Pub Date : 2018-09-01DOI: 10.1109/ICAWST.2018.8517231
Tomohiro Saito, Y. Watanobe
Programming education has recently received increased attention due to growing demands for programming and information technology skills. However, a lack of teaching materials and human resources presents a major challenge to meeting the growing demand for programming education. One way to compensate for a shortage of trained teachers is to use machine learning techniques to assist learners. Therefore, we propose a learning path recommendation system based on a learner’s ability charts by means of a recurrent neural network. In brief, a learning path is constructed from a learner’s submission history with a trial-and-error process, and the learner’s ability chart is used as a barometer of their current knowledge. In this paper, an approach for constructing a learning path recommendation system by using ability charts and its implementation based on a sequential prediction model by a recurrent neural network, are presented. Experimental evaluation with data from an e-learning system is also provided.
{"title":"Learning Path Recommender System based on Recurrent Neural Network","authors":"Tomohiro Saito, Y. Watanobe","doi":"10.1109/ICAWST.2018.8517231","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517231","url":null,"abstract":"Programming education has recently received increased attention due to growing demands for programming and information technology skills. However, a lack of teaching materials and human resources presents a major challenge to meeting the growing demand for programming education. One way to compensate for a shortage of trained teachers is to use machine learning techniques to assist learners. Therefore, we propose a learning path recommendation system based on a learner’s ability charts by means of a recurrent neural network. In brief, a learning path is constructed from a learner’s submission history with a trial-and-error process, and the learner’s ability chart is used as a barometer of their current knowledge. In this paper, an approach for constructing a learning path recommendation system by using ability charts and its implementation based on a sequential prediction model by a recurrent neural network, are presented. Experimental evaluation with data from an e-learning system is also provided.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116907802","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517193
Shoichi Ichimura, Ryo Ota, Qiangfu Zhao
Smart environments such as smart homes and smart offices have attracted great attention in recent years. Smart home is one solution for senior care in a super–aging society like Japan. Since smart home is a private space, devices like video camera and voice recorder cannot be used. The objective of this research is to investigate technologies for constructing privacypreserving smart home systems. In this paper, we try to use an array of binary infrared sensors to recognize the activity strengths. By activity strength here we mean the speed of a certain action. Because daily–life activities (DLAs) can be considered time sequences of different activity strengths, results obtained in this paper can provide insights about sensor–based DLA recognition. Experimental results show that an array consisting of 15 sensors can provide information for a machine learner to recognize activity strengths well, and the accuracy does not depend on the location of the subject.
{"title":"Activity Strength Recognition Using a Binary Infrared Sensor Array","authors":"Shoichi Ichimura, Ryo Ota, Qiangfu Zhao","doi":"10.1109/ICAWST.2018.8517193","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517193","url":null,"abstract":"Smart environments such as smart homes and smart offices have attracted great attention in recent years. Smart home is one solution for senior care in a super–aging society like Japan. Since smart home is a private space, devices like video camera and voice recorder cannot be used. The objective of this research is to investigate technologies for constructing privacypreserving smart home systems. In this paper, we try to use an array of binary infrared sensors to recognize the activity strengths. By activity strength here we mean the speed of a certain action. Because daily–life activities (DLAs) can be considered time sequences of different activity strengths, results obtained in this paper can provide insights about sensor–based DLA recognition. Experimental results show that an array consisting of 15 sensors can provide information for a machine learner to recognize activity strengths well, and the accuracy does not depend on the location of the subject.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125946501","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517250
Ryohei Matsumoto, Momoko Kanmura, K. Ohnishi, Shinya Watanabe
-Interactive and human-based evolutionary computation methods both enable people to solve a given problem together, but it is hard for us to analyze the processes of the problem solving because people interact with each other nonlinearly in the methods. Therefore, studies of those evolutionary methods are likely to be practical. To make such evolutionary methods involving people more widely used, they need to be traceable and obtain more trust from users. So, in this study, we develop a new traceable evolutionary method involving people. In the method, two or more people produce and evaluate solutions in turn one by one, while being aware of the preferences of each other. In addition, assuming two people solve a problem together, we construct not only an experimental system for the method but also asimulation model of the experimental system. Then, we obtain results of experiments by human subjects and simulations and realize from the results that the simulation results assuming completely rational people are different from the experimental ones, in which cooperation beyond rationality among people can occur.
