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Keyword: DEMIoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring
Gas leakage caused by various causes poses significant risks to public safety. To address this problem, an intelligent model is proposed for the accurate monitoring of Liquefied Petroleum Gas (LPG) distribution based on the integration of Internet of Things (IoT) and Business Intelli- gence (BI) technologies. Through the use of sensors and actuators, it seeks…
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 MoreGPT-Enhanced Hierarchical Deep Learning Model for Automated ICD Coding
In healthcare, accurate communication is critical, and medical coding, especially coding using the ICD (International Classification of Diseases) standards, plays a vital role in achieving this accuracy. Traditionally, ICD coding has been a time-consuming manual process performed by trained professionals, involving the assignment of codes to patient records, such as doctor’s notes. In this paper,…
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 MoreEvaluation of Various Deep Learning Models for Short-Term Solar Forecasting in the Arctic using a Distributed Sensor Network
The solar photovoltaic (PV) power generation industry has experienced substantial, ongoing growth over the past decades as a clean, cost-effective energy source. As electric grids use ever-larger proportions of solar PV, the technology’s inherent variability—primarily due to clouds—poses a challenge to maintaining grid stability. This is especially true for geographically dense, electrically isolated grids common…
Read MoreButon Rock Asphalt Paving Block Innovation using Waste Engine Oil and Recycled Concrete Aggregate
Road surface coating using concrete paving block cement has been used for a long time. As an aggregate binding agent, asphalt can be made into paving blocks. Utilizing waste in the recycling process is an activity to control the sustainability of natural resources. Waste Engine Oil and Recycled Concrete Aggregate can be used as road…
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 MoreDevelopment of a GSM-RC Automated Device for Measuring Mobile Communication Signal Strength and Meteorological Parameters
The automated Global System for Mobile Communication Signal Strength and Radio Climatological (GSM-RC) measuring device is an integration of different electronic sensors in a box for an in-situ measuring system. The sensor, data logging, and communication subsystems are integrated for transmitting information on meteorological parameters (MPs) and GSM signal strength level (SSL). The goal is…
Read MoreEnhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data
The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…
Read MoreAnalysis of Emotions and Movements of Asian and European Facial Expressions
The aim of this study is to develop an advanced framework that not only recognize the dominant facial emotion, but also contains modules for gesture recognition and text-to-speech recognition. Each module is meticulously designed and integrated into unified system. The implemented models have been revised, with the results presented through graphical representations, providing prevalent emotions…
Read MoreStrengthening LoRaWAN Servers: A Comprehensive Update with AES Encryption and Grafana Mapping Solutions
This work enhances the LoRaWAN server framework, focusing on an innovative approach for robust security and dynamic data visualization in network management. Migrating from RVC4 to AES encryption, it fortifies the network’s defense against cyber threats, a crucial advancement in IoT security. Furthermore, the integration with Grafana’s mapping plugin capitalizes on geolocation data, a strategic…
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 MoreEnhancing Cloud Security: A Comprehensive Framework for Real-Time Detection, Analysis and Cyber Threat Intelligence Sharing
Cloud computing has emerged as a pivotal component of contemporary IT systems, affording organizations the agility and scalability required to meet the ever-changing demands of business. However, this technological evolution has introduced a new era of cybersecurity challenges, as attackers employ increasingly sophisticated strategies to breach cloud networks. Such breaches can have far-reaching consequences, including…
Read MoreTowards Real-Time Multi-Class Object Detection and Tracking for the FLS Pattern Cutting Task
The advent of laparoscopic surgery has increased the need to incorporate simulator-based training into traditional training programs to improve resident training and feedback. However, current training methods rely on expert surgeons to evaluate the dexterity of trainees, a time-consuming and subjective process. Through this research, we aim to extend the use of object detection in…
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 MoreIoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal
In this work, our contribution will intervene to reduce the impact of noises on the ECG signals. Various ECG denoising approaches were tested to see how efficient they were in removing dominant noises that add to pure ECG signals. Due to different causes such as interference, muscular noise, body movement related to breathing, and so…
Read MoreDesign and Prototyping of a 3DOF Worm-drive Robot Arm
Many designs for robot arms exist. Here we present an affordable revolute arm, capable of executing simple pick-and-place tasks. The arm employs a double parallelogram structure, which ensures its endpoint angle in the plane of the upper arm remains fixed without the need for additional actuation. Its limbs are fabricated from circular tubes made from…
Read MoreCondition Assessment of Medium Voltage Assets: A Review
Condition assessment of medium voltage assets is essential to ensure reliability and cost-effective operation of power distribution networks. This article presents a literature review of condition assessment of medium voltage assets related to a distribution system in a non-interconnected zone in Colombia, namely, power transformers, photovoltaic systems, switchgear, lines and cables, and instrument transformers. Advanced…
Read MoreApplication of Lean Practices in Food Supply Chain: The Case of Morocco
Recent studies show the benefits of lean manufacturing implementation in agri-food industries to improve operational and environmental performance. However, only a restricted number of studies have addressed the implementation of lean practices in food companies located in developing countries. This study aims to assess the current implementation status of lean practices in Moroccan agri-food companies,…
Read MoreA Circuit Designer’s Perspective to MOSFET Behaviour: Common Questions and Practical Insights
Metal Oxide Semiconductor Field-Effect Transistors are commonly taught in courses for electrical engineers as they are the most common components within integrated circuits. However, despite numerous papers and books on MOSFETs, students still struggle with understanding their behaviour, particularly in the saturation region. This paper presents an expanded explanation of MOSFET behaviour, with a consistent…
Read MoreInvestigating the Impression Effects of a Teacher-Type Robot Equipped a Perplexion Estimation Method on College Students
In recent years, the adoption of ICT education has increased in educational settings. Research and development of educational support robots have garnered considerable interest as a promising approach to inspire and engage students. Conventional robots provide learning support through button operations by the learners. However, the frequent need for button operation to request support may…
Read MoreDoubling the Number of Connected Devices in Narrow-band Internet of Things while Maintaining System Performance: An STC-based Approach
Narrow-band Internet of Things (NB-IoT) is a low-power wide-area network (LPWAN) method that was first launched by the 3rd generation partnership project (3GPP) Rel-13 with the purpose of enabling low-cost, low-power, and wide-area cellular connections for the Internet of Things (IoT). As the demand for over-the-air services grows and with the number of linked wireless…
Read MoreSimulation of Obstacle Detection Based on Optical Flow Images for Avoidance Control of Mobile Robots
The article presents a simulation of obstacle detection based on noise-free optical flow images for motion control of mobile robots. The detection of hazardous areas in optical flow images is accomplished by dividing multiple layers of optical flow vectors into equal parts. Based on the results of calculating the average magnitude of the vectors in…
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