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Relevant bibliographies by topics / Performance; Engineering / Journal articles

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Journal articles on the topic 'Performance; Engineering'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Brethower, Dale M., and Connie J. Wittkopp. "Performance Engineering." Journal of Organizational Behavior Management 9, no. 1 (1988): 83–104. http://dx.doi.org/10.1300/j075v09n01_07.

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2

Hager, Georg, and Gerhard Wellein. "Performance Engineering." Informatik-Spektrum 41, no. 5 (2018): 323–27. http://dx.doi.org/10.1007/s00287-018-1122-1.

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3

Stillwagon, Wesley W. "Technical systems performance engineering and human performance engineering." Human Resource Development International 1, no. 2 (1998): 146–48. http://dx.doi.org/10.1080/13678869800000021.

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4

Cho, A. "Engineering Peak Performance." Science 305, no. 5684 (2004): 643–44. http://dx.doi.org/10.1126/science.305.5684.643.

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5

Jarvis, S. A. "Editorial: Performance engineering." IEE Proceedings - Software 150, no. 4 (2003): 213. http://dx.doi.org/10.1049/ip-sen:20030827.

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6

Awan, I. "Editorial: Performance engineering." IEE Proceedings - Software 151, no. 5 (2004): 217. http://dx.doi.org/10.1049/ip-sen:20040740.

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7

Ould-Khaoua, M., and L. M. Mackenzie. "Editorial: Performance engineering." IEE Proceedings - Computers and Digital Techniques 150, no. 2 (2003): 66. http://dx.doi.org/10.1049/ip-cdt:20030403.

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8

Horning, Susan Schmidt. "Engineering the Performance." Social Studies of Science 34, no. 5 (2004): 703–31. http://dx.doi.org/10.1177/0306312704047536.

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9

Argent-Katwala, A., J. Bradley, N. Dingle, U. Harder, and W. Knottenbelt. "Editorial: Performance engineering." IET Software 3, no. 6 (2009): 443. http://dx.doi.org/10.1049/iet-sen.2009.9049.

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10

DeLozier, Randall, and Neil Snyder. "ENGINEERING PERFORMANCE METRICS." INCOSE International Symposium 3, no. 1 (1993): 599–605. http://dx.doi.org/10.1002/j.2334-5837.1993.tb01632.x.

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AbstractImplementation of a Total Quality Management (TQM) approach to engineering work required the development of a system of metrics which would serve as a meaningful management tool for evaluating effectiveness in accomplishing project objectives and in achieving improved customer satisfaction. A team effort was chartered with the goal of developing a system of engineering performance metrics which would measure customer satisfaction, quality, cost effectiveness, and timeliness. The approach to developing this system involved normal systems design phases including conceptual design, detail

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11

Naeim, Farzad. "Earthquake Engineering—From Engineering Seismology to Performance-Based Engineering." Earthquake Spectra 21, no. 2 (2005): 609–11. http://dx.doi.org/10.1193/1.1896960.

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12

Ruark, Benjamin. "Performance engineering goes OD: Total productivity engineering." Performance + Instruction 28, no. 8 (1989): 8–12. http://dx.doi.org/10.1002/pfi.4170280803.

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13

Kenett, Ron S. "Engineering, Emulators, Digital Twins, and Performance Engineering." Electronics 13, no. 10 (2024): 1829. http://dx.doi.org/10.3390/electronics13101829.

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Developments in digital twins are driven by the availability of sensor technologies, big data, first principles knowledge, and advanced analytics. In this paper, we discuss these changes at a conceptual level, presenting a shift from nominal engineering, aiming at design optimisation, to performance engineering, aiming at adaptable monitoring diagnostic, prognostic, and prescriptive capabilities. A key element introduced here is the role of emulators in this transformation. Emulators, also called surrogate models or metamodels, provide monitoring and diagnostic capabilities. In particular, we

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14

A., Elabbasy. "PERFORMANCE BASED SEISMIC ENGINEERING." International Conference on Civil and Architecture Engineering 7, no. 7 (2008): 671. http://dx.doi.org/10.21608/iccae.2008.45574.

