Informatica

The invention of public-key cryptography makes many new network applications, such as electronic commerce (CE), possible. However, the widely used Internet is open and unprotected. Therefore, verifying the legitimacy of an individual's public key is very important. Most of the key authentication schemes require one or more trustworthy authorities to authenticate the key of a user. Consequently, the system security is mainly dependent on the honesty of these third parties. Unfortunately, a security solution in wide area networks (for example, the Internet) often cannot be applied to local area networks directly without any modification. Sometimes, a complete rebuild is necessary, especially for performance criteria consideration. In this paper, we propose two simple key authentication schemes that require no certification authorities for computer systems in local area networks, in which a host is responsible for user authentication and it uses a designated password authentication mechanism.

Abstract data types constitute a central tool in computer science and play an important role in problem solving, knowledge representation, and programming. In this paper, formal and practical aspects of utilizing abstract data types (ADTs) are discussed in the context of logic programming when using the Prolog programming language. The approach is presented in the following stages: (a) First, alternative ways of implementing ADTs in terms of Prolog constructs are presented and partial encapsulation of ADTs in terms of grey boxes is demonstrated. (b) Next, complete encapsulation of ADTs in terms of black boxes is suggested in a way that strictly reflects the concept's formal computer science definition while taking into consideration the characteristics and constraints of the logic programming paradigm. (c) Finally, implications for instruction are discussed.

This paper presents a method of minutiae based fingerprint matching that is robust to deformations and does not do fingerprint alignment. It concentrates on comparing rotation and translation invariant local structures defined by minutiae point and its neighboring minutiae points. Then the collection of most probable correspondences of matched minutiae is found. Finally, the local structures of higher order are validated. All three steps are completely rotation and translation invariant, robust to nonlinear deformations and do not use any fingerprint alignment. Experimental results on publicly available as well as internal databases show an improved performance of the proposed method in comparison with the traditional minutiae based algorithms that perform fingerprint registration.

The aim is to investigate two emerging information technologies in graduate studies and scientific cooperation. Internet is the first technology. The open source is the second. They help each other in many ways. The joint influence of both is regarded in this paper.

This paper presents the application of multi-criterion approach to the analysis and comparison of reference alternatives of wind power park information system (WPPIS) which complies with the standard IEC 61400-25. The comparison is based on multi-criterion preferences measured in domination rate (index). The reference alternatives include centralized, mixed and seamless communication topologies. The major features of these alternatives are discussed as well as the multi-criterion methodology applied covering pair comparison, Pareto sets and fuzzy sets methods. The current investigation described is an extension of the preceding investigation of the same reference alternatives of WPPIS. As we have showed, the transition from the concerted experts view as it was a case in previous investigation to the conflicting expert views in the current investigation proved the high robustness of solution made for the case of concerted expert views: the rank of preferences for alternatives remained the same, with seamless communication topology on the top the rank.

This paper presents a bimodal biometric verification system based on the fusion of palmprint and face features at the matching-score level. The system combines a new approach to palmprint principal lines recognition based on hypotheses generation and evaluation and the well-known eigenfaces approach for face recognition. The experiments with different matching-score normalization techniques have been performed in order to improve the performance of the fusion at the matching-score level. A “chimerical” database consisting of 1488 palmprint and face image pairs of 241 persons was used in the system design (440 image pairs of 110 persons) and testing (1048 image pairs of 131 persons). The experimental results show that system performance is significantly improved over unimodal subsystems.

This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set characterizing the objects increases. We propose an adaptive clustering method based on a hierarchical agglomerative approach, Hierarchical Adaptive Clustering (HAC), that adjusts the partitioning into clusters that was established by applying the hierarchical agglomerative clustering algorithm (HACA) (Han and Kamber, 2001) before the feature set changed. We aim to reach the result more efficiently than running HACA again from scratch on the feature-extended object set. Experiments testing the method's efficiency and a practical distributed systems problem in which the HAC method can be efficiently used (the problem of adaptive horizontal fragmentation in object oriented databases) are also reported.

The study of databases began with the design of efficient storage and data sharing techniques for large amount of data. This paper concerns the processing of imprecision and indiscernibility in relational databases using vague rough technique leading to vague rough relational database model. We utilize the notion of indiscernibility and possibility from rough set theory coupled with the idea of membership and non-membership values from vague set theory to represent uncertain information in a manner that maintains the degree of uncertainty of information for each tuple of the original database and also those resulting from queries. Comparisons of theoretical properties of operators within this model with those in the standard relational database model are discussed. A simple entity-relationship type diagram for database design, a database definition language and an SQL-like query language for vague rough relational database model are described.

Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data block is basically a random sample from a stationary distribution, but many databases available violate this assumption. That is, the class of an instance may change over time, known as concept drift. In this paper, we propose a Sensitive Concept Drift Probing Decision Tree algorithm (SCRIPT), which is based on the statistical X² test, to handle the concept drift problem on data streams. Compared with the proposed methods, the advantages of SCRIPT include: a) it can avoid unnecessary system cost for stable data streams; b) it can immediately and efficiently corrects original classifier while data streams are instable; c) it is more suitable to the applications in which a sensitive detection of concept drift is required.