Adaptive Measurement-Based Policy-Driven QoS Management with Fuzzy-Rule-based Resource Allocation

Fixed and wireless networks are increasingly converging towards common connectivity with IP-based core networks. Providing effective end-to-end resource and QoS management in such complex heterogeneous converged network scenarios requires unified, adaptive and scalable solutions to integrate and co-ordinate diverse QoS mechanisms of different access technologies with IP-based QoS. Policy-Based Network Management (PBNM) is one approach that could be employed to address this challenge. Hence, a policy-based framework for end-to-end QoS management in converged networks, CNQF (Converged Networks QoS Management Framework) has been proposed within our project. In this paper, the CNQF architecture, a Java implementation of its prototype and experimental validation of key elements are discussed. We then present a fuzzy-based CNQF resource management approach and study the performance of our implementation with real traffic flows on an experimental testbed. The results demonstrate the efficacy of our resource-adaptive approach for practical PBNM systems

PtRuO/Ti anodes with a varying Pt:Ru ratio for direct methanol fuel cells

PtRuO/Ti anodes with a varying Pt:Ru ratio were prepared by thermal deposition of a PtRuO catalyst layer onto a Ti mesh for the direct methanol fuel cell (DMFC). The morphology and structure of the catalyst layers were analyzed by SEM, EDX, and XRD. The catalyst coating layers became porous with increase of the Ru content, and showed oxide and alloy characteristics. The relative activities of the PtRuO/Ti electrodes were assessed and compared using half-cell tests and single DMFC experiments. The results showed that these electrodes were very active for the methanol oxidation and that the optimum Ru surface coverage was ca. 38% for a DMFC operating at 20-60 °C. © 2006 Elsevier B.V. All rights reserved.

PtRu/Ti anodes with varying Pt:Ru ratio prepared by electrodeposition for the direct methanol fuel cell

PtRu/Ti anodes with varying Pt : Ru ratio were prepared by electrodeposition of a thin PtRu catalyst layer onto Ti mesh for a direct methanol fuel cell (DMFC). The morphology and structure of the catalyst layers were analyzed by SEM, EDX and XRD. The catalyst coating layer shows an alloy character. The relative activities of the PtRu/Ti electrodes were assessed and compared in half cell and single DMFC experiments. The results show that these electrodes are very active for the methanol oxidation and that the optimum Ru surface coverage was ca. 9 at.% for DMFC operating at 20°C and 11 at.% at 60°C. The PtRu/Ti anode shows a performance comparable to that of the conventional carbon-based anode in a DMFC operating with 0.25 M or 0.5 M methanol solution and atmosphere oxygen gas at 90°C. © the Owner Societies 2006.

Determination of geographical origin of distillers dried grains and solubles using isotope ratio mass spectrometry

In recent years distillers dried grains and solubles (DDGS), co-products of the bio-ethanol and beverages industries, have become globally traded commodity for the animal feed sector. As such it is becoming increasingly important to be able to trace the geographical origin of commodities in case of a contamination incident or authenticity issue arise. In this study, 137 DDGS samples from a range of different geographical origins (China, USA, Canada and European Union) were collected and analyzed. Isotope ratio mass spectrometry (IRMS) was used to analyze the DDGS for ²H/¹H, ¹³C/¹²C, ¹⁵N/¹⁴N, ¹⁸O/¹⁶O and ³⁴S/³²S isotope ratios which can vary depending on geographical origin and processing. Univariate and multivariate statistical techniques were employed to investigate the feasibility of using the IRMS data to determine botanical and geographical origin of the DDGS. The results indicated that this commodity could be differentiated according to their place of origin by the analysis of stable isotopes of hydrogen, carbon, nitrogen and oxygen but not with sulfur. By adding data to the models produced in this study, potentially an isotope databank could be set up for traceability procedures for DDGS, similar to the one established already for wine which will help in feed and food security issues arising worldwide.

Parental leave regulations and the persistence of the male breadwinner model: Using fuzzy-set ideal type analysis to assess gender equality in an enlarged Europe

his paper uses fuzzy-set ideal type analysis to assess the conformity of European leave regulations to four theoretical ideal typical divisions of labour: male breadwinner, caregiver parity, universal breadwinner and universal caregiver. In contrast to the majority of previous studies, the focus of this analysis is on the extent to which leave regulations promote gender equality in the family and the transformation of traditional gender roles. The results of this analysis demonstrate that European countries cluster into five models that only partly coincide with countries’ geographical proximity. Second, none of the countries considered constitutes a universal caregiver model, while the male breadwinner ideal continues to provide the normative reference point for parental leave regulations in a large number of European states. Finally, we witness a growing emphasis at the national and EU levels concerning the universal breadwinner ideal, which leaves gender inequality in unpaid work unproblematized.

The effect of variability in the powder/liquid ratio on the strength of zinc phosphate cement

Aim. To investigate (a) variability in powder/liquid proportioning and (b) effect of variability on diametral tensile strength (DTS), in a zinc phosphate cement. Statistical analyses (α = 0.05) were by Student's t-test in the case of powder/liquid ratio and one-way ANOVA and Tukey HSD for pair-wise comparisons of mean DTS. The Null hypotheses were that (a) the powder-liquid mixing ratios would not differ from the manufacturer's recommended ratio (b) DTS of the set cement samples using the extreme powder/liquid ratios would not differ from those made using the recommended ratio. 

Methodology. 34 dental students dispensed the components according to the manufacturer's instructions. The maximum and minimum powder/liquid ratios, together with the manufacturer's recommended ratio, were used to prepare samples for DTS testing. 

Results. Powder/liquid ratios ranged from 2.386 to 1.018. The mean ratio (1.644) was not significantly different from the recommended value of 1.718 (P = 0.189). DTS values for the maximum and minimum ratios were both significantly different from each other (P < 0.001) and from the mean value obtained from the recommended ratio (P < 0.001). 

Conclusions. Variability exists in powder/liquid ratio for hand dispensed zinc phosphate cement. This variability can affect the DTS of the set material.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.