Academic literature on the topic 'Metrics'

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Journal articles on the topic "Metrics"

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Pentecost, Michael J. "Metrics, Metrics, Metrics." Journal of the American College of Radiology 13, no. 6 (June 2016): 628–29. http://dx.doi.org/10.1016/j.jacr.2016.03.002.

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Jekl, Jan, and Jiří Jánský. "Security Challenges and Economic-Geographical Metrics for Analyzing Safety to Achieve Sustainable Protection." Sustainability 14, no. 22 (November 16, 2022): 15161. http://dx.doi.org/10.3390/su142215161.

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In this article, we aim to develop the theoretical background for the possible application of Economic-Geographical metrics in the field of population protection. We deal with various options for analyzing the availability of “safety” for citizens using studied metrics. Among others, we apply well-known metrics such as the Gini coefficient, Hoover index and even establish their generalizations. We develop a theoretical background and evaluate our findings on generated and actual data. We find that the metrics used can have an opposite interpretation depending on the scenario we are considering. We also discover that some scenarios demand a modification to the usual metric. We conclude that Economic-Geographical metrics give valuable tools to address specific security challenges. Metric’s generalizations could serve as a potent tool for other authors working in the field of population protection. Nevertheless, we must keep in mind that metrics also have drawbacks.
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Hoffman, Robert R., Peter A. Hancock, and Jeffrey M. Bradshaw. "Metrics, Metrics, Metrics, Part 2: Universal Metrics?" IEEE Intelligent Systems 25, no. 6 (November 2010): 93–97. http://dx.doi.org/10.1109/mis.2010.147.

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SABAU, SORIN V., KAZUHIRO SHIBUYA, and HIDEO SHIMADA. "Metric structures associated to Finsler metrics." Publicationes Mathematicae Debrecen 84, no. 1-2 (January 1, 2014): 89–103. http://dx.doi.org/10.5486/pmd.2014.5886.

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Jakfar, Muhammad, Manuharawati, Dwi Nur Yunianti, and Mey Dita Kumala. "Metrics on a G-metric Space." Journal of Physics: Conference Series 1417 (December 2019): 012023. http://dx.doi.org/10.1088/1742-6596/1417/1/012023.

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Hoffman, R. R., M. Marx, and P. Hancock. "Metrics, Metrics, Metrics: Negative Hedonicity." IEEE Intelligent Systems 23, no. 2 (March 2008): 69–73. http://dx.doi.org/10.1109/mis.2008.31.

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Mennucci, Andrea C. G. "Designing metrics; the delta metric for curves." ESAIM: Control, Optimisation and Calculus of Variations 25 (2019): 59. http://dx.doi.org/10.1051/cocv/2018044.

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In the first part, we revisit some key notions. Let M be a Riemannian manifold. Let G be a group acting on M. We discuss the relationship between the quotient M∕G, “horizontality” and “normalization”. We discuss the distinction between path-wise invariance and point-wise invariance and how the former positively impacts the design of metrics, in particular for the mathematical and numerical treatment of geodesics. We then discuss a strategy to design metrics with desired properties. In the second part, we prepare methods to normalize some standard group actions on the curve; we design a simple differential operator, called the delta operator, and compare it to the usual differential operators used in defining Riemannian metrics for curves. In the third part we design two examples of Riemannian metrics in the space of planar curves. These metrics are based on the “delta” operator; they are “modular”, they are composed of different terms, each associated to a group action. These are “strong” metrics, that is, smooth metrics on the space of curves, that is defined as a differentiable manifolds, modeled on the standard Sobolev space H2. These metrics enjoy many important properties, including: metric completeness, geodesic completeness, existence of minimal length geodesics. These metrics properly project on the space of curves up to parameterization; the quotient space again enjoys the above properties.
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Saraswathula, Anirudh, Samantha J. Merck, Ge Bai, Christine M. Weston, Elizabeth Ann Skinner, April Taylor, Allen Kachalia, Renee Demski, Albert W. Wu, and Stephen A. Berry. "The Volume and Cost of Quality Metric Reporting." JAMA 329, no. 21 (June 6, 2023): 1840. http://dx.doi.org/10.1001/jama.2023.7271.

