Academic literature on the topic 'Performance evaluation'

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Journal articles on the topic "Performance evaluation"

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Hangargi, Sumeet. "Performance Evaluation of Bimetallic Piston." International Journal of Psychosocial Rehabilitation 24, no. 4 (April 30, 2020): 5775–81. http://dx.doi.org/10.37200/ijpr/v24i4/pr2020383.

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Zhou, Jing Kun. "Thoughts on Improving Evaluation of Enterprise Employees’ Performances." Applied Mechanics and Materials 722 (December 2014): 396–99. http://dx.doi.org/10.4028/www.scientific.net/amm.722.396.

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As an important part of enterprise management, evaluation of employees’ performances is focused by more and more enterprise administrators. This paper briefly analyzes the reasons for failure evaluation of employees’ performances and provides some measures for improvement, including cultivating employees’ consciousness of treating performance evaluation in a correct way, paying attention to rationality of performance evaluation indicators, enhancing communications on performances, selecting performance evaluation subjects in a scientific way, strengthening trainings on performance evaluation for evaluators, comprehensively utilizing results of performance evaluation, doing work analysis well, classifying duties of posts, using proper methods of evaluation, establishing complaint mechanism for the evaluations, etc.
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Morita, Hiroshi, Kazuyuki Sekitani, Hiroshi Yabe, Tohru Ueda, and Hirofumi Fukuyama. "EDITORIAL INTRODUCTION : A SPECIAL ISSUE ON "OPERATIONS RESEARCH FOR PERFORMANCE EVALUATION"(Operations Research for Performance Evaluation)." Journal of the Operations Research Society of Japan 52, no. 2 (2009): 75. http://dx.doi.org/10.15807/jorsj.52.75.

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COTFAS, Petru-Adrian, Daniel-Tudor COTFAS, Octavian MACHIDON, and Cristina CIULAVU. "PERFORMANCE EVALUATION OF THE THERMOELECTRIC GENERATOR." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (June 24, 2016): 239–46. http://dx.doi.org/10.19062/2247-3173.2016.18.1.32.

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Dr. A. Elangovan, Dr A. Elangovan, and S. K. P. Palanisamy S. K. P. Palanisamy. "Performance Evaluation of Special Economic Zones." Indian Journal of Applied Research 3, no. 10 (October 1, 2011): 1–5. http://dx.doi.org/10.15373/2249555x/oct2013/23.

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Schettler, Daniel Philipp. "Performance: Differences in measuring performance." Humanities and Social Sciences Latvia 31, no. 1 (July 12, 2023): 65–79. http://dx.doi.org/10.22364/hssl.31.1.05.

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An important issue in human resources is the procedure of the employees’ performance evaluation. The appraisal is essential in the sense of employee appreciation and motivation. Most employers use a subjective performance evaluation of a single superior or a group of persons involved in the employee’s working processes. The subjective evaluation of a group or one person is often questioned about being appropriate. An often-named solution for a more objective criteria could be data driven performance measures. Professional sport provides a unique opportunity to compare objective and subjective performance evaluation measures. A data set of the German Bundesliga was used to test if the two different performance measure come to equal results. It is shown that differences in means exist but equivalence tests support the hypothesis that both measures could be treated as equal. In toto, it seems that in an environment where performance is relatively good to measure objective and subjective performance evaluations lead to equivalent results.
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Murata, Koichi, and Hiroshi Katayama. "AN EVALUATION OF FACTORY PERFORMANCE UTILIZED KPI/KAI WITH DATA ENVELOPMENT ANALYSIS(Operations Research for Performance Evaluation)." Journal of the Operations Research Society of Japan 52, no. 2 (2009): 204–20. http://dx.doi.org/10.15807/jorsj.52.204.

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Le Boudec, Jean-Yves. "Performance Evaluation." ACM SIGMETRICS Performance Evaluation Review 49, no. 4 (June 2, 2022): 20–23. http://dx.doi.org/10.1145/3543146.3543151.

