This paper aims to present a tool named "Stubs and Drivers Generation Tool" which is a web application for generating stub and driver source code from an UML, sequence diagram and a class diagram. Testers can automate the unit testing with our tool. The tool will read the XML file of a sequence diagram and a class diagram. Next, the tool processes the XML file and create a call graph from the sequence diagram. After a tester selects a class under test and set values of the class under test source code attributes, the tool will create the stub and driver from set attributes. The tester can customize the source code and export the source code file for using in the testing process.
{"title":"Stubs and Drivers Generator for Object-Oriented Program Testing Using Sequence and Class Diagrams","authors":"Peerawut Luengruengroj, T. Suwannasart","doi":"10.1109/CSII.2018.00013","DOIUrl":"https://doi.org/10.1109/CSII.2018.00013","url":null,"abstract":"This paper aims to present a tool named \"Stubs and Drivers Generation Tool\" which is a web application for generating stub and driver source code from an UML, sequence diagram and a class diagram. Testers can automate the unit testing with our tool. The tool will read the XML file of a sequence diagram and a class diagram. Next, the tool processes the XML file and create a call graph from the sequence diagram. After a tester selects a class under test and set values of the class under test source code attributes, the tool will create the stub and driver from set attributes. The tester can customize the source code and export the source code file for using in the testing process.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128501755","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}
Childhood education is a precious experience that can foster children's imagination and creativity. Within childhood education, storybook creation can provide a powerful experience that expands children's creativity. We developed a digital storybook-creation tool that can be used in a Web browser. This tool enables children to create cartoon books with handdrawn illustrations that are captured using a tablet's camera. With this tool, children can move and rotate illustrations using multitouch finger gestures and can supplement stories with their own illustrations. We examined the tool in four kindergarten classes, and we ensured that the children could use it with support from adult staff members. We then explained how the tool works, summarized our analysis of the situation and described the usability we observed.
{"title":"An Interactive Storybook-Creation Tool on a Tablet for Kindergarteners","authors":"Y. Niwa, Yasuji Katase, Chieko Hiramatsu","doi":"10.1109/CSII.2018.00010","DOIUrl":"https://doi.org/10.1109/CSII.2018.00010","url":null,"abstract":"Childhood education is a precious experience that can foster children's imagination and creativity. Within childhood education, storybook creation can provide a powerful experience that expands children's creativity. We developed a digital storybook-creation tool that can be used in a Web browser. This tool enables children to create cartoon books with handdrawn illustrations that are captured using a tablet's camera. With this tool, children can move and rotate illustrations using multitouch finger gestures and can supplement stories with their own illustrations. We examined the tool in four kindergarten classes, and we ensured that the children could use it with support from adult staff members. We then explained how the tool works, summarized our analysis of the situation and described the usability we observed.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128155059","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}
To eliminate mismatches between the intentions of questioners and respondents of Question and Answer (Q&A) sites, we have clarified that the impression of the statements could be captured by nine factors, and the factor scores could be estimated from the feature values of the statements. Objective scores of the statements could be estimated fairly good, and that those of subjective statements could be estimated well by taking the natural logarithm of the factor scores with the consideration of cross-validation. With the consideration of semantic similarity between Q&A, semantic similarity could be effective in estimating objective scores in the previous preliminary analysis. This paper tries to perform multiple regression analysis with the consideration of multicollinearity between feature values of semantic similarity with those other than semantic similarity. As a result of analysis, feature values of semantic similarity was obtained as a part of regression formula in 8 out of 15 trials. With the consideration of semantic similarity, average estimation error becomes smaller for three categories.
{"title":"Estimation Improvement of Objective Scores of Answer Statements with Consideration of Multicollinearity and Semantic Similarity","authors":"Yuya Yokoyama, T. Hochin, Hiroki Nomiya","doi":"10.1109/CSII.2018.00036","DOIUrl":"https://doi.org/10.1109/CSII.2018.00036","url":null,"abstract":"To eliminate mismatches between the intentions of questioners and respondents of Question and Answer (Q&A) sites, we have clarified that the impression of the statements could be captured by nine factors, and the factor scores could be estimated from the feature values of the statements. Objective scores of the statements could be estimated fairly good, and that those of subjective statements could be estimated well by taking the natural logarithm of the factor scores with the consideration of cross-validation. With the consideration of semantic similarity between Q&A, semantic similarity could be effective in estimating objective scores in the previous preliminary analysis. This paper tries to perform multiple regression analysis with the consideration of multicollinearity between feature values of semantic similarity with those other than semantic similarity. As a result of analysis, feature values of semantic similarity was obtained as a part of regression formula in 8 out of 15 trials. With the consideration of semantic similarity, average estimation error becomes smaller for three categories.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126477578","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}
{"title":"CSII 2018 International Program Committee","authors":"","doi":"10.1109/csii.2018.00007","DOIUrl":"https://doi.org/10.1109/csii.2018.00007","url":null,"abstract":"","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130573081","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}
T. Pial, Shahreen Salim Aunti, Shabbir Ahmed, Hasnain Heickal
Text to speech synthesis is a well-researched area, yet no system has been developed which can claim to be as convincing as a human voice. An end-to-end system in the context of speech synthesis denotes a system capable of synthesizing speech from text using training data as minimal as transcribed audio data without any language-specific knowledge and phoneme dictionaries. But an end-to-end system should also have the capability to integrate any language-specific rules to improve its performance. In this paper, we propose an end-to-end speech synthesis system for Bangla (also known as Bengali) which uses a minimal front end and a neural network as its statistical parametric model. We also propose a Text Normalization Procedure(TNP) for Bangla and incorporate it to the end-to-end system. We have conducted extensive experiments using different models. From the feedback from the participants of the experiment, we have found out that they felt more positively towards the system if TNP is incorporated. A Wilcoxon signed-rank test was conducted to validate the results of the experiment and the probability of the results being like this because of experimental errors rather than TNP was calculated to be less than 5%.
