2026 August - 98 articles
Cardiovascular Disease (CVD) is a prevailing issue across the world. It requires an accurate method for diagnosing in order to treat the disease effectively. The use of machine learning (ML) techniques has gained popularity for diagnosing CVDs. Some...
A fixed-odds contract on short-horizon price direction has a positive expected value only when its win probability exceeds the break-even rate implied by the payout ratio. A deployable predictor must also produce signals at a sufficiently stable rate...
The rapid diffusion of generative artificial intelligence (GenAI) tools such as ChatGPT has unsettled established academic practices related to assessment, authorship, integrity, and disciplinary knowledge production. This qualitative repeated cross-...
This paper presents an optimized control strategy that enables a grid-connected photovoltaic (PV) system to operate as a static synchronous compensator (PV-STATCOM) to damp power oscillations in the transmission system, using an arithmetic optimizati...
The Proportional-Integral-Derivative (PID) controller has been recorded as the most practical, reliable, and easy to implement feedback control system since its invention in the second decade of the twentieth century. Its adequacy has led to its util...
China’s publishing industry continues to expand across production, warehousing, circulation, and export. Book quality inspection affects product grading, logistics sorting, customer satisfaction, and the international image of Chinese publishin...
Low-altitude UAV aerial imagery often has complex backgrounds with densely distributed small objects, posing challenges to accurate small-object detection. To address these problems, we propose a spatial–frequency response aware synergistic net...
Accurate prediction of the state trend of pumped storage units (PSUs) is essential for timely anomaly detection and preventive maintenance to improve the overall economic performance of power plants. Nevertheless, the complex and time-varying charact...
Sparse autoencoders (SAEs) decompose transformer activations into sparse feature dictionaries, but one-shot support selection can leave many features unused and become difficult to optimize at very small active budgets. We study an SAE-like dictionar...
This study proposes a stand-alone automatic wild boar capture system using artificial intelligence to reduce damage caused by wild boars. First, a data collection device using a low-cost microcontroller capable of running deep learning models with co...
Accurate wind speed forecasting plays a crucial role in the safe and stable operation of wind farms and the efficient integration of renewable energy into modern power systems. However, wind speed exhibits complex spatiotemporal variations affected b...
Lightweight vision models must maximize representational capacity under strict constraints on parameters and computational cost. We investigate whether principle-level architectural composition—the systematic integration of complementary design...
Digital ad fraud continuously evolves through device spoofing, behavior simulation, and coordinated traffic attacks, making the detection of sophisticated fraudulent activities a persistent challenge. In real-world settings, only a small fraction of...
AIS trajectories in and around ports are often incomplete because of transmission interruptions, reception failures, and infrastructure outages. In this paper, we investigate whether the Data-driven AIS Trajectory Interpolation method (DAISTIN), whic...
Automatic classification of Ataulfo mango (Mangifera indica L.) ripeness is essential to ensure consistent quality, standardize post-harvest processes, and reduce the subjectivity of traditional visual inspection, which is unreliable and error-prone....
The energy transition requires efficient management of decentralized resources, in which Renewable Energy Communities (RECs) play an increasingly important role. However, the variability of solar generation and the unpredictability of consumption cre...
This paper addresses fault diagnosis in nonlinear systems where reliable mathematical models are unavailable and only input–output measurements are accessible. The proposed methodology consists of three stages. First, a data-driven identificati...
Android malware continues to evolve in sophistication, creating a need for accurate, efficient, and interpretable detection mechanisms. This paper proposes a novel Android malware detection framework that integrates graph-based software engineering a...
Algorithmic team formation is a well-studied problem in workforce analytics. Most prior research has focused on team-oriented outcomes, such as cost and performance, while individual-oriented outcomes have been limited to operational constraints. We...
With the rapid growth of social media, multimodal content combining text and images has become a major medium for rumor dissemination. However, existing multimodal rumor detection methods primarily focus on semantic modeling in the spatial domain, ma...
Accurate teeth segmentation in panoramic dental radiographs remains a challenging task due to high image noise, low contrast, the similarity in intensity between teeth and surrounding tissues, and blurred tooth boundaries. To address these challenges...
Curves constructed directly on point clouds are a core primitive in reverse engineering, product design, and point-based CAD; many workflows additionally require the curve to lie in a plane—e.g., as a section profile, inspection path, or design...
This paper studies parameter estimation of Wiener systems with quantized inputs and multiple-valued observations in the presence of replay attacks. The proposed approach effectively addresses the destruction of the data temporal structure caused by r...
Generative AI (GenAI) adoption in higher education (HE) raises significant ethical concerns. The focus is shifting from rules- or outcomes-based learning environments towards the development of moral character, personality traits, integrity, and prac...
This paper introduces an integrated multi-objective evolutionary framework for synthesis of heterogeneous regression ensembles featuring localized, learner-specific feature selection. Rather than enforcing global feature spaces, the proposed paradigm...
