Out of Challenge, Opportunity: Central America's Electric Sector & Key Issues and Recommendations for Enhanced Regional Electric Integration

Taken together, the six nations of Central America count a population of roughly 40 million people and an energy market equal in size to that of Colombia, sufficient to benefit from economies of scale. The region has traditionally been a net importer of hydrocarbons, and hydroelectricity has dominated electric generation. But more recently, thermoelectric generation (diesel and fuel oil) has greatly increased as a percentage of the regional generation market. Progress has been made across the region’s electric sector, beginning with reforms in the 1990s and the 1996 signing of a regional treaty aimed at the development of a regional energy integration project – the Central American Electrical Interconnection System, or SIEPAC. A fundamental SIEPAC goal is to set up a regional electric market and a regulatory system. Indeed, after many years of development, SIEPAC is poised to open a new chapter in Central America’s electric infrastructure and market. But this new era must contend with critical issues such as the need to consolidate the regional electric market, political issues surrounding the venture, and security concerns. Moreover, local conflicts, in different degrees, have become priorities for policymakers, and these are possible barriers to completing the project. The goals of the SIEPAC project and of deepening the broader electric integration process are possible if national and regional decision makers understand that cooperative decision making will produce better results than separate national decision making. Enhanced regional understanding and cooperative decision making, combined with an effort to reorient the terminology and dialogue vis-à-vis energy efficiency in Central America, form the core recommendations of this paper.

Disney's Internship Program: More than Hands-On Experience

The vast majority of hospitality management programs require students to participate in a hands-on work experience, which helps bridge the gap between theory and practice, providing the student with an opportunity to practice the theory learned in the classroom. The Walt Disney World Co. developed, implemented, and operates one of the most successful internship programs in the hospitality industry. It recognizes the need for business practitioners to become more involved in the education of future hospitality managers. The authors summarize the company's program and offer suggestions for other employers looking to give interns more than hands-on experience.

The relationship of aptitude, course grades, and program length, to performance on a standards based test (NCLEX -RN)

The purpose of this study was threefold: first, to investigate variables associated with learning, and performance as measured by the National Council Licensure Examination for Registered Nurses (NCLEX-RN). The second purpose was to validate the predictive value of the Assessment Technologies Institute (ATI) achievement exit exam, and lastly, to provide a model that could be used to predict performance on the NCLEX-RN, with implications for admission and curriculum development. The study was based on school learning theory, which implies that acquisition in school learning is a function of aptitude (pre-admission measures), opportunity to learn, and quality of instruction (program measures). Data utilized were from 298 graduates of an associate degree nursing program in the Southeastern United States. Of the 298 graduates, 142 were Hispanic, 87 were Black, non-Hispanic, 54 White, non-Hispanic, and 15 reported as Others. The graduates took the NCLEX-RN for the first time during the years 2003–2005. This study was a predictive, correlational design that relied upon retrospective data. Point biserial correlations, and chi-square analyses were used to investigate relationships between 19 selected predictor variables and the dichotomous criterion variable, NCLEX-RN. The correlation and chi square findings indicated that men did better on the NCLEX-RN than women; Blacks had the highest failure rates, followed by Hispanics; older students were more likely to pass the exam than younger students; and students who passed the exam started and completed the nursing program with a higher grade point average, than those who failed the exam. Using logistic regression, five statistical models that used variables associated with learning and student performance on the NCLEX-RN were tested with a model adapted from Bloom's (1976) and Carroll's (1963) school learning theories. The derived model included: NCLEX-RNsuccess = f (Nurse Entrance Test and advanced medical-surgical nursing course grade achieved). The model demonstrates that student performance on the NCLEX-RN can be predicted by one pre-admission measure, and a program measure. The Assessment Technologies Institute achievement exit exam (an outcome measure) had no predictive value for student performance on the NCLEX-RN. The model developed accurately predicted 94% of the student's successful performance on the NCLEX-RN.

A heuristic algorithm to generate test program sequences for moving probe electronic test equipment

The electronics industry, is experiencing two trends one of which is the drive towards miniaturization of electronic products. The in-circuit testing predominantly used for continuity testing of printed circuit boards (PCB) can no longer meet the demands of smaller size circuits. This has lead to the development of moving probe testing equipment. Moving Probe Test opens up the opportunity to test PCBs where the test points are on a small pitch (distance between points). However, since the test uses probes that move sequentially to perform the test, the total test time is much greater than traditional in-circuit test. While significant effort has concentrated on the equipment design and development, little work has examined algorithms for efficient test sequencing. The test sequence has the greatest impact on total test time, which will determine the production cycle time of the product. Minimizing total test time is a NP-hard problem similar to the traveling salesman problem, except with two traveling salesmen that must coordinate their movements. The main goal of this thesis was to develop a heuristic algorithm to minimize the Flying Probe test time and evaluate the algorithm against a "Nearest Neighbor" algorithm. The algorithm was implemented with Visual Basic and MS Access database. The algorithm was evaluated with actual PCB test data taken from Industry. A statistical analysis with 95% C.C. was performed to test the hypothesis that the proposed algorithm finds a sequence which has a total test time less than the total test time found by the "Nearest Neighbor" approach. Findings demonstrated that the proposed heuristic algorithm reduces the total test time of the test and, therefore, production cycle time can be reduced through proper sequencing.