2025 May - 47 articles
Deep learning models offer innovative solutions for cervical cancer screening in vulnerable regions such as the Brazilian Amazon. These tools are particularly relevant in areas with limited access to healthcare services, where the high prevalence of...
Dyscalculia is a specific learning disorder that affects numerical comprehension, arithmetic reasoning, and problem-solving skills, significantly impacting academic performance and daily life activities. Traditional teaching methods often fail to add...
Fiber-flaw detection on pill surfaces is a critical yet challenging task in industrial pharmacy due to diverse defect characteristics. To overcome the limitations of traditional methods in accuracy and real-time performance, this study introduces SA-...
Automating agricultural processes holds significant promise for enhancing efficiency and sustainability in various farming practices. This paper contributes to the automation of agricultural processes by providing a dedicated mushroom detection datas...
Plant-parasiticnematodes represent a significant biosecurity threat in cross-border plant quarantine, necessitating precise identification for effective border control. While DL models have demonstrated success in nematode image classification based...
Timely diagnosis of soybean diseases is essential to protect yields and limit global economic loss, yet current deep learning approaches suffer from small, imbalanced datasets, single-organ focus, and limited interpretability. We propose MaxViT-XSLD...
In the face of accelerating digitalization and growing systemic vulnerabilities, the ability to make accurate, real-time economic decisions has become a critical capability for financial and institutional stability. This study investigates how edge c...
To address critical challenges in tiny object detection within remote sensing imagery, including resolution–semantic imbalance, inefficient feature fusion, and insufficient localization accuracy, this study proposes Hierarchical Feature Compens...
This review paper presents a comprehensive analysis of the evolving landscape of data exchange, with a particular focus on the transformative role of emerging technologies such as blockchain, field-programmable gate arrays (FPGAs), and artificial int...
Artificial Intelligence is a disruptive technology that is revolutionizing the accounting sector, e.g., by reducing costs, detecting fraud, and generating reports. However, the manual maintenance of booking ledgers remains a significant challenge, pa...
Education nowadays requires a certain variety of resources that allow for the acquisition of 21st-century skills, including computational thinking. Educational robotics emerges as a digital resource that supports the development of these skills in bo...
This systematic review provides an analysis of information gathered from 33 chosen publications during the past decade. The analysis reveals the primary methodologies applied and identifies the visitor behaviors that enable personalized content deliv...
This study analyzes global energy trends from January 1973 to November 2022, using the “World Energy Statistics” dataset from Kaggle, which includes data on the production, consumption, import, and export of fossil fuels, nuclear energy,...
The increasing complexity of algorithms in embedded applications has amplified the demand for high-performance computing. Heterogeneous embedded systems, particularly FPGA-based systems-on-chip (SoCs), enhance execution speed by integrating hardware...
Industry 4.0 has revolutionized the way companies manufacture, improve, and distribute their products through the use of new technologies, such as artificial intelligence, robotics, and machine learning. Autonomous Mobile Robots (AMRs), especially, h...
Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, requiring early detection for effective treatment. Deep learning models have been widely used for automated DR classification, with Convolutional Neural Networks (CNNs) bein...
Traffic accident prediction is essential for improving road safety and optimizing intelligent transportation systems. However, deep learning models often struggle with distribution shifts and class imbalance, leading to degraded performance in real-w...
This systematic review and meta-analysis investigates the impact of artificial intelligence (AI) tools, including ChatGPT 3.5 and GitHub Copilot, on learning outcomes in computer programming courses. A total of 35 controlled studies published between...
Driver distraction can have severe safety consequences, particularly in public transportation. This paper presents a novel approach for detecting bus driver actions, such as mobile phone usage and interactions with passengers, using Kolmogorov–Arnold...
Despite the growing adoption of Property Graph Databases, like Neo4j, interacting with them remains difficult for non-technical users due to the reliance on formal query languages. Natural Language Interfaces (NLIs) address this by translating natura...
Concrete surface crack detection plays a crucial role in infrastructure maintenance and safety. Deep learning-based methods have shown great potential in this task. However, under real-world conditions such as poor image quality, environmental interf...
This work presents two variants of an odd–even sort algorithm that are implemented in a dataflow-based polymorphic computing architecture. The two odd–even sort algorithms are the “fully unrolled” variant and the “compac...
The quest for effective pedagogical practices in mathematics education has increasingly highlighted the flipped classroom model. This model has been shown to be particularly successful in higher education settings within developed countries, where re...
