P. R. S. C. Junior, Alexandre Abreu de Freitas, Rafael Daisuke Akiyama, B. Miranda, Tiago Araújo, Carlos G. R. Santos, B. Meiguins, J. Morais
Different information visualization techniques can be found in the literature due to the quantity and variety of data stored in computational systems. In this context, the classification of chart images becomes important because it allows various types of graphs to be detected automatically in different contexts, allowing a more specific processing for each type of visualization, for example, data extraction. Several techniques of image classification can be used, where the most common are based on the extraction of features of the images, and a later classification using these features. However, one technique that has been gaining prominence in the context of image classification is the Convolutional Neural Network (CNN). This technique is based on deep learning and, in a way, encapsulates the feature extraction process. In this way, the proposal of this article is to use an architecture of a client-server based model to do the chart image classification and later data extraction from this image. The main advantage is doing the CNN processing on the server side, so the application does not rely on client device limitations. For this, an image dataset was generated from the web, and it has ten classes of graphs. From the experiments done, it was seen that the use of this technique was feasible, and modifications in the architecture can be made as a proposal to improve the accuracy of the model.
{"title":"Architecture Proposal for Data Extraction of Chart Images Using Convolutional Neural Network","authors":"P. R. S. C. Junior, Alexandre Abreu de Freitas, Rafael Daisuke Akiyama, B. Miranda, Tiago Araújo, Carlos G. R. Santos, B. Meiguins, J. Morais","doi":"10.1109/iV.2017.37","DOIUrl":"https://doi.org/10.1109/iV.2017.37","url":null,"abstract":"Different information visualization techniques can be found in the literature due to the quantity and variety of data stored in computational systems. In this context, the classification of chart images becomes important because it allows various types of graphs to be detected automatically in different contexts, allowing a more specific processing for each type of visualization, for example, data extraction. Several techniques of image classification can be used, where the most common are based on the extraction of features of the images, and a later classification using these features. However, one technique that has been gaining prominence in the context of image classification is the Convolutional Neural Network (CNN). This technique is based on deep learning and, in a way, encapsulates the feature extraction process. In this way, the proposal of this article is to use an architecture of a client-server based model to do the chart image classification and later data extraction from this image. The main advantage is doing the CNN processing on the server side, so the application does not rely on client device limitations. For this, an image dataset was generated from the web, and it has ten classes of graphs. From the experiments done, it was seen that the use of this technique was feasible, and modifications in the architecture can be made as a proposal to improve the accuracy of the model.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"239 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114098220","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}
Constructing a curve that incorporates the intrinsic feature of data is of immense importance in the realms of data visualization, computer graphics and computer aided geometric design. In this paper, most general types of positive data has been envisaged.For this purpose, a piecewise, C1 rational cubic piecewise trigonometric function has been constrained on parameters to retain inherent data shape.
{"title":"Visualization of Constrained Data Using Trigonometric Splines","authors":"Farheen Ibraheem, M. Hussain","doi":"10.1109/iV.2017.32","DOIUrl":"https://doi.org/10.1109/iV.2017.32","url":null,"abstract":"Constructing a curve that incorporates the intrinsic feature of data is of immense importance in the realms of data visualization, computer graphics and computer aided geometric design. In this paper, most general types of positive data has been envisaged.For this purpose, a piecewise, C1 rational cubic piecewise trigonometric function has been constrained on parameters to retain inherent data shape.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130659617","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}
M. Nakaya, Masahiro Okawa, M. Nakajima, H. Tominaga
Practical education about information security is needed for system developers and administrators in Web service suppliers. We propose a hacking contest CTF as attack and defense style with a website for a multiple online game. The contest organizer prepares a game server site as a contest environment which contains several vulnerability. The contest participants are divided into an attacker team as game players and a defender team as game Website operators. While the attackers access the game site with normal actions, they find vulnerabilities and try cheating actions. While the defenders monitor server logs, they detect illegal events and prevent them for maintenance. An action of each side is calculated as a point and makes each score for victory or defeat by the contest rule. The contest organizer reviews the progress situation with all participants. In this paper, we introduce several functions of a trial system and discuss the result of a trial practice.
