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In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

Machine learning has evolved into a potent tool for analysing patterns and making predictions from complex data. In this machine learning era, we employed neural network techniques to estimate the parameters of statistic...

During the golden-time phase of urban disasters, emergency response systems must issue timely directives that remain compliant with jurisdictional policies and regulations, even when early human reports precede reliable ...

This paper investigates the distributed state estimation problem for a class of continuous-time nonlinear systems over sensor networks. The nonlinearities considered are assumed to satisfy the Incremental Quadratic Const...

This study investigates the long-term aging effects and structural degradation mechanisms of photovoltaic (PV) modules integrated into smart city furniture, with a particular focus on panels of 10 W, 25 W, and 40 W nomin...

This paper presents a comprehensive review of Medium Voltage (MV) Wind Energy Conversion Systems (WECS) with the integration of Wide-bandgap (WBG) semiconductor devices. With the growing demand for high-power offshore wi...

ARM-based systems are widely deployed in edge and IoT settings, where penetration-testing tools must operate under strict memory, power, and thermal constraints, yet prior work offers limited deployment-oriented guidance...

Presents corrections to the paper, (Demand Forecasting in Data-Scarce and Resource-Restricted Environments).

With advances in aerospace technology, high-resolution optical imagery from satellites, such as China’s Gaofen series, is vital for climate monitoring and agriculture. However, cloud cover significantly impedes th...

Electrochemical potential noise signals from LiFePO4 batteries often contain a slowly varying trend component that overlaps with and distorts the intrinsic low-frequency electrochemical noise. This component must therefo...

The design of a bistatic inverse synthetic aperture radar (ISAR) images simulator is described, as a response to the need of databases with classification purposes in bistatic radar scenarios characterized by numerous de...

The increasing penetration of renewable energy sources (RES) reduces power system inertia, causing severe frequency excursions following disturbances. Conventional Automatic Generation Control (AGC) using fixed-gain cont...

In the present study, the transmission error (TE) behaviour of an identical involute spur gear pair dynamically coupled with an attached subsystem is investigated through numerical modelling. The surrounding mechanical s...

The ceiling effect, a phenomenon in which rotor thrust increases near a ceiling wall, holds significant potential for applications in energy-efficient drones and aerial manipulation. However, previous studies have not re...

This study develops a first-order quasi-static framework for climbing initiation in passive handcarts and proposes two passive modules to relax the resulting geometric constraints. Unlike motorized platforms that apply t...

Industry 4.0 has brought numerous advantages, such as increasing productivity through automation. However, it also presents major cybersecurity issues, such as cyberattacks affecting industrial processes. Federated Learn...

User populations in modern recommendation systems consist of diverse communities with distinct and often non-overlapping preferences. However, most existing models, such as traditional Variational Autoencoders (VAEs), op...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

Federated Prompt Learning (FPL) enables efficient collaborative adaptation of large-scale models, but it remains vulnerable to data heterogeneity: locally optimized prompts may become biased, thereby weakening the aggreg...

To achieve high accuracies in deep learning-based inspection of IC markings, a large number of manually labeled images of good and defective markings are needed. In many IC production lines, only a handful of labeled ima...

We tackle the challenging problem of single-source domain generalization (DG) for medical image segmentation, where we train a network on one domain (e.g., CT) and directly apply it to a different domain (e.g., MR) witho...

Reliable trajectory similarity estimation underpins applications such as map matching, mobility anomaly detection, and travel behavior analysis. However, traditional distance-based methods are computationally expensive a...

Attacks on network components and devices pose a significant threat to service continuity, necessitating robust detection mechanisms. This paper presents a Distributed Denial of Service (DDoS) attack detection framework ...

Efficient UAV path planning in large and dynamic environments requires adaptive strategies that account for varying regional importance. Traditional coverage or Reinforcement Learning-based methods often suffer from redu...