Unsteady transverse injection of kerosene into a supersonic flow

A shadowgraph and a new fuel injection system were used to study kerosene transversely injected into a supersonic flow. High pressure and velocity of injection can be attained. The pressure time histories were detected in oil-line and the shadowgraphs of the flow field were obtained at different time-delays. The inflow stagnation pressure was varied to change the local flow speed in test section. The results indicate that kerosene jet exhibits deep penetration and four regimes appear clearly during the fuel jet atomization in a high-speed flow. The jet disintegration is caused by surface waves propagating along the jet surface, and the breakup point is located at the wave trough. The surface waves are dominantly generated by aerodynamic force. The jet shock is close to windward surface of the jet. The shock reflects on and transmits in duct boundary layers. In the case of unsteady injection, the shock structure is very complicated and different from that of hydrogen injection. The results of kerosene inj     

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Impedance spectroscopy of bismuth sodium titanate: Barium titanate ceramics with manganese doping

In this work we use Impedance Spectroscopy (IS) to study lead‐free ceramics of perovskite structure (Bi_1/2Na_1/2TiO₃)_0.925(BaTiO₃)_0.075 with Mn doping of 0, 0.2, 1.0, and 2.0 at.%. We compare our IS results with permittivity results, using dielectric to resistivity transformation equations which allow us to display results either as permittivity or as resistivity. We observe ionic conductivity dominating at lower temperatures, giving way to electronic conductivity at higher temperatures. The permittivity shows deviations from Curie‐Weiss behavior characteristic of relaxor ferroelectrics. The 0.2% Mn samples show the highest ionic resistivity, which will reduce heating for high voltage piezoelectric applications. They also have the highest Curie‐Weiss temperature and Burns temperature.     

Knowledge management in production alliances

This paper develops a managerial model of production network organizations (PNOs), inter-firm alliances for product development and delivery, in which inter-firm network structure and knowledge management practices play a major role in venture performance. The paper addresses the issue of alignment between the adopted network structure, the scope of the joint production task, and consequent inter-firm information flow requirements, hypothesizing that venture performance is a joint function of network structure and task integration scope. In situations with a difficult alignment between the chosen network structure, joint task scope, and information flow requirements, knowledge management investments across the PNO are proposed as a moderating factor leading to improved venture performance. The paper demonstrates the proposed model with three case studies, providing preliminary verification of the key proposition that knowledge management interventions can mediate the impact of loose integrating structures for joint production ventures that are undertaking complex joint tasks.     

Citizens’ Adoption Behavior of Mobile Government (mGov): A Cross-Cultural Study

This study aims to address the paradigms of consumers’ adoption behavior for mobile government, posits the factors which pursue citizens’ intention to adopt mobile government services, and reveals the impact of cultural dimensions in perceiving driving factors of mobile government adoption. The mobile government adoption model was developed and tested among users of three different countries, namely Bangladesh, Canada, and Germany. The finding suggests the rationale that cross-cultural differences impact consumers’ perception of mobile government adoption behavior.     

Goodness-of-fit tests for logistic regression models when data are collected using a complex sampling design

Logistic regression models are frequently used in epidemiological studies for estimating associations that demographic, behavioral, and risk factor variables have on a dichotomous outcome, such as disease being present versus absent. After the coefficients in a logistic regression model have been estimated, goodness-of-fit of the resulting model should be examined, particularly if the purpose of the model is to estimate probabilities of event occurrences. While various goodness-of-fit tests have been proposed, the properties of these tests have been studied under the assumption that observations selected were independent and identically distributed. Increasingly, epidemiologists are using large-scale sample survey data when fitting logistic regression models, such as the National Health Interview Survey or the National Health and Nutrition Examination Survey. Unfortunately, for such situations no goodness-of-fit testing procedures have been developed or implemented in available software. To address this problem, goodness-of-fit tests for logistic regression models when data are collected using complex sampling designs are proposed. Properties of the proposed tests were examined using extensive simulation studies and results were compared to traditional goodness-of-fit tests. A Stata ado function svylogitgof for estimating the F-adjusted mean residual test after svylogit fit is available at the author's website http://www.people.vcu.edu/~kjarcher/Research/Data.htm.