Computer Science Review最新文献

{"title":"A review on fingerprint based authentication-its challenges and applications","authors":"Diptadip Maiti ,&nbsp;Madhuchhanda Basak ,&nbsp;Debashis Das","doi":"10.1016/j.cosrev.2025.100735","DOIUrl":"10.1016/j.cosrev.2025.100735","url":null,"abstract":"<div><div>In digital era, human authentication and identification mostly relies on biometric traits of an individual. Amongst different biometrics, fingerprint has been playing a crucial role and employing as fundamental evidence due to some of its inherent properties. Moreover, it establishes itself as the strongest verification component in several applications like – court of law, criminal and forensic investigations. In the present study we primarily focus on various application domains of fingerprint based identification systems. We also highlight the different challenges and security threats that the system may encounter during its implementation. The review analyses the state of the art methods with its technical details along with their implementation and security issues which lead to a thematic analysis of the literature. To facilitate a better comprehension towards the system, we also provide a few fundamental knowledge on fingerprint datasets and system performance measures. Finally, the future prospects of fingerprint biometric in the identification system are highlighted.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"57 ","pages":"Article 100735"},"PeriodicalIF":13.3,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maritime search and rescue missions with aerial images: A survey","authors":"Juan P. Martinez-Esteso,&nbsp;Francisco J. Castellanos,&nbsp;Jorge Calvo-Zaragoza,&nbsp;Antonio Javier Gallego","doi":"10.1016/j.cosrev.2025.100736","DOIUrl":"10.1016/j.cosrev.2025.100736","url":null,"abstract":"<div><div>The speed of response by search and rescue teams at sea is of vital importance, as survival may depend on it. Recent technological advancements have led to the development of more efficient systems for locating individuals involved in a maritime incident, such as the use of Unmanned Aerial Vehicles (UAVs) equipped with cameras and other integrated sensors. Over the past decade, several researchers have contributed to the development of automatic systems capable of detecting people using aerial images, particularly by leveraging the advantages of deep learning. In this article, we provide a comprehensive review of the existing literature on this topic. We analyze the methods proposed to date, including both traditional techniques and more advanced approaches based on machine learning and neural networks. Additionally, we take into account the use of synthetic data to cover a wider range of scenarios without the need to deploy a team to collect data, which is one of the major obstacles for these systems. Overall, this paper situates the reader in the field of detecting people at sea using aerial images by quickly identifying the most suitable methodology for each scenario, as well as providing an in-depth discussion and direction for future trends.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"57 ","pages":"Article 100736"},"PeriodicalIF":13.3,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design practices in visualization driven data exploration for non-expert audiences","authors":"Natasha Tylosky,&nbsp;Antti Knutas,&nbsp;Annika Wolff","doi":"10.1016/j.cosrev.2025.100731","DOIUrl":"10.1016/j.cosrev.2025.100731","url":null,"abstract":"<div><div>Data exploration is increasingly relevant to the average person in our data-driven world, as data is now often open source and available to the general public and other non-expert users via open data portals and other similar data sources. This has introduced the need for data exploration tools, methods and techniques to engage non-expert users in data exploration, and thus a proliferation of new research in the field of Human Computer Interaction (HCI) that relates to engaging non-expert audiences with data. In particular data exploration that contains a data visualization component can be useful for making data understandable and engaging for non-expert audiences.</div><div>Currently, the range of design practices most commonly used in the field of HCI to engage non-expert audiences in data exploration that includes a visualization component has yet to be formalized or given a comprehensive overview. This paper is a systematic mapping study (SMS) which aims to fill that gap by analyzing design trends engaging non-expert audiences in visualization driven data exploration via interactive systems, providing an overview of existing design practices and engagement methods, as well as set of three recommendations for how future designers can best engage non-expert audiences in visualization driven data exploration.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100731"},"PeriodicalIF":13.3,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 comprehensive survey of golden jacal optimization and its applications","authors":"Mehdi Hosseinzadeh ,&nbsp;Jawad Tanveer ,&nbsp;Amir Masoud Rahmani ,&nbsp;Abed Alanazi ,&nbsp;Monji Mohamed Zaidi ,&nbsp;Khursheed Aurangzeb ,&nbsp;Hamid Alinejad-Rokny ,&nbsp;Thantrira Porntaveetus ,&nbsp;Sang-Woong Lee","doi":"10.1016/j.cosrev.2025.100733","DOIUrl":"10.1016/j.cosrev.2025.100733","url":null,"abstract":"<div><div>In recent decades, there has been an increasing interest from the research community in various scientific and engineering fields, including robotic control, signal processing, image processing, feature selection, classification, clustering, and other issues. Many optimization problems are inherently complicated and complex. They cannot be solved by traditional optimization methods, such as mathematical programming, because most conventional optimization methods focus on evaluating first derivatives. On the other hand, metaheuristic algorithms have high ability and adaptability in finding near-optimal solutions in a reasonable time for different optimization problems due to parallel search and balance between exploration and exploitation. This study discusses the basic principles and mechanisms of the GJO algorithm and its challenges. This review aims to provide valuable insights into the potential of the GJO algorithm for real-world and scientific optimization tasks. In this paper, a complete review of the Golden Jackal Optimization (GJO) algorithm for various optimization problems is done. The GJO algorithm is one of the metaheuristic algorithms invented in 2022 and inspired by the life of natural jackals. This paper's complete classification of GJO in hybrid, improved, binary, multi-objective, and optimization problems is done. The analysis shows that the percentage of studies conducted in the four fields of hybrid, improved variants of GJO (binary, multi-objective), and optimization are 11 %, 44 %, 9 %, and 36 %, respectively. Studies have shown that this algorithm performs well in real-world challenges. GJO is a powerful tool for solving scientific and engineering problems flexibly.