Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011760
Shyr-Shen Yu, C. Chiu, Chia-Chi Liu, Y. Chan, M. Tsai
An excersice prescription is a professionally designed excersice plan for improving one's health according to the results of his health-related physical fitness (HRPF) tests. Traditionally, an excersice prescription is formulated by manually checking the norm-referenced chart of HRPF; however, it is time consuming and a highly specialized and experienced expert on health-related physical fitness testing is needed to formulate this prescription. To solve above problems, it is necessary to develope an automatic excersice prescription formulating scheme for categorizing the measured data of HRPF tests and then assign the best appopriate excersice prescription for each class. In this study, a two-layer classifier, integrating the techiques of K-means clustering algorithm and genetic algorithm, is hence propsed to classify the measured data of HRPF tests and provide the best appopriate excersice prescription for each class. When the data variance within one class is very large, the centroid of the class cannot effectively represent each datum in the class. The two-layer classifier therefore partitions each class into several clusters (subclasses) and then classifiy the measured data of HRPF tests into clusters. In this study, a genetic algorithm is provided to determine the number of clusters, which each class should be separated into, and the best suitable values of the parameters used in the two-layer classifier. The experimental results demonstrate that the two-layer classifier can effectively and efficiently classify the measured data of HRPF tests and design excersice plan.
{"title":"Exercise prescription formulating scheme based on a two-layer K-means classifier","authors":"Shyr-Shen Yu, C. Chiu, Chia-Chi Liu, Y. Chan, M. Tsai","doi":"10.1109/INDCOMP.2014.7011760","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011760","url":null,"abstract":"An excersice prescription is a professionally designed excersice plan for improving one's health according to the results of his health-related physical fitness (HRPF) tests. Traditionally, an excersice prescription is formulated by manually checking the norm-referenced chart of HRPF; however, it is time consuming and a highly specialized and experienced expert on health-related physical fitness testing is needed to formulate this prescription. To solve above problems, it is necessary to develope an automatic excersice prescription formulating scheme for categorizing the measured data of HRPF tests and then assign the best appopriate excersice prescription for each class. In this study, a two-layer classifier, integrating the techiques of K-means clustering algorithm and genetic algorithm, is hence propsed to classify the measured data of HRPF tests and provide the best appopriate excersice prescription for each class. When the data variance within one class is very large, the centroid of the class cannot effectively represent each datum in the class. The two-layer classifier therefore partitions each class into several clusters (subclasses) and then classifiy the measured data of HRPF tests into clusters. In this study, a genetic algorithm is provided to determine the number of clusters, which each class should be separated into, and the best suitable values of the parameters used in the two-layer classifier. The experimental results demonstrate that the two-layer classifier can effectively and efficiently classify the measured data of HRPF tests and design excersice plan.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122674057","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011750
Wen-Chang Cheng
In this study, we proposed a multi-piecewise thinning description method. Thinning is a preprocessing technology often applied in the fields of binary image processing; it is used to transform thick elements in an image into lines with a single pixel width. Because lines include closed and open lines, an effective description method is required for post-processing procedures. Regarding the proposed method, branch points of thinning lines are first identified and used as a basis for segmenting the lines, which are originally connected, into multiple line segments. Subsequently, we employed the find contour function available in the OpenCV library to describe the coordinates of the contours of the line segments. The starting and endpoints of closed lines can be directly obtained using the contour results of closed lines. By contrast, the starting and endpoints of open lines are achieved by first using turning points to confirm the position of line-end points and employing the adjacent pixels of the line-end and branch points before the contour results of open lines can be used. The experimental results indicated that the proposed method effectively achieved accurate descriptions for thinned lines.
