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Artykuły w czasopismach na temat "Performance metrics"
Mary, A. Viji Amutha, i Dr T. Jebarajan Dr. T. Jebarajan. "Performance Metrics of Clustering Algorithm". Indian Journal of Applied Research 4, nr 8 (1.10.2011): 165–67. http://dx.doi.org/10.15373/2249555x/august2014/47.
Pełny tekst źródłaPijpers, Frank P. "Performance metrics". Astronomy & Geophysics 47, nr 6 (grudzień 2006): 6.17–6.18. http://dx.doi.org/10.1111/j.1468-4004.2006.47617.x.
Pełny tekst źródłaM. Taaffe, Kevin, Robert William Allen i Lindsey Grigg. "Performance metrics analysis for aircraft maintenance process control". Journal of Quality in Maintenance Engineering 20, nr 2 (6.05.2014): 122–34. http://dx.doi.org/10.1108/jqme-07-2012-0022.
Pełny tekst źródłaLiu, Yangguang, Yangming Zhou, Shiting Wen i Chaogang Tang. "A Strategy on Selecting Performance Metrics for Classifier Evaluation". International Journal of Mobile Computing and Multimedia Communications 6, nr 4 (październik 2014): 20–35. http://dx.doi.org/10.4018/ijmcmc.2014100102.
Pełny tekst źródłaBaker, Noel C., i Patrick C. Taylor. "A Framework for Evaluating Climate Model Performance Metrics". Journal of Climate 29, nr 5 (26.02.2016): 1773–82. http://dx.doi.org/10.1175/jcli-d-15-0114.1.
Pełny tekst źródłaLi, Shanshan, i Weiyang Sun. "Image Encryption Performance Evaluation Based on Poker Test". Advances in Multimedia 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/6714164.
Pełny tekst źródłaCzachura, Agnieszka, Jouri Kanters, Niko Gentile i Maria Wall. "Solar Performance Metrics in Urban Planning: A Review and Taxonomy". Buildings 12, nr 4 (23.03.2022): 393. http://dx.doi.org/10.3390/buildings12040393.
Pełny tekst źródłaNochur, A., H. Vedam i J. Koene. "Alarm Performance Metrics". IFAC Proceedings Volumes 34, nr 27 (czerwiec 2001): 203–8. http://dx.doi.org/10.1016/s1474-6670(17)33592-9.
Pełny tekst źródłaLoo, Jessica, Traci E. Clemons, Emily Y. Chew, Martin Friedlander, Glenn J. Jaffe i Sina Farsiu. "Beyond Performance Metrics". Ophthalmology 127, nr 6 (czerwiec 2020): 793–801. http://dx.doi.org/10.1016/j.ophtha.2019.12.015.
Pełny tekst źródłaDeLozier, Randall, i Neil Snyder. "ENGINEERING PERFORMANCE METRICS". INCOSE International Symposium 3, nr 1 (lipiec 1993): 599–605. http://dx.doi.org/10.1002/j.2334-5837.1993.tb01632.x.
Pełny tekst źródłaRozprawy doktorskie na temat "Performance metrics"
Sundfors, David. "Performance Metrics for Sustainability Value". Licentiate thesis, KTH, Bygg- och fastighetsekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-200315.
Pełny tekst źródłaQC 20170124
Akcay, Koray. "Performance Metrics For Fundamental Estimation Filters". Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606510/index.pdf.
Pełny tekst źródłaAlpha-Beta Filter, Alpha-Beta-Gamma Filter, Constant Velocity (CV) Kalman Filter, Constant Acceleration (CA) Kalman Filter, Extended Kalman Filter, 2-model Interacting Multiple Model (IMM) Filter and 3-model IMM with respect to their resource requirements and performance. In resource requirement part, fundamental estimation filters are compared according to their CPU usage, memory needs and complexity. The best fundamental estimation filter which needs very low resources is the Alpha-Beta-Filter. In performance evaluation part of this thesis, performance metrics used are: Root-Mean-Square Error (RMSE), Average Euclidean Error (AEE), Geometric Average Error (GAE) and normalized form of these. The normalized form of performance metrics makes measure of error independent of range and the length of trajectory. Fundamental estimation filters and performance metrics are implemented in MATLAB. MONTE CARLO simulation method and 6 different air trajectories are used for testing. Test results show that performance of fundamental estimation filters varies according to trajectory and target dynamics used in constructing the filter. Consequently, filter performance is application-dependent. Therefore, before choosing an estimation filter, most probable target dynamics, hardware resources and acceptable error level should be investigated. An estimation filter which matches these requirements will be &lsquo
the best estimation filter&rsquo
.
