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Keyword: ULACharacteristics of Crystal Defects due to the Inverse Piezoelectric Effect in Aluminum Gallium Nitride / Gallium Nitride High Electron Mobility Transistors
Gallium nitride (GaN) is expected to be used as a material for power semiconductor devices. However, it is crucial to focus on the dielectric properties of GaN. In this study, we investigated the transient response of the drain current during high-frequency application after intentionally maintaining the current collapse in the AlGaN/GaN high electron mobility transistors.…
Read MoreA Study of the Digital Health Management Needs of the Elderly
The purpose of this paper is to explore the feasibility and development trend of utilizing smart medical technology for chronic disease health management in older people in the context of ageing at home. As the ageing society intensifies, the elderly population faces multiple health challenges, especially the management of chronic diseases. This paper analyzes the…
Read MoreAI-Based Photography Assessment System using Convolutional Neural Networks
Providing timely and meaningful feedback in photography education is challenging, particularly in large classes where manual assessment can delay skill development. This paper presents M-Stock, an AI-based automated photo evaluation system that uses Convolutional Neural Networks (CNNs) to assess student photography assignments on web browser. M-Stock evaluates both technical aspects (such as lighting, composition, and…
Read MoreIntroducing a Stress Management and Navigation System for Blind Individuals
The most challenging task in daily life of blind individuals is navigating outdoors. In this context, we are introducing and describing a navigation system that will provide two important tasks for blind individuals. Initially, the system will suggest the least stressful route for the blind to navigate among the various possible paths between a starting…
Read MoreGenerative Artificial Intelligence and Prompt Engineering: A Comprehensive Guide to Models, Methods, and Best Practices
This article enhances discussions on Generative Artificial Intelligence (GenAI) and prompt engineering by exploring critical pitfalls and industry-specific advantages. It begins with a foundational overview of AI evolution, emphasizing how generative models such as GANs, VAEs, and Transformers have revolutionized language processing, image generation, and drug discovery. Prompt engineering is highlighted as a key methodology…
Read MoreText Line Segmentation on Myanmar Handwritten Document using Average Linkage Clustering Algorithm
Text line segmentation from document images is a significant challenge in the field of document image analysis. It involves extracting individual text lines from Myanmar handwritten document images to enable text recognition. This task becomes particularly challenging in Myanmar handwritten documents, especially those with irregular or cursive writing styles, due to variations in line spacing,…
Read MoreAnalytical Study on the Effect of Rotor Slot Skewing on the Parasitic Torques of the Squirrel Cage Induction Machine
Skewing of the rotor slot of a squirrel-cage induction machine has been commonly used since the beginning. However, little guidance is given regarding the principle of the working effect of the method, but even in such rare cases, the explanation does not cover the true physical reality. Consequently no formula exists for calculation of the…
Read MoreLightning Detection System for Wind Turbines Using a Large-Diameter Rogowski Coil
A lightning detection system based on a large-diameter Rogowski coil and an analog integrator was developed for wind turbine applications and is presented in this paper. To accurately detect lightning current, the Rogowski coil was designed with a lower cutoff frequency of 0.1 Hz. The analog integrator, comprising an inverting active integrator, and an amplifier,…
Read MoreTrue Random Number Generator Implemented in ReRAM Crossbar Based on Static Stochasticity of ReRAMs
True Random Number Generators (TRNG) find applications in various fields, especially hardware security. We suggest a TRNG that exploits the intrinsic static stochasticity of Resistive Switching Random Access Memories (ReRAMs) to generate random bits. Other suggested designs use stochasticity in the switching mechanism, which requires high precision over input voltage and time. In the proposed…
Read MoreAdvanced Fall Analysis for Elderly Monitoring Using Feature Fusion and CNN-LSTM: A Multi-Camera Approach
As society ages, the imbalance between family caregivers and elderly individuals increases, leading to inadequate support for seniors in many regions. This situation has ignited interest in automatic health monitoring systems, particularly in fall detection, due to the significant health risks that falls pose to older adults. This research presents a vision-based fall detection system…
Read MoreAdvancements in Explainable Artificial Intelligence for Enhanced Transparency and Interpretability across Business Applications
This manuscript offers an in-depth analysis of Explainable Artificial Intelligence (XAI), em- phasizing its crucial role in developing transparent and ethically compliant AI systems. It traces AI’s evolution from basic algorithms to complex systems capable of autonomous de- cisions with self-explanation. The paper distinguishes between explainability—making AI decision processes understandable to humans—and interpretability, which provides…
Read MoreWeb Application Interface Data Collector for Issue Reporting
Insufficient information is often pointed out as one of the main problems with bug reports as most bugs are reported manually, they lack detailed information describing steps to reproduce the unexpected behavior, leading to increased time and effort for developers to reproduce and fix bugs. Current bug reporting systems lack support for self-hosted systems that…
Read MoreEarly Detection of SMPS Electromagnetic Interference Failures Using Fuzzy Multi-Task Functional Fusion Prediction