{"title":"The development of a multi-piecewise-based thinning description method","authors":"Wen-Chang Cheng","doi":"10.1109/INDCOMP.2014.7011750","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011750","url":null,"abstract":"In this study, we proposed a multi-piecewise thinning description method. Thinning is a preprocessing technology often applied in the fields of binary image processing; it is used to transform thick elements in an image into lines with a single pixel width. Because lines include closed and open lines, an effective description method is required for post-processing procedures. Regarding the proposed method, branch points of thinning lines are first identified and used as a basis for segmenting the lines, which are originally connected, into multiple line segments. Subsequently, we employed the find contour function available in the OpenCV library to describe the coordinates of the contours of the line segments. The starting and endpoints of closed lines can be directly obtained using the contour results of closed lines. By contrast, the starting and endpoints of open lines are achieved by first using turning points to confirm the position of line-end points and employing the adjacent pixels of the line-end and branch points before the contour results of open lines can be used. The experimental results indicated that the proposed method effectively achieved accurate descriptions for thinned lines.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114427362","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011746
Ryota Hanyu, Kazuki Murakami, Qiangfu Zhao
Recently, many kinds of cloud computing based services are provided and they are becoming more and more popular. But we think it is an urgent problem to improve the security of cloud services especially for storage services because the number of cyber-attacks is increasing. Currently, our research group proposed an image morphing based technology for improving the security of cloud services. This technology provides a novel way both for encrypting and for hiding secret information. In this paper, we verify and discuss about the vulnerability of the proposed technology, and suggest possible methods for further improvement.
{"title":"Verification of an image morphing based technology for improving the security in cloud storage services","authors":"Ryota Hanyu, Kazuki Murakami, Qiangfu Zhao","doi":"10.1109/INDCOMP.2014.7011746","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011746","url":null,"abstract":"Recently, many kinds of cloud computing based services are provided and they are becoming more and more popular. But we think it is an urgent problem to improve the security of cloud services especially for storage services because the number of cyber-attacks is increasing. Currently, our research group proposed an image morphing based technology for improving the security of cloud services. This technology provides a novel way both for encrypting and for hiding secret information. In this paper, we verify and discuss about the vulnerability of the proposed technology, and suggest possible methods for further improvement.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117249876","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011756
Min-Hsuan Fan, En-Chih Liao, Mu-Yen Chen
In this study, we used the Google Trends as a prediction tool to predict the investors' behavior and its impact on stock market. In the behavior and social perspective, more and more Internet users use Google Trends as the search engine to surf on the websites every day. Therefore, these search actions can be seen as personal votes because Internet users often search items they are interested in. Based on this motivation, this study wanted to investigate the relationship between Internet search and Taiwan Stock Exchange Weighted Index. Finally, this study provides the investors a different approach from fundamental analysis and technical analysis. It offers a more understandable reference standard to investors new to the stock market. For investors who are good at fundamental analysis and technical analysis, it can be also used as a reference subject.
{"title":"A TAIEX forecasting model based on changes of keyword search volume on Google Trends","authors":"Min-Hsuan Fan, En-Chih Liao, Mu-Yen Chen","doi":"10.1109/INDCOMP.2014.7011756","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011756","url":null,"abstract":"In this study, we used the Google Trends as a prediction tool to predict the investors' behavior and its impact on stock market. In the behavior and social perspective, more and more Internet users use Google Trends as the search engine to surf on the websites every day. Therefore, these search actions can be seen as personal votes because Internet users often search items they are interested in. Based on this motivation, this study wanted to investigate the relationship between Internet search and Taiwan Stock Exchange Weighted Index. Finally, this study provides the investors a different approach from fundamental analysis and technical analysis. It offers a more understandable reference standard to investors new to the stock market. For investors who are good at fundamental analysis and technical analysis, it can be also used as a reference subject.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128108392","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011741
John M. Medellin
Software Configuration Management auditing is the fourth of four sub processes recommended by the IEEE and the ACM in the area of SCM. Little guidance is offered in the area of estimation. This paper proposes an initial model for estimating overall system Configuration Items size and effort that might be required to execute the audit. The model is built from formulae and other input from other studies of Empirical Software Engineering and is therefore theoretical. A second part of the study tests the sensitivity to the parameters of white box/structural testing, organizational competence in CMMi level 3 and above and usage of automation in SCM auditing. It is an initial study aimed at discovering the extent of potential impact of certain environment characteristics on the level of effort required to execute the audit.
