2024 October - 78 articles
In recent years, there has been growing interest in recommendation systems, which is matched by their widespread adoption across various sectors. This can be attributed to their effectiveness in reducing an avalanche of data into individualized infor...
The objective of this research was to design a method to assign topics to claims debunked by fact-checking agencies. During the fact-checking process, access to more structured knowledge is necessary; therefore, we aim to describe topics with semanti...
Mobile devices face significant security challenges due to the increasing proliferation of Android malware. This study introduces an innovative approach to Android malware detection, combining Support Vector Regression (SVR) and dynamic feature analy...
Self-healing systems have become essential in modern computing for ensuring continuous and secure operations while minimising downtime and maintenance costs. These systems autonomously detect, diagnose, and correct anomalies, with effective self-heal...
This paper presents a novel MRI super-resolution analysis model, MRISR. Through the utilization of generative adversarial networks for the estimation of degradation kernels and the injection of noise, we have constructed a comprehensive dataset of hi...
Over the past few decades, the field of fuzzy logic has evolved significantly, leading to the development of diverse techniques and applications. Fuzzy logic has been successfully combined with other artificial intelligence techniques such as artific...
Traffic sensors are vital to the development and operation of Intelligent Transportation Systems, providing essential data for traffic monitoring, management, and transportation infrastructure planning. However, optimizing the placement of these sens...
Brain tumor detection is crucial for effective treatment planning and improved patient outcomes. However, existing methods often face challenges, such as limited interpretability and class imbalance in medical-imaging data. This study presents a nove...
Great advances in stitching high-quality retinal images have been made in recent years. On the other hand, very few studies have been carried out on low-resolution retinal imaging. This work investigates the challenges of low-resolution retinal image...
The growing volume of information available to decision-makers makes it increasingly challenging to process all data during decision-making. As a result, a method for selecting only relevant information is highly desirable. Moreover, since the meanin...
When single-phase ground faults occur in distribution systems, the fault characteristics of zero-sequence current signals are not prominent. They are quickly submerged in noise, leading to difficulties in fault section location. This paper proposes a...
In modern industrial applications, production quality, system performance, process reliability, and safety have received considerable attention. This article proposes a dynamic event-triggered attack estimator for Markovian jump stochastic systems su...
The study of linguistics applied to computer science is a much-discussed topic today. In this area, particularly relevant is the software localization process describing the linguistic and cultural adaptation of software products to a specific market...
One of the most critical aspects in the seismic behavior or reinforced concrete (RC) structures pertains to beam–column joints. Modern seismic design codes dictate that, if failure is to occur, then this should be the ductile yielding of the be...
Four types of archaeogenetic data mining are used to investigate the origin of the Minoans and the Uralic peoples: (1) six SNP mutations related to eye, hair, and skin phenotypes; (2) whole-genome admixture analysis using the G25 system; (3) an analy...
Autonomous vehicles (AVs) represent a transformative innovation in transportation, promising enhanced safety, efficiency, and sustainability. Despite these promises, achieving robustness, reliability, and adherence to ethical standards in AV systems...
Blockchain consensus mechanisms play a critical role in ensuring the security, decentralization, and integrity of distributed networks. As blockchain technology expands beyond cryptocurrencies into broader applications such as supply chain management...
Academic research on the human element in phishing attacks is essential for developing effective prevention and detection strategies and guiding policymakers to protect individuals and organizations from cyber threats. This bibliometric study offers...
This study addresses the prevalent gap between structured models and informal architectural methodologies in software engineering. Recognizing the potential of informal architecture artifacts in analytical processes, we introduce a methodology that e...
Tumors in the brain can be life-threatening, making early and precise detection crucial for effective treatment and improved patient outcomes. Deep learning (DL) techniques have shown significant potential in automating the early diagnosis of brain t...
Human–robot collaboration (HRC) has become increasingly prevalent due to innovative advancements in the automation industry, especially in manufacturing setups. Although HRC increases productivity and efficacy, it exposes human workers to psych...
Support vector regression (SVR) is a powerful kernel-based regression prediction algorithm that performs excellently in various application scenarios. However, for real-world data, the general SVR often fails to achieve good predictive performance du...
This study investigates the integration of generative AI in higher education and the development of the SPARRO framework, a structured approach to improving human–AI interaction in academic settings. This ethnographic study explores the integra...
In recent decades, with the expansion of distributed energy generation technologies and the increasing need for more flexibility and efficiency in energy distribution systems, microgrids have been considered a promising innovative solution for local...
City planners are facing an emergency to develop, promote, and implement actions that allow the mobility needs of people and businesses in cities (and their surroundings) to be satisfied to assure a better quality of life. Among the different actions...
eHealth literacy (eHL) is directly linked to disease prevention, health promotion, and improved healthcare outcomes. The objectives of this study are to assess undergraduate university students’ knowledge and perceived skills of finding, apprai...
