Article
Computer Science, Information Systems
Jiguo Li, Yichen Zhang, Jianting Ning, Xinyi Huang, Geong Sen Poh, Debang Wang
Summary: This article proposes a CP-ABE scheme for access control of IoT data on the cloud, providing fine-grained and flexible access control and addressing key abuse issues.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Xiaolong Xu, Haoyuan Li, Weijie Xu, Zhongjian Liu, Liang Yao, Fei Dai
Summary: This article explores the use of artificial intelligence (AI) for optimizing edge services in the Internet of Vehicles (IoV). It begins by introducing the concepts of IoV, edge computing (EC), and AI. It then reviews the edge service frameworks for IoV and examines the application of AI in edge server placement and service offloading. Finally, it discusses several open issues in optimizing edge services with AI.
TSINGHUA SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Hardware & Architecture
Dezhi Han, Nannan Pan, Kuan-Ching Li
Summary: The proposed CP-ABE scheme in this article achieves revocation, white-box traceability, and the application of hidden policy. The ciphertext is composed of two parts: the access policy encrypted by attribute value and the revocation information related to a binary tree. The scheme is proven to be IND-CPA secure, efficient, and promising in the standard model.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Article
Computer Science, Information Systems
Jiguo Li, Hao Yan, Yichen Zhang
Summary: To increase the availability and durability of outsourced data, many customers store multiple copies on multiple cloud servers. Existing PDP protocols mainly focus on single-copy storage and rely on PKI technique, which has security vulnerabilities and high communication/computational costs. In this paper, we propose a novel identity-based PDP scheme for multi-copy on multiple cloud storage servers, achieving both security and efficiency.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Yun Li, Shichao Xia, Mengyan Zheng, Bin Cao, Qilie Liu
Summary: In order to improve mobile users' service experience, careful design of offloading policy is necessary in mobile cloud computing. This paper investigates the offloading policy in heterogeneous wireless networks by formulating the mobile users' workload offloading problem and proposing optimization frameworks and methods. Experimental results show the effectiveness of the proposed methods for deterministic and random WiFi connections.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Tausif Diwan, G. Anirudh, Jitendra Tembhurne
Summary: Object detection is a significant problem in computer vision, and deep learning has greatly improved its performance. Object detectors can be categorized into two stage and single stage detectors, with two stage detectors typically achieving higher accuracy and single stage detectors having faster inference time. YOLO, a widely adopted single stage object detection algorithm, has the advantage of faster inference speed. This paper provides a comprehensive review of single stage object detectors, particularly YOLO, and compares them with two stage detectors. It also summarizes different versions of YOLO and their applications, as well as future research directions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Zhenglai Li, Chang Tang, Xinwang Liu, Xiao Zheng, Wei Zhang, En Zhu
Summary: This novel multi-view clustering method constructs an essential similarity graph in a spectral embedding space, addressing the issue of noise and redundancy from learning similarity graph directly from original features. By imposing a weighted tensor nuclear norm constraint, it captures high-order consistent information and effectively handles clustering of multi-view datasets.
IEEE TRANSACTIONS ON MULTIMEDIA
(2022)
Review
Computer Science, Software Engineering
Xin Ning, Xinran Wang, Shaohui Xu, Weiwei Cai, Liping Zhang, Lina Yu, Wenfa Li
Summary: This article summarizes the recent research on Co-training algorithm, which is a main method of semi-supervised learning in machine learning. It introduces the main steps of relevant Co-training algorithms and discusses the existing problems. Suggestions for improvement and future development directions are also provided.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Software Engineering
Robin Verschueren, Gianluca Frison, Dimitris Kouzoupis, Jonathan Frey, Niels van Duijkeren, Andrea Zanelli, Branimir Novoselnik, Thivaharan Albin, Rien Quirynen, Moritz Diehl
Summary: The acados software package is a collection of solvers for fast embedded optimization, designed for fast embedded applications. It provides efficient optimal control algorithms targeting embedded devices, high-performance linear algebra library, user-friendly interfaces, and compatibility with modeling languages, all without the need for automatic code generation, ensuring flexibility and performance.
MATHEMATICAL PROGRAMMING COMPUTATION
(2022)
Article
Computer Science, Information Systems
Juntao Chen, Quan Zou, Jing Li
Summary: N6-methyladenosine (m(6)A) is a prevalent methylation modification that is related to common diseases such as cancer, tumors, and obesity. Accurate prediction of m(6)A methylation sites in RNA sequences has become a critical issue in bioinformatics. Researchers developed an m(6)A site predictor called DeepM6ASeq-EL, which integrates LSTM and CNN classifiers with the strategy of hard voting. However, its accuracy in m(6)A site prediction is lower compared to the state-of-the-art method WHISTLE.