{"title":"End-to-End Speech Synthesis for Bangla with Text Normalization","authors":"T. Pial, Shahreen Salim Aunti, Shabbir Ahmed, Hasnain Heickal","doi":"10.1109/CSII.2018.00019","DOIUrl":"https://doi.org/10.1109/CSII.2018.00019","url":null,"abstract":"Text to speech synthesis is a well-researched area, yet no system has been developed which can claim to be as convincing as a human voice. An end-to-end system in the context of speech synthesis denotes a system capable of synthesizing speech from text using training data as minimal as transcribed audio data without any language-specific knowledge and phoneme dictionaries. But an end-to-end system should also have the capability to integrate any language-specific rules to improve its performance. In this paper, we propose an end-to-end speech synthesis system for Bangla (also known as Bengali) which uses a minimal front end and a neural network as its statistical parametric model. We also propose a Text Normalization Procedure(TNP) for Bangla and incorporate it to the end-to-end system. We have conducted extensive experiments using different models. From the feedback from the participants of the experiment, we have found out that they felt more positively towards the system if TNP is incorporated. A Wilcoxon signed-rank test was conducted to validate the results of the experiment and the probability of the results being like this because of experimental errors rather than TNP was calculated to be less than 5%.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129671697","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}
Fast Marching method provides a solution to the Eikonal equation, and it also can be used to solve the Shape from Shading problem. But it still has some limitations. This paper proposes a new approach to recover 3-D shape by using improved Fast Marching method. The second-order finite difference, the diagonal grid points, and new update mode is used to improved FMM and the method can recover 3-D shape for Lambert image. Then we propose a method to modify the original Scanning Electron Microscope (SEM) image with intensity modification by using affine transform and NN learning, thus the improved FMM can recover 3-D shape from SEM image. Finally, the results were compared between the proposed method and previous method. Experiment includes numerical experiments, computer simulation experiments and real image. The results show the method is satisfied with Lambert and SEM image, and both robust and accurate.
{"title":"Shape Recovery Using Improved Fast Marching Method for SEM Image","authors":"Y. Iwahori, Lei Huang, Aili Wang, M. Bhuyan","doi":"10.1109/CSII.2018.00018","DOIUrl":"https://doi.org/10.1109/CSII.2018.00018","url":null,"abstract":"Fast Marching method provides a solution to the Eikonal equation, and it also can be used to solve the Shape from Shading problem. But it still has some limitations. This paper proposes a new approach to recover 3-D shape by using improved Fast Marching method. The second-order finite difference, the diagonal grid points, and new update mode is used to improved FMM and the method can recover 3-D shape for Lambert image. Then we propose a method to modify the original Scanning Electron Microscope (SEM) image with intensity modification by using affine transform and NN learning, thus the improved FMM can recover 3-D shape from SEM image. Finally, the results were compared between the proposed method and previous method. Experiment includes numerical experiments, computer simulation experiments and real image. The results show the method is satisfied with Lambert and SEM image, and both robust and accurate.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"864 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115113546","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}
Morphology is an important research method that reveals the properties of materials. Each material has a unique scattering pattern that it depends on the kind of material, preparation method, and the composition of the blends. These scattering patterns are captured to images by the scanning electron microscopy (SEM). Since there are a lot of scattering patterns, it is very hard to interpret and recognize the scattering pattern of any materials. This work applied the CNN model to recognize the scattering pattern in the SEM images by creating the appropriate model that suits for recognize these images. The SEM image dataset was built and characterized the model structure. The experiment results reveal that the CNN model could significantly recognized the SEM images. In which way, this work could solve the problem of false interpretation of the material morphology and improve the efficiency of classification obviously. Moreover, the CNN model could recognize the scattering pattern with an accuracy at 97.02% and 2.98% of error. A contribution of this study is a new utilization of SEM images classification and recognition, which utilize the laboratory experiments. This work also created the SEM images dataset which is a new knowledge for enhancing the morphology study in the material engineering.
