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Search Results: 1 - 10 of 21 matches for " Angamuthu Thilagavathy "
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RETRACTED: An Improved Fuzzy Based Algorithm for Detecting Text from Images Using Stroke Width Transform  [PDF]
Angamuthu Thilagavathy, Arulgnanaprakasam Chilambuchelvan
Circuits and Systems (CS) , 2016, DOI: 10.4236/cs.2016.74031
Abstract:

Short Retraction Notice

This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused.

The full retraction notice in PDF is preceding the original paper, which is marked \"RETRACTED\".

Chromatic Number of Graphs with Special Distance Sets-V  [PDF]
Venkataraman Yegnanarayanan, Angamuthu Parthiban
Open Journal of Discrete Mathematics (OJDM) , 2013, DOI: 10.4236/ojdm.2013.31001
Abstract: An integer distance graph is a graph G(Z,D) with the set of integers as vertex set and an edge joining two vertices u and v if and only if u - v\"\"D where D is a subset of the positive integers. It is known that x(G(Z,D) )=4 where P is a set of Prime numbers. So we can allocate the subsets D of P to four classes, accordingly as is 1 or 2 or 3 or 4. In this paper we have considered the open problem of characterizing class three and class four sets when the distance set D is not only a subset of primes P but also a special class of primes like Additive primes, Deletable primes, Wedderburn-Etherington Number primes, Euclid-Mullin sequence primes, Motzkin primes, Catalan primes, Schroder primes, Non-generous primes, Pell primes, Primeval primes, Primes of Binary Quadratic Form, Smarandache-Wellin primes, and Highly Cototient number primes. We also have indicated the membership of a number of special classes of prime numbers in class 2 category.
Multi-Dimension Support Vector Machine Based Crowd Detection and Localisation Framework for Varying Video Sequences  [PDF]
Manoharan Mahalakshmi, Radhakrishnan Kanthavel, Divakaran Thilagavathy Dinesh
Circuits and Systems (CS) , 2016, DOI: 10.4236/cs.2016.711303
Abstract: In this paper, we propose a novel method for anomalous crowd behaviour detection and localization with divergent centers in intelligent video sequence through multiple SVM (support vector machines) based appearance model. In multi-dimension SVM crowd detection, many features are available to track the object robustly with three main features which include 1) identification of an object by gray scale value, 2) histogram of oriented gradients (HOG) and 3) local binary pattern (LBP). We propose two more powerful features namely gray level co-occurrence matrix (GLCM) and Gaber feature for more accurate and authenticate tracking result. To combine and process the corresponding SVMs obtained from each features, a new collaborative strategy is developed on the basis of the confidence distribution of the video samples which are weighted by entropy method. We have adopted subspace evolution strategy for reconstructing the image of the object by constructing an update model. Also, we determine reconstruction error from the samples and again automatically build an update model for the target which is tracked in the video sequences. Considering the movement of the targeted object, occlusion problem is considered and overcome by constructing a collaborative model from that of appearance model and update model. Also if update model is of discriminative model type, binary classification problem is taken into account and overcome by collaborative model. We run the multi-view SVM tracking method in real time with subspace evolution strategy to track and detect the moving objects in the crowded scene accurately. As shown in the result part, our method also overcomes the occlusion problem that occurs frequently while objects under rotation and illumination change due to different environmental conditions.
A STUDY OF ATTITUDE TOWARDS ENVIRONMENTAL EDUCATION AND ENVIRONMENTALAWARENESS OF B.ED. TRAINEES
K. MANIKANDAN,T. THILAGAVATHY
Indian Streams Research Journal , 2013,
Abstract: This study examines the relationship between the attitude towardsenvironmental education and environmental awareness of the B.Ed. Trainees. Normative survey method was employed. 400 B.Ed,. trainees were selected from Cuddalore and Villupuram District in Tamilnadu by using random sample method. The environmental attitude scale and the environmental awareness scale were used to collect the required information. The results of the study reveal that the B.Ed. trainees are having favourable attitude towards environmental education and also having a good level of environmental awareness. The demographic variables gender, subject, location, age, and optional subjects played vital role in the present study
Multiple foot sinuses due to schizomycetes
Amaravati Rajkumar,Angamuthu N
Indian Journal of Orthopaedics , 2005,
Abstract:
Prevalence and antimicrobial susceptibility of extended-spectrum β-lactamase-producing Escherichia coli and Klebsiella pneumoniae in a general hospital
Kader Abdulrahman,Kumar Angamuthu
Annals of Saudi Medicine , 2005,
