{"title":"Feature Selection of Imbalanced Gene Expression Microarray Data","authors":"Ali Anaissi, Paul J. Kennedy, M. Goyal","doi":"10.1109/SNPD.2011.12","DOIUrl":"https://doi.org/10.1109/SNPD.2011.12","url":null,"abstract":"Gene expression data is a very complex data set characterised by abundant numbers of features but with a low number of observations. However, only a small number of these features are relevant to an outcome of interest. With this kind of data set, feature selection becomes a real prerequisite. This paper proposes a methodology for feature selection for an imbalanced leukaemia gene expression data based on random forest algorithm. It presents the importance of feature selection in terms of reducing the number of features, enhancing the quality of machine learning and providing better understanding for biologists in diagnosis and prediction. Algorithms are presented to show the methodology and strategy for feature selection taking care to avoid over fitting. Moreover, experiments are done using imbalanced Leukaemia gene expression data and special measurement is used to evaluate the quality of feature selection and performance of classification.","PeriodicalId":336771,"journal":{"name":"2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114683881","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":"An Improvement on Hsiang and Shih's Remote User Authentication Scheme Using Smart Cards","authors":"Chin-Ling Chen, Yu-Fan Lin, Neng-Chung Wang, Young-Long Chen","doi":"10.1109/SNPD.2011.35","DOIUrl":"https://doi.org/10.1109/SNPD.2011.35","url":null,"abstract":"Recently, Hsiang and Shih proposed remote user authentication scheme using smart cards, they claims that their schemes defended against parallel session attack, and password guessing attacks, In this paper, we show that Hsiang and Shih's schemes are still vulnerable to off-line password guessing attacks and undetectable on-line password guessing attacks. Notably, problems remain in situations where the user loses a smart card. To remedy these flaws, this paper proposes an improvement on Hsiang and Shih's remote user authentication schemes using smart cards.","PeriodicalId":336771,"journal":{"name":"2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114436621","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}
Jahangir Dewan, M. Chowdhury, Shak Hossain, Jessy Dewan
{"title":"A Framework for eLearning with Social Media Using DRM","authors":"Jahangir Dewan, M. Chowdhury, Shak Hossain, Jessy Dewan","doi":"10.1109/SNPD.2011.15","DOIUrl":"https://doi.org/10.1109/SNPD.2011.15","url":null,"abstract":"This paper provides a proposal for personal e-learning system (PELS) architecture in the context of social network environment. The main objective of PELS is to develop individual skills on a specific subject and share resources with peers. Our system architecture defines organization and management of personal learning environment that aids in creating, verifying and sharing learning artifacts and making money at the same time. We also focus on in our research one of the most interesting arenas in digital content or document management called Digital Right Management (DRAM) and its application to eLearning.","PeriodicalId":336771,"journal":{"name":"2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121565504","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}
S. Mukherjee, J. Yearwood, P. Vamplew, Md. Shamsul Huda
{"title":"Reinforcement Learning Approach to AIBO Robot's Decision Making Process in Robosoccer's Goal Keeper Problem","authors":"S. Mukherjee, J. Yearwood, P. Vamplew, Md. Shamsul Huda","doi":"10.1109/SNPD.2011.39","DOIUrl":"https://doi.org/10.1109/SNPD.2011.39","url":null,"abstract":"Robocup is a popular test bed for AI programs around the world. Robosoccer is one of the two major parts of Robocup, in which AIBO entertainment robots take part in the middle sized soccer event. The three key challenges that robots need to face in this event are manoeuvrability, image recognition and decision making skills. This paper focuses on the decision making problem in Robosoccer -- The goal keeper problem. We investigate whether reinforcement learning (RL) as a form of semi-supervised learning can effectively contribute to the goal keeper's decision making process when penalty shot and two attacker problem are considered. Currently, the decision making process in Robosoccer is carried out using rule-base system. RL also is used for quadruped locomotion and navigation purpose in Robosoccer using AIBO. In this paper, we propose a reinforcement learning based approach that uses a dynamic state-action mapping using back propagation of reward and space quantized Q-learning (SQQL) for the choice of high level functions in order to save the goal. The novelty of our approach is that the agent learns while playing and can take independent decision which overcomes the limitations of rule-base system due to fixed and limited predefined decision rules. Performance of the proposed method has been verified against the bench mark data set made with Upenn'03 code logic. It was found that the efficiency of our SQQL approach in goalkeeping was better than the rule based approach. The SQQL develops a semi-supervised learning process over the rule-base system's input-output mapping process, given in the Upenn'03 code.","PeriodicalId":336771,"journal":{"name":"2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","volume":"55 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114038010","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}