{"title":"Static hand gesture recognition using stacked Denoising Sparse Autoencoders","authors":"Varun Kumar, G. Nandi, R. Kala","doi":"10.1109/IC3.2014.6897155","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897155","url":null,"abstract":"With the advent of personal computers, humans have always wanted to communicate with them in either their natural language or by using gestures. This gave birth to the field of Human Computer Interaction and its subfield Automatic Sign Language Recognition. This paper proposes the method of automatic feature extraction of the images of hand. These extracted features are then used to train the Softmax classifier to classify them into 20 classes. Five stacked Denoising Sparse Autoencoders (DSAE) trained in unsupervised fashion are used to extract features from image. The proposed architecture is trained and tested on a standard dataset [1] which was extended by adding random jitters such as rotation and Gaussian noise. The performance of the proposed architecture is 83% which is better than shallow Neural Network trained on manual hand-engineered features called Principal Components which is used as a benchmark.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114995400","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":"Information metrics for low-rate DDoS attack detection: A comparative evaluation","authors":"M. Bhuyan, D. Bhattacharyya, J. Kalita","doi":"10.1109/IC3.2014.6897151","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897151","url":null,"abstract":"Invasion by Distributed Denial of Service (DDoS) is a serious threat to services offered on the Internet. A low-rate DDoS attack allows legitimate network traffic to pass and consumes low bandwidth. So, detection of this type of attacks is very difficult in high speed networks. Information theory is popular because it allows quantifications of the difference between malicious traffic and legitimate traffic based on probability distributions. In this paper, we empirically evaluate several information metrics, namely, Hartley entropy, Shannon entropy, Renyi's entropy and Generalized entropy in their ability to detect low-rate DDoS attacks. These metrics can be used to describe characteristics of network traffic and an appropriate metric facilitates building an effective model to detect low-rate DDoS attacks. We use MIT Lincoln Laboratory and CAIDA DDoS datasets to illustrate the efficiency and effectiveness of each metric for detecting mainly low-rate DDoS attacks.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130464461","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":"Automated generation of song lyrics using CFGs","authors":"S. Pudaruth, Sandiana Amourdon, Joey Anseline","doi":"10.1109/IC3.2014.6897243","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897243","url":null,"abstract":"This paper gives an overview of how challenging song writing is and gives an insight on how we developed a semi-automatic lyric generator for English songs. Writing lyrics has always been a challenging task as it involves not only creativity but also inspiration. Prior to implementation of the lyrics generator, much analysis were carried out so as to get in-depth information about the requirements of good lyrics. Research has been done in various fields such as artificial intelligence and natural language processing to be able to master the various techniques for text processing and to be able to use them in our own way. And finally, we carried out our evaluation by making a survey about the generated and existing lyrics and it proved to be very satisfactory. Many people rated the generated lyrics as being an existing lyric.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117323760","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":"LectureKhoj: Automatic tagging and semantic segmentation of online lecture videos","authors":"Esha Baidya, S. Goel","doi":"10.1109/IC3.2014.6897144","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897144","url":null,"abstract":"Online educational lecture videos are very popular nowadays. However, effective search of relevant videos remains a difficult task. Texts displayed in lecture video slides have important information about the video content. Therefore, it can be utilized as a valuable source of content analysis and tagging. In this paper, we present an automated method for semantic segmentation and tag recommendation of online lecture videos using OCR technology.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115861423","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":"A modified BP network using malsburg learning for rotation and location invariant fingerprint recognition and localization with and without occlusion","authors":"Sumana Kundu, G. Sarker","doi":"10.1109/IC3.2014.6897244","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897244","url":null,"abstract":"This present paper designs and develops a modified Malsburg Learning and Back Propagation (BP) Network combination for recognizing and localizing clear as well as occluded fingerprints in single and multiple fingerprint image frames. The present method of fingerprint recognition is completely rotation and location invariant of the different fingerprints in an image frame. The technique of using the combination of Malsburg learning and BP Network to perform learning of the different fingerprint images and subsequent identification and location invariant localization of clear and occluded images is efficient, effective and fast. Also the accuracy, precision, recall and F-score of the classifier are substantially moderate and the recognition time of fingerprints are quite low.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114363440","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":"CoSDEES: A framework for developing CSD environments for educational settings","authors":"R. Arora, S. Goel, R. K. Mittal","doi":"10.1109/IC3.2014.6897143","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897143","url":null,"abstract":"The recent drift towards the use of Collaborative Software Development (CSD) practices in software industry may prove to be an escalating movement towards changing software development philosophies. Consequently, research is in progress in developing related computing technologies for supporting the collaborative engagements of software developers. Eventually, it is essential that software engineering curriculum also focuses on developing collaborative programming skills of the students. Fostering collaborative learning and programming competencies of students through collaborative software development education at undergraduate level would facilitate their amalgamation into the team-oriented and intensively-collaborative, software development industry. In this paper, we propose a framework, CoSDEES, for the collaborative engagements of students involved in software development, in the form of CSD Activity WorkSpace. The proposed framework is based on Activity Theory. Furthermore, we also propose a comprehensive set of requirement specifications for the CSD environment that manifest the proposed framework. These specifications can be used as a set of guidelines for implementing CSD environments in educational settings. The primary aim of this research is to augment the collaborative activities of students engaged in software development, through the usage of the proposed collaborative software development environments.