Dynamic content-page identification for media-rich websites

Knowledge of the information goal of users is critical in website design, analyzing the efficacy of such designs, and in ensuring effective user-access to desired information. Determining the information goal is complex due to the subjective and latent nature of user information needs. This challenge is further exacerbated in media-rich websites since the semantics of media-based information is context-based and emergent. A critical step in determining information goals lies in the identification of content pages. These are the pages which contain the information the user seeks. We propose a method to automatically determine the content pages by taking into account the organization of the web site, the media-based information content, as well as the influence of a specific user browsing pattern. Given a specific browsing pattern, in our method, putative content pages are identified as the pages corresponding to the local minima of page-content entropy values. For an (unknown) user information goal this intuitively corresponds to modeling the progressive transition of the user from pages with generic information to those with specific information. Experimental investigations on media rich sites demonstrate the effectiveness of the technique and underline its potential in modeling user information needs and actions in a media-rich web.     

Globally Exponential Stability for Delayed Neural Networks Under Impulsive Control

In this paper, the dynamic behaviors of a class of neural networks with time-varying delays are investigated. Some less weak sufficient conditions based on p-norm and ∞-norm are obtained to guarantee the existence, uniqueness of the equilibrium point for the addressed neural networks without impulsive control by applying homeomorphism theory. And then, by utilizing inequality technique, Lyapunov functional method and the analysis method, some new and useful criteria of the globally exponential stability with respect to the equilibrium point under impulsive control we assumed are derived based on p-norm and ∞-norm, respectively. Finally, an example with simulation is given to show the effectiveness of the obtained results.     

Fundamental dynamics of flow through carbon nanotube membranes

The flow of a model non-polar liquid through small carbon nanotubes is studied using non-equilibrium molecular dynamics simulation. We explain how a membrane of small-diameter nanotubes can transport this liquid faster than a membrane consisting of larger-diameter nanotubes. This effect is shown to be back-pressure dependent, and the reasons for this are explored. The flow through the very smallest nanotubes is shown to depend strongly on the depth of the potential inside, suggesting atomic separation can be based on carbon interaction strength as well as physical size. Finally, we demonstrate how increasing the back-pressure can counter-intuitively result in lower exit velocities from a nanotube. Such studies are crucial for optimisation of nanotube membranes.     

A robust motion estimation with center-biased diamond search and its parallel architecture for motion-compensated de-interlace

For motion compensated de-interlace, the accuracy and reliability of the motion vectors have a significant impact on the performance of the motion compensated interpolation. In order to improve the robustness of motion vector, a novel motion estimation algorithm with center-biased diamond search and its parallel VLSI architecture are proposed in this paper. Experiments show that it works better than conventional motion estimation algorithms in terms of motion compensation error and robustness, and its architecture overcomes the irregular data flow and achieves high efficiency. It also efficiently reuses data and reduces the control overhead. So, it is highly suitable for HDTV applications.     

Autonomous topological modeling of a home environment and topological localization using a sonar grid map

This paper presents a method of autonomous topological modeling and localization in a home environment using only low-cost sonar sensors. The topological model is extracted from a grid map using cell decomposition and normalized graph cut. The autonomous topological modeling involves the incremental extraction of a subregion without predefining the number of subregions. A method of topological localization based on this topological model is proposed wherein a current local grid map is compared with the original grid map. The localization is accomplished by obtaining a node probability from a relative motion model and rotational invariant grid-map matching. The proposed method extracts a well-structured topological model of the environment, and the localization provides reliable node probability even when presented with sparse and uncertain sonar data. Experimental results demonstrate the performance of the proposed topological modeling and localization in a real home environment.     

Piecewise Pseudo-Maximum Likelihood Estimation for Risk Aversion Case in First-Price Sealed-Bid Auction

In the literature, more and more clues show that the bidders indeed tend to risk averse. But as a good structure estimation procedure in first-price sealed-bid auctions, the traditional PPMLE (Piecewise Pseudo-Maximum Likelihood Estimation) approach is only applicable to the risk neutrality case. This study generalizes this approach to the risk aversion case, and obtains a simple estimation procedure for the Pareto family of private costs. In the procedure, the estimation order of distribution parameters of private costs is not important, which is different from the traditional PPMLE method. Though there is no unique estimator for θ ₁ and γ, some guidance is given for real-world applications on the basis of our Monte Carlo simulation experiments. What’s more, this procedure can be reduced further, if one is only interested in estimating the private costs. Extensive simulation experimental results indicate that our approach outperforms or matches at least the traditional one in the case of risk neutrality, and is applicable to the risk aversion case.     

Gender differences in digital music distribution methods

This study examines gender differences among Greek Internet users in using digital music distribution methods. First, a Web-based questionnaire was developed and placed on most popular Greek forums. Then, 300 Greek Internet users stated their opinions regarding digital music and the following downloading methods: 1) Http downloading, 2) P2P downloading, 3) Torrent downloading, and 4) Combined iTunes method. The results revealed that P2P programs are the first choice for downloading mp3. The responders were satisfied with the P2P’s easiness of use, the variety of songs and the no need to pay. However, they worried about P2P’s safety. Gender differences were identified in several areas. Music industry managers could consider these findings in their strategies to reach the consumers. Advertising companies could use the results to target differently male or female consumers.     

Model predictive control for systems with stochastic multiplicative uncertainty and probabilistic constraints

Robust predictive control handles constrained systems that are subject to stochastic uncertainty but propagating the effects of uncertainty over a prediction horizon can be computationally expensive and conservative. This paper overcomes these issues through an augmented autonomous prediction formulation, and provides a method of handling probabilistic constraints and ensuring closed loop stability through the use of an extension of the concept of invariance, namely invariance with probability p.