Joint assessment of Network- and Perceived-QoS in video delivery networks

Given the increasing number of IP streaming video customers, service providers are seeking an efficient way to monitor in real time the offered quality of service, as perceived by each end user. Since real-time video quality assessment via image processing algorithms is quite bandwidth- and processing-power-demanding, a feasible alternative could be to monitor the Network-level Quality of Service (NQoS) and associate it with the Perceived QoS (PQoS). This article presents a network-agnostic framework for the joint assessment of N- and P-QoS, with the aim of correlating these two parameters for a specific network and service configuration. This framework/architecture is implemented with open source software tools and is being demonstrated in an actual WiMAX streaming video distribution platform.     

Modeling scale formation in flat‐sheet membrane modules during water desalination

Modeling the operation of spiral‐wound membrane modules is essential for their successful design and optimization. Such models must include the main types of membrane fouling, degrading desalination plant performance, including scaling due to sparingly soluble salts. Unfortunately, the complexity of underlying physicochemical processes and the coexistence of several spatial and temporal scales render intractable modeling of membrane scaling based on first principles. Therefore, a suitable (albeit simplified) framework is developed for incorporating scaling dynamics into a fluid flow model formulated at an intermediate (i.e., mesoscopic) length scale of membrane operation. The general mesoscopic approach involves integration of spatially distributed submodels, thereby allowing predictions at the large (entire membrane sheet) scale; these submodels comprise constitutive laws and kinetic rate expressions derived at fine scales. A submodel for the effect of pre‐existing bulk particles on scale formation is developed herein. Several numerical results are presented to exemplify the potential of the proposed framework. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2917–2927, 2013     

Experimental and Modeling Study on Zeolite Catalysts for Diesel Engines

The work presented in this paper was aimed at detecting, understanding and modeling some critical behavior aspects of zeolite-containing diesel catalysts. An already available mathematical model for precious metal catalysts was used as a starting point. A specially designed set of experiments provided the information needed to improve certain modeling features. New submodels were introduced to account for hydrocarbon and H₂O adsorption, as well as diffusion limitations in the zeolite. The effect of flow maldistribution during real world operation was investigated experimentally and computationally. Although a number of issues (especially regarding the DeNOx mechanisms) are not yet fully resolved, significant progress was achieved as regards the understanding and computational prediction of diesel catalyst operation.     

Separation of tungstates from aqueous mixtures containing impurities (arsenate,phosphate and silicate anions) using ion flotation

Ion flotation, using dodecylamine as surfactant and magnesium ions as depressant agents, was found to be an effective method for the selective separation and recovery of tungstate from arsenate anions in dilute aqueous solutions. Arsenates represent the main impurity in tungsten-containing waste waters or leaching solutions of hydrometallurgical origin; magnesium chloride is a relatively common precipitant, used in tungsten hydrometallurgy. The main parameters affecting this process were investigated, namely concentrations of reagents (Mg²⁺ ions, dodecylamine, arsenate and tungstate), solution pH, co-existence and effective separation from other impurities, such as phosphate and/or silicate anions, and the effectiveness of the separation process in solutions of high ionic strength (using NaCl and Na₂SO₄ salts). It was found that at pH range between 2 and 5, tungstate anions can be quantitatively recovered from aqueous mixtures containing arsenates, phosphates and silicates, while the co-removal of the impurities was below 20%.     

Long‐term development of thermophysical and mechanical properties of cold‐curing structural adhesives due to post‐curing

The long‐term changes in the thermophysical and mechanical properties of a cold‐curing structural epoxy adhesive were investigated by accelerating the curing reaction by post‐curing at elevated temperatures. Experimental data concerning the glass transition temperature for periods of up to 7 years and tensile strength and stiffness measurements could be extrapolated for a period of up to 17 years. An existing model for the long‐term development of concrete properties was modified for the prediction of the long‐term mechanical properties of adhesives. The applicability of the acceleration procedure and the new model was confirmed by several verification procedures. Structural adhesives exhibit significant increases in glass transition temperature, strength and stiffness over the long term provided that joints are adequately sealed and protected from humidity and UV radiation. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Polymers in mixed solvents: application of the new representation of viscosity data as a function of molecular weight

The relation proposed between the intrinsic viscosity and the molecular weight of a polymer^1,2 (1/[η]versus 1/M^1/2), has been applied in this paper in cases when the polymer is dissolved in a binary solvent mixture. We have then shown that even in this case we can calculate in a very accurate way the molecular weight of the polymer from its intrinsic viscosity, especially in the molecular weight range where the Mark-Houwink-Sakurada equation is the least applicable (M_w < 150 000).     

