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2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)最新文献

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A New Algorithm to Compute Single Source Shortest Path in a Real Edge Weighted Graph to Optimize Time Complexity 一种计算实边加权图中单源最短路径优化时间复杂度的新算法
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466444
Fahim Ahmed, Fahim Anzum, M. Islam, Wali Mohammad Abdullah, Sazid Al Ahsan, Moneruzzaman Rana
{"title":"A New Algorithm to Compute Single Source Shortest Path in a Real Edge Weighted Graph to Optimize Time Complexity","authors":"Fahim Ahmed, Fahim Anzum, M. Islam, Wali Mohammad Abdullah, Sazid Al Ahsan, Moneruzzaman Rana","doi":"10.1109/ICIS.2018.8466444","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466444","url":null,"abstract":"A prime concern of a Shortest-Path problem is to handle any real edge weight values whether it is positive or negative with the feature of negative weight cycle detection if exists. Number of single source shortest-path algorithms are available that can handle negative weight cycle, where the most stable algorithm till date executes with polynomial time complexity. In this paper, an algorithm is proposed for graphs with real edge weights to solve single source shortest path problem with the feature of negative weight cycle detection in order to optimize time complexity. The time complexity analysis and proof of correctness confirmed that, for graph with identical configuration, the proposed algorithm provides faster and accurate solutions with quasilinear time complexity than the existing algorithm that comes out with the same solution with a polynomial time complexity.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134093287","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: 2
Color Image Enhancement with Preservation of Gamut Range 保留色域范围的彩色图像增强
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466453
M. Maw, Renu
{"title":"Color Image Enhancement with Preservation of Gamut Range","authors":"M. Maw, Renu","doi":"10.1109/ICIS.2018.8466453","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466453","url":null,"abstract":"Color image enhancement plays a key role in digital image processing more than grayscale image enhancement due to its wide color expressions with three perceptual attributes including hue, saturation and intensity of an image. It has been a popular research since many recent years but it is still an open issue in order to enhance the color for low intensity, blurred or incomplete images, etc. This paper proposes a color enhancement algorithm with an affine algorithm for enhancing illumination in gamut preserving color image enhancement. The proposed method firstly uses non-linear sigmoidal function for luminance enhancement while an improved histogram specification model is used to preserve gamut of an input image. The proposed algorithm is experimented with low intensity images obtained from standard image datasets which are compared with quite popular image enhancement methods. According to the experimental results, the proposed method produces less error rate than other models.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132345014","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: 2
Identify Key Factors for Career Choice by Using TOPSIS and Fuzzy Cognitive Map 运用TOPSIS和模糊认知图识别职业选择的关键因素
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466384
Yu-Tso Chen, Wenzhi Peng, Hsin-Yu Yu
{"title":"Identify Key Factors for Career Choice by Using TOPSIS and Fuzzy Cognitive Map","authors":"Yu-Tso Chen, Wenzhi Peng, Hsin-Yu Yu","doi":"10.1109/ICIS.2018.8466384","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466384","url":null,"abstract":"Many career surveys report that nearly half of high school and college students in Taiwan are not sure what their future career will be. This is a serious issue regarding to career choice and planning. In order to solve this problem, this paper introduces a study integrating the typical and atypical factors to build a comprehensive factor model for better career matching. Through exploring the relationship between typical factors, atypical factors and occupational items, as well as leveraging the operations of TOPSIS and Fuzzy Cognitive Map (FCM), the proposed model identifies the key factors for career choice. The research results can not only indicate a valuable research field towards career counseling and human resource planning, but also can benefit the design and implementation of an operational career prediction system in the future.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129202324","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: 4
Automatic Categorization of Traditional Clothing Using Convolutional Neural Network 基于卷积神经网络的传统服装自动分类
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466523
M. Nawaz, Rasik Hasan, Md Abid Hasan, Mahadi Hassan, R. Rahman
{"title":"Automatic Categorization of Traditional Clothing Using Convolutional Neural Network","authors":"M. Nawaz, Rasik Hasan, Md Abid Hasan, Mahadi Hassan, R. Rahman","doi":"10.1109/ICIS.2018.8466523","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466523","url":null,"abstract":"The research proposes an approach that can automatically classify real world pictures of some traditional clothing worn in Bangladesh into the predefined classes using Convolutional Neural Networks (CNN). The research is driven by considering the growing market of online shops in mind. For classification purpose, we have collected clothing images from several online stores and labeled them accordingly. Our CNN model is based on the Google Inception model. For comparison purposes we have tried several architectures of CNN and some variations to see how our model perform against them. We have tested our own model with three different optimizers – SGD, Adam and RmsProp. Among these optimizers, RmsProp performed the best. The final result shows our model could classify the images of the training and testing set with 92.05% and 89.22% accuracy respectively.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133800873","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: 5
Research on LDA Model Algorithm of News-oriented Web Crawler 面向新闻的网络爬虫LDA模型算法研究
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466502
Yuxin Wang, Zhiguo Hong, Minyong Shi
{"title":"Research on LDA Model Algorithm of News-oriented Web Crawler","authors":"Yuxin Wang, Zhiguo Hong, Minyong Shi","doi":"10.1109/ICIS.2018.8466502","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466502","url":null,"abstract":"With fast development of big data, the data quantities and information types on the webpage are increasing tremendously. Consequently, it is becoming more difficult for users to obtain the valuable and interesting data and information from the webpage. The paper designs and implements a topic-focused crawler which utilizes Nodejs lightweight directional crawler to capture the data with great improvement on the efficiency of page retrievals.Firstly, the design idea and flow of the web crawler project is introduced. Furthermore, on the basis of crawled data jieba package of python is used to achieve text participle. Finally, LDA model algorithm is used to classify keyword texts to reach the purpose of classifying different types of news.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132924498","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
