Journal of Information Science and Engineering最新文献_第3页

Optimizing Read Operations of Hadoop Distributed File System on Heterogeneous Storages Hadoop分布式文件系统在异构存储上的读操作优化

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-05-01 DOI: 10.6688/JISE.202105_37(3).0013

Jongbaeg Lee, Jong-Woo Lee, Sang-Won Lee

引用次数: 0

Stepwise Adaptive Video Streaming in the Wireless Mobile Network Using the Temporal-Geo Bandwidth Estimation Method 基于时地带宽估计方法的无线移动网络逐步自适应视频流

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-05-01 DOI: 10.6688/JISE.20210537(3).0011

Chung-Ming Huang, Chung-Ming Wei

{"title":"Stepwise Adaptive Video Streaming in the Wireless Mobile Network Using the Temporal-Geo Bandwidth Estimation Method","authors":"Chung-Ming Huang, Chung-Ming Wei","doi":"10.6688/JISE.20210537(3).0011","DOIUrl":"https://doi.org/10.6688/JISE.20210537(3).0011","url":null,"abstract":"With the advance of wireless mobile communication technologies, video streaming has advanced much more on these years. However, the wireless mobile network usually suffers fluctuation in available bandwidth because mobile users usually keep moving and playing streaming video simultaneously. To overcome the situation, this work proposed a method called Stepwise Adaptive Streaming using Temporal-Geo Bandwidth Estimation (SASTGBE) for the wireless mobile networking environment based on MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH). To have better Quality Of Experience (QoE), e.g., no or fewer quality switching, lower bitrate difference between two continuous video segments, no or fewer suspended times, no or shorter paused time, etc., (1) the proposed method considers location, time, and date for estimating the available bandwidth in the future and (2) the proposed stepwise adaptive streaming control scheme considers buffer level, video quality of the most recently downloaded segment, the downloading rate of the most recently downloaded segment and the estimated bandwidth to decide the video quality for the next downloaded segment. The proposed method has been implemented in the Android system for the client side and the Linux system for the server side. The experiments using SASTGBE in the real environment shown that SASTGBE has improvement in the performance of bandwidth utilization, suspended times, quality switch percentage, average bitrate difference considering suspending, and standard deviation of bitrate difference over the wireless mobile network.","PeriodicalId":50177,"journal":{"name":"Journal of Information Science and Engineering","volume":"78 1","pages":"679-696"},"PeriodicalIF":1.1,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81065813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 1

Radar Automatic Target Recognition Based on Real-Life HRRP of Ship Target by Using Convolutional Neural Network 基于舰船目标真实HRRP的卷积神经网络雷达自动目标识别

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-04-01 DOI: 10.6688/JISE.202107_37(4).0001

Tsung-Pin Chen, Lin Chih-Lung, Kuo-Chin Fan, Lin Wan-Yu, Wan-Yu Kao

引用次数: 0

Rectangle-Based Neo-Plasticism-Like Image - A New Type of Art Image and its Application to Covert Communication 基于矩形的新造型主义图像——一种新型的艺术图像及其在隐蔽传播中的应用

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-03-01 DOI: 10.6688/JISE.202103_37(2).0011

Shan-Chun Liu, Da-Chun Wu, Wen-Hsiang Tsai

{"title":"Rectangle-Based Neo-Plasticism-Like Image - A New Type of Art Image and its Application to Covert Communication","authors":"Shan-Chun Liu, Da-Chun Wu, Wen-Hsiang Tsai","doi":"10.6688/JISE.202103_37(2).0011","DOIUrl":"https://doi.org/10.6688/JISE.202103_37(2).0011","url":null,"abstract":"A new type of art image, called rectangle-based Neo-Plasticism-like image, is proposed, via which messages can be hidden for covert communication. Also proposed is an automatic method for creating such art images, which applies recursive binary partitioning to a source image by finding the maximum mutual information of the spatial positions and image intensities of the divided sub-regions. The resulting image consists of rectangular regions separated by horizontal and vertical lines, which show the abstraction style of the Neo-Plasticism art. Attracted by the artistic image content, a hacker hopefully will pay no attention to the hidden secret. Two data hiding techniques based on the binary partition tree constructed in the art image creation process are proposed, which embed messages by replacing the LSBs of each rectangular region's colors or by generating additional partition lines in the region. A message extraction process is also proposed. Data security is considered seriously by randomizing the message bits before being embedded, changing randomly the priorities of the sub-regions used in message hiding, and embedding fake messages to interfere with the hacker. Good experimental results show the feasibility of the proposed techniques for covert communication via the proposed type of art image.","PeriodicalId":50177,"journal":{"name":"Journal of Information Science and Engineering","volume":"23 1","pages":"441-468"},"PeriodicalIF":1.1,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81834497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Outpatient Text Classification System Using LSTM 基于LSTM的门诊文本分类系统

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-03-01 DOI: 10.6688/JISE.202103_37(2).0006

Che-Wen Chen, Shih-Pang Tseng, Jhing-Fa Wang

引用次数: 4

A Dynamic Parallel Meshless Method for the Problems with Large-Scale Movable and Deformable Boundary 大规模可动可变形边界问题的动态并行无网格法

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-01-01 DOI: 10.6688/JISE.202101_37(1).0006

Liang Wang, Ruixia Xue, Ning Cai, Pan Chen, Xiaobo Cui, Wei Wu, Miaomiao Niu, Dongliang Zhang, Zhao Zhang, Xiaosong Zhang

