Realization of modular multidimensional complex digital filters using GIC concept

It is known that complex digital filters possess certain advantages over real digital filters in processing complex signals such as increased computational speed and efficiency. In this paper, a simple and systematic procedure which can be implemented through a computer program is presented for realizing a specific class of multidimensional (M-D) complex digital filters. The proposed filter structures are derived from analog reference configurations comprising generalized immittance converters and resistors by making use of wave concept. These filters possess many salient properties such as low noise, low sensitivity and capability of realizing multiple transfer functions simultaneously which are inherited from the reference analog filters they are derived from. These features make them attractive for very large-scale integrated (VLSI) implementation. It is shown that the proposed filter structures can be obtained directly from the specified M-D discrete transfer function without the need for realizing any analog reference configuration.     

Oxygen-enrichment of YBa2Cu3 YBa2Cu3O7-δ using the fluidization techniqueusing the fluidization technique

The oxygen-deficient phase of the highT _c superconductor, YBa₂Cu₃O₇, was oxygen-enriched using the fluidization technique to give good superconducting properties. The normal method of oxygen treatment at 900°C for 24 h and at 600°C for 24 h has been reduced to just one treatment at 600°C for 12 h by the fluidization technique to achieve almost the same strength of superconducting signal for the YBa₂Cu₃O₇ powder, which establishes the attractiveness of the latter route for the large-scale preparation of superconducting material. The particle sizes were in the range 0–90, 90–180 and 180–420 μm. The fluidized particles were crystalline with orthorhombic distortion.T _c ^onset , estimated using the a.c. magnetic susceptibility method, was 91·3 K. The volume fraction of superconducting material in the product was 83·7–85·3%, one of the highest values reported so far for YBa₂Cu₃O₇.     

Analysis of frictional energy dissipation on an annular surface with harmonic loading

Metallic mating surfaces in structural joints offer a good source of frictional energy dissipation resulting in a damped dynamic structural response. This paper reports the results of experiments where the energy dissipation per cycle occurring at a preloaded flat metallic annular interface subjected to cyclic tangential forces is measured. The effects of certain pertinent joint variables on this frictional energy dissipation are investigated by the application of Response Surface Methodology. A central composite rotatable design was utilized for developing empirical expressions for energy loss. The methodology presented suggests a useful technique for tribological research.     

Forced convection in cross flow of power law fluids over a tube bank

The forced convective heat transfer characteristics for incompressible power-law fluids past a bundle of circular cylinders have been investigated numerically. The cylinder-to-cylinder hydrodynamic interactions have been approximated via a simple cell model. The momentum and energy equations have been solved using a finite difference based numerical method for a range of physical and kinematic conditions. The role of the two commonly used thermal boundary conditions, namely, constant temperature or constant heat flux, on heat transfer characteristics has also been studied. Extensive numerical results elucidating the effect of shear-thinning viscosity on the values of Nusselt number have been obtained for Peclet numbers ranging from 1 to 5000, Reynolds number in the range 1-500, flow behaviour index 1?n?0.5 and three values of voidages, namely, 0.4, 0.5 and 0.6, typical of tubular heat exchangers and tube banks. Under all conditions, varying levels of enhancement in Nusselt number are observed due to shear-thinning behaviour. The surface averaged Nusselt number shows strong dependence on the values of voidage, power-law index, Reynolds and Peclet numbers. The paper is concluded by presenting comparisons with the scant experimental results available in the literature.     

A comparative investigation of interfacial adhesion behaviour of polyamide based self-reinforced polymer composites by single fibre and multiple fibre pull-out tests

Abstract

Interfacial adhesion of composite materials plays an important role in their mechanical properties and performance. In the present investigation, analysis of the interfacial properties of self-reinforced polyamide composites by using microbond multiple fibre pull-out test is emphasised. Microbond specimens prepared through thermal processing are tested for their interfacial properties by multiple fibre bundle pull-out tests and compared with that of traditional single fibre pull-out test specimens. Multiple fibre pull-out addresses the volume fraction as well as eliminates the possibility of fibre breakage before matrix shear. Higher scatter in the data in the samples is addressed in the present studies. FTIR and Fractographic studies are carried out for deep understanding of the post pull-out interfacial adhesion.     

Comparison of TiAIN,AICrN, and AICrN/TiAIN coatings for cutting-tool applications

Monolayer and bilayer coatings of TiAlN, AlCrN, and AlCrN/TiAlN were deposited onto tungsten carbide inserts using the plasma enhanced physical vapor deposition process. The microstructures of the coatings were characterized using scanning electron microscopy （SEM） and atomic force microscopy （AFM）. The SEM micrographs revealed that the AlrN and AlCrN/TiAlN coatings were uniform and highly dense and contained only a limited number of microvoids. The TiAIN coating was non-uniform and highly porous and contained more micro droplets. The hardness and scratch resistance of the specimens were measured using a nanoindentation tester and scratch tester, respectively. Different phases formed in the coatings were analyzed by X-ray diffraction （XRD）. The AlCrN/TiAlN coating exhibited a higher hardness （32.75 GPa）, a higher Young＇s modulus （561.97 GPa）, and superior scratch resistance （LcN = 46 N） compared to conventional coatings such as TiAlN, A1CrN, and TiN.     

Using genetic algorithm to select the presentation order of training patterns that improves simplified fuzzy ARTMAP classification performance

The presentation order of training patterns to a simplified fuzzy ARTMAP (SFAM) neural network affects the classification performance. The common method to solve this problem is to use several simulations with training patterns presented in random order, where voting strategy is used to compute the final performance. Recently, an ordering method based on min–max clustering was introduced to select the presentation order of training patterns based on a single simulation. In this paper, another single simulation method based on genetic algorithm is proposed to obtain the presentation order of training patterns for improving the performance of SFAM. The proposed method is applied to a 40-class individual classification problem using visual evoked potential signals and three other datasets from UCI repository. The proposed method has the advantages of improved classification performance, smaller network size and lower training time compared to the random ordering and min–max methods. When compared to the random ordering method, the new ordering scheme has the additional advantage of requiring only a single simulation. As the proposed method is general, it can also be applied to a fuzzy ARTMAP neural network when it is used as a classifier.     

Horizontal Voting Ensemble Based Predictive Modeling System for ColonCancer

Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models from the last epochs of the proposed architecture. Ten thousand (10000) microscopic images are taken to test the classification performance of the proposed PMS with the HVE method. The microscopic images obtained from the colon tissues are classified into ACA or benign by the proposed PMS. Results prove that the proposed PMS has ~8% performance improvement over the architecture without using the HVE method. The proposed PMS for colon cancer reduces the misclassification rate and attains 99.2% of sensitivity and 99.4% of specificity. The overall accuracy of the proposed PMS is 99.3%, and without using the HVE method, it is only 91.3%.