Perceived risk and trust associated with purchasing at electronic marketplaces

Understanding consumer behaviour is of vital importance to consumer-oriented e-business models today. In this paper, we study the relationships between consumer perceptions of risk and trust and the attitude towards purchasing at a consumer-to-consumer electronic marketplace (EM). Typical for EM settings is that consumer behaviour is subject to perceptions of the selling party as well as of the institutional structures of the intermediary that is operating the EM. Building upon the well-established literature of trust, we consider the concepts of intermediary trust and seller trust. We extend this categorisation by introducing the concepts of intermediary risk and seller risk. We developed measurement instruments for intermediary risk and seller risk. All measurement scales have acceptable alphas and are unidimensional. An empirical study is conducted to explore the relationships between the risk and trust types and consumer purchase attitude. The results reveal significant, direct effects of seller trust and seller risk. Second-order effects of intermediary trust and intermediary risk are investigated and reported. The paper concludes with general observations and recommendations for research and practice.     

Numerical simulation of two-phase turbulent flow in hydraulic and hydropower engineering

In connection with the specific features of high velocity aerated flow generated by hydraulic engineering structures, the mathematical model is developed for high turbulence air-water two-phase flow with the use of twin flow theoretical model in this paper. Furthermore the numerical method is proposed to treat bubbled flows. In addition, on the basis of air-water stratified twin flow model, the new calculation methods and free surface tracking technique are proposed to describe complicated movements of the free surface. Finally, the proposed model is used to calculate artificial aerated flows. The computed results coincide quite well with experimental results. This means that the proposed method can provide solid basis for practical engineering design.     

Assessment model of dam operation risk based on monitoring data

Although the dams produce remarkable social and economic benefits, the threat made by unsafe dams to the life and property of people who live in the lower river area is un-negligible. Based on the monitoring data which reflect the safety condition of dams, the risk degree concept is proposed and the analysis system and model for evaluating risk degree (rate) are established in this paper by combining the reliability theory and field monitoring data. The analysis method for risk degree is presented based on Bayesian approach. A five-grade risk degree system for dam operation risk and corresponding risk degree is put forward according to the safety condition of dams. The operation risks of four cascade dams on some river are analyzed by the model and approach presented here and the result is adopted by the owner.     

Electrical properties and positron annihilation study of (Ba<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript>Ho<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>)TiO<Subscript>3</Subscript> ceramics

DC resistivity, dielectric constant, dielectric loss and positron annihilation spectra of (Ba_1−x Ho _x )TiO₃ ceramics have been measured as a function of holmium concentration x. It has been found that the DC resistivity of (Ba_1−x Ho _x )TiO₃ is strongly dependent on the Ho content: it decreases three orders of magnitude and reaches a minimum at x = 0.4%. Doping with 0.6% holmium increases the permittivity of BaTiO₃ by approximately three times (from ∼1,300 to ∼4,000), with only a slight increase in the corresponding dielectric loss. The local electron density and defect concentration estimated using positron annihilation technique conforms well to the features found in the dielectric and resistivity measurements. The results have been discussed in terms of a mixed compensation model.     

A Study of Integrated Document and Connection Caching in the WWW

Document caching and connection caching are extensively studied problems. In document caching, one has to maintain caches containing documents accessible in a network. In connection caching, one has to maintain a set of open network connections that handle data transfer. Previous work investigated these two problems separately while in practice the problems occur together: In order to load a document, one has to establish a connection between network nodes if the required connection is not already open. In this paper we present the first study that integrates document and connection caching. We first consider a very basic model in which all documents have the same size and the cost of loading a document or establishing a connection is equal to 1. We present deterministic and randomized online algorithms that achieve nearly optimal competitive ratios unless the size of the connection cache is extremely small. We then consider general settings where documents have varying sizes. We investigate a FAULT model in which the loading cost of a document is 1 as well as a BIT model in which the loading cost is equal to the size of the document.     

Non-redundant data clustering

Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice, this discovery process should avoid redundancies with existing knowledge about class structures or groupings, and reveal novel, previously unknown aspects of the data. In order to deal with this problem, we present an extension of the information bottleneck framework, called coordinated conditional information bottleneck, which takes negative relevance information into account by maximizing a conditional mutual information score subject to constraints. Algorithmically, one can apply an alternating optimization scheme that can be used in conjunction with different types of numeric and non-numeric attributes. We discuss extensions of the technique to the tasks of semi-supervised classification and enumeration of successive non-redundant clusterings. We present experimental results for applications in text mining and computer vision.