{"title":"A Dynamic Parallel Meshless Method for the Problems with Large-Scale Movable and Deformable Boundary","authors":"Liang Wang, Ruixia Xue, Ning Cai, Pan Chen, Xiaobo Cui, Wei Wu, Miaomiao Niu, Dongliang Zhang, Zhao Zhang, Xiaosong Zhang","doi":"10.6688/JISE.202101_37(1).0006","DOIUrl":"https://doi.org/10.6688/JISE.202101_37(1).0006","url":null,"abstract":"This paper puts forward a dynamic parallel meshless computing algorithm that efficiently solves flow fields with largescale motions of movable and deformable boundaries. The partition boundary is updated, as the moving boundary moves across the material interface. Meanwhile, the point clouds near the moving boundary are reconstructed. Our algorithm also solves the workload balance between nodes and information exchange in each region of the computational field, using the governing equations in the arbitrary Lagrangian-Eulerian (ALE) form. The AUFS scheme is extended to calculate the numerical convective flux. Take the interaction between a helium bubble and a shockwave as an example. Our algorithm is applied to compute the flow field with different numbers of discrete points (33,044 and 66,089) and partitions (2 and 4). The results show that our algorithm achieves an efficiency of over 80%, and captures the interaction between shockwaves and the bubble accurately. Hence, our parallel algorithm is suitable for solving problems with largescale motions of deformation boundaries. The research results shed new light on the calculation speed for similar problems.","PeriodicalId":50177,"journal":{"name":"Journal of Information Science and Engineering","volume":"58 1","pages":"79-92"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78081687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Dynamic Production Scheduling of Digital Twin Job-Shop Based on Edge Computing 基于边缘计算的数字双作业车间动态生产调度

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-01-01 DOI: 10.6688/JISE.202101_37(1).0007

Li-Zhang Xu, Q. Xie

引用次数: 7

Mgini - Improved Decision Tree using Minority Class Sensitive Splitting Criterion for Imbalanced Data of Covid-19 基于少数派类敏感分割准则的新冠肺炎不平衡数据改进Mgini决策树

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-01-01 DOI: 10.6688/jise.202109_37(5).0008

Pratik A. Barot, H. Jethva

{"title":"Mgini - Improved Decision Tree using Minority Class Sensitive Splitting Criterion for Imbalanced Data of Covid-19","authors":"Pratik A. Barot, H. Jethva","doi":"10.6688/jise.202109_37(5).0008","DOIUrl":"https://doi.org/10.6688/jise.202109_37(5).0008","url":null,"abstract":"In the time of COVID-19, medical facilities struggling to fight against the pandemic. Most of the countries face a tough time fighting against this virus outbreak. Even developed countries are struggling to deal with this virus outbreak. Common problem countries face is a lack of medical staff and medical equipment. Machine learning has the potential to play an important role in a different area of medical facilities. With the help of the machine learning model, an effective diagnostic tool can be built which helps in the time of scarcity of medical staff. However medical data is imbalanced and this skew nature of data prevent machine learning algorithm from achieving high accuracy. To deal with this problem of imbalanced data, we proposed a modified decision tree algorithm that uses a minority sensitive Gini index called Mgini. In an imbalanced dataset of COVID-19, it is important to focus on the reduction of overall misclassification cost instead of trying improvement in accuracy value. Mgini is useful splitting criteria when the misclassification cost of the minority sample is huge as compared to the majority class. The use of this proposed new Gini index as a splitting criterion in the decision tree reduces the misclassification cost. Mgini based decision tree has higher accuracy and low misclassification cost as compare to the traditional Gini index based CART algorithm. Our proposed cost-sensitive approach improves imbalanced data classification without the use of data level sampling techniques.","PeriodicalId":50177,"journal":{"name":"Journal of Information Science and Engineering","volume":"22 1","pages":"1097-1108"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81769048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 1

Anti-Spoofing of Live Face Authentication on Smartphone 智能手机实时人脸认证的防欺骗研究

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-01-01 DOI: 10.6688/JISE.20210537(3).0007

Tz-Chia Tseng, Teng-Fu Shih, C. Fuh

引用次数: 0

Building Student Course Performance Prediction Model Based on Deep Learning 基于深度学习的学生课程成绩预测模型构建

IF 1.1 4区计算机科学

Journal of Information Science and Engineering Pub Date : 2021-01-01 DOI: 10.6688/JISE.202101_37(1).0015

J. Kuo, Hao-Ting Chung, Ping-Feng Wang, Baiying Lei

{"title":"Building Student Course Performance Prediction Model Based on Deep Learning","authors":"J. Kuo, Hao-Ting Chung, Ping-Feng Wang, Baiying Lei","doi":"10.6688/JISE.202101_37(1).0015","DOIUrl":"https://doi.org/10.6688/JISE.202101_37(1).0015","url":null,"abstract":"The deferral of graduation rate in Taiwan's universities is estimated 16%, which will affect the scheduling of school resources. Therefore, if we can expect to take notice of students' academic performance and provide guidance to students who cannot pass the threshold as expected, the waste of school resources can effectively be reduced. In this research, the recent years' student data and course results are used as training data to construct student performance prediction models. The K-Means algorithm was used to classify all courses from the freshman to the senior. The related courses will be grouped in the same cluster, which will more likely to find similar features and improve the accuracy of the prediction. Then, this study constructs independent neural networks for each course according to the different academic year. Each model will be pre-trained by using Denoising Auto-encoder. After pre-training, the corresponding structure and weights are taken as the initial value of the neural network model. Each neural network is treated as a base predictor. All predictors will be integrated into an Ensemble predictor according to different years' weights to predict the current student's course performance. As the students finish the course at the end of each semester, the prediction model will continue track and update to enhance model accuracy through online learning.","PeriodicalId":50177,"journal":{"name":"Journal of Information Science and Engineering","volume":"238 1","pages":"243-257"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73263857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 6