963 resultados para digital performance
Resumo:
As the first step toward developing performance benchmarks for non profit private clubs, the authors identify the criteria that club managers use to evaluate club performance. Responses from 254 club managers across the US. indicate that all 16 performance criteria included in the survey were utilized to some extent, but the top three were membership satisfaction, quality of services offered, and quality of staff.
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Context: Core strength training (CST) has been popular in the fitness industry for a decade. Although strong core muscles are believed to enhance athletic performance, only few scientific studies have been conducted to identify the effectiveness of CST on improving athletic performance. Objective: Identify the effects of a 6-wk CST on running kinetics, lower extremity stability, and running performance in recreational and competitive runners. Design and Setting: A test-retest, randomized control design was used to assess the effect of CST and no CST on ground reaction force (GRF), lower extremity stability scores, and running performance. Participants: Twenty-eight healthy adults (age, 36.9+9.4yrs, height, 168.4+9.6cm, mass, 70.1+15.3kg) were recruited and randomly divided into two groups. Main outcome Measures: GRF was determined by calculating peak impact vertical GRF (vGRF), peak active vGRF, duration of the breaking or horizontal GRF (hGRF), and duration of the propulsive hGRF as measured while running across a force plate. Lower extremity stability in three directions (anterior, posterior, lateral) was assessed using the Star Excursion Balance Test (SEBT). Running performance was determined by 5000 meter run measured on selected outdoor tracks. Six 2 (time) X 2 (condition) mixed-design ANOVA were used to determine if CST influences on each dependent variable, p < .05. Results: No significant interactions were found for any kinetic variables and SEBT score, p>.05. But 5000m run time showed significant interaction, p < .05. SEBT scores improved in both groups, but more in the experimental group. Conclusion: CST did not significantly influence kinetic efficiency and lower extremity stability, but did influence running performance.
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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^
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In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.
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This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as "Clickers", improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.
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During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.
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Objective: To evaluate the impact of alcohol use, which is widespread in human immunodeficiency virus (HIV)+ individuals, on highly active antiretroviral therapy (HAART)-associated immune and cognitive improvements and the relationship between those two responses. Methods: In a case-control longitudinal study, thymic volume, cognition, and immune responses were evaluated at baseline and after 6 months therapy in HIV+ and HIV- controls. Cognitive performance was evaluated using the HIV Dementia Score (HDS) and the California Verbal Learning Test (CVLT). Results: Prior to HAART, thymic volume varied considerably from 2.7 to 29.3 cm3 (11 ± 7.2 cm3). Thymic volume at baseline showed a significantly inverse correlation with the patient’s number of years of drinking (r2 = 0.207; p < 0.01), as well as HDS and the CVLT scores in both HIV-infected (r2 = 0.37, p = 0.03) and noninfected (r2 = 0.8, p = 0.01). HIV-infected individuals with a small thymic volume scored in the demented range, as compared with those with a larger thymus (7 ± 2.7 vs. 12 ± 2.3, p = 0.005). After HAART, light/moderate drinkers exhibited thymus size twice that of heavy drinkers (14.8 ± 10.4 vs. 6.9 ± 3.3 cm3). Conclusions: HAART-associated increases of thymus volume appear to be negatively affected by alcohol consumption and significantly related to their cognitive status. This result could have important clinical implications.
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This article reveals the median financial results for the club industry for 2011 using 24 financial ratios. The results are based on the submission of balance sheet and selected income statement numbers from 80 clubs. The ratios are reported as median results for the entire sample as well as the median results for the top and low performing clubs delineated by return on assets. The biggest differences between the two extreme groups of clubs are (1) average collection period, (2) operating cash flows to current liabilities and long-term debt, (3) fines interest earned, (4) fixed charge coverage ratio, (5) food and beverage inventory turnovers, (6) profit margin, (7) return on assets, (8) operating efficiency ratio, (9) labor cost percentage.
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This research examines the performance of Hong Kong hotel websites in terms of information quality, and compares the performance among different hotel categories. Different from exsisting theoretical studies analyzing hotel websites, this research incorporates the perceptions of hotel guests and practitioners in the evaluation development process. Empirical results reveal that significant differences exist in the performance scores of luxury, mid-priced, and economy hotels. The authors also discuss implications for hotel industry practitioners and policymakers.
