A design method for substrate integrated waveguide electromagnetic bandgap (SIW-EBG) filters

An efficient design method for substrate integrated waveguide electromagnetic bandgap (SIW-EBG) filters is proposed which provides direct dimensional synthesis approach for desired filter objectives without using network representations. The method is applied to the design of an X band SIW-EBG filter and its response is compared with HFSS (high frequency structure simulator) simulations for validation purposes. Fairly good agreement between the results shows the applicability of the proposed method for SIW-EBG filter design.     

Phase/State Transitions of Confectionery Sweeteners: Thermodynamic and Kinetic Aspects

Abstract: It has been said that the key to making high‐quality candy is understanding and controlling the transitions of sugar. Whether found as crystal, glass, or fluid solution, sugars impart the texture necessary to distinguish one confection from another and to provide a unique experience to the consumer. In principle, the phase/state transitions of sugars are best understood through careful application of the phase diagram. However, many, if not all, confections are not at equilibrium, meaning that the phase diagram is simply a starting point for understanding and controlling the state of sugars. An understanding of the thermodynamic driving forces that push a confection towards equilibrium and the kinetic constraints that control the rate of approaching that equilibrium are key elements to creating products with the desired texture, quality, and shelf life. In this review, we summarize the thermodynamic and kinetic aspects of controlling phase/state transitions in sweeteners, with particular emphasis on applications to confectionery products.     

Investigation of polymerization parameters affecting dopamine selectivity of a polymeric membrane

Summary By means of electrochemical oxidative polymerization, poly (1,3-phenylenediamine) films on a gold electrode were prepared at a potential of 0.8 V. The permeation properties of polymeric films at the different thickness were investigated by cyclic and differential pulse voltammetry techniques. Voltammetric studies showed that polymeric film at the 1.2 mC thickness exhibited selective permeation for dopamine while rejecting ascorbic acid. Then, all the polymerization parameters affecting the permselective characteristics were systematically investigated and the optimal values were determined. Moreover, stability of polymeric membrane was examined. The results showed that polymeric membrane, owing to permselective character, could be used as a dopamine selective membrane. Received: 10 December 1999/Revised version: 12 March 2000/Accepted: 27 March 2000     

A highly selective and sensitive benzothiazole‐based ‘turn‐on’ fluorescent sensor for Hg2+ ion

A simple benzothiazole‐based fluorescent probe (TDA) for the determination of Hg²⁺ ion in aqueous solutions was synthesised in one step and characterised by ¹H NMR, ¹³C NMR, APT, COSY, FTIR, and elemental analysis. TDA shows a significant fluorescence change upon the interaction of Hg²⁺ ion in DMF–water (v/v = 1/1), while only minor changes in fluorescence intensity are observed with 18 other metal ions. Fluorescence enhancement by a factor of 15 is achieved upon selective interaction with Hg²⁺ ion. The Hg²⁺ ion detection process is found to be pH dependent; therefore, TDA could be feasible within a pH range of 4.0–7.0.     

Image enhancement via space-adaptive lifting scheme exploiting subband dependency

This paper proposes an image enhancement method based on space-adaptive, 2-D lifting scheme. In the space-adaptive update-first lifting scheme, the prediction stage is adapted to the signal structure point-by-point which results in a better signal representation and enhancement result. In this paper, a novel edge-sensitive adaptive prediction method is introduced in the 2-D lifting framework. The method adaptively chooses the best predictor among a set of predictors minimizing the prediction error. The proposed prediction method is sensitive to both even and odd indexed edge pixels in the 2-D lifting context. The bivariate shrinkage which assumes the dependence of the subband wavelet coefficients is used for subband image enhancement. As an objective quality measure, the peak signal-to-noise ratio test is applied to the results of the proposed image enhancement algorithm. Results of the proposed algorithm are compared with those of the VisuShrink, BayesShrink, and NorShrink. Experimental and objective quality test results prove the superior performance of the proposed image enhancement method.     

