2025 February - 31 articles
The rising prevalence of social media turns them into huge, rich repositories of human emotions. Understanding and categorizing human emotion from social media content is of fundamental importance for many reasons, such as improvement of user experie...
The rapid integration of Machine Learning (ML) in organizational practices has driven demand for substantial computational resources, incurring both high economic costs and environmental impact, particularly from energy consumption. This challenge is...
Previously, it was suggested that the “persona-driven” approach can contribute to producing sufficiently diverse synthetic training data for Large Language Models (LLMs) that are currently about to run out of real natural language texts....
The topic of this study is the testing of the robustness of machine learning (ML) and neural network (NN) models with a new idea based on corrupted data. Typically, ML and NN classifiers are trained on real feature data; however, a portion of the fea...
The convergence of cloud computing and the Industrial Internet of Things (IIoT) has significantly transformed industrial operations, enabling intelligent, scalable, and efficient systems. This survey provides a comprehensive analysis of the role clou...
The decline in oral health commonly occurs as a natural consequence of aging or due to various pathological factors. Tooth loss, which diminishes masticatory ability, has been associated with negative impacts on cognitive function. This observational...
This article addresses the impact of generative artificial intelligence on the creation of composite sketches for police investigations. The automation of this task, traditionally performed through artistic methods or image composition, has become a...
As Large Language Models (LLMs) continue to advance, their capabilities in code clone detection have garnered significant attention. While much research has assessed LLM performance on human-generated code, the proliferation of LLM-generated code rai...
Artificial intelligence (AI) affects many aspects of modern life, and most predictions are that the impact of AI on business and society will only increase. In the marketing function of today’s leading businesses, two main types of AI can be di...
Convolutional Neural Networks (CNNs) have proven to be very effective in image classification due to their status as a powerful feature learning algorithm. Traditional approaches have considered the problem of multiclass classification, where the goa...
Finding a template location in a query image is a fundamental problem in many computer vision applications, such as localization of known objects, image registration, image matching, and object tracking. Currently available methods fail when insuffic...
The COVID-19 pandemic has generated a vast corpus of online conversations regarding vaccines, predominantly on social media platforms like X (formerly known as Twitter). However, analyzing sentiment in Arabic text is challenging due to the diverse di...
Integrating deep learning into microbiological and cell analysis from microscopic image samples has gained significant attention in recent years, driven by the rise of novel medical technologies and pressing global health challenges. Numerous methods...
The importance of enhancing the accuracy of time-series forecasting using artificial intelligence tools is increasingly critical in light of the rapid advancements in modern technologies, particularly deep learning and neural networks. These approach...
Human cultural complexity did not arise in a vacuum. This study employs agent-based modeling (ABM) and ecological modeling perspectives, combined with reinforcement-learning techniques, to investigate whether conditions that allowed for the lower spo...
Stance detection for low-resource languages, such as the Kuwaiti dialect, poses a significant challenge in natural language processing (NLP) due to the scarcity of annotated datasets and specialized tools. This study addresses these limitations by ev...
We propose dependency reduction techniques for the performance enhancement of the Hyperledger Fabric blockchain. A dependency hazard may result from the parallelism in Hyperledger Fabric, which executes multiple transactions simultaneously in a singl...
Digital transformation (DT) has become an imperative for companies seeking to evolve in a constantly changing industrial ecosystem, driven by the continual development and application of innovative digital technologies. Nevertheless, the success rate...
The influence of scientific papers is measured by their citations. Although predicting the papers’ citation impact based on non-content factors has garnered extensive attention, the influence of such factors is rarely compared. In this article,...
For the past few decades, brain tumors have had a substantial influence on human life, and pose severe health risks if not treated and diagnosed in the early stages. Brain tumor problems are highly diverse and vary extensively in terms of size, type,...
Multi-class object detectors often suffer from the class imbalance issue, where substantial model performance discrepancies exist between classes. Generative adversarial networks (GANs), an emerging deep learning research topic, are able to learn fro...
Android malware detection using artificial intelligence today is a mandatory tool to prevent cyber attacks. To address this problem in this paper the proposed methodology consists of the application of genetic programming symbolic classifier (GPSC) t...
Recent studies have highlighted the potential of Large Language Models (LLMs) to become experts in specific areas of knowledge through the utilization of techniques that enhance their context. Nevertheless, an interesting and underexplored applicatio...
Pneumonia remains a significant cause of morbidity and mortality among pediatric patients worldwide. Accurate and timely diagnosis is crucial for effective treatment and improved patient outcomes. Traditionally, pneumonia diagnosis has relied on a co...
The rapid growth of Internet banking has necessitated advanced systems for secure, real-time decision making. This paper introduces BankNet, a predictive analytics framework integrating big data tools and a BiLSTM neural network to deliver high-accur...
Analysts in Security Operations Centers (SOCs) are often occupied with time-consuming investigations of alerts from Network Intrusion Detection Systems (NIDSs). Many NIDS rules lack clear explanations and associations with attack techniques, complica...
In healthcare applications, often it is not possible to record sufficient data as required for deep learning or data-driven classification and feature detection systems due to the patient condition, various clinical or experimental limitations, or ti...
Forecasting of time series data presents some challenges because the data’s nature is complex and therefore difficult to accurately forecast. This study presents the design and development of a novel forecasting system that integrates efficient...
Understanding public sentiment on health and fitness is essential for addressing regional health challenges in Saudi Arabia. This research employs sentiment analysis to assess fitness awareness by analyzing content from the X platform (formerly Twitt...
The Internet of Things (IoT) represents a transformative technology that allows interconnected devices to exchange data over the Internet, enabling automation and real-time decision making in a variety of areas. A key aspect of the success of the IoT...
Synthetic Data Generation (SDG) is a promising solution for healthcare, offering the potential to generate synthetic patient data closely resembling real-world data while preserving privacy. However, data scarcity and heterogeneity, particularly in u...
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