Design of Smart Door Closer System with Image Classification over WLAN

Wireless Personal Communications - A dual purpose system is presented in this paper which serves not only as a door closer, but is equally effective for surveillance purposes. The currently...     

Synthesis and characterization of biocompatible hydroxyapatite coated ferrite

Ferrite particles coated with biocompatible phases can be used for hyperthermia treatment of cancer. We have synthesized substituted calcium hexaferrite, which is not stable on its own but is stabilized with small substitution of La. Hexaferrite of chemical composition (CaO)_0.75(La₂0₃)_0.20(Fe₂O₃)₆ was prepared using citrate gel method. Hydroxyapatite was prepared by precipitating it from aqueous solution of Ca(NO₃)₂ and (NH₄)₂HPO₄ maintaining pH above 11. Four different methods were used for coating of hydroxyapatite on ferrite particles. SEM with EDX and X-ray diffraction analysis shows clear evidence of coating of hydroxyapatite on ferrite particles. These coated ferrite particles exhibited coercive field up to 2 kOe, which could be made useful for hysteresis heating in hyperthermia. Studies by culturing BHK-21 cells and WBC over the samples show evidence of biocompatibility. SEM micrographs and cell counts give clear indication of cell growth on the surface of the sample. Finally coated ferrite particle was implanted in Kasaulli mouse to test its biocompatibility. The magnetic properties and biocompatibility studies show that these hydroxyapatite coated ferrites could be useful for hyperthermia.     

The temperature dependence of optical absorption near the absorption edge of Tl3 As Se3

The optical transmission of Tl₃ As Se₃ as a function of wavelength and temperature is reported for the 1.2 – 2.5 um spectral range, and at temperatures from 40 to 300K. The absorption edge for the material occurs at about 1.011 eV. The material also indicated direct transitions at about 1.015 eV and indirect transitions at about 1.001 eV. The direct and indirect transitions are found to be independent of temperature. Electrical measurements have identified the sample as p-type, with hole concentrations of 5 × 10¹⁵ and 6 × 10¹² cm^?3 at 395 and 300K, respectively. The sample seems to be a good insulator at all temperatures between 40 ?300K.     

Hyaluronic acid induced hyaluronic acid binding protein phosphorylation and inositol triphosphate formation in lymphocytes

In this report, the role of 34 kDa HA-binding protein in hyaluronic acid-induced cellular signalling in lymphocytes has been examined. The binding of 125I-HA to lymphocytes in vivo was found to be inhibited by pre-incubation of the cells with anti-34 kDa HA-binding protein antibodies, thus confirming 34 kDa HA-binding protein as the specific HA-receptor in lymphocytes. This observation was substantiated by anti-34 kDa HA-binding protein antibodies immunoblotting and 125I-HA ligand blotting of lymphocytes cell lysate. The HA-induced cell aggregation, tyrosine phosphorylation and cytoskeletal protein phosphorylation demonstrate the HA-induced early cellular signalling events in lymphocytes. Further, to study the involvement of 34 kDa HA-binding protein in mitogen induced lymphocyte signalling, we studied in vivo phosphorylation and secondary messenger formation. The enhanced 34 kDa HA-binding protein phosphorylation by HA and the inhibition of cellular aggregation and IP3 formation by anti-HA-binding protein antibodies revealed that 34 kDa HA-binding protein is one of the potential mediators in HA-induced signal transduction.     

A comparison between isoparametric Lagrangian elements in 2D BEM

A comparison between a family of isoparametric C°-continucus elements in the context of two-dimensional elastostatics using the direct boundary element method is presented. The elements studied use Lagrangian shape functions of orders quadratic, cubic and quartic. The relative efficiencies of these elements from the viewpoint of accuracy of solution as well as cost effectiveness are examined through certain selected problems. It emerges from the present study that the quartic element is more reliable in accuracy than the lower members of the family without being necessarily more expensive.     

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.     

On the sizing of a solar thermal electricity plant for multiple objectives using evolutionary optimization

Design, implementation and operation of solar thermal electricity plants are no more an academic task, rather they have become a necessity. In this paper, we work with power industries to formulate a multi-objective optimization model and attempt to solve the resulting problem using classical as well as evolutionary optimization techniques. On a set of four objectives having complex trade-offs, our proposed procedure first finds a set of trade-off solutions showing the entire range of optimal solutions. Thereafter, the evolutionary optimization procedure is combined with a multiple criterion decision making (MCDM) approach to focus on preferred regions of the trade-off frontier. Obtained solutions are compared with a classical generating method. Eventually, a decision-maker is involved in the process and a single preferred solution is obtained in a systematic manner. Starting with generating a wide spectrum of trade-off solutions to have a global understanding of feasible solutions, then concentrating on specific preferred regions for having a more detailed understanding of preferred solutions, and then zeroing on a single preferred solution with the help of a decision-maker demonstrates the use of multi-objective optimization and decision making methodologies in practice. As a by-product, useful properties among decision variables that are common to the obtained solutions are gathered as vital knowledge for the problem. The procedures used in this paper are ready to be used to other similar real-world problem solving tasks.