2012 11th International Conference on Machine Learning and Applications最新文献

A Cooperative Learning Scheme for Energy Efficient Routing in Wireless Sensor Networks 无线传感器网络中节能路由的合作学习方案

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.143

S. Al-Wakeel, N. Al-Nabhan

引用次数: 1

PQL: Protein Query Language PQL:蛋白质查询语言

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.217

S. Elfayoumy, Paul Bathen

{"title":"PQL: Protein Query Language","authors":"S. Elfayoumy, Paul Bathen","doi":"10.1109/ICMLA.2012.217","DOIUrl":"https://doi.org/10.1109/ICMLA.2012.217","url":null,"abstract":"This paper introduces a Protein Query Language (PQL) for querying protein structures in an expressive yet concise manner. One of the objectives of the paper is to demonstrate how such a language would be beneficial to protein researchers to obtain in-depth protein data from a relational database without extensive SQL knowledge. The language features options such as limiting query results by key protein characteristics such as methyl donated hydrogen bond interactions, minimum and maximum phi and psi angles, repulsive forces, CH/Pi calculations, and other pertinent factors. A backend data model was designed to support storage and retrieval of protein primary and secondary sequences, atomic-level data, as well as calculations on said data. A relational DBMS is used as the persistent storage backend, with every effort made to ensure transparent portability to most relational database systems. In addition, front end applications can be developed to support retrieving, transforming, and preprocessing of information from the Research Collaboratory for Structural Bioinformatics (RCSB) into the backend data repository. The new language and associated architecture allow users to load additional protein files from RCSB into the database, issue standard queries to download pertinent data in user-friendly formats including CSV files, issue non-standard queries against secondary structures via the protein query language, and run error-detection routines against data in the database. Query results may include normalized or denormalized data, model and chain data, residue data, atom detail data, and primary as well as secondary structure data.","PeriodicalId":157399,"journal":{"name":"2012 11th International Conference on Machine Learning and Applications","volume":"321 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116121785","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}

引用次数: 0

Generation of Tests for Programming Challenge Tasks on Graph Theory Using Evolution Strategy 基于进化策略的图论编程挑战任务的测试生成

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.194

M. Buzdalov

引用次数: 5

Monitoring and Determination of Wind Energy Potential by Web Based Wireless Network 基于Web无线网络的风能潜力监测与测定

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.205

Onur Keskin, Ismet Ates, Z. H. Karadeniz, A. Turgut, Z. Kıral

引用次数: 1

Approach to Control of the Output Voltage in Renewable Energy Sources on the Basis of AE-method Using Genetic Algorithm 基于ae -方法的遗传算法控制可再生能源输出电压的方法

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.168

Viktor Ten, N. Isembergenov, Y. Akhmetbekov, D. Sarbassov, A. Iglikov, B. Matkarimov

引用次数: 2

Automated Storage Tiering Using Markov Chain Correlation Based Clustering 基于马尔可夫链关联聚类的自动存储分层

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.71

Malak Alshawabkeh, Alma Riska, Adnan Sahin, Motasem Awwad

{"title":"Automated Storage Tiering Using Markov Chain Correlation Based Clustering","authors":"Malak Alshawabkeh, Alma Riska, Adnan Sahin, Motasem Awwad","doi":"10.1109/ICMLA.2012.71","DOIUrl":"https://doi.org/10.1109/ICMLA.2012.71","url":null,"abstract":"In this paper, we develop an automated and adaptive framework that aims to move active data to high performance storage tiers and inactive data to low cost/high capacity storage tiers by learning patterns of the storage workloads. The framework proposed is designed using efficient Markov chain correlation based clustering method (MCC), which can quickly predict or detect any changes in the current workload based on what the system has experienced before. The workload data is first normalized and Markov chains are constructed from the dynamics of the IO loads of the data storage units. Based on the correlation of one-step Markov chain transition probabilities k-means method is employed to group the storage units that have similar behavior at each point. Such framework can then easily be incorporated in various resource management policies that aim at enhancing performance, reliability, availability. The predictive nature of the model, particularly makes a storage system both faster and lower-cost at the same time, because it only uses high performance tiers when needed, and uses low cost/high capacity tiers when possible.","PeriodicalId":157399,"journal":{"name":"2012 11th International Conference on Machine Learning and Applications","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123818530","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}

引用次数: 4

Classification, Segmentation and Chronological Prediction of Cinematic Sound 电影声音的分类、分割和时间预测

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.172

Pedro Silva

引用次数: 5

Animal Cognition, Epistemic Fluency, Social Networks and the Scientific Habit of Mind 动物认知、认知流畅性、社会网络与科学思维习惯

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.166

D. M. Morrison, Xiangen Hu

引用次数: 0

On the Validity of a New SMS Spam Collection 一种新的短信垃圾邮件收集方法的有效性研究

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.211

J. M. G. Hidalgo, Tiago A. Almeida, A. Yamakami

{"title":"On the Validity of a New SMS Spam Collection","authors":"J. M. G. Hidalgo, Tiago A. Almeida, A. Yamakami","doi":"10.1109/ICMLA.2012.211","DOIUrl":"https://doi.org/10.1109/ICMLA.2012.211","url":null,"abstract":"Mobile phones are becoming the latest target of electronic junk mail. Recent reports clearly indicate that the volume of SMS spam messages are dramatically increasing year by year. Probably, one of the major concerns in academic settings was the scarcity of public SMS spam datasets, that are sorely needed for validation and comparison of different classifiers. To address this issue, we have recently proposed a new SMS Spam Collection that, to the best of our knowledge, is the largest, public and real SMS dataset available for academic studies. However, as it has been created by augmenting a previously existing database built using roughly the same sources, it is sensible to certify that there are no duplicates coming from them. So, in this paper we offer a comprehensive analysis of the new SMS Spam Collection in order to ensure that this does not happen, since it may ease the task of learning SMS spam classifiers and, hence, it could compromise the evaluation of methods. The analysis of results indicate that the procedure followed does not lead to near-duplicates and, consequently, the proposed dataset is reliable to use for evaluating and comparing the performance achieved by different classifiers.","PeriodicalId":157399,"journal":{"name":"2012 11th International Conference on Machine Learning and Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121418837","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}

引用次数: 42

A Hybrid Approach to Coping with High Dimensionality and Class Imbalance for Software Defect Prediction 软件缺陷预测中高维类不平衡的混合处理方法

2012 11th International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.145

Kehan Gao, T. Khoshgoftaar, Amri Napolitano

引用次数: 15