Pub Date : 2017-11-01DOI: 10.1109/ICAWST.2017.8256531
Tsai-Fa Yen
The development of organic food industry has changed dramatically, from a neglected niche market into the food market mainstream. China's organic food demand will reach or exceed 5%. How to attract consumers' attentions and enhance their intentions to purchase organic food has become an important issue. To the best of the author's knowledge, this study aims at investigating the effects of gender difference on self-congruity. The study was designed as a cross-sectional survey. The survey instruments were borrowed from previous studies. The population of interest consists of the consumers in Fujian Province in Southeast China. Survey was adopted and finally a total of 295 samples were received. After deleting 12 samples which didn't completely finish or poor quality, 283 valid samples were met and a respond rate of valid samples was 96%. The results of current study find that the proposed model across gender has adequately validated the data collected from Fujian, China. Findings can benefit the sustainable development of the organic food industry and the more contributions to this field can be met by the future followers.
{"title":"Managing self-congruity across gender in organic food contexts","authors":"Tsai-Fa Yen","doi":"10.1109/ICAWST.2017.8256531","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256531","url":null,"abstract":"The development of organic food industry has changed dramatically, from a neglected niche market into the food market mainstream. China's organic food demand will reach or exceed 5%. How to attract consumers' attentions and enhance their intentions to purchase organic food has become an important issue. To the best of the author's knowledge, this study aims at investigating the effects of gender difference on self-congruity. The study was designed as a cross-sectional survey. The survey instruments were borrowed from previous studies. The population of interest consists of the consumers in Fujian Province in Southeast China. Survey was adopted and finally a total of 295 samples were received. After deleting 12 samples which didn't completely finish or poor quality, 283 valid samples were met and a respond rate of valid samples was 96%. The results of current study find that the proposed model across gender has adequately validated the data collected from Fujian, China. Findings can benefit the sustainable development of the organic food industry and the more contributions to this field can be met by the future followers.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"12 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":"133760054","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.2017.8256489
Cédric Bornand, A. Stantzos, A. Güsewell, Emilie Bovet, G. Bangerter, G. Chakraborty
The efficacy of music for healing psychiatric patients is a well investigated area of research. Often, soothing background music is run and improvement in patients' conditions monitored. It is believed that instead of a general soothing music, if the patient could have the privilege to select music to her/his own choice at that very moment, it would enhance many times the healing effect. On the other hand, as interacting with violent psychiatric patients is often impossible or even dangerous, it is tricky to extend the privilege that would enable patients to select themselves the pieces of music they want to listen to. In this research, we put forward several technical solutions, evaluated them, and finally came up with an effective solution. The core idea of the proposed user aware interface could be extended to other similar situations, like prison.
{"title":"A user aware interface for seclusion rooms","authors":"Cédric Bornand, A. Stantzos, A. Güsewell, Emilie Bovet, G. Bangerter, G. Chakraborty","doi":"10.1109/ICAWST.2017.8256489","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256489","url":null,"abstract":"The efficacy of music for healing psychiatric patients is a well investigated area of research. Often, soothing background music is run and improvement in patients' conditions monitored. It is believed that instead of a general soothing music, if the patient could have the privilege to select music to her/his own choice at that very moment, it would enhance many times the healing effect. On the other hand, as interacting with violent psychiatric patients is often impossible or even dangerous, it is tricky to extend the privilege that would enable patients to select themselves the pieces of music they want to listen to. In this research, we put forward several technical solutions, evaluated them, and finally came up with an effective solution. The core idea of the proposed user aware interface could be extended to other similar situations, like prison.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"117 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":"117279757","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.2017.8256431
Weilun Wang, G. Chakraborty
We present a novel approach to detect P300 Signal by using the difference between target trial signal and nontarget trail signal generated by P300 BCI Speller. Conventional P300 BCI Speller uses 8 probes at pre-defined locations on the scalp. It works for any person and could deliver a reasonable performance. In P300 BCI speller, system needs to decipher the event related potential (ERP), called P300. Though it is strong in the parietal region of the brain, location of the strongest signal varies from person to person. If we can adapt the location of probes for an individual, we could eliminate un-necessary probes. At first, we want to eliminate probes that did not generate similar signal for target stimuli. We calculated signal distance between different experiments for every probe. The probes that generated quite different signal in different experiments are unsuitable for classification. Then, we search for the probes that will generate strong P300 signal from the remaining probes. In this work, we concentrated on the difference between target trail signal and non-target trail signal. P300 signal's distinctive property is that its amplitude has a strong negative correlation with the event probability. In P300 BCI Speller, the target trail's probability is 1/6 and the non-target trail's probability is 5/6. Infrequent target trail P300 signal's amplitude is larger than the nontarget trial signal's amplitude. We designed an algorithm to calculate the P300 signal's amplitude and selected the probes with larger difference between target trial P300 signal's amplitude and non-target trail signal's amplitude. We achieved over 81% classification accuracy on average with 3 probes from only one pair of target stimuli signal and non-target stimuli signal.