{"title":"A Support Environment and a Trial Practice of Hacking Contest with Attack and Defense Style on a Game Website","authors":"M. Nakaya, Masahiro Okawa, M. Nakajima, H. Tominaga","doi":"10.1109/iV.2017.78","DOIUrl":"https://doi.org/10.1109/iV.2017.78","url":null,"abstract":"Practical education about information security is needed for system developers and administrators in Web service suppliers. We propose a hacking contest CTF as attack and defense style with a website for a multiple online game. The contest organizer prepares a game server site as a contest environment which contains several vulnerability. The contest participants are divided into an attacker team as game players and a defender team as game Website operators. While the attackers access the game site with normal actions, they find vulnerabilities and try cheating actions. While the defenders monitor server logs, they detect illegal events and prevent them for maintenance. An action of each side is calculated as a point and makes each score for victory or defeat by the contest rule. The contest organizer reviews the progress situation with all participants. In this paper, we introduce several functions of a trial system and discuss the result of a trial practice.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132735745","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}
A weighted free tree is an undirected connected graph with no cycles whose edges and nodes have weights (positive real numbers). The purpose of our research is to support the comparative analysis of weighted free trees. The fundamental categories of visualization techniques that support comparison are juxtaposition, superposition, and explicit encoding. Juxtaposition is often used for comparison. However, the cognitive load required to grasp a difference is large. Superposition is effective for recognizing a difference, but select information may be difficult to observe. Explicit encoding is an effective technique specialized in a specific task, but representation switching may occur frequently during analysis. Hence, there is the risk of destructing a viewer's mental map, which reduces work efficiency. We divide the working process of analysis into 14 tasks and develop four visualization techniques that can continually perform these tasks. Moreover, we conduct an experiment to investigate whether our proposed techniques are able to perform these tasks. We confirm that these tasks can be performed efficiently by applying our techniques to a case study that compares two trees.
{"title":"Visualization Techniques for the Comparative Analysis of Weighted Free Trees","authors":"Yuichi Naragino, Kazuo Misue","doi":"10.1109/iV.2017.30","DOIUrl":"https://doi.org/10.1109/iV.2017.30","url":null,"abstract":"A weighted free tree is an undirected connected graph with no cycles whose edges and nodes have weights (positive real numbers). The purpose of our research is to support the comparative analysis of weighted free trees. The fundamental categories of visualization techniques that support comparison are juxtaposition, superposition, and explicit encoding. Juxtaposition is often used for comparison. However, the cognitive load required to grasp a difference is large. Superposition is effective for recognizing a difference, but select information may be difficult to observe. Explicit encoding is an effective technique specialized in a specific task, but representation switching may occur frequently during analysis. Hence, there is the risk of destructing a viewer's mental map, which reduces work efficiency. We divide the working process of analysis into 14 tasks and develop four visualization techniques that can continually perform these tasks. Moreover, we conduct an experiment to investigate whether our proposed techniques are able to perform these tasks. We confirm that these tasks can be performed efficiently by applying our techniques to a case study that compares two trees.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126954770","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}
Rafael L. Dias, S. A. T. Mpinda, Renato Bueno, M. X. Ribeiro
Digital imaging plays an important role in many human activities, such as agriculture and forest management, earth sciences, urban planning, weather forecasting, medical imaging and so on. Processing, exploring and visualizing the inconceivable volumes of such images has turned out to be progressively troublesome. The Content-Based Image Retrieval (CBIR) remains an important issue that finds potential applications, given the place that retrieving digital images similar to a user-defined specification or pattern in huge databases now occupies in the day-to-day. CBIR systems use visual information like color, shape and texture to represent images in feature vectors. In general, there is an inconsistency in the evaluation of similarity between images according to human perception and the results computed by CBIR systems, which is called Semantic Gap. One way to improve CBIR systems is by the addition of techniques to visualize and interact with CBIR regarding similarity and diversity criteria, where the user can participate more actively in the process and steer the results according to its needs. In this paper we present the Visual-Interactive k-NDN Method (ViK): a novel approach to visualize and interact with Content-Based Image Retrieval systems. This paper aims at making use of Visual Data Mining techniques applied to queries in CBIR systems, improving the interpretability of the measure of diversity, applied using fractal analysis, as well as the relevance of results according to the prior knowledge of the user. Therefore, the user takes an active role in the content-based image retrieval, guiding its result and, consequently, reducing the Semantic Gap. Additionally, a better understanding of the diversity and similarity factors involved in the query is supported by visualization and interaction techniques.