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ImportanceUS hospitals report data on many health care quality metrics to government and independent health care rating organizations, but the annual cost to acute care hospitals of measuring and reporting quality metric data, independent of resources spent on quality interventions, is not well known.ObjectiveTo evaluate externally reported inpatient quality metrics for adult patients and estimate the cost of data collection and reporting, independent of quality-improvement efforts.Design, Setting, and ParticipantsRetrospective time-driven activity-based costing study at the Johns Hopkins Hospital (Baltimore, Maryland) with hospital personnel involved in quality metric reporting processes interviewed between January 1, 2019, and June 30, 2019, about quality reporting activities in the 2018 calendar year.Main Outcomes and MeasuresOutcomes included the number of metrics, annual person-hours per metric type, and annual personnel cost per metric type.ResultsA total of 162 unique metrics were identified, of which 96 (59.3%) were claims-based, 107 (66.0%) were outcome metrics, and 101 (62.3%) were related to patient safety. Preparing and reporting data for these metrics required an estimated 108 478 person-hours, with an estimated personnel cost of $5 038 218.28 (2022 USD) plus an additional $602 730.66 in vendor fees. Claims-based (96 metrics; $37 553.58 per metric per year) and chart-abstracted (26 metrics; $33 871.30 per metric per year) metrics used the most resources per metric, while electronic metrics consumed far less (4 metrics; $1901.58 per metric per year).Conclusions and RelevanceSignificant resources are expended exclusively for quality reporting, and some methods of quality assessment are far more expensive than others. Claims-based metrics were unexpectedly found to be the most resource intensive of all metric types. Policy makers should consider reducing the number of metrics and shifting to electronic metrics, when possible, to optimize resources spent in the overall pursuit of higher quality.
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Rhodes, Frank. "Metric subgraphs of the chamfer metrics and the Melter-Tomescu path generated metrics." Discrete Mathematics 147, no. 1-3 (December 1995): 197–209. http://dx.doi.org/10.1016/0012-365x(94)00238-e.

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Lin, Shuang, Mingxue Guo, and Yu Zhong. "A Representation Theorem for L-fuzzy Pseudo-metrics." Journal of Physics: Conference Series 2449, no. 1 (March 1, 2023): 012010. http://dx.doi.org/10.1088/1742-6596/2449/1/012010.

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Abstract Through this article, the definitions of an L -fuzzy pseudo-metric and a family of pseudo-metric that satisfies the property of lower-semicontinuity (or named nests of pseudo-metrics) are introduced. After that, we indicated that an L -fuzzy pseudo-metric can be constructed from nests of pseudo-metrics and nests of pseudo-metrics can be constructed from an L -fuzzy pseudo-metric. Therefore, we establish a each to each association between L - fuzzy pseudo-metrics and nests of pseudo-metrics.
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Dissertations / Theses on the topic "Metrics"

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Remiáš, Richard. "Systém pro podporu metrik v projektech vývoje softwaru." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236616.

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This work is aimed at design and implementation of system for supporting metrics in software development projects. The procedure of design and application of measurement methods is described. Further metrics data analysis in three domains is described: frequency domain, time domain and relationship domain; together with forms of visualization. Finally, the requirements for system for supporting metrics are enlisted, along with design of architecture and details of implementation.
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Gotham, Mark Robert Haigh. "The metre metrics : characterising (dis)similarity among metrical structures." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709080.

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Kwan, Pak Leung. "Design metrics forensics : an analysis of the primitive metrics in the Zage design metrics." Virtual Press, 1994. http://liblink.bsu.edu/uhtbin/catkey/897490.

