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Keyword: HANCIRB-Edge for Secure, Energy-Efficient, and Real-Time Edge Computing
In this work, we present CIRB-Edge, a novel integer compression method designed specifically to overcome the limitations of traditional techniques such as Huffman coding, Delta encoding, and dictionary-based algorithms. These legacy methods often fall short in meeting the stringent requirements of secure, energy-efficient, and real-time edge computing due to their high computational overhead, memory demands,…
Read MoreOptimization of Investment in Decision – Making in Engineering Economy
Investment decision-making plays a pivotal role in shaping both individual and institutional economic outcomes. Given the increasing complexity and uncertainty in global markets, optimizing investment decisions has become essential for maximizing returns while managing risks. This work explores modern optimization approaches in investment decision-making, focusing on mathematical modeling techniques such as linear programming (LP), mixed-integer…
Read MoreEconomic Replacement of Plants and Equipment: A Decision-Making Framework in Engineering
While prior research has focused on siloed approaches to equipment replacement, this study introduces an integrated decision-making framework that synergizes predictive maintenance (IoT/M), dynamic multi-criteria analysis (MCDM), and sustainability-driven material selection. By validating this model through cross-sector case studies and strategic operational planning across various industrial sectors. We demonstrate a 30% improvement in replacement timing…
Read MoreIntegration and Innovation of a Micro-Topic-Pedagogy Teaching Model under the New Engineering Education Paradigm
The rapid evolution of global technologies and industrial restructuring demands innovative pedagogical approaches to foster interdisciplinary engineering expertise. This research pioneers a blended instructional framework anchored in micro-topic pedagogy under the New Engineering Education (NEE) paradigm, orchestrating case studies, heuristic scaffolding, and research-driven inquiry strategies within digitally augmented learning ecosystems. A quasi-experimental study was conducted…
Read MoreComplete System and Interactions of MMF Harmonics in a Squirrel Cage Induction Motor; Differential Leakage; Analytic Calculation
The importance of MMF space harmonics in squirrel-cage induction motors has been recognized in the literature since the beginning. Their details have been analyzed over the years, but only partly systematized. In this article, however, not only the origin and the entire system of that harmonics are described, but also their interaction causing the asynchronous…
Read MoreThe First Study on Ionospheric Peak Variability over Equatorial Africa (COSMIC-2)
In regions like the African equatorial region, where ground-based sensors like ionosondes and incoherent scatter radars are limited, satellite-based radio occultation (RO) observations offer a new alternative for ionospheric data collecting and optimization. Using RO measurements from the mostly newly launched COSMIC-2 (Constellation Observing System for Meteorology, Ionosphere, and Climate-2) mission, hence, the equatorial Africa,…
Read MoreMachine Learning Methods for University Student Performance Prediction in Basic Skills based on Psychometric Profile
Ensuring the quality of higher education in Brazil presents a complex challenge, intensified by factors that directly affect students’ academic performance. The pervasive influence of social media and the overconsumption of superficial digital content undermine students’ ability to engage in deep comprehension, critical thinking, and the practical application of knowledge. Furthermore, inadequate preparation during the…
Read MorePredictive Analytics in Marketing: Evaluating its Effectiveness in Driving Customer Engagement
Understanding and responding to customer feedback is critical for business success. Customer response data offers valuable insights into preferences, behaviours, and sentiment. By analysing this data, businesses can optimize strategies, enhance customer experiences, and drive growth. Many analysis have been conducted in this field, while the review covers a broad range of AI and ML…
Read MoreExplainable AI and Active Learning for Photovoltaic System Fault Detection: A Bibliometric Study and Future Directions
Persistent anomalies in modern photovoltaic (PV) systems present a formidable challenge, impeding optimal power output and system resilience. Artificial Intelligence (AI) has surfaced as a game-changing solution, yet existing research has merely scratched the surface of solar panel prognosis, leaving a critical void in leveraging AI’s explainable nature and active learning capabilities. This pioneering study…
Read MoreCooperative Game Theory for Grid Service Pricing: A Utility-Centric Approach
This study presents a novel alternative to traditional Net Energy Metering (NEM) by proposing a set of innovative pricing schemes for solar customers participating in utility-led grid service programs through the aggregation of Distributed Energy Resources (DERs). Grounded in cooperative game theory, the proposed framework facilitates equitable and efficient value allocation among key stakeholders, namely…
Read MoreCharacteristics 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 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 MoreImpact of Integrating Chatbots into Digital Universities Platforms on the Interactions between the Learner and the Educational Content
The rapid expansion of digital universities across Africa addresses the need for scalable higher education solutions, but challenges such as limited physical infrastructure and high dropout rates persist. In digital learning environments, effective interaction with educational content is crucial for student success. This article explores the transformative role of chatbots integrated into digital university platforms,…
Read MoreEvaluation of Physicochemical Stability in Extemporaneous Omeprazole-Based Preparations
Extemporaneous omeprazole-based preparations are commonly used in hospitals; however, there are no validated studies about physicochemical stability. This study aimed to determine if temperature, luminosity, and the type of diluent affect the stability of omeprazole in the extemporaneous preparation. For stability, the methodology validated previously by our group was used. The 2k experimental design included…
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 MoreUtilizing 3D models for the Prediction of Work Man-Hour in Complex Industrial Products using Machine Learning
The integration of machine learning techniques in industrial production has the potential to revolutionize traditional manufacturing processes. In this study, we examine the efficacy of gradient-boosting machine learning models, specifically focusing on feature engineering techniques, applied to a novel dataset with 3D product models pertaining to work moan-hours in metal sheet stamping projects, framed as…
Read MoreEvaluation of a Classroom Support System for Programming Education Using Tangible Materials
In recent years, the utilization of tangible educational materials has attracted attention on educational settings. They provide hands-on learning experiences for beginners. This trend is especially notable in the field of programming education. Such educational materials are employed in many institutions worldwide. They liberate learners of programming from programming languages that are confined in a…
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 MoreAssistive System for Collaborative Assembly Task using Augmented Reality
Augmented reality (AR) technology has been increasingly used in developing teaching materials with the aim of sparking more interest in technology (T) and engineering (E) among students in STEM education. In the proposed system, AR is integrated with an educational robot controlled by a KidBright microcontroller board, developed by the Educational Technology research team (EDT)…
Read MoreEnergy Management Policy and Strategies in ASEAN
This research analyses the challenges faced by ASEAN countries in managing its energy efficiencies and resources due to rapid economic growth, increasing energy demand, and diverse energy infrastructures across member states. This paper explores the energy management policies and strategies within the ASEAN region, focusing on the integration of energy efficiency measures, renewable energy initiatives,…
Read MoreOn Mining Most Popular Packages
In this paper, we will discuss two algorithms to solve the so-called package design problem, by which a set of queries (referred to as a query log) is represented by a collection of bit strings with each indicating the favourite activities or items of customers. For such a query log, we are required to design…
Read MoreIntegrating Speech and Gesture for Generating Reliable Robotic Task Configuration
This paper presents a system that combines speech and pointing gestures along with four distinct hand gestures to precisely identify both the object of interest and parameters for robotic tasks. We utilized skeleton landmarks to detect pointing gestures and determine their direction, while a pre-trained model, trained on 21 hand landmarks from 2D images, was…
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…
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