{"title":"A model for estimating SCM audit effort with key characteristic sensitivity analysis","authors":"John M. Medellin","doi":"10.1109/INDCOMP.2014.7011741","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011741","url":null,"abstract":"Software Configuration Management auditing is the fourth of four sub processes recommended by the IEEE and the ACM in the area of SCM. Little guidance is offered in the area of estimation. This paper proposes an initial model for estimating overall system Configuration Items size and effort that might be required to execute the audit. The model is built from formulae and other input from other studies of Empirical Software Engineering and is therefore theoretical. A second part of the study tests the sensitivity to the parameters of white box/structural testing, organizational competence in CMMi level 3 and above and usage of automation in SCM auditing. It is an initial study aimed at discovering the extent of potential impact of certain environment characteristics on the level of effort required to execute the audit.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123659763","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011743
Joseph C. Tsai, N. Yen, Takafumi Hayashi
Renewable energy is an important research issue in recent years, it's also regarded by most of the governments in the world. In order to manage or employ the power well, the aspect of smart gird is proposed to process many kinds of situations renewable energy. Power scheduling is one of the focal points in this research field. By this work, users can understand the volume of power consumption and decide a finer province electricity plan. Based on this concept, renewable energy generation prediction is the approach to enhance the power scheduling and performance of power using. We propose a prediction approach by the theory of social networking and machine learning. We use the SVM, its kernel is RBF, to process the power generation prediction by weather forecasts. The social networking is used to improve the accuracy of the prediction. In the experimental result, the accuracy rate is showed with the excellent results.
{"title":"Social network based smart grids analysis","authors":"Joseph C. Tsai, N. Yen, Takafumi Hayashi","doi":"10.1109/INDCOMP.2014.7011743","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011743","url":null,"abstract":"Renewable energy is an important research issue in recent years, it's also regarded by most of the governments in the world. In order to manage or employ the power well, the aspect of smart gird is proposed to process many kinds of situations renewable energy. Power scheduling is one of the focal points in this research field. By this work, users can understand the volume of power consumption and decide a finer province electricity plan. Based on this concept, renewable energy generation prediction is the approach to enhance the power scheduling and performance of power using. We propose a prediction approach by the theory of social networking and machine learning. We use the SVM, its kernel is RBF, to process the power generation prediction by weather forecasts. The social networking is used to improve the accuracy of the prediction. In the experimental result, the accuracy rate is showed with the excellent results.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124011383","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011755
C. Hsieh, Chih-Tsung Chen, Yu-sheng Lin
Recently, a single image haze removal scheme based on dark channel prior (DCP) is presented in [1] and is getting popular because of its satisfactory performance for most of cases. However, the DCP scheme has at least three problems: halos, high computational cost and over-exposure. In our previous paper [2], a dehazing algorithm with dual dark channels was presented where high computational cost and over-exposure problems are relieved. In this paper, the objective of proposed dehazing algorithm (PDA) is to relieve the three problems in [1] simultaneously. Four examples are given to verify the PDA where comparison with the DCP scheme is made as well. The simulation results indicate that the PDA is 87.87 times, on average, faster than the DCP in the given examples. Besides, in general better color situation is found for the PDA with similar visual quality and without the three problems in the DCP scheme.
