937 resultados para Android,Multihoming,LISP,LISPmob,Performance,Test,Development,Analysis


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Despite considerable and growing interest in the subject of academic researchers and practising managers jointly generating knowledge (which we term ‘co-production’), our searches of management literature revealed few articles based on primary data or multiple cases. Given the increasing commitment to co-production by academics, managers and those funding research, it seems important to strengthen the evidence base about practice and performance in co-production. Literature on collaborative research was reviewed to develop a framework to structure the analysis of this data and relate findings to the limited body of prior research on collaborative research practice and performance. This paper presents empirical data from four completed, large scale co-production projects. Despite major differences between the cases, we find that the key success factors and the indicators of performances are remarkably similar. We demonstrate many, complex influences between factors, between outcomes, and between factors and outcomes, and discuss the features that are distinctive to co-production. Our empirical findings are broadly consonant with prior literature, but go further in trying to understand success factors’ consequences for performance. A second contribution of this paper is the development of a conceptually and methodologically rigorous process for investigating collaborative research, linking process and performance. The paper closes with discussion of the study’s limitations and opportunities for further research.

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AOSD'03 Practitioner Report Performance analysis is motivated as an ideal domain for benefiting from the application of Aspect Oriented (AO) technology. The experience of a ten week project to apply AO to the performance analysis domain is described. We show how all phases of a performance analysts’ activities – initial profiling, problem identification, problem analysis and solution exploration – were candidates for AO technology assistance – some being addressed with more success than others. A Profiling Workbench is described that leverages the capabilities of AspectJ, and delivers unique capabilities into the hands of developers exploring caching opportunities.

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Organizations can use the valuable tool of data envelopment analysis (DEA) to make informed decisions on developing successful strategies, setting specific goals, and identifying underperforming activities to improve the output or outcome of performance measurement. The Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis highlights the advantages of using DEA as a tool to improve business performance and identify sources of inefficiency in public and private organizations. These recently developed theories and applications of DEA will be useful for policymakers, managers, and practitioners in the areas of sustainable development of our society including environment, agriculture, finance, and higher education sectors. All rights reserved.

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Communication through relay channels in wireless sensor networks can create diversity and consequently improve the robustness of data transmission for ubiquitous computing and networking applications. In this paper, we investigate the performances of relay channels in terms of diversity gain and throughput via both experimental research and theoretical analysis. Two relaying algorithms, dynamic relaying and fixed relaying, are utilised and tested to find out what the relay channels can contribute to system performances. The tests are based on a wireless relay sensor network comprising a source node, a destination node and a couple of relay nodes, and carried out in an indoor environment with rare movement of objects nearby. The tests confirm, in line with the analytical results, that more relay nodes lead to higher diversity gain in the network. The test results also show that the data throughput between the source node and the destination node is enhanced by the presence of the relay nodes. Energy consumption in association with the relaying strategy is also analysed. Copyright © 2009 John Wiley & Sons, Ltd.

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Environmental protectionism and sustainable development has been gaining increased attention among governments, investors and consumers alike. As a result, firms are facing growing pressure from the various stakeholders to improve their environmental performance. This study is focusing on the food industry, which in recent years has been a subject of increased scrutiny due to their role in resource consumption, waste generation and unsustainable production practices. Our research is aiming to examine how the financial community evaluates the environmental stewardship of food industry companies as proxied by market reactions in response to environmental news. Are all company related environmental news items evaluated equally, and which financial and non-financial firm-specific attributes can influence market responses? Have there been changes in reactions on the stock exchange in the past two decades?

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An assessment tool designed to measure a customer service orientation among RN's and LPN's was developed using a content-oriented approach. Critical incidents were first developed by asking two samples of healthcare managers (n = 52 and 25) to identify various customer-contact situations. The critical incidents were then used to formulate a 121-item instrument. Patient-contact workers from 3 hospitals (n = 102) completed the instrument along with the NEO-FFI, a measure of the Big Five personality factors. Concurrently, managers completed a performance evaluation scale on the employees participating in the study in order to determine the predictive validity of the instrument.^ Through a criterion-keying approach, the instrument was scaled down to 38 items. The correlation between HealthServe and the supervisory ratings of performance evaluation data supported the instrument's criterion-related validity (r =.66, p $<$.0001). Incremental validity of HealthServe over the Big Five was found with HealthServe accounting for 46% of the variance.^ The NEO-FFI was used to assess the correlation between personality traits and HealthServe. A factor analysis of HealthServe suggested 4 factors which were correlated with the NEO-FFI scores. Results indicated that HealthServe was related to Extraversion, Openness to Experience, Agreeableness, Conscientiousness and negatively related to Neuroticism.^ The benefits of the test construction procedure used here over the use of broad-based measures of personality were discussed as well as the limitations of using a concurrent validation strategy. Recommendations for future studies were provided. ^

