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To address the sensitivity of traditional Two-Dimensional Principal Component Analysis (2DPCA) to outliers and the breakdown of variance-reconstruction equivalence under noise, we propose an Angle-Aware Weighted 2DPCA (A...

Customer churn prediction is essential across data-driven industries such as insurance, digital banking, e-commerce, and subscription platforms, where retaining existing customers is typically more cost-effective than ac...

Structural health monitoring (SHM) has become a central tool for managing civil infrastructure. In modern SHM, the physical structure and the SHM system together form a coupled cyber-physical system. Due to the networked...

Metamaterial based approaches have emerged as promising solutions for mitigating mutual coupling in compact multiple input multiple output antenna systems operating at fifth generation sub-6 GHz frequencies for smartphon...

Electric vehicles are currently the leading solution in the automotive market to reduce greenhouse gas emissions. However, transitioning from traditional internal combustion engines poses many challenges. One of these ch...

In recent years, Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) have gained significant momentum in the automation of software development. Although, previous research studies have also explo...

The Zulfikar sword is a highly standardized sacred weapon symbol in Shia visual culture, forming a stable iconographic lineage across the Middle East and the Irano-Ottoman world. However, it is notably absent from Chines...

Integration of Photovoltaic (PV) generation into oil and gas power networks has transformed fault behaviour by creating highly complex sensitivity challenges for conventional Overcurrent Relay (OCR) coordination and trip...

Radiography or X-ray imaging is a diagnostic imaging used in medicine to produce images of inner anatomical structures such as bones, teeth, lungs, and chest organs. Impulse noise is one of the major factors that degrade...

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...

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...

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...

This study focuses on the explainability of AI operations for diagnosing degradations in cloud applications. Log data can provide essential contextual information on misbehaving applications in monitoring, evaluated agai...

Cybersecurity education often struggles to engage learners while effectively conveying complex web vulnerabilities. This challenge is particularly evident in topics such as cross-site scripting (XSS), where understanding...

Time-series forecasting is fundamental to decision-making across numerous domains; however, systematic temporal delays in predictions remain a largely overlooked or unrecognised phenomenon. This phenomenon occurs when fo...

In classical vernacular Chinese fiction, inferring affective stance in the presence of rhetorical devices often depends on implicit semantics and contextual cues, which poses substantial challenges for joint pragmatic mo...

This work presents a radiation-hardened Superjunction Vertical Double-Diffused MOSFET (SJ-VDMOS) architecture designed to improve robustness against destructive single-event effects (SEEs), specifically Single-Event Gate...

In this paper, a multispectral demosaicking algorithm that builds upon bilinear decomposition of a color image is proposed. The proposed algorithm can be summarized into three parts, where the first part constructs a gra...

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...

The validity of research findings critically depends on the selection of software samples. However, Mining Software Repositories studies often rely on outdated datasets and lack systematic, transparent procedures for rep...

Graph-based text classification has become an effective paradigm for modeling corpus-level structure, particularly under limited supervision. However, most existing approaches rely on document–word representations...

In modern industrial process monitoring of multivariate time series, the effectiveness of data-driven event detection is often constrained by scarce labels and the dynamic complexity of real-world telemetry. While unsupe...