{"title":"Adaptive fast image dehazing algorithm","authors":"C. Hsieh, Chih-Tsung Chen, Yu-sheng Lin","doi":"10.1109/INDCOMP.2014.7011755","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011755","url":null,"abstract":"Recently, a single image haze removal scheme based on dark channel prior (DCP) is presented in [1] and is getting popular because of its satisfactory performance for most of cases. However, the DCP scheme has at least three problems: halos, high computational cost and over-exposure. In our previous paper [2], a dehazing algorithm with dual dark channels was presented where high computational cost and over-exposure problems are relieved. In this paper, the objective of proposed dehazing algorithm (PDA) is to relieve the three problems in [1] simultaneously. Four examples are given to verify the PDA where comparison with the DCP scheme is made as well. The simulation results indicate that the PDA is 87.87 times, on average, faster than the DCP in the given examples. Besides, in general better color situation is found for the PDA with similar visual quality and without the three problems in the DCP scheme.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129442903","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}
Recently, in Internet of Things field, cooperation between smartphone and home appliances becomes important and popular. Especially, smart phones equipped with Bluetooth4.0 can reduce the power consumption, increase connectable devices, and promote the cooperation between things and smart terminals. Currently, many smartphone-based control system for home appliances have appeared by combining 3G and Wi-Fi technology. However, the problem of using Wi-Fi is big power consumption, and difficult for minimization. In addition, some methods adopt Infrared in smartphone to control appliances. But many smartphones have no Infrared ready, and have to set up many processes to use. Compared with the above approaches, BLE can resolve those problems. BLE has the advantages of low-power consumption, minimization, and ready reminding service. In this paper, we develop a smartphone-based appliance control system based on BLE. The system has a dynamic control menu that can scan any appliance around a user at anywhere. Meanwhile, we develop a device named “Middle-Device” for the communication between smartphone and appliances using Arduino, because Arduino is popular, easy to be used for hardware programming, and better extensibility by attaching a function board called “Shield” with many functions such as Wi-Fi, ZigBee, Bluetooth, and etc.
{"title":"Development of a control system for home appliances based on BLE technique","authors":"Hideki Matsuoka, Junbo Wang, Lei Jing, Yinghui Zhou, Yilang Wu, Zixue Cheng","doi":"10.1109/INDCOMP.2014.7011751","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011751","url":null,"abstract":"Recently, in Internet of Things field, cooperation between smartphone and home appliances becomes important and popular. Especially, smart phones equipped with Bluetooth4.0 can reduce the power consumption, increase connectable devices, and promote the cooperation between things and smart terminals. Currently, many smartphone-based control system for home appliances have appeared by combining 3G and Wi-Fi technology. However, the problem of using Wi-Fi is big power consumption, and difficult for minimization. In addition, some methods adopt Infrared in smartphone to control appliances. But many smartphones have no Infrared ready, and have to set up many processes to use. Compared with the above approaches, BLE can resolve those problems. BLE has the advantages of low-power consumption, minimization, and ready reminding service. In this paper, we develop a smartphone-based appliance control system based on BLE. The system has a dynamic control menu that can scan any appliance around a user at anywhere. Meanwhile, we develop a device named “Middle-Device” for the communication between smartphone and appliances using Arduino, because Arduino is popular, easy to be used for hardware programming, and better extensibility by attaching a function board called “Shield” with many functions such as Wi-Fi, ZigBee, Bluetooth, and etc.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132289864","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011749
Junbo Wang, Yilang Wu, Zixue Cheng
IoT/Bigdata is a hot research topic all over the world in recent years and is expecting to change the world greatly in the near future. Comparing with the data in traditional websites, Bigdata from IoT devices have 4 big V-features, i.e., volume, velocity, variety, and veracity. Due to the above four features, it is hard to provide timely services to users by data analysis, especially with the great growth of data types, volume and so on. Data should be able to aware situations/demands of users, and automatically be adjusted for discovering the situations/demands of users'. Therefore, in this paper, we propose a two-ties-aware mechanism for Bigdata management and analysis. The first-tie-aware is to automatically grasp the situations around the user, and encapsulate the situation together when data is generated. The second-tie-aware is to automatically change the data to fit users' situations/demands. Furthermore, we propose a novel discovery algorithm based on the two-tiles-aware model. Given the user inputs from their ambiguous memory fragments, the discovery algorithm tries to discover the truly wanted information. Currently, the system is going to be implemented based on some open sources.
