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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…

Energy Efficiency (EE) plays a key role in decreasing energy consumption at a European level, while it is considered as one of the most cost-efficient means to achieve carbon reduction and reinforce energy sufficiency and security. EE financing is imperative to implement measures that will lead to achieving the desired carbon neutrality and, thus, avert…

The remarkable presence of side lobes levels in ultrasound B-mode imaging significantly decreases the image quality. Therefore, the use of an apodization function is of great importance. Linear windowing functions are among the most efficient techniques used to optimize antenna directivity by suppression of the side lobes. However, the apodization causes the degradation of lateral…

We introduce a sign algorithm based on the normalised least mean square with Hammerstein adaptive filtering using adaptive averaging step-size mechanism, which is derived by the minimised absolute a posteriori squared error. To improve the performance by reducing computational complexity, we suggest an adaptive averaging using energy of errors to update step-size variant. The analysis…

Storage-Class Memory (SCM) like OptaneTM has advanced as a fast storage medium, and conventional memory management systems designed for the hard disk storage need to be reconsidered. In this article, we revisit the memory management system that adopts SCM as the underlying storage medium and discuss the issues in two layers: file caching and virtual…

Increased recycling of PVC has become a requirement in industrial and scientific research level. Several studies will be realized. To confirm and check the recycled materials performance, it will be important to go through numerical modeling, which consists not only in validating the results of the experiments, but also in predicting what happens when the…

The 5G is the fifth generation of mobile broadband, cellular technologies, and networks that promises a major change in mobility by evolving connected business realities. In such an emerging environment, reliable Service Level Agreements (SLA) and anticipation of breaches of Service Level Objectives (SLO) become compulsory. Thus, guaranteeing the required service quality, while also ensuring…

The number of smart devices inside the living environments grows more and more every day, and with it the need to interface them in order to share data and activate functions. Each day, new scenarios and new applications emerge to make our lives easier in many different contexts. The AAL SOCIALIZE project aims to create…

This paper presents a resource-friendly dynamic digital beamformer for a portable ultrasound imaging system based on a single field-programmable gate array (FPGA). The core of the ultrasound imaging system is a 128- channel receive beamformer with fully dynamic focusing embedded in a single FPGA chip, which operates at a frequency of 40 MHz. The Rx…

In order to increase the diagnosis accuracy of schizophrenia (SCZ) disease, it is essential to comprehensively employ complementary information from multiple types of data. It is well known that a network is a general method for analyzing relationships between patients, with its nodes representing patients and its edges showing relationships between them. In this study,…

Small animal modeling is an exciting research field where human pathogenic frameworks can be replicated in a controlled environment. Accurate Imaging is in high demand when modeling abnormalities and, magnetic resonance imaging plays a vital role due to its demonstrated lowest intrusion when compared with other imaging methods. However, the required high-resolution yields low-quality images…

Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…

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…

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…

As models based in artificial intelligence increase in sophistication, there is a higher demand for the integration of hardware components to heighten real-world implementations. Both facial feature tracking and shape-from-focus are known techniques in computer vision. However, the combination of these two elements, particularly in a cost-effective configuration, has not been extensively explored. In this…

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…

This study aims to examine the impact of Gen AI utilization on students’ visual literacy skills using a quantitative approach and data instruments in the form of post-test scores of the control class and experimental class which are analyzed to measure the effectiveness of GEN AI in improving students’ visual literacy skills at four universities.…

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…

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,…

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,…

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…

The study aimed to create a chronological overview of the royal development projects initiated by King Rama IX and to analyze their spatial distribution patterns. The research used a mixed-methods approach, combining quantitative and qualitative data collection methods such as obtaining data from relevant offices, internet research, and field observations. Data analysis involved descriptive statistics…

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 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…