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The maritime industry is experiencing significant growth due to globalized trade, but this expansion has led to increasing environmental concerns. Studies project that shipping emissions could reach 90–130% of 2008 levels by 2050 without interv...

This paper focuses on a section of the state road D28, Bjelovar northern bypass, Republic of Croatia, which was opened to traffic in 2002. Following the expiration of the 20-year design service life, it was determined that the section required recons...

This study introduces the Deep Learning Assisted Composite Clock (DLACC), aiming to improve the robustness of the GNSS timescale. If traditional Kalman filter-based composite clocks are today used in systems like GPS and EGNOS, the non-linear, non-Ga...

In this study, we emphasize that the maximum sum rate can be achieved through AI-based subchannel allocation, while taking into account all users’ quality of service (QoS) requirements in data rates for hybrid beamforming systems. We assume a l...

This article provides an in-depth evaluation of sustainability performance within the mining sector by employing the Fuzzy Analytic Network Process (FANP). The assessment centers on five fundamental dimensions: economic, social, environmental, operat...

Future wireless networks require efficient device-to-device (D2D) communication to meet the demands of increasing connectivity; however, practical challenges such as limited coverage and severe interference persist. This paper addresses these issues...

We investigated how adding interaction modules—including a category-themed image, slogan, and narrative text—affects user attention during exploratory browsing within category-based recommender interfaces. Eye-tracking data and post-task...

This paper introduces the GRIPP (GNSS/SBAS Receiver, Independent and Portable PVT) system, an open-source SDR oriented GNSS/SBAS receiver. Composed of a Pocket SDR FE device, an L-band antenna and a computer, this system aims to ease the deployment a...

Geospatial data analysis systems are currently very relevant. Most such systems use either relational databases or graph databases. This paper presents the idea of using both approaches, taking into account the main features and advantages of each. A...

Supervisory control and data acquisition systems are an essential part of industrial control systems that form part of the critical infrastructure in the energy sector, which in the last decade have increased their interconnection, complexity, and de...

A strategic approach to integrating generative AI (GAI) into design education is explored in this article to enhance students’ creativity, critical thinking, and practical skills. Based on a cross-departmental initiative at National United Univ...

Global Navigation Satellite Systems (GNSSs) are exploited in a wide range of applications, and their reliability and accuracy are more critical than ever. Weak GNSS signals are extremely susceptible to intentional or unintentional interference. The J...

Sixth-generation (6G) networks will operate with pervasive autonomy and minimal centralised control, imposing stringent requirements on security and trust. This short communication presents a hybrid trust evaluation approach that combines fuzzy infer...

Phosphate coatings were obtained by cold method from solutions based on Mazev Salt (containing Mn(H₂PO₄)₂∙2H₂O and iron phosphates). Metal nitrates and nitrites were introduced into solutions as accelerators of the phosphating process. To obtai...

This paper presents the work on integrating our Vision-Aided Inertial Navigation System (VaINS) with orthophoto matching to increase robustness to GNSS failure. Normalized cross-correlation is used to match onboard camera images with geo-referenced a...

The Galileo High Accuracy Service (HAS) offers free, real-time precise point positioning (PPP) corrections via Galileo (E6-B) and internet, supporting Galileo (E1, E5a, E5b, E6) and GPS (L1, L5) signals. As of Service Level 1, HAS provides SSR orbit,...

We developed a novel pattern-based dual-image reversible data hiding scheme utilizing vertical bars and bitten square blocks to improve data capacity, security, embedding efficiency, and visual quality. By embedding secret messages into two grayscale...

In Cyber Threat Intelligence, anticipating threat events and linking forecasts to standards-based mitigations is essential, yet many approaches rely on non-unified event representations within the analysis window, introducing bias and weakening tacti...

The rapid decline of linguistic diversity, driven by globalization and technological standardization, presents significant challenges for the preservation of endangered languages, many of which lack sufficient parallel corpora for effective machine t...

Renewable energy sources play a critical role in modern energy production and transmission systems. This paper presents a GIS-enhanced deep learning framework for spatially informed renewable energy potential assessment, integrating environmental var...

As a fundamental component of GNSS signals, messages act as a critical medium for transmitting information required for PNT, serving the needs of both service providers and users. Over the years, message structures for GNSS signals have evolved from...

Due to people’s increasing access to computers, IT security has become extremely important in today’s society. This increase in connectivity has also led cybercriminals to take advantage of the anonymity and privacy offered by the Interne...

Quantum computing has the potential to transform modern computation by offering exponential advantages in areas such as cryptography, optimization, and intelligent data processing. To effectively realize these advantages, particularly in fault-tolera...

Fine particulate matter (${\mathrm{P}\mathrm{M}}_{2.5}$) is a hazardous air pollutant that poses serious risks to human health. Long-term exposure to high concentrations of ${\mathrm{P}\mathrm{M}}_{2.5}$ increases the likelihood of developing cardiovascular and respiratory diseases. Therefore, accur...

