Pub Date : 2017-11-01DOI: 10.1109/ICAWST.2017.8256511
K. Chiou, Ming-min Lo, Guo-Wei Wu
In this study, we have adopted factors such as intellectual capital, financial ratios and corporate governance variables to construct a financial distress forecasting model by logistic regression. Furthermore, we employ the criteria of minimizing the sum of the two error probability in models I and II to determine the optimal threshold value, so as to increase the forecasting ability of a financial crisis forecasting model. We have taken 54 electronics companies listed in Taiwan Stock Exchange (TSE) and Over the Counter (OTC) during the periods from 2012 to 2015 to be our observation. 18 companies out of the 54 has been financially distressed in 2015. The results show that we could effectively construct a lower threshold value on the basis of the dynamic threshold value to carry out early warning (such as p = 0.32 ∼ 0.43 < p = 0.5) than those in terms of the traditional one half rule. The total error prediction probability could be reduced by 8.33% to 30.56%. In addition, the empirical evidence shows that after adding the intellectual capital variables, it could enhance the forecasting power.
{"title":"The minimizing prediction error on corporate financial distress forecasting model: An application of dynamic distress threshold value","authors":"K. Chiou, Ming-min Lo, Guo-Wei Wu","doi":"10.1109/ICAWST.2017.8256511","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256511","url":null,"abstract":"In this study, we have adopted factors such as intellectual capital, financial ratios and corporate governance variables to construct a financial distress forecasting model by logistic regression. Furthermore, we employ the criteria of minimizing the sum of the two error probability in models I and II to determine the optimal threshold value, so as to increase the forecasting ability of a financial crisis forecasting model. We have taken 54 electronics companies listed in Taiwan Stock Exchange (TSE) and Over the Counter (OTC) during the periods from 2012 to 2015 to be our observation. 18 companies out of the 54 has been financially distressed in 2015. The results show that we could effectively construct a lower threshold value on the basis of the dynamic threshold value to carry out early warning (such as p = 0.32 ∼ 0.43 < p = 0.5) than those in terms of the traditional one half rule. The total error prediction probability could be reduced by 8.33% to 30.56%. In addition, the empirical evidence shows that after adding the intellectual capital variables, it could enhance the forecasting power.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121148799","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256427
I. Surjandari, Asma Rosyidah
Implementation of marketing strategy plays an important role in increasing the number of sales and market penetration, especially in competitive market. In geo-marketing approach, spatial analysis of customer distribution patterns is used as a parameter to determine a comprehensive marketing strategy. Hence, this study was conducted to find the spatial patterns of fixed broadband customer distribution from geographic information system based customer data. This research was conducted using spatial analysis method, which is kernel density estimation. The results obtained from this study provide an overview of customer area mapping in the form of heatmap.
{"title":"Fixed broadband customer area mapping using spatial analysis","authors":"I. Surjandari, Asma Rosyidah","doi":"10.1109/ICAWST.2017.8256427","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256427","url":null,"abstract":"Implementation of marketing strategy plays an important role in increasing the number of sales and market penetration, especially in competitive market. In geo-marketing approach, spatial analysis of customer distribution patterns is used as a parameter to determine a comprehensive marketing strategy. Hence, this study was conducted to find the spatial patterns of fixed broadband customer distribution from geographic information system based customer data. This research was conducted using spatial analysis method, which is kernel density estimation. The results obtained from this study provide an overview of customer area mapping in the form of heatmap.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125771380","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256529
Roozbeh Sadeghian Broujeny, K. Madani, A. Chebira, Laurent Hurtard
The challenging problem of energy consumption of building, and in a more general way of cities, and its enormous growth due to recent decades' human activities leaded to an appealing development of fields focusing smart buildings and smart cities regarding energy efficiency. Ability to avoid of wasting energy is appealing now and thus researchers are looking for new energy consumption trend and new way for building energy management system. However, such smart edifices or cities have to integrate the ability of their own awareness as well about the environment in which they evolve as about the impact of their users on their energy efficiency. Within this context, in this paper we introduce a multi-layer system able as well to monitor as to control energy consumption and state of a building, proffering the buildings a kind of self-awareness about its energetic state. The investigated system has been implemented in a five-floors building of Senart Campus of UPEC (one of main campuses of this Parisian university) providing an appealing experimental platform for validation of the investigated concept. The present paper describes the aforementioned system and gives first results of validation of the investigated system.
