HybridMiner: Mining Maximal Frequent Itemsets Using Hybrid Database Representation Approach

In this paper we present a novel hybrid (arraybased layout and vertical bitmap layout) database representation approach for mining complete Maximal Frequent Itemset (MFI) on sparse and large datasets. Our work is novel in terms of scalability, item search order and two horizontal and vertical projection techniques. We also present a maximal algorithm using this hybrid database representation approach. Different experimental results on real and sparse benchmark datasets show that our approach is better than previous state of art maximal algorithms.Comment: 8 Pages In the proceedings of 9th IEEE-INMIC 2005, Karachi, Pakistan, 200

Multiple Route Generation Using Simulated Niche Based Particle Swarm Optimization

This research presents an optimization technique for multiple routes generation using simulated niche based particle swarm optimization for dynamic online route planning, optimization of the routes and proved to be an effective technique. It effectively deals with route planning in dynamic and unknown environments cluttered with obstacles and objects. A simulated niche based particle swarm optimization (SN-PSO) is proposed using modified particle swarm optimization algorithm for dealing with online route planning and is tested for randomly generated environments, obstacle ratio, grid sizes, and complex environments. The conventional techniques perform well in simple and less cluttered environments while their performance degrades with large and complex environments. The SN-PSO generates and optimizes multiple routes in complex and large environments with constraints. The traditional route optimization techniques focus on good solutions only and do not exploit the solution space completely. The SN-PSO is proved to be an efficient technique for providing safe, short, and feasible routes under dynamic constraints. The efficiency of the SN-PSO is tested in a mine field simulation with different environment configurations and successfully generates multiple feasible routes

FastLMFI: An Efficient Approach for Local Maximal Patterns Propagation and Maximal Patterns Superset Checking

Maximal frequent patterns superset checking plays an important role in the efficient mining of complete Maximal Frequent Itemsets (MFI) and maximal search space pruning. In this paper we present a new indexing approach, FastLMFI for local maximal frequent patterns (itemset) propagation and maximal patterns superset checking. Experimental results on different sparse and dense datasets show that our work is better than the previous well known progressive focusing technique. We have also integrated our superset checking approach with an existing state of the art maximal itemsets algorithm Mafia, and compare our results with current best maximal itemsets algorithms afopt-max and FP (zhu)-max. Our results outperform afopt-max and FP (zhu)-max on dense (chess and mushroom) datasets on almost all support thresholds, which shows the effectiveness of our approach.Comment: 8 Pages, In the proceedings of 4th ACS/IEEE International Conference on Computer Systems and Applications 2006, March 8, 2006, Dubai/Sharjah, UAE, 2006, Page(s) 452-45

Simulation of the research process

This paper presents first steps towards the development of a formal model of the research process. We evaluate the use of simulation as a tool for the evaluation of research strategies in nascent research organizations faced with the absence of significant data. We start by modeling the research process by using the ”Publish or Perish” paradigm, a well-known criteria of evaluation of research. We demonstrate the use of this model for researchers to evaluate the effects of selection of a particular publishing venue over time. We then perform various experiments using this basic idea. By means of various visualization techniques, we see how researchers with similar publishing policies might self-organize in the form of groups. We also evaluate the effects of giving higher weights to articles in journals and see where the effects of publishing in these venues breaks even for both top as well as average acceptance rates

Detecting change and dealing with uncertainty in imperfect evolutionary environments

Imperfection of information is a part of our daily life; however, it is usually ignored in learning based on evolutionary approaches. In this paper we develop an Imperfect Evolutionary System that provides an uncertain and chaotic imperfect environment that presents new challenges to its habitants. We then propose an intelligent methodology which is capable of learning in such environments. Detecting changes and adapting to the new environment is crucial to exploring the search space and exploiting any new opportunities that may arise. To deal with these uncertain and challenging environments, we propose a novel change detection strategy based on a Particle Swarm Optimization system which is hybridized with an Artificial Neural Network. This approach maintains a balance between exploitation and exploration during the search process. A comparison of approaches using different Particle Swarm Optimization algorithms show that the ability of our learning approach to detect changes and adapt as per the new demands of the environment is high

Effect of Curriculum-Based Video Games on Students’ Performance: An Experimental Study

This experimental study investigated the effect of the use of video games based on the curriculum on students' performance levels in Fourth, Fifth and Sixth grade Mathematics compared to traditional learning methods. The participants were seven hundred and eighty-nine female students from Fourth, Fifth and Sixth grades, and nineteen teachers, from different six schools in Riyadh city in Saudi Arabia. Three research null hypotheses were tested to explore students’ performance when they received two different instructional treatments: traditional learning methods (textbooks or worksheets) and a video game based on the Mathematics curriculum. The results indicate that video games based on Mathematics curriculum had a positively effect on students’ performance based on their score average in standard tests, when compared to traditional learning methods

UNE APPROCHE METHODOLOGIQUE DE L'UTILISATION DES STAN APPLIQUEE A LA RECONNAISSANCE VISUELLE DE LA PAROLE

RENNES1-BU Sciences Philo (352382102) / SudocSudocFranceF