This study addresses the need for improved prognostics in switch-mode power supplies (SMPS) that incorporate electromagnetic interference (EMI) filters, with a focus on aluminum electrolytic capacitors, which are critical for the reliability of these systems. The primary aim is to develop a robust model-based approach that can accurately predict the degradation and operational lifetime of…
Read MoreHybrid Optical Scanning Holography for Automatic Three-Dimensional Reconstruction of Brain Tumors from MRI using Active Contours
This paper presents a method for automatic 3D segmentation of brain tumors in MRI using optical scanning holography. Automatic segmentation of tumors from 2D slices (coronal, sagittal and axial) enables efficient 3D reconstruction of the region of interest, eliminating the human errors of manual methods. The method uses enhanced optical scanning holography with a cylindrical…
Read MoreDeploying Trusted and Immutable Predictive Models on a Public Blockchain Network
Machine learning-based predictive models often face challenges, particularly biases and a lack of trust in their predictions when deployed by individual agents. Establishing a robust deployment methodology that supports validating the accuracy and fairness of these models is a critical endeavor. In this paper, we introduce a novel approach to deploying predictive models, such as…
Read MoreLeveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity
Polyfluoroalkyl substances (PFAS) are persistent chemicals that accumulate in the body and environment. Although recent studies have indicated that PFAS may disrupt kidney function, the underlying mechanisms and overall effects on the organ remain unclear. Therefore, this study aims to elucidate the impact of PFAS on kidney health using machine learning techniques. Utilizing a dataset…
Read MoreEfficient Deep Learning-Based Viewport Estimation for 360-Degree Video Streaming
While Virtual reality is becoming more popular, 360-degree video transmission over the Internet is challenging due to the video bandwidth. Viewport Adaptive Streaming (VAS) was proposed to reduce the network capacity demand of 360-degree video by transmitting lower quality video for the parts of the video that are not in the current viewport. Understanding how…
Read MoreSolar Photovoltaic Power Output Forecasting using Deep Learning Models: A Case Study of Zagtouli PV Power Plant
Forecasting solar PV power output holds significant importance in the realm of energy management, particularly due to the intermittent nature of solar irradiation. Currently, most forecasting studies employ statistical methods. However, deep learning models have the potential for better forecasting. This study utilises Long Short-Term Memory (LSTM), Gate Recurrent Unit (GRU) and hybrid LSTM-GRU deep…
Read MoreVisualization of the Effect of Additional Fertilization on Paddy Rice by Time-Series Analysis of Vegetation Indices using UAV and Minimizing the Number of Monitoring Days for its Workload Reduction
This research is an extension of the research (ISEEIE 2023), which dealt with Time-Series Clustering (TSC) of Vegetation Index (VI) for paddy rice. The novelty of this research is “Visualization of growth changes before and after additional fertilization,” “Analyzing the appropriate amount of additional fertilizer,” and “Optimization of monitoring period to minimize the number of…
Read MoreAn Adaptive Heterogeneous Ensemble Learning Model for Credit Card Fraud Detection
The proliferation of internet economies has given the corporate world manifold advantages to businesses, as they can now incorporate the latest innovations into their operations, thereby enhancing ease of doing business. For instance, financial institutions have leveraged credit card usage on the aforesaid proliferation. However, this exposes clients to cybercrime, as fraudsters always find ways…
Read MoreSpatial Distribution Patterns of the Royal Development Projects Initiated by King Rama 9th of Thailand
The study aimed to create a chronological overview of the royal development projects initiated by King Rama IX and to analyze their spatial distribution patterns. The research used a mixed-methods approach, combining quantitative and qualitative data collection methods such as obtaining data from relevant offices, internet research, and field observations. Data analysis involved descriptive statistics…
Read MoreDouble-Enhanced Convolutional Neural Network for Multi-Stage Classification of Alzheimer’s Disease
Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…
Read MoreOptimal Engagement of Residential Battery Storage to Alleviate Grid Upgrades Caused by EVs and Solar Systems
The integration of distributed energy resources has ushered in a host of complex challenges, significantly impacting power quality in distribution networks. This work studies these challenges, exploring issues such as voltage fluctuations and escalating power losses caused by the integration of solar systems and electric vehicle (EV) chargers. We present a robust methodology focused on…
Read MoreBridging Culture and Care: A Mobile App for Diabetes Self-Care Honoring Native American Cultural Practices
Diabetes presents a significant public health issue for Native Americans, exacerbated by cultural nuances often ignored by conventional healthcare. To address this, we introduce a mobile app designed with the cultural context of Native American populations in mind. The app’s development followed participatory design principles, with direct input from Native American stakeholders through focus groups…
Read MoreDevelopment and Usability Evaluation of Mobile Augmented Reality Contents for Railway Vehicle Maintenance Training: Air Compressor Case
The air compressor of a railroad vehicle is an important equipment that produces compressed air used in braking systems. New visual interaction techniques were proposed and evaluated to develop effective augmented reality content for maintenance support and training of this device. To this end, modeling techniques capable of fast animation, storyboard production to support light…
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