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An assessment of how hotel guests view in-room entertainment-technology amenities was conducted to compare the importance of these technologies to how they performed. In-room entertainment technology continues to evolve in the hotel industry. However, given the multitude of entertainment products available in the marketplace today, hoteliers have little understanding of guests’ expectations and of which in-room entertainment-technology amenities will drive guest satisfaction and increase loyalty to the hotel brand. Given that technology is integral to a hotel stay, this study seeks to evaluate the importance and performance of in-room entertainment-technology amenities. Findings indicate that free-to-guest television (FTG TV) and high-speed Internet access were the two most important inroom entertainment-technology amenities when it comes to the selection of a hotel for both leisure and business travelers. The Importance/Satisfaction Matrix presented in the current study showed that many of the in-room entertainment-technology amenities are currently a low priority for guests. Keywords: importance-performance analysis, hotel, in-room entertainment technologies
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This study examined the relationships between gifted selection criteria used in the Dade County Public Schools of Miami, Florida and performance in sixth grade gifted science classes.^ The goal of the study was to identify significant predictors of performance in sixth grade gifted science classes. Group comparisons of performance were also made. Performance in sixth grade gifted science was defined as the numeric average of nine weeks' grades earned in sixth grade gifted science classes.^ The sample consisted of 100 subjects who were formerly enrolled in sixth grade gifted science classes over two years at a large, multiethnic public middle school in Dade County.^ The predictors analyzed were I.Q. score (all scales combined), full scale I.Q. score, verbal scale I.Q. score, performance scale I.Q. score, combined Stanford Achievement Test (SAT) score (Reading Comprehension plus Math Applications), SAT Reading Comprehension score, and SAT Math Applications score. Combined SAT score and SAT Math Applications score were significantly positively correlated to performance in sixth grade gifted science. Performance scale I.Q. score was significantly negatively correlated to performance in sixth grade gifted science. The other predictors examined were not significantly correlated to performance.^ Group comparison results showed the mean average of nine weeks grades for the full scale I.Q. group was greater than the verbal and performance scale I.Q. groups. Females outperformed males to a highly significant level. Mean g.p.a. for ethnic groups was greatest for Asian students, followed by white non-Hispanic, Hispanic, and black. Students not receiving a lunch subsidy outperformed those receiving subsidies.^ Comparisons of performance based on gifted qualification plan showed the mean g.p.a. for traditional plan and Plan B groups were not different. Mean g.p.a. for students who qualified for gifted using automatic Math Applications criteria was highest, followed by automatic Reading Comprehension criteria and Plan B Matrix score. Both automatic qualification groups outperformed the traditional group. The traditional group outperformed the Plan B Matrix group. No significant differences in mean g.p.a. between the Plan B subgroups and the traditional plan group were found. ^
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Recently, researchers have begun to investigate the benefits of cross-training teams. It has been hypothesized that cross-training should help improve team processes and team performance (Cannon-Bowers, Salas, Blickensderfer, & Bowers, 1998; Travillian, Volpe, Cannon-Bowers, & Salas, 1993). The current study extends previous research by examining different methods of cross-training (positional clarification and positional modeling) and the impact they have on team process and performance in both more complex and less complex environments. One hundred and thirty-five psychology undergraduates were placed in 45 three-person teams. Participants were randomly assigned to roles within teams. Teams were asked to “fly” a series of missions on a PC-based helicopter flight simulation. ^ Results suggest that cross-training improves team mental model accuracy and similarity. Accuracy of team mental models was found to be a predictor of coordination quality, but similarity of team mental models was not. Neither similarity nor accuracy of team mental models was found to be a predictor of backup behavior (quality and quantity). As expected, both team coordination (quality) and backup behaviors (quantity and quality) were significant predictors of overall team performance. Contrary to expectations, there was no interaction between cross-training and environmental complexity. Results from this study further cross-training research by establishing positional clarification and positional modeling as training strategies for improving team performance. ^
