2011 IEEE Recent Advances in Intelligent Computational Systems最新文献_第5页

Region based segmentation of satellite and medical imagery with level set evolution 基于水平集进化的卫星和医学图像区域分割

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069389

G. Raghotham Reddy, K. Ramudu, A. Srinivas, R. Rameshwar Rao

引用次数: 2

Generalize 3D model of energy consumption for deploying nodes in Sensor Network 推广传感器网络节点部署的三维能耗模型

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069286

R. Dutta, Indrajit Bhattacharya

{"title":"Generalize 3D model of energy consumption for deploying nodes in Sensor Network","authors":"R. Dutta, Indrajit Bhattacharya","doi":"10.1109/RAICS.2011.6069286","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069286","url":null,"abstract":"Wireless Sensor Networks (WSN) provide network access for mobile users. Therefore, most traffic flows in WSNs are to and from the sensor node and base station of the networks without wired connection. Power consumption is one of the most important issue in the sensor network. Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper describes a mathematical model for the power consumption of mobile node in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes)and mobile nodes are considered. Each source node must send all its locally generated data to the other nodes and vice -versa. To maximize mobile node's lifetime, it is essential to have optimum monitored region and radio range of each source node of WSNs. To find an optimal solution a mathematical model, which is proposed for optimal power consumption in terms of ratio of whole energy of sensor nodes to energy consumption speed of sensor nodes in any area should be constant. Through extensive simulation of the model we achieved the results of the model which is shown below and implies that this model has excellent performance and provides a near-optimal solution.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131992808","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: 1

Classification of aromatic and non-aromatic rice using electronic nose and artificial neural network 利用电子鼻和人工神经网络对芳香稻和非芳香稻进行分类

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069320

A. Jana, R. Bandyopadhyay, B. Tudu, J. Roy, N. Bhattacharyya, B. Adhikari, C. Kundu, Subhankar Mukherjee

引用次数: 15

Tool wear prediction by Regression Analysis in turning A356 with 10% SiC 10% SiC车削A356刀具磨损的回归分析

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069397

U. Prakash, Yogavardhanaswamy G.N, S. L. Ajit prasad, H. Ravindra, T. Rajan

{"title":"Tool wear prediction by Regression Analysis in turning A356 with 10% SiC","authors":"U. Prakash, Yogavardhanaswamy G.N, S. L. Ajit prasad, H. Ravindra, T. Rajan","doi":"10.1109/RAICS.2011.6069397","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069397","url":null,"abstract":"In recent years, the utilization of metal matrix composites (MMC) materials in many engineering fields has increased predominantly. The need for accurate machining of these composites has also increased enormously. Despite the recent developments in the near net shape manufacture, composite parts often require post-mold machining to meet dimensional tolerances, surface quality and other functional requirements. In general 70% of the components need machining to attain the final shape. In the present work, the tool wear has been studied in this paper by turning the composite bars using HSS and Carbide tools. The paper presents the results of experimental investigation machinability properties of silicon carbide particle (SiC-p) reinforced aluminum metal matrix composite. The effect of machining parameters, e.g. cutting speed, feed rate and depth of cut on tool wear and surface roughness was studied. Machinability properties of the selected material were studied using HSS and Carbide tool material; surface roughness was generally affected by feed rate and cutting speed. Hence the tool wear were measured at different speed and feed conditions. Experimental data collected are tested with Multiple Regression Analysis. On completion of the experimental test, multiple regression analysis is used to predict the wear behavior of the system under any condition within the operating range.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115564389","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: 10

Load balancing using past information of queue 使用队列的过去信息进行负载平衡

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069412

D. Guha, S. Pathak

{"title":"Load balancing using past information of queue","authors":"D. Guha, S. Pathak","doi":"10.1109/RAICS.2011.6069412","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069412","url":null,"abstract":"We provide an approach to balancing the load and splitting the traffic during the overload condition based on queue occupation using old information of the output interface queue. A common storage space known as bulletin board is used to store the queue length of the output interface buffer. Bulletin board is updated on a regular interval basis and new arrival verifies the queue length of the bulletin board instead of the output interface buffer. The assumption of our model are: packets arrive as a Poisson stream of rate λ1 for data and λ2 for voice. Packets are served according to FIFO and the service time for a packet is exponentially distributed with mean 1. The Partial Buffer Sharing scheme is applied to partition the output buffer between voice and data packets. The growth of voice buffer is bounded so that queueing delay is restricted for voice packets. Data packet can take their space if the allocated voice packet buffer is unused on an arrival of data packet. But voice packets are prohibited to take the space of unused allocated data packets. The bulletin board fetches the output queue length evolution on a regular interval basis. The model provides an abstraction of simple load balancing scheme in setting when to split the traffic and send it over another path. This model estimates the bandwidth usage on a local granularity basis instead of running periodic probe messages to estimate the bandwidth between two nodes.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114684723","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