{"title":"A multi-layer system for smart-buildings' functional and energy-efficiency awareness: Implementation on a real five-floors building","authors":"Roozbeh Sadeghian Broujeny, K. Madani, A. Chebira, Laurent Hurtard","doi":"10.1109/ICAWST.2017.8256529","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256529","url":null,"abstract":"The challenging problem of energy consumption of building, and in a more general way of cities, and its enormous growth due to recent decades' human activities leaded to an appealing development of fields focusing smart buildings and smart cities regarding energy efficiency. Ability to avoid of wasting energy is appealing now and thus researchers are looking for new energy consumption trend and new way for building energy management system. However, such smart edifices or cities have to integrate the ability of their own awareness as well about the environment in which they evolve as about the impact of their users on their energy efficiency. Within this context, in this paper we introduce a multi-layer system able as well to monitor as to control energy consumption and state of a building, proffering the buildings a kind of self-awareness about its energetic state. The investigated system has been implemented in a five-floors building of Senart Campus of UPEC (one of main campuses of this Parisian university) providing an appealing experimental platform for validation of the investigated concept. The present paper describes the aforementioned system and gives first results of validation of the investigated system.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126802377","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256471
Isuru Jayarathne, Michael Cohen, Senaka Amarakeerthi
User authentication systems based on EEG (electroencephalography) is currently popular, marking an inflection point in the field. Recently, the scientific community has been making tremendous attempts towards perceiving uniqueness of brain signal patterns. Several types of methodical approaches have been proposed and prototyped to analyze EEG data with various signal-processing methods and pattern-recognition algorithms. Even though there are many stimulation methods to produce reasonable distinctiveness between subjects, optimization and lowering task complexity are still desirable from technoeconomic points of view. With recent technological advancement of EEG signal capturing devices, the process is getting comparatively simpler as devices are capable of providing better portability with reduced calibration time. However, most detailed analysis suggests that a minimal number of most appropriate channels should be selected for better results, even if a system is equipped with the most advanced hardware. Researchers are now focusing on implementing computationally low cost systems with better accuracy, regardless of complexity of the tasks. This paper is a review of several approaches, providing an overview of crucial design considerations in handling EEG data for extended accuracy and practical applicability to authentication.
{"title":"Survey of EEG-based biometric authentication","authors":"Isuru Jayarathne, Michael Cohen, Senaka Amarakeerthi","doi":"10.1109/ICAWST.2017.8256471","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256471","url":null,"abstract":"User authentication systems based on EEG (electroencephalography) is currently popular, marking an inflection point in the field. Recently, the scientific community has been making tremendous attempts towards perceiving uniqueness of brain signal patterns. Several types of methodical approaches have been proposed and prototyped to analyze EEG data with various signal-processing methods and pattern-recognition algorithms. Even though there are many stimulation methods to produce reasonable distinctiveness between subjects, optimization and lowering task complexity are still desirable from technoeconomic points of view. With recent technological advancement of EEG signal capturing devices, the process is getting comparatively simpler as devices are capable of providing better portability with reduced calibration time. However, most detailed analysis suggests that a minimal number of most appropriate channels should be selected for better results, even if a system is equipped with the most advanced hardware. Researchers are now focusing on implementing computationally low cost systems with better accuracy, regardless of complexity of the tasks. This paper is a review of several approaches, providing an overview of crucial design considerations in handling EEG data for extended accuracy and practical applicability to authentication.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116243705","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256523
