{"title":"Outlier degree estimation in various sensor data for building maintenance using K-means clustering and Markov model","authors":"K. Aoki","doi":"10.4156/AISS.VOL5.ISSUE7.108","DOIUrl":"https://doi.org/10.4156/AISS.VOL5.ISSUE7.108","url":null,"abstract":"There are many sensors in a building. Those sensors gather huge amount of various data in every hour. The data must show some failures in the building. However, the amount of data prevents from utilizing the sign. The variety of the sensors makes difficult to uniform processing over all data. This paper discusses the uniform processing method over various sensor data in buildings using K-means clustering and Markov model.","PeriodicalId":247895,"journal":{"name":"The 3rd International Conference on Data Mining and Intelligent Information Technology Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125677735","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":"Towards discovering and predicting technical opportunities and technology trends","authors":"Hanmin Jung, Won-Kyung Sung","doi":"10.4156/AISS.VOL4.ISSUE11.19","DOIUrl":"https://doi.org/10.4156/AISS.VOL4.ISSUE11.19","url":null,"abstract":"This paper introduces an information service system named InSciTe Advanced with text/predictive analytics abilities. It especially aims at discovering and predicting technical opportunities and technology trends to improve user's task performance in the long run. One multiple target solution and five single target solutions of the system enable users to properly make decisions in R&D strategic planning. After all, our system can enhance the usefulness of conventional information systems and furthermore make move on to the next level of value pyramid.","PeriodicalId":247895,"journal":{"name":"The 3rd International Conference on Data Mining and Intelligent Information Technology Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126508354","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":"Enhancing parallel data mining performance on a large cluster using UCE scheduling","authors":"N. Benjamas, P. Uthayopas","doi":"10.4156/JNIT.VOL2.ISSUE4.7","DOIUrl":"https://doi.org/10.4156/JNIT.VOL2.ISSUE4.7","url":null,"abstract":"In this paper, we propose an algorithm called Unified Communication and Execution Scheduling (UCE) that combines the execution and communication scheduling for parallel data mining application together. This algorithm enables a better utilization of hardware and interconnection in a multicore cluster system for the data mining application. The idea is to choose a proper task execution sequence combine with a communication scheduling that avoids the communication conflict in the interconnection network switch. The simulation results show that a substantial performance improvement can be obtained especially with the large multicore cluster systems.","PeriodicalId":247895,"journal":{"name":"The 3rd International Conference on Data Mining and Intelligent Information Technology Applications","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129421549","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":"Forecasting analysis for global copper clad laminate market","authors":"Yu-Yao Hsiao, Fu‐Kwun Wang","doi":"10.4156/JCIT.VOL7.ISSUE3.29","DOIUrl":"https://doi.org/10.4156/JCIT.VOL7.ISSUE3.29","url":null,"abstract":"Demand forecasting is one of critical reference by top managers to make the strategy decision for future investment. The copper clad laminate(CCL) is the key material for print circuit board(PCB) and it can apply for consumer, computer, LCD, communication, automotive, aero space, medicine and defense application. The total global sale for PCB in 2008 is US$ 48.2 billion. In this research, we use grey model GM(1,1), rolling grey model(RGM) and Bass diffusion model to analysis global CCL market by six market segments — paper, composite, FR-4, FR-4 High Tg, FR-4 halogen free, Specialty between 2001–2008. The forecasting accuracy of global CCL market by six market segment was evaluated along with mean absolute percentage error(MAPE). In this study, Bass diffusion model MAPE outperforms the others two models GM(1,1) and RGM for this global CCL market forecasting analysis and is recommend for global CCL market forecasting analysis.","PeriodicalId":247895,"journal":{"name":"The 3rd International Conference on Data Mining and Intelligent Information Technology Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130645263","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}