ACM Computing Surveys最新文献_第5页

Physics-informed Machine Learning for Medical Image Analysis 基于物理的医学图像分析机器学习

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-15 DOI: 10.1145/3768158

Chayan Banerjee, Kien Nguyen, Olivier Salvado, Truyen Tran, Clinton Fookes

{"title":"Physics-informed Machine Learning for Medical Image Analysis","authors":"Chayan Banerjee, Kien Nguyen, Olivier Salvado, Truyen Tran, Clinton Fookes","doi":"10.1145/3768158","DOIUrl":"https://doi.org/10.1145/3768158","url":null,"abstract":"The incorporation of physical information in machine learning frameworks is transforming medical image analysis (MIA). Integrating fundamental knowledge and governing physical laws not only improves analysis performance but also enhances the model’s robustness and interpretability. This work presents a systematic review of over 100 papers on the utility of PINNs dedicated to MIA (PIMIA) tasks. We propose a unified taxonomy to investigate what physics knowledge and processes are modeled, how they are represented, and the strategies to incorporate them into MIA models. We delve deep into a wide range of image analysis tasks, from imaging, generation, prediction, inverse imaging (super-resolution and reconstruction), registration, and image analysis (segmentation and classification). For each task, we thoroughly examine and present the central physics-guided operation, the region of interest (with respect to human anatomy), the corresponding imaging modality, the datasets used for model training, the deep network architectures employed, and the primary physical processes, equations, or principles utilized. Additionally, we also introduce a novel metric to compare the performance of PIMIA methods across different tasks and datasets. Based on this review, we summarize and distill our perspectives on the challenges, and highlight open research questions and directions for future research.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"52 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145072304","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}

引用次数: 0

Lightweight Consensus in Blockchain: A Systematic Literature Review b区块链的轻量级共识：系统文献综述

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-15 DOI: 10.1145/3768149

Namrata Chacko, Narendra V G, Mamatha B C, Manoj T

{"title":"Lightweight Consensus in Blockchain: A Systematic Literature Review","authors":"Namrata Chacko, Narendra V G, Mamatha B C, Manoj T","doi":"10.1145/3768149","DOIUrl":"https://doi.org/10.1145/3768149","url":null,"abstract":"Blockchain technology has seen a rapid pace of development and expanded application domains swiftly due to the rising demand for decentralized trust, transparency, and integrity. The consensus algorithm plays a critical role in ensuring trust, immutability and governance of the decentralized network. However, traditional consensus face challenges such as high energy consumption, low scalability, security, and fault tolerance. Researchers have been investigating Lightweight Consensus to overcome these challenges. Lightweight Consensus is a mechanism that enables a more efficient and scalable blockchain system while ensuring security and immutability. This work uses the Systematic Literature Review method to comprehend Lightweight Consensus. 127 studies were grouped based on application specific network, and an in-depth analysis was done on the characteristics of the consensus. A novel taxonomy of Lightweight Consensus based on the agreement method and round propagation is proposed. Various parameters that needed consideration for a Lightweight Consensus are also analyzed. Finally, the study makes recommendations for future research on Lightweight Consensus in blockchain, emphasizing the importance of more empirical investigations and real-world implementations. This study offers a comprehensive overview of the current research landscape on lightweight consensus in blockchain, shedding light on its potential impact on the evolution of blockchain technology. It also serves as a valuable guide for researchers, helping them identify the most suitable consensus features for specific application domains with unique requirements.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"24 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145072307","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}

引用次数: 0

Artificial Intelligence in Educational Technology: A Systematic Review of Datasets and Applications 教育技术中的人工智能：数据集和应用的系统回顾

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-15 DOI: 10.1145/3768312

Luke Topham, Peter Atherton, Tom Reynolds, Yasir Hussain, Abir Hussain, Hoshang Kolivand, Wasiq Khan