Smart Self Position Aligning Chair for a Modern Conference Room 用于现代会议室的智能自定位椅
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466430
Fahim Anzum, Fahim Ahmed, M. Azim, Mosaddek Hossain, S. Zaman, Farhan Hasib, Sazid Al Ahsan
{"title":"Smart Self Position Aligning Chair for a Modern Conference Room","authors":"Fahim Anzum, Fahim Ahmed, M. Azim, Mosaddek Hossain, S. Zaman, Farhan Hasib, Sazid Al Ahsan","doi":"10.1109/ICIS.2018.8466430","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466430","url":null,"abstract":"We are surrounded by the blessings of modern technologies and smart systems that facilitate our everyday lives by getting us interacted with the advanced computing systems, automation, artificial intelligence and so on. The world has seen an outburst of smart devices in the last decade. To keep a significant contribution to the modern technological use, our proposed model adds to the growing need of smart systems. In this paper, a design of self-position aligning chair incorporated with the features of self-parking autonomous robot has been proposed. It reduces both human efforts and time consumption in the process of furnishing and decorating a conference room. Experimental results showed that the proposed model is more cost effective and affordable than the likely systems available till date. This work modernizes our lifestyles by reducing human efforts, saving time and also by maintaining more decorative working places.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115479739","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: 2
ICIS 2018 TOC
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/icis.2018.8466508
{"title":"ICIS 2018 TOC","authors":"","doi":"10.1109/icis.2018.8466508","DOIUrl":"https://doi.org/10.1109/icis.2018.8466508","url":null,"abstract":"","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116400861","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: 0
A Positive Real Order Strengthening Buffer Operator and Its Application in Data Prediction 一种正实阶强化缓冲算子及其在数据预测中的应用
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466520
Ying-Jian Qi, Zheng-peng Wu, L. Wu, Xiaomei Liu
{"title":"A Positive Real Order Strengthening Buffer Operator and Its Application in Data Prediction","authors":"Ying-Jian Qi, Zheng-peng Wu, L. Wu, Xiaomei Liu","doi":"10.1109/ICIS.2018.8466520","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466520","url":null,"abstract":"Buffer operator in grey system prediction model can help to balance the influence of disturbance components and the parameter estimation tracking speed. It can also improve the prediction precision. Some famous buffer operators have been proposed such as Average Strengthening Buffer operator, Arithmetic Average Strengthening Buffer operator and so on. They can be viewed as integer-order buffer operators from the accumulative system opinion. We try to extend them into positive real order and construct the corresponding strengthening buffer operators in this paper. The calculation results show that the proposed buffer operator can improve the prediction accuracy effectively.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116675545","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: 0
People Counting System with C-Deep Feature in Dense Crowd Views 稠密人群视图中具有C-Deep特征的计数系统
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466440
Htet Htet Lin, K. Win
{"title":"People Counting System with C-Deep Feature in Dense Crowd Views","authors":"Htet Htet Lin, K. Win","doi":"10.1109/ICIS.2018.8466440","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466440","url":null,"abstract":"People counting in a crowded scene is an urgent and vital task of monitoring the surveillance systems. Accrual guesses of a dense crowd views are effected from a different illuminations and inter-class variations, so comes to be a complicated issue and still remains as an active research area. To tackle this fact, this paper establishes an effective people counting framework in dense crowd views that automatically appraisals the accurate number of people. In this paper, a new intuition Color Deep system which utilizes based on the color-based feature and convolutional neural network (CNN)-based feature is proposed for detecting and estimating the people numbers. Unlike the other, this paper proposes C-Deep feature by contributing the color transformation matrix and segmentation. Firstly, the color transformation matrix is introduced and then C-Deep features is calculated by using the Deep CNN with color feature matrix to handle the occlusion, inter-class variations and density levels. Calculation experiments on the challenging public crowd counting dataset achieve the lowest miss rate than state-of-the-art results. This shows the effectiveness of the proposed framework.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115696963","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: 1
Classification Based on Spectral Characterization and Analysis of Land Cover Change in Dhaka 基于光谱特征的达卡土地覆盖变化分类与分析
2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466545
Farhan Rahman Wasee, Asif Amin, Zareen Tasnim Raisa, Sadia Chowdhury, Tanisha Nourin Alam, R. Rahman
{"title":"Classification Based on Spectral Characterization and Analysis of Land Cover Change in Dhaka","authors":"Farhan Rahman Wasee, Asif Amin, Zareen Tasnim Raisa, Sadia Chowdhury, Tanisha Nourin Alam, R. Rahman","doi":"10.1109/ICIS.2018.8466545","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466545","url":null,"abstract":"This study focuses on the temporally evolving geo-environmental characteristics of Dhaka. Dhaka is located at the center of Bangladesh. In the last few decades, it has undergone rapid development in terms of infrastructure and economy. The land use pattern in Dhaka is not the same as it had been previously. The focus has been to analyze the changes that have occurred in Dhaka, which consists of six smaller cities inside it. Using remote sensing techniques and various satellite images, the objects are classified into different categories. Multi spectral characteristics and spectral response patterns are analyzed and studied. Using the information extracted across different decades, changes in land use have been derived. Furthermore, changes in different features e.g. built up, crops, water bodies etc. are analyzed and studied across years to factor out the zones that are experiencing recent urban growth. This generalized pattern of urban growth can be a valuable finding for urban planning and policy for the government of Bangladesh.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123379708","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: 2
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