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Lectures that use probability or statistics often appear complex to students, sometimes because the underlying stochastic models are not explicited. Writing a stochastic simulation program is a common exercise in a performance evaluation course, and we can view a simulation program as an implementation of a stochastic model. Thus, students who took such a course are trained to fully specify stochastic models, and this can help them fully understand probabilistic statements. We give examples in the context of random graphs as well as in the interpretation of residual scores in machine learning. Last we observe that Palm calculus, which is at the heart of classical queuing theory, can be used to provide important insights into sampling problems encountered in data collection tasks.
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Le Boudec, Jean-Yves. "Performance Evaluation." ACM SIGMETRICS Performance Evaluation Review 49, no. 4 (June 2, 2022): 20–23. http://dx.doi.org/10.1145/3543146.3543151.

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Lectures that use probability or statistics often appear complex to students, sometimes because the underlying stochastic models are not explicited. Writing a stochastic simulation program is a common exercise in a performance evaluation course, and we can view a simulation program as an implementation of a stochastic model. Thus, students who took such a course are trained to fully specify stochastic models, and this can help them fully understand probabilistic statements. We give examples in the context of random graphs as well as in the interpretation of residual scores in machine learning. Last we observe that Palm calculus, which is at the heart of classical queuing theory, can be used to provide important insights into sampling problems encountered in data collection tasks.
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Mui Law, Lin, Vicky Xiaohang Gao, and Hui Ling Ng. "Performance evaluation." Library Management 30, no. 1/2 (January 2, 2009): 77–87. http://dx.doi.org/10.1108/01435120910927547.

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Dissertations / Theses on the topic "Performance evaluation"

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Markomanolis, Georgios. "Performance Evaluation and Prediction of Parallel Applications." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2014. http://tel.archives-ouvertes.fr/tel-00951125.

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Analyzing and understanding the performance behavior of parallel applicationson various compute infrastructures is a long-standing concern in the HighPerformance Computing community. When the targeted execution environments arenot available, simulation is a reasonable approach to obtain objectiveperformance indicators and explore various ''what-if?'' scenarios. In thiswork we present a framework for the off-line simulation of MPIapplications. The main originality of our work with regard to the literature is to rely on\tit execution traces. This allows for an extreme scalability as heterogeneousand distributed resources can be used to acquire a trace. We propose a formatwhere for each event that occurs during the execution of an application we logthe volume of instructions for a computation phase or the bytes and the type ofa communication. To acquire time-independent traces of the execution of MPI applications, wehave to instrument them to log the required data. There exist many profilingtools which can instrument an application. We propose a scoring system thatcorresponds to our framework specific requirements and evaluate the mostwell-known and open source profiling tools according to it. Furthermore weintroduce an original tool called Minimal Instrumentation that was designed tofulfill the requirements of our framework. We study different instrumentationmethods and we also investigate several acquisition strategies. We detail thetools that extract the \tit traces from the instrumentation traces of somewell-known profiling tools. Finally we evaluate the whole acquisition procedureand we present the acquisition of large scale instances. We describe in detail the procedure to provide a realistic simulated platformfile to our trace replay tool taking under consideration the topology of thereal platform and the calibration procedure with regard to the application thatis going to be simulated. Moreover we present the implemented trace replaytools that we used during this work. We show that our simulator can predictthe performance of some MPI benchmarks with less than 11\% relativeerror between the real execution and simulation for the cases that there is noperformance issue. Finally, we identify the reasons of the performance issuesand we propose solutions.
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Skimmons, Brian E. "Automated performance evaluation technique." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23551.

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Sommers, Carol A. "Designing a performance evaluation system how common is a good performance evaluation model? /." Instructions for remote access. Click here to access this electronic resource. Access available to Kutztown University faculty, staff, and students only, 1995. http://www.kutztown.edu/library/services/remote_access.asp.

