Mechanochemically assisted room temperature solid state metathesis reaction for the synthesis of MMoO4 (M = Ca, Sr and Ba)

This communication reports a novel mechanochemically assisted room temperature solid state metathesis reaction for the synthesis of submicron-size alkaline-earth molybdates crystallizing in a tetragonal Scheelite structure. The solids were characterized by powder XRD, FTIR, TGA, DTA, SEM, EDAX and TEM to ascertain their composition, phase homogeneity and morphology.     

Spectral characteristics of a binary dye-mixture laser

We have investigated laser action in a binary mixture of dyes, Rh-6G and DCM, resulting in tunable laser emission over an extended frequency region. The two dyes absorb the same pump radiation but fluoresce over frequency ranges that are shifted with respect to each other, thereby resulting in extended tunability. Following a time-dependent analysis of a rate-equation model that describe the operation of such a laser, theoretical estimates for optimum dye concentrations and the corresponding extension of the laser tuning range have been obtained.     

Influence of Interfacial LSMO Nanoparticles/Layer on the Vortex Pinning Properties of YBCO Thin Film

YBa₂Cu₃O_7?δ (YBCO) thin films have been deposited on bare and La_0.67Sr_0.33MnO₃ (LSMO) modified single crystal SrTiO₃ (STO) substrates. The effect of randomly distributed ferromagnetic LSMO nanoparticles and a complete LSMO layer, present at STO/YBCO interface, on the superconducting properties of YBCO thin films has been investigated by temperature dependent magnetization studies. The YBCO thin film on LSMO nanoparticles decorated STO substrate shows significant improvement in the critical current density and pinning force density as compared to the YBCO thin film deposited on bare STO substrate and this improvement is more significant at higher applied magnetic field. However, the LSMO/YBCO bilayer showed the improved flux pinning properties only up to a magnetic field of 1.5 T above which it deteriorates. In the case of LSMO/YBCO bilayer, the underlying LSMO layer gives rise to magnetic inhomogeneities due to domain structure, which leads to improved flux pinning properties limited to lower field. However, in the case of LSMO nanoparticles decorated substrate, the presence of LSMO nanoparticles at YBCO/STO interface seems to introduce magnetic inhomogeneities as well as structural defects, which might be acting as correlated pinning sites leading to improved flux pinning properties of the YBCO thin film over a wide range of applied magnetic field.     

EXSHOF: An artificial intelligence approach to high-order filter synthesis

A two-tier expert-system-based synthesis of high-order filters is developed. Expert-system techniques have been used for choosing a particular biquad structure and for selection of the high-order filter structure as well. The data inputs will be either filter specifications or transfer functions and the output will be a detailed filter circuit with all its element values. EXSHOF ( pert System based ynthesis of igh rder ilter) is totally menu-driven and highly interactive. It assumes little knowledge of computers or filters from the user. The complete package is implemented in Turbo PASCAL and Turbo PROLOG languages.     

A theoretical and empirical investigation of multi‐item on‐line auctions

In this paper we explore and analyze the structure of Internet auctions from an analytical and an empirical perspective. Such web‐based auctions are rapidly emerging as a mercantile process of choice in the electronic marketplace. We observe current Internet auctions for one‐time products, such as rapidly aging hardware, and analyze them within the framework of the existing auction theory. While traditional auction theory focuses on single‐item auctions, we observe that a majority of on‐line auctions are multi‐item auctions. A significant contribution of this work is the theoretical derivation of the structure of the winning bids in multi‐item progressive on‐line auctions. Additionally, for comparative purposes, we explore the structural characteristics of alternative multi‐item auction mechanisms proposed in the auction theory. We derive hypotheses based on our analytical results and compare two different types of auction mechanisms. We test the traditional auction theory assumption regarding the homogeneity of bidders and present the first ever empirically derived classification and performance‐comparison of on‐line bidders. We test our hypotheses using real‐world empirical data obtained by tracking a premier web‐based auction site. Statistical analysis of the data indicates that firms may gain by choosing alternative auction mechanisms. We also provide directions for further exploration of this emerging but important dimension of electronic commerce. This revised version was published online in July 2006 with corrections to the Cover Date.     

Fuzzy triangulation signature for detection of change in human emotion from face video image sequence

The present article proposes a geometry-based fuzzy relational technique for capturing gradual change in human emotion over time available from relevant face image sequences. As associated features, we make use of fuzzy membership arising out of five triangle signatures such as - (i) Fuzzy Isosceles Triangle Signature (FIS), (ii) Fuzzy Right Triangle Signature (FRS), (iii) Fuzzy Right Isosceles Triangle Signature (FIRS), (iv) Fuzzy Equilateral Triangle Signature (FES), and (v) Other Fuzzy Triangles Signature (OFS) to achieve the task of appropriate classification of facial transition from neutrality to one among the six expressions viz. anger (AN), disgust (DI), fear (FE), happiness (HA), sadness (SA) and surprise (SU). The effectiveness of the Multilayer Perceptron (MLP) classifier is tested and validated through 10 fold cross-validation method on three benchmark image sequence datasets namely Extended Cohn-Kanade (CK+), M&M Initiative (MMI), and Multimedia Understanding Group (MUG). Experimental outcomes are found to have achieved accuracy to the tune of 98.47%, 93.56%, and 99.25% on CK+, MMI, and MUG respectively vindicating the effectiveness by exhibiting the superiority of our proposed technique in comparison to other state-of-the-art methods in this regard.

     

Design of particle-reinforced polyurethane mould materials for soft tooling process using evolutionary multi-objective optimization algorithms

Polyurethane is used for making mould in soft tooling (ST) process for producing wax/plastic components. These wax components are later used as pattern in investment casting process. Due to low thermal conductivity of polyurethane, cooling time in ST process is long. To reduce the cooling time, thermal conductive fillers are incorporated into polyurethane to make composite mould material. However, addition of fillers affects various properties of the ST process, such as stiffness of the mould box, rendering flow-ability of melt mould material, etc. In the present work, multi-objective optimization of various conflicting objectives (namely maximization of equivalent thermal conductivity, minimization of effective modulus of elasticity, and minimization of equivalent viscosity) of composite material are conducted using evolutionary algorithms (EAs) in order to design particle-reinforced polyurethane composites by finding the optimal values of design parameters. The design parameters include volume fraction of filler content, size and shape factor of filler particle, etc. The Pareto-optimal front is targeted by solving the corresponding multi-objective problem using the NSGA-II procedure. Then, suitable multi-criterion decision-making techniques are employed to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of the ST process for industrial applications. Finally, the experimental study with a typical real industrial application demonstrates that the obtained optimal design parameters significantly reduce the cooling time in soft tooling process keeping other processing advantages.