Informatics Publishing Limited

K. S. Chandragupta Mauryan ¹, K. Thanushkodi ², C. K. Goghul Raman ³

Affiliations
1 Department of Electrical and Electronics Engineering, VLB Janakiammal College of Engineering and Technology, Coimbatore, IN
2 Akshaya College of Engineering and Technology, Coimbatore, IN
3 VLB Janakiammal College of Engineering and Technology, Coimbatore, IN

Abstract

This paper presents an optimization algorithm to solve the optimal real power loss control problem. In PSO, particle studies from itself and the best one among the group only. In the proposed Improved Particle Swarm Optimization (IPSO) it studies from itself, the best one among the group and also from neighboring particles. By this enhanced behavior of IPSO, the opportunity to find the global solution is guaranteed and the speed of convergence is improved. The feasibility of the proposed method is demonstrated and results are compared with classical PSO. The developed IPSO has been tested on 6 bus Ward-Hale system and modified IEEE 14 bus system for optimal real power loss control problem.

Keywords

IEEE 14 Bus Systems, Improved Particle Swarm Optimization, Optimal Real Power Control, Ward-Hale 6 Bus System.

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S. V. Sudha ¹, K. Thanushkodi ²

Affiliations
1 Department of Information Technology, Kalignar Karunanidhi Institute of Technology, Coimbatore 641402 , Tamil Nadu, IN
2 Akshaya College of Engineering and Technology, Coimbatore - 642 109, Tamil Nadu, IN

Abstract

Coarse Grain applications require all processes run with a very gross level of synchronization among them. Any collection of concurrent processes that need to communicate or synchronize can benefit from the use of a multiprocessor architecture. This type of application can be achieved from time and space slicing, but the algorithms suffer from fragmentation, where the processors are left idle because jobs cannot be packed with 100% efficiency. This fragmentation results to reduce utilization and poor performance. Spry algorithm concentrates on the above-mentioned problems and the results of the spry algorithm are compared with First Come First Serve. Gang Scheduling and Flexible Co scheduling. Spry Algorithm is implemented with Java thread and the results are compared with the performance metrics like Turn around Time, Mean Response Time, Mean Reaction Time, Mean Slowdown, Mean Utilization and Average waiting time of the Jobs.

Keywords

Parallel Job Scheduling, Performance Metric, Mean Slowdown.

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P. Thangam ¹, K. Thanushkodi ², T. V. Mahendiran ³

Affiliations
1 Computer Science and Engineering (PG) Department, Sri Ramakrishna Engineering College, Coimbatore, IN
2 Akshaya College of Engineering and Technology, Coimbatore, IN
3 Electrical Engineering Department, Coimbatore Institute of Engineering and Technology, Coimbatore, IN

Abstract

This paper proposes an automated system for bone age estimation from left hand-wrist radiographs. The input image is first preprocessed and segmented using Particle Swarm Optimization (PSO) consisting of graph-based and tetrolet-based segmentation procedures. Then the phalangeal bones specially used as Regions of Interest (ROIs) for the bone age estimation process are identified. From the phalangeal ROIs identified, 24 morphological features are extracted. Based on the results of feature extraction, the performances of the two segmentation approaches are compared. The system is validated with a data set of 100 images with 50 radiographs of female subjects and 50 of male subjects. The accuracy of feature extraction from the ROI segmented using both the segmentation procedures is calculated and the results are discussed.

Keywords

Bone Age, Bone Age Assessment (BAA), Particle Swarm Optimization (PSO), Graph-Based Segmentation, Tetrolets, Tetrolet-Based Segmentation, Feature Extraction.

