International Journals

Permanent URI for this collectionhttps://dspace.psgrkcw.com/handle/123456789/157

Browse

Author: search.filters.author.Kowsalya R

Search Results

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    ACUTE CYSTITIS AND ACUTE NEPHRITIS PREDICTION USING MACHINE LEARNING TECHNIQUES
    (Global Journal of Computer Science and Technology, 2010-09) Kowsalya R; Sasikala G; Sangeetha Priya J
    Urinary System includes kidneys, bladder, ureters and urethra. This is the major system involves electrolyte balance of the body and filters the blood and excretes the waste products in the form urine. Even the small disturbance in the renal function will step in a disasters manifestation. Among them we are considering the two diseases that affect the system are acute cystitis and acute nephritis. This paper presents the implementation of three supervised learning algorithms, ZeroR, J48 and Naive Bayes in WEKA environment. The classification models were trained using the data collected from 120 patients. The trained models were then used for predicting the acute cystitis or acute nephritis of the patients. The prediction accuracy of the classifiers was evaluated using 10-fold cross validation and the results were compared.
  • No Thumbnail Available
    Item
    A COMPARATIVE STUDY OF DIMENSION REDUCTION TECHNIQUES FOR CONTENT-BASED IMAGE RETRIEVAL
    (The International Journal of Multimedia & Its Applications, 2010) Sasikala G; Kowsalya R; Punithavalli M
    Efficient and effective retrieval techniques of images are desired because of the explosive growth of digital images. Content-based image retrieval is a promising approach because of its automatic indexing and retrieval based on their semantic features and visual appearance. This paper discusses the method for dimensionality reduction called Maximum Margin Projection (MMP). MMP aims at maximizing the margin between positive and negative sample at each neighborhood. It is designed for discovering the local manifold structure. Therefore, MMP is likely to be more suitable for image retrieval systems, where nearest neighbor search is usually involved. The performance of these approaches is measured by a user evaluation. It is found that the MMP based technique provides more functionalities and capabilities to support the features of information seeking behavior and produces better performance in searching images.
  • No Thumbnail Available
    Item
    CDARGA: CLUSTER-BASED DATA AGGREGATION WITH GENETIC ROUTING ALGORITHM IN WIRELESS SENSOR NETWORKS
    (International Journal of Recent Technology and Engineering, 2020-02) Kowsalya R; Rosiline Jeetha B
    In the wireless sensor networks (WSNs), the upholding the energy and routing formation at every sensor node is the major issues. The distance from base station and internal node mainly has imbalanced in the energy consumption during transformation of the data. To reduce the energy upholding and the data aggregation routing issues in Centralized Clustering-Task Scheduling for wireless sensor networks (WSNs), this paper focuses on a Cluster-Based Data Aggregation Routing with Genetic search Algorithm (CDARGA) , which reduces the energy consumption in a hyper round model. The proposed data aggregation routing protocol using the Genetic Algorithm (GA) estimates the fitness function using the three key parameters distance, energy, and Hyper round policy. The proposed methods were compared with RP-MAC and the experimental result shows that the proposed protocol is superior to RP-MAC protocol and the proposed algorithm improves the network lifetime which can used in real time application.