Cross layer architectural approaches for Wireless Sensor Networks 无线传感器网络的跨层架构方法

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069374

S. Gajjar, S. N. Pradhan, K. Dasgupta

{"title":"Cross layer architectural approaches for Wireless Sensor Networks","authors":"S. Gajjar, S. N. Pradhan, K. Dasgupta","doi":"10.1109/RAICS.2011.6069374","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069374","url":null,"abstract":"A Wireless Sensor Network is a network of sensors that senses specified parameter(s) related to environment; processes data locally or in a distributed manner and wirelessly communicates information to central Base Station. The Base Station analyzes information and initiates suitable response if required. The complexities introduced by severely limited processing capabilities, memory and power supply in the sensor node at one end and the design needs of versatile applications at the other end have forced researchers to dissect the layered protocol design process. As a result cross layer approaches which attempt to exploit a richer interaction among communication layers to achieve performance gains have emerged. Cross-layer interactions offer the possibility of dealing with the special properties of Wireless Sensor Network that cannot be handled well by layered architectures. For example, this can be handling the variations in link quality or adjusting the radio strength, which influences the transmission range, the number of collisions, and energy consumption. These parameters can further be used as routing metrics at Network Layer for efficient routing. This paper surveys cross layer architectures, presents performance benchmarking for the architectures and finally compares them on the basis of the introduced benchmarks.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117290109","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

Motor current signature analysis by multi-resolution methods using Support Vector Machine 基于支持向量机的多分辨率电机电流特征分析

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069280

Y. Moorthy, P. S. Chandran, S. Rishidas

引用次数: 10

A fast approximate kernel k-means clustering method for large data sets 大数据集的快速近似核k-均值聚类方法

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069372

T. Sarma, P. Viswanath, B. Reddy

{"title":"A fast approximate kernel k-means clustering method for large data sets","authors":"T. Sarma, P. Viswanath, B. Reddy","doi":"10.1109/RAICS.2011.6069372","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069372","url":null,"abstract":"In unsupervised classification, kernel k-means clustering method has been shown to perform better than conventional k-means clustering method in identifying non-isotropic clusters in a data set. The space and time requirements of this method are O(n2), where n is the data set size. The paper proposes a two stage hybrid approach to speed-up the kernel k-means clustering method. In the first stage, the data set is divided in to a number of group-lets by employing a fast clustering method called leaders clustering method. Each group-let is represented by a prototype called its leader. The set of leaders, which depends on a threshold parameter, can be derived in O(n) time. The paper presents a modification to the leaders clustering method where group-lets are found in the kernel space (not in the input space), but are represented by leaders in the input space. In the second stage, kernel k-means clustering method is applied with the set of leaders to derive a partition of the set of leaders. Finally, each leader is replaced by its group to get a partition of the data set. The proposed method has time complexity of O(n+p2), where p is the leaders set size. Its space complexity is also O(n+p2). The proposed method can be easily implemented. Experimental results shows that, with a small loss of quality, the proposed method can significantly reduce the time taken than the conventional kernel k-means clustering method.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114077663","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: 11

Performance analysis of fuzzy techniques hierarchical aggregation functions decision trees and Support Vector Machine (SVM)for the classification of epilepsy risk levels from EEG signals 模糊技术、层次聚合函数、决策树和支持向量机在脑电信号癫痫风险等级分类中的性能分析

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069364

R. Harikumar, T. Vijaykumar, C. Palanisamy

引用次数: 3

Early detection of retinal nerve fiber layer defects using fundus image processing 眼底图像处理早期检测视网膜神经纤维层缺损

2011 IEEE Recent Advances in Intelligent Computational Systems Pub Date : 2011-11-03 DOI: 10.1109/RAICS.2011.6069445

J. David, A. Sukesh Kumar

{"title":"Early detection of retinal nerve fiber layer defects using fundus image processing","authors":"J. David, A. Sukesh Kumar","doi":"10.1109/RAICS.2011.6069445","DOIUrl":"https://doi.org/10.1109/RAICS.2011.6069445","url":null,"abstract":"Glaucoma, the second leading cause of blindness is a disease characterized by loss of neural tissue over time. The key issue in dealing with this disease is early detection of its presence or progression, with the rapid initiation or advancement of appropriate treatment. Quantitative analysis of Retinal Nerve Fiber Layer (RNFL) via image processing of fundus images plays a major role in its early detection. The disease is characterized by the progressive degeneration of optic nerve fibers showing a distinct image of the optic nerve head. Glaucoma leads to (i) structural changes of the optic nerve head (ONH) and the nerve fiber layer and (ii) a simultaneous functional failure of the visual field. This work aims to develop a system which will recognize the presence of glaucoma by the changes in the fundus image of an eye of a person and automatically quantify the RNFL defect using image processing techniques which aids in the diagnosis of glaucoma disease. Input image of the system will be the fundus image of an eye saved in bitmap or JPEG format or a real time one. Results show that the performance of our system is appreciable with the clinical diagnosis. In the future, the system can provide a first low-priced glaucoma indication in order to possibly reduce the amount of false positives misrouted to the cost-intensive elaborate clinical investigations.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129521781","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: 20