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This study compared the performance of students who earned GED credentials in Florida with that of graduates of Florida high schools, when members of both groups enrolled for the first time in fall 1992 at an urban multicultural community college in south Florida. GED's and HSD's were matched on gender, race, age range, placement levels, and enrollment in college preparatory courses (reading, English, mathematics). The paired samples t-test compared course grades, first semester GPA, and total college GPA for the groups and subgroups of matched students at a probability level of .05. The McNemar test compared how many students in each group and subgroup re-enrolled for a second and third term, or ever; how many were placed on special academic status during their college enrollment; and how many graduated within 16 semesters. Differences between groups were found only for placement on probation—with HSD's on probation in significantly higher proportion than GED's. ^ Additional findings among subgroups revealed that male and Caucasian HSD subjects earned higher math grades than their GED counterparts. Male HSD's were more likely than male GED's to return to the college at some point after the first term. However, male HSD's were placed on probation in greater proportion than the GED's with whom they were matched. ^ Female GED's earned higher English grades and higher first semester and cumulative GPA's and returned to the college in greater proportion than their HSD counterparts. Black GED's earned higher first-semester GPA's, re-enrolled in terms 2 and 3 and graduated from the college in higher percentages than Black HSD's. Black HSD's were placed on probation in higher proportion than Black GED's. Lastly, greater percentages of HSD than GED subjects in the lowest age range (16–19) were placed on probation. ^ Results connected to the performance of Black GED subjects are likely to have been affected by the fact that 50% of Black study subjects had been born in Jamaica. The place of the GED in the constellation of methods for earning credit by examination is explored, future implications are discussed, and further study is recommended. ^

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Accounting students become practitioners facing ethical decision-making challenges that can be subject to various interpretations; hence, the profession is concerned with the appropriateness of their decisions. Moral development of these students has implications for a profession under legal challenges, negative publicity, and government scrutiny. Accounting students' moral development has been studied by examining their responses to moral questions in Rest's Defining Issues Test (DIT), their professional attitudes on Hall's Professionalism Scale Dimensions, and their ethical orientation-based professional commitment and ethical sensitivity. This study extended research in accounting ethics and moral development by examining students in a college where an ethics course is a requirement for graduation. ^ Knowledge of differences in the moral development of accounting students may alert practitioners and educators to potential problems resulting from a lack of ethical understanding as measured by moral development levels. If student moral development levels differ by major, and accounting majors have lower levels than other students, the conclusion may be that this difference is a causative factor for the alleged acts of malfeasance in the profession that may result in malpractice suits. ^ The current study compared 205 accounting, business, and nonbusiness students from a private university. In addition to academic major and completion of an ethics course, the other independent variable was academic level. Gender and age were tested as control variables and Rest's DIT score was the dependent variable. The primary analysis was a 2 x 3 x 3 ANOVA with post hoc tests for results with significant p-value of less than 0.05. ^ The results of this study reveal that students who take an ethics course appear to have a higher level of moral development (p = 0.013), as measured by the (DIT), than students at the same academic level who have not taken an ethics course. In addition, a statistically significant difference (p = 0.034) exists between freshmen who took an ethics class and juniors who did not take an ethics class. For every analysis except one, the lower class year with an ethics class had a higher level of moral development than the higher class year without an ethics class. These results appear to show that ethics education in particular has a greater effect on the level of moral development than education in general. Findings based on the gender specific analyses appear to show that males and females respond differently to the effects of taking an ethics class. The male students do not appear to increase their moral development level after taking an ethics course (p = 0.693) but male levels of moral development differ significantly (p = 0.003) by major. Female levels of moral development appear to increase after taking an ethics course (p = 0.002). However, they do not differ according to major (p = 0.097). ^ These findings indicate that accounting students should be required to have a class in ethics as part of their college curriculum. Students with an ethics class have a significantly higher level of moral development. The challenges facing the profession at the current time indicate that public confidence in the reports of client corporations has eroded and one way to restore this confidence could be to require ethics training of future accountants. ^

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Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

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The purpose of this study was to determine if there was a difference in the self-determined evaluations of work performance and support needs by adults with mental retardation in supported employment and in sheltered workshop environments. The instrument, Job Observation and Behavior Scale: Opportunity for Self-Determination (JOBS: OSD; Brady, Rosenberg, & Frain, 2006), was administered to 38 adults with mental retardation from sheltered workshops and 32 adults with mental retardation from supported employment environments. Cross-tabulations with Chi-square tests and independent samples t-tests were conducted to evaluate differences between the two groups, sheltered workshop and supported work. Two Multivariate Analyses of Variance (MANOVAs) were conducted to determine the effect of work environment on Quality of Performance (QP) and Types of Support (TS) test scores and their subscales. ^ This study found that there were significant differences between the groups on the QP Behavior and Job Duties subscales. The sheltered workshop group perceived themselves as performing significantly better on job duties than the supported work group. Conversely, the supported work group perceived themselves to have better behavior than the sheltered workshop group. However, there were no significant differences between groups in their perception of support needs for the three subscales. ^ The findings imply that work environment affects the self-determined evaluations of work performance by adults with mental retardation. Recommendations for further study include (a) detailing the characteristics of supported work and sheltered workshops that support and/or discourage self-determined behaviors, (b) exploring the behavior of adults with mental retardation in sheltered workshops and supported work environments, and (c) analysis of the support needs for and understanding of them by adults with mental retardation in sheltered workshops and in supported work environments. ^

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The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

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Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

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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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In this dissertation, I present an integrated model of organizational performance. Most prior research has relied extensively on testing individual linkages, often with cross-sectional data. In this dissertation, longitudinal unit-level data from 559 restaurants, collected over a one-year period, were used to test the proposed model. The model was hypothesized to begin with employee satisfaction as a key antecedent that would ultimately lead to improved financial performance. Several variables including turnover, efficiency, and guest satisfaction are proposed as mediators of the satisfaction-performance relationship. The current findings replicate and extend past research using individual-level data. The overall model adequately explained the data, but was significantly improved with an additional link from employee satisfaction to efficiency, which was not originally hypothesized. Management turnover was a strong predictor of hourly level team turnover, and both were significant predictors of efficiency. Full findings for each hypothesis are presented and practical organizational implications are given. Limitations and recommendations for future research are provided. ^

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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.