Chih-Wei Lin, W. Tan, Su-Shiang Lee, Shin-I Tseng, Yu-Sheng Lin, W. Hsu
This study aims to investigate the relationship between the experience satisfaction and sports attitude for the adolescent with the somatosensory experience of information technology products. Subject to the adolescents ranging from 13 to 15-year olds, this study issues a total of 445 surveys by using cluster sampling. As a result, 415 valid samples are received and the effective response rate is 93.2%. For the collected data, it is at first analyzed for the reliability and the validity, and then descriptive statistics and multiple regression analysis are applied. The main results induced from this study are as below. (1) The experience of Wii Sports can benefit the “Sensory Emotion” of the somatosensory experience. (2) The “Relaxation” of the experience satisfaction is the most impressive; the “Affection” of the exercise attitude is the highest. (3) The “Thinking Action”, “Sensory Emotion” and “Relevance” of somatosensory experiences in Wii Sports can effectively predict the experience satisfaction and sports attitude. (4) The sports attitudes can be effectively predicted by the “Relaxation”, “Physiological” and “Psychological” of the somatosensory experience in Wii Sports. Based on the above results, this study provides some practical suggestions for educational and related units as a reference to achieve an improvement in sports education.
{"title":"The influence of experience satisfaction and sports attitude on somatosensory experience of information technology products: A case study of Wii sports","authors":"Chih-Wei Lin, W. Tan, Su-Shiang Lee, Shin-I Tseng, Yu-Sheng Lin, W. Hsu","doi":"10.1109/ICAWST.2017.8256523","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256523","url":null,"abstract":"This study aims to investigate the relationship between the experience satisfaction and sports attitude for the adolescent with the somatosensory experience of information technology products. Subject to the adolescents ranging from 13 to 15-year olds, this study issues a total of 445 surveys by using cluster sampling. As a result, 415 valid samples are received and the effective response rate is 93.2%. For the collected data, it is at first analyzed for the reliability and the validity, and then descriptive statistics and multiple regression analysis are applied. The main results induced from this study are as below. (1) The experience of Wii Sports can benefit the “Sensory Emotion” of the somatosensory experience. (2) The “Relaxation” of the experience satisfaction is the most impressive; the “Affection” of the exercise attitude is the highest. (3) The “Thinking Action”, “Sensory Emotion” and “Relevance” of somatosensory experiences in Wii Sports can effectively predict the experience satisfaction and sports attitude. (4) The sports attitudes can be effectively predicted by the “Relaxation”, “Physiological” and “Psychological” of the somatosensory experience in Wii Sports. Based on the above results, this study provides some practical suggestions for educational and related units as a reference to achieve an improvement in sports education.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128299775","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256467
Chin-Feng Lee, Ying-Xiang Wang
Image data hiding technology is a secret communication which carries hidden data in such a way that no one apart from the sender and intended recipient can even realize there is a hidden message. High embedding capacity, good images quality and security are three important essentials. In this paper, each confidential hexadecimal will be carried by two cover pixels based on a magic matrix generated from a square template to reach the goal of higher embedding capacity while keeping good image visualization. Experimental results reveal that the proposed scheme guarantees higher embedding capacity of 2 bits per pixel and has the PSNR of 44.7 dB on average. Moreover, secret keys are used to ensure security consideration.
