Earticle

Distributed Denial of Service (DDoS) attacks has started posing a serious threat to all sorts of businesses, which have used the power of internet to their credit. DDoS attacks have put a big question mark on the capabilities and reliability of the World Wide Web. The use of supreme techniques to combat the DDoS attacks has not been substantial enough to fight the distributed nature of attacks. Hackers have been successful in blocking the services and flooding traffic to servers, in spite of a tight check on the network. Thus, in the view of personal data being present on the web and the threat to global economy worth million dollars, it becomes really important to devise some new techniques that are self-capable enough to capture, trace and nullify the dangers posed by such attacks. This term paper talks about such solutions to combat DDoS attacks. Here, the flow entropy in combination with average entropy technique is used to detect an attack. It highlights how the loop holes of one technique are covered by the other, resulting in a considerable improvisation in the methods of how we deal with these attacks.

We determine the N → ∞ asymptotics of the expected value of entanglement entropy for pure states in H_1,N ⊗ H_2,N, where H_1,N and H_2,N are the spaces of holomorphic sections of the N-th tensor powers of hermitian ample line bundles on compact complex manifolds.

1990년대 OCR에 대한 관심이 고조되면서, 다양한 필기 데이터베이스가 전 세계적으로 구축되었다. 그러나, 현재 연구분야에서 직면한 문제는 필기 품질을 포함하여 각기 다양한 방법으로 구축된 데이터베이스 내에서 필기 문자의 품질을 평가하는 것이다. 본 논문은 다양한 필기 데이터베이스를 비교하고, 문자 인식기의 성능을 객관적으로 평가하는데 사용할 수 있는 필기 품질을 측정하는 방법을 제안한다. 여기서 사용된 핵심 아이디어는 각각의 문자 샘플을 필기 품질에 따라 여러 개의 그룹으로 나누는 것이다. 제안된 방법의 성능을 평가하기 위하여, 대용량 필기 한글 데이터베이스인 KU-1 데이터베이스에 대한 실험을 수행한 결과, 제안된 방법이 필기 데이터베이스를 비교하고, 인식기의 성능을 객관적으로 평가하는데 유용하게 사용할 수 있는 가능성을 확인하였다.

With a surge of interest in OCR in 1990s a large number of handwriting or h handprinting databases have been built one after another around the world. One problem that researches encounter today is that all the databases differ in various ways including the script qualities. This paper proposes a method for measuring handwriting qualities that can be used for comparison of databases and objective test for character recognizers. The key idea i involved is classifying character samples into a number of groups each characterizing a set of qualities. In order to evaluate the proposed method we carried out experiments on KU-1 database. The result we achieve is meaningful and the method is helpful for the target tasks.