{"title":"Evolutionary Problem Solving by People Being Aware of Others’ Preferences","authors":"Ryohei Matsumoto, Momoko Kanmura, K. Ohnishi, Shinya Watanabe","doi":"10.1109/ICAWST.2018.8517250","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517250","url":null,"abstract":"-Interactive and human-based evolutionary computation methods both enable people to solve a given problem together, but it is hard for us to analyze the processes of the problem solving because people interact with each other nonlinearly in the methods. Therefore, studies of those evolutionary methods are likely to be practical. To make such evolutionary methods involving people more widely used, they need to be traceable and obtain more trust from users. So, in this study, we develop a new traceable evolutionary method involving people. In the method, two or more people produce and evaluate solutions in turn one by one, while being aware of the preferences of each other. In addition, assuming two people solve a problem together, we construct not only an experimental system for the method but also asimulation model of the experimental system. Then, we obtain results of experiments by human subjects and simulations and realize from the results that the simulation results assuming completely rational people are different from the experimental ones, in which cooperation beyond rationality among people can occur.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116880655","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517236
Yesaya Tommy Paulus, Herlina, Khairu Zeta Leni, C. Hiramatsu, G. Remijn
Visual passwords are passwords made by selecting a sequence of objects on a screen, such as symbols, pictures, or patterns, either by manual input or eye-gaze-based input. Visual passwords can be useful alternatives to alphanumeric passwords, particularly for authentication on devices in semi-private or public spaces (e.g., on ATMs, laptops, smartphones, or car dashboards). The grid is an essential factor in the use of a visual password, because it can act as a guide for the position of an object and its identification. In this study, we obtained user judgments of 16 different grid densities for three visual password formats. The grid densities were in between 2×2 to 7×7 cells (columns × rows). The participants were asked to judge how easy to use and how safe they thought the grid densities would be, if they would use it for password authentication with eye tracking in a public setting. The results showed that for each visual password format some grid densities were thought to be relatively difficult to use (e.g., a 7×7 grid) or potentially unsafe (e.g., a 2×2 grid). Following this, the password registration time was measured for 16 grid densities (from 3×3 to 6×6 cells). The participants were asked to memorize and register a visual password (short or long) using actual eye tracking. The preliminary results show that password registration time increased when the number of grid cells increased and that the password format might influence registration as well.
{"title":"A Preliminary Experiment on Grid Densities for Visual Password Formats","authors":"Yesaya Tommy Paulus, Herlina, Khairu Zeta Leni, C. Hiramatsu, G. Remijn","doi":"10.1109/ICAWST.2018.8517236","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517236","url":null,"abstract":"Visual passwords are passwords made by selecting a sequence of objects on a screen, such as symbols, pictures, or patterns, either by manual input or eye-gaze-based input. Visual passwords can be useful alternatives to alphanumeric passwords, particularly for authentication on devices in semi-private or public spaces (e.g., on ATMs, laptops, smartphones, or car dashboards). The grid is an essential factor in the use of a visual password, because it can act as a guide for the position of an object and its identification. In this study, we obtained user judgments of 16 different grid densities for three visual password formats. The grid densities were in between 2×2 to 7×7 cells (columns × rows). The participants were asked to judge how easy to use and how safe they thought the grid densities would be, if they would use it for password authentication with eye tracking in a public setting. The results showed that for each visual password format some grid densities were thought to be relatively difficult to use (e.g., a 7×7 grid) or potentially unsafe (e.g., a 2×2 grid). Following this, the password registration time was measured for 16 grid densities (from 3×3 to 6×6 cells). The participants were asked to memorize and register a visual password (short or long) using actual eye tracking. The preliminary results show that password registration time increased when the number of grid cells increased and that the password format might influence registration as well.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"96 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129294207","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517234
Ganbold Shagdar, Buyankhishig Zundui
We propose a simple and effective optical network unit (ONU)-driven energy-saving method in an Ethernet passive optical network implementing a look-aheadenhanced multipoint control protocol with a parameter 2 (MPCP-2). In the proposed method, with help of MPCP-2, each ONU has the knowledge of next cycle’s transmission before executing current cycle’s transmission. Therefore, each ONU enters power-saving mode between two consecutive upstream transmissions with a self-defined sleep time immediately after the completion of the current cycle’s transmission. In addition, when the sleep time expires, the ONUs can prolong himself the power-saving mode without waking up in every cycle if specific conditions are satisfied and consequently, no sleep-control message between the ONU and the optical line terminal is required. Thus, energy can be saved at ONUs during the idle time between consecutive cycle transmissions or over several cycles by allowing the ONUs enter power-saving mode under ONU’s self-decision. The simulation results demonstrate that the power consumption of ONUs could be reduced by 52.5– 56.0% over the entire traffic load.
