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scIAMC:Single-Cell Imputation via adaptive matrix completion scIAMC:通过自适应矩阵补全的单细胞植入
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00059
Shuai Zhang, Xiang Chen, Li Peng
{"title":"scIAMC:Single-Cell Imputation via adaptive matrix completion","authors":"Shuai Zhang, Xiang Chen, Li Peng","doi":"10.1109/CSCloud-EdgeCom58631.2023.00059","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00059","url":null,"abstract":"Single-cell sequencing techniques are often impacted by technical noise, leading to the generation of very sparse expression matrices. This technical noise is referred to as dropouts and poses as a major challenge for downstream analysis. In this study, we introduce scIAMC (single-cell imputation via adaptive parameter matrix completion), which is based on matrix completion theory to recover missing values in expression matrices. To expedite the algorithm's running time and avoid any parameter tuning on data, we formulated an optimization problem. Our approach led to an enhanced cell population identification and minimal errors, while also restoring biological landscapes that were damaged by these dropouts.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"23 1","pages":"305-310"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81656829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Weighted k-Medoids Clustering Algorithm Based on Granular Computing 基于颗粒计算的加权k-媒质聚类算法
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00032
Shao-Jie Sun, Linshu Chen, Benshan Mei, Tao Li, Xue-Qi Ye, Min Shi
{"title":"A Weighted k-Medoids Clustering Algorithm Based on Granular Computing","authors":"Shao-Jie Sun, Linshu Chen, Benshan Mei, Tao Li, Xue-Qi Ye, Min Shi","doi":"10.1109/CSCloud-EdgeCom58631.2023.00032","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00032","url":null,"abstract":"Because of the problems that the fast k-Medoids clustering algorithm does not consider the weight of each attribute and the initial clustering center may be in the same cluster, this paper proposes a weighted $boldsymbol{k}$-Medoids clustering algorithm based on granular computing. Firstly, the hierarchical structure in the fuzzy quotient space theory is introduced to define the decision attribute of the sample under each granularity, and the computing method of sample attribute weight is defined by the attributes of the sample set itself and the definition of attribute importance in the rough set model. Secondly, the sample similarity function is defined by the attribute weight coefficient, and the attribute weight is integrated into the similarity of the fast k-Medoids clustering algorithm to quantitatively define the importance of each sample's attribute. Finally, from the prospective view of granular computing, the samples are clustered according to the above similarity function, and the original clustering centers are initialized by K cluster centers with long distance. The experimental results on machine learning datasets UCI show that the proposed weighted k-Medoids clustering algorithm based on granular computing greatly improves the accuracy of clustering.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"64 1","pages":"138-143"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78574398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Energy-saving Processors Two-phases Frequency Reduction Algorithm on Heterogeneous Embedded Systems 异构嵌入式系统的节能处理器两相降频算法
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00083
Weihong Huang, Kuan Jiang, Jing Huang, Lisi F. Lisi, Yufeng Xiao, Zihao Deng
{"title":"Energy-saving Processors Two-phases Frequency Reduction Algorithm on Heterogeneous Embedded Systems","authors":"Weihong Huang, Kuan Jiang, Jing Huang, Lisi F. Lisi, Yufeng Xiao, Zihao Deng","doi":"10.1109/CSCloud-EdgeCom58631.2023.00083","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00083","url":null,"abstract":"Energy saving has become a key issue for heterogeneous embedded systems. Previous energy-saving methods attempt to minimize the energy consumption of applications in heterogeneous embedded systems subject to deadline constraints by reducing the processor frequency. However, good scheduling strategy can also minimize energy consumption to some extent. This paper proposes a novel energy-saving scheduling algorithm, called the Energy-saving Processors Two-phases Frequency Reduction (EPTFR) Algorithm. In the first stage, within the deadline constraints, the maximum working frequency of each processor is reasonably and synchronously reduced; in the second phase, when running sub-applications on the processor, under the constraints of the earliest start time and latest end time of sub-applications, the actual operating frequency of the processor is reasonably reduced. Finally, the effectiveness of the EPTFR algorithm is verified through numerical experiments, and the results show that the proposed EPTFR algorithm can achieve a significant energy-saving effect.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"98 1","pages":"452-457"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84119976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
An improved U-Net network for medical image segmentation 一种改进的U-Net医学图像分割方法
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00057