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15

Suhail, Muhammed. "Performance Engineering in Cloud." International Journal of Computer Applications 180, no. 46 (2018): 35–40. http://dx.doi.org/10.5120/ijca2018917238.

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16

Drelich, Jaroslaw. "Engineering for surface performance." Surface Innovations 1, no. 3 (2013): 138–39. http://dx.doi.org/10.1680/si.13.00013.

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17

Rabin, Steven. "Client/Server Performance Engineering." Information Systems Management 13, no. 4 (1996): 25–32. http://dx.doi.org/10.1080/10580539608907013.

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18

Lea, Doug, David F. Bacon, and David Grove. "Languages and performance engineering." ACM SIGPLAN Notices 43, no. 11 (2008): 87–92. http://dx.doi.org/10.1145/1480828.1480848.

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19

Bojesen, Jesper, Jyrki Katajainen, and Maz Spork. "Performance engineering case study." ACM Journal of Experimental Algorithmics 5 (December 31, 2000): 15. http://dx.doi.org/10.1145/351827.384257.

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20

Beauregard, Yvan, Nadia Bhuiyan, and Vincent Thomson. "Lean engineering performance analysis." International Journal of Product Development 19, no. 5/6 (2014): 366. http://dx.doi.org/10.1504/ijpd.2014.064887.

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21

Minjeong Park and SungJo Hong. "Engineering Students’ Perceptions of Accredited Engineering Program Performance." Journal of Engineering Education Research 18, no. 4 (2015): 57–65. http://dx.doi.org/10.18108/jeer.2015.18.4.57.

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22

Kuala, Seri Intan, Novita Dwi Susanti, Yusnan Hasani Siregar, Aidil Haryanto, and Galih Riyan Basuki. "Engineering Design, Performance Test and Cost Analysis of Nutrition Mixer." TEKNIK 42, no. 1 (2020): 1–9. http://dx.doi.org/10.14710/teknik.v42i1.24800.

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At present mixing of nutrients in the hydroponic is still done manually (ineffective and inefficient). For that we need a tool that can mix plant nutrients equipped with a system that regulates the amount of solute (Total Dissolved Solid, TDS with ppm units) and agitator. The design consist of structural and functional, construction, testing and cost analysis. The results obtained dimensions of 0,85 m x 0,55 m x 1,55 m, consisting of a reservoir, container nutrition with a capacity of 100 liters equipped with agitators driven by a 45 watt DC motor. The performance of the electrical system is c

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23

Singh Dhaliwal, Amarjot. "Telemetry in Release Engineering: Enhancing Software Deployment and Performance Monitoring." International Journal of Science and Research (IJSR) 10, no. 11 (2021): 1528–30. http://dx.doi.org/10.21275/sr24506174437.

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24

Smith, John, and Connie U. Smith. "Performance Engineering of Software Systems." Journal of the Operational Research Society 42, no. 10 (1991): 903. http://dx.doi.org/10.2307/2583419.

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25

Ilg, Markus, and Alexander Baumeister. "Performance Management in Software Engineering." International Journal of Information Technology Project Management 2, no. 1 (2011): 1–18. http://dx.doi.org/10.4018/jitpm.2011010101.

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Performance measurement in software engineering has to meet a multiplicity of challenges. Oftentimes, traditional metrics focus on sequential development instead of using incremental and iterative development. Output is measured on a pure quantitative (e.g., SLOC), quality-disregarding basis. A project’s input is hard to assign properly using enterprise-unspecific forecasting tools which have to be calibrated at first and which do not account for time preferences. Requirements necessary for behaviourally adjusted project management and control are rarely discussed. Focusing on these shortcomin

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26

SMITH, Ian F. C. "Enabling Performance Based Structural Engineering." IABSE Congress Report 16, no. 5 (2000): 1618–25. http://dx.doi.org/10.2749/222137900796314383.