{"title":"Probes minimization still maintaining high accuracy to classify target stimuli P300","authors":"Weilun Wang, G. Chakraborty","doi":"10.1109/ICAWST.2017.8256431","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256431","url":null,"abstract":"We present a novel approach to detect P300 Signal by using the difference between target trial signal and nontarget trail signal generated by P300 BCI Speller. Conventional P300 BCI Speller uses 8 probes at pre-defined locations on the scalp. It works for any person and could deliver a reasonable performance. In P300 BCI speller, system needs to decipher the event related potential (ERP), called P300. Though it is strong in the parietal region of the brain, location of the strongest signal varies from person to person. If we can adapt the location of probes for an individual, we could eliminate un-necessary probes. At first, we want to eliminate probes that did not generate similar signal for target stimuli. We calculated signal distance between different experiments for every probe. The probes that generated quite different signal in different experiments are unsuitable for classification. Then, we search for the probes that will generate strong P300 signal from the remaining probes. In this work, we concentrated on the difference between target trail signal and non-target trail signal. P300 signal's distinctive property is that its amplitude has a strong negative correlation with the event probability. In P300 BCI Speller, the target trail's probability is 1/6 and the non-target trail's probability is 5/6. Infrequent target trail P300 signal's amplitude is larger than the nontarget trial signal's amplitude. We designed an algorithm to calculate the P300 signal's amplitude and selected the probes with larger difference between target trial P300 signal's amplitude and non-target trail signal's amplitude. We achieved over 81% classification accuracy on average with 3 probes from only one pair of target stimuli signal and non-target stimuli signal.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"321 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":"116462563","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.2017.8256441
Zhe Guo, Yu Wang, Yanghua Shen, Xin Zhu, Daiki Nemoto, D. Takayanagi, Masoto Aizawa, N. Isohata, K. Utano, K. Kumamoto, S. Endo, K. Togashi
Colorectal cancer (CRC) is a leading cause of cancer. The incidence and mortality rates of CRC are expected to steadily increase in the future. Colonoscopy is the most popular and effect method for curing and screening CRC. However, 25% polyps were reported to be missed during colonoscopy examinations. In this study, we proposed a method to classify polyps from background based on bag-of-visual-words (BoW) from colonoscopy images. This method generates a histogram of visual word occurrences to represent an image. The histograms of a dataset were used to train an image category classifier. Validation was performed on 35 subjects' data with an average specificity of 97.01%, an average sensitivity of 99.43%, and an average accuracy of 97.8%.
{"title":"Automatic polyp recognition from colonoscopy images based on bag of visual words","authors":"Zhe Guo, Yu Wang, Yanghua Shen, Xin Zhu, Daiki Nemoto, D. Takayanagi, Masoto Aizawa, N. Isohata, K. Utano, K. Kumamoto, S. Endo, K. Togashi","doi":"10.1109/ICAWST.2017.8256441","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256441","url":null,"abstract":"Colorectal cancer (CRC) is a leading cause of cancer. The incidence and mortality rates of CRC are expected to steadily increase in the future. Colonoscopy is the most popular and effect method for curing and screening CRC. However, 25% polyps were reported to be missed during colonoscopy examinations. In this study, we proposed a method to classify polyps from background based on bag-of-visual-words (BoW) from colonoscopy images. This method generates a histogram of visual word occurrences to represent an image. The histograms of a dataset were used to train an image category classifier. Validation was performed on 35 subjects' data with an average specificity of 97.01%, an average sensitivity of 99.43%, and an average accuracy of 97.8%.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"25 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":"116468260","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.2017.8256442
Ja-Hwung Su, Chu-Yu Chin, Jyun-Yu Li, V. Tseng
Image data has grown rapidly because of advances on photo capturing devices. In traditional, because the image data has not been huge, most past studies focused on the effectiveness improvement. However, accessing the images from a huge amount of image data needs a large cost. Hence, how to perform efficient image retrieval has been a hot topic in the last few decades. To this end, in this paper, we propose efficient big image data retrieval by using clustering index and parallel computation. In the offline stage, the images are grouped into a number of clusters. In the online stage, the relevant images to the query image are retrieved by a level-wise search. Our intent is to conduct a more efficient image retrieval method in comparison with traditional methods but keep the same effectiveness still. In the experiments, four types of retrieval are compared and our proposed parallelized image data retrieval is much faster than the other compared methods under the very close accuracies.
