{"title":"Variable Width Rough-Fuzzy c-Means","authors":"A. Ferone, A. Galletti, A. Maratea","doi":"10.1109/SITIS.2017.81","DOIUrl":"https://doi.org/10.1109/SITIS.2017.81","url":null,"abstract":"The richness of soft clustering algorithms in the scientific literature reflects from one side the complexity of the underlying problem and from the other the many attempts that have been made to preserve interpretability while modeling vagueness through different theories. In this paper a hybrid rough-fuzzy unsupervised learning algorithm called Variable Width Rough-Fuzzy c-Means (VWRFCM) is derived from a unifying view of the most popular crisp, fuzzy, rough and fuzzy-rough partitive clustering algorithms. VWRFCM provides a user-defined parameter that sets the width of the core regions of all clusters in a probabilistic sense, allowing the domain experts to have both an intuitive interpretation and a powerful control possibility on the maximum allowed degree of vagueness in the clustering solution. Tests on several real datasets show a good effectiveness together with a speed-up in efficiency of VWRFCM compared to its baseline competitors.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124273960","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":"Opposition-Based Sine Cosine Algorithm (OSCA) for Training Feed-Forward Neural Networks","authors":"Divya Bairathi, D. Gopalani","doi":"10.1109/SITIS.2017.78","DOIUrl":"https://doi.org/10.1109/SITIS.2017.78","url":null,"abstract":"Neural network is an effective machine learning technique for classification and regression. In recent studies many stochastic population based techniques are applied to train neural networks. In this paper, Opposition-Based Sine Cosine Algorithm (OSCA) is applied for feed-forward neural network (FNN) training. OSCA is a new population based metaheuristic, which is improved version of Sine Cosine Algorithm (SCA) and uses the opposition based learning (OBL) for better exploration. Performance is analysed and compared with Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Evolution Strategy (ES) for eight different datasets.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133732381","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":"Toward Altmetric-Driven Research-Paper Recommender System Framework","authors":"Maake Benard Magara, S. Ojo, T. Zuva","doi":"10.1109/SITIS.2017.21","DOIUrl":"https://doi.org/10.1109/SITIS.2017.21","url":null,"abstract":"The volume of literature and more particularly research-oriented publications is growing at an exponential rate, and better tools and methodologies are required to efficiently and effectively retrieve desired documents. The development of academic search engines, digital libraries and archives has led to better information filtering mechanisms that has resulted to improved search results. However, the state-of-the art research-paper recommender systems are still retrieving research articles without explicitly defining the domain of interest of the researchers. Also, a rich set of research output (research objects) and their associated metrics are also not being utilized in the process of searching, querying, retrieving and recommending articles. Consequently, a lot of irrelevant and unrelated information is being presented to the user. Then again, the use of citation counts to rank and recommend research-paper to users is still disputed. Recommendation metrics like citation counts, ratings in collaborative filtering, and keyword analysis' cannot be fully relied on as the only techniques through which similarity between documents can be computed, and this is because recommendations based on such metrics are not accurate and have lots of biasness. Henceforth, altmetric-based techniques and methodologies are expected to give better recommendations of research papers since the circumstances surrounding a research papers are taken into consideration. This paper proposes a research paper recommender system framework that utilizes paper ontology and Altmetric from research papers, to enhance the performance of research paper recommender systems.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"40 1-8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123379365","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}
Alain Trésor Kemgue, O. Monga, S. M. Mpong, S. Foufou
{"title":"Modelling Complex Volume Shape Using Ellipsoid: Application to Pore Space Representation","authors":"Alain Trésor Kemgue, O. Monga, S. M. Mpong, S. Foufou","doi":"10.1109/SITIS.2017.52","DOIUrl":"https://doi.org/10.1109/SITIS.2017.52","url":null,"abstract":"Natural shapes have complex volume forms that are usually difficult to model using simple analytical equations. The complexity of the representation is due to the heterogeneity of the physical environment and the variety of phenomena involved. In this study we consider the representation of the porous media. Thanks to the technological advances in Computed Topography scanners, the acquisition of images of complex shapes becomes possible. However, and unfortunately, the image data is not directly usable for simulation purposes. In this paper, we investigate the modeling of such shapes using a piece wise approximation of image data by ellipsoids. We propose to use a split-merge strategy and a region growing algorithm to optimize a functional including an error term and a scale term. The input of our algorithm is voxel-based shape description and the result is a set of tangent or disjoint ellipsoids representing the shape in an intrinsic way. We apply our method to represent 3D soil pore space from CT volume images. Within this specific context, we validate our geometrical modelling by using it for water draining simulation in porous media.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124614711","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":"Texture Based Video Steganography Technique Using Block-Wise Encryption","authors":"S. Goyal, Maninder Singh Nehra","doi":"10.1109/SITIS.2017.28","DOIUrl":"https://doi.org/10.1109/SITIS.2017.28","url":null,"abstract":"Video steganography is the technique which can hide the sensitive text data. In the past times, various techniques have been proposed for video steganography which is broadly into wavelet transformation and discrete transformation. In this research paper, novel technique has been proposed which is based on textual feature extraction, selection and encryption. The GLCM algorithm is applied for the textual feature analysis, PCA algorithm is used for feature selection and block wise encryption is applied to generate final stegno image. The proposed algorithm is implemented in MATLAB and it has been analyzed that it performs well in terms of PSNR and MSE.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114479909","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}
