development when limited experimental data are available. The model was tested on two drugs, Ketoprofen and Ibuprofen, which yielded satisfactory results in accordance with the existing literature. Full article

(This article belongs to the Proceedings of The 1st International Online Conference on Bioengineering)

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6 pages, 1638 KiB

Open AccessProceeding Paper

The Efficiency of Drone Propellers—A Relevant Step Towards Sustainability

by Jaan Susi, Karl-Eerik Unt and Siim Heering

Eng. Proc. 2025, 90(1), 89; https://doi.org/10.3390/engproc2025090089 - 31 Mar 2025

Abstract

The static efficiency of a propeller cannot be determined in the same way as for propellers operating in the presence of freestream airflow. As various kinds of multirotor drones and small UAVs operate in hovering or nearly hovering modes, it is necessary to [...] Read more.

The static efficiency of a propeller cannot be determined in the same way as for propellers operating in the presence of freestream airflow. As various kinds of multirotor drones and small UAVs operate in hovering or nearly hovering modes, it is necessary to develop methods for determining and measuring the static aerodynamic efficiency of small-scale propellers. Propellers with a Reynolds number near the 0.75 R, where the blade section is less than 500,000, are considered to be at a critical value, i.e., the estimated border between two flow modes—laminar and turbulent. The efficiency of small-scale propellers may be hard to predict through modeling, making direct empirical measurements invaluable in this situation. Full article

(This article belongs to the Proceedings of The 14th EASN International Conference on "Innovation in Aviation & Space Towards Sustainability Today & Tomorrow")

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8 pages, 1148 KiB

Open AccessProceeding Paper

Temporal Dynamics and Sources of Heavy Metals in an Aquatic Ecosystem: An Applied Study

by Olha Biedunkova, Pavlo Kuznietsov and Yuliia Trach

Eng. Proc. 2025, 87(1), 30; https://doi.org/10.3390/engproc2025087030 - 31 Mar 2025

Abstract

This study investigates the sources and distribution of heavy metals in the Styr River, particularly in the area influenced by the cooling water blowdown from the Rivne Nuclear Power Plant (Ukraine). The concentrations of eight heavy metals (Zn, Cd, Pb, Cu, Ni, Mn, [...] Read more.

This study investigates the sources and distribution of heavy metals in the Styr River, particularly in the area influenced by the cooling water blowdown from the Rivne Nuclear Power Plant (Ukraine). The concentrations of eight heavy metals (Zn, Cd, Pb, Cu, Ni, Mn, As, and Cr) were measured over a period from 2018 to 2022. Monthly water samples were collected and analyzed using an inductively coupled plasma optical emission spectroscopy (ICAP 7400 Duo, Thermo Fisher Scientific, Waltham, MA, USA). The results show that the average concentrations (M ± SD) of the heavy metals decreased in the following order: Cu (6.43 ± 1.82 ppb), As (5.1 ± 0.2 ppb), Zn (4.67 ± 1.14 ppb), Mn (4.03 ± 2.81 ppb), Ni (3.3 ± 0.8 ppb), Cr (1.06 ± 0.22 ppb), Pb (1.05 ± 0.11 ppb), and Cd (1.01 ± 0.03 ppb). Seasonal and annual variations in metal concentrations were observed, with notable decreases in Zn, Cu, and Mn in 2021, likely due to anthropogenic activities. Pearson correlation analysis and cluster analysis were employed to explore relationships between the metals. The findings suggest that certain metals, such as Pb, Cr, and Ni, share common sources, likely industrial emissions or urban pollution, while others, such as Cd and As, have more isolated sources. This research highlights the complex interplay of natural and anthropogenic factors influencing heavy metal levels in the Styr River. Full article