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The Software Engineering Research Center (SERC) Design Metrics Research Team at Ball State University has developed a design metric D(G) of the form:D(G) = D~ + DiWhere De is the architectural design metric (external design metric) and D; is the detailed design metric (internal design metric).Questions to be investigated in this thesis are:Why can D, be an indicator of the potential error modules?Why can D; be an indicator of the potential error modules?Are there any significant factors that dominate the design metrics?In this thesis, the report of the STANFINS data is evaluated by using correlation analysis, regression analysis, and several other statistical techiques. The STANFINS study is chosen because it contains approximately 532 programs, 3,000 packages and 2,500,000 lines of Ada.The design metrics study was completed on 21 programs (approximately 24,000 lines of code) which were selected by CSC development teams. Error reports were also provided by CSC personnel.
Department of Computer Science
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Smith, Mary Lou. "Assessing software metrics." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ38410.pdf.

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BATISTA, CARLOS FREUD ALVES. "SOFTWARE SECURITY METRICS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=10990@1.

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PETRÓLEO BRASILEIRO S. A.
A dependência cada vez maior da tecnologia de informação (TI) torna software seguro um elemento chave para a continuidade dos serviços de nossa sociedade atual. Nos últimos anos, instituições públicas e privadas aumentaram seus investimentos em segurança da informação, mas a quantidade de ataques vem crescendo mais rapidamente do que a nossa capacidade de poder enfrentálos, colocando em risco a propriedade intelectual, a relação de confiança de clientes e a operação de serviços e negócios apoiados pelos serviços de TI. Especialistas em segurança afirmam que atualmente boa parte dos incidentes de segurança da informação ocorrem a partir de vulnerabilidades encontradas no software, componente presente em boa parte dos sistemas de informação. Para tornar o software fidedigno em relação à segurança, a criação e o uso de métricas de segurança serão fundamentais para gerenciar e entender o impacto dos programas de segurança nas empresas. Porém, métricas de segurança são cobertas de mistério e consideradas bastante difíceis de serem implementadas. Este trabalho pretende mostrar que hoje ainda não é possível termos métricas quantitativas capazes de indicar o nível de segurança que o software em desenvolvimento virá a ter. Necessitam-se, então, outras práticas para assegurar níveis de segurança a priori, ou seja, antes de se por o software em uso.
Today`s growing dependency on information technology (IT) makes software security a key element of IT services. In recent years public and private institutions raised the investment on information security, however the number of attacks is growing faster than our power to face them, putting at risk intellectual property, customer`s confidence and businesses that rely on IT services. Experts say that most information security incidents occur due to the vulnerabilities that exist in software systems in first place. Security metrics are essential to assess software dependability with respect to security, and also to understand and manage impacts of security initiatives in organizations. However, security metrics are shrouded in mystery and very hard to implement. This work intends to show that there are no adequate metrics capable of indicating the security level that a software will achieve. Hence, we need other practices to assess the security of software while developing it and before deploying it.
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Singh, Rajat. "Software Metrics Tool." Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/29766.

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In the current world software applications are becoming more important with each passing day. They are present in all walks of life and it?s difficult to imagine a world without them. It?s a part of every known industry whether it be manufacturing, healthcare, financing. They are available on all forms in personal laptops, mobiles, and tablets. However, there is another challenging task to figure out the quality of the software. There are multiple measures available in the form of software metrics. The objective of this thesis is to present an extensible software for calculating software metrics. This tool proposed is a web application which calculates metrics and statistics for the source code files provided. This tool also provides an ability to the user to extend the tool by adding a metric to the tool.
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Sýkorová, Veronika. "Data Quality Metrics." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-2815.

