CSE

The string splicing was introduced by Tom Head which stands as an abstract model for the DNA recombination under the influence of re- striction enzymes. The complex chemical process of three dimensional molecules in three dimensional space can be modeled using graphs. The graph splicing systems which were studied so far, can only be applied to a particular type of graphs which could be interpreted as linear or circular graphs. In this paper, we take a different and a novel approach to splice two graphs and introduce a splicing system for graphs that can be applied to all types of graphs. Splicing two graphs can be thought of as a new operation, among the graphs, that generates many new graphs from the given two graphs. Taking a different line of thinking, some of the graph theoretical results of the splicing are studied.

The string splicing was introduced by Tom Head which stands as an abstract model for the DNA recombination under the influence of re- striction enzymes. The complex chemical process of three dimensional molecules in three dimensional space can be modeled using graphs. The graph splicing systems which were studied so far, can only be applied to a particular type of

A high level of glucose in the blood over a long period creates diabetes disease. Undiagnosed diabetes may trigger other complications such as cardiovascular disease, nerve damage, renal failure, and so on. There are many factors age, blood pressure, food habits, lifestyle changes are some of the reasons for diabetes. With increasing cases of diabetes in the smart Internet world, there is a need for an automated prediction system to facilitate the patients, to get know, whether they are affected by the disease or not. There are many diabetes prediction software that is already in use, still, the accurateness of a diabetes prediction is not complete. This paper presents a robust framework (PSO-NNDP), employs a novel hybrid feature selector to improvise the neural-based diabetes prediction system. The novel hybrid feature selector presented in this paper comprises the merits of the correlation coefficient, F-score, and particle swarm optimization methods to influence the feature selec...

Now a day’s face detection technology is widely used technique. It attracted attention for much valuable application in the market such as face recognition system. Biometric authentication is most important method in security system. Universally used Biometric fingerprint scanner can be bypassed quite easily. It can be broke easily. Biometric face recognition has been introduced to improve the security of a system. Methods such as Motion based and texture based are used for biometric face recognition. But these methods have less robustness and poor generalization ability. But apart from further security issues, this paper presents a new approach to make attendance of the student in class by the face recognition. Now a day’s attendance system is usually done manually or by the biometric fingerprint. Those are mistaken and tedious techniques. So this technique records the student’s participation in classroom consequently and provide facility for teachers for obtaining the data of the ...