Improving savonius marine current turbine

Also available in printed version : TK7882.P3 A924 2009 raf

Bibliographic Details
Main Author: Kathiravan Muniapan
Other Authors: Omar Yaakob, supervisor
Format: Bachelor thesis
Language:English
Published: Universiti Teknologi Malaysia 2025
Subjects:
Online Access:https://utmik.utm.my/handle/123456789/115256
Abstract Abstract here
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author Kathiravan Muniapan
author2 Omar Yaakob, supervisor
author_facet Omar Yaakob, supervisor
Kathiravan Muniapan
author_sort Kathiravan Muniapan
description Also available in printed version : TK7882.P3 A924 2009 raf
format Bachelor thesis
id utm-123456789-115256
institution Universiti Teknologi Malaysia
language English
publishDate 2025
publisher Universiti Teknologi Malaysia
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record_pdf Abstract
spelling utm-123456789-1152562025-08-20T21:43:45Z Improving savonius marine current turbine Kathiravan Muniapan Omar Yaakob, supervisor Turbines Also available in printed version : TK7882.P3 A924 2009 raf Writer Identification (WI) is an active research area in pattern recognition due to its immense potential for commercialization. The challenging process in WI is that handwriting varies from one person to another. However, it is individualistic where the consistent individual features are hidden in the handwriting. Due to these, most of the previous works focus on how to acquire individual features by deploying rigid characteristics (local features). These approaches contribute to large lexicon, increase the computational complexity and decrease the accuracy. Therefore, this study focuses on extracting global features from the handwritten word shape by using the proposed United Representation technique in order to address the issues of local features in WI. The extracted features are investigated granularly to validate the existence of individual features; hence the concept of Authorship Invarianceness is introduced. Authorship Invarianceness is defined as preservation of the individual features regardless of its handwriting transformations. It improves the Authorship Invarianceness by reducing the similarity error for intra-class (same writer) and increasing the similarity error for interclass (different writer). The individuality representation is implemented by presenting various representations of individual feature into standard representations using the proposed Invariant Discretization. Experimental results show that the performance of the proposed methods has improved with identification rate of 99.90% using various classifiers including the proposed Modified Immune Classifier (MIC) snhas UTM 73 p. Thesis (Ph.D (Sains Komputer)) - Universiti Teknologi Malaysia, 2009 2025-04-18T08:29:24Z 2025-04-18T08:29:24Z 2012-06 Bachelor thesis https://utmik.utm.my/handle/123456789/115256 valet-20151008-074959 vital:80281 ENG Closed Access UTM Complete Completion Unpublished application/pdf Universiti Teknologi Malaysia
spellingShingle Turbines
Kathiravan Muniapan
Improving savonius marine current turbine
thesis_level Other
title Improving savonius marine current turbine
title_full Improving savonius marine current turbine
title_fullStr Improving savonius marine current turbine
title_full_unstemmed Improving savonius marine current turbine
title_short Improving savonius marine current turbine
title_sort improving savonius marine current turbine
topic Turbines
url https://utmik.utm.my/handle/123456789/115256
work_keys_str_mv AT kathiravanmuniapan improvingsavoniusmarinecurrentturbine