2024 September - 73 articles
New technologies are tools that are present in daily life on a regular basis. In order to improve the didactic process, education must take into account these new technologies. In the field of physical education, the significance of these technologie...
In recent years, propelled by societal transformations and technological advancements, emerging technologies founded upon diverse disciplines such as financial and information technology have rapidly evolved. Identifying the trends associated with th...
This paper presents two innovative approaches: a synchronous multi-party dialogue system that engages in simultaneous interactions with multiple users, and multi-group simulations involving virtual user groups to evaluate the resilience of this syste...
As voice user interfaces (VUIs) rapidly transform the landscape of human–computer interaction, their potential to revolutionize user engagement is becoming increasingly evident. This paper aims to advance the field of human–computer inter...
Semantic ontologies have been widely utilized as crucial tools within natural language processing, underpinning applications such as knowledge extraction, question answering, machine translation, text comprehension, information retrieval, and text su...
This study examines the effectiveness of Student Evaluations of Teaching at the University of Peloponnese, which has systematically collected anonymous evaluations since 2015. The analysis focused on participation rates, average scores, and the corre...
This work proposes a novel method for the real-time identification and nonlinear control of a permanent-magnet synchronous motor (PMSM) based on a Physics-Informed Neural Network (PINN) and the exact feedback linearization approach. The proposed appr...
The COVID-19 pandemic has had a profound impact on global health, inspiring the widespread use of machine learning in combating the disease, particularly in prediction models. This study aimed to assess academic publications utilizing machine learnin...
Game reviews heavily influence public perception. User feedback is crucial for developers, offering valuable insights to enhance game quality. In this research, Metacritic game reviews for Elden Ring were analyzed for topic modeling using Latent Diri...
The increasing complexity of managing modern database systems, particularly in terms of optimizing query performance for large datasets, presents significant challenges that traditional methods often fail to address. This paper proposes a comprehensi...
Software security is an important topic that is gaining more and more attention due to the rising number of publicly known cybersecurity incidents. Previous research has shown that one way to address software security is by means of a serious game, t...
We introduce the Ising Network Opinion Formation (INOF) model and apply it to the analysis of networks of six Wikipedia language editions. In the model, Ising spins are placed at network nodes/articles and the steady-state opinion polarization of spi...
Over the past few years, safety and health have become major concerns in the warehouse and logistics sectors. Each year, warehouse fatalities, injuries, and accidents cause unrecoverable losses and huge financial costs. In spite of all the advancemen...
Managing modern, web-based, distributed applications effectively is a complex task that requires coordinating several aspects, including understanding the relationships among their components, the way they interact, the available hardware, the qualit...
Deep learning struggles with unsupervised tasks like community detection in networks. This work proposes the Enhanced Community Detection with Structural Information VGAE (VGAE-ECF) method, a method that enhances variational graph autoencoders (VGAEs...
Statistics modules are included in most university degrees, independent of the degree area, and this means that many students face these modules underprepared and struggle because of a lack of statistics knowledge. The Maths Support Centre (MSC) in t...
This study investigates the effectiveness of using augmented reality (AR), combined with guided inquiry and the Pecha Kucha technique, on students’ academic outcomes when learning meiosis. The main objective was to analyse whether this combinat...
Ontologies are essential for the management and integration of heterogeneous datasets. This paper presents OntoBuilder, an advanced tool that leverages the structural capabilities of semantic labeled property graphs (SLPGs) in strict alignment with s...
Cardiometabolic syndrome (CMS) is a growing concern in children and adolescents, marked by obesity, hypertension, insulin resistance, and dyslipidemia. This study aimed to predict CMS using machine learning based on data from the CASPIAN-V study, whi...
High-resolution imagery captured by drones can detect critical components on high-voltage transmission towers, providing inspection personnel with essential maintenance insights and improving the efficiency of power line inspections. The high-resolut...
Autonomous vehicles (AVs) face critical decisions in pedestrian interactions, necessitating ethical considerations such as minimizing harm and prioritizing human life. This study investigates machine learning models to predict human decision making i...
This paper proposes a novel method for diagnosing faults in oil-immersed transformers, leveraging feature extraction and an ensemble learning algorithm to enhance diagnostic accuracy. Initially, Dissolved Gas Analysis (DGA) data from transformers und...
Brain tumor detection and categorization of its subtypes are essential for early diagnosis and improving patient outcomes. This research presents a cutting-edge approach that employs advanced data augmentation and deep learning methodologies for brai...
Accurately predicting flight delays remains a significant challenge in the aviation industry due to the complexity and interconnectivity of its operations. The traditional prediction methods often rely on meteorological conditions, such as temperatur...