The validation of security protocols remains a complex and critical task in the cybersecurity landscape, often relying on labor-intensive testing or formal verification techniques with limited scalability. In this paper, we explore property-based tes...
Despite significant advancements in fingerprint-based authentication, existing models still suffer from challenges such as high false acceptance and rejection rates, computational inefficiency, and vulnerability to spoofing attacks. Addressing these...
Background/Objectives: Hospital readmissions within 30 days are a major challenge in general internal medicine (GIM), impacting patient outcomes and healthcare costs. This study aimed to develop and evaluate machine learning (ML) models for predictin...
In the past years, the education sector has suffered from repeated epidemics and their spread, and COVID-19 is a good example of this. Therefore, the search for other educational methods has become necessary. Therefore, e-learning is one of the best...
This research explores the improvement of tsunami occurrence forecasting with machine learning predictive models using earthquake-related data analytics. The primary goal is to develop a predictive framework that integrates a wide range of data sourc...
In 5G wireless communication, network slicing is considered one of the key network elements, which aims to provide services with high availability, low latency, maximizing data throughput, and ultra-reliability and save network resources. Due to the...
Cyberhate presents a multifaceted, context-sensitive challenge that existing detection methods often struggle to tackle effectively. Large language models (LLMs) exhibit considerable potential for improving cyberhate detection due to their advanced c...
Mango productivity suffers greatly from leaf diseases, leading to economic and food security issues. Current visual inspection methods are slow and subjective. Previous Deep-Learning (DL) solutions have shown promise but suffer from imbalanced datase...
This paper introduces a novel framework for addressing domain adaptation challenges in large language models (LLMs), emphasising privacy-preserving synthetic data generation and efficient fine-tuning. The proposed framework employs a multi-stage appr...
A key goal of inclusive education is to enhance health literacy skills, empowering students with intellectual disabilities (IDs) to access critical information needed to navigate everyday challenges. The COVID-19 pandemic, for example, highlighted un...
The structure and memory organization of graphics processor units (GPUs) manufactured by NVIDIA and the use of CUDA programming technology to solve computational fluid dynamics (CFD) problems is reviewed and discussed. The potential of using a genera...
As mentioned by the Food and Agriculture Organization of the United Nations, agriculture has a primary role in food security. Given the advantageous conditions that Colombia has as a biodiverse country, creating and implementing sustainable and compr...
This study conducts an in-depth investigation of the performance of six transformer models using 12 different datasets—10 with three classes and two with two classes—on sentiment classification. We use these six models and generate all co...
The mathematical model for photometric stereo makes several restricting assumptions, which are often not fulfilled in real-life applications. Specifically, an object surface does not always satisfies Lambert’s cosine law, leading to reflection...
Modern linguistic steganography faces the fundamental challenge of balancing embedding capacity with detection resistance, particularly against advanced AI-based steganalysis. This paper presents DeepStego, a novel steganographic system leveraging GP...
The growing adoption of supercomputers across various scientific disciplines, particularly by researchers without a background in computer science, has intensified the demand for parallel applications. These applications are typically developed using...
X-ray imaging, as a technique of non-destructive testing, has demonstrated considerable promise in COVID-19 diagnosis, particularly if supplemented with artificial intelligence (AI). Both radiologic technologists and AI researchers have raised the al...
This paper examines the ability of ChatGPT to generate synthetic comment datasets that mimic those produced by humans. To this end, a collection of datasets containing human comments, freely available in the Kaggle repository, was compared to comment...
Cross parity codes are mostly used as 2-dimensional codes, and sometimes as 3-dimensional codes. We argue that higher dimensions can help to reduce the number of parity bits, and thus deserve further investigation. As a start, we investigate parities...
The increase in malicious cyber activities has generated the need to produce effective tools for the field of digital forensics and incident response. Artificial intelligence (AI) and its fields, specifically machine learning (ML) and deep learning (...
Modern 5G network slicing centers on the precise design of virtual, independent networks operating over a shared physical infrastructure, each configured to meet specific service requirements. This approach plays a vital role in enabling highly custo...
This paper presents strategies for effectively integrating AI tools into programming education and provides recommendations for enhancing student learning outcomes through intelligent educational systems. Learning computer programming is a cognitivel...
The advancement of biomedical research depends on efficient data sharing, integration, and annotation to ensure reproducibility, accessibility, and cross-disciplinary collaboration. International collaborative research is crucial for advancing biomed...
This study investigated how undergraduate students collaborated when working with ChatGPT and what teamwork approaches they used, focusing on students’ preferences, conflict resolution, reliance on AI-generated content, and perceived learning o...