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11 pages, 2773 KiB

Open AccessProceeding Paper

Spatial Sensitivity of Navigation Using Signal-of-Opportunity (SoOP) from Starlink, Iridium-Next, GlobalStar, OneWeb, and Orbcomm Constellations

by Ahmad Esmaeilkhah and Rene Jr Landry

Eng. Proc. 2025, 88(1), 29; https://doi.org/10.3390/engproc2025088029 - 31 Mar 2025

Abstract

This paper presents a thorough investigation into the EKF-based SoOP navigation algorithm’s sensitivity to spatial parameters and receiver- and transmitter-related properties. Utilizing the innovative SoOPNE simulation platform, our study unveils significant insights. For instance, at high latitudes, Iridium-Next, and Oneweb show a ten-fold [...] Read more.

This paper presents a thorough investigation into the EKF-based SoOP navigation algorithm’s sensitivity to spatial parameters and receiver- and transmitter-related properties. Utilizing the innovative SoOPNE simulation platform, our study unveils significant insights. For instance, at high latitudes, Iridium-Next, and Oneweb show a ten-fold accuracy improvement over Orbcomm. Additionally, discrepancies between predicted and actual satellite trajectories, with a nominal drift of approximately 250 m, result in navigation errors of around 400 m. Our findings underscore the critical importance of addressing these factors to optimize SoOP navigation performance. Full article

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10 pages, 1920 KiB

Open AccessProceeding Paper

Radar-Altimeter Inertial Vertical Loop—Multisensor Estimation of Vertical Parameters for Autonomous Vertical Landing

by Tomas Vaispacher, Radek Baranek, Pavol Malinak, Vibhor Bageshwar and Daniel Bertrand

Eng. Proc. 2025, 88(1), 28; https://doi.org/10.3390/engproc2025088028 (registering DOI) - 31 Mar 2025

Abstract

The design, key functionalities, and performance requirements placed on modern aircraft navigation systems must adhere to the needs imposed by the progressively growing UAS/UAM and eVTOL segments, especially for terminal area operations in urban areas. This paper describes the design, implementation, and real-time [...] Read more.

The design, key functionalities, and performance requirements placed on modern aircraft navigation systems must adhere to the needs imposed by the progressively growing UAS/UAM and eVTOL segments, especially for terminal area operations in urban areas. This paper describes the design, implementation, and real-time validation of Honeywell’s Kalman filter-based radar-altimeter inertial vertical loop (RIVL) prototype. Inspired by the legacy of barometric altimeter-based technology, the RIVL prototype aims to provide high accuracy and integrity estimates of vertical parameters (altitude/height above ground and vertical velocity). The results from simulation tests, flight tests, and crane tests demonstrate that the vertical parameters estimated by the prototype satisfy vertical performance requirements across different terrains and scenarios. Full article

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10 pages, 852 KiB

Open AccessProceeding Paper

Advanced Receiver Autonomous Integrity Monitoring and Local Effect Models for Rail, Maritime, and Unmanned Aerial Vehicles Sectors

by Javier de Toro, Carlos Sanz, Elena Labrador, Roxana Clopot, Florin Mistrapau, Javier Fidalgo, Enrique Domínguez, Ginés Moreno, Fulgencio Buendía, Ana Cezón, Merle Snijders, Heiko Engwerda, Juliette Casals, Sophie Damy, Matteo Sgammini and Juan Pablo Boyero

Eng. Proc. 2025, 88(1), 27; https://doi.org/10.3390/engproc2025088027 - 31 Mar 2025

Abstract

Advanced Receiver Autonomous Integrity Monitoring (ARAIM) represents an advancement over RAIM, designed to utilize dual-frequency and multi-constellation technologies. Originally developed for aviation, the European Commission (EC) is now exploring its broader application. This paper examines the adaptation of ARAIM for rail, maritime, and [...] Read more.

