A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Agnes Kala Rani, X.
- Survey on Treatment of By-Pass Surgery Using Nanorobots
Authors
1 Department of Computer Science, Karpagam University, Coimbatore, Tamilnadu, IN
2 Department of Computer Application, iKarpagam University, Coimbatore, Tamilnadu, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 12 (2012), Pagination: 626-629Abstract
Nanotechnology process is used in the manufacturing process. To improve existing products by creating smaller components and better performance materials, all at a lower cost, the number of companies that will manufacture "nanoproducts" will grow very fast and soon make up the majority of all companies across many industries..This method is used presently for treatment-bypass surgery or angioplasty is outdated in this Nano world. Hence by working on such a small scale a Nano robot could operate seamlessly without leaving the scars that conventional surgery does. Nanorobots could remove obstructions in the circulatory system, kill cancer cells, or take over the function of sub cellular organelles. Viruses are among the most important causes of human disease and are of increasing concern as possible agents of biowarfare and bioterrorism. This paper shows any viral respiratory infection could be diagnosed with the help of quantum dot system in an efficient manner. Finally, this gives the concepts involved in detection and curing of heart blockage using nano devices and pictures the solutions for human illness using "Nanotechnology".
- SOM Based Clustering for Detecting Bacterial Spot Disease in Tomato Field
Authors
1 Department of Computer Applications, Karpagam University, Coimbatore, Tamil Nadu, IN
Source
Indian Journal of Innovations and Developments, Vol 5, No 7 (2016), Pagination: 1-8Abstract
Objectives: The main objective of introducing SOM based clustering method is to improve the classification accuracy and detection of bacterial spot disease in tomato field.
Methods: There are various image processing methods used to identify disease and severity of disease in plants. One of such methods uses visible spectrum Images for automatically detecting and classifying the severity of bacterial spot in tomato fields. Centroid-based K-means clustering was widely used for automatic segmentation.
Findings: Plant diseases are one of the major responsibilities for economic degradation in the agricultural industry. So regular monitoring of plant health and early detection of disease causing pathogens are required for minimizing disease spread and assist effective management practices. Centroid-based K-means clustering for segmentation always does not chose centroids that provide best results and also different initial set of centroids affect the shape and effectiveness of the final cluster.
Application/Improvements: To overcome the limitations of Centroid-based K-means clustering, Self-Organizing Maps (SOM) is introduced for achieving effective classification result and to improve the detection performance.
Keywords
Plant Diseases, Visible Spectrum Images, Centroid-Based K-Means Clustering, Self-Organizing Maps.Full Text
References
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