{"title":"ONU-driven Energy-saving Method in an EPON by Implementing Look-ahead MPCP-2","authors":"Ganbold Shagdar, Buyankhishig Zundui","doi":"10.1109/ICAWST.2018.8517234","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517234","url":null,"abstract":"We propose a simple and effective optical network unit (ONU)-driven energy-saving method in an Ethernet passive optical network implementing a look-aheadenhanced multipoint control protocol with a parameter 2 (MPCP-2). In the proposed method, with help of MPCP-2, each ONU has the knowledge of next cycle’s transmission before executing current cycle’s transmission. Therefore, each ONU enters power-saving mode between two consecutive upstream transmissions with a self-defined sleep time immediately after the completion of the current cycle’s transmission. In addition, when the sleep time expires, the ONUs can prolong himself the power-saving mode without waking up in every cycle if specific conditions are satisfied and consequently, no sleep-control message between the ONU and the optical line terminal is required. Thus, energy can be saved at ONUs during the idle time between consecutive cycle transmissions or over several cycles by allowing the ONUs enter power-saving mode under ONU’s self-decision. The simulation results demonstrate that the power consumption of ONUs could be reduced by 52.5– 56.0% over the entire traffic load.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134442798","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517195
Kuhaneswaran Banujan, B. Kumara, Incheon Paik
A natural disaster is a natural event which can cause damage to both lives and properties. The detection of natural disasters is a significant and non-trivial problem. Social media (SM) is a powerful resource to improve the management of disaster situations. Post-disaster management can be improved to a great extent if we mine the SM properly because SM is capable of real-time nature of sharing the information. In this paper, we proposed an approach to enhance post-natural disaster management activities by identifying the correct location and disaster type. As the first step, we fetch the twitter posts using predefined keywords relating to the disaster from Twitter API. Those posts were cleaned and the noise was reduced at the second stage. Then in the third stage, we get the geolocation and disaster type. Named Entity Recognizer library and Google Maps Geocoding API was used for getting the geolocation. We did the same three stages for news which was fetched from News API. As a final stage, we compared the twitter datum with news datum to give the rating for the trueness of each Twitter post. “More accurate” rating was obtained for 24% of the posts. 15% and 13% of the posts showed “Moderately accurate” and “Less accurate” rating respectively. “No correlation” was obtained for 48% of the posts. The precision of 85% for Twitter posts filtering and 92% for News posts filtering were obtained when compared to the posts manually. We strongly believe that using this model we can alert the organizations to do their disaster management activities in a timely manner. We are planning to extend our work with the weather data and as well as with other social media to provide more scaled ratings.
{"title":"Twitter and Online News analytics for Enhancing Post-Natural Disaster Management Activities","authors":"Kuhaneswaran Banujan, B. Kumara, Incheon Paik","doi":"10.1109/ICAWST.2018.8517195","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517195","url":null,"abstract":"A natural disaster is a natural event which can cause damage to both lives and properties. The detection of natural disasters is a significant and non-trivial problem. Social media (SM) is a powerful resource to improve the management of disaster situations. Post-disaster management can be improved to a great extent if we mine the SM properly because SM is capable of real-time nature of sharing the information. In this paper, we proposed an approach to enhance post-natural disaster management activities by identifying the correct location and disaster type. As the first step, we fetch the twitter posts using predefined keywords relating to the disaster from Twitter API. Those posts were cleaned and the noise was reduced at the second stage. Then in the third stage, we get the geolocation and disaster type. Named Entity Recognizer library and Google Maps Geocoding API was used for getting the geolocation. We did the same three stages for news which was fetched from News API. As a final stage, we compared the twitter datum with news datum to give the rating for the trueness of each Twitter post. “More accurate” rating was obtained for 24% of the posts. 15% and 13% of the posts showed “Moderately accurate” and “Less accurate” rating respectively. “No correlation” was obtained for 48% of the posts. The precision of 85% for Twitter posts filtering and 92% for News posts filtering were obtained when compared to the posts manually. We strongly believe that using this model we can alert the organizations to do their disaster management activities in a timely manner. We are planning to extend our work with the weather data and as well as with other social media to provide more scaled ratings.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132452988","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517220
R. Funaki, Kenta Sugimoto, J. Murata
Recently, interactive evolutionary computation (IEC) has been extensively applied in those systems that recommend objects, such as images and sounds, to users based on their preference. If an IEC user’s evaluation criteria are clearly known, they can be utilized for acceleration of IEC, merchandise development, and creativity support for designers. It is difficult to collect a large volume of evaluation data for their analysis because an IEC user cannot repeat the evaluation so many times. Therefore, the technique proposed in this study adopts paired comparison-based interactive differential evolution (IDE) to ease the burden of users, and it will extract the user evaluation criteria through less number of evaluation steps. These techniques estimate the user evaluation criteria using the distribution of solutions because IDE does not receive the evaluation values from its user. Techniques are proposed that estimate, through the IEC processes, the degree of influence of each variable on the evaluation by any given user. During the simulations, the proposed methods are evaluated on test problems.