Tucker, Christopher John. "Performance metrics for network intrusion systems". Thesis, University of Plymouth, 2013. http://hdl.handle.net/10026.1/1547.
Pełny tekst źródłaCirtita, Horatiu. "Performance Metrics in Downstream Supply Chain". Doctoral thesis, Università degli studi di Padova, 2008. http://hdl.handle.net/11577/3425091.
Pełny tekst źródłaDietrich, Nathan S. "Performance metrics for correlation and tracking algorithms". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA391959.
Pełny tekst źródłaWanderman-Milne, Skye A. "Virtualized application performance prediction using system metrics". Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/77450.
Pełny tekst źródłaCataloged from PDF version of thesis.
Includes bibliographical references (p. 79-80).
Virtualized datacenter administrators would like to consolidate virtual machines (VMs) onto as few physical hosts as possible in order to decrease costs, but must leave enough physical resources for each VM to meet application service level objectives (SLOs). The threshold between good and bad performance in terms of resource settings, however, is hard to determine and rarely static due to changing workloads and resource usage. Thus, in order to avoid SLO violations, system administrators must err on the side of caution by running fewer VMs per host than necessary or setting reservations, which prevents resources from being shared. To ameliorate this situation, we are working to design and implement a system that automatically monitors VM-level metrics to predict impending application SLO violations, and takes appropriate action to prevent the SLO violation from occurring. So far we have implemented the performance prediction, which is detailed in this document, while the preventative actions are left as future work. We created a three-stage pipeline in order to achieve scalable performance prediction. The three stages are prediction, which predicts future VM ESX performance counter values based on current time-series data; aggregation, which aggregates the predicted VM metrics into a single set of global metrics; and finally classification, which for each VM classifies its performance as good or bad based on the predicted VM counters and the predicted global state. Prediction of each counter is performed by a least-squares linear fit, aggregation is performed simply by summing each counter across all VMs, and classification is performed using a support vector machine (SVM) for each application. In addition, we created an experimental system running a MongoDB instance in order to test and evaluate our pipeline implementation. Our results on this experimental system are promising, but further research will be necessary before applying these techniques to a production system.
by Skye A. Wanderman-Milne.
M.Eng.
Burdett, Yan Liu. "Correlation of Software Quality Metrics and Performance". NSUWorks, 2012. http://nsuworks.nova.edu/gscis_etd/109.
Pełny tekst źródłaJackson, Kenneth J. "Forecast error metrics for Navy inventory management performance". Thesis, Monterey, California. Naval Postgraduate School, 2011. http://hdl.handle.net/10945/5756.
Pełny tekst źródłaThis research establishes metrics for determining overall Navy secondary inventory forecasting accuracy when compared to actual demands at the Naval Inventory Control Point (NAVICP). Specifically, two performance metrics are introduced: the average performance index (API) and the median absolute deviation performance index (MPI). API measures forecasting accuracy of secondary inventory when compared against demand or forecast performance over a four-quarter period. MPI measures the quarterly variability of forecast errors over the same period. The API and MPI metrics allow for the identification of poorly forecasted NAVICP secondary inventory items. The metrics can be applied to entire inventories or subsets of items based on type, demand, or cost. In addition, the API metric can be used to show overall inventory performance, providing NAVICP with a graphical means to assess forecasting performance improvements (or degradations) over time. The new forecasting accuracy methods developed in this research will allow the Navy to continually gauge the overall health of their inventory management practices and provide a method for improving forecasting accuracy. Additionally, they will assist NAVICP in complying with DoD directives that require NAVICP to monitor and continually develop improvements to inventory management practices.
Forman, Rachel Emily. "Objective performance metrics for improved space telerobotics training". Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68408.