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Thesis (M.P.A.)--Kutztown University of Pennsylvania, 1995.
Source: Masters Abstracts International, Volume: 45-06, page: 2962. Abstract precedes thesis as preliminary leaves [1-2]. Typescript. Includes bibliographical references (leaves 75-79).
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Fowke, Robert Andrew. "Performance Measures for Managerial Decision Making: Performance Measurement Synergies in Multi-Attribute Performance Measurement Systems." PDXScholar, 2010. https://pdxscholar.library.pdx.edu/open_access_etds/164.

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This research tests for correlation between corporate performance and use of financial measures, nonfinancial measures, and number of balanced scorecard categories used. Literature notes a preference for managing by nonfinancial measures because financial measures are lagging indicators, but little empirical evidence is available on the relationship between nonfinancial measures and financial performance, and few companies are found to realize the benefits of nonfinancial measurements. The balanced scorecard has been studied to find the impact of diversity of performance measures, and anecdotal improvements have been reported, but there is a paucity of empirical evidence regarding how the use of a balanced scorecard impacts organizational performance. These issues are investigated in this research with a web based survey distributed to a sample of publicly traded companies using a systematic selection process based on randomly selected numbers generated for each 3-digit NAICS category. The dependent variable is a rank of high, medium or low performance based on 12-month rolling average stock price comparisons from January 2005 to January 2009. These averages are analyzed as a percent change for each company, with performance standardized by 3-digit NAICS category to eliminate cross industry variance in performance ranking. Kruskal-Wallis one-way ANOVA is used to test for correlation. High performers show greatest utilization of both financial and nonfinancial measures, followed by medium performers, with low performers utilizing both measures the least. Nonfinancial performance measures are more correlated to firm value than financial measures with the high performers' mean score for nonfinancial measures being higher than for financial measures. By contrast, medium and low performers exhibit the opposite: higher mean scores for financial measures than for nonfinancial measures [p ≤ 0.05 for nonfinancial measures and p ≤ 0.1 for financial measures]. Correlation is found to be borderline significant (p = 0.06) for the number of balanced scorecard categories used with high performers utilizing the highest number of categories and low performers utilizing the lowest number of categories [p = 0.009 with inclusion of two respondents reporting no usage of balanced scorecard categories].
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Dhandapani, Mangayarkarasi. "Performance evaluation of high performance parallel I/O." Master's thesis, Mississippi State : Mississippi State University, 2003. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07072003-155031/unrestricted/mythesis.pdf.

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Girona, Turell Sergi. "Performance Prediction and Evaluation Tools." Doctoral thesis, Universitat Politècnica de Catalunya, 2003. http://hdl.handle.net/10803/5974.

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La predicció és un concepte de recerca molt interessant. No es només predir el resultat futur, sinó que també cal predir el resultat conegut, a vegades anomenat validació.

L'aplicació de tècniques de predicció sobre el comportament de sistemes és sempre molt útil perquè ens ajuda a comprendre el funcionament del elements que estem analitzant.

Aquest treball va començar tot analitzant la influència de l'execució concurrent de diverses aplicacions de pas de missatges. Així, l'objectiu original era trobar i proposar uns algorismes de planificació de processos que obtinguessin un throughput màxim, equitatiu, i amb un rendiment adecuat del sistema.

Per a poder avaluar adecuadament aquestes polítiques de planificació, varem trobar que ens calien eines d'analisi. Dimemas i Paraver són les eines de l'entorn que anomenem DiP. Tot i que aqueste eines varem estar dissenyades fa més de deu anys, són vàlides i ampliables.

