Journal of King Saud University-Computer and Information Sciences最新文献

{"title":"Flow prediction of mountain cities arterial road network for real-time regulation","authors":"Xiaoyu Cai ,&nbsp;Zimu Li ,&nbsp;Jiajia Dai ,&nbsp;Liang Lv ,&nbsp;Bo Peng","doi":"10.1016/j.jksuci.2024.102190","DOIUrl":"10.1016/j.jksuci.2024.102190","url":null,"abstract":"<div><div>This study aims to enhance the understanding of vehicle path selection behavior within arterial road networks by investigating the influencing factors and analyzing spatial and temporal traffic flow distributions. Using radio frequency identification (RFID) travel data, key factors such as travel duration, route familiarity, route length, expressway ratio, arterial road ratio, and ramp ratio were identified. We then proposed an origin–destination path acquisition method and developed a route-selection prediction model based on a multinomial logit model with sample weights. Additionally, the study linked the traffic control scheme with travel time using the Bureau of Public Roads function—a model that illustrates the relationship between network-wide travel time and traffic demand—and developed an arterial road network traffic forecasting model. Verification showed that the prediction accuracy of the improved multinomial logit model increased from 92.55 % to 97.87 %. Furthermore, reducing the green time ratio for multilane merging from 0.75 to 0.5 significantly decreased the likelihood of vehicles choosing this route and reduced the number of vehicles passing through the ramp. The flow prediction model achieved a 97.9 % accuracy, accurately reflecting actual volume changes and ensuring smooth operation of the main airport road. This provides a strong foundation for developing effective traffic control plans.</div></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102190"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DeepExtract: Semantic-driven extractive text summarization framework using LLMs and hierarchical positional encoding","authors":"Aytuğ Onan ,&nbsp;Hesham A. Alhumyani","doi":"10.1016/j.jksuci.2024.102178","DOIUrl":"10.1016/j.jksuci.2024.102178","url":null,"abstract":"<div><p>In the age of information overload, the ability to distill essential content from extensive texts is invaluable. DeepExtract introduces an advanced framework for extractive summarization, utilizing the groundbreaking capabilities of GPT-4 along with innovative hierarchical positional encoding to redefine information extraction. This manuscript details the development of DeepExtract, which integrates semantic-driven techniques to analyze and summarize complex documents effectively. The framework is structured around a novel hierarchical tree construction that categorizes sentences and sections not just by their physical placement within a text, but by their contextual and thematic significance, leveraging dynamic embeddings generated by GPT-4. We introduce a multi-faceted scoring system that evaluates sentences based on coherence, relevance, and novelty, ensuring that summaries are not only concise but rich with essential content. Further, DeepExtract employs optimized semantic clustering to group thematic elements, which enhances the representativeness of the summaries. This paper demonstrates through comprehensive evaluations that DeepExtract significantly outperforms existing extractive summarization models in terms of accuracy and efficiency, making it a potent tool for academic, professional, and general use. We conclude with a discussion on the practical applications of DeepExtract in various domains, highlighting its adaptability and potential in navigating the vast expanses of digital text.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102178"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002672/pdfft?md5=ee7790d3716e8b2a6454863f15695239&pid=1-s2.0-S1319157824002672-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142098684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing a multimodal dataset for Arabic Sign Language (ArSL) production","authors":"Samah Abbas ,&nbsp;Dimah Alahmadi ,&nbsp;Hassanin Al-Barhamtoshy","doi":"10.1016/j.jksuci.2024.102165","DOIUrl":"10.1016/j.jksuci.2024.102165","url":null,"abstract":"<div><p>This paper addresses the potential of Arabic Sign Language (ArSL) recognition systems to facilitate direct communication and enhance social engagement between deaf and non-deaf. Specifically, we focus on the domain of religion to address the lack of accessible religious content for the deaf community. We propose a multimodal architecture framework and develop a novel dataset for ArSL production. The dataset comprises 1950 audio signals with corresponding 131 texts, including words and phrases, and 262 ArSL videos. These videos were recorded by two expert signers and annotated using ELAN based on gloss representation. To evaluate ArSL videos, we employ Cosine similarities and mode distances based on MobileNetV2 and Euclidean distance based on MediaPipe. Additionally, we implement Jac card Similarity to evaluate the gloss representation, resulting in an overall similarity score of 85% between the glosses of the two ArSL videos. The evaluation highlights the complexity of creating an ArSL video corpus and reveals slight differences between the two videos. The findings emphasize the need for careful annotation and representation of ArSL videos to ensure accurate recognition and understanding. Overall, it contributes to bridging the gap in accessible religious content for deaf community by developing a multimodal framework and a comprehensive ArSL dataset.