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114656836","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":"Privacy breach of social relation from location based mobile applications","authors":"Vartika Srivastava, Vinayak Naik, Anuradha Gupta","doi":"10.1109/IC3.2014.6897194","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897194","url":null,"abstract":"In today's era everyone has a smart phone and with increase use of smart phone applications available in market, raise the risk of leaking crucial information about the user and increasing the risk of privacy breach. In this paper, we are analyzing the social relationship leakage of user through such applications which uses phones Global Positioning System (GPS) data. We specifically worked on latitude-longitude (lat-long) pairs and the friend's network in popular social networking site (Facebook) to identify the social relationship between users. An existing application Mobishare has been used to conduct an experimental study on 55 users. On the basis of their location information obtain by the Mobishare application and social network's friend-list obtain from the Facebook, we calculated the percentage of togetherness between the users for different span of time, a high percentage of togetherness means they are closely related. Through this, we were able to identify the social relation between two users without his/her consent just using the GPS data that leads the privacy leakage.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122052112","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":"Web service selection on the basis of QoS parameter","authors":"Neerja Negi, Satish Chandra","doi":"10.1109/IC3.2014.6897223","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897223","url":null,"abstract":"In the present day situation, web service plays an important role in companies for sharing information. But due to the availability of large amount of web services that offer identical functionality, it is very difficult for the users to select the best service. This paper provides a model for efficiently selecting the web services among the set of existing web services. A web service negotiator has been used to verify the QoS information published by the publisher. A stability analyzer has been used to assign the stability score to the web service if it consistently provides a good service otherwise assign a low stability score to that web service. The ranking of the web service has been done using the AHP and TOPSIS. The highest ranked web services then given to the user to fulfill his requirements.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128710496","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}
Swaminathan Jayaraman, D. KishorKamath, B. Jayaraman
{"title":"Towards program execution summarization: Deriving state diagrams from sequence diagrams","authors":"Swaminathan Jayaraman, D. KishorKamath, B. Jayaraman","doi":"10.1109/IC3.2014.6897190","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897190","url":null,"abstract":"We propose a summarization technique that provides a clear and concise picture of the history of program execution with respect to entities of interest to a programmer. We develop our technique in the context of JIVE, a tool for Java execution visualization that renders execution states and history using UML object and sequence diagrams respectively. While these notations have been developed for specifying design-time decisions, the distinguishing aspect of our work is that we adapt their use for execution-time. Sequence diagrams tend to be long and unwieldy, and often exhibit a repetitive structure, hence we develop a novel procedure to summarize the sequence diagram in the form a state diagram with finite states. This summarization is user-driven, in that the user annotates the key variables of interest in the source code. This information together with an execution trace of the program for a particular input enables us to systematically construct a state diagram that summarizes the program behavior for that input. Using multiple execution traces, we show how an integrated state summarization can be obtained. Finally, by choosing different sets of variables, the user may view different summarizations, or perspectives, of the execution. This paper presents our technique along with experimental results from summarizing several different program executions in order to illustrate the benefit of our approach.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131732223","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":"A wireless dynamic gesture user interface for HCI using hand data glove","authors":"S. Prasad, Piyush Kumar, Kumari Priyanka Sinha","doi":"10.1109/IC3.2014.6897148","DOIUrl":"https://doi.org/10.1109/IC3.2014.6897148","url":null,"abstract":"In this paper, DG5 hand data glove is used to design an intelligent and efficient human-computer interface to interact with VLC media player. It maps the static keyboard with dynamic human hand gestures with 22 Degree of Freedom (DoF) to interact more natural way with computer. The result is very much appreciated showing the confusion matrix of various gestures used. In this paper, 10 complex gestures are used, that is Play, Pause, Forward, Backward, Next, Previous, Stop, Mute, Full Screen, and Null gestures. To study about the human-hand gestures four different age groups are taken, User A (20-30 years), User B (31-45 years), User C (46-60 years), and User D (61-above years). The decision tree a powerful learning algorithm is used to classify these gestures correctly. This enhances the user's interaction level with immersion feeling in augmented reality to 98.88% of accuracy rate.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126476582","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}