Pełny tekst źródłaCataloged from PDF version of thesis.
Includes bibliographical references (p. 47-50).
NASA astronauts undergo many hours of formal training and self-study to gain proficiency in space teleoperation tasks. After each lesson, instructors score an astronaut's performance in several broad skill categories, including 'General Situational Awareness', 'Maneuvers/Task Performance', and 'Hand- Controller Techniques'. A plus, check, or minus indicates that the student is ahead of, at, or behind the expected skill level. The scoring of the final evaluation for a robotics training course is also largely subjective, with the instructor designating an integer score for the student between 1 (Unsatisfactory) and 5 (Strong) in the same skill categories. This thesis research project was designed to: (1) consider the variety of quantitative metrics that could be embedded into a space robotics training simulation, and (2) investigate at what point and by what means it is most constructive for performance assessment to be revealed to an operator-in-training. We reviewed the current largely qualitative space robotics performance metrics, as well as new quantitative kinematic metrics of manual control skills-including those explored thus far only in laboratory experiments-and additional measures of executive function and supervisory control performance. Kinematic metrics include quantitative measures such as rate of change of linear and rotational acceleration. Potential measures of executive function and supervisory control include camera selection and clearance monitoring. To instantiate our ideas, we chose a specific "fly-to" space telerobotics task taught in the early phases of NASA Generic Robotics Training (GRT) and developed a pilot training experiment (n=16) using our virtual robotics training workstation. Our goal was to evaluate potential performance metrics designed to encourage use of multi-axis control, and to compare real-time ("live") performance feedback alternatives (live visual vs. live aural vs. none). Movement time decreased and multi-axis and bimanual control use gradually increased across trials. All subjects had the opportunity to view post-trial performance feedback including these metrics. Although our subjects overwhelmingly preferred the live, visual feedback condition, no reliable additional effects of live feedback condition were found, except perhaps among the more experienced subjects. However, the experiment demonstrated that embedded performance metrics potentially could quantify and improve some important aspects of GRT evaluations.
Supported by the National Space Biomedical Research Institute through NASA NCC9-58
by Rachel Emily Forman.
S.M.
Wolbert, Daniel (Daniel Joseph). "Utilization of visual metrics to drive intended performance". Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39689.
Pełny tekst źródłaIncludes bibliographical references.
In recent years the American industrial landscape has undergone tremendous change as companies have worked to adopt Lean practices. This transformation has been difficult, but necessary, as American companies work to remain competitive with foreign competitors. A key enabler of these Lean transformations has been the use of visual metrics to communicate how a process has performed as well as to set goals for future performance. The challenge is to first identify what data is available and then create metrics that encourage and reward Lean behaviors. This thesis explores the introduction of visual metrics for a part inspection process at the Raytheon Company. Prior to the introduction of these metrics, there was limited ability to determine how the process was performing. As a result, downstream customers were able to track when a part entered the inspection process but were unable to predict when the inspection would be completed. This introduced a risk to the process and created a sense of frustration through the facility. The visual metrics for the inspection area were created on a series of visual dashboards that display common Lean metrics, such as cycle time and backlog (or work-in-process). Through these dashboards the area will be able to understand how it is performing and initiate continuous improvement projects to improve performance.
by Daniel Wolbert.
S.M.
M.B.A.
Książki na temat "Performance metrics"
Boyd, William J., Ann Brockhaus, Matthew R. Chini, Paul A. Esposito, Kul B. Garg, Jonathan M. Haas, Judy L. Jarrell i in., red. Industrial Hygiene Performance Metrics. 2700 Prosperity Ave., Suite 250 Fairfax, VA 22031: American Industrial Hygiene Association, 2001. http://dx.doi.org/10.3320/978-1-931504-12-6.
Pełny tekst źródłaAmerican Industrial Hygiene Association. Metrics Subcommittee., red. Industrial hygiene performance metrics. Fairfax, VA: American Industrial Hygiene Association, 2001.
Znajdź pełny tekst źródłaLehmann, Donald R. Marketing metrics and financial performance. Cambridge, Mass: Marketing Science Institute, 2006.
Znajdź pełny tekst źródłaAlbert, Sylvie, i Manish Pandey. Performance Metrics for Sustainable Cities. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003096566.