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102165"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002544/pdfft?md5=301cc3d87bf22d8e207fb35edd191aea&pid=1-s2.0-S1319157824002544-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A formal specification language and automatic modeling method of asset securitization contract","authors":"Yang Li ,&nbsp;Kai Hu ,&nbsp;Jie Li ,&nbsp;Kaixiang Lu ,&nbsp;Yuan Ai","doi":"10.1016/j.jksuci.2024.102163","DOIUrl":"10.1016/j.jksuci.2024.102163","url":null,"abstract":"<div><p>Asset securitization is an important financial derivative involving complicated asset transfer operations. Therefore, digitizing traditional asset securitization contracts will improve efficiency and facilitate reliability verification. Furthermore, accurate and verifiable requirement description is essential for collaborative development between financial professionals and software engineers. A domain specific language for writing asset securitization contract has been proposed. This solves the problem of difficulty for financial professionals to directly write smart contract by simplifying writing rules. However, due to existing design of the language focused on some simple scenarios, it is insufficient and informal to describe various detailed scenarios. What is more, there are still many reliability issues, such as verifying the correctness of the logical properties of the contract and ensuring the consistency between the contract text and the contract code, within the language in the generation and execution of smart contracts. To overcome the challenges stated above, we extend, simplify and innovate the syntax subset of the domain specific language and name it AS-SC (Asset Securitization – Smart Contract), which can be used by financial professionals to accurately describe requirements. Besides, because formal methods are math-based techniques that describe system properties and can generate programs in a more formal and reliable manner, we propose a semantic consistent code conversion method, named AS2EB, for converting from AS-SC to Event-B, a common and useful formal language. AS2EB method can be used by software engineers to verify requirements. The combination of AS-SC and AS2EB ensures consistency and reliability of the requirements, and reduces the cost of repeated communications and later testing. Taking the credit asset securitization contract as case study, the feasibility and rationality of AS-SC and AS2EB are validated. In addition, by carrying out experiments on three randomly selected real cases in different classic scenarios, we show high-efficiency and reliability of AS2EB method.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102163"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002520/pdfft?md5=9af49e4b57c4f2d8d674b3287497b478&pid=1-s2.0-S1319157824002520-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142088599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective optimization in order to allocate computing and telecommunication resources based on non-orthogonal access, participation of cloud server and edge server in 5G networks","authors":"Liying Zhao ,&nbsp;Chao Liu ,&nbsp;Entie Qi ,&nbsp;Sinan Shi","doi":"10.1016/j.jksuci.2024.102187","DOIUrl":"10.1016/j.jksuci.2024.102187","url":null,"abstract":"<div><div>Mobile edge processing is a cutting-edge technique that addresses the limitations of mobile devices by enabling users to offload computational tasks to edge servers, rather than relying on distant cloud servers. This approach significantly reduces the latency associated with cloud processing, thereby enhancing the quality of service. In this paper, we propose a system in which a cellular network, comprising multiple users, interacts with both cloud and edge servers to process service requests. The system assumes non-orthogonal multiple access (NOMA) for user access to the radio spectrum. We model the interactions between users and servers using queuing theory, aiming to minimize the total energy consumption of users, service delivery time, and overall network operation costs. The problem is mathematically formulated as a multi-objective, bounded non-convex optimization problem. The Structural Correspondence Analysis (SCA) method is employed to obtain the global optimal solution. Simulation results demonstrate that the proposed model reduces energy consumption, delay, and network costs by approximately 50%, under the given assumptions.