Win Kong, M. Saad, M. A. Zulkifley, A. HannanM, A. Hussain
{"title":"Geometrical gait based model for fall detection using thresholding","authors":"Win Kong, M. Saad, M. A. Zulkifley, A. HannanM, A. Hussain","doi":"10.12733/JICS20106973","DOIUrl":"https://doi.org/10.12733/JICS20106973","url":null,"abstract":"","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"335 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131465456","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":"Research of Spatial Data Query Optimization Methods Based on K-Nearest Neighbor Algorithm","authors":"Jie Wu","doi":"10.12733/jics20106985","DOIUrl":"https://doi.org/10.12733/jics20106985","url":null,"abstract":"","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115597713","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 Algebraic-trigonometric Blended Piecewise Curve","authors":"Lanlan Yan, strong, Tao Huang, Rong-Sheng Wen","doi":"10.12733/JICS20150009","DOIUrl":"https://doi.org/10.12733/JICS20150009","url":null,"abstract":"","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123089539","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 Improved Discrete Optimization Algorithm Based on Artificial Fish Swarm and Its Application for Attribute Reduction","authors":"Zhiwei Ni","doi":"10.12733/JICS20105617","DOIUrl":"https://doi.org/10.12733/JICS20105617","url":null,"abstract":"","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115368309","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}
The prediction of Linz-Donawitz Gas (LDG) production and consumption tendency was paramount important in gas balancing and scheduling since it’s an important secondary energy which each process in the steel and iron enterprise needed. Therefore, this paper proposed a prediction method combining curve fitting and GA optimized BP neural network to predict LDG short-term production trend. Specifically, proposed method firstly utilized SVD decomposition to preprocess instantaneous values of LDG production in order to extract a standard type of LDG production during a smelting cycle. Then the standard type was curve fitted to attain function formulas of the overall recovery about time series and meanwhile a series of function clusters and values were procured. Afterwards, GA optimized BP neural network was employed to train parameters of function clusters and thus a recovery trend of LDG during a production period was obtained, which was also called the prediction of short-time production trend. Finally, the actual data from a certain steel and iron enterprise was adopted to verify feasibility and efficiency of the proposed method, the results showed that proposed method had a good performance in predicting short-term LDG generation trend.
{"title":"Short-term Prediction of Linz-Donawitz Gas Generation Tendency Based on SVD-NCF-GA-BP ⋆","authors":"Z. Lv, Ting Li, Zhao Wang, Ziyang Wang","doi":"10.12733/JICS20105771","DOIUrl":"https://doi.org/10.12733/JICS20105771","url":null,"abstract":"The prediction of Linz-Donawitz Gas (LDG) production and consumption tendency was paramount important in gas balancing and scheduling since it’s an important secondary energy which each process in the steel and iron enterprise needed. Therefore, this paper proposed a prediction method combining curve fitting and GA optimized BP neural network to predict LDG short-term production trend. Specifically, proposed method firstly utilized SVD decomposition to preprocess instantaneous values of LDG production in order to extract a standard type of LDG production during a smelting cycle. Then the standard type was curve fitted to attain function formulas of the overall recovery about time series and meanwhile a series of function clusters and values were procured. Afterwards, GA optimized BP neural network was employed to train parameters of function clusters and thus a recovery trend of LDG during a production period was obtained, which was also called the prediction of short-time production trend. Finally, the actual data from a certain steel and iron enterprise was adopted to verify feasibility and efficiency of the proposed method, the results showed that proposed method had a good performance in predicting short-term LDG generation trend.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121339586","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}
Hui Zhang, Peng Zhao, Jian Gao, Chengxiang Zhuge, Xiangming Yao
Transit network design plays a signiflcant role in transit system design and optimization. However, it is di‐cult to flnd an optimal solution on the NP-Hard problem, especially balancing the beneflts between passenger demand and operational cost. Typically, a transit trip includes four steps: walking from dwelling to the station, waiting for the vehicle in the station, traveling in the vehicle and transferring. Considering the four steps and fare, an improved bee colony intelligent algorithm is proposed to settle network design. The results show that our method is e‐cient and can successfully resolve the transit network design.
{"title":"An Effective Intelligent Method for Optimal Urban Transit Network Design","authors":"Hui Zhang, Peng Zhao, Jian Gao, Chengxiang Zhuge, Xiangming Yao","doi":"10.12733/JICS20105667","DOIUrl":"https://doi.org/10.12733/JICS20105667","url":null,"abstract":"Transit network design plays a signiflcant role in transit system design and optimization. However, it is di‐cult to flnd an optimal solution on the NP-Hard problem, especially balancing the beneflts between passenger demand and operational cost. Typically, a transit trip includes four steps: walking from dwelling to the station, waiting for the vehicle in the station, traveling in the vehicle and transferring. Considering the four steps and fare, an improved bee colony intelligent algorithm is proposed to settle network design. The results show that our method is e‐cient and can successfully resolve the transit network design.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127295131","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}
In this paper, we apply the texture conception of natural language to the texture classiflcation, and classify the natural texture into ten classes. Basing on the above, we found a small image library of natural texture. In the thesis, we discuss the common means of texture feature extraction, and bring forward a speciflc algorithm for Gabor fllter. In order to validity of the feature extraction, we adopt the BP network as the classifler to carry out our experiments, which bring us satisfying results.
