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Web search query logs contain valuable information which can be utilized for personalization and improvement of search engine performance. The aim in this paper 1 is to cluster users based on their interests, and analyze the temporal dynamics of these clusters. In the proposed approach, we first apply clustering techniques to group similar users with respect to their web searches. Anticipating that the small number of query terms used in search queries would not be sufficient to obtain a proper clustering scheme, we extracted the summary content of the clicked web page from the query log. In this way, we enriched the feature set more efficiently than the content crawling. We also provide preliminary survey results to evaluate clusters. Clusters may change with the user flow from one cluster to the other as time passes. This is due to the fact that users' interests may shift over time. We used statistical methods for the analysis of temporal changes in users' interests. As a case study, we experimented on the query logs of a search engine.

Proteins are large molecules that are vital for all living organisms and they are essential components of many industrial products. The process of binding a protein to another is called protein-protein docking. Many automated algorithms have been proposed to find docking configurations that might yield promising protein-protein complexes. However, these automated methods are likely to come up with false positives and have high computational costs. Consequently, Virtual Reality has been used to take advantage of user's experience on the problem; and proposed applications can be further improved. Haptic devices have been used for molecular docking problems; but they are inappropriate for protein-protein docking due to their workspace limitations. Instead of haptic rendering of forces, we provide a novel visual feedback for simulating physicochemical forces of proteins. We propose an interactive 3D application, DockPro, which enables domain experts to come up with dockings of protein-protein couples by using magnetic trackers and gloves in front of a large display.

We propose a new method based on the use of fractional differentiation for improving the efficiency and realism of simulations based on smoothed particle hydrodynamics (SPH). SPH represents a popular particle‐based approach for fluid simulation and a high number of particles is typically needed for achieving high quality results. However, as the number of simulated particles increase, the speed of computation degrades accordingly. The proposed method employs fractional differentiation to improve the results obtained with SPH in a given resolution. The approach is based on the observation that effects requiring a high number of particles are most often produced from colliding flows, and therefore, when the modeling of this behavior is improved, higher quality results can be achieved without changing the number of particles being simulated. Our method can be employed to reduce the resolution without significant loss of quality, or to improve the quality of the simulation in the current chosen resolution. The advantages of our method are demonstrated with several quantitative evaluations. Copyright © 2013 John Wiley & Sons, Ltd.

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