{"title":"Convolutional Neural Network Models for Scattering Pattern Recognition of Scanning Electron Microscopy Images","authors":"M. Phankokkruad, S. Wacharawichanant","doi":"10.1109/CSII.2018.00012","DOIUrl":"https://doi.org/10.1109/CSII.2018.00012","url":null,"abstract":"Morphology is an important research method that reveals the properties of materials. Each material has a unique scattering pattern that it depends on the kind of material, preparation method, and the composition of the blends. These scattering patterns are captured to images by the scanning electron microscopy (SEM). Since there are a lot of scattering patterns, it is very hard to interpret and recognize the scattering pattern of any materials. This work applied the CNN model to recognize the scattering pattern in the SEM images by creating the appropriate model that suits for recognize these images. The SEM image dataset was built and characterized the model structure. The experiment results reveal that the CNN model could significantly recognized the SEM images. In which way, this work could solve the problem of false interpretation of the material morphology and improve the efficiency of classification obviously. Moreover, the CNN model could recognize the scattering pattern with an accuracy at 97.02% and 2.98% of error. A contribution of this study is a new utilization of SEM images classification and recognition, which utilize the laboratory experiments. This work also created the SEM images dataset which is a new knowledge for enhancing the morphology study in the material engineering.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125762456","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}
Post-it notes are popular on meetings, such as brainstorming or card sorting. On brainstorming, we arrange paper cards for grouping. The positional relationship of paper notes is important. However, there is a problem between an image resolution and positional relationship of paper notes. Extraction of the paper notes content requires high resolution image data. As a capture point is close to paper notes, positional relationship of paper notes is less clear. More and more paper notes make that problem tangible. We present a method to solve the trade-off problem about the positional relationship on extracting paper sticky notes. We developed three extract mode: Single shot, Semi auto, and Full auto. Our method extends the area where we use for brainstorming. The result of experimental evaluation shows that our system can project virtual cards at the same position as the original accurately.
{"title":"Extracting Paper Sticky Notes with Visual-Inertial Odometry of ARKit","authors":"Eishun Ito, Tadachika Ozono, T. Shintani","doi":"10.1109/CSII.2018.00014","DOIUrl":"https://doi.org/10.1109/CSII.2018.00014","url":null,"abstract":"Post-it notes are popular on meetings, such as brainstorming or card sorting. On brainstorming, we arrange paper cards for grouping. The positional relationship of paper notes is important. However, there is a problem between an image resolution and positional relationship of paper notes. Extraction of the paper notes content requires high resolution image data. As a capture point is close to paper notes, positional relationship of paper notes is less clear. More and more paper notes make that problem tangible. We present a method to solve the trade-off problem about the positional relationship on extracting paper sticky notes. We developed three extract mode: Single shot, Semi auto, and Full auto. Our method extends the area where we use for brainstorming. The result of experimental evaluation shows that our system can project virtual cards at the same position as the original accurately.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129550178","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}
We can enjoy sightseeing more by communicating with friends. Communication with friends is about sightseeing spots. Recently, we can get information of sightseeing spots from a trip guide system through a smartphone or tablet. However, these systems provide information even in unnecessary situations, which may interfere with sightseeing. So, we proposed ways to estimate the mood of tourists using wearable devices. This paper describes the usefulness of information systems and systems developed based on that method. This information system detects an excitement degree of the party in a place through by using a pulse rate of all tourists which are collected by the Apple Watch. And it offers the information of spot for changing the mood of the party when they are not enjoying sightseeing. In the evaluation experiment of three group, this information system has been found to be useful. However, the experiment result shows that information service in this time to the members to shift their emotions to positive is not effective. In the future, it is necessary to consider how to provide and contents.
{"title":"Information System for Estimating People's Mood at Sightseeing Using Their Pulses Information","authors":"Yusuke Ikematsu, A. Ogino","doi":"10.1109/CSII.2018.00034","DOIUrl":"https://doi.org/10.1109/CSII.2018.00034","url":null,"abstract":"We can enjoy sightseeing more by communicating with friends. Communication with friends is about sightseeing spots. Recently, we can get information of sightseeing spots from a trip guide system through a smartphone or tablet. However, these systems provide information even in unnecessary situations, which may interfere with sightseeing. So, we proposed ways to estimate the mood of tourists using wearable devices. This paper describes the usefulness of information systems and systems developed based on that method. This information system detects an excitement degree of the party in a place through by using a pulse rate of all tourists which are collected by the Apple Watch. And it offers the information of spot for changing the mood of the party when they are not enjoying sightseeing. In the evaluation experiment of three group, this information system has been found to be useful. However, the experiment result shows that information service in this time to the members to shift their emotions to positive is not effective. In the future, it is necessary to consider how to provide and contents.","PeriodicalId":202365,"journal":{"name":"2018 5th International Conference on Computational Science/ Intelligence and Applied Informatics (CSII)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126217606","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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