FRONTIERS OF COMPUTER SCIENCE
(2022)
Article
Computer Science, Information Systems
Zhihan Lv, Dongliang Chen, Haibin Lv
Summary: This article explores the method of using digital twins and BIM to process big data, in order to accelerate the construction of smart cities and improve the accuracy of data processing. By using multiple GPUs and the Bayesian network structural learning algorithm, complex data in smart cities can be effectively processed.
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
(2022)
Article
Computer Science, Software Engineering
Khaled Bayoudh, Raja Knani, Faycal Hamdaoui, Abdellatif Mtibaa
Summary: The research discusses the rapid progress in multimodal learning, particularly in computer vision, with a focus on developing deep models that integrate heterogeneous visual cues. Key concepts and algorithms in deep multimodal learning are explored to enhance understanding within the computer vision community. The article summarizes six perspectives on deep multimodal learning and presents benchmark datasets for solving problems in various vision domains, while also highlighting limitations, challenges, and future research directions.
Article
Computer Science, Information Systems
Zaixing Sun, Boyu Zhang, Chonglin Gu, Ruitao Xie, Bin Qian, Hejiao Huang
Summary: In this article, a hybrid heuristic algorithm called ET2FA is proposed to solve deadline-constrained workflow scheduling in the cloud. With new features such as hibernation and per-second billing, ET2FA can generate efficient and economical scheduling schemes. Extensive simulation experiments show that ET2FA outperforms state-of-the-art algorithms.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Chunpeng Ge, Willy Susilo, Joonsang Baek, Zhe Liu, Jinyue Xia, Liming Fang
Summary: This article explores a new security requirement for revocable attribute-based encryption schemes: integrity. It introduces a formal definition and security model for revocable attribute-based encryption with data integrity protection (RABE-DI) and proposes a concrete scheme that ensures confidentiality and integrity. The implementation result and performance evaluation demonstrate the efficiency and practicality of the proposed scheme.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Article
Computer Science, Information Systems
Arman Haghanifar, Mahdiyar Molahasani Majdabadi, Younhee Choi, S. Deivalakshmi, Seokbum Ko
Summary: This study focuses on efficiently detecting imaging features of novel coronavirus pneumonia using deep convolutional neural networks. The proposed COVID-CXNet model is capable of precise localization based on relevant and meaningful features, which is a step towards a fully automated and robust COVID-19 detection system.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Review
Computer Science, Software Engineering
Sukhpal Singh Gill, Adarsh Kumar, Harvinder Singh, Manmeet Singh, Kamalpreet Kaur, Muhammad Usman, Rajkumar Buyya
Summary: Quantum computing is an emerging field that utilizes quantum-mechanical principles to provide computational advantages in solving complex problems. Recent progress in quantum hardware and software has brought quantum computing closer to reality. However, challenges such as quantum decoherence and qubit interconnectivity need to be addressed in order to achieve quantum advantage in the Noisy Intermediate Scale Quantum era. A systematic review of the existing literature and identification of research gaps are important for further advancements in quantum computing.
SOFTWARE-PRACTICE & EXPERIENCE
(2022)
Review
Computer Science, Artificial Intelligence
S. Suganyadevi, V Seethalakshmi, K. Balasamy
Summary: Ongoing advances in AI, particularly in deep learning techniques, have been crucial in identifying, classifying, and quantifying patterns in clinical images. The rapid development of deep learning has found effective applications in various medical fields, including neurology, pathology, radiology, and more. This paper presents research on the application of deep learning in medical image processing, showcasing both fundamental information and cutting-edge approaches in this area.
INTERNATIONAL JOURNAL OF MULTIMEDIA INFORMATION RETRIEVAL
(2022)
Article
Computer Science, Artificial Intelligence
Peishu Wu, Han Li, Nianyin Zeng, Fengping Li
Summary: In this paper, a novel face mask detection framework called FMDYolo is proposed for monitoring whether people wear masks correctly in public. Experimental results demonstrate the superiority of FMDYolo in face mask detection.
IMAGE AND VISION COMPUTING
(2022)
Article
Computer Science, Software Engineering
Xin Ning, Fangzhe Nan, Shaohui Xu, Lina Yu, Liping Zhang
Summary: This article summarizes existing methods for frontal face generation and compares their performance. Through these methods, we can gain a better understanding of the advantages and key issues in frontal face generation, and look towards future development trends.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Information Systems
Di Yuan, Xiaojun Chang, Zhihui Li, Zhenyu He
Summary: This paper proposes an adaptive spatial-temporal context-aware (ASTCA) model within the DCF-based tracking framework to improve tracking accuracy and reduce background interference in UAV-tracking scenarios. The ASTCA model learns spatial-temporal context weight and incorporates spatial context information, which outperforms state-of-the-art tracking methods on standard UAV datasets.
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
(2022)
