22 resultados para hypoxia, performance, training, repeated sprint training in hypoxia, RSH

em Digital Commons at Florida International University


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This study was conducted to examine how occupational therapists (OTs) practicing in the physical disabilities area received their training in the use of physical agent modalities (PAMs); to determine the frequency of PAMs usage by those therapists; and to obtain their opinions regarding the training of OTs and OT students in the administration of PAMs. Three hundred OTs practicing in physical diabilities (n = 194 returned) were surveyed. The most frequently used modalities were hot and cold packs, paraffin, and ultrasound. The least frequently used modalities were transcutaneous electrical stimulation (TENS) and whirlpool. On-the-job training was the most common educational method received by the respondents for PAMs usage. The respondents considered a combination of undergraduate education, fieldwork, continuing education and on-the-job training as the most appropriate educational setting for training in modalities. While few of the respondents received preparation in PAMs during entry-level academic programs, the majority felt that OT students should be trained in PAMs usage as part of their education curriculum. ^

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Different cultures and historical precedents produce a broad range of influences on the training of hotel managers in Europe and the United States. The author isolates a certain number of facts the nature of which clarify an understanding of two attitudes which complement each other to the benefit of their common objective - efficient professional training.

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Researchers and practitioners contend that hospitality management curricula tend to focus on teaching students technical skills they need to function effectively in the work- place but do not emphasize human and conceptual skills, one of which is leadership. Universities and companies strive to address leadership training, acknowledging that leadership is perhaps one of the most important roles any hospitality manager will fill and is probably least prepared for.

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Menu analysis is the gathering and processing of key pieces of information to make it more manageable and understand- able. Ultimately, menu analysis allows managers to make more informed decisions about prices, costs, and items to be included on a menu. The author discusses If labor as well as food casts need to be included in menu analysis and if managers need to categorize menu items differently when doing menu analysis based on customer eating patterns.

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Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

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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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Many firms from emerging markets flocked to developed countries at high cost with hopes of acquiring strategic assets that are difficult to obtain in home countries. Adequate research has focused on the motivations and strategies of emerging country firms' (ECFs') internationalization, while limited studies have explored their survival in advanced economies years after their venturing abroad. Due to the imprinting effect of home country institutions that inhibit their development outside their home market, ECFs are inclined to hire executives with international background and affiliate to world-wide organizations for the purpose of linking up with the global market, embracing multiple perspectives for strategic decisions, and absorbing the knowledge of foreign markets. However, the effects of such orientation on survival are under limited exploration. Motivated by the discussion above, I explore ECFs' survival and stock performance in a developed country (U.S.). Applying population ecology, signaling theory and institutional theory, the dissertation investigates the characteristics of ECFs that survived in the developed country (U.S.), tests the impacts of global orientation on their survival, and examines how global-oriented activities (i.e. joining United Nations Global Compact) affect their stock performance. The dissertation is structured in the form of three empirical essays. The first essay explores and compares different characteristics of ECFs and developed country firms (DCFs) that managed to survive in the U.S. The second essay proposes the concept of global orientation, and tests its influences on ECFs' survival. Employing signaling theory and institutional theory, the third essay investigates stock market reactions to announcements of United Nation Global Compact (UNGC) participation. The dissertation serves to explore the survival of ECFs in the developed country (U.S.) by comparison with DCFs, enriching traditional theories by testing non-traditional arguments in the context of ECFs' foreign operation, and better informing practitioners operating ECFs about ways of surviving in developed countries and improving stockholders' confidence in their future growth.

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Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

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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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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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Many firms from emerging markets flocked to developed countries at high cost with hopes of acquiring strategic assets that are difficult to obtain in home countries. Adequate research has focused on the motivations and strategies of emerging country firms' (ECFs') internationalization, while limited studies have explored their survival in advanced economies years after their venturing abroad. Due to the imprinting effect of home country institutions that inhibit their development outside their home market, ECFs are inclined to hire executives with international background and affiliate to world-wide organizations for the purpose of linking up with the global market, embracing multiple perspectives for strategic decisions, and absorbing the knowledge of foreign markets. However, the effects of such orientation on survival are under limited exploration. Motivated by the discussion above, I explore ECFs’ survival and stock performance in a developed country (U.S.). Applying population ecology, signaling theory and institutional theory, the dissertation investigates the characteristics of ECFs that survived in the developed country (U.S.), tests the impacts of global orientation on their survival, and examines how global-oriented activities (i.e. joining United Nations Global Compact) affect their stock performance. The dissertation is structured in the form of three empirical essays. The first essay explores and compares different characteristics of ECFs and developed country firms (DCFs) that managed to survive in the U.S. The second essay proposes the concept of global orientation, and tests its influences on ECFs’ survival. Employing signaling theory and institutional theory, the third essay investigates stock market reactions to announcements of United Nation Global Compact (UNGC) participation. The dissertation serves to explore the survival of ECFs in the developed country (U.S.) by comparison with DCFs, enriching traditional theories by testing non-traditional arguments in the context of ECFs’ foreign operation, and better informing practitioners operating ECFs about ways of surviving in developed countries and improving stockholders’ confidence in their future growth.