{"title":"An Algorithm of Texture Classification Based on Feature Extraction and BP Neural Network","authors":"Tongyang Liu, Zongguo Liu, Guoqing Wu","doi":"10.12733/JICS20105651","DOIUrl":"https://doi.org/10.12733/JICS20105651","url":null,"abstract":"In this paper, we apply the texture conception of natural language to the texture classiflcation, and classify the natural texture into ten classes. Basing on the above, we found a small image library of natural texture. In the thesis, we discuss the common means of texture feature extraction, and bring forward a speciflc algorithm for Gabor fllter. In order to validity of the feature extraction, we adopt the BP network as the classifler to carry out our experiments, which bring us satisfying results.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123346850","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}
Con∞ict between software developers and testers is common due to frequent interactions and diverse goals. Such con∞ict often leads to meaningless human struggle and then in∞uences product performance. This paper provides a graph model method to resolve the con∞ict based on the difierent con∞ict management styles (collaborating and dominating) between developers and testers. A case study is used to illustrate the proposed model. The con∞ict model considers the decision makers, the options, and relative preference order. After an in-depth stability analysis, this study conflrms the equilibrium states of con∞ict resolution. Through contrastive analysis of the con∞ict resolution with the graph model method, the study found that collaborating con∞ict management style is a win-win con∞ict resolution for developers and testers. The analytical results closely predict the con∞ict decision and provide valuable insights into the developers and testers’ con∞ict.
{"title":"Resolution of Conflict between Developers and Testers in Software Development: Based on Graph Model Method","authors":"Lianying Zhang, Xiaoyan Huo","doi":"10.12733/JICS20105743","DOIUrl":"https://doi.org/10.12733/JICS20105743","url":null,"abstract":"Con∞ict between software developers and testers is common due to frequent interactions and diverse goals. Such con∞ict often leads to meaningless human struggle and then in∞uences product performance. This paper provides a graph model method to resolve the con∞ict based on the difierent con∞ict management styles (collaborating and dominating) between developers and testers. A case study is used to illustrate the proposed model. The con∞ict model considers the decision makers, the options, and relative preference order. After an in-depth stability analysis, this study conflrms the equilibrium states of con∞ict resolution. Through contrastive analysis of the con∞ict resolution with the graph model method, the study found that collaborating con∞ict management style is a win-win con∞ict resolution for developers and testers. The analytical results closely predict the con∞ict decision and provide valuable insights into the developers and testers’ con∞ict.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125981441","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}
Algebraic Reconstruction Technique (ART) algorithm is the conventional iterative algorithm of concrete ultrasonic CT tomography, it has many shortcomings, such as its calculation accuracy is not high, convergence speed is slow slower, and the peripheral units of abnormal body is affected by abnormal body and so on. An improved algebraic reconstruction technique algorithm based on block iteration is proposed in this paper. The main idea of the new algorithm is to divide the meshes into blocks step by step, and to compute the wave speed of each block by ART algorithm, put the wave speed of next higher level units as the iterative initial value of next lower level units. Do this process until each block can not be divided any more. Through continuous division block unit, finally reach the purpose of rebuilding the structure image of test area in concretes. Computer simulation and concrete model of ultrasonic computerized tomography show that ART algorithm based on block iteration is capable of reconstructing moderate, improving precision of computing, and weakening the influence caused by abnormal area.
{"title":"Application of Improved ART Algorithm in Concrete Ultrasonic Imaging","authors":"Yao Fan","doi":"10.12733/JICS20105576","DOIUrl":"https://doi.org/10.12733/JICS20105576","url":null,"abstract":"Algebraic Reconstruction Technique (ART) algorithm is the conventional iterative algorithm of concrete ultrasonic CT tomography, it has many shortcomings, such as its calculation accuracy is not high, convergence speed is slow slower, and the peripheral units of abnormal body is affected by abnormal body and so on. An improved algebraic reconstruction technique algorithm based on block iteration is proposed in this paper. The main idea of the new algorithm is to divide the meshes into blocks step by step, and to compute the wave speed of each block by ART algorithm, put the wave speed of next higher level units as the iterative initial value of next lower level units. Do this process until each block can not be divided any more. Through continuous division block unit, finally reach the purpose of rebuilding the structure image of test area in concretes. Computer simulation and concrete model of ultrasonic computerized tomography show that ART algorithm based on block iteration is capable of reconstructing moderate, improving precision of computing, and weakening the influence caused by abnormal area.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114643320","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}
Time series analysis and genetic algorithm have a good application in many flelds. In present paper, we utilized graph theory, and established a multi-objective optimal water distribution model according to current situation in China. Then, we utilized time series analysis to predict water supply and demand situation, and put forward an improved genetic algorithm solution for optimal water resources strategy. Furthermore, sensitivity and efiectivity of the improved genetic algorithm is flt to resolve the model. This method can be extended to other various resources-distribution flelds.
{"title":"A Multi-objective Optimal Water Strategy Using Time Series Analysis and Improved Genetic Algorithm","authors":"Changqing Lai, Zheng Xu, Yuning Jiang","doi":"10.12733/JICS20105730","DOIUrl":"https://doi.org/10.12733/JICS20105730","url":null,"abstract":"Time series analysis and genetic algorithm have a good application in many flelds. In present paper, we utilized graph theory, and established a multi-objective optimal water distribution model according to current situation in China. Then, we utilized time series analysis to predict water supply and demand situation, and put forward an improved genetic algorithm solution for optimal water resources strategy. Furthermore, sensitivity and efiectivity of the improved genetic algorithm is flt to resolve the model. This method can be extended to other various resources-distribution flelds.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125649120","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}
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