An Iterative Algebraic Geometric Approach for Identification of Switched ARX Models with Noise

The algebraic geometric (AG) approach has been used to identify switched auto regressive exogenous (SARX) models in hybrid systems, and it has several advantages over other SARX identification methods. This paper is focused on improving the estimation accuracy of the AG approach for systems corrupted with indispensable noises. A stochastic hybrid decoupling polynomial (SHDP) is constructed by reformulating the hybrid decoupling polynomial (HDP) used in the original AG method. An iterative scheme is developed to estimate parameters of the SHDP, which are used to calculate the SARX model parameters. This estimation involves linear regression with multiplicative noises, therefore a novel approach is proposed to solve this regression problem. Then, the parameters are recovered from the SHDP. Finally, all these steps for SARX model identification are summarized in an algorithm called the iterative algebraic geometric (IAG) approach. Simulations and experimental validation results are shown to demonstrate the effectiveness of and the improvement made by the proposed IAG method.     

Elastic caching solutions for content dissemination services of ip-based internet technologies prospective

Multimedia Tools and Applications - The Information-Centric Networking (ICN) provides a new data dissemination Internet paradigm to support the communication services that will meet the...     

A networking laboratory for the developing world

Internet-based communication is assuming an increasingly important role in the developing world. It is thus crucial that students be exposed to contemporary networking equipment in a realistic setting, in order to connect theoretical material taught in lecture courses with the realities of physical hardware. To this end, a large computer networking laboratory has been set up to provide a realistic environment for teaching internetworking concepts. This laboratory provides university-level students with a testbed to experiment with fundamental issues of internetworking in a way that cannot be provided by simulators and to a degree of rigor not possible with the commonly available laboratory setups designed for technicians. We describe the motivations for setting up the laboratory, its network structure and equipment, and the type of experiments students conduct. The laboratory structure is influenced heavily by the limited funds at our disposal - a common problem in the developing world. Many of the problems we faced in setting up our equipment (such as the crucial impact of proper electrical grounding on system performance) are not ordinarily encountered in developed nations. Our experiences are thus likely to be of value to others in the developing world who are contemplating setting up experimental facilities for teaching networking.     

Online 3-D tracking of suspension living cells imaged with phase-contrast microscopy

Neural stem cells/neural progenitors (NSCs/NPs) are cells that give rise to the main cell types of the nervous system: oligodendrocytes, neurons, and astrocytes. Studying NSCs/NPs with time-lapse microscopy is critical to the understanding of the biology of these cells. However, NSCs/NPs are very sensitive to phototoxic damage, and therefore, fluorescent dyes cannot be used to follow these cells. Also, since in most of NSC/NP-related experiments, a large number of cells neesd to be monitored. Consequently, the acquisition of a huge amount of images is required. An additional difficulty is related to our original suspension living, tracking objective, behavior much closer to the natural, in vivo, way of development of the cells. Indeed, unlike adherent cells, suspension cells float freely in a liquid solution, thus, making their dynamics very different from that of adherent cells. As a result, existing visual tracking algorithms that have primarily been developed to track adherent cells are no longer adequate to tackle living cells in suspension. This paper presents a novel automated 3-D visual tracking of suspension living cells for time-lapse image acquisition using phase-contrast microscopy. This new tracking method can potentially strongly impact on current 3-D video microscopy methods, paving the way for innovative analysis of NSCs/NPs and as a result, on the study of neurodegenerative diseases.     

Development of paracetamol-caffeine co-crystals to improve compressional,formulation and in vivo performance

Paracetamol, a frequently used antipyretic and analgesic drug, has poor compression moldability owing to its low plasticity. In this study, new co-crystals of paracetamol (PCM) with caffeine (as a co-former) were prepared and delineated. Co-crystals exhibited improved compaction and mechanical behavior. A screening study was performed by utilizing a number of methods namely dry grinding, liquid assisted grinding (LAG), solvent evaporation (SE), and anti-solvent addition using various weight ratios of starting materials. LAG and SE were found successful in the screening study. Powders at 1:1 and 2:1 weight ratio of PCM/CAF by LAG and SE, respectively, resulted in the formation of co-crystals. Samples were characterized by PXRD, DSC, and ATR-FTIR techniques. Compressional properties of PCM and developed co-crystals were analyzed by in-die heckle model. Mean yield pressure (Py), an inverse measure of plasticity, obtained from the heckle plots decreased significantly (p?In vitro dissolution studies on tablets also showed enhanced dissolution profiles (～90–97%) in comparison to the tablets of PCM prepared by direct compression (～55%) and wet granulation (～85%) methods. In a single dose sheep model study, co-crystals showed up to twofold increase in AUC and C_max. A significant (p?in vitro and in vivo profile. Enhancement in AUC and C_max of PCM by co-crystallization might suggest the dose reduction and avoidance of side effects.     

