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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…

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…

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,…

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…

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…

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…

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…

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…

The integration of fluctuating renewable resources such as wind and solar into existing power systems poses challenges to grid reliability and the seamless incorporation of these resources. To address the inherent variability in renewable generation, direct load control emerges as a promising method for demand-side management. Thermostatically controlled appliances, like air conditioners, hold a significant…

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…

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…

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…

Cybercriminal exploits integrity, confidentiality, and availability of information resources. Cyberattacks are typically invisible to the naked eye, even though they target a wide range of our digital assets, such as internet-connected smart devices, computers, and networking devices. Implementing network anomaly detection proves to be an effective method for identifying these malicious activities. The traditional anomaly…

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…

A reliable healthcare system ensures that the population has access to top-notch medical ser- vices, ultimately enhancing their overall health most efficiently. At times, data are not secured or handled appropriately. Addressing these concerns, blockchain technology is projected to bring about a substantial revolution in the medical industry by assuring the confidentiality of electronic health…

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…

In this paper, we delve into the pressing necessity for proficient battery cell balancing, an imperative in the context of the escalating adoption of renewable energy and electric vehicles. While traditional methodologies, including the passive technique, offer a straightforward and cost-effective solution, they compromise on efficiency. The active technique, though superior in efficiency, is hindered…

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…

In a challenging and increasingly technological world, it is important to promote critical thinking, multidisciplinary problem solving, and collaboration through STEAM education; however, there are important economic, administrative, and especially pedagogical manage- ment limitations for its implementation at the secondary level. Therefore, this paper presents systematic recommendations for an effective and sustainable implementation of STEAM…

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…

The human resource development of robotics and automation in the smart factory is an important factor in “Thailand 4.0” roadmap, which is following the industry 4.0 model. To pursue this goal of Thailand 4.0 roadmap of labor development, the effective and intuitive training system must be easy to understand. This study proposes the implementation of…

Early warning systems have had a significant impact on society by providing timely information to mitigate the effects of natural disasters. To enhance early warning capabilities, researchers are exploring the use of digital terrestrial television systems to broadcast alerts across large urban and rural areas. In this research project, the aim is to integrate the…

Over the past ten years, deep learning models have considerably advanced research in artificial intelligence, particularly in the segmentation of medical images. One of the key benefits of medical picture segmentation is that it allows for a more accurate analysis of anatomical data by separating only pertinent areas. Numerous studies revealed that these models could…

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…

Due to the variations in weather conditions, photovoltaic systems adopt a technique based on maximum power point tracking to extract the maximal power of the solar module. In the literature, there are many different methods classical and intelligent of maximum power point tracking (MPPT). But, due to the semiconductor effect, the current-voltage characteristics of the…