Article
Computer Science, Hardware & Architecture
Jia Ke, Ying Wang, Mingyue Fan, Xiaojun Chen, Wenlong Zhang, Jianping Gou
Summary: This study integrates the emotional correlation analysis model and Self-organizing Map (SOM) to construct fine-grained user emotion vector based on review text and perform visual cluster analysis, which helps platform merchants quickly mine user clustering and characteristics.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Chang Xu, Zijian Chan, Liehuang Zhu, Rongxing Lu, Yunguo Guan, Kashif Sharif
Summary: The advancements and adoption of cloud-assisted ehealthcare systems enable efficient and easy access to massive electronic medical records (EMRs) stored in the cloud. Patients can search for similar EMRs as references, which helps them find appropriate medical services quickly. However, ensuring the efficiency and privacy of queries remains a challenge in large-scale ehealthcare systems. This study proposes an efficient and privacy-preserving similar EMR query scheme to address this challenge and help patients find similar EMRs in a large-scale ehealthcare system.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Mohammadpayam Almasian, Alireza Shafieinejad
Summary: This paper presents a novel collaboration scheme for secure cloud file sharing using blockchain and attribute-based encryption (ABE). The scheme utilizes a decentralized and fault-tolerant approach facilitated by smart contracts in blockchain, allowing data owners to control access to their files and preserving user anonymity. The scheme also supports fast revocation of user access without communication overhead. Through formal verification, the scheme is proven to be secure in terms of confidentiality and authentication. Evaluation results demonstrate the scalability and acceptable performance of the scheme for up to 20,000 users.
COMPUTER STANDARDS & INTERFACES
(2024)
Review
Computer Science, Hardware & Architecture
P. Anitha, H. S. Vimala, J. Shreyas
Summary: Congestion control is crucial for maintaining network stability, reliability, and performance in IoT. It ensures that critical applications can operate seamlessly and that IoT devices can communicate efficiently without overwhelming the network. Congestion control algorithms ensure that the network operates within its capacity, preventing network overload and maintaining network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Chen Wen, Zhang Di, Ma Jingjing, Wu Guowen
Summary: This article presents a comprehensive array of remedies for the challenges in acquiring, processing, and displaying 3D content. It proposes a strategic framework divided into three key modules and introduces two novel convolutional neural networks for depth map and virtual viewpoint image generation and optimization. The results demonstrate the efficacy of the proposed system in improving the efficiency of 3D content production while reducing costs.
Article
Computer Science, Hardware & Architecture
Mengqi Feng, Chao Lin, Wei Wu, Debiao He
Summary: Digital signature provides resistance against information tampering and identity impersonation, but lacks specific anonymity requirement for scenarios such as voting and whistle-blowing. Ring signature was introduced for achieving anonymity, but existing schemes face size limitations. In this paper, a novel construction paradigm called DualRing is proposed for logarithmic-sized ring signature. The SM2 digital signature is transformed into Type-T and integrated with DualRing technology, proving unforgeability and anonymity. Optimized and linkable schemes are proposed, and the performance in communication and computation costs are demonstrated.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Hardware & Architecture
Ruizhong Du, Jingya Wang, Yan Gao
Summary: To address the challenge of efficiently processing intensive applications in real-time for smart devices in healthcare IoT, a collaborative cloud-edge offloading model tailored for ultra-dense edge computing networks is developed. The model takes into account non-orthogonal multiple access (NOMA) as a physical technology and uses deep deterministic policy gradient to optimize the system. Simulation results show that the proposed scheme can significantly reduce the system cost.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
G. Jagadeesh, J. Gitanjali, J. Vellingiri, M. Pounambal, E. Sathiyamoorthy, Celestine Iwendi
Summary: This paper proposes a modified deep reinforcement oppositional wolf learning-based group key management (MDROWL-GKM) system to monitor data obtained in the IoT. By introducing an opposition-based learning gray wolf optimization algorithm, the system eliminates overload issues and enhances performance.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Zhonggui Pei