Dimemas es l'eina de predicció de rendiment. Tot fent ús de models senzills, pot predir el temps d'execució de les aplicacions de pas de missatges, fent servir un conjunt de paràmetres que modelitzen el funcionament del sistema. No és només una eina que prediu el temps d'execució, sinó que s'ha demostrat molt útil per entendre la influència dels diferents paràmetres del sistema en el temps de resposta de les aplicacions

L'eina d'anàlisi de l'entorn DiP s'anomena Paraver. Permet analitzar simultàniament moltes aplicacions i el sistema des de diferent punts de vista: analitzant els missatges, les contencions a la xarxa de comunicació, la planificació del processador.

Promenvir/ST-ORM és l'eina d'anàlisi estocàstic. Inclou utilitats que permeten analitzar la influència de qualsevol paràmetre del sistema, així com sintonitzar els paràmetres de simulació, per aconseguir que les prediccions s'aproximin a la realitat.

La qualitat i categoria de les decisions que varem prendre fa anys queda demostrada per la mètode de com cal utilitzar conjuntament totes les eines, i perquè són eines què es corresponen a l'estat de l'art actual.

Aquest treball inclou la descripció de les diferents eines, des de el punt de vista de disseny fins la seva utilització (en cert grau), la validació de Dimemas, el disseny conceptual de Promenvir, la presentació del mètode que cal emprar amb aquestes eines (incloent anàlisi d'aplicacions individuals fins a anàlisis més complex), i alguns dels nostres primers anàlisi sobre polítiques de planificació de processador.
Prediction is an interesting research topic. It is not only to predict the future result, but also to predict the past, often called validation. Applying prediction techniques to observed system behavior has always been extremely useful to understand the internals of the elements under analysis.

We have started this work to analyze the influence of several message passing application when running in parallel. The original objective was to find and propose a process scheduling algorithm that maximizes the system throughput, fair, proper system utilization.

In order to evaluate properly the different schedulers, it is necessary to use some tools. Dimemas and Paraver, conform the core of DiP environment. These tools has been designed ten years ago, but still valid and extensible.

Dimemas is a performance prediction tool. Using a single models, it capable to predict execution time for message passing applications, considering few system parameters for the system. It is useful not only to predict the result of an execution, but to understand the influence of the system parameters in the execution time of the application.

Paraver is the analysis tool of DiP environment. It allows the analysis of applications and system from several points of view: analyzing messages, contention in the interconnection network, processor scheduling.

Promenvir/ST-ORM is a stochastic analysis tool. It incorporates facilities to analyze the influence of any parameter in the system, as well as to tune the simulation parameters, so the prediction is close to reality.

The methodology on how to use these tools as a group to analyze the whole environment, and the fact that all those tools are State of the Art, demonstrates the quality of the decisions we made some years ago.

This work includes description of the different tools, from its internal design to some external utilization, the validation of Dimemas, the concept design of Promenvir, the architecture for Promenvir, the presentation of the methodology used with these tools (for simple application analysis to complex system analysis), and some of our first analyses on processor scheduling policies.
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Askeland, Christian Emil, Anders Emil Salvesen, and Arne Fjæren Østvold. "Senatus - Implementation and Performance Evaluation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for telematikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19076.

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Traffic anomaly detection in backbone networks has received increased at-tention from the research community over the last years. A variety of tech-niques and implementations has been proposed in this area, some which hasbecome commercial products. However, studies have revealed that theseproducts are hardly used, mainly because of high false-positive rates andthe fact that manual inspection of alarms is a time consuming task for thenetwork administrator.Senatus is a recently proposed technique for combined anomaly detectionand root-cause analysis, originally proposed by Atef Abdelkefi. In this the-sis, we provide a complete high-performance implementation of Senatus,including a web Dashboard with overview of anomalies and the possibil-ity for manual fine-tuning of parameters. Furthermore, we have verifiedSenatus performance by comparing Senatus with a implementation of awell-known histogram-based anomaly detection technique.Our results show that Senatus performs very well for detection scans, andthat it matches the histogram-based anomaly detector for Denial of Service-attacks.
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Valenzuela, German Eduardo Serna. "Performance evaluation of manufacturing systems." Thesis, University of Liverpool, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490908.