Zhenzhen Wang, Jia Zhang, Zhihuan Liu, Shaomiao Chen, Danqing Lu
{"title":"An improved U-Net network for medical image segmentation","authors":"Zhenzhen Wang, Jia Zhang, Zhihuan Liu, Shaomiao Chen, Danqing Lu","doi":"10.1109/CSCloud-EdgeCom58631.2023.00057","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00057","url":null,"abstract":"In many computer-aided spinal imaging and disease diagnosis, automating the segmentation of the spine and cones from CT images is a challenging problem. Therefore, in this paper, we propose a triple channel expansion attention segmentation network based on U-Net for spinal CT images. We design a triple channel expansion attention to solve the problem of low accuracy caused by the loss of important feature information in the downsampling process of ordinary convolution, which uses different sizes of convolution set kernels to extract different features. Then through this attention, we output a feature image for each layer of the down-sampling, and finally skip connection with it during the up-sampling. Finally, many experimental results on VerSe 2019 and VerSe 2020 datasets show that our proposed network is superior to other prior art segmentation networks.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"27 1","pages":"292-297"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77924302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Using User-Item Sub-Block to Improve Recommendation Systems 使用User-Item子块改进推荐系统
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00047
Shuping Wang, Chongze Lin, Yitong Zheng
{"title":"Using User-Item Sub-Block to Improve Recommendation Systems","authors":"Shuping Wang, Chongze Lin, Yitong Zheng","doi":"10.1109/CSCloud-EdgeCom58631.2023.00047","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00047","url":null,"abstract":"As an indispensable technique in the field of information filtering, recommendation systems (RSs) have been well studied and developed both in academia and in industry recently. In this paper, we propose the intimacy among users to obtain a user-item objective rating matrix, which can reflect user’s real interest. For the sake of better predicting ratings, a user-item sub-block is presented to cluster a group of intimate users and a subset of items. Then, the sub-block can be detected through intimacy among users and similarity between items. In order to improve recommendation accuracy, we propose a social contribution degree and social similarity based matrix factorization method to predict scores in sub-block. The final predicted ratings are obtained by combining all sub-blocks. Top- N items with highest predicted scores are recommended to each user. Systematic simulations on real world data set have demonstrated the effectiveness of our proposed approach.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"54 1","pages":"229-234"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91155255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
DPCNN-based Models for Text Classification 基于dpcnn的文本分类模型
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00068
Meijiao Zhang, Jiacheng Pang, Jiahong Cai, Yingzi Huo, Ce Yang, Huixuan Xiong
{"title":"DPCNN-based Models for Text Classification","authors":"Meijiao Zhang, Jiacheng Pang, Jiahong Cai, Yingzi Huo, Ce Yang, Huixuan Xiong","doi":"10.1109/CSCloud-EdgeCom58631.2023.00068","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00068","url":null,"abstract":"In recent years, with the wide application of CNN in the field of deep learning, the related model of CNN, the Deep Pyramid Convolutional Neural Networks for Text Categorization (DPCNN) model, has emerged, and by the idea of deepening the depth of the network to obtain the best accuracy, DPCNN has made breakthroughs in related fields, especially in the field of text categorization, and its concrete applications in solving practical problems have achieved good results. This paper first introduces the text classification system, then introduces the mainstream model CNN for text classification, after that this paper focuses on the analysis of the DPCNN model, introduces its background and its principle analysis, and introduces the application of DPCNN in specific examples, and finally summarizes and outlooks on DPCNN, emphasizes its application advantages and builds suitable application scenarios.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"103 1","pages":"363-368"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88139020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Sentiment-Support Graph Convolutional Network for Aspect-Level Sentiment Analysis 面向层面情感分析的情感支持图卷积网络
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00039
Rui-Ding Gao, Lei Jiang, Ziwei Zou, Yuan Li, Yu-Rong Hu
