2011 10th International Conference on Machine Learning and Applications and Workshops最新文献_第10页

Performance Analysis of a Hydrofoil with and without Leading Edge Slat 带和不带前缘板的水翼性能分析

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.113

T. Yavuz, B. Kilkis, Hursit Akpinar, Özgür Erol

{"title":"Performance Analysis of a Hydrofoil with and without Leading Edge Slat","authors":"T. Yavuz, B. Kilkis, Hursit Akpinar, Özgür Erol","doi":"10.1109/ICMLA.2011.113","DOIUrl":"https://doi.org/10.1109/ICMLA.2011.113","url":null,"abstract":"Operational effectiveness of the wind and hydrokinetic turbines depend on the performance of the airfoils chosen. Standard airfoils historically used for wind and hydrokinetic turbines had and have the maximum lift coefficients of about 1.3 at the stall angle of attack, which is about 12o. At these conditions, the minimum flow velocities to generate electric power are about 7 m/s and 3 m/s for wind turbine and hydrokinetic turbine, respectively. Using leading edge slat, the fluid dynamics governing the flow field eliminates the separation bubble by the injection of the high momentum fluid through the slat over the main airfoil-by meaning of the flow control delays the stall up to an angle of attack of 20o, with a maximum lift coefficient of 2.2. In this study, NACA 2415 was chosen as a representative of hydrofoils while NACA 22 and NACA 97, were chosen as slat profiles, respectively. This flow has been numerically simulated by FLUENT, employing the Realizable k-e turbulence model. In the design of the wind and hydrokinetic turbines, the performance of the airfoils presented by aerodynamics CL = f (a,d), CD = f (a,d) and CL/CD = f (a,d) are the basic parameters. In this paper, optimum values of the angle of attack, slat angle and clearance space between slat and main airfoil leading to maximum lift and minimum drag, and consequently to maximum CL/CD have been numerically determined. Hence, using airfoil and hydrofoil with leading edge slat in the wind and hydrokinetic turbines, minimum wind and hydrokinetic flow velocities to produce meaningful and practical mechanical power reduces to 3-4 m /s for wind turbines and 1-1.5 m/s or less for hydrokinetic turbines. Consequently, using hydrofoil with leading edge slat may re-define the potentials of wind power and hydrokinetic power potential of the countries in the positive manner.","PeriodicalId":439926,"journal":{"name":"2011 10th International Conference on Machine Learning and Applications and Workshops","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128794014","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: 7

Extending k-Means-Based Algorithms for Evolving Data Streams with Variable Number of Clusters 基于k-均值的变聚类演化数据流扩展算法

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.67

J. Silva, Eduardo R. Hruschka

引用次数: 20

Network-Based Filtering of Unreliable Markers in Genome Mapping 基因组定位中基于网络的不可靠标记过滤

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.103

O. Azzam, Loai Al Nimer, Charith D. Chitraranjan, A. Denton, Ajay Kumar, F. Bassi, M. Iqbal, S. Kianian

引用次数: 7

Extended Finite-State Machine Induction Using SAT-Solver 基于sat求解器的扩展有限状态机感应

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.166

V. Ulyantsev, F. Tsarev

引用次数: 48

Towards Automatic Classification on Flying Insects Using Inexpensive Sensors 利用廉价传感器对飞虫进行自动分类

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.145

Gustavo E. A. P. A. Batista, Yuan Hao, Eamonn J. Keogh, A. Mafra‐Neto

{"title":"Towards Automatic Classification on Flying Insects Using Inexpensive Sensors","authors":"Gustavo E. A. P. A. Batista, Yuan Hao, Eamonn J. Keogh, A. Mafra‐Neto","doi":"10.1109/ICMLA.2011.145","DOIUrl":"https://doi.org/10.1109/ICMLA.2011.145","url":null,"abstract":"Insects are intimately connected to human life and well being, in both positive and negative senses. While it is estimated that insects pollinate at least two-thirds of the all food consumed by humans, malaria, a disease transmitted by the female mosquito of the Anopheles genus, kills approximately one million people per year. Due to the importance of insects to humans, researchers have developed an arsenal of mechanical, chemical, biological and educational tools to help mitigate insects' harmful effects, and to enhance their beneficial effects. However, the efficiency of such tools depends on knowing the time and location of migrations/infestations/population as early as possible. Insect detection and counting is typically performed by means of traps, usually \"sticky traps\", which are regularly collected and manually analyzed. The main problem is that this procedure is expensive in terms of materials and human time, and creates a lag between the time the trap is placed and inspected. This lag may only be a week, but in the case of say, mosquitoes or sand flies, this can be more than half their adult life span. We are developing an inexpensive optical sensor that uses a laser beam to detect, count and ultimately classify flying insects from distance. Our objective is to use classification techniques to provide accurate real-time counts of disease vectors down to the species/sex level. This information can be used by public health workers, government and non-government organizations to plan the optimal intervention strategies in the face of limited resources. In this work, we present some preliminary results of our research, conducted with three insect species. We show that using our simple sensor we can accurately classify these species using their wing-beat frequency as feature. We further discuss how we can augment the sensor with other sources of information in order to scale our ideas to classify a larger number of species.","PeriodicalId":439926,"journal":{"name":"2011 10th International Conference on Machine Learning and Applications and Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128415777","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: 55