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Numerous approaches on manufacturing strategies have been formulated to address new challenges and to remain competitive in globalization. Within such a Performance measurement frameworks have been important in manufacturing has offered an effective approach for the analysis and quantification of continuous improvement of their operational performance of production production systems. Moreover, they are necessary to understand and monitor the manufacturing strategies and to compete in the market place. associated with the adoption of performance measures aligned with strategies is a key requirement for gaining competitive advantages. This research comprises the study of theoretical and empirical modelling of performance measures and the development of a new performance measurement framework applicable to manufacturing industry. The purpose of this research is to create a new performance measurement framework for the complete evaluation of manufacturing systems. The framework comprises a complete methodology to facilitate the definition of manufacturing strategy and manufacturing system behaviours. management systems. The creation of performance measurement frameworks Nowadays, manufacturing organizations have focused their attention on the , I variability of the production activities in order to increase the effectiveness of their performance measurement system. The performance measurement system includes the development of a performance measure allocation system to enable the correct allocation of performance measures to the problems encountered in manufacturing processes. The analysis of manufacturing process is an essential activity to identify main contributory causes which affect the overall performance of manufacturing systems. For that reason, the research provides a systematic review of the characteristics of performance measures to make inferences about manufacturing process behaviour and to establish most appropriate corrective actions and practice that lead companies to sustainable competitive advantage. Supplied by The British Library - 'The world's knowledge'
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Martell, Victor, and Aron Sandberg. "Performance Evaluation of A* Algorithms." Thesis, Blekinge Tekniska Högskola, Institutionen för kreativa teknologier, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-12900.

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Context. There have been a lot of progress made in the field of pathfinding. One of the most used algorithms is A*, which over the years has had a lot of variations. There have been a number of papers written about the variations of A* and in what way they specifically improve A*. However, few papers have been written comparing A* with several different variations of A*. Objectives. The objectives of this thesis is to find how Dijkstra's algorithm, IDA*, Theta* and HPA* compare against A* based on the variables computation time, number of opened nodes, path length as well as number of path nodes. Methods. To find the answers to the question in Objectives, an experiment was set up where all the algorithms were implemented and tested over a number of maps with varying attributes. Results. The experimental data is compiled in a table showing the result of the tested algorithms for computation time, number of opened nodes, path length and number of path nodes over a number of different maps as well as the average performance over all maps. Conclusions. A* is shown to perform well overall, with Dijkstra's algorithm trailing shortly behind in computation time and expanded nodes. Theta* finds the best path, with overall good computation time marred by a few spikes on large, open maps. HPA* performs poorly overall when fully computed, but has by far the best computation time and node expansion when partially pre-computed. IDA* finds the same paths as A* and Dijkstra's algorithm but has a notably worse computation time than the other algorithms and should generally be avoided on octile grid maps.
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Tekelmariam, Hailay, and Mekides Chane. "Evaluation of Smartphone Network Performance." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2646.

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Nowadays most Desktop based softwares, operating system (OS) and applications features are being adapted to Smartphones (SMPs). The simplicity and mobility of SMPs are some of the qualities which make them interesting to run different network applications. In order to develop mobile applications with efficient functionality and competitive in marketability, application developers need to have knowledge on network performance of SMPs. In this thesis, an experimental based methodology is provided to evaluate the effect of transmission patterns on One Way Delay (OWD), throughput and packet loss across designed setup for different SMPs. Based on these metrics the SMPs have been compared with each other under the same experimental setting with relatively higher accuracy of measurement techniques. For accurate measurement DAG 3.6E card together with GPS for synchronization is used to capture traffic for further analysis. To avoid undeterministic inputs in the network, the experiment is made to be in a controlled and continuously monitored wireless local area network. Moreover the nodes or sub networks constituting the entire network are evaluated to conceive the effects on the estimated output. From this work application developers will have the opportunity to design their application according to the network performance of SMPs and users are also able to select suitable applications and SMPs.
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Books on the topic "Performance evaluation"

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Dyckhoff, Harald, and Rainer Souren. Performance Evaluation. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38732-7.

