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.

A Secretory Leukocyte Protease Inhibitor Variant with Improved Activity against Lung Infection

Secretory leukocyte protease inhibitor (SLPI) is an important respiratory tract host defense protein, which is proteolytically inactivated by excessive neutrophil elastase (NE) during chronic Pseudomonas infection in the cystic fibrosis (CF) lung. We generated two putative NE-resistant variants of SLPI by site-directed mutagenesis, SLPI-A16G and SLPI-S15G-A16G, with a view to improving SLPI’s proteolytic stability. Both variants showed enhanced resistance to degradation in the presence of excess NE as well as CF patient sputum compared with SLPI-wild type (SLPI-WT). The ability of both variants to bind bacterial lipopolysaccharides and interact with nuclear factor-κB DNA binding sites was also preserved. Finally, we demonstrate increased anti-inflammatory activity of the SLPI-A16G protein compared with SLPI-WT in a murine model of pulmonary Pseudomonas infection. This study demonstrates the increased stability of these SLPI variants compared with SLPI-WT and their therapeutic potential as a putative anti-inflammatory treatment for CF lung disease.

Demand response to improved walking infrastructure: A study into the economics of walking and health behaviour change

Walking is the most common form of moderate‐intensity physical activity among adults, is widely accessible and especially appealing to obese people. Most often policy makers are interested in valuing the effect on walking of changes in some characteristics of a neighbourhood, the demand response for walking, of infrastructure changes. A positive demand response to improvements in the walking environment could help meet the public health target of 150 minutes of at least moderate‐intensity physical activity per week. We model walking in an individual’s local neighbourhood as a ‘weak complement’ to the characteristics of the neighbourhood itself. Walking is affected by neighbourhood
characteristics, substitutes, and individual’s characteristics, including their opportunity cost of time.  Using compensating variation, we assess the economic benefits of walking and how walking behaviour is affected by improvements to the neighbourhood.  Using a sample of 1,209 respondents surveyed over a 12 month period (Feb 2010‐Jan 2011) in East Belfast, United Kingdom, we find that a policy that increased walkability and people’s perception of access to shops and facilities  would lead to an increase in walking of about 36 minutes/person/week, valued at £13.65/person/week. When focusing on inactive residents, a policy that improved the walkability of the area would lead to guidelines for physical activity being reached by only 12.8% of the population who are currently inactive. Additional interventions would therefore be needed to encourage inactive residents to
achieve the recommended levels of physical activity, as it appears that interventions that improve the walkability of an area are particularly effective in increasing walking among already active citizens, and, among the inactive ones, the best response is found among healthier, younger and wealthier citizens.

Material Identification of Loose Particles in Sealed Electronic Devices Using PCA and SVM

The existence of loose particles left inside the sealed electronic devices is one of the main factors affecting the reliability of the whole system. It is important to identify the particle material for analyzing their source. The conventional material identification algorithms mainly rely on time, frequency and wavelet domain features. However, these features are usually overlapped and redundant, resulting in unsatisfactory material identification accuracy. The main objective of this paper is to improve the accuracy of material identification. First, the principal component analysis (PCA) is employed to reselect the nine features extracted from time and frequency domains, leading to six less correlated principal components. And then the reselected principal components are used for material identification using a support vector machine (SVM). Finally, the experimental results show that this new method can effectively distinguish the type of materials including wire, aluminum and tin particles.

An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.

Experimental and Numerical Benchmarking of an Improved Impeller Meanline Modelling Method for Automotive Turbocharger Centrifugal Compressors

After the development of a new single-zone meanline modelling technique, benchmarking of the technique and the modelling methods used during its development are presented. The new meanline model had been developed using the results of three automotive turbocharger centrifugal compressors, and single passage CFD models based on their geometry.

The target of the current study was to test the new meanline modelling method on two new centrifugal compressor stages, again from the automotive turbocharger variety. Furthermore the single passage CFD modelling method used in the previous study would be again employed here and also benchmarked.

The benchmarking was twofold; firstly test the overall performance prediction accuracy of the single-zone meanline model. Secondly, test the detailed performance estimation of the CFD model using detailed interstage static pressure tappings.

The final component of this study exposed the weaknesses in the current modelling methods used (explicitly during this study). The non-axisymmetric flow field at the leading and trailing edges for the two compressors was measured and is presented here for the complete compressor map, highlighting the distortion relative to the tongue.

