Papers

The main aim of this paper is to generalize fuzzy decision system for the Assessment of Students in an Engineering colleges or Universities. Roughly speaking, the student's category can be classified into three major classes: so- called Good, Average and Poor. The Teachers who are involved in the course & regularly delivering the lecture Classes, interacting with the students are the best persons to judge or assess a student. The various factors that are taken into consideration for the Student's Assessment are Appearance, Communication skills, IQ, Class Attendance, Punctuality, Alertness, Class Performance and Extra-curricular Activities. Periodically, the University Director is interested in studying the performance Assessment of the Students. Generally, meetings are held where the Teachers involved in the course give their opinion linguistically to the respective Students depending upon the various factors that are taken into consideration for Student's Assessment Process. Then a decision is taken to find out the best Student in the University. A requirement fuzzy subset has been formulated. A relationship is formed between the respective students and the teacher's opinion using the fuzzy subset representation. It is proposed to construct fuzzy decision set which includes the relative merits of all Students in the University. The Index of fuzziness of various Teacher involved in the course are measured and compared. A decision system has been developed using fuzzy distance approach to select the best Student.

Image de-noising and restoration represent basic problems in image processing with many different applications including engineering, reconstruction of missing data during their transmission and enhancement of biomedical structures as well. This problem occurs also in filling-in blocks of missing or corrupted data. The paper presents the use of Wavelet transform in this area including its application for image decomposition and rejection of its components at first. The main part of the paper is then devoted to methods of restoration of missing image blocks by the search of similar structures of a given image in the Wavelet domain space and comparison of this approach with iterated Wavelet interpolation and predictive image modeling. Proposed methods are verified for simulated images and then applied for processing of magnetic resonance images.

Establishing hidden communication is an important subject of discussion that has gained increasing importance nowadays. There has been many secret communication techniques proposed in the last few years. The focus was given to steganography to build such techniques .Utilizing stego-keys to hide secret messages into images strengthen the security of these techniques. Informally, steganography refers to the practice of hiding secret messages in communications over a public channel so that an eavesdropper (who listens to all communications) cannot even tell that a secret message is being sent. In contrast to the common LSB method used for hiding information in images we have generated a better algorithm for steganography along with its implementation with better security. In this work we have illustrated the fact that next to LSB method with minimum noise of steganography gives less chance for the hacker to hack the information in the network as compared to LSB method.