Physical and mechanical properties of Gokceada: Imbros (NE Aegean Sea) Island andesites

The physical and mechanical properties of the andesite forming much of the island of Gökçeada (Imbros), Turkey, were investigated using 54 mm samples cores from 12 blocks obtained from a quarry. The results were evaluated using regression analysis and good empirical relationships were obtained.     

Synthesis,characterization of phosphine oxide-containing polyimides and their use as selective membrane for dopamine

Tris-(p-aminophenoxy)phosphineoxide, t-APPO, was prepared from 4-nitrophenol and POCl₃, followed by hydrogenation. A series of polyimides prepared from t-APPO and the corresponding dianhydrides by two-stage polycondensation method was characterized by Fourier Transform Infrared Spectrometer (FTIR), GPC, thermal analysis and physical methods. Moreover, in order to check the permeation properties of the resulting polyimide film, the selectivity of the polyimide-coated electrode toward electroactive species (ascorbic acid and dopamine) was examined by means of cyclic voltammetry (CV), differential pulse voltammetry (DPV) and time-base amperometric measurement (TB) techniques. As a result, it has been found that polyimide electrode showed selective permeation for dopamine while blocking the permeation of ascorbic acid through film. Therefore, it has been claimed that phosphine oxide-containing polyimide electrode can be used as a dopamine-selective membrane in the presence of ascorbic acid.     

Polymer/concrete composites—A review

The development of polymer/concrete composites is directed at both improved and new construction materials by combining the ancient technology of hydraulic-cement-concrete with the modern technology of polymers. The need for such materials has always existed since the traditional construction material portland-cement-concrete (PCC) suffers the drawbacks 4 little or no resistance to chemical attack; rapid deterioration under freeze/thaw conditions due to cyclic temperature changes; low tensile, shear and bond strengths; and inherent micro-structural menaces (voids, shrinkage-cracks, capillaries) which, individually or in combination with each other, shorten the service life of the structures.     

Classification of EEG signals using neural network and logistic regression

Epileptic seizures are manifestations of epilepsy. Careful analyses of the electroencephalograph (EEG) records can provide valuable insight and improved understanding of the mechanisms causing epileptic disorders. The detection of epileptiform discharges in the EEG is an important component in the diagnosis of epilepsy. As EEG signals are non-stationary, the conventional method of frequency analysis is not highly successful in diagnostic classification. This paper deals with a novel method of analysis of EEG signals using wavelet transform and classification using artificial neural network (ANN) and logistic regression (LR). Wavelet transform is particularly effective for representing various aspects of non-stationary signals such as trends, discontinuities and repeated patterns where other signal processing approaches fail or are not as effective. Through wavelet decomposition of the EEG records, transient features are accurately captured and localized in both time and frequency context. In epileptic seizure classification we used lifting-based discrete wavelet transform (LBDWT) as a preprocessing method to increase the computational speed. The proposed algorithm reduces the computational load of those algorithms that were based on classical wavelet transform (CWT). In this study, we introduce two fundamentally different approaches for designing classification models (classifiers) the traditional statistical method based on logistic regression and the emerging computationally powerful techniques based on ANN. Logistic regression as well as multilayer perceptron neural network (MLPNN) based classifiers were developed and compared in relation to their accuracy in classification of EEG signals. In these methods we used LBDWT coefficients of EEG signals as an input to classification system with two discrete outputs: epileptic seizure or non-epileptic seizure. By identifying features in the signal we want to provide an automatic system that will support a physician in the diagnosing process. By applying LBDWT in connection with MLPNN, we obtained novel and reliable classifier architecture. The comparisons between the developed classifiers were primarily based on analysis of the receiver operating characteristic (ROC) curves as well as a number of scalar performance measures pertaining to the classification. The MLPNN based classifier outperformed the LR based counterpart. Within the same group, the MLPNN based classifier was more accurate than the LR based classifier.