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Keyword: EnvironmentADOxx Modelling Method Conceptualization Environment
The importance of Modelling Methods Engineering is equally rising with the importance of domain specific languages (DSL) and individual modelling approaches. In order to capture the relevant semantic primitives for a particular domain, it is necessary to involve both, (a) domain experts, who identify relevant concepts as well as (b) method engineers who compose a…
Read MoreDevelopment of a Motorized Afifia Mowing Machine Design for Controlling Environmental Conservation and Menace for Home Use
Technology has become more affordable and penetrates every aspect of daily life, even in developing country like Nigeria. However many of the users in developing countries are still finding difficulty in using the technologies due to lack of experience as they undergo a technology leap. The aim of this research work explores the approach in…
Read MoreSemantic modeling of portfolio assessment in e-learning environment
In learning environment, portfolio is used as a tool to keep track of learner’s progress. Particularly, when it comes to e-learning, continuous assessment allows greater customization and efficiency in learning process and prevents students lost interest in their study. Also, each student has his own characteristics and learning skills that must be taken into account…
Read MoreInvestigating the Influence Biomass Additive on the Thermal Performance of a Fired-Clay for Producing the Inner Liner of a Biomass Cook-Stove
This study investigated the influence of a biomass additive on the thermal performance of the inner liner of fired-clay cook-stoves. Fired-clay cook-stoves are essential cooking devices, particularly in areas with limited access to modern energy resources. The study aimed to enhance the thermal efficiency of the cook-stoves by incorporating rice husk into the inner liner…
Read MoreFederated Learning with Differential Privacy and Blockchain for Security and Privacy in IoMT A Theoretical Comparison and Review
The growing integration of the Internet of Medical Things (IoMT) into healthcare has amplified the need for secure and privacy-preserving artificial intelligence. Federated Learning (FL) has emerged as a pivotal paradigm for decentralized medical data processing; however, it still faces challenges concerning data confidentiality, trust management, and scalability. This review presents an extended theoretical comparison…
Read MoreSystem-Level Test Case Design for Field Reliability Alignment in Complex Products
Achieving targeted reliability for complex products in real-world field environments remains a persistent challenge, even when laboratory validation suggests high performance. A significant reliability gap often emerges during the initial deployment phase, typically within the first one to five years where field failure rates can be up to twice those predicted in controlled settings. Compounding…
Read MoreStradNet: Automated Structural Adaptation for Efficient Deep Neural Network Design
Deep neural networks (DNNs) have demonstrated remarkable success across a wide range of machine learning tasks. However, determining an effective network architecture, particularly the sizes of the hidden layers, remains a significant challenge and often relies on inefficient trial-and-error experimentation. In this paper, we propose an automated architecture design approach based on structurally adaptive DNNs,…
Read MoreTIMeFoRCE: An Identity and Access Management Framework for IoT Devices in A Zero Trust Architecture
Zero Trust Architecture offers a transformative approach to network security by emphasizing ”never trust, always verify.” IoT devices, while increasingly integral to modern ecosystems, pose unique challenges for identity management and access control due to their constrained processing power, memory, and energy capabilities. In a Zero Trust framework, every IoT device is treated as a…
Read MoreCIRB-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 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 MoreImplementation and Simulation of Sequential Adverse Condition Scenarios for Autonomous Driving
Establishing an environment that allows for the quantitative evaluation of the ability of autonomous driving systems to respond to real-world adverse conditions is crucial to ensuring their safety and reliability. This study proposes a dynamic scenario-based simulation framework that simulates complex and sequential hazardous scenarios frequently encountered in actual road environments. The proposed scenarios are…
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 MoreThe Impact of Digitalization on Shipbuilding as Measured by Artificial Intelligence (AI) Maturity Models: a Systematic Review
Artificial Intelligence (AI) is reshaping the global shipbuilding sector, yet existing maturity models fail to capture the domain-specific complexities of this capital-intensive industry. This study reviews over 50 AI maturity models and introduces a specialized framework tailored for shipbuilding. The proposed model outlines four progressive stages—Beginner, Innovation, Integration, and Expert—across eight key dimensions: culture, resilience,…
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 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 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 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 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 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 MoreMalaysia’s Renewable Energy Policy and its Impact on ASEAN Countries
As the global community increasingly shifts its focus towards sustainable development and combating climate change, renewable energy policies have become pivotal in shaping national and regional energy landscapes. Malaysia, as a developing nation with a rapidly growing economy, has recognized the importance of renewable energy sources in achieving its socio-economic goals while addressing environmental concerns.…
Read MoreA Smart Farming Management System based on IoT Technologies for Sustainable Agriculture
Advances in Internet of Things (IoT) and wireless technologies are revolutionizing various sectors, including environment, education, healthcare, industry, etc. In the same dynamic, as the world population constantly evolves, solutions based on such technologies need to be proposed to improve the agricultural sector. Senegalese agriculture, primarily rain-fed and based on both cash crops and subsistence…
Read MoreImplementation of a GAS Injection Type Prefabricated Lifting Device for Underwater Rescue Based on Location Tracking
In this paper, we have developed a gas injection-type prefabricated lifting device based on location tracking to efficiently lift the human body in the event of an accident that occurs underwater on the sea or land. The efficiency of the lifting system is very important to ensure the golden time of the rescue and the…
Read MoreComparative Study of J48 Decision Tree and CART Algorithm for Liver Cancer Symptom Analysis Using Data from Carnegie Mellon University
Liver cancer is a major contributor to cancer-related mortality both in the United States and worldwide. A range of liver diseases, such as chronic liver disease, liver cirrhosis, hepatitis, and liver cancer, play a role in this statistic. Hepatitis, in particular, is the main culprit behind liver cancer. As a consequence, it is decisive to…
Read MoreControl Program Generator for Vehicle Robot using Grammatical Evolution
A robot development has spread widely for various purposes. It is difficult to create a control program for an autonomous mobile robot manually. Therefore, an automatic design of the control program for an autonomous mobile robot is proposed in this research. The autonomous mobile robot is created with LEGO MINDSTORMS EV3, and the control program…
Read MoreModeling Control Agents in Social Media Networks Using Reinforcement Learning
Designing efficient control strategies for opinion dynamics is a challenging task. Understanding how individuals change their opinions in social networks is essential to countering malicious actors and fake news and mitigating their effect on the network. In many applications such as marketing design, product launches, etc., corporations often post curated news or feeds on social…
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