Improved model for interfacial stresses accounting for the effect of shear deformation in plated beams

A significant increase in strength and performance of reinforced concrete, timber and metal beams may be achieved by adhesively bonding a fibre reinforced polymer composite, or metallic such as steel plate to the tension face of a beam. One of the major failure modes in these plated beams is the debonding of the plate from the original beam in a brittle manner. This is commonly attributed to the interfacial stresses between the adherends whose quantification has led to the development of many analytical solutions over the last two decades. The adherends are subjected to axial, bending and shear deformations. However, most analytical solutions have neglected the effect of shear deformation in adherends. Few solutions consider this effect approximately but are limited to one or two specific loading conditions. This paper presents a more rigorous solution for interfacial stresses in plated beams under an arbitrary loading with the shear deformation of the adherends duly considered in closed form using Timoshenko’s beam theory. The solution is general to linear elastic analysis of prismatic beams of arbitrary cross section under arbitrary loading with a plate of any thickness bonded either symmetrically or asymmetrically with respect to the span of the beam.

Towards an Improved Phasor Measurement Unit Data Communications Framework

This paper discusses a proposed new communications framework for phasor measurement units (PMU) optimized for use on wide area networks. Traditional PMU telecoms have been optimized for use in environments where bandwidth is restricted. The new method takes the reliability of the telecommunications medium into account and provides guaranteed delivery of data whilst optimizing for realtime delivery of the most current data. Other important aspects, such as security, are also considered.

Accumulating research: a systematic account of how cumulative meta-analyses would have provided knowledge, improved health, reduced harm and saved resources

BACKGROUND: "Cumulative meta-analysis" describes a statistical procedure to calculate, retrospectively, summary estimates from the results of similar trials every time the results of a further trial in the series had become available. In the early 1990 s, comparisons of cumulative meta-analyses of treatments for myocardial infarction with advice promulgated through medical textbooks showed that research had continued long after robust estimates of treatment effects had accumulated, and that medical textbooks had overlooked strong, existing evidence from trials. Cumulative meta-analyses have subsequently been used to assess what could have been known had new studies been informed by systematic reviews of relevant existing evidence and how waste might have been reduced.

METHODS AND FINDINGS: We used a systematic approach to identify and summarise the findings of cumulative meta-analyses of studies of the effects of clinical interventions, published from 1992 to 2012. Searches were done of PubMed, MEDLINE, EMBASE, the Cochrane Methodology Register and Science Citation Index. A total of 50 eligible reports were identified, including more than 1,500 cumulative meta-analyses. A variety of themes are illustrated with specific examples. The studies showed that initially positive results became null or negative in meta-analyses as more trials were done; that early null or negative results were over-turned; that stable results (beneficial, harmful and neutral) would have been seen had a meta-analysis been done before the new trial; and that additional trials had been much too small to resolve the remaining uncertainties.

CONCLUSIONS: This large, unique collection of cumulative meta-analyses highlights how a review of the existing evidence might have helped researchers, practitioners, patients and funders make more informed decisions and choices about new trials over decades of research. This would have led to earlier uptake of effective interventions in practice, less exposure of trial participants to less effective treatments, and reduced waste resulting from unjustified research.

Improved shear strength model for FRP-strengthened RC beams accounting for adverse FRP-steel interaction

RC beams shear-strengthened with externally-bonded FRP side strips or U-strips usually fail by debonding. As such debonding occurs in a brittle manner at relatively small shear crack widths, some of the internal steel stirrups may not have reached yielding at beam shear failure. Consequently, the internal steel stirrups cannot be fully utilized. This adverse shear interaction between internal steel stirrups and external FRP strips may significantly reduce the benefit of shear-strengthening FRP but has not been considered by any of the existing FRP strengthening design guidelines. In this paper, an improved shear strength model capable of accounting for the effect of the above shear interaction is first presented, in which the unfavorable effect of shear interaction is reflected through a reduction factor (i.e. shear interaction factor). Using a large test database established in the present study, the performance of the proposed model as well as that of three other shear strength models is then assessed. This assessment shows that the proposed shear strength model performs better than the three existing models. The assessment also shows that the inclusion of the proposed shear interaction factor in the existing models can significantly improve their performance.

Improved Efficiency for Partial Oxidation of Methane by Controlled Copper Deposition on Surface-Modified ZSM-5

The mono(μ-oxo) dicopper cores present in the pores of Cu-ZSM-5 are active for the partial oxidation of methane to methanol. However, copper on the external surface reduces the ratio of active, selective sites to unselective sites. More efficient catalysts are obtained by controlling the copper deposition during synthesis. Herein, the external exchange sites of ZSM-5 samples were passivated by bis(trimethylsilyl) trifluoroacetamide (BSTFA) followed by calcination, promoting selective deposition of intraporous copper during aqueous copper ion exchange. At an optimum level of 1–2 wt % SiO2, IR studies showed a 64 % relative reduction in external copper species and temperature-programmed oxidation analysis showed an associated increase in the formation of methanol compared with unmodified Cu-ZSM-5 samples. It is, therefore, reported that the modified zeolites contained a significantly higher proportion of active, selective copper species than their unmodified counterparts with activity for partial methane oxidation to methanol.