A New Control Method for dc-dc Converter by Neural Network Predictor with Repetitive Training 一种基于重复训练神经网络预测器的dc-dc变换器控制新方法

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.17

F. Kurokawa, K. Ueno, H. Maruta, H. Osuga

引用次数: 12

Training Data Subdivision and Periodical Rotation in Hybrid Fuzzy Genetics-Based Machine Learning 混合模糊遗传机器学习中的训练数据细分和周期轮换

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.147

H. Ishibuchi, S. Mihara, Y. Nojima

{"title":"Training Data Subdivision and Periodical Rotation in Hybrid Fuzzy Genetics-Based Machine Learning","authors":"H. Ishibuchi, S. Mihara, Y. Nojima","doi":"10.1109/ICMLA.2011.147","DOIUrl":"https://doi.org/10.1109/ICMLA.2011.147","url":null,"abstract":"We have already proposed an idea of simultaneous implementation of population subdivision and training data set subdivision, which leads to significant decrease in computation time of genetics-based machine learning (GBML) for large data sets. In our idea, a population is subdivided into multiple sub-populations as in island models where subdivided training data are rotated over the sub-populations. In this paper, we focus on the effect of training data rotation on the generalization ability and the computation time of our hybrid fuzzy GBML algorithm. First we show parallel distributed implementation of our hybrid fuzzy GBML algorithm. Then we examine the effect of training data rotation through computational experiments where both single-population (i.e., non-parallel) and multi-population (i.e., parallel) versions of our GBML algorithm are applied to a multi-class high-dimensional problem with a large number of training patterns. Experimental results show that training data rotation improves the generalization ability of our GBML algorithm. It is also shown that the population size is more directly related to the computation time than the training data set size.","PeriodicalId":439926,"journal":{"name":"2011 10th International Conference on Machine Learning and Applications and Workshops","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124150873","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: 7

Ranking Interactions for a Curation Task 排序互动的策展任务

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.119

S. Clematide, Fabio Rinaldi

引用次数: 5

Kernel Methods for Minimum Entropy Encoding 最小熵编码的核方法

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.83

S. Melacci, M. Gori

引用次数: 1

Microarray Classification Using Sub-space Grids 基于子空间网格的微阵列分类

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI: 10.1109/ICMLA.2011.125

M. Wani

{"title":"Microarray Classification Using Sub-space Grids","authors":"M. Wani","doi":"10.1109/ICMLA.2011.125","DOIUrl":"https://doi.org/10.1109/ICMLA.2011.125","url":null,"abstract":"The work presented in this paper describes how sub-space grids can be employed to extract rules for micro array classification. The paper first describes principal component analysis (PCA) algorithm for obtaining sub-space grids from the projected low dimensional space. A recursive procedure is then used to obtain rules where sub-space grids form premises of rules. The extracted set of rules is evaluated on both training and testing data sets. The sub-space grids from PCA algorithm are characterized by overlapped data from different classes and use of even more than two premises in a rule does not fully address the problem of overlapped data. As such the rules obtained do not discriminate different classes accurately. To increase the effectiveness of the set of rules, multiple discriminant analysis (MDA) algorithm instead of PCA algorithm is employed to obtain sub-space grids from the projected low dimensional space. These sub-space grids from MDA algorithm improve the classification accuracy of the system. However, the size of set of rules extracted is large and these rules are sensitive to local variations associated with the data. To address these issues, the paper explores using both the PCA and MDA algorithms simultaneously fo projected low dimensional space for obtaining sub-space grids. The resulting set of rules produce better classification accuracy results. The paper discusses a comprehensive evaluation of this rule based system. The system is tested on a dataset of 62 samples (40 colon tumor and 22 normal colon tissue). The results show that the use of sub-space grids that are obtained from a projected low dimensional space of combined PCA and MDA algorithms increase the accuracy of classification results of micro array data.","PeriodicalId":439926,"journal":{"name":"2011 10th International Conference on Machine Learning and Applications and Workshops","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126825127","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: 14