In modern cybersecurity and deep learning, conditional password guessing plays a critical role in improving password-cracking efficiency by leveraging known patterns and constraints. In contrast with traditional brute-force or dictionary-based attack...

Tracert-retrieval-augmented generation (RAG) is a novel retrieval-augmented framework designed for efficient, document-level multi-hop reasoning. Unlike conventional RAG systems that retrieve top-k text segments based solely on dense similarity, Trac...

We developed an AI-assisted zero-trust control system at low capital expenditure to retrofit brownfield Ethernet environments without disruptive hardware upgrades or costly software-defined networking migration. Legacy network infrastructures in smal...

We investigated how mechanical material properties, magnetic material properties, and geometric structure affect the performance of magnetic inductors. Magnetic thin film samples were prepared using a sputter deposition system. Mechanical properties,...

We developed a deep learning model for automated extraction and assessment of earthquake damage from dashcam and post-disaster images. By combining a custom-designed deep multi-layer perceptron model with an enhanced feature extraction methodology, w...

In the digital forensics process, an essential step is the analysis of evidence contained in seized devices, a task that requires a significant investment of time to identify patterns and evidence that strengthen a judicial investigation. Advances in...

Star ratings alone are noisy, manipulable, and ignore aspect-level sentiment. We present Scrape2Repute, a compact and reproducible pipeline that ingests Yelp reviews under policy constraints; cleans and normalises text/metadata; learns a calibrated t...

Modern cyber threats exhibit sophisticated, evasive behaviors that overwhelm traditional security systems, leading to prolonged periods of attackers remaining undetected. AI-driven autonomous agents promise a proactive solution but are themselves vul...

This work has developed a Deep Learning model that analyses the semantics of the Python code used when working with TensorFlow and detects vulnerabilities to improve data security and bug recognition. This research not only seeks to improve the secur...

The use of technology in mobile devices and the integration of Artificial Intelligence offers a wide range of benefits and personalised services that help users perform countless activities that assist them in their daily lives, such as at work, scho...

In early-stage product ideation, generative AI has emerged as a design support tool, yet most prompts still rely on designers’ subjective intent with limited grounding in user context. Therefore, we developed a user-centered prompting method, i...

Dental composite reconstructive materials (DCRMs) used in caries treatment possess satisfactory functional properties but lack antimicrobial activity, which may lead to secondary caries. This research aimed to modify the DCRM matrix with urethane-dim...

The rapid expansion of Internet of Things (IoT) technologies has introduced diverse applications while simultaneously exposing devices to increasing cybersecurity risks. Sensitive data handled within IoT networks and the limited resources of connecte...

Trust assurance will be a cornerstone of the security and autonomy of sixth-generation (6G) networks. Traditional trust models focus on data authenticity and integrity; however, 6G systems increasingly rely on autonomous decision-making. This article...

The widespread distribution of digital videos in social networks, streaming services, and surveillance systems has increased the risk of manipulation, unauthorized redistribution, and adversarial tampering. This paper presents a lightweight deep lear...

The 8th International Conference of Engineering Against Failure (ICEAF VIII) was successfully held in the beautiful city of Kalamata, Greece, from June 22nd to 25th, 2025 [...]

The increasing demand for sustainable development necessitates sophisticated computational frameworks that facilitate intricate, long-term decision-making in circular economy systems. Therefore, we developed a novel machine learning based Markov deci...

In submitting conference proceedings to Engineering Proceedings, the Volume Editors of the proceedings would like to certify to the publisher that all papers published in this volume have been subjected to peer review by the designated expert referee...

This study aims to model and optimize the process parameters influencing the efficiency and yield of oil extraction from Mongolian sea buckthorn seeds using supercritical carbon dioxide (CO₂). The experiments were planned using response surface metho...

We present a computational model for studying morphogenesis based on pairwise interactions among cells in this article. Extending a previous single-particle model, we represent each cell using two particles connected by an internal link. This two-par...

With the widespread adoption of cloud services, ensuring the quality and security of the representational state transfer application programming interface (REST API) has become critical. Among various REST API testing techniques, fuzz testing stands...

Existing origin-destination (OD) forecasting models struggle to jointly capture local topology and global flow patterns in urban mobility. Therefore, we developed a multi-view spatio-temporal network (MVSTN), a novel dual-branch spatio-temporal model...

With the implementation of the 2022 revised curriculum in South Korea, significant changes are taking place in education as of 2025. This curriculum emphasizes self-directed learning and a proactive attitude toward life, which are essential in the er...

Thyroid cancer is the most common type of endocrine cancer. Most cases are called differentiated thyroid cancer (DTC), which includes papillary, follicular, and hurthle cell types. DTC usually grows slowly and has a good prognosis, especially when fo...

We modeled water inrush propagation in mines and the optimization of evacuation routes. By constructing a water flow model, the propagation process of water flow through the tunnel network is simulated to explore branching, superposition, and water l...

This work studies the ability of a single-sided vibro-impact nonlinear energy sink (SSVI NES) and a tuned mass damper (TMD) to maintain their vibration reduction performance when the natural frequency of the primary structure (PS), which is determine...