Informatics Publishing Limited

S. A. Jameel ¹, A. R. Mohamed Shanavas ²

Affiliations
1 Department of Computer Science, Jamal Mohamed College (Autonomous), Tiruchirappalli-620 020, IN
2 Jamal Mohamed College (Autonomous), Tiruchirappalli-620 020, IN

Abstract

Tortuosity assessments are used to estimate the tortuosity of retinal vessels as well as the retinal vessel system. In literature numerous strategies for retinal vessel tortuosity focused on curvature have been proposed.  In our paper we have proposed a proficient methodology for retinal vessel tortuosity curve estimation utilizing eigen values of Hessian matrix combined with binarisation with threshold entropy and Hough transform.

Keywords

Curvature, Hessian Matrix, Hough Transform, Retinal Vessel Tortuosity.

Full Text

     

S. A. Jameel ¹, A. R. Mohamed Shanavas ²

Affiliations
1 Department of Computer Science, Jamal Mohamed College (Autonomous), Tiruchirappalli-620 020, IN
2 Jamal Mohamed College (Autonomous), Tiruchirappalli-620 020, IN

Abstract

Advances in retinal imaging modalities have got enabled to spot new options in retinal vessel tortuosity. One amongst the explanations is that this disease is often treated if known within the early stages. Several algorithms and techniques with tortuosity measures are projected. With this intention we have a tendency to propose an approach that could be fast randomized circle detection for tortuosity of retinal images using Hough transform.

Keywords

Retinal Vessel Tortuosity, Tortuosity Measures, Fast Randomized Circle Detection and Hough Transform.

Full Text

     

A. R. Mohamed Shanavas ¹, M. S. Mythili ², D. Regina Margaret ²

Affiliations
1 Department of Computer Science, Jamal Mohamed College, Trichy, IN
2 Department of Computer Applications, Bishop Heber College, Trichy, IN

Abstract

Knowledge and skill of the stake holders are the most dominant factors to evaluate their quality of education. The aim of the paper is to analyze the performance of students of selected UG departments who have consistently figured in the top ten ranks in the first five semester marks by correlating the college marks with their higher secondary marks. The study also includes the correlation of male and female, rural and urban, residential and non residential students. The analysis is done by Statistical Data Mining, Regression Techniques and Hypothesis testing. Data mining is the key to the Knowledge Discovery Database (KDD).. The results of this analysis help the educational institutions to admit quality students for further studies and to retain the good results with high quality education.

Keywords

Data Mining, KDD, DSS, Hypothesis Testing, Prediction.

Full Text

     

A. R. Mohamed Shanavas ¹, M. Arul Kothai Priya ²

Affiliations
1 Jammal Mohamed College, Tiruchirappalli, IN
2 Bharathidasan University, IN

Abstract

The main focus of image mining in the proposed system is concerned with the identification of meningitis in the membrane of brain using CT scan brain image. Identifying the type of tuberculosis affecting the meninges of brain is a crucial step in computer assisted Meningitis TB detection. The system proposes a method based on modified K mean clustering to enhance the diagnosis of medical images like CT scan brain image. The system analyzes medical images and automatically generates suggestions of diagnosis employing modified K mean clustering and Hu Moment Invariant method. The proposed method uses two important algorithm of image mining. The first method extracts features present in the CT scan of brain image and the second method cluster the type of meningitis present in the image. In the existing system it classifies the presence of bacteria through the sputum analysis and identifies the TB affecting the lung. The proposed system identifies Meningitis TB affecting the membranes of the brain. The method has been applied on several real datasets, and the results shows high accuracy to claim that the use of modified K mean clustering is a powerful means to assist in the diagnosing task.

Keywords

Image Mining, Data Mining, Tuberculosis Meningitis (TBM), Hu Moment Invariant, Modified K Mean Clustering.

Full Text

     

A. R. Mohamed Shanavas ¹, S. A. Jameel ²

Affiliations
1 Jamal Mohamed College, Tiruchirappalli, IN
2 Jamal Mohamed College, Tiruchirappalli

Abstract

This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition, relevant topics such as psychophysical studies, system evaluation, and issues of illumination and pose variation are covered. To investigate its importance, we present an eye perturbation sensitivity analysis, as well as empirical evidence that reinforces the notion that eye localization plays a key role in the accuracy of face recognition systems. In particular, correct measurement of eye separation is shown to be more important than correct eye location, highlighting the critical role of eye separation in the scaling and normalization of face images. Results suggest that significant gains in recognition accuracy may be achieved by focusing more effort on the eye localization stage of the face recognition process.

Keywords

Face Recognition, Eye Localization, Biometrics.

Full Text

     

M. S. Mythili ¹, A. R. Mohamed Shanavas ²

Affiliations
1 Bharathidasan University and Department of Computer Applications, Bishop Heber College, Tiruchirappalli - 620017, Tamil Nadu, IN
2 Department of Computer Science, Jamal Mohamed College, Tiruchirappalli - 620020, Tamil Nadu, IN

Abstract

Background: The main objective of this paper is to focus on the early prediction of occurrence of cognitive disorders such as Autism, Dyslexia and Delirium among children. The common primary attributes are related to learning, social interaction, behaviour, understanding of objects and so on. Detecting this disorder at an early age is challenge lying among health care specialists, and researchers. Methodology: The proposed prediction method involves the modelling approach such as Meta Heuristic and Fuzzy Cognitive Map named as MEHECOM. Findings: The primary aim of MEHECOM model is to identify the disorders among children as an early measure and support towards early mechanism to alleviate from these disorders. The performance shows that MEHECOM predicts chances of dyslexia and autism disorders at an average of 65.22% compared to 48.7% of FEAST which adopts fuzzy cognitive map and 35.92% of decision tree approach. Applications: This MEHECOM model can be applied for the earlier prediction of all other cognitive disorders like amnesia, dementia etc.

Keywords

Cognitive Disorders, Early Prediction, Fuzzy Cognitive Map, Meta Heuristic Approach

Full Text

   

B. Mohamed Ibrahim ¹, A. R. Mohamed Shanavas ²

Affiliations
1 Software Solution Architect & Research Scholar Camp, MY
2 Jamal Mohamed College, Trichy, IN

Abstract

Web Services has emerged as a dominant paradigm for constructing and composing distributed business collaborations over the web. Security is one of the major concerns when developing mission critical business applications and this concern motivates Web Services Security specifications. This paper provides the literature review on the construction of solutions to SOA attacks on SOAP based web services.

Keywords

SOA, Security Threats, SOA Attacks, Web Services, SOAP, Security Solutions.

Full Text