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The aim of the thesis is to prove measurability of the Data Quality which is a relatively subjective measure and thus is difficult to measure. In doing this various aspects of measuring the quality of data are analyzed and a Complex Data Quality Monitoring System is introduced with the aim to provide a concept for measuring/monitoring the overall Data Quality in an organization. The system is built on a metrics hierarchy decomposed into particular detailed metrics, dimensions enabling multidimensional analyses of the metrics, and processes being measured by the metrics. The first part of the thesis (Chapter 2 and Chapter 3) is focused on dealing with Data Quality, i.e. provides various definitions of Data Quality, gives reasoning for the importance of Data Quality in a company, and presents some of the most common tools and solutions that target to managing Data Quality in an organization. The second part of the thesis (Chapter 4 and Chapter 5) builds on the previous part and leads into measuring Data Quality using metrics, i.e. contains definition and purpose of Data Quality Metrics, places them into the multidimensional context (dimensions, hierarchies) and states five possible decompositions of Data Quality metrics into detail. The third part of the thesis (Chapter 6) contains the proposed Complex Data Quality Monitoring System including description of Data Quality Management related dimensions and processes, and most importantly detailed definition of bottom-level metrics used for calculation of the overall Data Quality.
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Abounader, Joe Raymond. "Object oriented design metrics." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ28170.pdf.

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Liu, Xiaowei. "Object-oriented software metrics." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0013/MQ41734.pdf.

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Brianas, Christopher G. "DoN procurement metrics evaluation." Monterey, California. Naval Postgraduate School, 2005. http://hdl.handle.net/10945/10027.

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MBA Professional Report
The purpose of this MBA Project was to investigate and provide a comprehensive evaluation of the current Department of the Navy Procurement Metrics that are collected. These metrics are collected by the Office of the Deputy Assistant Secretary of the Navy for Acquisition Management. This project was conducted at their request and with their support. The goal of this project was to determine if the current metrics are the appropriate procurement performance measures. Specifically, this MBA Project attempted to answer these three questions: (1) Do the metrics align with strategy? (2) Can they be measured effectively? and (3) Are they linked to value? The framework used to explore these questions is Robert Simon's Levers of Control model. These procurement metrics are part of a Diagnostic Control System and are being evaluated as such. Simon's Nature of Measures model is also used in the analysis and helps determine metric objectiveness, completeness and responsiveness.
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Books on the topic "Metrics"

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Montana. Department of Transportation. Advanced road design metrics. [Helena, Mont.?]: Montana Dept. of Transportation, 1995.

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Klubeck, Martin. Metrics. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3.

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Lehner, Franz, Reiner Dumke, and Alain Abran, eds. Software Metrics. Wiesbaden: Deutscher Universitätsverlag, 1997. http://dx.doi.org/10.1007/978-3-322-99929-0.

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Eusgeld, Irene, Felix C. Freiling, and Ralf Reussner, eds. Dependability Metrics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-68947-8.

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Klubeck, Martin. Success Metrics. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2586-8.

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Murdoch, Joseph B. Lighting metrics. New York, N.Y: Illuminating Engineering Society of North America, 2001.

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Sterne, Jim. Web Metrics. New York: John Wiley & Sons, Ltd., 2002.

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Cutler, Matt. E-metrics: Business metrics for the new economy. Cambridge, MA: NetGenesis, 2000.

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Ince, Darrel. System quality metrics. (s.l.): Information Technology Briefings, 1988.

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Schneidewind, Norman F. Validating software metrics. Monterey, Calif: Naval Postgraduate School, 1990.

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Book chapters on the topic "Metrics"

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Klubeck, Martin. "Establishing A Common Language." In Metrics, 1–23. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_1.

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Klubeck, Martin. "Final Product: The Metrics Report Card." In Metrics, 211–41. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_10.

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Klubeck, Martin. "Advanced Metrics." In Metrics, 243–69. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_11.

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Klubeck, Martin. "Creating the Service Catalog." In Metrics, 271–81. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_12.

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Klubeck, Martin. "Establishing Standards and Benchmarks." In Metrics, 283–91. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_13.

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Klubeck, Martin. "Respecting the Power of Metrics." In Metrics, 293–307. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_14.

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Klubeck, Martin. "Avoiding the Research Trap." In Metrics, 309–17. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_15.

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Klubeck, Martin. "Embracing Your Organization’s Uniqueness." In Metrics, 319–30. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_16.

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Klubeck, Martin. "Designing Metrics." In Metrics, 25–56. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_2.

