Journal of King Saud University - Computer and Information Sciences

Edge computing has gained widespread adoption for time-sensitive applications by offloading a portion of IoT system workloads from the cloud to edge nodes. However, the limited resources of IoT edge devices hinder service deployment, making auto-...

One of these challenges in the analysis of social networks is the problem of link prediction. The purpose of this problem is to find links that have not yet been observed, but may exist in the future. There are many solutions for link prediction ...

Fake reviews in e-commerce can lead to customer deception and financial losses. Despite the importance of fake reviews detection, studies for Arabic language are scarce due to the lack of comprehensive datasets. This study addresses this gap by ...

• Constructing the first Arabic dataset for fake reviews detection based on gold-standard.
• Conducting single-domain, multi-domain, and cross-domain experiments.
• Introducing a cascading approach for results optimization.

The existing methods for detecting surface defects in electrolytic capacitors are typically based on conventional machine vision, with limited feature extraction capabilities, poor versatility, slow detection speed, and the inability to achieve ...

Recognizing speed limit information is crucial for advanced driver assistance systems (ADAS) as it directly affects the safety planning and decision-making process of intelligent driving systems. However, traditional image recognition-based ...

Existing AI-based medicine prediction systems require substantial training time, computing resources, and extensive labeled data, yet they often lack scalability. To bridge these gaps, this study introduces a novel MED-Prompt framework that ...

In the era of internet-based data, recommendation systems are crucial for helping users access personalized content and facilitating business promotion and sales. Recommendation systems based on social relationships have gained popularity due to ...

The electric meter box is a terminal device with a large number in the power grid. It may cause electrical hazards and property loss if damaged. Inspection of electricity meter boxes still relies on manual inspection with low efficiency and low ...

As the IoT devices are highly ubiquitous and connected, their computational tasks can be processed on the Multi-access edge computing (MEC) servers because of the IoT devices’ limited battery, computing power and storage capacities. Due to the ...

Millions of people who have trouble hearing rely heavily on sign language as their primary means of communication. As a form of visual language, sign language is primarily used as features by the deaf and hard of hearing to communicate with one ...

Sentiment analysis, a subtask of affective computing, endows machines with the ability to sense and comprehend emotions. Recently, research attention has shifted from traditional isolated modality to ubiquitous multi-modalities, requiring to ...

Extracting high-quality correspondences is a critical challenge in current feature-learning based point cloud registration methods. Recently, coarse-to-fine network structures have shown great potential in addressing this challenge. Inspired by ...

Alzheimer’s Disease (AD) is a worldwide concern impacting millions of people, with no effective treatment known to date. Unlike cancer, which has seen improvement in preventing its progression, early detection remains critical in managing the ...

It is a challenging task to devise an effective model for object segmentation considering numerous classes because different classes might have different features and different backgrounds. We propose a unique segmentation and classification ...

Automatic Speech Recognition (ASR) has standard rules which must be followed and considered carefully. Some difficulties that lead to less ASR performance is variations in pronunciation and small words misrecognition. Arabic ASR faces some ...

Private information retrieval (PIR) enables a client to search data from a single (or multiple) untrusted server, without revealing which entry was queried. PIR can be divided into two categories: information-theoretic PIR (IT-PIR) and ...

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Traceability links between issues and commits (issue-commit links recovery (ILR)) play a significant role in software maintenance tasks by enhancing developers’ observability in practice. Recent advancements in large language models, particularly ...

Several studies were conducted to demonstrate the application of Process Mining (PM) techniques to Ethereum-compatible application event data. However, the availability of event data is constrained by the application’s process awareness, which is ...

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Ensuring robust security in the Internet of Things (IoT) landscape is of paramount importance. This research article presents a novel approach to enhance IoT security by leveraging collaborative threat intelligence and integrating blockchain ...

Machine learning contributes in improving the accuracy of melanoma detection. There are extensive studies in classic and deep learning-based approaches for melanoma detection in the literature. Still, they are not accurate or require high ...

DeepDefend is an advanced framework for real-time detection and prevention of DDoS attacks in cloud environments. It employs deep learning techniques, notably CNN-LSTM-Transformer networks, to predict network traffic entropy and detect potential ...

With the development of smart agricultural Internet of Things (IoT) projects, the need for extensive collaboration among agricultural devices from different domains has surged, necessitating the authentication of device identities for secure ...

Retrieving relevant source code from large repositories is a significant and ongoing challenge in the field of software engineering, primarily due to the vast and ever-expanding amount of available code. Existing deep learning methods, although ...

Collaborative filtering recommender systems type have been increasingly used in e-commerce sites both to facilitate users' decision-making and increase sales. On the one hand, the open and interactive nature of recommender systems makes them ...

Multi-step stock index forecasting is vital in finance for informed decision-making. Current forecasting methods for this task frequently produce unsatisfactory results due to the inherent randomness and instability of the data, thereby ...

Crowd localization can provide the positions of individuals and the total number of people, which has great application value for security monitoring and public management, meanwhile it meets the challenges of lighting, occlusion and perspective ...

Underwater object detection has been shown to exhibit significant potential for exploring underwater environments. However, underwater datasets often suffer from degeneration due to uneven underwater light distribution, complex underwater ...

Arabic hateful speech recognition has long been a major area of focus in Natural Language Processing (NLP) research. In light of recent advancements in transformer models and deep learning, researchers are now turning to transfer learning ...

Amyotrophic Lateral Sclerosis (ALS) is a rare disease and also known as Lou Gehrig’s disease. In addition, this disease is characterized by a progression in the nerve cells of the brain and spinal cord. These neuron cells control most of the ...

The proliferation of blockchain technology has resulted in diverse token standards, posing challenges for compatibility, security, and performance in existing cross-chain bridges. This paper introduces a novel framework capable of concurrently ...