Christian S. Wirawan, Hu Qingyao, Liu Yi, Senglidet Yean, Bu-Sung Lee, Fang Ran
{"title":"Pholder: An Eye-Gaze Assisted Reading Application on Android","authors":"Christian S. Wirawan, Hu Qingyao, Liu Yi, Senglidet Yean, Bu-Sung Lee, Fang Ran","doi":"10.1109/SITIS.2017.64","DOIUrl":"https://doi.org/10.1109/SITIS.2017.64","url":null,"abstract":"Eye-gaze has been used extensively in human computer interface design, web layout design and as assistive technology. We successfully built a reading application with automatic scrolling, using the images captured by the in-build camera to determine the eye-gaze. The application, Pholder, uses the appearance-based method for gaze estimation and tracking of gaze movement directions for scrolling of the screen. We used an innovative technique, using the integration of pixel intensity, for gaze movement estimation which is more robust then other techniques.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117073912","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":"Classification in Big Image Datasets Using Layered-SOM","authors":"Akihiko Nakagawa, Andrea Kutics","doi":"10.1109/SITIS.2017.33","DOIUrl":"https://doi.org/10.1109/SITIS.2017.33","url":null,"abstract":"Adequately classifying big image datasets containing images of arbitrary domains is getting more and more important nowadays. However the above mentioned problem has yet to be solved generally. The most suitable descriptors recognizing possible underlying structures and similar characteristics within large image datasets have to be selected and combined in order to carry out multi-feature analysis and thus image classification. This paper presents an enhancement of the original SOM via developing an unsupervised learning method using multiple layers. This method is appropriate of analyzing and classifying big image datasets with combining multiple image descriptors nonlinearly. It increases the precision of image clustering as well as reducing the time required for computation.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130716641","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":"New Color Filter Array Interpolation Method Based on Mixed Color Channel Correlation","authors":"Yipeng Hua, Xiaoyang Miao, Xiangdong Chen","doi":"10.1109/SITIS.2017.51","DOIUrl":"https://doi.org/10.1109/SITIS.2017.51","url":null,"abstract":"In this paper, we proposed a new demosaicking method based on mixed color channel correlation. Different from conventional interpolation methods based on only two or four directions, the proposed method exploits the mixed color channel correlation within the local sliding window to improve the interpolation performance. The principle idea of our proposed method is based on the correlation of spatial closeness and spectral similarity between the high and low-resolution from the raw CFA image. By using geometric duality of Bayer CFA pattern, a robust interpolation model is proposed with optimal interpolation coefficients. As compared with the latest demosaicking algorithms, experiments show that the proposed algorithm provides superior performance in terms of both objective and subjective image qualities.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127627803","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":"I Am 'Totally' Human: Bypassing the reCaptcha","authors":"S. S. Brown, Nicholas DiBari, Sajal Bhatia","doi":"10.1109/SITIS.2017.13","DOIUrl":"https://doi.org/10.1109/SITIS.2017.13","url":null,"abstract":"In recent years, website administrators have searched for a tool to prevent automated “bots” from using their sites' resources, hindering legitimate user access. By offering a “challenge” in the form of analyzing a picture for certain features, matching like symbols from a selection, or listening to an audio clip and transcribing the text, these tasks are intended to be easy for humans to solve but impossible for a program to overcome. More recently, there have been many successful attempts at using modern technology to automate passing these challenges. In this paper, we propose a simple approach which makes use of open-source tools (reCaptcha Widget, Selenium – a proxy server pool and a public Speech to Text API) to circumvent the reCaptcha tool utilized by Google. Preliminary results demonstrate an approximately 35% success rate which can be easily improved with minor modification. However, the focal point is the simplicity of the proposed approach to highlight the vulnerability of Google's reCaptcha tool against Speech to Text API attack.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134599885","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":"Adaptive Reuse of Cultural Heritage Elements and Fragments in Public Spaces: The Internet of Cultural Things and Applications as Infrastructures for Learning in Smart Cities","authors":"H. McKenna","doi":"10.1109/SITIS.2017.84","DOIUrl":"https://doi.org/10.1109/SITIS.2017.84","url":null,"abstract":"This work explores mechanisms for realization of the Internet of Cultural Things (IoCT) and applications in public spaces in the context of learning cities and smart cities. Focusing on the constructs of awareness, learning, and engagement, the purpose of this work is to explore the potential for animating cultural heritage elements or fragments using the IoCT and applications in public spaces. Theoretically this work is situated at the intersection of adaptive reuse and designing for deconstruction enabled by the IoCT and applications in support of learning cities and smart cities. Using a case study approach, qualitative and quantitative data are gathered through in-depth interviews and an online survey. Anecdotal evidence is also gathered in parallel with this study through group and individual interviews enabling further analysis and triangulation of data. This work makes a contribution to the research literature across several domains – the IoCT and applications, cultural heritage, learning cities, and smart cities. This work also contributes to the discussion and debate spaces for ambient culture and ambient heritage with the potential to influence new directions for future research and practice.","PeriodicalId":153165,"journal":{"name":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132877128","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}