{"title":"A Sentiment-Support Graph Convolutional Network for Aspect-Level Sentiment Analysis","authors":"Rui-Ding Gao, Lei Jiang, Ziwei Zou, Yuan Li, Yu-Rong Hu","doi":"10.1109/CSCloud-EdgeCom58631.2023.00039","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00039","url":null,"abstract":"The task of aspect-level sentiment analysis is to identify the sentiment polarity of sentences when expressed in different aspects. The attention mechanism-based approach allows for attentional interaction between the target and context, but it only combines sentences from a semantic perspective, overlooking the syntactic information present in the sentences. Although graph convolutional networks are capable of handling syntactic information well, they are still unable to effectively combine semantic and syntactic information. This paper proposes a sentiment-supported graph convolutional network (SSGCN), which first extracts the semantic information of words using aspect-aware attention and self-attention. Then, the grammar mask matrix and graph convolutional network are used to combine semantic and grammatical information. The features are then split into two parts - one part extracts semantic and syntactic information related to aspect words, and the other part extracts features related to sentiment-supportive words. Finally, the results from the two parts are concatenated to effectively combine semantic and syntactic information. Experimental results show that the proposed model outperforms the benchmark models in terms of accuracy and macro F1 values on three public datasets.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"24 1","pages":"181-185"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90105173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Exploring Heterogeneous Decentralized Markets in DeFi and NFT on Ethereum Blockchain 探索以太坊区块链上DeFi和NFT的异构分散市场
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00052
Peilin Zheng, Bowei Su, Zigui Jiang, Chan-Ming Yang, Jiachi Chen, Jiajing Wu
{"title":"Exploring Heterogeneous Decentralized Markets in DeFi and NFT on Ethereum Blockchain","authors":"Peilin Zheng, Bowei Su, Zigui Jiang, Chan-Ming Yang, Jiachi Chen, Jiajing Wu","doi":"10.1109/CSCloud-EdgeCom58631.2023.00052","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00052","url":null,"abstract":"Blockchain applications have grown tremendously recently, especially in the Decentralized Finance (DeFi) and Non-fungible Token (NFT) markets. The DeFi and NFT markets generate massive transactions and research-worthy data. However, few studies have systematically processed and analyzed them, preventing users from understanding the ecosystem. The main challenge of analyzing the DeFi & NFT markets is the heterogeneity of data that different markets have heterogeneous businesses and data. To address this problem, in this paper, we propose a framework to explore the heterogeneous decentralized markets in DeFi and NFT on the Ethereum blockchain. Based on this framework, we analyze the data of 21 exchange/lending markets in DeFi/NFT, with 184,173,656 records in total. We investigate the activity, profitability, and security of these markets. We obtain several findings to help market users through quantitative analysis. Datasets and codes are released.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"1 1","pages":"259-267"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79413109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Message from the Program Chairs - CSCloud 2023 来自CSCloud 2023项目主席的信息
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/cscloud-edgecom58631.2023.00006
{"title":"Message from the Program Chairs - CSCloud 2023","authors":"","doi":"10.1109/cscloud-edgecom58631.2023.00006","DOIUrl":"https://doi.org/10.1109/cscloud-edgecom58631.2023.00006","url":null,"abstract":"","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"13 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86577307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Research and design of a machine vision-based silk cocoon quality inspection system 基于机器视觉的蚕茧质量检测系统的研究与设计
IF 4 3区 计算机科学
Journal of Cloud Computing-Advances Systems and Applications Pub Date : 2023-07-01 DOI: 10.1109/CSCloud-EdgeCom58631.2023.00069
Chengjun Yang, Jansheng Peng, Jiahong Cai, Yun Tang, Ling Zhou, YaoSheng Yang
{"title":"Research and design of a machine vision-based silk cocoon quality inspection system","authors":"Chengjun Yang, Jansheng Peng, Jiahong Cai, Yun Tang, Ling Zhou, YaoSheng Yang","doi":"10.1109/CSCloud-EdgeCom58631.2023.00069","DOIUrl":"https://doi.org/10.1109/CSCloud-EdgeCom58631.2023.00069","url":null,"abstract":"Silk cocoon is one of the critical textile raw materials, and its quality has a significant impact on production and processing. In view of the problems such as time-consuming, labor-intensive, and low efficiency in the existing silk cocoon quality inspection methods, this paper proposes a machine vision-based silk cocoon quality inspection system. For different types of silk cocoons, multiple machine vision techniques are used for image processing and feature extraction. The quality characteristics of silk cocoons are discriminated and analyzed by machine learning algorithms to achieve automatic detection of the cocoon quality. Experimental results show that the proposed system has high accuracy and fast detection speed and can meet the requirements of automated detection in the silk cocoon production process.","PeriodicalId":56007,"journal":{"name":"Journal of Cloud Computing-Advances Systems and Applications","volume":"61 1","pages":"369-374"},"PeriodicalIF":4.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79491152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
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