Research ArticleOpen accessIn the abstractTWO PHASE CLUSTERING METHOD FOR LEACH PROTOCOL FOR EFFECTIVE CLUSTER HEAD SELECTIONRathi, ViswanathanA Wireless Sensor Networks (WSN) comprise of a huge quantity of clusters of sensor nodes that can inter communicate with all nodes and with the base station through a wireless link. All clusters are corresponding to a cluster head to provide a direct communication to the base station and in addition with other cluster heads. Obviously well-organized selection of cluster … …Journal of Computer Science, Vol. 10, Issue 3 · 21 Nov 2013 · 7,122 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL APPROACH BASED ON GENETIC FUZZY CLUSTERING AND ADAPTIVE NEURAL NETWORKS FOR SALES FORECASTINGAttariuas Hichama, Bouhorma Mohameda, El Fallahi AbdellahbThis article proposes a new hybrid sales forecasting system based on genetic fuzzy clustering and Back-Propagation (BP) Neural Networks with adaptive learning rate (GFCBPN).The proposed architecture consists of three stages: (1) utilizing Winter’s Exponential Smoothing method and Fuzzy C-Means clustering, all normalized data records will be categorized into k clusters; (2) using an adapted Genetic Fuzzy System (MCGFS), the fuzzy … …Journal of Computer Science, Vol. 9, Issue 8 · 2 Jul 2013 · 6,669 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Bee Colony Algorithm Integrated with Fuzzy C-mean Operator for Data ClusteringM. Krishnamoorthi, A. M. NatarajanClustering task aims at the unsupervised classification of patterns in different groups. To enhance the quality of results, the emerging swarm-based algorithms now-a-days become an alternative to the conventional clustering methods. In this study, an optimization method based on the swarm intelligence algorithm is proposed for the purpose of clustering. The significance of the proposed algorithm is that it uses … …Journal of Computer Science, Vol. 9, Issue 4 · 6 May 2013 · 6,299 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Overview of Research Challenges for Classification of Cardiotocogram DataC. Sundar, M. Chitradevi, G. GeetharamaniCardiotocography (CTG) is a simultaneous recording of Fetal Heart Rate (FHR) and Uterine Contractions (UC). The most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. There are several signal processing and computer programming based techniques for interpreting a typical Cardiotocography … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Clustering Based Exposition to Multiple Dictionary Bag of WordsK. S. Sujatha, B. VinodObject classification is a highly important area of computer vision and has many applications including robotics, searching images, face recognition, aiding visually impaired people, censoring images and many more. A new common method of classification that uses features is the Bag of Words approach. In this method a codebook of visual words is created using various clustering methods. For increasing … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,389 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Fuzzy Technique for Cancer Detection in Noisy Breast Ultrasound ImagesN. Alamelumangai, J. DeviShreeProblem statement: Detecting tumor areas in breast Ultrasound (US) images is a challenging task. The occurrence of benign areas in breast may result in false identification of malignant areas which may have serious outcome. Approach: The CAD system could act as a major function in the early detection of breast cancer and could decrease the death rate among women with … …American Journal of Applied Sciences, Vol. 9, Issue 5 · 12 Mar 2012 · 6,959 accessesView PDFCite
Research ArticleOpen accessIn the abstractSegmentation of Medical Image using Clustering and Watershed AlgorithmsM.C. Jobin Christ, R.M.S. ParvathiProblem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the image into dissimilar regions of similar attribute. In this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 22 Oct 2011 · 8,780 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the abstractIncreasing the Reliability of Fuzzy Inference System-Based Skin DetectorAlaa Y. Taqa, Hamid A. JalabProblem statement: Skin detection is a common primitive for many human-related image processing applications, such as video surveillance, naked image filters and face detection. Skin color is considered as a useful and discriminating spatial feature for many applications, but it is not robust enough to deal with complex image environments. Skin tones range from dark (some Africans) to light white … …American Journal of Applied Sciences, Vol. 7, Issue 8 · 31 Aug 2010 · 7,138 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzy Meta Node Fuzzy Metagraph and its Cluster AnalysisD. Gaur, A. Shastri, R. BiswasProblem statement: In this study researchers propose a new fuzzy graph theoretic construct called fuzzy metagraph and a new method of clustering finding the similar fuzzy nodes in a fuzzy metagraph. Approach: We adopted T-norms (Triangular Norms) functions and join two or more T-norms to cluster the fuzzy nodes. Fuzzy metagraph is the fuzzyfication of the crisp Metagraphs using fuzzy … …Journal of Computer Science, Vol. 4, Issue 11 · 30 Nov 2008 · 6,951 accessesView PDFCite