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27

Mohebali, Khashayar, and Roger N. Wixtrom. "Breast Implant Engineering and Performance." Plastic and Reconstructive Surgery 142 (October 2018): 6S—11S. http://dx.doi.org/10.1097/prs.0000000000004997.

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28

Davidge, R. W. "Engineering performance prediction for ceramics." Materials Science and Technology 2, no. 9 (1986): 902–9. http://dx.doi.org/10.1179/mst.1986.2.9.902.

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29

Neumann, Thomas. "Engineering high-performance database engines." Proceedings of the VLDB Endowment 7, no. 13 (2014): 1734–41. http://dx.doi.org/10.14778/2733004.2733076.

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30

Yasuda, Takeo. "Performance design of engineering plastics." Kobunshi 39, no. 2 (1990): 90–93. http://dx.doi.org/10.1295/kobunshi.39.90.

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31

Smith, John. "Performance Engineering of Software Systems." Journal of the Operational Research Society 42, no. 10 (1991): 903–4. http://dx.doi.org/10.1057/jors.1991.172.

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32

OEPEN, STEPHAN, and JOHN CARROLL. "Parser engineering and performance profiling." Natural Language Engineering 6, no. 1 (2000): 81–97. http://dx.doi.org/10.1017/s1351324900002394.

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We describe and argue for a strategy of performance profiling and comparison in the engineering of parsing systems for wide-coverage linguistic grammars. A performance profile is a precise, rich and structured snapshot of system (and grammar) behaviour at a given development point. The aim is to characterize system performance at a very detailed technical level, but at the same time to abstract away from idiosyncracies of particular processors. Profiles are obtained with minimal effort by applying a specialized profiling tool to a set of structured reference data (taken from both existing test

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33

Czerniak, Mike, Steve Cheeseman, Kurt J. Lesker, et al. "VSW technology — engineering MBE performance." III-Vs Review 5, no. 4 (1992): 28–29. http://dx.doi.org/10.1016/0961-1290(92)90125-t.

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34

Nambiar, Manoj, Ajay Kattepur, Gopal Bhaskaran, Rekha Singhal, and Subhasri Duttagupta. "Model Driven Software Performance Engineering." ACM SIGMETRICS Performance Evaluation Review 43, no. 4 (2016): 53–62. http://dx.doi.org/10.1145/2897356.2897363.

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35

Jarvis, S. A. "UK Performance Engineering Workshop 2010." Computer Journal 54, no. 6 (2011): 960–61. http://dx.doi.org/10.1093/comjnl/bxr015.

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36

Charman, J. H., P. J. Carey, and P. G. Fookes. "Engineering classification for environmental performance." Geological Society, London, Engineering Geology Special Publications 18, no. 1 (2001): 23–28. http://dx.doi.org/10.1144/gsl.eng.2001.018.01.04.

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37

Suh, In Soo, and Choul-Gyun Lee. "Photobioreactor engineering: Design and performance." Biotechnology and Bioprocess Engineering 8, no. 6 (2003): 313–21. http://dx.doi.org/10.1007/bf02949274.

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38

Laure, Erwin, Heinz Stockinger, and Kurt Stockinger. "Performance engineering in data Grids." Concurrency and Computation: Practice and Experience 17, no. 2-4 (2005): 171–91. http://dx.doi.org/10.1002/cpe.923.

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39

Ruark, Benjamin E. "Performance engineering: The next generation." Performance + Instruction 28, no. 3 (1989): 17–21. http://dx.doi.org/10.1002/pfi.4170280305.

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40

Adinda, Riztia Putri, Munadi Rendy, and Muldina Negara Ridha. "Bulletin of Electrical Engineering and Informatics." Bulletin of Electrical Engineering and Informatics 9, no. 5 (2020): 2008–11. https://doi.org/10.11591/eei.v9i4.1953.