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Klubeck, Martin. "Planning a Good Metric." In Metrics, 57–81. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3727-3_3.

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Conference papers on the topic "Metrics"

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Bartal, Yair. "On approximating arbitrary metrices by tree metrics." In the thirtieth annual ACM symposium. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/276698.276725.

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Srivastav, V. S. P., and Piyush Prakash. "Green metrics for OO codes: CAAEC metric." In 2013 International Conference on Green Computing, Communication and Conservation of Energy (ICGCE). IEEE, 2013. http://dx.doi.org/10.1109/icgce.2013.6823448.

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"Proceedings Fifth International Software Metrics Symposium. Metrics (Cat. No.98TB100262)." In Proceedings Fifth International Software Metrics Symposium. Metrics 1998. IEEE, 1998. http://dx.doi.org/10.1109/metric.1998.731215.

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"11th IEEE International Software Metrics Symposium - Table of Contents." In 11th IEEE International Software Metrics Symposium (METRICS'05). IEEE, 2005. http://dx.doi.org/10.1109/metrics.2005.2.

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"Proceedings Seventh International Software Metrics Symposium." In Proceedings Seventh International Software Metrics Symposium. METRICS 2001. IEEE, 2001. http://dx.doi.org/10.1109/metric.2001.915509.

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"Author Index." In Proceedings Seventh International Software Metrics Symposium. METRICS 2001. IEEE, 2001. http://dx.doi.org/10.1109/metric.2001.915544.

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"Author index." In Proceedings Fifth International Software Metrics Symposium. Metrics 1998. IEEE, 1998. http://dx.doi.org/10.1109/metric.1998.731254.

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"Message from the General and Program Chairs." In 11th IEEE International Software Metrics Symposium (METRICS'05). IEEE, 2005. http://dx.doi.org/10.1109/metrics.2005.34.

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"Organizing Committee." In 11th IEEE International Software Metrics Symposium (METRICS'05). IEEE, 2005. http://dx.doi.org/10.1109/metrics.2005.37.

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"Program Committee." In 11th IEEE International Software Metrics Symposium (METRICS'05). IEEE, 2005. http://dx.doi.org/10.1109/metrics.2005.39.

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Reports on the topic "Metrics"

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Niiler, Pearn P. Metrics. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada622362.

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Stephan, E. IP Performance Metrics (IPPM) Metrics Registry. RFC Editor, August 2005. http://dx.doi.org/10.17487/rfc4148.

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Mills, Everald E. Software Metrics. Fort Belvoir, VA: Defense Technical Information Center, December 1988. http://dx.doi.org/10.21236/ada236140.

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Berl, Frederick. MSS Metrics. Office of Scientific and Technical Information (OSTI), April 2023. http://dx.doi.org/10.2172/1972077.

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Duffield, N., A. Morton, and J. Sommers. Loss Episode Metrics for IP Performance Metrics (IPPM). RFC Editor, May 2012. http://dx.doi.org/10.17487/rfc6534.

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Demichelis, C., and P. Chimento. IP Packet Delay Variation Metric for IP Performance Metrics (IPPM). RFC Editor, November 2002. http://dx.doi.org/10.17487/rfc3393.

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Almes, G., S. Kalidindi, and M. Zekauskas. A One-Way Delay Metric for IP Performance Metrics (IPPM). Edited by A. Morton. RFC Editor, January 2016. http://dx.doi.org/10.17487/rfc7679.

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Almes, G., S. Kalidindi, and M. Zekauskas. A One-Way Loss Metric for IP Performance Metrics (IPPM). Edited by A. Morton. RFC Editor, January 2016. http://dx.doi.org/10.17487/rfc7680.

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Abelson, L. A. Object-Oriented Metrics. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada400493.

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Morton, A., L. Ciavattone, G. Ramachandran, S. Shalunov, and J. Perser. Packet Reordering Metrics. RFC Editor, November 2006. http://dx.doi.org/10.17487/rfc4737.

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