Pub Date : 2017-11-01DOI: 10.1109/ICAWST.2017.8256480
Tsung-Nan Chou
In recent years, small and medium businesses across different industries have confronted the challenges of big data analysis since a huge amount of data being generated daily by their business activities. Most of these companies are unable to achieve efficient data analysis and decision-making based on such a high dimensional and voluminous data. Normally, the performance of analytic models will be limited if the business companies directly use the original data to train, verify and test their models. Therefore, to eliminate the complexity and computation of data analysis, the raw data requires an effective transformation to reduce the dimensionality of data. In this study, non-temporal data are transformed to a two-dimensional polar graph for further analysis. On the other hand, the temporal data combined with cross-sectional data are mapped to another two-dimensional contour graph that derived and sliced from their corresponding three-dimensional data profile. Both the transforming strategies are converted and fulfilled with various geometric shape descriptors and invariant moments, and three conventional machine-learning approaches are implemented to evaluate their predictive performance. In addition, an autoencoder neural network based on unsupervised learning algorithm is also employed to evaluate predictive accuracy in comparison with the conventional approaches. The experiment results suggested that the autoencoder neural network achieved the highest accuracy, and the rest approaches were considered worse than the below-chance accuracy.
{"title":"Perception of patterns and trends in financial markets using polar graph and contour mapping","authors":"Tsung-Nan Chou","doi":"10.1109/ICAWST.2017.8256480","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256480","url":null,"abstract":"In recent years, small and medium businesses across different industries have confronted the challenges of big data analysis since a huge amount of data being generated daily by their business activities. Most of these companies are unable to achieve efficient data analysis and decision-making based on such a high dimensional and voluminous data. Normally, the performance of analytic models will be limited if the business companies directly use the original data to train, verify and test their models. Therefore, to eliminate the complexity and computation of data analysis, the raw data requires an effective transformation to reduce the dimensionality of data. In this study, non-temporal data are transformed to a two-dimensional polar graph for further analysis. On the other hand, the temporal data combined with cross-sectional data are mapped to another two-dimensional contour graph that derived and sliced from their corresponding three-dimensional data profile. Both the transforming strategies are converted and fulfilled with various geometric shape descriptors and invariant moments, and three conventional machine-learning approaches are implemented to evaluate their predictive performance. In addition, an autoencoder neural network based on unsupervised learning algorithm is also employed to evaluate predictive accuracy in comparison with the conventional approaches. The experiment results suggested that the autoencoder neural network achieved the highest accuracy, and the rest approaches were considered worse than the below-chance accuracy.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"200 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":"125732907","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.2017.8256444
Xiaodong Wang, R. Chen, Fei Yan
K-means is an efficient method and has achieved empirical success in various kinds of applications. However, it is hard to deal with high-dimensional data, which often contain noises and redundant features. Although existing methods try to fix this problem via dimension reduction or introducing the robust loss function, they still have two limitations. On one hand, they usually impose the eigenvalue decomposition to obtain the transformation matrix, which needs expensive computational cost. On the other hand, the extensions with robust loss function perform similarity measurement in the original feature space, which suffers from the outliers. To solve these problems, we propose a fast and robust subspace clustering algorithm. The proposed algorithm combines the group sparsity loss function and feature selection into a joint framework, which can reduce the effect of outliers. Besides, within such framework, the optimal feature subset can be calculated without eigenvalue decomposition, and thus it can be applied to high-dimensional data. Experimental results on several benchmark datasets demonstrate the advantage of the proposed model.
{"title":"Fast and robust K-means clustering via feature learning on high-dimensional data","authors":"Xiaodong Wang, R. Chen, Fei Yan","doi":"10.1109/ICAWST.2017.8256444","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256444","url":null,"abstract":"K-means is an efficient method and has achieved empirical success in various kinds of applications. However, it is hard to deal with high-dimensional data, which often contain noises and redundant features. Although existing methods try to fix this problem via dimension reduction or introducing the robust loss function, they still have two limitations. On one hand, they usually impose the eigenvalue decomposition to obtain the transformation matrix, which needs expensive computational cost. On the other hand, the extensions with robust loss function perform similarity measurement in the original feature space, which suffers from the outliers. To solve these problems, we propose a fast and robust subspace clustering algorithm. The proposed algorithm combines the group sparsity loss function and feature selection into a joint framework, which can reduce the effect of outliers. Besides, within such framework, the optimal feature subset can be calculated without eigenvalue decomposition, and thus it can be applied to high-dimensional data. Experimental results on several benchmark datasets demonstrate the advantage of the proposed model.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"24 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":"132019750","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.2017.8256504
Masaki Otomo, K. Hashimoto, Noriki Uchida, Y. Shibata
During large-scale disasters, such as the Great East Japan Earthquake in 2011 or Kumamoto huge Earthquake in 2016, many regions were isolated from critical information exchanges due to problems with communication infrastructures. In those serious disasters, quick and flexible disaster recovery network is required to deliver the disaster related information after disaster. In this paper, mobile cloud computing for vehicle server for information exchange among isolated shelters in such cases is introduced. The vehicle with mobile cloud server traverses the isolated shelters and exchanges information and returns to the disaster headquarter which is connected to Internet. DTN function is introduced to store, carry and exchange message as a message ferry among the shelters even in the challenged network environment where wired and wireless communication means are completely damaged. The prototype system is constructed using Wi-Fi network as mobility network and a note PC mobile cloud server and IBR-DTN and DTN2 software as the DTN function.