{"title":"An image hiding scheme based on magic square","authors":"Chin-Feng Lee, Ying-Xiang Wang","doi":"10.1109/ICAWST.2017.8256467","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256467","url":null,"abstract":"Image data hiding technology is a secret communication which carries hidden data in such a way that no one apart from the sender and intended recipient can even realize there is a hidden message. High embedding capacity, good images quality and security are three important essentials. In this paper, each confidential hexadecimal will be carried by two cover pixels based on a magic matrix generated from a square template to reach the goal of higher embedding capacity while keeping good image visualization. Experimental results reveal that the proposed scheme guarantees higher embedding capacity of 2 bits per pixel and has the PSNR of 44.7 dB on average. Moreover, secret keys are used to ensure security consideration.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122077430","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256472
Chuan-Bi Lin, T. Hu, Hsiang-Yu Chan
In the Internet, Software-Defined Network (SDN) is an attractive issue because it allows network managers to use software program to control and manage the networks instead of the setup of hardware equipment. Therefore, in this study, we established an experiment platform by Raspberry Pi boards and proposed a method, Weight-Based Flow Dividing (WFD) method, to implement the OpenFlow switching in the SDN. The proposed method uses the multipath to transmit the packets by weighted configurations because the single-path transmission causes the routing security at high risk and is difficult to effectively use the path bandwidth. In addition, we use network simulation software Mininet on this study for comparison purposes. The simulations show the results can achieve the multipath transmissions through the hardware OpenFlow switch platform with WFD in different weighted configurations, as Mininet.
{"title":"The implementation of multi-path delivery for data flows using Raspberry Pi boards in software-defined networks","authors":"Chuan-Bi Lin, T. Hu, Hsiang-Yu Chan","doi":"10.1109/ICAWST.2017.8256472","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256472","url":null,"abstract":"In the Internet, Software-Defined Network (SDN) is an attractive issue because it allows network managers to use software program to control and manage the networks instead of the setup of hardware equipment. Therefore, in this study, we established an experiment platform by Raspberry Pi boards and proposed a method, Weight-Based Flow Dividing (WFD) method, to implement the OpenFlow switching in the SDN. The proposed method uses the multipath to transmit the packets by weighted configurations because the single-path transmission causes the routing security at high risk and is difficult to effectively use the path bandwidth. In addition, we use network simulation software Mininet on this study for comparison purposes. The simulations show the results can achieve the multipath transmissions through the hardware OpenFlow switch platform with WFD in different weighted configurations, as Mininet.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123583014","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256521
Atsushi Kawamura, B. Chakraborty
Feature subset selection is very important as a preprocessing step for pattern recognition and data mining problems. The selected feature subset is expected to produce maximum possible classification accuracy with a minimum possible number of features. For optimal feature selection, a suitable evaluation function and an efficient search method are needed. There are two main approaches. In filter approach, the inherent characteristics of the data set is used for feature evaluation while in wrapper approach, the classification accuracy is used as the evaluation function. Both the approaches have relative merits and demerits. In this paper a suitable combination of both filter and wrapper approch is proposed for selection of optimal feature subset with evolutionary algorithm. Correlation based feature selection (CFS) and minimum redundancy and maximum relevance (mRMR) algorithms are used as filter evaluation approach, binary genetic algorithm (BGA) and binary particle swarm optimization (BPSO) are used as evolutionary serach algorithms. The simulation experiments are done with benchmark data sets. The simulation results show that proper hybridization approach is effective in achieving optimal feature subset selection with minimum number of features having high classification accuracy and low computational cost.