The growing industry and its complex and large information sets require Big Data (BD) technology and its open-source frameworks (Apache Hadoop) to (1) collect, (2) analyze, and (3) process the information. This information usually ranges in size from...
This paper presents a comparative analysis of deep learning techniques for anomaly detection and failure prediction. We explore various deep learning architectures on an IoT dataset, including recurrent neural networks (RNNs, LSTMs and GRUs), convolu...
As the field of artificial intelligence (AI) continues to evolve, its potential applications in various domains, including public policy development, have garnered significant interest. This research aims to investigate the role of AI in shaping publ...
Classic video compression methods usually suffer from long encode time and requires large memories, making it hard to deploy on edge devices; thus, video compressive sensing, which requires less resources during encoding, is receiving more attention....
Private Set Intersection (PSI) is a cryptographic method in secure multi-party computation that allows entities to identify common elements in their datasets without revealing their private data. Traditional approaches assume similar-sized datasets a...
Electric vehicles (EVs) are alternatives to traditional combustion engine-powered vehicles. This work focuses on a thermal management system for battery EVs using liquid cooling and a machine learning (ML) model to predict their thermal-related healt...
The adoption of telemedicine among the elderly is vital due to their unique healthcare needs and growing engagement with technology. This study explores the factors influencing their adoption behaviors, identifying both facilitating and inhibiting el...
This study investigates the effectiveness of Apple’s privacy labels, introduced in iOS 14, in promoting transparency around app data collection practices with respect to the GDPR. Specifically, we address two key research questions: (1) What sp...
The development of artificial intelligence (AI) and self-driving technology is expected to enhance intelligent transportation systems (ITSs) by improving road safety and mobility, increasing traffic flow, and reducing vehicle emissions in the near fu...
Bias is a disproportionate prejudice in favor of one side against another. Due to the success of transformer-based masked language models (MLMs) and their impact on many NLP tasks, a systematic evaluation of bias in these models is now needed more th...
In today’s competitive and environmentally conscious industries, the ability of organizations to adapt and respond is more important than ever. This study focuses on overcoming the obstacles faced by the Iranian automobile sector by highlightin...
The Kullback–Leibler (KL) divergence is a widely used measure for comparing probability distributions, but it faces limitations such as its unbounded nature and the lack of comparability between distributions with different quantum values (the...
In the financial sector, insurance companies generate large volumes of data, including policy transactions, customer interactions, and risk assessments. These historical data on established customers provide opportunities to enhance decision-making p...
This paper presents a novel waste-heat-powered, wireless, and battery-less Industrial Internet of Things (IIoT) device designed for predictive maintenance in Industry 4.0 environments. With a focus on real-time quality data, this device addresses the...
Peer-to-peer (P2P) lending has gained significant traction in the financial landscape, particularly in developing economies such as Indonesia, where access to traditional banking services remains a challenge for many. The aim of this study is to inve...
ChatGPT is a large language model trained on increasingly large datasets to perform diverse language-based tasks. It is capable of answering multiple-choice questions, such as those posed by diverse medical examinations. ChatGPT has been generating c...
In this paper, we undertake a critical analysis of how chatbots built on generative artificial intelligence impact assumptions underlying definitions of trust. We engage a particular definition of trust and the object-oriented model of trust that was...
In the original publication [...]
In natural language processing, word sense disambiguation (WSD) continues to be a major difficulty, especially for low-resource languages where linguistic variation and a lack of data make model training and evaluation more difficult. The goal of thi...
With quantum computers, the quantum resistance of cryptographic systems has gradually attracted attention. To overcome the shortcoming of existing identity-based encryption (IBE) schemes in resisting quantum attacks, we introduce an IBE scheme based...
Fire detection and extinguishing systems are critical for safeguarding lives and minimizing property damage. These systems are especially vital in combating forest fires. In recent years, several forest fires have set records for their size, duration...
Objective: Interstitial fibrosis/tubular atrophy (IFTA) is a common, irreversible, and progressive form of chronic kidney allograft injury, and it is considered a critical predictor of kidney allograft outcomes. The extent of IFTA is estimated throug...
The digital advancement of “as a service” models has led to the rapid emergence of mozbility as a service (MaaS) in transportation. This study aims to identify the motivational factors used among users of integrated mobility application s...
The wheel–rail contact force is a crucial indicator for ensuring the secure operation of a heavy-load train. However, obtaining the real-time wheel–rail contact force of a heavy-load train is a challenging task as, due to safety considera...
Incorporating knowledge graphs as auxiliary information to enhance recommendation systems can improve the representations learning of users and items. Recommendation methods based on knowledge graphs can introduce user–item interaction learning...
Cancer remains a major global health challenge, affecting diverse populations across various demographics. Integrating Artificial Intelligence (AI) into clinical settings to enhance disease outcome prediction presents notable challenges. This study a...
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