{"title":"Mobile cloud computing usage for onboard vehicle servers in collecting disaster data information","authors":"Masaki Otomo, K. Hashimoto, Noriki Uchida, Y. Shibata","doi":"10.1109/ICAWST.2017.8256504","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256504","url":null,"abstract":"During large-scale disasters, such as the Great East Japan Earthquake in 2011 or Kumamoto huge Earthquake in 2016, many regions were isolated from critical information exchanges due to problems with communication infrastructures. In those serious disasters, quick and flexible disaster recovery network is required to deliver the disaster related information after disaster. In this paper, mobile cloud computing for vehicle server for information exchange among isolated shelters in such cases is introduced. The vehicle with mobile cloud server traverses the isolated shelters and exchanges information and returns to the disaster headquarter which is connected to Internet. DTN function is introduced to store, carry and exchange message as a message ferry among the shelters even in the challenged network environment where wired and wireless communication means are completely damaged. The prototype system is constructed using Wi-Fi network as mobility network and a note PC mobile cloud server and IBR-DTN and DTN2 software as the DTN function.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"64 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":"133393249","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.2017.8256488
Weng-Chung Tsai, Shi-Xiang Zhu, Ming-Hong Lu, J. Merzoug, C. Yu, Ian Huang
In the network and communication generation, smart-phone is becoming a basic equipment for most of the people. As such, IoT (Internet of Things) device controlled by smart-phone is feasible and convenient for users. Therefore, this paper proposes to apply infrared signal to implement an IoT gateway that can enable users to control their home appliances such as television, air conditioner, and refrigerator using portable devices such as smart-phone, tablet-computer, and smart-watch. By doing so, a more intelligent smart-home control style is promising for future smart-home living of people. To put it more concretely, in the end of this paper, videos are provided to demonstrate four commercial home appliances that can be controlled by our implemented FPGA-based IoT gateway.
{"title":"An implementation of IoT gateway for home appliances control over cellular network","authors":"Weng-Chung Tsai, Shi-Xiang Zhu, Ming-Hong Lu, J. Merzoug, C. Yu, Ian Huang","doi":"10.1109/ICAWST.2017.8256488","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256488","url":null,"abstract":"In the network and communication generation, smart-phone is becoming a basic equipment for most of the people. As such, IoT (Internet of Things) device controlled by smart-phone is feasible and convenient for users. Therefore, this paper proposes to apply infrared signal to implement an IoT gateway that can enable users to control their home appliances such as television, air conditioner, and refrigerator using portable devices such as smart-phone, tablet-computer, and smart-watch. By doing so, a more intelligent smart-home control style is promising for future smart-home living of people. To put it more concretely, in the end of this paper, videos are provided to demonstrate four commercial home appliances that can be controlled by our implemented FPGA-based IoT gateway.","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":"130172224","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.2017.8256462
Akira Sakuraba, Y. Shibata
This paper introduces a new design of disaster state presentation system using large size and ultra high definition displaying system to satisfy requirement of quick and wide collecting and sharing disaster state information from disaster areas to make decision by the officers as decision makers who work in the headquarters. The collected disaster state information are processed as workspace and interactively controlled using workspace controller to display on the Tiled Display Wall (TDW). We designed and implemented our system using current available technology as a prototype.