{"title":"Efficient big image data retrieval using clustering index and parallel computation","authors":"Ja-Hwung Su, Chu-Yu Chin, Jyun-Yu Li, V. Tseng","doi":"10.1109/ICAWST.2017.8256442","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256442","url":null,"abstract":"Image data has grown rapidly because of advances on photo capturing devices. In traditional, because the image data has not been huge, most past studies focused on the effectiveness improvement. However, accessing the images from a huge amount of image data needs a large cost. Hence, how to perform efficient image retrieval has been a hot topic in the last few decades. To this end, in this paper, we propose efficient big image data retrieval by using clustering index and parallel computation. In the offline stage, the images are grouped into a number of clusters. In the online stage, the relevant images to the query image are retrieved by a level-wise search. Our intent is to conduct a more efficient image retrieval method in comparison with traditional methods but keep the same effectiveness still. In the experiments, four types of retrieval are compared and our proposed parallelized image data retrieval is much faster than the other compared methods under the very close accuracies.","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":"123396579","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.2017.8256517
Xiaofeng Du, Yifan He, Jianmin Li, Xiaozhu Xie
An important practical issue in building Convolutional Neural Network (CNN) is a trade-off between the number of parameters and the performance. This paper proposes multiscale fusion convolutional neural network for single image superresolution. The network has the following two advantages: 1) the multi-scale convolutional layer provides the multi-context for image reconstruction; and 2) the fusion of cross-channel features reduces the dimensionality of the output of the intermediate layer. Thus the experimental results on image super-resolution demonstrate that our network achieves better performance over the state-of-art approaches.
{"title":"Single image super-resolution via multi-scale fusion convolutional neural network","authors":"Xiaofeng Du, Yifan He, Jianmin Li, Xiaozhu Xie","doi":"10.1109/ICAWST.2017.8256517","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256517","url":null,"abstract":"An important practical issue in building Convolutional Neural Network (CNN) is a trade-off between the number of parameters and the performance. This paper proposes multiscale fusion convolutional neural network for single image superresolution. The network has the following two advantages: 1) the multi-scale convolutional layer provides the multi-context for image reconstruction; and 2) the fusion of cross-channel features reduces the dimensionality of the output of the intermediate layer. Thus the experimental results on image super-resolution demonstrate that our network achieves better performance over the state-of-art approaches.","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":"127663797","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.2017.8256510
Peng Mei, Fuquan Zhang, Lin Xu, Hongyong Leng, Lei Chen, Guo Liu
Overcome context-independent probabilities based reasoning, with decomposition of categories and predicates into features as non-stable predicates. With distinction between generative classifier and discriminative classifier, we purpose to use some discriminative classifiers such as dual-form perceptron and kernelized support vector machine to improve to result of reasoning process. With capability of dual-form perceptron and kernelized support vector machine, finding linear or non-linear decision boundary for similarity-like supporting predicate for reasoning process.
{"title":"Transitioning conditional probability to discriminative classifier over inductive reasoning","authors":"Peng Mei, Fuquan Zhang, Lin Xu, Hongyong Leng, Lei Chen, Guo Liu","doi":"10.1109/ICAWST.2017.8256510","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256510","url":null,"abstract":"Overcome context-independent probabilities based reasoning, with decomposition of categories and predicates into features as non-stable predicates. With distinction between generative classifier and discriminative classifier, we purpose to use some discriminative classifiers such as dual-form perceptron and kernelized support vector machine to improve to result of reasoning process. With capability of dual-form perceptron and kernelized support vector machine, finding linear or non-linear decision boundary for similarity-like supporting predicate for reasoning process.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"1 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":"130290881","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.2017.8256446
Noriki Uchida, Takahiro Shingai, Takato Shigetome, Y. Shibata
It is necessary to concern the deficient network resources if there happened to be a severe disaster, and the DTN is widely known as the suitable network routing methods for such a robust network conditions. On the contrary, the DTN has pointed out the subjects of low date delivery rate and the high latency for the uses. Therefore, this paper proposed the enhanced DTN routing methods based on the Data Triage, the Dynamic FEC controls, and the antenna directional controls. Also, it is reported the implementations of the Data Triage methods in the prototype system, and the experimental results are used for the effectiveness of the proposed methods and the future studies.