Summary: This paper presents a data-driven framework for evaluating collaboration efficiency within scientific research teams. The framework introduces a team efficiency evaluation system consisting of 40 specific indicators, which are analyzed and modeled using statistical methods. The adaptive enhancement algorithm model achieves the highest accuracy, recall, and F1 values. These findings demonstrate the feasibility of the proposed data-driven research team collaboration model and offer theoretical support for enhancing the effectiveness of group collaboration.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Chaozhi Cai, Xiaoyu Guo, Yingfang Xue, Jianhua Ren
Summary: This paper proposes a new DSKNet model for structure damage diagnosis of bleacher, which demonstrates superior diagnostic performance and noise resistance in experiments. It can accurately identify the location and type of damage, ensuring the safety of bleacher personnel.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Xin-miao Chen, Shi Wang, Yong-jin Ye, Yong-zheng Wu, Bo Jiang
Summary: This paper introduces a strategy based on the business of each individual qubit to improve the execution efficiency of quantum circuits by inserting SWAP gates. The strategy exploits the uneven distribution of quantum gates over qubits to reduce the time overhead caused by inserted SWAP gates, while minimizing the negative impact on subsequent operations.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
James Fang, Dmitry Lychagin, Michael J. Carey, Vassilis J. Tsotras
Summary: Window queries are valuable tools for analyzing ordered data, and have been studied in both streaming and stored data environments. We propose a new window syntax that incorporates ideas from existing systems, making a diverse range of window queries easier to write and optimize. By implementing this syntax in SQL++ on top of AsterixDB, we can efficiently process window queries over large datasets in a parallel manner.
Article
Computer Science, Hardware & Architecture
Zhenhua Chen, Ting Li, Junrui Xie, Ni Li, Jingjing Nie
Summary: The kth min threshold is a fundamental operation in data evaluation that determines whether the kth smallest element in an attribute set exceeds a predefined threshold. However, conducting such evaluations compromises the privacy of confidential files due to the sensitive information involved. In this research, a new encryption notion called kth min threshold encryption (KTE) is proposed to preserve the privacy of confidential files during data evaluation. The construction of KTE in the public-key setting ensures optimally short private keys, making it practical with only two pairing operations for decryption computation.
Article
Computer Science, Hardware & Architecture
Tertulien Ndjountche
Summary: Due to increasing recording densities, efficient read channels are needed for high-speed operation. Improved algorithms and pipeline stages can achieve speed improvements and power consumption reductions.
ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING
(2023)
Article
Computer Science, Hardware & Architecture
Yinsheng Chen, Jiahao Li, Kun Sun, Ying Zhang
Summary: This paper proposes a lightweight early forest fire and smoke detection method based on GS-YOLOv5, which improves the detection accuracy and speed by improving the network structure and introducing the coordinate attention module.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Weihong Fu, Haoyi Li
Summary: An improved phase gradient autofocus algorithm is proposed in this paper to address the issues in ISAR imaging, achieving more stable and evident focusing results by using an amplitude-based traversal method and Kaiser window.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Yihong Wang, Baolei Cheng, Yan Wang, Jia Yu, Jianxi Fan
Summary: This paper studies the strongly Menger connectedness of r-dimensional recursive networks with triangles and provides related results.
Article
Computer Science, Hardware & Architecture
Qingchun Bai, Mengmeng Tang, Yang Song, Jun Xiao
Summary: By combining syntactic rule-based techniques with advanced pre-trained language models, this paper proposes an innovative strategy for extracting entities and relationships from danmaku comments. Experimental results demonstrate that this approach achieves competitive performance on large-scale data.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Shahzadi Bano, Weimei Zhi, Baozhi Qiu, Muhammad Raza, Nabila Sehito, Mian Muhammad Kamal, Ghadah Aldehim, Nuha Alruwais
Summary: This research paper focuses on the challenges of learning classifiers from large-scale, highly imbalanced datasets. The proposed self-paced ensemble framework addresses the challenges of class overlap and skewed distributions, while maintaining computational efficiency.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Haroon Yousuf Mir, Omkar Singh
Summary: This paper presents a novel method for removing power line interference in ECG signals using VMD and digital filtering techniques. By decomposing the noisy ECG signal, narrow-band VMFs are created and a variable notch filter is designed to eliminate power line interference. Experimental results demonstrate that the proposed method effectively reduces power line interference noise.
ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING
(2023)