Pełny tekst źródłaSamur, Evren. Performance Metrics for Haptic Interfaces. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4225-6.
Pełny tekst źródłaLehmann, Donald R. Marketing metrics and financial performance. Cambridge, Mass: Marketing Science Institute, 2006.
Znajdź pełny tekst źródłaLehmann, Donald R. Marketing metrics and financial performance. Cambridge, Mass: Marketing Science Institute, 2006.
Znajdź pełny tekst źródłaservice), SpringerLink (Online, red. Performance Metrics for Haptic Interfaces. London: Springer London, 2012.
Znajdź pełny tekst źródłaTouran, Northeastern University Ali. Performance Metrics for Publicâ€"Private Partnerships. Washington, D.C.: Transportation Research Board, 2021. http://dx.doi.org/10.17226/26171.
Pełny tekst źródłaKounev, Samuel, Ian Gorton i Kai Sachs, red. Performance Evaluation: Metrics, Models and Benchmarks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69814-2.
Pełny tekst źródłaCzęści książek na temat "Performance metrics"
Goldshtein, Sasha, Dima Zurbalev i Ido Flatow. "Performance Metrics". W Pro .NET Performance, 1–6. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4459-2_1.
Pełny tekst źródłaTokhi, M. O., M. A. Hossain i M. H. Shaheed. "Performance Metrics". W Parallel Computing for Real-time Signal Processing and Control, 81–110. London: Springer London, 2003. http://dx.doi.org/10.1007/978-1-4471-0087-4_4.
Pełny tekst źródłaCarstens, Deborah Sater, i Gary L. Richardson. "Performance Metrics". W Project Management Tools and Techniques, 233–44. Second Edition. | Boca Raton : CRC Press, 2019. | Revised edition of Project management tools and techniques, [2013]: CRC Press, 2019. http://dx.doi.org/10.1201/9780429263163-17.
Pełny tekst źródłaSproull, ByBob. "Performance Metrics". W The Focus and Leverage Improvement Book, 191–206. 1 Edition. | New York, NY : Taylor & Francis, [2019]: Productivity Press, 2018. http://dx.doi.org/10.4324/9780429444456-10.
Pełny tekst źródłaLeasure, Bruce, David J. Kuck, Sergei Gorlatch, Murray Cole, Gregory R. Watson, Alain Darte, David Padua i in. "Performance Metrics". W Encyclopedia of Parallel Computing, 1522–25. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-09766-4_2182.
Pełny tekst źródłaKurtz, David. "Performance Metrics". W PeopleSoft for the Oracle DBA, 213–67. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3708-2_9.
Pełny tekst źródłaEeckhout, Lieven. "Performance Metrics". W Computer Architecture Performance Evaluation Methods, 5–14. Cham: Springer International Publishing, 2010. http://dx.doi.org/10.1007/978-3-031-01727-8_2.
Pełny tekst źródłaSproull, Bob. "Performance Metrics". W Learning from the Past, Present, and Future to Drive Profits to New Levels, 265–86. New York: Productivity Press, 2023. http://dx.doi.org/10.4324/9781003462385-19.
Pełny tekst źródłaLink, Albert N., i John T. Scott. "Performance Evaluation Metrics". W Public Accountability, 17–21. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5639-8_4.
Pełny tekst źródłaKasilingam, Raja G. "Logistics performance metrics". W Logistics and Transportation, 214–34. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5277-2_9.
Pełny tekst źródłaStreszczenia konferencji na temat "Performance metrics"
Mackey, Jamie. "UDOT Signal Performance Metrics: New and Upcoming Metrics". W Automated Traffic Signal Performance Measure Workshop. Purdue University, 2016. http://dx.doi.org/10.5703/1288284316023.
Pełny tekst źródłaTalbot, R. G., Chris R. Benn i Rene G. M. Rutten. "Telescope performance metrics". W Astronomical Telescopes and Instrumentation, redaktor Peter J. Quinn. SPIE, 2002. http://dx.doi.org/10.1117/12.460734.
Pełny tekst źródłaStevenson, Scott. "Maintaining Signal Performance Metrics". W Automated Traffic Signal Performance Measure Workshop. Purdue University, 2016. http://dx.doi.org/10.5703/1288284316040.
