A fuzzy assessment framework to select among transportation investment projects in Turkey

Selecting the best transportation investment project (TIP) is often a difficult task, since many social, environmental and economic criteria have to be considered simultaneously. Evaluating a set of different projects, especially the best set of alternatives, portfolios, is even more complex. Pursuing the goal of selecting the best TIP portfolio, we propose a fuzzy assessment method to aid the selection process of a multi-criterion project by utilizing the concept of entropy and interval normalization procedure in a fuzzy analytic hierarchy process (F-AHP). Then, regarding this informative phase, we propose a fuzzy linear programming model to select the best TIP portfolio under uncertain cost pressure. A real case study is conducted to illustrate the efficiency of the proposed method.     

Robust MIMO disturbance observer analysis and design with application to active car steering

A multi‐input–multi‐output extension of the well‐known two control degrees‐of‐freedom disturbance observer architecture that decouples the problem into single‐input–single‐output disturbance observer loops is presented in this paper. Robust design based on mapping D‐stability and the frequency domain specifications of weighted sensitivity minimization and phase margin bound to a chosen controller parameter space is presented as a part of the proposed design approach. The effect of the choice of disturbance observer Q filter on performance is explained with a numerical example. This is followed by the use of structured singular values in the robustness analysis of disturbance observer controlled systems subject to structured, real parametric and mixed uncertainty in the plant. A design and simulation study based on a four wheel active car steering control example is used to illustrate the methods presented in the paper. Copyright © 2009 John Wiley & Sons, Ltd.     

A class of adaptive directional image smoothing filters

The gray level distribution around a pixel of an image usually tends to be more coherent in some directions compared to other directions. The idea of adaptive directional filtering is to estimate the direction of higher coherence around each pixel location and then to employ a window which approximates a line segment in that direction. Hence, the details of the image may be preserved while maintaining a satisfactory level of noise suppression performance. In this paper we describe a class of adaptive directional image smoothing filters based on generalized Gaussian distributions. We propose a measure of spread for the pixel values based on the maximum likelihood estimate of a scale parameter involved in the generalized Gaussian distribution. Several experimental results indicate a significant improvement compared to some standard filters.     

Neutron dose transmission measurements for several new concrete samples including colemanite

We have prepared four baryte and four concrete samples having respectively 0%, 5%, 10% and 15% colemanite concentrations. Neutron dose transmission measurements have been done by using a source of mono-energetic neutrons (E_eff = 4.5 MeV–²⁴¹Am–Be). It has been shown that when colemanite percentages of the samples increase, neutron dose transmission values for the samples decrease. It is thus possible to enhance the neutron shielding property of baryte and ordinary concrete by adding different proportions of colemanite.     

Item response theory modeling of substance use: An index based on 10 drug categories.

This study examined the psychometric characteristics of an index of substance use involvement using item response theory. The sample consisted of 292 men and 140 women who qualified for a Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; American Psychiatric Association, 1987) substance use disorder (SUD) diagnosis and 293 men and 445 women who did not qualify for a SUD diagnosis. The results indicated that men ha4 a higher probability of endorsing substance use compared with women. The index significantly predicted health, psychiatric, and psychosocial disturbances as well as level of substance use behavior and severity of SUD after a 2-year follow-up. Finally, this index is a reliable and useful prognostic indicator of the risk for SUD and the medical and psychosocial sequelae of drug consumption. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Determination of flavan-3-ols and trans-resveratrol in grapes and wine using HPLC with fluorescence detection

Concentrations of trans-resveratrol, catechin and epicatechin were analyzed in musts and wines produced from seven red and four white grape cultivars from various wine growing regions of Turkey. Phenolics were quantified using an HPLC method optimized for the separation of wine phenolics. Wine samples contained higher phenolics levels than the corresponding musts. With the exception of Semillion, white wines and musts contained lower concentrations of phenolics than red wines and musts. However, the white cultivar Semillion had the highest concentrations of catechin and epicatechin among all wine and must samples. Semillion wine catechin and epicatechin were 13.7 and 11.8 mg/L, respectively. The highest level of trans-resveratrol among the white cultivars was found in Narince wine (1.93 mg/L). Within the red wine and must cultivars, Bo?azkere, Öküzgozü, and Cabernet contained the highest concentrations of flavan-3-ols and trans-resveratrol. Catechin was the major phenolic in all wines and most musts. Epicatechin was the major phenolic in 6 of the 11 must samples, but none of the wine samples. trans-Resveratrol was generally found in lowest concentrations in both wines and musts.     

What determines static friction and controls the transition to sliding?

We studied the shear response of a confined lubricant layer on approach of the transition to sliding with a surface force apparatus modified for oscillatory shear. In a given experiment, we found that the transition to sliding occurred always around the same deformation amplitude although the shear stress needed to initiate sliding varied up to a factor of two depending on sample history. This suggests the concept of deformation-controlled switching from rest to sliding. The elastic spring-constant, in the stick state, weakened with increasing deformation amplitude. This decrease can be described by a power law when plotted versus the distance to a critical deformation amplitude. The build-up of solid-like behavior after sliding stopped was also gradual and was consistent with a logarithmic time dependence. We suggest a model relating the gradual decrease of stiffness to weakening of the boundary layer, specifically to destruction of some elastic links between molecules or between molecules and the solid surfaces. Static friction (the force that must be overcome at the onset of kinetic motion) is proportional to the number of such links formed during the time of stick.     

Numerical modelling of honeycomb core crush behaviour

In this work several numerical techniques for modelling the transverse crush behaviour of honeycomb core materials were developed and compared with test data on aluminium and Nomex™ honeycomb. The methods included a detailed honeycomb micromechanics model, a homogenised material model suitable for use in FE code solid elements, and a homogenised discrete/finite element model used in a semi-adaptive numerical coupling (SAC) technique. The micromechanics model is shown to be suitable for honeycomb design, since it may be used to compute crush energy absorption for different honeycomb cell sizes, cell wall thicknesses and cell materials. However, the very fine meshes required make it unsuitable for analysis of large sandwich structures. The homogenised FE model may be used for such structures, but gives poor agreement when failure is due to core crushing. The SAC model is shown to be most appropriate for use in structural simulations with extensive compression core crushing failures, since the discrete particles are able to model the material compaction during local crushing.     

Prediction of the pH and the temperature-dependent swelling behavior of -alginate hydrogels by artificial neural networks

This paper considers the possibility of using artificial neural network models to identify model for swelling behavior as new techniques. Multi-layer feed-forward, radial basis function and generalized regression neural network models were employed to predict the swelling behaviors of Ca²⁺-alginate hydrogels under different environmental conditions of pH and temperature. The results show that an excellent correlation between the experimental and predicted swelling ratios was obtained by the artificial neural networks. Generalized regression neural network has a better performance than the other neural network models. The absolute mean error, the determination coefficient and the standard error of prediction were used as performance criteria. In addition, the performances of the neural network models are significantly superior compared with those of second-order swelling kinetics, quadratic and cubic models of response surface methodology.