{"title":"Estimation of Influence of Each Variable on User’s Evaluation in Interactive Evolutionary Computation","authors":"R. Funaki, Kenta Sugimoto, J. Murata","doi":"10.1109/ICAWST.2018.8517220","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517220","url":null,"abstract":"Recently, interactive evolutionary computation (IEC) has been extensively applied in those systems that recommend objects, such as images and sounds, to users based on their preference. If an IEC user’s evaluation criteria are clearly known, they can be utilized for acceleration of IEC, merchandise development, and creativity support for designers. It is difficult to collect a large volume of evaluation data for their analysis because an IEC user cannot repeat the evaluation so many times. Therefore, the technique proposed in this study adopts paired comparison-based interactive differential evolution (IDE) to ease the burden of users, and it will extract the user evaluation criteria through less number of evaluation steps. These techniques estimate the user evaluation criteria using the distribution of solutions because IDE does not receive the evaluation values from its user. Techniques are proposed that estimate, through the IEC processes, the degree of influence of each variable on the evaluation by any given user. During the simulations, the proposed methods are evaluated on test problems.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"102 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116296113","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517249
Yue Sheng, Shuang Liu, Wen Wang, Yuchen He, Xiaoya Liu, Yufeng Ke, X. An, Dong Ming
Most visual brain-computer interface (BCI) speller based on the event related potential (ERP) primarily use matrix layouts, and often need patients to complete spelling with moderate eye movement. The fundamental aim of our study is to enhance the perceptibility of target characters by introducing classical rapid serial visual presentation (RSVP) spellers that do not require any eye movement, thereby applying them to the paralyzed patients suffered from oculomotor nerve dysfunction, such as amyotrophic lateral sclerosis (ALS), spinal cord injury, stroke or muscular dystrophy. To test the feasibility of the proposed RSVP paradigm based-BCI, a series of symbols exploded quickly for 20 participants. The flash stimulus on time was 88 ms, and the off time was 22 ms. The effects of sequential letters on target induction with different colors were studied. The P300 component was locked on the target representation by time. The offline classification showed that the average accuracy of choosing the target symbol among 26 possibilities was as high as 90% and above. When calculating the accuracy across subjects under the condition of a certain sample size, the classification rate was changing, up to 68% with the increase of the number of subjects in the sample. The results showed that RSVP speller based-BCI is a promising new model and can be applied to patients with eye movement disorder.
{"title":"A Study on RSVP Paradigm Based on Brain Computer Interface Across Subjects","authors":"Yue Sheng, Shuang Liu, Wen Wang, Yuchen He, Xiaoya Liu, Yufeng Ke, X. An, Dong Ming","doi":"10.1109/ICAWST.2018.8517249","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517249","url":null,"abstract":"Most visual brain-computer interface (BCI) speller based on the event related potential (ERP) primarily use matrix layouts, and often need patients to complete spelling with moderate eye movement. The fundamental aim of our study is to enhance the perceptibility of target characters by introducing classical rapid serial visual presentation (RSVP) spellers that do not require any eye movement, thereby applying them to the paralyzed patients suffered from oculomotor nerve dysfunction, such as amyotrophic lateral sclerosis (ALS), spinal cord injury, stroke or muscular dystrophy. To test the feasibility of the proposed RSVP paradigm based-BCI, a series of symbols exploded quickly for 20 participants. The flash stimulus on time was 88 ms, and the off time was 22 ms. The effects of sequential letters on target induction with different colors were studied. The P300 component was locked on the target representation by time. The offline classification showed that the average accuracy of choosing the target symbol among 26 possibilities was as high as 90% and above. When calculating the accuracy across subjects under the condition of a certain sample size, the classification rate was changing, up to 68% with the increase of the number of subjects in the sample. The results showed that RSVP speller based-BCI is a promising new model and can be applied to patients with eye movement disorder.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128285641","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517252
Rojanee Khummongkol, M. Yokota
This paper describes an original methodology for cross-language paraphrase via intermediate semantic expression in a knowledge representation language called Mental-image Description Language $(L_{md)}$ and its application to an experimental system for English-Thai translation. This system interprets English text into $L_{md}$ expression to understand it and interprets the understanding result into Thai text without using any syntactic information of the input English text. That is, the system performs free translation, namely, generates target language texts only from intermediate semantic representations of source language texts. It works as one kind of inter-Iingual machine translation system but actually is a subsystem of our natural language understanding system to paraphrase an input text in another language. Some experimental results were evaluated by several native Thai speakers with good knowledge of English, which gave a good perspective to our future work on this system.