{"title":"Disaster state information management gis system based on tiled diplay environment","authors":"Akira Sakuraba, Y. Shibata","doi":"10.1109/ICAWST.2017.8256462","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256462","url":null,"abstract":"This paper introduces a new design of disaster state presentation system using large size and ultra high definition displaying system to satisfy requirement of quick and wide collecting and sharing disaster state information from disaster areas to make decision by the officers as decision makers who work in the headquarters. The collected disaster state information are processed as workspace and interactively controlled using workspace controller to display on the Tiled Display Wall (TDW). We designed and implemented our system using current available technology as a prototype.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"36 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":"114505947","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.2017.8256526
Jia-Wei Liu, T. Lu, Qiangfu Zhao
In recent years, pixel value ordering (PVO)-based information embedding techniques have been broadly applied in reversible steganography. So far, researchers have focused on finding the best predictor value to decrease the image distortion. In practice, the secret data size is the main factor that affects the quality of the restored cover image. Therefore, in this research we introduce a technique to reduce the data size. The technique is based on data sharing in which the sender and the receiver share the same “vocabulary table” (VT). Using this VT, any secret datum (text, image, or sound) can be converted to a list of indices. Encoding this list using another lossless encoding method, we can compress the datum greatly, and thus reduce the distortion caused in the embedding process. Experimental results show that the proposed method outperforms existing PVO techniques. The proposed method can save around 80% of data space for text data, and about 98% of data space for image data.
{"title":"Improving the performance of lossless reversible steganography via data sharing","authors":"Jia-Wei Liu, T. Lu, Qiangfu Zhao","doi":"10.1109/ICAWST.2017.8256526","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256526","url":null,"abstract":"In recent years, pixel value ordering (PVO)-based information embedding techniques have been broadly applied in reversible steganography. So far, researchers have focused on finding the best predictor value to decrease the image distortion. In practice, the secret data size is the main factor that affects the quality of the restored cover image. Therefore, in this research we introduce a technique to reduce the data size. The technique is based on data sharing in which the sender and the receiver share the same “vocabulary table” (VT). Using this VT, any secret datum (text, image, or sound) can be converted to a list of indices. Encoding this list using another lossless encoding method, we can compress the datum greatly, and thus reduce the distortion caused in the embedding process. Experimental results show that the proposed method outperforms existing PVO techniques. The proposed method can save around 80% of data space for text data, and about 98% of data space for image data.","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":"114642982","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 the present study, there are a number of recognition methods with high recognition accuracy, which are based on deep learning. However, these methods usually have a good effect in a restricted environment, but in the natural environment, the accuracy of face recognition has decreased significantly, especially in the case of occlusion, face recognition will appear inaccurate or unrecognized situation. Based on this, this paper presents a face recognition method based on the deep learning in the natural environment, hoping to achieve robust performance in the natural environment, especially in the case of occlusion. The main contribution of this paper is improving the method of multi-patches by using 4 areas' patches in the face. And in order to have a higher performance, we use a Joint Bayesian (JB) measure in face-verification. Finally, we trained the model by the set of CASIA-WebFace and test it in the Labeled Faces in the Wild (LFW).
{"title":"Research on face recognition method based on deep learning in natural environment","authors":"Jiali Yan, Longfei Zhang, Yufeng Wu, Penghui Guo, Shuo Tang, Gangyi Ding, Fuquan Zhang, Lin Xu","doi":"10.1109/ICAWST.2017.8256509","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256509","url":null,"abstract":"In the present study, there are a number of recognition methods with high recognition accuracy, which are based on deep learning. However, these methods usually have a good effect in a restricted environment, but in the natural environment, the accuracy of face recognition has decreased significantly, especially in the case of occlusion, face recognition will appear inaccurate or unrecognized situation. Based on this, this paper presents a face recognition method based on the deep learning in the natural environment, hoping to achieve robust performance in the natural environment, especially in the case of occlusion. The main contribution of this paper is improving the method of multi-patches by using 4 areas' patches in the face. And in order to have a higher performance, we use a Joint Bayesian (JB) measure in face-verification. Finally, we trained the model by the set of CASIA-WebFace and test it in the Labeled Faces in the Wild (LFW).","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"3 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":"124944432","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.2017.8256515
Kenta Ito, K. Hashimoto, Y. Shibata
We developed a system for deterring traffic problems by understanding the road surface condition, collecting information from many vehicles and calling attention at various levels to the driver. We focus on the sharing method of sensor data with road condition using V2X communication. The Wi-Fi communication in the 2.4 GHz band which is the conventional method, has a short communication distance and must understand the communication partner in advance. We use 920 MHz band communication which is long distance communication to compensate for these problems. We propose a cognitive network method to optimize V2X communication by combining both WiFi and 920MHz bands.
