Project Engineering

Karthika S Manu

EMAIL: ********.*****@*****.***

MOB: 949-***-****

Carrier Objective

To have a challenging career with ample opportunities to learn and get

skilled on various technologies and processes, where my abilities are

utilized to the fullest for the benefit of the organization.

Software Skills

Languages C, C++ and HTML

Database MS SQL

Technologies

Operating System Windows 98, NT, 2000, XP

Web Designing Adobe Photoshop 7.0

Projects

MINI PROJECT:

Project Name : ZIGBEE CONTROLLED HOME DEVICE

Organization : MUSALIAR COLLEGE OF ENGINEERING

Developing Tool : C PROGRAMMING

Project Description:-

ZigBee is a specification for a suite of high level communication protocols

used to create personal area networks built from small, low-power digital

radios. ZigBee is based on IEEE 802.15 standard. ZigBee Home Automation

technology establishes a standard approach for wireless products worldwide,

eliminating the need for proprietary technology. Home automation solutions

can take advantage of a consistent wireless communication technology which

offers unprecedented benefits in operational reliability, control,

convenience, and security. ZigBee Remote Control simplifies how consumers

control and use devices of many types.

MAIN PROJECT:

Project Name : NEURAL NETWORK BASED HANDWRITTEN

CHARACTER RECOGNITION

Organization : KELTRON CONTROLS, ERNAKULAM, KERALA

Developing Tool : MATLAB

Project Description:-

This project investigates a method of Handwritten English Character

Recognition using Artificial Neural Network (ANN). This work has been done

in offline Environment for non correlated characters, which do not possess

any linear relationships among them. We test that whether the particular

tested character belongs to a cluster or not. The implementation is carried

out in Matlab environment and successfully tested. Fifty-two sets of

English alphabets are used to train the ANN and test the network. The

algorithms are tested with 26 capital letters and 26 small letters. The

testing result showed that the proposed ANN based algorithm showed a

maximum recognition rate of 85%.

Academic Qualifications

B-tech Musaliar College of 2009-2013 70%

(Electronics & Engineering& technology,

Communication Pathanamthitta (MG

Engineering) University)

Plus-Two Amrita Vidyalayam (CBSE), 2009 May 79%

Thiruvalla,

Pathanamthitta

SSLC Amrita Vidyalayam (CBSE),

Thiruvalla, 2007 March 86%

Pathanamthitta

Personal Information

Date of birth : 10-06-1992

Sex : Female

Nationality : Indian

Religion : Hindu

Languages Known : English, Malayalam

Mother Tongue : Malayalam

Father : Mr. Manoharan Pillai

Mother : Mrs. Sajitha Manoharan

Hobbies : Browsing, Movies, Chess, Music, Travelling

Mobile Number : 949-***-****

E-mail id : ********.*****@*****.***

Declaration

I hereby declare that all the above information furnished by me is true and

correct to the best of my knowledge and belief.

(Karthika S Manu)

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