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Current demands for accountability in education emphasize outcome-based program evaluation and tie program funding to individual student performance. As has been the case for elementary and secondary programs, demands for accountability have increased pressure on adult educators to show evidence of the benefits of their programs in order to justify their financial support. In Florida, recent legislation fundamentally changes the delivery of adult education in the state by establishing a performance-based funding system that is based on outcomes related to the retention, completion, and employment of program participants.^ A performance-based funding system requires an evaluation process that stresses outcome indicators over indicators that focus on program context or process. Although the state has adopted indicators of program quality to evaluate its adult education programs, these indicators focus mostly on program processes rather than student outcomes. In addition, the indicators are not specifically tied to workforce development outcomes, a priority to federal and local funding agents.^ Improving the accountability of adult education programs and defining the role of these programs in Florida's Workforce Development System has become a priority to policy makers across the state. Another priority has been to involve adult education practitioners in every step of this process.^ This study was conducted in order to determine what performance indicators, as judged by the directors and supervisors of adult education programs in the state of Florida, are important and feasible in measuring the quality and effectiveness of these programs. The results of the study indicated that, both statewide and by region, the respondents consistently gave the highest ratings on both importance and feasibility to the indicators of Program Context, which reflect the needs, composition, and structure of the programs, and to the indicators of Educational Gain, which reflect learner progress in the attainment of basic skills and competencies. In turn, the respondents gave the lowest ratings on both importance and feasibility to the indicators in the areas of Return on State's Investment, Efficiency, Retention, and Workforce Training. In general, the indicators that received high ratings for importance also received high ratings for feasibility. ^

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In - Appraising Work Group Performance: New Productivity Opportunities in Hospitality Management – a discussion by Mark R. Edwards, Associate Professor, College of Engineering, Arizona State University and Leslie Edwards Cummings, Assistant Professor, College of Hotel Administration University of Nevada, Las Vegas; the authors initially provide: “Employee group performance variation accounts for a significant portion of the degree of productivity in the hotel, motel, and food service sectors of the hospitality industry. The authors discuss TEAMSG, a microcomputer based approach to appraising and interpreting group performance. TEAMSG appraisal allows an organization to profile and to evaluate groups, facilitating the targeting of training and development decisions and interventions, as well as the more equitable distribution of organizational rewards.” “The caliber of employee group performance is a major determinant in an organization's productivity and success within the hotel and food service industries,” Edwards and Cummings say. “Gaining accurate information about the quality of performance of such groups as organizational divisions, individual functional departments, or work groups can be as enlightening...” the authors further reveal. This perspective is especially important not only for strategic human resources planning purposes, but also for diagnosing development needs and for differentially distributing organizational rewards.” The authors will have you know, employee requirements in an unpredictable environment, which is what the hospitality industry largely is, are difficult to quantify. In an effort to measure elements of performance Edwards and Cummings look to TEAMSG, which is an acronym for Team Evaluation and Management System for Groups. They develop the concept. In discussing background for employees, Edwards and Cummings point-out that employees - at the individual level - must often possess and exercise varied skills. In group circumstances employees often work at locations outside of, or move from corporate unit-to-unit, as in the case of a project team. Being able to transcend individual-to-group mentality is imperative. “A solution which addresses the frustration and lack of motivation on the part of the employee is to coach, develop, appraise, and reward employees on the basis of group achievement,” say the authors. “An appraisal, effectively developed and interpreted, has at least three functions,” Edwards and Cummings suggest, and go on to define them. The authors do place a great emphasis on rewards and interventions to bolster the assertion set forth in their thesis statement. Edwards and Cummings warn that individual agendas can threaten, erode, and undermine group performance; there is no - I - in TEAM.

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This dissertation investigated the effects of a peer coaching relationship between a special education teacher and two general education teachers. More specifically, a two-tier multiple baseline design across subjects was used to evaluate the effects of peer coaching on the general education teachers' use of effective instructional practices (EIPs) and subsequent effects on the engagement rate and academic performance of students with and without disabilities. The peer coaching process included modeling, direct support, and feedback on the use of effective instructional practices including getting student attention, giving specific directions, asking specific questions with wait time, contingent positive reinforcement, positive error correction, precorrection, prompting, and proximity control. A 30-second partial interval recording procedure was used to observe the general education teachers' use of effective instructional practices and student engagement rates. Student participants' academic performance was measured using weekly quizzes. ^ Peer coaching resulted in an overall increase in the teachers' use of EIPs. One general education teacher had a 30% increase in average EIP use from 46% during the baseline phase to 76% during intervention. Student engagement for her two student participants with and without disabilities indicated an increase from 54% to 69% and from 47% to 65% respectively. Results for the second general education teacher indicated a 34% increase in average EIP use from 55% during the baseline to 89% during intervention. Student engagement for the two student participants with and without disabilities in her class increased from 48% to 83% and from 29% to 71% respectively. Student academic performance showed a small increase. In follow-up observations, the effects of peer coaching on teacher use of EIPs and student engagement and academic performance were maintained. ^ The results of this study suggest that using peer coaching to support general education teachers can be an effective method to improve the educational outcomes of students with and without disabilities in general education. Further research is needed to investigate the effects of peer coaching with other special and general educator partnerships and other student participants. ^