Understanding trust in ms-commerce: The roles of reported experience,linguistic style,profile photo,emotional, and cognitive trust

This paper examines what influences trust in mobile social commerce environment. Drawing on trust-based acceptance model (i.e. cognitive and emotional trust) and online review features (i.e. profile photo, linguistic style, and reported experience), we examine how these factors affect trust in mobile social commerce. Hypotheses were tested using survey data. The results of our model showed that there are significant influences of profile photo, reported experience, cognitive, and emotional trust towards trust in ms-commerce. This work contributes to existing literature by examining the roles of previous trust in mobile payments and online reviews on trust in mobile social commerce.     

Macrophage Immunomodulation Through New Polymers that Recapitulate Functional Effects of Itaconate as a Power House of Innate Immunity

Itaconate (ITA) is an emerging powerhouse of innate immunity with therapeutic potential that is limited in its ability to be administered in a soluble form. A library of polyester materials that incorporate ITA into polymer backbones resulting in materials with inherent immunoregulatory behavior is developed. Harnessing hydrolytic degradation release from polyester backbones, ITA polymers result in the mechanism specific immunoregulatory properties on macrophage polarization in vitro. In a functional assay, the polymer-released ITA inhibits bacterial growth on acetate. Translation to an in vivo model of biomaterial associated inflammation, intraperitoneal injection of ITA polymers demonstrate a rapid resolution of inflammation in comparison to a control polymer silicone, demonstrating the value of sustained biomimetic presentation of ITA.     

Efficient Low Dissipative High Order Schemes for Multiscale MHD Flows, II: Minimization of ∇·B Numerical Error

An adaptive numerical dissipation control in a class of high order filter methods for compressible MHD equations is systematically discussed. The filter schemes consist of a divergence-free preserving high order spatial base scheme with a filter approach which can be divergence-free preserving depending on the type of filter operator being used, the method of applying the filter step, and the type of flow problem to be considered. Some of these filter variants provide a natural and efficient way for the minimization of the divergence of the magnetic field (∇·B) numerical error in the sense that commonly used divergence cleaning is not required. Numerical experiments presented emphasize the performance of the ∇·B numerical error. Many levels of grid refinement and detailed comparison of the filter methods with several commonly used compressible MHD shock-capturing schemes will be illustratedA condensed version appears in the Proceedings of the International Conference on High Performance Scientific Computing, March 10-14, 2003, Hanoi, Vietnam. This is a revised version of a longer internal report, Feb. 19, 2004. The longer internal report was published as a RIACS Technical Report TR03.10, July 2003, NASA Ames Research Center     

Antenna-array pattern nulling using a differential evolution algorithm

A new method based on the differential evolution (DE) algorithm is proposed for antenna-array pattern synthesis with prescribed nulls. The array excitation amplitudes are the only controlling parameters, and the objectives are to synthesize array patterns with nulls imposed on directions of interferences while keeping the sidelobe levels (SLLs) below prescribed levels. Many factors such as the excitation dynamic range ratio, null depth level, null width, and SLLs are taken into account in the synthesis. Simulation results of several typical problems are compared with published results to illustrate the effectiveness of the proposed method. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 14: 57–63, 2004.     

High-performance automatic target recognition through data-specificVLSI

Under the Mojave configurable computing project, we have developed a system for achieving high performance on an automatic target recognition (ATR) application through the use of configurable computing technology. The ATR system studied here involves real-time image acquisition from a synthetic aperture radar (SAR). SAR images exhibit statistical properties which can be used to improve system performance. In this paper, the Mojave configurable computing system uses field programmable gate arrays (FPGA's) to implement highly specialized circuits while retaining the flexibility of programmable components. A controller sequences through a set of specialized circuits in response to real-time events. Computer-aided design (CAD) tools have been developed to support the automatic generation of these specialized circuits. The resulting configurable computing system achieves a significant performance advantage over the existing solution, which is based on application specific integrated circuit (ASIC) technology     

Two‐phase production of cyclohexene and cyclooctene oxides in water as an approach to pollution prevention

Liquid–liquid two‐phase epoxidation from cyclohexene and cyclooctene in aqueous potassium peroxymonosulfate (commercially available as Oxone^®) solution was studied as an application in pollution prevention. To avoid potential emissions of volatile organic compounds an aqueous solution was employed to replace the usual chlorinated solvents used in epoxide production. A droplet column reactor and stirred tank reactor were used to investigate two‐phase synthesis of epoxide. An aqueous Oxone^® solution was used to oxidize a dispersion of alkene droplets and form epoxide. The study of aqueous epoxidation in both reactors showed that the epoxidation of alkenes can be represented as a first order reaction with respect to alkene. The salting out effect of Oxone^® concentration was studied in both reactors and found to be very similar at optimal conditions. In comparing the two reactors, it was found that the droplet column reactor produces larger quantities of product per unit reactor volume for the same reaction time. The objective of this study is to provide an alternative reactor design and synthesis route that can meet pollution prevention goals. Copyright © 2004 Society of Chemical Industry     

Adaptive weighted outer-product learning associative memory

Associative-memory neural networks with adaptive weighted outer-product learning are proposed in this paper. For the correct recall of a fundamental memory (FM), a corresponding learning weight is attached and a parameter called signal-to-noise-ratio-gain (SNRG) is devised. The sufficient conditions for the learning weights and the SNRG's are derived. It is found both empirically and theoretically that the SNRG's have their own threshold values for correct recalls of the corresponding FM's. Based on the gradient-descent approach, several algorithms are constructed to adaptively find the optimal learning weights with reference to global- or local-error measure.     

Transformations for nonideal uniform circular arrays operating in correlated signal environments

The Davies transformation is a method to transform the steering vector of a uniform circular array (UCA) to one with Vandermonde form. As such, it allows techniques such as spatial smoothing for direction-of-arrival (DOA) estimation in a correlated signal environment, developed originally for uniform linear arrays, to be applied to UCAs. However, the Davies transformation can be highly sensitive to perturbations of the underlying array model. This paper presents a method for deriving a more robust transformation using optimization techniques. The effectiveness of the method is illustrated through a number of DOA estimation examples.