{"title":"Implementations of data triage methods for DTN based disaster information networks","authors":"Noriki Uchida, Takahiro Shingai, Takato Shigetome, Y. Shibata","doi":"10.1109/ICAWST.2017.8256446","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256446","url":null,"abstract":"It is necessary to concern the deficient network resources if there happened to be a severe disaster, and the DTN is widely known as the suitable network routing methods for such a robust network conditions. On the contrary, the DTN has pointed out the subjects of low date delivery rate and the high latency for the uses. Therefore, this paper proposed the enhanced DTN routing methods based on the Data Triage, the Dynamic FEC controls, and the antenna directional controls. Also, it is reported the implementations of the Data Triage methods in the prototype system, and the experimental results are used for the effectiveness of the proposed methods and the future studies.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"6 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":"129702209","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.2017.8256473
Long-Sheng Chen, Meng-Ru Lin, Yi-Ting Pan
According to the several forecasts, mobile games industry will account for ever increasing contributions, with a market share approaching 35% by 2020. Consequently, the game applications (App) providers need to know how to design products that match consumer's requirements, continuously use, and in-app purchase are important issue. In particular, in-App purchase is the major revenue models. Hence, this study attempts to define the potential factors of influencing in-App purchases for game users. Then, we use two feature selection methods, Neural Network Pruning and Chi-square test to identify important factors that affect users' in-game purchases behaviors. The results can be used as a reference when designing game Apps for game developers and researchers.
{"title":"Find crucial factors of in-game purchase using neural networks","authors":"Long-Sheng Chen, Meng-Ru Lin, Yi-Ting Pan","doi":"10.1109/ICAWST.2017.8256473","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256473","url":null,"abstract":"According to the several forecasts, mobile games industry will account for ever increasing contributions, with a market share approaching 35% by 2020. Consequently, the game applications (App) providers need to know how to design products that match consumer's requirements, continuously use, and in-app purchase are important issue. In particular, in-App purchase is the major revenue models. Hence, this study attempts to define the potential factors of influencing in-App purchases for game users. Then, we use two feature selection methods, Neural Network Pruning and Chi-square test to identify important factors that affect users' in-game purchases behaviors. The results can be used as a reference when designing game Apps for game developers and researchers.","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":"125565038","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.2017.8256457
Rojanee Khummongkol, M. Yokota
It must be rather difficult for ordinary people to communicate with robots using special technical languages. Therefore, it must be more desirable for them to use natural language (NL) for such a purpose because it is the most conventional among them. This work proposes a methodology for natural language understanding through an AI system named Conversation Management System (CMS) based on Mental Image Directed Semantic Theory proposed by M. Yokota. CMS is intended to enable a robot to understand NL in the same way as people do, and actually can reach the most plausible semantic interpretation of an input text and return desirable outcomes by employing word concepts, postulates, and inference rules. Recently, the authors have applied several spatial terms in English language, for example verbs, prepositions (e.g. between, along, left, right, and so on). We found that the methodology is outstanding from conventional approaches with the attempt to provide robots understand NL based on mental image model. This paper focuses on how CMS understands static spatial (3D) relations expressed in NL.
{"title":"An approach to mental image based understanding of natural language: Focused on static and dynamic spatial relations","authors":"Rojanee Khummongkol, M. Yokota","doi":"10.1109/ICAWST.2017.8256457","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256457","url":null,"abstract":"It must be rather difficult for ordinary people to communicate with robots using special technical languages. Therefore, it must be more desirable for them to use natural language (NL) for such a purpose because it is the most conventional among them. This work proposes a methodology for natural language understanding through an AI system named Conversation Management System (CMS) based on Mental Image Directed Semantic Theory proposed by M. Yokota. CMS is intended to enable a robot to understand NL in the same way as people do, and actually can reach the most plausible semantic interpretation of an input text and return desirable outcomes by employing word concepts, postulates, and inference rules. Recently, the authors have applied several spatial terms in English language, for example verbs, prepositions (e.g. between, along, left, right, and so on). We found that the methodology is outstanding from conventional approaches with the attempt to provide robots understand NL based on mental image model. This paper focuses on how CMS understands static spatial (3D) relations expressed in NL.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"9 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":"116917765","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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