Advanced Receiver Autonomous Integrity Monitoring (ARAIM) represents an advancement over RAIM, designed to utilize dual-frequency and multi-constellation technologies. Originally developed for aviation, the European Commission (EC) is now exploring its broader application. This paper examines the adaptation of ARAIM for rail, maritime, and Unmanned Aerial Vehicles (UAVs) sectors. It briefly discusses aspects of the integrity concept, including architecture and user algorithms while the main focus is on characterizing local error models for local effects using real data campaigns. Full article

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9 pages, 4007 KiB

Open AccessProceeding Paper

Additive Functionalization: Combining the Benefits of Additive Manufacturing and Conventional Composite Production by Overprinting

by Fabian Kühnast and Malte Kürzel

Eng. Proc. 2025, 90(1), 88; https://doi.org/10.3390/engproc2025090088 - 28 Mar 2025

Abstract

Additive functionalization is a novel additive manufacturing approach that aims to combine design freedom and process agility at low tooling costs through thermoplastic additive extrusion with the extraordinary performance of conventionally manufactured thermoset composites by overprinting the latter. A key prerequisite for enabling [...] Read more.

Additive functionalization is a novel additive manufacturing approach that aims to combine design freedom and process agility at low tooling costs through thermoplastic additive extrusion with the extraordinary performance of conventionally manufactured thermoset composites by overprinting the latter. A key prerequisite for enabling this production scenario is to achieve sufficient bond strength between the thermoset composite substrate and the overprinted thermoplastic material. Therefore, thermoset composite plates with different surface modifications were prepared and subsequently overprinted with thermoplastic material. The bond strength of the thermoset–thermoplastic hybrid specimens was evaluated by mechanical testing, while optical and laser scanning microscopy was used to analyze the thermoset–thermoplastic interface and the failure mode. Significant improvements in bond strength for overprinted specimens were achieved by modifying the thermoset composite surface, either through plasma treatment or the integration of thermoplastic films as skin layers. Full article

(This article belongs to the Proceedings of The 14th EASN International Conference on "Innovation in Aviation & Space Towards Sustainability Today & Tomorrow")

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10 pages, 3736 KiB

Open AccessProceeding Paper

Assessing Advanced Propulsion Systems Using the Impact Monitor Framework

by Utkarsh Gupta, Atif Riaz, Felix Brenner, Thierry Lefebvre, Patrick Ratei, Marko Alder, Prajwal Shiva Prakasha, Lukas Weber, Jordi Pons-Prats and Dionysios Markatos

Eng. Proc. 2025, 90(1), 87; https://doi.org/10.3390/engproc2025090087 - 28 Mar 2025

Abstract

Presented in this paper is the Impact Monitor framework and interactive Dashboard Application (DA) validated through a use case, focusing on investigating the viability and competitiveness of future propulsion architectures for next-generation aircraft concepts. This paper presents a novel collaborative framework for integrated [...] Read more.

Presented in this paper is the Impact Monitor framework and interactive Dashboard Application (DA) validated through a use case, focusing on investigating the viability and competitiveness of future propulsion architectures for next-generation aircraft concepts. This paper presents a novel collaborative framework for integrated aircraft-level assessments, focusing on secure, remote workflows that protect intellectual property (IP) while enabling comprehensive and automated analyses. The research addresses a key gap in the aerospace domain: the seamless matching and sizing of aircraft engines within an automated workflow that integrates multiple tools and facilitates real-time data exchanges. Specifically, thrust requirements are iteratively shared between aircraft and engine modeling environments for synchronized sizing. Subsequently, the fully defined aircraft data are transferred to other tools for trajectory analysis and emissions and other assessments. The Impact Monitor framework and Dashboard Application demonstrate improved efficiency and data security, promoting effective collaboration across institutions and industry partners. Full article

(This article belongs to the Proceedings of The 14th EASN International Conference on "Innovation in Aviation & Space Towards Sustainability Today & Tomorrow")

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11 pages, 8265 KiB

Open AccessProceeding Paper

Development of Innovative 3D Spherical Retrieval System and Virtual Reality for Insomnia Prescriptions in Traditional Chinese Medicine

by Chia-Hui Shih, Geng-Hao Liu and Ting-An Fan

Eng. Proc. 2025, 89(1), 44; https://doi.org/10.3390/engproc2025089044 - 28 Mar 2025

Abstract

Insomnia is prevalent in modern society, and traditional Chinese medicine is gradually replacing Western medicine in its treatment. This study utilized insomnia symptoms and prescriptions from the “Dictionary of Chinese Medicine Prescriptions” to establish a 3D TCM spherical retrieval system, which intuitively displays [...] Read more.