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The emergence of the container in various cloud platforms from Open Stack to Google Cloud Platform has marked the industry interest in opting for container as their cloud service solution. However, the cloud users should aware of performance overheads of different virtualization solutions in order to avoid quality of service degradation because different container platforms delivered different performances. This research evaluated how different container platforms (Docker, LXC, and LXD) impacted in running different TCP services and also measured system performance of each container compared t

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41

Tatineni, Sumanth. "Cloud-Based Reliability Engineering: Strategies for Ensuring High Availability and Performance." International Journal of Science and Research (IJSR) 12, no. 11 (2023): 1005–12. http://dx.doi.org/10.21275/sr231113060258.

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42

UCHIDA, Ken. "Stress Engineering for High-Performance MOSFETs." Journal of the Vacuum Society of Japan 51, no. 5 (2008): 301–5. http://dx.doi.org/10.3131/jvsj2.51.301.

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43

A. Whittaker, Y. N. Huang, and R. O. Hamburger. "Next-generation performance based earthquake engineering*." Electronic Journal of Structural Engineering, no. 2 (December 1, 2007): 49–57. http://dx.doi.org/10.56748/ejse.812.

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The next-generation tools and procedures for performance-based earthquake engineering that are being developed in the United States represent a radical departure from traditional seismic design practice and performance assessment. Performance will be measured in terms of direct economic loss, indirect economic loss and casualties rather than by building component deformations and accelerations. Uncertainty and randomness will be captured in every step of the performance assessment process. The paper summarizes the types of performance assessment made possible by the next-generation tools and p

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44

Pillay, Deveshan L., Oladimeji B. Olalusi, Moses W. Kiliswa, Paul O. Awoyera, John Temitope Kolawole, and Adewumi John Babafemi. "Engineering performance of metakaolin based concrete." Cleaner Engineering and Technology 6 (February 2022): 100383. http://dx.doi.org/10.1016/j.clet.2021.100383.

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45

Arcelli, Davide. "Envisioning Model-Based Performance Engineering Frameworks." Procedia Computer Science 184 (2021): 541–48. http://dx.doi.org/10.1016/j.procs.2021.04.008.

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46

Ellingwood, B. R. "Structural reliability and performance-based engineering." Proceedings of the Institution of Civil Engineers - Structures and Buildings 161, no. 4 (2008): 199–207. http://dx.doi.org/10.1680/stbu.2008.161.4.199.

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47

Aktan, A. Emin, Bruce R. Ellingwood, and Brian Kehoe. "Performance-Based Engineering of Constructed Systems." Journal of Structural Engineering 133, no. 3 (2007): 311–23. http://dx.doi.org/10.1061/(asce)0733-9445(2007)133:3(311).

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48

Barbierato, Enrico, Marco Gribaudo, and Giuseppe Serazzi. "Multi-formalism Models for Performance Engineering." Future Internet 12, no. 3 (2020): 50. http://dx.doi.org/10.3390/fi12030050.

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Nowadays, the necessity to predict the performance of cloud and edge computing-based architectures has become paramount, in order to respond to the pressure of data growth and more aggressive level of service agreements. In this respect, the problem can be analyzed by creating a model of a given system and studying the performance indices values generated by the model’s simulation. This process requires considering a set of paradigms, carefully balancing the benefits and the disadvantages of each one. While queuing networks are particularly suited to modeling cloud and edge computing architect

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49

Hey, Tony, and Juri Papay. "Performance Engineering, PSEs and the GRID." Scientific Programming 10, no. 1 (2002): 3–17. http://dx.doi.org/10.1155/2002/354024.

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Performance Engineering is concerned with the reliable prediction and estimation of the performance of scientific and engineering applications on a variety of parallel and distributed hardware. This paper reviews the present state of the art in 'Performance Engineering' for both parallel computing and meta-computing environments and attempts to look forward to the application of these techniques in the wider context of Problem Solving Environments and the Grid. The paper compares various techniques such as benchmarking, performance measurements, analytical modelling and simulation, and highlig

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50

Fisher, Donald L. "Optimal Performance Engineering: Good, Better, Best." Human Factors: The Journal of the Human Factors and Ergonomics Society 35, no. 1 (1993): 115–39. http://dx.doi.org/10.1177/001872089303500107.

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