Machine learning and directional switching median-based filter for highly corrupted images

In this paper, two-stage machine learning-based noise detection scheme has been proposed for identification of salt-and- pepper impulse noise which gives excellent detection results for highly corrupted images. In the first stage, a window of size $3\times 3$ is taken from image and some other features of this window are used as input to neural network. This scheme has distinction of having very low missed detection (MD) and false positives rates. In the second stage, decision tree-based algorithm (J48) is applied on some well-known statistical parameters to generate rules for noise detection. These noise detection methods give promising results for identification of noise from highly corrupted images. A modified version of switching median filter (directional weighted switching median filter) is proposed for noise removal. Performance of noise detector is measured using MD and false alarm FA. Filtering results are compared with state-of-the-art noise removal techniques in terms of peak signal-to-noise ratio and structural similarity index measure. Extensive experiments are performed to show that the proposed technique gives better results than state-of-the-art noise detection and filtering methods.     

Dynamic integral sliding mode for MIMO uncertain nonlinear systems

In this paper the authors propose a novel sliding mode control methodology for Multi-Input and Multi-Output (MIMO) uncertain nonlinear systems. The proposed approach synthesizes dynamic sliding mode and integral sliding mode control strategies into dynamic integral sliding mode. The new control laws establish sliding mode without reaching phase with the use of an integral sliding manifold. Consequently, robustness against uncertainties increases from the very beginning of the process. Furthermore, the control laws considerably alleviate chattering along the switching manifold. In addition, the performance of the controller boost up in the presence of uncertainties. A comprehensive comparative analysis carried out with dynamic sliding mode control and integral sliding mode control demonstrates superiority of the newly designed control law. A chatter free regulation control of two uncertain nonlinear systems with improved performance in the presence of uncertainties ensures the robustness of the proposed dynamic integral sliding mode controller.     

The impact of team task and job engagement on the transfer of tacit knowledge in e-business virtual teams

This research focuses on the initiative to integrate team task and job engagement as related to the transfer of tacit knowledge. The aim of this study is to investigate if team task and job involvement enhances the overall work efficiency through transfer of tacit knowledge between e-business virtual teams. We develop a model that is based on the relationship between tacit degree of knowledge, job engagement, team tasks, and their effect on knowledge transfer. The conceptual model is validated with the data collected from a survey. The results indicate that the tacit knowledge does not have a positive effect on team tasks and job engagement, and the team tasks and job engagement have a significant positive effect on knowledge transfer. In addition, the study found that team tasks and job engagement have mediating effects in the process of tacit knowledge transfer. Also, we discuss the theoretical and practical implications and contributions of this study.     

Survivability of probiotics encapsulated in alginate gel microbeads using a novel impinging aerosols method

Encapsulation of probiotic bacteria in cross-linked alginate beads is of major interest for improving the survivability in harsh acid and bile environment and also in food matrices. Alginate micro beads (10-40 μm) containing the probiotics Lactobacillus rhamnosus GG and Lactobacillus acidophilus NCFM were produced by a novel technique based on dual aerosols of alginate solution and CaCl₂ cross linking solution. Extruded macro beads (approximately 2 mm diameter) produced by the conventional method and micro beads produced by novel aerosols technique offered comparable protection to L. rhamnosus in high acid and bile environment. Chitosan coating of micro beads resulted in a significant increase in survival time of L. rhamnosus from 40 to 120 min in acid condition and the reduction in cell numbers was confined to 0.94 log over this time. Alginate macro beads are more effective than micro beads in protecting L. acidophilus against high acid and bile. Chitosan coating of micro beads resulted in similar protection to L. acidophilus in macro beads in acid and extended the survival time from 90 to at least 120 min. Viability of this organism in micro beads was 3.5 log after 120 min. The continuous processing capability and scale-up potential of the dual aerosol technique offers potential for an efficient encapsulation of probiotics in very small alginate micro beads below sensorial detection limits while still being able to confer effective protection in acid and bile environment.