Pełny tekst źródłaHuang, Hui-Min, i Seungbin Moon. "Session details: Measures & metrics". W PerMIS '10: Performance Metrics for Intelligent Systems. New York, NY, USA: ACM, 2010. http://dx.doi.org/10.1145/3260126.
Pełny tekst źródłaFarnsworth, Grant. "UDOT Automated Freeway Performance Metrics". W Automated Traffic Signal Performance Measure Workshop. Purdue University, 2016. http://dx.doi.org/10.5703/1288284316026.
Pełny tekst źródłaMackey, Jamie. "UDOT Signal Performance Metrics: Configuration". W Automated Traffic Signal Performance Measure Workshop. Purdue University, 2016. http://dx.doi.org/10.5703/1288284316039.
Pełny tekst źródłaKonell, Jeremiah P., Jack Van Schenck, Joseph P. Bratton i Steven J. Polasik. "Practical IMP Performance Metrics". W 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64528.
Pełny tekst źródłaBrunnert, Andreas. "Green Software Metrics". W ICPE '24: 15th ACM/SPEC International Conference on Performance Engineering. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3629527.3652883.
Pełny tekst źródłaBalakirsky, Stephen, Thomas Kramer i Frederick Proctor. "Metrics for mixed pallet stacking". W the 10th Performance Metrics for Intelligent Systems Workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/2377576.2377587.
Pełny tekst źródłaBalakirsky, Stephen, i Henrik Christensen. "Session details: Performance metrics for mixed palletizing operations". W PerMIS '10: Performance Metrics for Intelligent Systems. New York, NY, USA: ACM, 2010. http://dx.doi.org/10.1145/3260127.
Pełny tekst źródłaRaporty organizacyjne na temat "Performance metrics"
Stephan, E. IP Performance Metrics (IPPM) Metrics Registry. RFC Editor, sierpień 2005. http://dx.doi.org/10.17487/rfc4148.
Pełny tekst źródłaDuffield, N., A. Morton i J. Sommers. Loss Episode Metrics for IP Performance Metrics (IPPM). RFC Editor, maj 2012. http://dx.doi.org/10.17487/rfc6534.
Pełny tekst źródłaDietz, R., i R. Cole. Transport Performance Metrics MIB. RFC Editor, sierpień 2005. http://dx.doi.org/10.17487/rfc4150.
Pełny tekst źródłaBagnulo, M., B. Claise, P. Eardley, A. Morton i A. Akhter. Registry for Performance Metrics. RFC Editor, listopad 2021. http://dx.doi.org/10.17487/rfc8911.
Pełny tekst źródłaDemichelis, C., i P. Chimento. IP Packet Delay Variation Metric for IP Performance Metrics (IPPM). RFC Editor, listopad 2002. http://dx.doi.org/10.17487/rfc3393.
Pełny tekst źródłaAlmes, G., S. Kalidindi i M. Zekauskas. A One-Way Delay Metric for IP Performance Metrics (IPPM). Redaktor A. Morton. RFC Editor, styczeń 2016. http://dx.doi.org/10.17487/rfc7679.
Pełny tekst źródłaAlmes, G., S. Kalidindi i M. Zekauskas. A One-Way Loss Metric for IP Performance Metrics (IPPM). Redaktor A. Morton. RFC Editor, styczeń 2016. http://dx.doi.org/10.17487/rfc7680.
Pełny tekst źródłaKoles, G., R. Hitchcock i M. Sherman. Metrics for building performance assurance. Office of Scientific and Technical Information (OSTI), lipiec 1996. http://dx.doi.org/10.2172/374167.
Pełny tekst źródłaPaxson, V., G. Almes, J. Mahdavi i M. Mathis. Framework for IP Performance Metrics. RFC Editor, maj 1998. http://dx.doi.org/10.17487/rfc2330.
Pełny tekst źródłaPressel, D. M. Performance Metrics for Parallel Systems. Fort Belvoir, VA: Defense Technical Information Center, styczeń 2000. http://dx.doi.org/10.21236/ada373437.
Pełny tekst źródła