J. Inf. Process. Syst.最新文献_第8页

ICT Agriculture Support System for Chili Pepper Harvesting 辣椒收获ICT农业支持系统

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.01.0056

Young-Mi Byun, Se-Chang Oh, Min Choi

引用次数: 5

The Dilemma of Parameterizing Propagation Time in Blockchain P2P Network 区块链P2P网络中参数化传播时间的困境

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.03.0140

S. Rahmadika, Si-Wan Noh, Kyeongmo Lee, Bruno Joachim Kweka, K. Rhee

{"title":"The Dilemma of Parameterizing Propagation Time in Blockchain P2P Network","authors":"S. Rahmadika, Si-Wan Noh, Kyeongmo Lee, Bruno Joachim Kweka, K. Rhee","doi":"10.3745/JIPS.03.0140","DOIUrl":"https://doi.org/10.3745/JIPS.03.0140","url":null,"abstract":"Propagation time on permissionless blockchain plays a significant role in terms of stability and performance in the decentralized systems. A large number of activities are disseminated to the whole nodes in the decentralized peer-to-peer network, thus causing propagation delay. The stability of the system is our concern in the first place. The propagation delay opens up opportunities for attackers to apply their protocol. Either by accelerating or decelerating the propagation time directly without proper calculation, it brings numerous negative impacts to the entire blockchain system. In this paper, we thoroughly review and elaborate on several parameters related to the propagation time in such a system. We describe our findings in terms of data communication, transaction propagation, and the possibility of an interference attack that caused an extra propagation time. Furthermore, we present the influence of block size, consensus, and blockchain scalability, including the relation of parameters. In the last session, we remark several points associated with the propagation time and use cases to avoid dilemmas in the light of the experiments and literary works.","PeriodicalId":415161,"journal":{"name":"J. Inf. Process. Syst.","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114054924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Abnormal Behavior Recognition Based on Spatio-temporal Context 基于时空背景的异常行为识别

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.02.0134

Yuanfeng Yang, Lin Li, Zhaobin Liu, Gang Liu

{"title":"Abnormal Behavior Recognition Based on Spatio-temporal Context","authors":"Yuanfeng Yang, Lin Li, Zhaobin Liu, Gang Liu","doi":"10.3745/JIPS.02.0134","DOIUrl":"https://doi.org/10.3745/JIPS.02.0134","url":null,"abstract":"This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects’ behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.","PeriodicalId":415161,"journal":{"name":"J. Inf. Process. Syst.","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131924882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Receiver Protection from Electrical Shock in Vehicle Wireless Charging Environments 车载无线充电环境中接收器防触电保护

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.03.0139

Taejun Park, Kwang-il Hwang

引用次数: 1

Research and Implementation of U-Learning System Based on Experience API 基于经验API的U-Learning系统的研究与实现

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.04.0176

Xinghua Sun, Yongfei Ye, Jie Yang, Li Hao, L. Ding, Haomin Song

引用次数: 2

One-Dimensional Search Location Algorithm Based on TDOA 基于TDOA的一维搜索定位算法

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.04.0172

Yuyao He, Yanli Chu, San-hua Guo

引用次数: 3

Advances in Algorithms, Security, and Systems for ICT Convergence 信息通信技术融合的算法、安全性和系统进展

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.03.0141

Ji Su Park, J. Park

引用次数: 1

A Health Management Service with Beacon-Based Identification for Preventive Elderly Care 基于信标识别的健康管理服务在预防性老年护理中的应用

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.04.0173

Jian-Wei Li, Yi-Chun Chang, Min-Xiong Xu, De-Yao Huang

引用次数: 5

A Sentiment Classification Approach of Sentences Clustering in Webcast Barrages 网络广播中句子聚类的情感分类方法

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.04.0174

Jun Li, Guimin Huang, Ya Zhou

{"title":"A Sentiment Classification Approach of Sentences Clustering in Webcast Barrages","authors":"Jun Li, Guimin Huang, Ya Zhou","doi":"10.3745/JIPS.04.0174","DOIUrl":"https://doi.org/10.3745/JIPS.04.0174","url":null,"abstract":"Conducting sentiment analysis and opinion mining are challenging tasks in natural language processing. Many of the sentiment analysis and opinion mining applications focus on product reviews, social media reviews, forums and microblogs whose reviews are topic-similar and opinion-rich. In this paper, we try to analyze the sentiments of sentences from online webcast reviews that scroll across the screen, which we call live barrages. Contrary to social media comments or product reviews, the topics in live barrages are more fragmented, and there are plenty of invalid comments that we must remove in the preprocessing phase. To extract evaluative sentiment sentences, we proposed a novel approach that clusters the barrages from the same commenter to solve the problem of scattering the information for each barrage. The method developed in this paper contains two subtasks: in the data preprocessing phase, we cluster the sentences from the same commenter and remove unavailable sentences; and we use a semi-supervised machine learning approach, the naïve Bayes algorithm, to analyze the sentiment of the barrage. According to our experimental results, this method shows that it performs well in analyzing the sentiment of online webcast barrages.","PeriodicalId":415161,"journal":{"name":"J. Inf. Process. Syst.","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114275722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

A Point Clouds Fast Thinning Algorithm Based on Sample Point Spatial Neighborhood 基于样本点空间邻域的点云快速细化算法

J. Inf. Process. Syst. Pub Date : 2020-06-02 DOI: 10.3745/JIPS.01.0057

Jiaxing Wei, Maolin Xu, Hongling Xiu

引用次数: 4