This paper presents a deep learning framework for automated Parkinson’s disease (PD) detection from T1-weighted MRI scans using the NTUA dataset. The proposed pipeline combines advanced preprocessing, robustness evaluation, and explainable AI t...
Modeling large shape changes efficiently is an important challenge in deformable kinematics, soft robotics, compliant mechanisms, geometric modeling, and deformation-based path planning. This paper presents Projective Estimation with Per-Point Scales...
This study develops a computer-aided molecular design (CAMD) framework for selecting solvents to extract octacosanol from multicomponent sugarcane wax. The solvent-selection problem is formulated as a mixed-integer nonlinear programming problem in wh...
Campus waste-sorting mobile manipulators operate in cluttered environments. This paper presents a task-oriented framework decoupling mobile-base navigation from manipulator motion. Its contribution is the safety-verified integration of goal-biased sa...
Aggregate model-comparison metrics identify which model performs better on average, but not whether that result is broadly supported or depends on a small number of high-impact cases. This study presents Decision Reliability Profiles (DRP) for fixed-...
Public cattle re-identification benchmarks remain limited in scale and rarely provide leakage-controlled open-set and cross-camera evaluation. Using 25,209 curated crops of 197 Holstein cows recorded by four synchronized side-view cameras in a passag...
(1) Objective: Remote sensing object detection faces significant challenges, including complex background interference, large variations in target scales, and insufficient multi-scale feature representation, which often result in missed detections of...
Human–robot collaboration (HRC) significantly enhances manufacturing flexibility and productivity, yet it faces persistent operational challenges stemming from the fundamental capability asymmetry between humans and robots. Task scheduling is a...
This paper provides a narrative review on the role of artificial intelligence in cryptography, with a substantial focus on the Advanced Encryption Standard (AES) and, where the distinction matters, on AES with 256-bit keys (AES-256), at the intersect...
Satellite battery subsystems are fundamental for reliable operation during periods when solar power is unavailable. Their performance is strongly influenced by the harsh and variable thermal conditions of the space environment. Pre-launch thermal sim...
Autonomous driving systems face significant challenges in deploying object detection models that must balance accuracy, real-time performance, and lightweight design on resource-constrained in-vehicle platforms. However, inadequate multi-scale featur...
Topological indices provide numerical descriptions of graph structure and support graph analysis in cheminformatics, network design, and graph mining. This study presents a reproducible computational framework that combines controlled cyclic-graph ge...
Visual emotion recognition plays a critical role in human–computer interaction and mental health applications. Although existing Vision–Language Models (VLMs) alleviate the limitations of conventional vision models in high-level semantic...
Hospital-acquired infections (HAIs) constitute a critical challenge in intensive care units (ICUs). In Greece, data limitations due to incomplete electronic record implementation hinder advanced risk management. This study aims to compare the predict...
Electric trucks operating as mobile depots for delivery drones are promising for last-mile logistics, yet fleet electrification makes depot charging a critical issue governed by distribution-grid limits. Existing truck–drone routing formulation...
To address the problems of the Electromagnetic Wave Propagation Algorithm (EMWPA)—insufficient initial-population coverage, an imbalance between exploration and exploitation, and a tendency to fall into local optima—in high-dimensional co...
Gait analysis is increasingly used as a dynamic functional biomarker for computer-aided diagnosis (CADx), although strong internal performance alone does not establish clinical utility. This targeted narrative review examines Parkinson’s diseas...
Accurate remaining useful life (RUL) estimation underpins safe operation and cost-effective maintenance of aerospace propulsion systems. We propose a Hybrid Quantum Recurrent Neural Network (HQRNN) for jet-engine RUL forecasting on the NASA C-MAPSS F...
Power IoT acts as the final frontier of the modern grid, where the reliability of energy supply hinges on precise monitoring. However, current systems often suffer from delayed responses, poor feature separation, and a computational wall when dealing...
Residential short-term load forecasting (STLF) plays a critical role in maintaining grid stability and enabling effective demand response in smart grid environments. However, residential electricity consumption exhibits strong stochastic variability,...
Forecasting agricultural futures prices across multiple commodities remains highly challenging due to nonlinear price dynamics, strong market volatility, and complex cross-market and cross-commodity interactions. To address these issues, this paper p...
Early identification of depression risk from social media text can support large-scale screening and timely follow-up. However, posts are often emotionally complex and linguistically ambiguous, which makes robust detection challenging. This paper pro...
Strategic bidding in day-ahead electricity markets requires generation companies to maximize expected profits while managing financial risks arising from market uncertainty and competitors’ strategic behavior. This paper proposes a game-theoret...
As false news benchmarks are increasingly being developed from fact-checking sources, this introduces a slight, but under cited, threat to validity: source bias. The two classes are not necessarily similar in style or structure; a classifier could di...
Smart home provision faces many challenges, resulting from the growing demand for monitoring smart home services in uncertain environments, such as rural areas, and regions with high humidity, pollution, and unstable electricity supply. Effective dat...
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