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One of the most important goals of American educational institutions over the past 47 years has been the desegregation of pubic schools. This goal reflected the Supreme Court's decision in Brown v. Board of Education that segregated schools are inherently unequal and deny segregated minority students equal educational opportunities as mandated by the United States Constitution. This study examined the extent, nature, and causes of segregation in the Miami-Dade County Public Schools and the effects of segregation on the educational performance of minority students. ^ Research questions were analyzed using demographic data from the United States Census Bureau, the Metro-Dade County Planning Department, the United States Commission on Civil Rights, the United States Department of Education, and the Miami Dade County Public Schools. The extent of residential and school segregation in MiamiDade County was measured using the Dissimilarity Index. Historical and sociological literature were analyzed to explain the causes of school segregation, the socioeconomic characteristics of segregated minority students, and the relationship between school segregation and equal educational opportunities. A causal-comparative research method was chosen because it is the most appropriate method to compare the educational performance of minority students in segregated schools with the educational performance of minority students in desegregated schools. ^ The results of this study demonstrates that there is a high degree of residential and school segregation in Miami-Dade County, Florida. Furthermore, the Miami-Dade County Public Schools are characterized by a high degree of socioeconomic segregation. This is significant considering that the socioeconomic status of a student's peers is, after the student's family background, the most influential factor in determining academic performance. Clearly, schools and other social institutions must continue efforts to throughly desegregate the school district and improve minority student academic performance. A racially and economically desegregated school system would constitute an important component in Miami-Dade County's efforts to provide equal educational opportunities to all students. ^
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The purpose of this study was to determine the degree to which the Big-Five personality taxonomy, as represented by the Minnesota Multiphasic Personality Inventory (MMPI), California Psychological Inventory (CPI), and Inwald Personality Inventory (IPI) scales, predicted a variety of police officer job performance criteria. Data were collected archivally for 270 sworn police officers from a large Southeastern municipality. Predictive data consisted of scores on the MMPI, CPI, and IPI scales as grouped in terms of the Big-Five factors. The overall score on the Wonderlic was included in order to assess criterion variance accounted for by cognitive ability. Additionally, a psychologist's overall rating of predicted job fit was utilized to assess the variance accounted for by a psychological interview. Criterion data consisted of supervisory ratings of overall job performance, State Examination scores, police academy grades, and termination. Based on the literature, it was hypothesized that officers who are higher on Extroversion, Conscientiousness, Agreeableness, Openness to Experience, and lower on Neuroticism, otherwise known as the Big-Five factors, would outperform their peers across a variety of job performance criteria. Additionally, it was hypothesized that police officers who are higher in cognitive ability and masculinity, and lower in mania would also outperform their counterparts. Results indicated that many of the Big-Five factors, namely, Neuroticism, Conscientiousness, Agreeableness, and Openness to Experience, were predictive of several of the job performance criteria. Such findings imply that the Big-Five is a useful predictor of police officer job performance. Study limitations and implications for future research are discussed. ^
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The present investigation examined the relationships among personality (as conceptualized by the Big Five Factors), leader-member exchange (LMX) quality, action control, organizational citizenship behaviors (OCB), and overall job performance (OJP). Two mediator variables were proposed and tested in this study: LMX and Action Control. Two-hundred and seven currently employed regular elementary school classroom teachers provided data during the 2000–2001 academic school year. Teachers provided personality, LMX quality (member or subordinate perspective), action control, job tenure, and demographic data. Nine school administrators (i.e., Principals, Assistant Principals) were the source for supervisor ratings of OCB, OJP, and LMX quality (leader or supervisor perspective). In eight of the nine total schools, teachers completed questionnaires during an after-school teacher gathering; in the remaining school location questionnaires were dropped off, distributed to teachers, and re-collected two weeks later. Results indicated a significant relationship between the OCB scale and overall supervisory ratings of OJP. The relationship among the big five factors of personality and OJP did not reach statistical significance, nor did the relationships among personality and OCB. The data indicated that none of the teacher tenure variables (i.e., teacher, school, or time worked with principal tenure) moderated the personality-OCB relationship nor the personality-OJP relationship. Finally, a review of the correlations among the variables of interest precluded conducting a mediation between personality-performance by OCB, mediation of personality-OCB by action control, and mediation of personality-OCB by LMX. In conclusion, the data reveal that personality was not significantly correlated with supervisory ratings of OJP or significantly related to supervisory ratings of overall OCB. Moreover, LMX quality and action control did not mediate the relationships between Personality-OJP nor the Personality-OCB relationship. Significant relationships were found between disengagement and overall LMX quality and between Initiative and overall LMX quality (both LMX-Teacher perspectives) as well as between personality variables and both Disengagement and Initiative action control variables. Despite the limitations inherent in this study, these latter findings suggest “lessons” for teachers and school administrators alike. ^