{"title":"A concept model of ‘two-ties-aware’ and design of a discovery engine based on user experienced Bigdata","authors":"Junbo Wang, Yilang Wu, Zixue Cheng","doi":"10.1109/INDCOMP.2014.7011749","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011749","url":null,"abstract":"IoT/Bigdata is a hot research topic all over the world in recent years and is expecting to change the world greatly in the near future. Comparing with the data in traditional websites, Bigdata from IoT devices have 4 big V-features, i.e., volume, velocity, variety, and veracity. Due to the above four features, it is hard to provide timely services to users by data analysis, especially with the great growth of data types, volume and so on. Data should be able to aware situations/demands of users, and automatically be adjusted for discovering the situations/demands of users'. Therefore, in this paper, we propose a two-ties-aware mechanism for Bigdata management and analysis. The first-tie-aware is to automatically grasp the situations around the user, and encapsulate the situation together when data is generated. The second-tie-aware is to automatically change the data to fit users' situations/demands. Furthermore, we propose a novel discovery algorithm based on the two-tiles-aware model. Given the user inputs from their ambiguous memory fragments, the discovery algorithm tries to discover the truly wanted information. Currently, the system is going to be implemented based on some open sources.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130968337","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}
Pub Date : 2014-12-01DOI: 10.1109/INDCOMP.2014.7011745
Yuya Kaneda, Yan Pei, Qiangfu Zhao, Yong Liu
Outlier detection is a method to improve performances of machine learning models. In this paper, we use an outlier detection method to improve the performance of our proposed algorithm called decision boundary making (DBM). The primary objective of DBM algorithm is to induce compact and high performance machine learning models. To obtain this model, the DBM reconstructs the performance of support vector machine (SVM) on a simple multilayer perceptron (MLP). If machine learning model has compact and high performance, we can implement the model into mobile application and improve usability of mobile devices, such as smart phones, smart tablets, etc. In our previous research, we obtained high performance and compact models by DBM. However in few cases, the performances are not well. We attempt to use a SVM-based outlier detection method to improve the performance in this paper. We define outlier using the method, and remove these outliers from training data that is generated by DBM algorithm. To avoid deleting normal data, we set a parameter δoutlier, which is used to control the boundary for deciding outlier point. Experimental results using public databases show the performance of DBM without outliers is improved. We investigate and discuss the effectiveness of parameter δoutlier as well.
{"title":"Improving performance of decision boundary making with support vector machine based outlier detection","authors":"Yuya Kaneda, Yan Pei, Qiangfu Zhao, Yong Liu","doi":"10.1109/INDCOMP.2014.7011745","DOIUrl":"https://doi.org/10.1109/INDCOMP.2014.7011745","url":null,"abstract":"Outlier detection is a method to improve performances of machine learning models. In this paper, we use an outlier detection method to improve the performance of our proposed algorithm called decision boundary making (DBM). The primary objective of DBM algorithm is to induce compact and high performance machine learning models. To obtain this model, the DBM reconstructs the performance of support vector machine (SVM) on a simple multilayer perceptron (MLP). If machine learning model has compact and high performance, we can implement the model into mobile application and improve usability of mobile devices, such as smart phones, smart tablets, etc. In our previous research, we obtained high performance and compact models by DBM. However in few cases, the performances are not well. We attempt to use a SVM-based outlier detection method to improve the performance in this paper. We define outlier using the method, and remove these outliers from training data that is generated by DBM algorithm. To avoid deleting normal data, we set a parameter δoutlier, which is used to control the boundary for deciding outlier point. Experimental results using public databases show the performance of DBM without outliers is improved. We investigate and discuss the effectiveness of parameter δoutlier as well.","PeriodicalId":246465,"journal":{"name":"2014 IEEE International Symposium on Independent Computing (ISIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114753766","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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