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Hannover, Bettina. Evaluation of Performance. New York, NY: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-0632-0.

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Preiser, Wolfgang F. E., Andrea E. Hardy, and Ulrich Schramm, eds. Building Performance Evaluation. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-56862-1.

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Karasulu, Bahadir, and Serdar Korukoglu. Performance Evaluation Software. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6534-8.

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Puigjaner, Ramon, Nunzio N. Savino, and Bartomeu Serra, eds. Computer Performance Evaluation. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-68061-6.

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Aragon, George O. Portfolio performance evaluation. Boston: Now, 2008.

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Baks, Klaas. Bayesian performance evaluation. Cambridge, MA: National Bureau of Economic Research, 1999.

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Workplace performance evaluation. Vancouver, BC: EduServ, 1990.

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Deb, Arun K. Distribution system performance evaluation. Denver, CO: AWWA Research Foundation and American Water Works Association, 1995.

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Nambiar, Raghunath, and Meikel Poess, eds. Performance Evaluation and Benchmarking. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84924-5.

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Book chapters on the topic "Performance evaluation"

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Bryant, Peter T. "Evaluation of Performance." In Augmented Humanity, 199–223. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76445-6_7.

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AbstractAgents evaluate their performances to assess progress, learn, and improve. In doing so, they refer to criteria of various kinds. Some criteria are deeply encoded in mental models, organizational procedures, or cultural norms and logics, while other evaluative criteria are adaptive and may upregulate or downregulate, depending on the agent’s goals, expectations, and context. Here, too, digitalization is transformative. Artificial agents bring unprecedented power to the evaluation of performance, including the rapid intra-cyclical evaluation of ongoing processes. These mechanisms support feedforward guidance in real time. Therefore, when human and artificial agents combine in the evaluation of augmented performance, they face additional risks. Artificial evaluative processing could be fast and precise, while at the same time, human evaluation may be relatively sluggish and imprecise. Overall evaluations of performance could be distorted and dysfunctional.
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Dyckhoff, Harald, and Rainer Souren. "Main Performance Categories: Effectiveness and Efficiency." In Performance Evaluation, 1–18. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38732-7_1.

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Dyckhoff, Harald, and Rainer Souren. "Multi-criteria Production Theory: Foundation of Performance Evaluation." In Performance Evaluation, 19–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38732-7_2.

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Dyckhoff, Harald, and Rainer Souren. "Data Envelopment Methodology of Performance Evaluation." In Performance Evaluation, 47–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38732-7_3.

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Dyckhoff, Harald, and Rainer Souren. "Challenges of Performance Evaluation in Practice." In Performance Evaluation, 83–106. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38732-7_4.

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Dyckhoff, Harald, and Rainer Souren. "Correction to: Performance Evaluation." In Performance Evaluation, C1. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38732-7_5.

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Bredrup, Harald. "Performance Evaluation." In Performance Management, 191–98. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-1212-3_9.

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Hinsch, Martin. "Performance Evaluation." In ISO 9001:2015 for Everyday Operations, 49–52. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-25550-3_9.

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Lu, Tong, Shivakumara Palaiahnakote, Chew Lim Tan, and Wenyin Liu. "Performance Evaluation." In Video Text Detection, 247–54. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6515-6_10.

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Tian, Ye, Min Zhao, and Xinming Zhang. "Performance Evaluation." In SpringerBriefs in Computer Science, 45–55. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6523-1_6.

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Conference papers on the topic "Performance evaluation"

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Fleming, M. "Super Resolution Imaging: Performance Studies." In QUANTITATIVE NONDESTRUCTIVE EVALUATION. AIP, 2006. http://dx.doi.org/10.1063/1.2184600.

