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Keyword: CANIoT 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 MoreEffectiveness of a voice analysis technique in the assessment of depression status of individuals from Ho Chi Minh City, Viet Nam: A cross-sectional study
The Mind Monitoring System (MIMOSYS) is a novel voice analysis technique for mental health assessment that has been validated in some languages; however, no research has been conducted on the Vietnamese yet. This study aimed to examine the ability of the Vitality score extracted from the MIMOSYS system to assess depression status based on the…
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 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 MoreFrom Sensors to Data: Model and Architecture of an IoT Public Network
RetePAIoT of Emilia-Romagna region is an IoT Public Network, financed by Emilia-Romagna Region and developed by Lepida Scpa, where citizens, private companies and Public Administrations can integrate free of charge their own sensors of any type and anywhere in the region. The main objective of the project is to provide a facility to implement the…
Read MoreProposal and Implementation of Seawater Temperature Prediction Model using Transfer Learning Considering Water Depth Differences
Aquaculture is one of the most important industries worldwide, and most marine products are produced by aquaculture. On the other hand, the aquaculture farmers are faced on the challenge of damage to marine products due to abnormal seawater temperatures. Research on seawater temperature prediction have been conducted, but many of them require a large amount…
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 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 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 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 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 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 MoreRevolutionizing Robo-Advisors: Unveiling Global Financial Markets, AI-Driven Innovations, and Technological Landscapes for Enhanced Investment Decisions
Robo-advisors, fundamental to the financial services sector, have undergone substantial technological metamorphosis. Innovations in artificial intelligence, blockchain, cloud technology, augmented reality, and virtual reality have reshaped the financial industry’s landscape. As automated investment solutions, robo-advisors are on the brink of further technological evolution. This comprehensive research amalgamates historical data, behavioral insights, and emerging market trends…
Read MoreAnalysis of Components and Effects of Chest Compression Posture using CPR Training System
Cardiopulmonary resuscitation (hereafter CPR) is a life-saving procedure to combat our day-to-day risks of cardiac arrest. However, there are a few citizens who can accurately carry out CPR by encountering the scene of the cardiac arrest of others, and there are many unclear parts on the methods such as the correct attitude of CPR, and…
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 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 MoreInvestigating Heart Rate Variability Index Classification in Macaca fascicularis and Humans: Exploring Applications for Personal Identification and Anonymization Studies
In this paper, we determine the feasibility of differentiating between the heart rate patterns of Macaca fascicularis and human infants by comparing pertinent hyperparameters. This verification process was undertaken to ascertain the suitability of Macaca fascicularis heart rate data as a testbed for evaluating heart rate parameter privacy safeguarding methodologies. The biological characteristics of Macaca…
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…
Read MoreEnhancing Compressive Strength of Pervious Concrete for Use as Pavement Layer in Urban Roads Aper
South African Drainage and Stormwater Systems in urban roads has been of great concern, more so with recent flash floods in Gauteng and KwaZulu Natal Province in South Africa. Pervious concrete can be used to mitigate these challenges for urban roads. Pervious concrete is a concrete that contains no fines or only a small amount…
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 MoreVerify of Left and Right Differences in Sleep Index using the Ring-type Sensor
In this study, two healthy women in their 40s wore Oura Rings on both fingers and verified left and right differences in sleep index. Bed time, sleep time, rem sleep, sleep score, and heart rate had small left and right differences in both subjects, and a high correlation of 0.8 or more was observed(subjectA:P<0.001,subjectB:P<0.01). Subject…
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