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Kavipriya, P.
- OVSF Dynamic Code Allocation Quality based Glowworm Swarm Optimization Approach in WCDM
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Authors
Affiliations
1 Electronics and Communication Engineering, Sathyabama University, Chennai - 600 119, IN
1 Electronics and Communication Engineering, Sathyabama University, Chennai - 600 119, IN
Source
Indian Journal of Science and Technology, Vol 8, No 12 (2015), Pagination:Abstract
OVSF codes are used as channelization codes to support applications with different bandwidth requirements for the downlink of 3G mobile communication systems. The code assignment and reassignment problem focuses on the subject of minimizing the number of code relocations. OVSF (Orthogonal Variable Spreading Factor) code assignment method considering traffic characteristics in the WCDMA systems. The previously proposed Dynamic Code Assignment (DCA) scheme allows code reassignments to improve code utilization, but induces some service delay time to on-going calls, unlikely assumptions, including fixed service data rates and code-limited system capacities. Thus, OVSF code tree has insufficient number of available codes. Method/Statistical Analysis: In order to solve these problems and efficiently utilized OVSF codes, in this paper presents novel Glow warm Swarm Intelligence (GSO) based approach for active OVSF code assignment in WCDMA based networks. GSO algorithm is completely dependent on the behavioral pattern of glowworm (fireflies). The optimization algorithm requires an understanding of this behavioral pattern. The intensity of the emission of Lucifer in can be changed by glow worms which glow at different intensities. In order to improve the ability of the GSO it employs various phases until code allocation is completed. Results: By permitting only codes in the data branch to be reassigned the quality of service guarantee for real time traffic is possible. The simulation results shows that proposed GSO schemes not only guarantees the QoS but also gives high code utilization which is comparable with other existing techniques. Conclusion/ Application: Performances of these methods are evaluated in terms of blocking probability, spectral efficiency, delay and throughput. In addition to this different GSO operator are tested under varying traffic loads to increase the overall system performance.Keywords
ABC, Dynamic Code Assignment, GSO, MAGA Performance Parameters, PSO, Resource Allocation, WCDMAFull Text
- Detection of AML in Blood Microscopic Images using Local Binary Pattern and Supervised Classifier
Abstract Views :168 |
PDF Views:0
Authors
Affiliations
1 ECE Department, Sathyabama Institute of Science and Technology, Chennai-119, IN
1 ECE Department, Sathyabama Institute of Science and Technology, Chennai-119, IN
Source
Research Journal of Pharmacy and Technology, Vol 12, No 4 (2019), Pagination: 1717-1720Abstract
A novel method of detecting Acute myelogenous leukemia (AML) disease using image processing algorithms is discussed in this paper. AML is an high risk disease which should be diagnosed early. AML detection is challenging, and should be performed by a qualified hematopathologist or hematologist. This paper discusses an automatic detection of AML using image processing methods. The algorithm consists contrast enhancement, Local binary pattern detection and Fuzzy C mean clustering technique. This Automatic detection method will helps the hematologists for easier identification and early detection of leukemia from blood microscopic images which will improve the chances of survival for the patient. A fuzzy based two stage color segmentation strategy is employed for segregating leukocytes or white blood cells (WBC) from other blood components. Discriminative features i.e. nucleus shape, texture are used for final detection of leukemia.Keywords
Acute Myelogenous Leukemia, Fuzzy C Mean Clustering, Local Binary Pattern Feature Extraction.
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