Engineering Computer Science

SHARMILA S

Address: **/** **** **: * Mail to:

*******************@*****.***

South Sivan Kovil Street,

Vadapalani, chennai.

Mobile: 875-***-****

OBJECTIVE

Intend to build a career with committed and dedicated people, which will

help me to explore myself fully and realize my potential. Willing to work

as a key player in challenging and creative environment.

SKILLS & KNOWLEDGE PROFICIENCY

V Operating Systems: Windows98, 2000, XP, Vista

V Languages : C, Java(core)

V Testing: Manual, Automation

V Automation: Quick Test Professional

Quality center

Load Runner

Open STA

ACADEMIC QUALIFICATIONS

V M.E (Software Engineering) - Rajalakshmi Engineering College, ANNA

UNIVERSITY with 7.5(CGPA)(till 3rd sem)

V B.E (Computer Science Engineering) - S.R.M Valliammai Engineering

College, ANNA UNIVERSITY with 66%

V Higher secondary - Govt Girls Higher Sec School, Ashok Pillar, Chennai

STATEBOARD with 64%

V SSLC- Vidyaniketan Matriculation Higher Sec School, Chennai

MATRICULATION with 74%.

AREAS OF INTEREST

V Software Testing

V Software Project Management

V Software Engineering

KEY PROJECTS

AN ARTIFICIAL NEURAL NETWORK BASED VESSEL DETECTION ON THE OPTIC DISC USING

RETINAL PHOTOGRAPHS

Abstract:

Diabetic retinopathy caused by complications of diabetes, which can

eventually lead to blindness. It affects up to 80% of all patients who have

had diabetes for 10 years or more. Despite of these statistics, research

indicates that at least 90% of new cases could be reduced if there was

proper and vigilant treatment and monitoring of the eyes. The longer a

person has diabetes, higher the chances of developing diabetic retinopathy

.The aim of the project is to detect abnormal vessels in the optic disc of

human eye and also prevent from the eye related disease by measuring the

features (shape, position, orientation, brightness, contrast) and applying

segmentation by replacing the values of the feature measurements the

vessels are detected. The existing system uses support vector machine (SVM)

to categorize each segment as normal or abnormal. The SVM is used to

analyze data and recognize patterns but it cannot detect the vessels

automatically, accuracy is not clear and the prediction of disease needs

better knowledge. The proposed system uses neural network algorithm for

training the features and prediction of disease that is accurate and faster

and can find the disease based on ranking its features.

A NOVEL APPROACH FOR RESTRICTING THE MALICIOUS SPOOFING OF IP ADDRESSES IN

THE INTERNET USING IDPF

Abstract:

The paper provably correct algorithm for computing the outcome of BGP route

selection process for each router in a network. Prevention mechanism are

thwarted by the ability of attackers to forge or spoof the source addresses

in IP packets. By employing IP spoofing, attackers can evade detection and

put a substantial burden on the destination network for policing attack

packets. The algorithms require only static inputs that can be easily

obtained from the routers: the BGP routes learned from the neighboring

domains, the import policies configured on the BGP sessions, and the

internal topology. Solving the problem would be easy if the route selection

process was deterministic and every router received all candidates BGP

routes. However two important features of BGP-the multiple exit

discriminators (MED) attribute and route reflectors violate these

properties. a key feature of our scheme is that it does not require global

routing information. It establishes the condition under which IDPF

framework correctly works in that it does not discard packets with valid

source addresses. After presenting a simple route prediction algorithm for

networks that do not use these features, we present algorithms for networks

that do not use these features, we present the algorithms that capture the

effects of the MED attribute and route reflectors in isolation.

CERTIFICATION COURSE:

Certification in Software Testing from -MSME Guindy

ACHIEVEMENTS

Published paper "An Artificial Neural Network based vessel detection on the

optic disc using retinal photographs" on journal "International Journal of

Engineering and Computer Science".

Presented IEEE paper "Artificial Neural Network based vessel detection on

the optic disc using retinal photographs" in the National conference

on,"Advances in Computing & Networking(NCACNET) 2012

EXTRA CURRICULAR:

V Won prizes in classical dance competition.

V Performed in natyanjali

PERSONAL SKILLS

V Adaptability.

V Hardworking.

V Self-starter and Quick learner

PERSONAL DETAILS

Father's Name: Subramanyan.M

Date of Birth: 11-01-1988

Nationality: Indian

Language Known: English Telugu Tamil Hindi

DECLARATION:

I hereby declare that the particulars of information and facts stated

herein above are true, correct and complete to the best of my knowledge and

belief.

Place: Chennai.

Date: 01/07/2013

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(S.SHARMILA)

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