{"title":"Artificial Intelligence in Educational Technology: A Systematic Review of Datasets and Applications","authors":"Luke Topham, Peter Atherton, Tom Reynolds, Yasir Hussain, Abir Hussain, Hoshang Kolivand, Wasiq Khan","doi":"10.1145/3768312","DOIUrl":"https://doi.org/10.1145/3768312","url":null,"abstract":"Artificial Intelligence (AI) has the potential to impact a diverse range of domains. For instance, AI for the education domain has received increasing interest with various applications, including predicting performance, curating learning materials, and automated assessment and feedback. Despite the developments, some imbalances appear in the literature; for example, traditional classrooms and non-scientific academic subjects received little attention. This survey provides a systematic review of the current trends in AI research for education, specifically addressing applications within secondary education (ages 11+) through to higher education (HE), and offers a detailed compilation of datasets and methods, facilitating a deeper understanding of the field and encouraging further investigation. It includes a thorough review of the datasets available to encourage and enable future research, development, and collaboration, as well as the establishment of performance benchmarks. Furthermore, this survey provides an overview of issues and problems arising from recent developments, which may aid policymakers in their decision-making and addressing ethical concerns and standards. For example, many AI in Education (AIEd) platforms are not grounded in educational theory. We also present several guidelines to aid future developments in AIEd, guiding long-term impactful projects and investments.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"84 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145072305","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}

引用次数: 0

Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey 维数约简中的非负矩阵分解：综述

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-13 DOI: 10.1145/3767726

Farid Saberi-Movahed, Kamal Berahmand, Razieh Sheikhpour, Yuefeng Li, Shirui Pan, Mahdi Jalili

引用次数: 0

Virtualization Technology for Dependable Embedded Systems: A Survey for Transportation and Industrial Domains 可靠嵌入式系统的虚拟化技术：交通和工业领域的调查

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-13 DOI: 10.1145/3765736

Jon Perez-Cerrolaza, Patricia Balbastre, Enrico Mezzetti, Alfons Crespo, Jon González Eguiluz, Miguel Martin Acosta, Charles-Alexis Lefebvre

引用次数: 0

A Systematic Literature Review of Inter-Commit Fine-Grained Source Code Changes: Assessing Readiness for Large-Scale Data Collection 提交间细粒度源代码变更的系统文献综述：评估大规模数据收集的准备情况

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-12 DOI: 10.1145/3767321

Paweł Rzanny, Mirosław Ochodek

引用次数: 0

Security Management of Horizontal IoT Platforms: A Survey and Comparison 横向物联网平台安全管理：调查与比较

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-11 DOI: 10.1145/3766888

Anastassia Gharib, Jason Jaskolka, Mohamed Ibnkahla, Ashraf Matrawy

{"title":"Security Management of Horizontal IoT Platforms: A Survey and Comparison","authors":"Anastassia Gharib, Jason Jaskolka, Mohamed Ibnkahla, Ashraf Matrawy","doi":"10.1145/3766888","DOIUrl":"https://doi.org/10.1145/3766888","url":null,"abstract":"With the rise of Industry 4.0, horizontal Internet of Things (IoT) platforms are becoming a standardized approach for managing interoperability within complex and heterogeneous IoT systems. Horizontal IoT platforms are software solutions that provide overall IoT system orchestration and management. They work to facilitate IoT services and resources, where security management remains one of the main challenges. This paper provides a survey and comparison of security management in IoT systems using horizontal IoT platforms. For this purpose, we first define and compare vertical and horizontal IoT platforms. Although vertical IoT platforms provide solutions to many industries, horizontal IoT platforms improve system connectivity by interconnecting multiple vertical domains. We then describe the security management functionalities of horizontal IoT platforms. With these in mind, we perform a comparative study on the current state of security management approaches of existing horizontal IoT platforms. Particularly, we survey and compare the security management features of the selected standard-based reference implementations. Through discussions, we cover concerns that researchers and developers should be aware of when selecting specific reference implementations for their works. Finally, we identify open issues in the existing security management principles of these reference implementations to be addressed in future studies and practical implementations.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"53 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145035277","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}