Agriculture stands as the cornerstone of Africa’s economy, supporting over 60% of the continent’s labor force. Despite its significance, the quality assessment of agricultural products remains a challenging task, particularly at a large s...
Interactive segmentation methods utilize user-provided positive and negative clicks to guide the model in accurately segmenting target objects. Compared to fully automatic medical image segmentation, these methods can achieve higher segmentation accu...
This study aims to develop a new theoretical framework from the perspective of the Technology Acceptance Model (TAM), incorporating flow theory, to explore the factors influencing behavioral intentions to participate in metaverse tourism. Using data...
The exponential growth of the Internet of Things (IoT) sector has resulted in a surge of interconnected gadgets in smart households, thus exposing them to new cyber-attack susceptibilities. This systematic literature review investigates machine learn...
The real-time data collected by wearable devices enables personalized health management and supports public health monitoring. However, sharing these data with third-party organizations introduces significant privacy risks. As a result, protecting an...
Object detection and action/gesture recognition have become imperative in security and surveillance fields, finding extensive applications in everyday life. Advancement in such technologies will help in furthering cybersecurity and extended reality s...
Public participation is a requirement for contemporary urban governance in China, especially in the protection planning of historic districts. In the rapid development stage, many historic districts have lost their functional positioning in cities an...
Cancer is a prominent global cause of mortality, primarily due to delayed detection leading to limited treatment options. Current screening methods are mostly invasive and involve complex lengthy processes with high costs. Moreover, each screening ty...
Graph neural networks (GNNs) are deep learning algorithms that process graph-structured data and are suitable for applications such as social networks, physical models, financial markets, and molecular predictions. Bibliometrics, a tool for tracking...
Automated Machine Learning (AutoML) enhances productivity and efficiency by automating the entire process of machine learning model development, from data preprocessing to model deployment. These tools are accessible to users with varying levels of e...
This study explores the process of creating avatars for Virtual Reality and metaverse environments using a variety of specialized applications, including VRChat, Ready Player Me, VRoidStudio, Mixamo, Convai, and MetaHuman. By evaluating these platfor...
Currently, as an increasing number of people have been addicted to using cellular phones, smartphone tenosynovitis has become common from long-term use of fingers for their operations. Hand exercise while playing video games, which is called exergame...
This paper addresses the challenge of objectively determining a website’s personality by developing a methodology based on automated quantitative analysis, thus avoiding the biases inherent in human surveys. Utilizing a database of 3000 website...
Accurately classifying road signs is crucial for autonomous driving due to the high stakes involved in ensuring safety and compliance. As Convolutional Neural Networks (CNNs) have largely replaced traditional Machine Learning models in this domain, t...
This study focuses on the development and evaluation of an AI-based digital therapeutic prototype for adolescent mental health management and disaster response. The system integrates real-time monitoring, AI-driven conversation analysis, personalized...
This review addresses the fragmented literature on administrative interventions for cybercrime mitigation within e-government services, which often prioritise technological aspects over a unified theoretical framework. By analysing 32 peer-reviewed a...
This study investigated the potential of the generative adversarial neural network (cGAN) image reconstruction in industrial electrical capacitance tomography. The image reconstruction quality was examined using image patterns typical for a two-phase...
An approach to approximate the 2D Gaussian filter for all possible kernel sizes based on the binary optimization technique is introduced. The approximate filter coefficients are designed as negative powers of two, allowing hardware implementation wit...
Effective fiscal control and monitoring of public management are critical for preventing and mitigating corruption, which in turn, enhances government performance and benefits citizens. Given the vast amounts of data involved in government operations...
Analyzing the uncertainty of outcomes based on estimates of the data’s membership degrees to fuzzy sets is essential for making decisions. These fuzzy sets are often designated by experts as strong fuzzy partitions of the data domain with trape...
Nowadays, with the common use of smartphones in daily lives, mobile applications have become popular around the world, which will lead to a rise in Flutter framework. Developed by Google, Flutter with Dart programming provides a cross-platform develo...
The article examines issues of web accessibility ecosystems for people with special needs. Methods, models, accessibility standards, and technologies related to the structure, design, and functionality of the web accessibility ecosystem are studied....
Detecting Traumatic Brain Injuries (TBI) through imaging remains challenging due to limited sensitivity in current methods. This study addresses the gap by proposing a novel approach integrating deep-learning algorithms and advanced image-fusion tech...
Pulmonary diseases, including pneumonia, represent a significant health challenge and are often diagnosed using X-rays. This study investigates the effectiveness of artificial intelligence (AI) in enhancing the diagnostic capabilities of X-ray imagin...
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