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100733"},"PeriodicalIF":13.3,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Offloading decision and resource allocation in aerial computing: A comprehensive survey","authors":"Ahmadun Nabi,&nbsp;Sangman Moh","doi":"10.1016/j.cosrev.2025.100734","DOIUrl":"10.1016/j.cosrev.2025.100734","url":null,"abstract":"<div><div>Aerial computing can facilitate the successful execution of tasks, ensuring low latency for Internet of things (IoT) devices. It gains greater significance and practicality by offering both edge and cloud computing services for IoT applications. However, in aerial computing, resources such as computing power, energy, and bandwidth are limited and constrained. Consequently, certain tasks must be offloaded to different platforms for sustained operation. Hence, the offloading decision (OD) and resource allocation (RA) are closely interconnected. Currently, numerous research efforts are underway to address efficient offloading and resource management. However, a comprehensive review of OD and RA in aerial computing platforms is yet to be explored. This study presents a thorough survey of OD and RA in aerial computing platforms, extensively reviewing and comparatively discussing various algorithms and approaches. The discussion delves deep into key design issues and also explores unresolved challenges, providing possible future directions. Our work can help researchers in studying and designing efficient methods for task offloading and resource management across different application scenarios.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100734"},"PeriodicalIF":13.3,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in natural language processing for healthcare: A comprehensive review of techniques, applications, and future directions","authors":"Fatmah Alafari ,&nbsp;Maha Driss ,&nbsp;Asma Cherif","doi":"10.1016/j.cosrev.2025.100725","DOIUrl":"10.1016/j.cosrev.2025.100725","url":null,"abstract":"<div><div>Natural Language Processing (NLP) techniques have gained significant traction within the healthcare domain for analyzing textual healthcare-related datasets, sourced primarily from Electronic Health Records (EHR) and increasingly from social networks. This study delves into applying NLP technologies within the healthcare sector, drawing insights from textual datasets from various sources. It reviews the relevant articles from 2019 to 2023 and compares the pertinent solutions included therein. In addition, it explores the various NLP technologies used for processing healthcare datasets in multiple languages. The review focuses on existing studies related to various medical conditions, including cancer and chronic and infectious diseases. It categorizes these cutting-edge studies into four different NLP task categories: prediction and detection, text analysis and modeling, information processing, and other healthcare applications. Notably, the findings reveal that the most prevalent NLP tasks employed in healthcare revolve around risk prediction and text classification. Moreover, the study identifies a pressing need for more extensive research that encompasses the utilization of non-textual medical datasets from EHR, such as X-rays, computed tomography (CT) scans, and magnetic resonance imaging (MRI) scans. A key observation is that much of the current research studies about NLP related to the healthcare field were primarily using conventional data processing methods, such as ML and DL techniques. Despite their success, these methods frequently have several distinct limitations as they are not able to handle large-scale, complex datasets. In contrast, there is less focus on sophisticated technologies such as big data analytics and transformer-based modeling. Big data analytics can manage massive amounts of unstructured data from sources such as EHRs and social media, providing a more comprehensive insight into healthcare patterns. Transformer models, like BERT and GPT, are designed to detect complex patterns and contextual relationships in text, making them particularly useful for medical text classification, sentiment analysis, and disease prediction. Current research studies have not fully explored the potential of these advanced technologies, which could significantly increase the efficiency and scalability of natural language processing applications in healthcare. This highlights opportunities for further exploration and innovation within the domain of NLP in healthcare.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100725"},"PeriodicalIF":13.3,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143232645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A survey of heuristics for matrix bandwidth reduction","authors":"S.L. Gonzaga de Oliveira","doi":"10.1016/j.cosrev.2025.100724","DOIUrl":"10.1016/j.cosrev.2025.100724","url":null,"abstract":"<div><div>This paper surveys heuristic methods for matrix bandwidth reduction, including low-cost methods and metaheuristics. This optimization min–max problem represents a demanding problem for heuristic methods. This paper poses the graph layout problem with its formal definition. The study also considers the application domains in which practitioners employ the linear graph layout problem on general matrices. Furthermore, this paper focuses on the techniques and procedures that provide excellent results and provides an extensive perspective of approaches to devise heuristics for matrix bandwidth reduction. Thus, this paper surveys the most significant research in the field and examines the current state-of-the-art heuristics for the bandwidth reduction problem.