IEEE Access

The recursive (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U|U+V</i>) construction, a generalization of which includes polar codes, provides a powerful framework for building complex codes from simpler components. However, existing approaches predominantly rely on fixed or symmetric tree architectures, overlooking the critical impact of decomp…

Large Language Models (LLMs) have evolved beyond being mere downstream Natural Language Processing (NLP) components: an increasing number of recent LLM-based systems can perform end-to-end planning, assembly, and evaluation of machine learning (ML) workflows. Advances in alignment techniques, tool integration, and program-generation methods enable LLMs to create end-to-end automated pipelines tha…

Software product management involves overseeing a product throughout its lifecycle to maximise business value. However, with the multitude of choices available, identifying valuable future development options and determining how to pursue them can be challenging. This process requires input from multiple stakeholders, adding to the complexity of the task. Effective communication is essential, esp…

This paper presents a comprehensive study on the quality and reliability of commercially available medium voltage surge arresters, with particular emphasis on their electrical performance and structural degradation under aging conditions. Samples from four manufacturers were subjected to 8/20 μs aging impulses and accelerated durability tests. Electrical analysis revealed that some products exhib…

This study introduces GRAFNeT (Guided Recursive Attention Fusion Network for Multimodal Medical Imaging), a novel multi-stage image fusion framework designed to achieve high-quality multi-modal integration with minimal computational overhead. The framework employs CNN feature extraction and attention modules, followed by an iterative refinement of fusion parameters at inference time. The methodol…

Automated offensive language detection (OLD) is essential for online safety, yet remains particularly challenging for under-resourced languages and their dialectal variations. This paper addresses these challenges by evaluating OLD across three low-resource Arabic dialects: Egyptian, Libyan, and Levantine, using newly collected dialect-specific datasets and a novel parallel corpus for controlled …

In this paper, we propose a scalable approximate multiplier design, scaleTRIM, that approximates the multiplication operation using fitted linear functions, also referred to as linearization. We show that multiplication operations can be completely replaced by low-cost addition and bit-wise shift operations by exploiting linearization. Moreover, our proposed design utilizes a lookup table (LUT)-b…

Representing molecular structures effectively in chemistry remains a challenging task. Language models and graph-based models are extensively utilized within this domain, consistently achieving state-of-the- art results across an array of tasks. However, the prevailing practice of representing chemical compounds in the SMILES format – used by most data sets and many language models – presents not…

Forecasting inflation in Thailand is challenging because limited time series and strong external exposures create an imbalance between few observations and many potential predictors. We evaluate modern Bayesian shrinkage and factor models, including Horseshoe regressions, factor-augmented autoregressions, factor-augmented VARs, dynamic factor models, and Bayesian additive regression trees, using …

The abrupt transition to Emergency Remote Learning during the COVID-19 pandemic significantly elevated psychological stress among higher education students. Yet, most existing research studies have either identified factors contributed by COVID-19 as stress predictors or general stress perceived as a result of the pandemic. Moreover, these studies predominantly employ binary stress detection usin…

This paper proposed a novel stator structure for outer rotor type surface permanent magnet (SPM) motors. The magnet overhang structure is a technique to increase the magnet flux by utilizing the space at the coil end, and has been widely used in SPM motors. However, because leakage flux is generated in the overhung area, which is longer than the stator core in the axial direction, the effect of t…

Any digital system on very large scale integrations requires clock distributions. For the realization, a dedicated clock tree or a mesh clock is frequently used. Field programmable gate arrays have numerous general-purpose programmable wires based on switching matrices to connect the outputs and inputs of look-up tables and input/output ports. However, field programmable gate arrays never use num…

This paper presents a dual-mode sentinel surveillance architecture for shared vehicles that combines low-power inertial event triggering with low-rate fisheye vision and temporal decision logic. Unlike conventional sentry systems based on continuous vision or motion-only alarms, the proposed approach prioritizes energy efficiency while preserving contextual awareness. We introduce SentinelCAR, a …

Medical body area networks (MBANs) operating in the 2360–2390 MHz band enable continuous health monitoring across a wide range of clinical and home-care applications. This paper presents a comprehensive performance evaluation of off-body MBAN links based on Monte Carlo simulations using empirically derived channel models from the IEEE 802.15.6 standard. Two transmitter locations, chest mounted an…

In this work, we address the challenge of accurately predicting latency in packet-switched Xhaul networks, enabling the convergent transport of fronthaul (FH) and midhaul (MH) traffic within radio access networks (RANs). Although deterministic worst-case (WC) models provide strict latency bounds, they tend to significantly overestimate actual flow latencies, leading to inefficient resource alloca…

A three dimensional reconstruction of vertebrae from CT Scans is necessary for surgical planning, medical teaching and diagnosis. Traditional methods are computationally expensive, while state-of-the art deep learning techniques lack in effective handling of sparse or incomplete data.We propose a deep learning pipeline composed of transfer learning, convolutional autoencoders, and cGANs for recon…

Countries in South Asia experience many catastrophic flooding events regularly. It takes time to execute Search and Rescue (SAR) missions in such flooded areas.With the help of image classification, it is possible to expedite such initiatives by classifying flood zones and other locations of interest like houses and humans within such regions. In this paper, we propose a new dataset to enhance SA…

This paper presents Random Motion Differential Evolution (RanMoDE) as a method for online indoor localization of flight robots using a minimal sensor setup. The sensor setup consists of six directional 1D infrared distance sensors and an inertial measurement unit (IMU) with an attitude heading reference system (AHRS). Pose estimation is performed offboard within a digital environment model, witho…

The current style transfer methods usually suffer from an imbalance in learning the content features and style features. Some of them tend to learn style information in the style domain, while others are more affinitive with the content domain. This feature imbalance learning leads to unsatisfactory image visual performance and thus provides a new perspective for the image style transfer study. I…