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S. V. Sudha ¹, K. Thanushkodi ²

Affiliations
1 Department of Information Technology, Kalignar Karunanidhi Institute of Technology, Coimbatore-641402, Tamil Nadu, IN
2 Akshaya College of Engineering and Technology, Coimbatore-642109, Tamil Nadu, IN

Abstract

The problem of scheduling a set of dependent or independent tasks to be processed in a parallel fashion is one of the most challenging problems in parallel computing. The goal of a scheduler is to assign tasks to available processors such that precedence requirements between tasks are satisfied and the overall length of time required to execute the entire program, the schedule length or make span is minimized. A Parallel Genetic Algorithm Approach has been developed to the problem of task scheduling. GA is competitive in terms of solution quality if it has sufficient resources to perform its search. The Job taken for the Scheduling is the Detection of a Moving Object in a Video Sequence. The Moving Object Segmentation is suitable for real time content-based multimedia communication systems. First a background registration technique is used to construct as reliable background image from the accumulated frame difference information. The moving object region is then separated from the background region by comparing the current frame with the constructed background image. The implementation is optimized using parallel processing and achieved on a personal computer with a 3.0 GHZ Pentium IV Processor. Good segmentation performance is demonstrated by the simulation results.

Keywords

Background Registration, Moving Object Segmentation, Genetic Algorithm, Parallel Genetic Algorithm, Fitness Function.

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S. Bhavani ¹, K. Thanushkodi ²

Affiliations
1 Sri Shakthi Institute of Engineering and Technology, Coimbatore, IN
2 Akshaya Institute of Technology, Coimbatore, IN

Abstract

Magnetic resonance images play a major role in the diagnosis of vital organs of the human body. Huge amount of medical image data is generated on a daily basis. This data needs to be stored for future study and follow up. This requires a large amount of storage space which is especially true for three - dimensional (3-D) medical data formed by image sequences. This has resulted in image compression being an important issue in reducing the cost of data storage and transmission time. Mesh based compression is one among them. Wavelet transform is a powerful mathematical tool with many unique qualities that are useful for image compression and processing applications. Although wavelet concepts can be traced to back 1910, the mathematics of wavelets has only been recently formalized. By exploiting the spatial and spectral redundancy information in images, wavelet based methods offer better results for compressing medical images than do compression algorithms. Wavelet based methods does not suffer from blocking artifacts and the restored image quality is generally superior at high compression rates. This paper explains the compression based on content-based non-uniform meshes, spatial transformation for motion compensation of MR images using wavelet coding which optimizes the above said issue and also aids in medicine applications.

Keywords

Image Content-Based Mesh, Context-Based Modeling, Image Compression, Medical Imaging, Wavelet Coding.

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K. S. Chandragupta Mauryan ¹, K. Thanushkodi ², K. Sasikumar ¹, T. Satheesh Kumar ³, T. Thirupathi ¹

Affiliations
1 Department of Electrical and Electronics Engineering, Sri Krishna College of Technology, Coimbatore, IN
2 Akshaya College of Engineering and Technology, Coimbatore, IN
3 Department of Electrical and Electronics Engineering, Sri Krishna College of Technology, Coimbatore, IN

Abstract

This paper presents the algorithm to optimize the reactive power using colonial behavior of the ants. The reactive power problem has become a major threat and has been given much of importance since many blackouts occurred in USA and some European countries. The reactive power is essential to drive the active or real power that is needed on the load side. Especially the generator and transformer loads require reactive power for efficient functioning. But excess amount of the reactive power increases the loss as it contributes nothing to the load. The voltage profile is made as the major concern and it is modified using the proposed algorithm in order to minimize the loss. In this proposal of ant colonization algorithm, the particle taken to consideration interacts with its surroundings and its neighboring particles. Thereby the particle is updated periodically. By this phenomena the power flow problem at various points are updated periodically from which the optimization is being performed. Though various other algorithms have dealt with the same issue the ant algorithm provides a better result at higher convergence rate with better voltage profile. The developed algorithm deals with IEEE 14 bus system.

Keywords

Ant Colony, IEEE 14 Bus System, Power Loss, Reactive Power Optimization.

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M. Vanitha ¹, K. Thanushkodi ²

Affiliations
1 Coimbatore Institute of Engineering and Technology, Coimbatore, IN
2 Akshaya College of Engineering and Technology, Kinathukadavu, Coimbatore, IN

Abstract

Economic dispatch (ED) is an important optimization task in power system operation for allocating generation among the committed units. This paper presents a novel optimization technique to determine the feasible optimal solution of the economic dispatch problem considering valve-point effect. The proposed PSODE-SA method combines the Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) with Simulated Annealing (SA) technique to optimize the performance of ED problems. The combined methodology and its variants are validated for a test system consisting of 40 thermal units whose fuel cost function takes into account the valve-point loading effects. Thus the proposed method is one of the state-of-the-art algorithms in solving load dispatch problems with the valve-point effect.