</div></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102187"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and FPGA implementation of nested grid multi-scroll chaotic system","authors":"Guofeng Yu,&nbsp;Chunlei Fan,&nbsp;Jiale Xi,&nbsp;Chengbin Xu","doi":"10.1016/j.jksuci.2024.102186","DOIUrl":"10.1016/j.jksuci.2024.102186","url":null,"abstract":"<div><p>Conventional multi-scroll chaotic systems are often constrained by the number of attractors and the complexity of generation, making it challenging to meet the increasing demands of communication and computation. This paper revolves around the modified Chua’s system. By modifying its differential equation and introducing traditional nonlinear functions, such as the step function sequence and sawtooth function sequence. A nested grid multi-scroll chaotic system (NGMSCS) can be established, capable of generating nested grid multi-scroll attractors. In contrast to conventional grid multi-scroll chaotic attractors, scroll-like phenomena can be initiated outside the grid structure, thereby revealing more complex dynamic behavior and topological features. Through the theoretical design and analysis of the equilibrium point of the system and its stability, the number of saddle-focused equilibrium points of index 2 is further expanded, which can generate (2 N+2) × M attractors, and the formation mechanism is elaborated and verified in detail. In addition, the generation of an arbitrary number of equilibrium points in the <em>y</em>-direction is achieved by transforming the <em>x</em> and <em>y</em> variables, which can generate M×(2 N+2) attractors, increasing the complexity of the system. The system’s dynamical properties are discussed in depth via time series plots, Lyapunov exponents, Poincaré cross sections, 0–1 tests, bifurcation diagrams, and attraction basins. The existence of attractors is confirmed through numerical simulations and FPGA-based hardware experiments.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102186"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002751/pdfft?md5=5a97268ac1950c4cb177bec835b9c871&pid=1-s2.0-S1319157824002751-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards the development of believable agents: Adopting neural architectures and adaptive neuro-fuzzy inference system via playback of human traces","authors":"Naveed Anwer Butt ,&nbsp;Mian Muhammad Awais ,&nbsp;Samra Shahzadi ,&nbsp;Tai-hoon Kim ,&nbsp;Imran Ashraf","doi":"10.1016/j.jksuci.2024.102182","DOIUrl":"10.1016/j.jksuci.2024.102182","url":null,"abstract":"<div><p>Artificial intelligence (AI) research on video games primarily focused on the imitation of human-like behavior during the past few years. Moreover, to increase the perceived worth of amusement and gratification, there is an enormous rise in the demand for intelligent agents that can imitate human players and video game characters. However, the agents developed using the majority of current approaches are perceived as rather more mechanical, which leads to frustration, and more importantly, failure in engagement. On that account, this study proposes an imitation learning framework to generate human-like behavior for more precise and accurate reproduction. To build a computational model, two learning paradigms are explored, artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS). This study utilized several variations of ANN, including feed-forward, recurrent, extreme learning machines, and regressions, to simulate human player behavior. Furthermore, to find the ideal ANFIS, grid partitioning, subtractive clustering, and fuzzy c-means clustering are used for training. The results demonstrate that ANFIS hybrid intelligence systems trained with subtractive clustering are overall best with an average accuracy of 95%, followed by fuzzy c-means with an average accuracy of 87%. Also, the believability of the obtained AI agents is tested using two statistical methods, i.e., the Mann–Whitney U test and the cosine similarity analysis. Both methods validate that the observed behavior has been reproduced with high accuracy.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102182"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002714/pdfft?md5=542b4e8449657f4dbd195276e5fb54c1&pid=1-s2.0-S1319157824002714-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A low-time-consumption image encryption combining 2D parametric Pascal matrix chaotic system and elementary operation","authors":"Jun Lu ,&nbsp;Jiaxin Zhang ,&nbsp;Dezhi An ,&nbsp;Dawei Hao ,&nbsp;Xiaokai Ren ,&nbsp;Ruoyu Zhao","doi":"10.1016/j.jksuci.2024.102169","DOIUrl":"10.1016/j.jksuci.2024.102169","url":null,"abstract":"<div><p>The rapid development of the big data era has resulted in traditional image encryption algorithms consuming more time in handling the huge amount of data. The consumption of time cost needs to be reduced while ensuring the security of encryption algorithms. With this in mind, the paper proposes a low-time-consumption