{"title":"Experiment on English-Thai Machine Translation via Text Understanding Based on Mental Image Directed Semantic Theory","authors":"Rojanee Khummongkol, M. Yokota","doi":"10.1109/ICAWST.2018.8517252","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517252","url":null,"abstract":"This paper describes an original methodology for cross-language paraphrase via intermediate semantic expression in a knowledge representation language called Mental-image Description Language $(L_{md)}$ and its application to an experimental system for English-Thai translation. This system interprets English text into $L_{md}$ expression to understand it and interprets the understanding result into Thai text without using any syntactic information of the input English text. That is, the system performs free translation, namely, generates target language texts only from intermediate semantic representations of source language texts. It works as one kind of inter-Iingual machine translation system but actually is a subsystem of our natural language understanding system to paraphrase an input text in another language. Some experimental results were evaluated by several native Thai speakers with good knowledge of English, which gave a good perspective to our future work on this system.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129836993","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 : 2018-09-01DOI: 10.1109/ICAWST.2018.8517219
K. Murata, Masataka Mito, Daisuke Eguchi, Yuichiro Mori, M. Toyonaga
IoT cameras and sensors collect images and sensing data from everywhere in the world to transmit them via the Internet. These collected images are stacked into the servers, and an image recognition system on the server, such as CNN (Convolutional Neural Net), mines valuable information. In the near future, when the enormous number of IoTs collect images at various places, these servers would reach an overflow. Hence, if IoTs would send not only images but also analyzed results to the server, it would reduce server loads; however, the conventional CNN is too large to implement this.We propose a single-filter CNN model that can be implemented even ona small IoT. Our CNN model is of minimal configuration with an input layer, an affine transformation layer, a convolution layer, a pooling layer, and a fully connection layer.We evaluate our proposed CNN model with two experiments. First, we check whether it can learn the eleven basic shapes, i.e., a circle, a triangle, a square, etc. Second, we check whether it can classify the basic shapes against their shape reduction and their noise mixture. Results of the first experiment show that our system can classify all the basic shapes perfectly, results of the second experiment show that accuracy depends on the types of filters for both the scaled-shape classification and the inverse-pixel noiseshape classification.
{"title":"A Single Filter CNN Performance for Basic Shape Classification","authors":"K. Murata, Masataka Mito, Daisuke Eguchi, Yuichiro Mori, M. Toyonaga","doi":"10.1109/ICAWST.2018.8517219","DOIUrl":"https://doi.org/10.1109/ICAWST.2018.8517219","url":null,"abstract":"IoT cameras and sensors collect images and sensing data from everywhere in the world to transmit them via the Internet. These collected images are stacked into the servers, and an image recognition system on the server, such as CNN (Convolutional Neural Net), mines valuable information. In the near future, when the enormous number of IoTs collect images at various places, these servers would reach an overflow. Hence, if IoTs would send not only images but also analyzed results to the server, it would reduce server loads; however, the conventional CNN is too large to implement this.We propose a single-filter CNN model that can be implemented even ona small IoT. Our CNN model is of minimal configuration with an input layer, an affine transformation layer, a convolution layer, a pooling layer, and a fully connection layer.We evaluate our proposed CNN model with two experiments. First, we check whether it can learn the eleven basic shapes, i.e., a circle, a triangle, a square, etc. Second, we check whether it can classify the basic shapes against their shape reduction and their noise mixture. Results of the first experiment show that our system can classify all the basic shapes perfectly, results of the second experiment show that accuracy depends on the types of filters for both the scaled-shape classification and the inverse-pixel noiseshape classification.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130266092","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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