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100724"},"PeriodicalIF":13.3,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning in automated diagnosis of autism spectrum disorder: a comprehensive review","authors":"Khosro Rezaee","doi":"10.1016/j.cosrev.2025.100730","DOIUrl":"10.1016/j.cosrev.2025.100730","url":null,"abstract":"<div><div>Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition characterized by social communication challenges, repetitive behaviors, and restricted interests. Early and accurate diagnosis is paramount for effective intervention and treatment, significantly improving the quality of life for individuals with ASD. This comprehensive review aims to elucidate the various methodologies employed in the automated diagnosis of ASD, providing a comparative analysis of their diagnostic accuracy, privacy considerations, non-invasiveness, cost implications, computational complexity, and feasibility for clinical and therapeutic use. The study encompasses a wide range of techniques including neuroimaging, EEG signal analysis, speech and crying signal analysis, eye tracking, facial recognition, and body movement analysis, highlighting their potential and limitations in the context of ASD diagnosis. By exploring these diverse diagnostic approaches, the review seeks to offer insights into the most promising methods and identify areas for future research and development.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100730"},"PeriodicalIF":13.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143072454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WebAssembly and security: A review","authors":"Gaetano Perrone,&nbsp;Simon Pietro Romano","doi":"10.1016/j.cosrev.2025.100728","DOIUrl":"10.1016/j.cosrev.2025.100728","url":null,"abstract":"<div><div>WebAssembly is revolutionizing the approach to developing modern applications. Although this technology was born to create portable and performant modules in web browsers, currently, its capabilities are extensively exploited in multiple and heterogeneous use-case scenarios. With the extensive effort of the community, new toolkits make the use of this technology more suitable for real-world applications. In this context, it is crucial to study the liaisons between the WebAssembly ecosystem and software security. Indeed, WebAssembly can be a medium for improving the security of a system, but it can also be exploited to evade detection systems or for performing crypto-mining activities. In addition, programs developed in low-level languages such as C can be compiled in WebAssembly binaries, and it is interesting to evaluate the security impacts of executing programs vulnerable to attacks against memory in the WebAssembly sandboxed environment. Also, WebAssembly has been designed to provide a secure and isolated environment, but such capabilities should be assessed in order to analyze their weaknesses and propose new mechanisms for addressing them. Although some research works have provided surveys of the most relevant solutions aimed at discovering WebAssembly vulnerabilities or detecting attacks, at the time of writing there is no comprehensive review of security-related literature in the WebAssembly ecosystem. We aim to fill this gap by proposing a comprehensive review of research works dealing with security in WebAssembly. We analyze 147 papers by identifying seven different security categories.</div><div>We hope that our work will provide insights into the complex landscape of WebAssembly and guide researchers, developers, and security professionals towards novel avenues in the realm of the WebAssembly ecosystem.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100728"},"PeriodicalIF":13.3,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143072455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Advancing smart transportation: A review of computer vision and photogrammetry in learning-based dimensional road pavement defect detection","authors":"Adamu Tafida ,&nbsp;Wesam Salah Alaloul ,&nbsp;Noor Amila Bt Wan Zawawi ,&nbsp;Muhammad Ali Musarat ,&nbsp;Adamu Abubakar Sani","doi":"10.1016/j.cosrev.2025.100729","DOIUrl":"10.1016/j.cosrev.2025.100729","url":null,"abstract":"<div><div>Road infrastructure networks are crucial in facilitating smart mobility, as indicated by the emergence of innovative transportation concepts that offer improved efficiency and environmental sustainability. This study seeks to review the literature regarding road pavement condition assessment performance improvement tools which utilize various computer vision and photogrammetry tools aided by machine learning algorithms towards mitigating challenges encountered and promoting smart transportation trends. A comprehensive search of available literature was conducted, and relevant studies were analyzed to identify computer vision and photogrammetry tools used, learning-based algorithms deployed and contribution to the improvement of road infrastructure to aid smart transportation. The review considered emerging challenges of the techniques, identified research gaps and explored the potentials of the techniques as it relates to aiding wider acceptance of the implementation of autonomous vehicles and smart transportation The study found gaps in knowledge relating to the computer vision (CV) and photogrammetry tools standardization of evaluation parameters, the applicability of the models for real-time assessment and implications regarding the adoption of autonomous vehicles and smart transportation which were not sufficiently considered in the previous cited literature. Future research areas were highlighted and its implication regarding the promotion of smart transportation.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"56 ","pages":"Article 100729"},"PeriodicalIF":13.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}