{"title":"A hybrid approach for optimal feature subset selection with evolutionary algorithms","authors":"Atsushi Kawamura, B. Chakraborty","doi":"10.1109/ICAWST.2017.8256521","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256521","url":null,"abstract":"Feature subset selection is very important as a preprocessing step for pattern recognition and data mining problems. The selected feature subset is expected to produce maximum possible classification accuracy with a minimum possible number of features. For optimal feature selection, a suitable evaluation function and an efficient search method are needed. There are two main approaches. In filter approach, the inherent characteristics of the data set is used for feature evaluation while in wrapper approach, the classification accuracy is used as the evaluation function. Both the approaches have relative merits and demerits. In this paper a suitable combination of both filter and wrapper approch is proposed for selection of optimal feature subset with evolutionary algorithm. Correlation based feature selection (CFS) and minimum redundancy and maximum relevance (mRMR) algorithms are used as filter evaluation approach, binary genetic algorithm (BGA) and binary particle swarm optimization (BPSO) are used as evolutionary serach algorithms. The simulation experiments are done with benchmark data sets. The simulation results show that proper hybridization approach is effective in achieving optimal feature subset selection with minimum number of features having high classification accuracy and low computational cost.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123117466","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256435
Arian Dhini, B. Kusumoputro, I. Surjandari
Steam turbine is the main system of a steam power plant and critical for power generation. Therefore, there is urgency for maintaining the reliability and availability of a steam turbine. A fast and accurate fault detection and diagnosis (FDD) system should be developed as an integral part to prevent a system from catastrophic disaster due to unhandled failures. Many previous studies applied model-based methods to build the FDD system. However, using those approaches required prior knowledge of the system. The power plant is a complex system, where comprehensive process knowledge is a real challenge. On the other hand, power plants have implemented condition monitoring which resulted in process monitoring data. Therefore, this study proposed a data-driven FDD system in a steam turbine of thermal power plant. The study used the process monitoring data from an Indonesian government owned steam power plant. A neural network based classifier was constructed to detect and diagnose faults as well as normal operating condition based on three scenarios. The result showed that the last two scenarios, with and without PCA approach, outperformed the first scenario which only used selected process parameters. The study demonstrated the superiority of data driven approach in the fault detection and diagnosis area.
{"title":"Neural network based system for detecting and diagnosing faults in steam turbine of thermal power plant","authors":"Arian Dhini, B. Kusumoputro, I. Surjandari","doi":"10.1109/ICAWST.2017.8256435","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256435","url":null,"abstract":"Steam turbine is the main system of a steam power plant and critical for power generation. Therefore, there is urgency for maintaining the reliability and availability of a steam turbine. A fast and accurate fault detection and diagnosis (FDD) system should be developed as an integral part to prevent a system from catastrophic disaster due to unhandled failures. Many previous studies applied model-based methods to build the FDD system. However, using those approaches required prior knowledge of the system. The power plant is a complex system, where comprehensive process knowledge is a real challenge. On the other hand, power plants have implemented condition monitoring which resulted in process monitoring data. Therefore, this study proposed a data-driven FDD system in a steam turbine of thermal power plant. The study used the process monitoring data from an Indonesian government owned steam power plant. A neural network based classifier was constructed to detect and diagnose faults as well as normal operating condition based on three scenarios. The result showed that the last two scenarios, with and without PCA approach, outperformed the first scenario which only used selected process parameters. The study demonstrated the superiority of data driven approach in the fault detection and diagnosis area.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"397 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122859862","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 : 2017-11-01DOI: 10.1109/ICAWST.2017.8256466
Hiroaki Yuze, S. Nabeta, M. Sagara
Since 1999, University of Shizuoka has been developing and operating an Internet-based safety confirmation system for students and university staffs. In the instance of Kumamoto Earthquake in 2016, University of Shizuoka provided Prefectural University of Kumamoto with the safety confirmation system. In this study, we used safety data collected through the safety confirmation system at University of Shizuoka during the Great East Japan Earthquake in 2011 and at Prefectural University of Kumamoto during the Kumamoto Earthquake in 2016 to comparatively analyze the users' safety information registration behaviors.
{"title":"Analysis of information registration behavior to safety confirmation system for university","authors":"Hiroaki Yuze, S. Nabeta, M. Sagara","doi":"10.1109/ICAWST.2017.8256466","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256466","url":null,"abstract":"Since 1999, University of Shizuoka has been developing and operating an Internet-based safety confirmation system for students and university staffs. In the instance of Kumamoto Earthquake in 2016, University of Shizuoka provided Prefectural University of Kumamoto with the safety confirmation system. In this study, we used safety data collected through the safety confirmation system at University of Shizuoka during the Great East Japan Earthquake in 2011 and at Prefectural University of Kumamoto during the Kumamoto Earthquake in 2016 to comparatively analyze the users' safety information registration behaviors.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117035012","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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