Abstract: Background: The prevalence of extended-spectrum a-lactamases (ESBLs) varies between countries and institutions. We studied the prevalence of ESBL among clinical isolates of Escherichia coli and Klebsiella pneumoniae and analyzed patterns of susceptibilities to different antimicrobial agents in a general hospital in Saudi Arabia over a 15-month period. Methods: A total of 2455 clinical isolates of E. coli and K. pneumoniae were tested for ESBL production by double-disk diffusion. The minimum inhibitory concentration to imipenem, meropenem, piperacillin-tazobactam, cefepime, ciprofloxacin, gentamicin and amikacin were determined by the agar dilution method. Results: Of the 2455 isolates of E. coli and K. pneumoniae tested, 268 (11%) produced ESBL. The ESBL phenotype was detected in 10.3% of 1674 E. coli isolates and 12.2% of 781 K. pneumoniae isolates. The majority of these isolates were from urine (57.5%) and wounds (17%). Only 7% of the blood culture isolates were ESBL-producing. Overall, carbapenems (imipenem and meropenem) had good activity against the ESBL-producing isolates tested (over 92% of isolates were susceptible). There was no difference in the activity of imipenem and meropenem against the ESBL-producing E. coli or K. pneumoniae. Over 66% of the isolates were susceptible to piperacillin-tazobactam. Susceptibilities of the isolates to amikacin varied, ranging from 72.8% for E. coli to 62% for K. pneumoniae. Gentamicin, ciprofloxacin and cefepime were active against 58.6%, 55% and 22.8% of the isolates, respectively. Conclusion: Our findings demonstrate the increasing incidence of infection with ESBL-producing bacteria, and the high rates of antimicrobial resistance encountered among them. Clinicians should be familiar with the clinical importance of these enzymes and potential strategies for dealing with them.
An Autonomous Framework for Early Detection of Spoofed Flooding Attacks
Malliga Subramanian,Tamilarasi Angamuthu
International Journal of Network Security , 2010,
Abstract: One of the challenging tasks on the Internet is differentiating the attack traffic from legitimate traffic. Tackling this challenge would aid in the detection of Denial of Service/Distributed DoS (DoS/DDoS) attacks. In this paper, we propose a flow profiling scheme that adopts itself to detect these flooding attacks by monitoring the trends in the current traffic. Moreover, our scheme filters most of the traffic, which are found to be suspicious, at the source end, thus avoiding flooding at the target. The scheme distinguishes itself from other source end defenses in the manner in which it gathers and profiles the statistics. Information entropy, a measure to find correlation among traffic flows, is used. We made this attempt to infer the current state of the dynamic network. The result of correlation is then used to support the evidences which justify the necessity of filtering the packets. We use Theory of evidence to improve the decision making with regard to filtering. We implemented and tested our scheme using network traffic traces and found the results to be appreciable.
A new approach to geographic routing for location aided cluster based MANETs
Mangai SenthilVelmurugan,Tamilarasi Angamuthu
EURASIP Journal on Wireless Communications and Networking , 2011,
Abstract: Routing has been the main challenge for ad hoc networks due to dynamic topology as well as resource constraints. Completely GPS(Global Positioning System) free as well as GPS scarce positioning systems for wireless, mobile, ad-hoc networks has been proposed recently by many authors. High computational overhead and high mobility of the nodes typically require completely GPS enabled MANETs for higher performance. In this article, Improved Location aided Cluster based Routing Protocol (ILCRP) for GPS enabled MANETs has been evaluated for performance metrics such as end to end delay, control overhead, and packet delivery ratio. Use of cluster based routing as well as exact location information of the nodes in ILCRP reduces the control overhead resulting in higher packet delivery ratio. GPS utility in nodes reduces the end to end delay even during its high mobility. Simulations are performed using NS2 by varying the mobility (speed) of nodes as well as number of the nodes. The results illustrate that ILCRP performs better compared to other protocols.
Identifying Semantic Relations for DiseaseTreatment in Medline
P. Menaka,Prof.D.Thilagavathy
International Journal of Electronics and Computer Science Engineering , 2012,
Abstract: The Machine Learning (ML) is almost used in any domain of research and now it has become a reliable tool in the medical domain.ML is a tool by which medical field is integrated with the computer based systems to provide more efficient medical care. The main objective of this work is to show what Natural Language Processing (NLP) and Machine Learning (ML) techniques used for representation of information and what classification algorithms are suitable for identifying and classifying relevant medical information in short texts. It acknowledges the fact that tools capable of identifying reliable information in the medical domain stand as building blocks for a healthcare system that is up-to-date with the latest discoveries. In this research, it focuses on diseases and treatment information, and the relation that exists between these two entities.
Investigation of Citrus aurantiifolia Leaves Extract as Corrosion Inhibitor for Mild Steel in 1 M HCL
R. Saratha,S. V. Priya,P. Thilagavathy
Journal of Chemistry , 2009, DOI: 10.1155/2009/107807
Abstract:
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