引用次数: 0

A Survey of Quantum Machine Learning: Foundations, Algorithms, Frameworks, Data and Applications 量子机器学习概览：基础、算法、框架、数据和应用

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-11 DOI: 10.1145/3764582

Francesc Rodríguez-Díaz, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez

{"title":"A Survey of Quantum Machine Learning: Foundations, Algorithms, Frameworks, Data and Applications","authors":"Francesc Rodríguez-Díaz, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez","doi":"10.1145/3764582","DOIUrl":"https://doi.org/10.1145/3764582","url":null,"abstract":"Quantum machine learning combines quantum computing with machine learning to solve complex computational problems more efficiently than classical approaches. This survey provides an introduction to the foundations, algorithms, frameworks, data and applications of quantum machine learning, serving as a resource for researchers and practitioners. We begin by reviewing existing surveys to identify gaps that this work addresses, followed by a detailed discussion of the foundational principles of quantum mechanics and machine learning essential for quantum machine learning. Key algorithms are examined, highlighting their mechanisms, advantages, and applications across various domains. Current frameworks and platforms for implementing quantum machine learning algorithms are explored, emphasizing their unique features and suitability for different contexts. Existing quantum datasets for practical usage are also reported and commented on. This survey also reviews over 135 papers, categorized into theoretical and practical contributions, to identify key advances, limitations, and application areas within quantum machine learning. Critical challenges such as hardware limitations, error rates, and scalability are analyzed to detect the obstacles that must be addressed for practical deployment. By synthesizing these elements into a structured overview, this survey aims to serve as both an introduction and a guide for advancing research and development in this disruptive field.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"14 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145035278","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}

引用次数: 0

A Survey of Fundamental Principles and Analysis for Job Scheduling on Warehouse-Scale Computers 仓库级计算机作业调度的基本原理及分析综述

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-11 DOI: 10.1145/3766543

Kevin Exton, Maria Rodriguez Read

引用次数: 0

A Survey on Spatio-Temporal Prediction: From Transformers to Foundation Models 时空预测研究综述：从变压器到地基模型

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-09-11 DOI: 10.1145/3766546

Yingchi Mao, Hongliang Zhou, Ling Chen, Rongzhi Qi, Zhende Sun, Yi Rong, Xiaoming He, Mingkai Chen, Shahid Mumtaz, Valerio Frascolla, Mohsen Guizani, Joel Rodrigues

{"title":"A Survey on Spatio-Temporal Prediction: From Transformers to Foundation Models","authors":"Yingchi Mao, Hongliang Zhou, Ling Chen, Rongzhi Qi, Zhende Sun, Yi Rong, Xiaoming He, Mingkai Chen, Shahid Mumtaz, Valerio Frascolla, Mohsen Guizani, Joel Rodrigues","doi":"10.1145/3766546","DOIUrl":"https://doi.org/10.1145/3766546","url":null,"abstract":"Spatio-Temporal (ST) data is pervasive on the various aspects in our daily lives. By mining the ST information from the data, we are able to predict trends in numerous domains. The Transformer, and one of its more recent enhancements, foundation models, have achieved a remarkable success in such ST prediction. In this paper, we first survey the state of the art of Transformers-related work, then introduce the network architecture of the Transformer and summarize the improvements to adapt to the ST prediction Transformer and foundation models, including module enhancement and adjustment. Subsequently, we categorize the ST Transformer and foundation models in selected applications in some relevant domains, mainly urban transportation, climate monitoring, and motion prediction. Next, we propose an evaluation method in the ST prediction with Transformers and foundation models, list the most relevant open-source datasets, evaluation metrics and performance analysis. Finally, we discuss some future directions on the task of ST prediction with Transformer and foundation models. Relevant papers and open-source resources have been collated and are continuously updated at: https://github.com/cyhforlight/Spatio-Temporal-Prediction-Transformer-Review.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"27 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145035281","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}

引用次数: 0