{"title":"Visual-Interactive k-NDN Method (VIK): A Novel Approach to Visualize and Interact with Content-Based Image Retrieval Systems Regarding Similarity and Diversity","authors":"Rafael L. Dias, S. A. T. Mpinda, Renato Bueno, M. X. Ribeiro","doi":"10.1109/iV.2017.41","DOIUrl":"https://doi.org/10.1109/iV.2017.41","url":null,"abstract":"Digital imaging plays an important role in many human activities, such as agriculture and forest management, earth sciences, urban planning, weather forecasting, medical imaging and so on. Processing, exploring and visualizing the inconceivable volumes of such images has turned out to be progressively troublesome. The Content-Based Image Retrieval (CBIR) remains an important issue that finds potential applications, given the place that retrieving digital images similar to a user-defined specification or pattern in huge databases now occupies in the day-to-day. CBIR systems use visual information like color, shape and texture to represent images in feature vectors. In general, there is an inconsistency in the evaluation of similarity between images according to human perception and the results computed by CBIR systems, which is called Semantic Gap. One way to improve CBIR systems is by the addition of techniques to visualize and interact with CBIR regarding similarity and diversity criteria, where the user can participate more actively in the process and steer the results according to its needs. In this paper we present the Visual-Interactive k-NDN Method (ViK): a novel approach to visualize and interact with Content-Based Image Retrieval systems. This paper aims at making use of Visual Data Mining techniques applied to queries in CBIR systems, improving the interpretability of the measure of diversity, applied using fractal analysis, as well as the relevance of results according to the prior knowledge of the user. Therefore, the user takes an active role in the content-based image retrieval, guiding its result and, consequently, reducing the Semantic Gap. Additionally, a better understanding of the diversity and similarity factors involved in the query is supported by visualization and interaction techniques.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124606928","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}
Retrieving information based on the users’ preferences and profiles represent a challenging issue to overcome. Moreover, in the public transport field, this task becomes increasingly complex due to the heterogeneous data fetched from various sources. Though, ontologies have emerged in retrieving information field to reduce this complexity. This paper describes a visual framework aiming to search and extract the suitable itinerary that fits better with the user’s information needs and based on the ontologies. The framework relies on three main components: a simple search component, an advanced search based on users’ preferences and profile component and a Question-Answering search component represented in a natural language. Our framework has been implemented and evaluated.
{"title":"An Ontology Driven Framework for Personalized Itinerary Visualization","authors":"Essayeh Aroua, Hajer Baazaoui Zghal, M. Abed","doi":"10.1109/iV.2017.51","DOIUrl":"https://doi.org/10.1109/iV.2017.51","url":null,"abstract":"Retrieving information based on the users’ preferences and profiles represent a challenging issue to overcome. Moreover, in the public transport field, this task becomes increasingly complex due to the heterogeneous data fetched from various sources. Though, ontologies have emerged in retrieving information field to reduce this complexity. This paper describes a visual framework aiming to search and extract the suitable itinerary that fits better with the user’s information needs and based on the ontologies. The framework relies on three main components: a simple search component, an advanced search based on users’ preferences and profile component and a Question-Answering search component represented in a natural language. Our framework has been implemented and evaluated.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121442239","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}
Jari Varsaluoma, H. Väätäjä, T. Heimonen, Katariina Tiitinen, Jaakko Hakulinen, M. Turunen, Harri Nieminen
Analyzing data from complex production systems and processes can be used in improving existing products, processes, and services, and innovating novel offerings. We report the findings from a six-month case study with a company developing flexible manufacturing systems. During a collaborative development process of a data analytics and visualization tool, our goal was to identify potential metrics, business opportunities, and challenges when utilizing logged data of end-users' human-machine interactions in development activities. Our key contributions include a characterization of the potential usage data metrics to be logged and visualized, identification of opportunities this data entails for business, and discussion about the challenges related to usage data logging in the studied context. Finally, we propose topics that should be considered in the organization before investing in usage data logging in the context of flexible manufacturing systems.