Keywords

Differential Evolution, Economic Dispatch, Particle Swarm Optimization, Simulated Annealing.

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J. Jaya ¹, K. Thanushkodi ²

Affiliations
1 Anna University, IN
2 ACET, Coimbatore, IN

Abstract

The overall motivation of this paper is the implementation of detection of suspicious region from the medical images using metaheuristic algorithms. Segmentation is the very essential stage for extracting the region of interest (ROI) fr4om the medical images. In this paper Genetic algorithm and parallel Ant colony optimization techniques are used for the detection of MRI brain tumor.

Keywords

MRI, Genetic Algorithm, Parallel Ant Colony Optimization (PACO).

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K. Deeba ¹, K. Thanushkodi ²

Affiliations
1 Department of Computer Science and Engineering, Kalaignar Karunanidhi Institute of Technology, Coimbatore, Tamil Nadu, IN
2 Akshaya College of Engineering and Technology, IN

Abstract

This paper proposes a genetic algorithm optimization approach to solve job scheduling problems in a multiprocessor architecture. Job scheduling problem (JSP) is an extremely difficult hard problem because it requires a large combinatorial search space and also precedence constraints between the processes considered. Efficient assignment and scheduling of tasks is of high importance in the effective utilization of multiprocessor systems. With regard to this kind of JSP problem, a genetic algorithm based approach is utilized. In this approach, the chromosomes are encoded and the population size is devised for the optimized goal of scheduling problem. Then the fitness function is formulated. Next, utilizing the genetic algorithm operators to prevent the premature convergence, a best or satisfactory scheduling path can be determined. The execution results using the devised algorithms in certain multiprocessor architecture are given in the paper.

Keywords

Finishing Time, Genetic Algorithm, Job Scheduling Problem, Multiprocessor Architecture, Waiting Time.

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S. V. Sudha , K. Thanushkodi

Abstract

In this paper, we introduce a fuzzy based engine for the scheduling problem. In real world scheduling problems, due to the synchronization granularity of processes, the scheduling of parallel jobs becomes ineffective. A good way of characterizing a parallel system is to consider the synchronization granularity or frequency of synchronization between processes in a system. The scientific applications of the parallel system consist of multiple processes running on different processors that communicate frequently. The performance evaluation of such systems mainly depends on how the processes are co scheduled. If the processes are not co scheduled properly, then the system will lead to severe performance penalties. The various co scheduling techniques available are First Come First Served, Gang Scheduling and Flexible Co Scheduling and nimble algorithm. The paper focuses on an attempt to develop fuzzy systems based on the scheduling criteria which decides the best scheduling algorithm for parallel jobs.

Keywords

First Come First Served, Gang Scheduling, Nimble Algorithm, Mean Response Time, Turn Around Time.

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P. Manimegalai ¹, K. Thanushkodi ²

Affiliations
1 Department of Electronics and Instrumentation Engineering, Karunya University, Coimbatore, Tamilnadu, IN
2 Akshaya College of Engineering and Technology, Coimbatore, Tamilnadu, IN

Abstract

An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. CBIR aims at avoiding the use of textual descriptions and instead retrieves images based on their visual similarity to a user-supplied query image or user-specified image features. Although classical wavelet transform is effective in representing image feature and thus is suitable in CBIR, it still encounters problems especially in implementation, e.g. floating-point operation and decomposition speed, which may nicely be solved by lifting scheme, a novel spatial approach for constructing biorthogonal wavelet filters. Lifting scheme has such intriguing properties as convenient construction, simple structure, integer-to-integer transform, low computational complexity as well as flexible adaptivity, revealing its potentialsin CBIR. In this paper, by using general lifting and its adaptive version, we decompose HSI color images into multi-level scale and wavelet coefficients, with which, we can perform image feature extraction.

Keywords

Content Based Image Retrieval, Lifting Scheme, Adaptive Lifting.

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