An approach to knowledge engineering to support knowledge-based simulation of payload ground processing at the Kennedy Space Center

Planning for processing payloads was always difficult and time-consuming. With the advent of Space Station Freedom and its capability to support a myriad of complex payloads, the planning to support this ground processing maze involves thousands of man-hours of often tedious data manipulation. To provide the capability to analyze various processing schedules, an object oriented knowledge-based simulation environment called the Advanced Generic Accomodations Planning Environment (AGAPE) is being developed. Having nearly completed the baseline system, the emphasis in this paper is directed toward rule definition and its relation to model development and simulation. The focus is specifically on the methodologies implemented during knowledge acquisition, analysis, and representation within the AGAPE rule structure. A model is provided to illustrate the concepts presented. The approach demonstrates a framework for AGAPE rule development to assist expert system development

Mktg

A new approach to learning the principles of marketing, MKTG is the Asia–Pacific edition of a proven, innovative solution to enhance the students' learning experience. Concise, yet complete, coverage supported by a suite of online learning aids equips students with the tools required to successfully undertake an introductory marketing course. Paving a new way to both teaching and learning, MKTG is designed to truly connect with today's busy tech-savy student. Students have access to online interactive quizzing, videos, podcasts, flashcards, marketing plans, games and more. An accessible, easy-to-read text along with tear out review cards complete a package which helps students to learn important concepts faster

The Validity of Conscientiousness Is Overestimated in the Prediction of Job Performance

Introduction Sensitivity analyses refer to investigations of the degree to which the results of a meta-analysis remain stable when conditions of the data or the analysis change. To the extent that results remain stable, one can refer to them as robust. Sensitivity analyses are rarely conducted in the organizational science literature. Despite conscientiousness being a valued predictor in employment selection, sensitivity analyses have not been conducted with respect to meta-analytic estimates of the correlation (i.e., validity) between conscientiousness and job performance. Methods To address this deficiency, we reanalyzed the largest collection of conscientiousness validity data in the personnel selection literature and conducted a variety of sensitivity analyses. Results Publication bias analyses demonstrated that the validity of conscientiousness is moderately overestimated (by around 30%; a correlation difference of about .06). The misestimation of the validity appears to be due primarily to suppression of small effects sizes in the journal literature. These inflated validity estimates result in an overestimate of the dollar utility of personnel selection by millions of dollars and should be of considerable concern for organizations. Conclusion The fields of management and applied psychology seldom conduct sensitivity analyses. Through the use of sensitivity analyses, this paper documents that the existing literature overestimates the validity of conscientiousness in the prediction of job performance. Our data show that effect sizes from journal articles are largely responsible for this overestimation

Spatial Demography as a Method for Population Estimation: Addressing Census Bureau Under-estimation of New Mexico\u27s Populations Using GIS Technologies

This article discusses the census undercount problem in New Mexico and plans to remedy the situation by using GIS technology to improve the quality and accuracy of local population estimates. It describes the geospatial demographic estimation modeling methods used by researchers at the UNM Bureau of Business and Economic Research-Population Estimates Program (BBER-PEP) to reduce undercount. The article also briefly describes future population studies planned by BBER-PEP using GIS technology. Illustrated with maps and tables