{"title":"Usage Data Analytics for Human-Machine Interactions with Flexible Manufacturing Systems: Opportunities and Challenges","authors":"Jari Varsaluoma, H. Väätäjä, T. Heimonen, Katariina Tiitinen, Jaakko Hakulinen, M. Turunen, Harri Nieminen","doi":"10.1109/iV.2017.38","DOIUrl":"https://doi.org/10.1109/iV.2017.38","url":null,"abstract":"Analyzing data from complex production systems and processes can be used in improving existing products, processes, and services, and innovating novel offerings. We report the findings from a six-month case study with a company developing flexible manufacturing systems. During a collaborative development process of a data analytics and visualization tool, our goal was to identify potential metrics, business opportunities, and challenges when utilizing logged data of end-users' human-machine interactions in development activities. Our key contributions include a characterization of the potential usage data metrics to be logged and visualized, identification of opportunities this data entails for business, and discussion about the challenges related to usage data logging in the studied context. Finally, we propose topics that should be considered in the organization before investing in usage data logging in the context of flexible manufacturing systems.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123140722","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}
Alexandre Perrot, Romain Bourqui, N. Hanusse, D. Auber
Heatmap visualization is a well-known type of visualization to alleviate the overplot problem of point visualization. As such, it is well suited to visualize Big Data. In order to tackle the velocity problem of Big Data, one has to leverage streaming computations. Recently, canopy clustering was shown to be well suited for Big Data heatmap visualization. In this article, we present how to design a streaming algorithm to compute canopy clustering using Apache Spark. This result is directly applicable to be included into a lambda architecture.
{"title":"HeatPipe: High Throughput, Low Latency Big Data Heatmap with Spark Streaming","authors":"Alexandre Perrot, Romain Bourqui, N. Hanusse, D. Auber","doi":"10.1109/iV.2017.45","DOIUrl":"https://doi.org/10.1109/iV.2017.45","url":null,"abstract":"Heatmap visualization is a well-known type of visualization to alleviate the overplot problem of point visualization. As such, it is well suited to visualize Big Data. In order to tackle the velocity problem of Big Data, one has to leverage streaming computations. Recently, canopy clustering was shown to be well suited for Big Data heatmap visualization. In this article, we present how to design a streaming algorithm to compute canopy clustering using Apache Spark. This result is directly applicable to be included into a lambda architecture.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127322377","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}
This paper investigates the uses of interactive video as a medium for teaching and learning activities. Based on the characteristics of interactive video annotations, various use cases are proposed and discussed. Two real experiments are then described. The first experiment is to add annotations to a video by teachers to produce course materials. The second is to produce a video and annotations on this video by student as an assessment work. The feedbacks of teachers and students are then summarized and discussed. The goal is to assess their feelings about the production of interactive videos as part of teaching and learning activities.
{"title":"Enriched Interactive Videos for Teaching and Learning","authors":"Clement Benkada, L. Moccozet","doi":"10.1109/iV.2017.74","DOIUrl":"https://doi.org/10.1109/iV.2017.74","url":null,"abstract":"This paper investigates the uses of interactive video as a medium for teaching and learning activities. Based on the characteristics of interactive video annotations, various use cases are proposed and discussed. Two real experiments are then described. The first experiment is to add annotations to a video by teachers to produce course materials. The second is to produce a video and annotations on this video by student as an assessment work. The feedbacks of teachers and students are then summarized and discussed. The goal is to assess their feelings about the production of interactive videos as part of teaching and learning activities.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131697016","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}
The exploration of moderately dense networks is used in various challenges of visual data analysis. Frequently, the solutions lay in graph drawing, based on automatic forcedirected layout, which results in a spontaneous and irreproducible node-link diagram. Currently available approaches to improve its readability are generally oriented to finite rendering without providing to the analyst handy tools for post-layout manipulations. Enabling indirect manual control on visualizations through multi-step menus may appear difficult to learn and use. Thus, this problem requires a more intuitive way of solving. This paper presents an original toolset for userguided refinement of the force-directed graph layout, with a bias on pen-centric sketching techniques.
{"title":"Sketch-Based Interactions for Untangling of Force-Directed Graphs","authors":"V. Guchev, Cristina Gena","doi":"10.1109/iV.2017.64","DOIUrl":"https://doi.org/10.1109/iV.2017.64","url":null,"abstract":"The exploration of moderately dense networks is used in various challenges of visual data analysis. Frequently, the solutions lay in graph drawing, based on automatic forcedirected layout, which results in a spontaneous and irreproducible node-link diagram. Currently available approaches to improve its readability are generally oriented to finite rendering without providing to the analyst handy tools for post-layout manipulations. Enabling indirect manual control on visualizations through multi-step menus may appear difficult to learn and use. Thus, this problem requires a more intuitive way of solving. This paper presents an original toolset for userguided refinement of the force-directed graph layout, with a bias on pen-centric sketching techniques.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"18 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116093298","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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