A process of knowledge discovery from web log data: Systematization and critical review

This paper presents a comprehensive survey of web log/usage mining based on over 100 research papers. This is the first survey dedicated exclusively to web log/usage mining. The paper identifies several web log mining sub-topics including specific ones such as data cleaning, user and session identification. Each sub-topic is explained, weaknesses and strong points are discussed and possible solutions are presented. The paper describes examples of web log mining and lists some major web log mining software packages.     

Computer Aided Engineering Methods for Implementing the Fastbus Standard

In this paper, we discuss the benefits of using Computer Aided Engineering (CAE) methods for implementing a bus standard (Fastbus, ANSI/IEEE Std 960). We describe the CAE methods, how standard design implementations and reference models complement CAE tools to form an integrated engineering environment, and we propose to use these methods for future standard developments.     

Comparative Study of Improved Neurolinear Method to Two Other Novel Feature Extraction Techniques

This paper compares Neurolinear feature extraction technique to two other feature extraction techniques. The author has developed all three methods recently, but in this paper, Neurolinear method has been improved even further. The study is performed in respect to performance, accuracy and suitability for visualisation. Experimental study is performed on a variety of datasets from numerous domains: Chemistry, biology, finance etc. In total, 19 real and two artificial datasets were used. Comparison is performed in terms of computational efficiency and accuracy. Results show that Neurolinear method achieves best accuracy while Best directions method is not so accurate but often much faster.     

Automatic verification of competitive stochastic systems

We present automatic verification techniques for the modelling and analysis of probabilistic systems that incorporate competitive behaviour. These systems are modelled as turn-based stochastic multi-player games, in which the players can either collaborate or compete in order to achieve a particular goal. We define a temporal logic called rPATL for expressing quantitative properties of stochastic multi-player games. This logic allows us to reason about the collective ability of a set of players to achieve a goal relating to the probability of an event’s occurrence or the expected amount of cost/reward accumulated. We give an algorithm for verifying properties expressed in this logic and implement the techniques in a probabilistic model checker, as an extension of the PRISM tool. We demonstrate the applicability and efficiency of our methods by deploying them to analyse and detect potential weaknesses in a variety of large case studies, including algorithms for energy management in Microgrids and collective decision making for autonomous systems.