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Rover, Diane T. "Performance evaluation." In the 1994 ACM/IEEE conference. New York, New York, USA: ACM Press, 1994. http://dx.doi.org/10.1145/602770.602819.

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"Performance Evaluation." In Proceedings. 2006 31st IEEE Conference on Local Computer Networks. IEEE, 2006. http://dx.doi.org/10.1109/lcn.2006.322067.

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Mach, Pavel, and Robert Bestak. "WiMAX Performance Evaluation." In Sixth International Conference on Networking (ICN'07). IEEE, 2007. http://dx.doi.org/10.1109/icn.2007.107.

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Fayad, M. E. "Performance Evaluation Engine." In 2007 IEEE International Conference on Information Reuse and Integration. IEEE, 2007. http://dx.doi.org/10.1109/iri.2007.4296697.

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Howard, Stefen, and Jim Martin. "DOCSIS performance evaluation." In the 43rd annual southeast regional conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1167253.1167265.

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Panke, Karola, Tatjana Pladere, Mara Velina, Aiga Svede, Gatis Ikaunieks, and Gunta Krumina. "Ocular performance evaluation." In the 2nd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3309772.3309786.

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Kambhampati, Ashwin. "Robust Performance Evaluation." In EC '21: The 22nd ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3465456.3467529.

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Zaslavskiy, Mark, and Kirill Krinkin. "Geo2Tag performance evaluation." In 2012 12th Conference of Open Innovations Association (FRUCT) and Seminar on e-Travel. IEEE, 2012. http://dx.doi.org/10.23919/fruct.2012.8122103.

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Batra, Pooja, and Aman Jatain. "Measurement Based Performance Evaluation of DevOps." In 2020 International Conference on Computational Performance Evaluation (ComPE). IEEE, 2020. http://dx.doi.org/10.1109/compe49325.2020.9200149.

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Reports on the topic "Performance evaluation"

1

Harvey, Campbell, and Yan Liu. Rethinking Performance Evaluation. Cambridge, MA: National Bureau of Economic Research, March 2016. http://dx.doi.org/10.3386/w22134.

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Botlo, M., M. Jagielski, and A. Romero. EPICS performance evaluation. Office of Scientific and Technical Information (OSTI), September 1993. http://dx.doi.org/10.2172/10190661.

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Baks, Klaas, Andrew Metrick, and Jessica Wachter. Bayesian Performance Evaluation. Cambridge, MA: National Bureau of Economic Research, April 1999. http://dx.doi.org/10.3386/w7069.

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Hanssen, J. L., Christopher R. Ekstrom, and Warren F. Walls. High Performance Oscillator Evaluation. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada513242.

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Countryman, Jason. Performance Evaluation and Measurement. Office of Scientific and Technical Information (OSTI), May 2019. http://dx.doi.org/10.2172/1571793.

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Martin, Paul J. Model Performance and Evaluation. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada629080.

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Moore, R. T., R. Michael McCabe, and R. Allen Wilkinson. AFRS performance evaluation tests. Gaithersburg, MD: National Bureau of Standards, January 1988. http://dx.doi.org/10.6028/nbs.ir.88-3831.

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Wilson, III, and George R. Flash Point Performance Evaluation. Fort Belvoir, VA: Defense Technical Information Center, March 2014. http://dx.doi.org/10.21236/ada601268.

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Fujita, Jun-ichi, Jitsuji Ohtsuki, and Yoshihiko Shindo. Performance evaluation of PEFC stack. Office of Scientific and Technical Information (OSTI), December 1996. http://dx.doi.org/10.2172/460309.

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Gansler, Jacques S., and William Lucyshyn. Evaluation of Performance Based Logistics. Fort Belvoir, VA: Defense Technical Information Center, August 2006. http://dx.doi.org/10.21236/ada536805.

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