The design and evaluation of a computerized adaptive test on mobile devices

The use of computerized adaptive testing (CAT) has expanded rapidly over recent years mainly due to the advances in communication and information technology. Availability of advanced mobile technologies provides several benefits to e-learning by creating an additional channel of access with mobile devices such as PDAs and mobile phones. This paper describes the design issues that were considered for the development and the implementation of a CAT on mobile devices, the computerized adaptive test on mobile devices (CAT-MD). Throughout the development of the system, formative evaluation was an integral part of the design methodology. The recommendations, suggestions and the results of the formative evaluation were used to improve the system in order to make the assessment procedure more effective and efficient. These results of the formative evaluation are also presented here.     

Studies on the roles and identification of the small molecule factors on phenolase activation in Norway lobster (Nephrops norvegiens)

The direct effect of small molecule factor(s) on the activation of phenolase in the suggested multiple component process of blackspot development in Norway lobster (Nephrops norvegicus) was studied.

When acetone-precipitated phenolase was treated with the small molecule filtrate, the phenolase activation profile was lower compared to the control, particularly at pH 6.7. However, when purified form I phenolase was treated with small molecule filtrate no activation was observed, the assayed phenolase activity being constant but lower than the control. A similar effect was observed when form I phenolase was treated with 1.5 mM dihydroxyphenylalanine (DOPA) (approximately the concentration found in the small molecule filtrate), indicating that this lower pattern resulted from the competition of the phenolase substrates (catechol, DOPA, and possibly tyrosine) in the small molecule filtrate. When the activity of the three proteases in the acetone-precipitated phenolase was studied, it was found that there was a high recovery of proteases I and II in the precipitate but little protease III. This also confirms that the effect of the small molecule filtrate on phenolase activity in acetone-precipitated phenolase was due to its indirect effect on the proteases present.

The modification of the compounds that absorb at 270 nm was studied by a high-performance liquid chromatographic (HPLC) separation method and the quantitative analysis of tyrosine and DOPA in the small molecule filtrate was achieved. Some of the small molecules were identified, by an HPLC method, as tyrosine, DOPA, oxidised DOPA, vitamin C in oxidised form or breakdown product of vitamin C. Oxidised DOPA, DOPA, tyrosine and N-acetyldopamine inhibit the proteases to varying degrees. Vitamin C also inhibits all three proteases at pH 6.4; however, at pH 8.2 it markedly activates protease III and slightly activates the two thiol proteases (I and II).     

Generalized Radial Basis Function Networks Trained with Instance Based Learning for Data Mining of Symbolic Data

The application of the Radial Basis Function neural networks in domains involving prediction and classification of symbolic data requires a reconsideration and a careful definition of the concept of distance between patterns. This distance in addition to providing information about the proximity of patterns should also obey some mathematical criteria in order to be applicable. Traditional distances are inadequate to access the differences between symbolic patterns. This work proposes the utilization of a statistically extracted distance measure for Generalized Radial Basis Function (GRBF) networks. The main properties of these networks are retained in the new metric space. Especially, their regularization potential can be realized with this type of distance. However, the examples of the training set for applications involving symbolic patterns are not all of the same importance and reliability. Therefore, the construction of effective decision boundaries should consider the numerous exceptions to the general motifs of classification that are frequently encountered in data mining applications. The paper supports that heuristic Instance Based Learning (IBL) training approaches can uncover information within the uneven structure of the training set. This information is exploited for the estimation of an adequate subset of the training patterns serving as RBF centers and for the estimation of effective parameter settings for those centers. The IBL learning steps are applicable to both the traditional and the statistical distance metric spaces and improve significantly the performance in both cases. The obtained results with this two-level learning method are significantly better than the traditional nearest neighbour schemes in many data mining problems.     

The effect of emotional feedback on behavioral intention to use computer based assessment

This study introduces emotional feedback as a construct in an acceptance model. It explores the effect of emotional feedback on behavioral intention to use Computer Based Assessment (CBA). A female Embodied Conversational Agent (ECA) with empathetic encouragement behavior was displayed as emotional feedback. More specifically, this research aims at investigating the effect of Emotional Feedback on Behavioral Intention to Use a CBA system, Perceived Playfulness, Perceived Usefulness, Perceived Ease of Use, Content and Facilitating Conditions. An appropriate survey questionnaire was completed by 134 students. Results demonstrate that Emotional Feedback has a direct effect on Behavioral Intention to Use a CBA system and on other crucial determinants of Behavioral Intention. Finally, the proposed acceptance model for computer based assessment extended with the Emotional Feedback variable explains approximately 52% of the variance of Behavioral Intention.