{"title":"V2X communication system for sharing road alert information using cognitive network","authors":"Kenta Ito, K. Hashimoto, Y. Shibata","doi":"10.1109/ICAWST.2017.8256515","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256515","url":null,"abstract":"We developed a system for deterring traffic problems by understanding the road surface condition, collecting information from many vehicles and calling attention at various levels to the driver. We focus on the sharing method of sensor data with road condition using V2X communication. The Wi-Fi communication in the 2.4 GHz band which is the conventional method, has a short communication distance and must understand the communication partner in advance. We use 920 MHz band communication which is long distance communication to compensate for these problems. We propose a cognitive network method to optimize V2X communication by combining both WiFi and 920MHz bands.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"44 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":"129252515","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.2017.8256478
Chao-Kuei Hung
Machine learning advancements could greatly benefit the general public. Many programs or even trained weight matrices are available as open source software or free download. At its present form, however, most results are not directly accessible to most people. We present a front end for the t-SNE algorithm and a front-end for querying English language word embedding as examples to illustrate what's needed to make these results more accessible to people outside this field. The way their usage can be combined also demonstrates the author's envisioned development of such tools in the future, following the unix tools philosophy.
{"title":"Making machine-learning tools accessible to language teachers and other non-techies: T-SNE-lab and rocanr as first examples","authors":"Chao-Kuei Hung","doi":"10.1109/ICAWST.2017.8256478","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256478","url":null,"abstract":"Machine learning advancements could greatly benefit the general public. Many programs or even trained weight matrices are available as open source software or free download. At its present form, however, most results are not directly accessible to most people. We present a front end for the t-SNE algorithm and a front-end for querying English language word embedding as examples to illustrate what's needed to make these results more accessible to people outside this field. The way their usage can be combined also demonstrates the author's envisioned development of such tools in the future, following the unix tools philosophy.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"51 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":"127596803","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.2017.8256525
Yu-Che Huang, Tai-Shen Huang
As the R&D technology of sporting goods advances, many exercise patterns have been, and more are being, designed into equipment for sport. Presently commonly used exercise modes that can set at certain measurements include treadmill, step exercise, upright stationary bicycle, among others. With so wide a range of sporting products, most of their program designers would duplicate the parameters of exercise dose inside one single product to a different product to save time and cost. However, can the program for exercise doses used on similar products be duplicable? Also, will it bring about the same effects or even be able to replace? These all are questions to be answered. This study conducted experiments with the elliptical trainer and the bicycle, both of which have similar exercise trails of lower extremity for two specific objects. One, to compare the physiological responses resulting from these exercise modes of elliptical trainer and bicycle; and, the other, to analyze the variances and correlation between age, genders and physiological responses to each of these exercise modes. The subjects of test were 80 healthy grown-ups of ages between 20 and 65, each received tests of the two modes of exercise in random order. The test involved two phases; the first gathered the subjects' basic data. The second conducted the submaximal exercise test to understand the differences between the exercise modes of elliptical trainer and bicycle, both of the same intensity, in the physiological responses for different ages and genders. The results also aim to provide as reference for product R&D persons in the development of different product attributes and formulating exercise prescriptions.
{"title":"A study of physiological responses to different forms of exercise","authors":"Yu-Che Huang, Tai-Shen Huang","doi":"10.1109/ICAWST.2017.8256525","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256525","url":null,"abstract":"As the R&D technology of sporting goods advances, many exercise patterns have been, and more are being, designed into equipment for sport. Presently commonly used exercise modes that can set at certain measurements include treadmill, step exercise, upright stationary bicycle, among others. With so wide a range of sporting products, most of their program designers would duplicate the parameters of exercise dose inside one single product to a different product to save time and cost. However, can the program for exercise doses used on similar products be duplicable? Also, will it bring about the same effects or even be able to replace? These all are questions to be answered. This study conducted experiments with the elliptical trainer and the bicycle, both of which have similar exercise trails of lower extremity for two specific objects. One, to compare the physiological responses resulting from these exercise modes of elliptical trainer and bicycle; and, the other, to analyze the variances and correlation between age, genders and physiological responses to each of these exercise modes. The subjects of test were 80 healthy grown-ups of ages between 20 and 65, each received tests of the two modes of exercise in random order. The test involved two phases; the first gathered the subjects' basic data. The second conducted the submaximal exercise test to understand the differences between the exercise modes of elliptical trainer and bicycle, both of the same intensity, in the physiological responses for different ages and genders. The results also aim to provide as reference for product R&D persons in the development of different product attributes and formulating exercise prescriptions.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"44 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":"117253140","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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