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Articles by K. Rajalakshmi
Total Records ( 2 ) for K. Rajalakshmi
  T.I. Manish , D. Murugan , K. Rajalakshmi and T. Ganesh Kumar
  The sun spots is the major solar activity which represent the sun’s magnetic activity and prominent in the solar feature. This study present a new hybrid model for segmentation and further classification of sunspots from solar images obtained from Michelson Doppler Imager (MDI). Sunspots are regions on the solar surface that look black because they are cooler than the surrounding photosphere. The sunspots are regions where strong magnetic fields emerge from the solar interior and where major eruptive events occur. These energetic events can cause power outages, interrupt telecommunication and navigation services and pose hazards to astronauts. In this study, we present a new hybrid method to detect and extract sunspot features. Based on the efficient classifiers the sunspots classification is done. The input is a sequence of MDI images and the output is detection and classification of solar events. Initially, processing is done to enhance and remove noise from the image. Finally, we analyze the result with the globally accepted solar indices like international sunspot number and different standard data sources are used.
  K. Rajalakshmi , Prakash Kumar and Hima M. Bindu
  In this study, a hybridized heuristics approach based on Iterative Local search and Simulated Annealing is proposed to solve the assignment problem of Cellular Mobile Network. In Cellular Mobile Networks, assigning of cells to switch is known as assignment problem. The conventional integer programming method could be used for solving this problem but then, when the number of cells exceeds 35, the total computational data surpass the memory available, computational time grow too larger and it becomes unfeasible to obtain the optimal solution. Thus, this assignment problem is a complex integer programming problem which is proved to be NP hard problem. Particularly, in this study 2-opt Local search and 3-opt Local search methods are embedded to improve the CPU performance of the proposed hybridized algorithm. The objective function is to minimize the link cost between cells and switches upon their assignment alongwiththe constraint that number of cells assigned to each switch. Empirical results show that the proposed heuristic produces results proximity to optimal solution as expected.
 
 
 
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