{"title":"ICIS 2018 Index","authors":"","doi":"10.1109/icis.2018.8466536","DOIUrl":"https://doi.org/10.1109/icis.2018.8466536","url":null,"abstract":"","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"7 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":"123063144","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}
{"title":"Speech Recognition of Confusable Word Based on Ideal Distance Matrix","authors":"Qiang Gao, Shutao Sun","doi":"10.1109/ICIS.2018.8466413","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466413","url":null,"abstract":"In order to improve the recognition efficiency of classical DTW algorithm in speech recognition of confusable word, a new method for recognition of confusable word is proposed in this paper. The distance between the measured speech and the template speech is calculated by the general distance matrix and the ideal state distance matrix. The Offset-Loss is introduced and it is used to evaluate the similarity between the measured speech and the template speech. The experimental results show that it improves the matching speed and the accuracy of the improved algorithm is almost the same as the classical DTW algorithm.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"55 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":"123068171","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}
{"title":"ICIS 2018 Title Page","authors":"","doi":"10.1109/icis.2018.8466441","DOIUrl":"https://doi.org/10.1109/icis.2018.8466441","url":null,"abstract":"","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"85 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":"126258656","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}
{"title":"Parametric Representation of Voiced Speech Phoneme using Multicomponent AM Signal Model","authors":"M. Bansal, P. Sircar","doi":"10.1109/ICIS.2018.8466519","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466519","url":null,"abstract":"In this paper, the amplitude modulated (AM) sinusoidal signal model is used for parametric modelling of speech signal. The multicomponent AM sinusoidal signal model is found to be well suited for voiced speech phonemes. The Fourier-Bessel (FB) expansion is used to separate individual components of a multicomponent signal. Parameter estimation of the AM sinusoidal signal model is presented in detail. The cyclo-stationary analysis is used for frequency estimation of the AM sinusoidal signal with high accuracy under noisy signal condition. The symmetric Itakura-Saito (IS-COSH) distance measure is used for comparison of original and reconstructed signals.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"34 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120913023","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}
{"title":"Fake Accounts Detection on Twitter Using Blacklist","authors":"M. Swe, Nyein Nyein Myo","doi":"10.1109/ICIS.2018.8466499","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466499","url":null,"abstract":"Social networking sites such as Twitter, Facebook, Weibo etc. are extremely mainstream today. Also, the greater part of the malicious users utilize these sites to persuade legitimate users for different purposes, for example, to promote their products item, to enter their spam links, to stigmatize other persons and so forth. An ever increasing number of users are utilized these social networking sites and fake accounts on these destinations are turned into a major issue. In this paper, fake accounts are detected using blacklist instead of traditional spam words list. Blacklist is created by using topic modeling approach and keyword extraction approach. We conduct an evaluation experiment with not only 1KS - 10KN dataset but also Social Honeypot dataset. The accuracy of the traditional spam words list based approach and our blacklist based approach are compared. Decorate, a meta-learner classifier is applied for classifying fake accounts on Twitter from legitimate accounts. Our approach achieves 95.4% accuracy and true positive rate is 0.95.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"20 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":"121643441","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}
{"title":"Quality Inspection of Size, Shape and Arrangement of Sweet Corn Seeds by Image Processing","authors":"Monlica Wattana, Thichakorn Phonarin, Ubon Ketnork","doi":"10.1109/ICIS.2018.8466509","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466509","url":null,"abstract":"This article proposes the techniques for inspecting the quality of sweet corn using image processing. The size, shape and arrangement of sweet corn kernels were considered in quality inspection. The measurement of the size of sweet corn was done by measuring the distance between the two endpoints of the sweet corn image. The shape of the sweet corn was examined by the symmetry of the sweet corn. In order to determine the arrangement of the kernels, the edges of the image were figured out by Laplacian of Gaussian which was then used to calculate the uniformity of the distance between lines. The experimental results showed that, the size of sweet corn, the average error was 0.18 cm and the shape and the symmetry of corn cob and the arrangement of the corn kernels were correct.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"64 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113961047","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}
{"title":"An Evaluation Algorithm for the Complexity of Distributed 3D Rendering","authors":"Jiyu Mao, Shuang Feng","doi":"10.1109/ICIS.2018.8466529","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466529","url":null,"abstract":"In order to solve the problem of the consuming resources of animation, the idea of distributed rendering is proposed. This paper from the stand of the distributed rendering, emphasized the importance of the evaluation of rendering task’s complexity quantitative through the analysis of the distributed rendering system architecture. In this paper, we proved three factors include the visual number of Triangular face, the pixel of the output image and the complexity of the object motion in the scene have important impact on the rendering time by analyzing the results of experiment. At the same time, a method based on the above three factors is proposed to evaluate the complexity of rendering task. The algorithm proposed is helpful for the optimal dynamic task assignment scheme and the construction of distributed system architecture.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"48 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":"128149343","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}
Kazi Kowshin Raihana, Syed Mosahid Khurshid Rishad, T. Sadia, Sarfaraz Ahmed, M. S. Alam, R. Rahman
{"title":"Identifying Flood Prone Regions in Bangladesh by Clustering","authors":"Kazi Kowshin Raihana, Syed Mosahid Khurshid Rishad, T. Sadia, Sarfaraz Ahmed, M. S. Alam, R. Rahman","doi":"10.1109/ICIS.2018.8466533","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466533","url":null,"abstract":"Bangladesh suffers more for being susceptible to flood driven loses than relishing the natural advantages of being a riverine country. It is crucial for flood management department to identify the severity of flood and the factors behind it. Though three main contributors to flood occurrences are the Brahmaputra, Ganges and Meghna river basins, there are several factors such as rainfall, location, elevation and many more that also has prominent influences in causing flood in different regions of Bangladesh. This paper intends to identify the flood condition of different regions of Bangladesh by implementing different clustering techniques such as K-means, Expectation Maximization and Agglomerative Hierarchical clustering algorithm. This paper aims not only to analyze the factors that lead to flood condition but also observe the effectiveness of applying the chosen clustering methods for further analysis.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"30 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":"134140597","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}
{"title":"A Fast and Simple Model in Practice for Ranking","authors":"Weijian Fan, Wen Liu, Jing An, Yongbin Wang","doi":"10.1109/ICIS.2018.8466506","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466506","url":null,"abstract":"Recent work has shown success in using neural network as ranking model in question answering(QA). While the precision of these models has increased significantly over time, most models need long training time, which leads to it cannot be used effectively in practical applications. In this paper, we propose a simple model to accelerate training speed with noise-contrastive estimation. This model mainly inspired by an architecture based entirely on convolutional neural networks and noise-contrastive estimation. We investigate the behavior of the model on the financial dataset which we use in practice and show that it reduces the training times by more than an order of magnitude without affecting the quality of the resulting models. The model is also more efficient and more stable than importance sampling because it requires fewer noise samples to perform well.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"28 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":"122187230","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}
{"title":"Comprehensive Evaluation Research on Farmer Entrepreneurship Based on Poverty Alleviation","authors":"Xianhong Xu, R. Han","doi":"10.1109/ICIS.2018.8466386","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466386","url":null,"abstract":"Based on economics and entrepreneurship theory, this paper has analyzed influence factors of famer entrepreneurship under the background of targeted poverty alleviation from \"three bodies one agent\". And then, it reported farmer entrepreneur' current situation and built farmer entrepreneurship evaluation index system. Using fuzzy mathematics analytical method and MATLAB software, this paper did not only conduct evaluation analysis on farmer entrepreneurship in Qixian County, Henan Province, but reflected the overall ability of farmer entrepreneurship in this town.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"39 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":"125360961","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}