image encryption (LTC-IE) combining 2D parametric Pascal matrix chaotic system (2D-PPMCS) and elementary operation. First, the 2D-PPMCS with robustness and complex chaotic behavior is adopted. Second, the SHA-256 hash values are applied to the chaotic sequences generated by 2D-PPMCS, which are processed and applied to image permutation and diffusion encryption. In the permutation stage, the pixel matrix is permutation encrypted based on the permutation matrix generated from the chaotic sequences. For diffusion encryption, elementary operations are utilized to construct the model, such as exclusive or, modulo, and arithmetic operations (addition, subtraction, multiplication, and division). After analyzing the security experiments, the LTC-IE algorithm ensures security and robustness while reducing the time cost consumption.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102169"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002581/pdfft?md5=db7fa2d27baba2dde9365c9407528c9f&pid=1-s2.0-S1319157824002581-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142098681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SARD: Fake news detection based on CLIP contrastive learning and multimodal semantic alignment","authors":"Facheng Yan,&nbsp;Mingshu Zhang,&nbsp;Bin Wei,&nbsp;Kelan Ren,&nbsp;Wen Jiang","doi":"10.1016/j.jksuci.2024.102160","DOIUrl":"10.1016/j.jksuci.2024.102160","url":null,"abstract":"<div><p>The automatic detection of multimodal fake news can be used to effectively identify potential risks in cyberspace. Most of the existing multimodal fake news detection methods focus on fully exploiting textual and visual features in news content, thus neglecting the full utilization of news social context features that play an important role in improving fake news detection. To this end, we propose a new fake news detection method based on CLIP contrastive learning and multimodal semantic alignment (SARD). SARD leverages cutting-edge multimodal learning techniques, such as CLIP, and robust cross-modal contrastive learning methods to integrate features of news-oriented heterogeneous information networks (N-HIN) with multi-level textual and visual features into a unified framework for the first time. This framework not only achieves cross-modal alignment between deep textual and visual features but also considers cross-modal associations and semantic alignments across different modalities. Furthermore, SARD enhances fake news detection by aligning semantic features between news content and N-HIN features, an aspect largely overlooked by existing methods. We test and evaluate SARD on three real-world datasets. Experimental results demonstrate that SARD significantly outperforms the twelve state-of-the-art competitors in fake news detection, with an average improvement of 2.89% in Mac.F1 score and 2.13% in accuracy compared to the leading baseline models across three datasets.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102160"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002490/pdfft?md5=497eb195281148df13643994f201fe62&pid=1-s2.0-S1319157824002490-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142076508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unsupervised selective labeling for semi-supervised industrial defect detection","authors":"Jian Ge ,&nbsp;Qin Qin ,&nbsp;Shaojing Song ,&nbsp;Jinhua Jiang ,&nbsp;Zhiwei Shen","doi":"10.1016/j.jksuci.2024.102179","DOIUrl":"10.1016/j.jksuci.2024.102179","url":null,"abstract":"<div><p>In industrial detection scenarios, achieving high accuracy typically relies on extensive labeled datasets, which are costly and time-consuming. This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. Integral to USCL, we employ the multi-task fusion self-supervised learning (MTSL) method to extract robust feature representations through multiple self-supervised tasks. Additionally, we introduce the Enhanced Spectral Clustering (ESC) method and a dynamic selecting function (DSF). ESC effectively integrates both local and global similarity matrices, improving clustering accuracy. The DSF maximally selects the most valuable instances for labeling, significantly enhancing the representativeness and diversity of the labeled data. USCL consistently improves various SSL methods compared to traditional instance selection methods. For example, it boosts Efficient Teacher by 5%, 6.6%, and 7.8% in mean Average Precision(mAP) on the Automotive Sealing Rings Defect Dataset, the Metallic Surface Defect Dataset, and the Printed Circuit Boards (PCB) Defect Dataset with 10% labeled data. Our work sets a new benchmark for SSL in industrial settings.</p></div>","PeriodicalId":48547,"journal":{"name":"Journal of King Saud University-Computer and Information Sciences","volume":"36 8","pages":"Article 102179"},"PeriodicalIF":5.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1319157824002684/pdfft?md5=2e9ae7d3bfac3922191cefd8f900c5a6&pid=1-s2.0-S1319157824002684-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}