Insomnia is prevalent in modern society, and traditional Chinese medicine is gradually replacing Western medicine in its treatment. This study utilized insomnia symptoms and prescriptions from the “Dictionary of Chinese Medicine Prescriptions” to establish a 3D TCM spherical retrieval system, which intuitively displays the relationship between TCM prescriptions and insomnia symptoms. It enhances public and student interest in learning about TCM. Survey results indicate that the system effectively improves public knowledge of TCM and supports the United Nations Sustainable Development Goal 4: Quality Education. Full article

(This article belongs to the Proceedings of 2024 IEEE 7th International Conference on Knowledge Innovation and Invention)

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9 pages, 3190 KiB

Open AccessProceeding Paper

Predicting Hit Songs Using Audio and Visual Features

by Cheng-Yuan Lee and Yi-Ning Tu

Eng. Proc. 2025, 89(1), 43; https://doi.org/10.3390/engproc2025089043 - 28 Mar 2025

Abstract

Factors contributing to a song’s popularity are explored in this study. Recent studies have mainly focused on using acoustic features to identify popular songs. However, we combined audio and visual data to make predictions on 1000 YouTube songs. In total, 1000 songs were [...] Read more.

Factors contributing to a song’s popularity are explored in this study. Recent studies have mainly focused on using acoustic features to identify popular songs. However, we combined audio and visual data to make predictions on 1000 YouTube songs. In total, 1000 songs were grouped into two categories based on YouTube view counts: popular and non-popular. The visual features were extracted using OpenCV. These features were applied using machine learning algorithms, including random forest, support vector machines, decision trees, K-nearest neural networks, and logistic regression. Random forest performed the best, with an accuracy of 82%. Average accuracy increased by 9% in all models when using audio and visual features together. This indicates that visual elements are beneficial for identifying hit songs. Full article

(This article belongs to the Proceedings of 2024 IEEE 7th International Conference on Knowledge Innovation and Invention)

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5 pages, 1824 KiB

Open AccessProceeding Paper

The Design and Application of a Rubber Vibration Isolator for Aerospace Equipment

by Ke Duan and Feng Hou

Eng. Proc. 2024, 80(1), 42; https://doi.org/10.3390/engproc2024080042 - 28 Mar 2025

Abstract

In this study, a rubber vibration isolator is designed for certain aerospace equipment, and a finite element simulation is carried out to obtain the modal frequency and random vibration response, and to verify the accuracy of the design. The test verifies that there [...] Read more.

In this study, a rubber vibration isolator is designed for certain aerospace equipment, and a finite element simulation is carried out to obtain the modal frequency and random vibration response, and to verify the accuracy of the design. The test verifies that there is no amplification of vibration within 100 Hz; the damping efficiency values of vertical and horizontal random vibration are, respectively, 42.12% and 40.54%; and the impact isolation rate is more than 80%. The test results show that the vibration isolation buffer effect of the isolator is satisfactory and meets the design requirements. Full article

(This article belongs to the Proceedings of 2nd International Conference on Green Aviation (ICGA 2024))

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Journal Description

Engineering Proceedings

Vol. 90

EASN 2024

Vol. 89

IEEE ICKII 2024

Vol. 84

MEST 2024

Vol. 83

CITIIC 2023

Vol. 81

IOCBE 2024

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ICGA 2024

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