Journal articles on the topic 'Real time performance'

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1

Ueno, Sadao, and Itaru Nakamori. "Real–Time Performance Monitoring." JAPAN TAPPI JOURNAL 73, no. 3 (2019): 225–30. http://dx.doi.org/10.2524/jtappij.73.225.

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2

Ueno, Sadao. "Real-Time Performance Monitoring." JAPAN TAPPI JOURNAL 74, no. 3 (2020): 239–43. http://dx.doi.org/10.2524/jtappij.74.239.

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3

deBondeli, Patrick. "Real-time Ada systems: development methodology and real-time performance." ACM SIGAda Ada Letters VII, no. 6 (October 1987): 119–20. http://dx.doi.org/10.1145/36792.36818.

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4

Cavender, K. D. "Real Time Foam Performance Testing." Journal of Cellular Plastics 29, no. 4 (July 1993): 350–64. http://dx.doi.org/10.1177/0021955x9302900402.

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5

Huitian Lu, W. J. Kolarik, and S. S. Lu. "Real-time performance reliability prediction." IEEE Transactions on Reliability 50, no. 4 (2001): 353–57. http://dx.doi.org/10.1109/24.983393.

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6

Penner, Andrew, Jeffrey Hall, Lindsey Hall, Nakul Jeirath, and Omar Shaikh. "Filter enables real-time performance." IEEE Potentials 26, no. 2 (March 2007): 17–24. http://dx.doi.org/10.1109/mp.2007.343024.

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7

Koh, Jae-Hwan, and Byoung-Wook Choi. "Performance Evaluation of Real-time Mechanisms for Real-time Embedded Linux." Journal of Institute of Control, Robotics and Systems 18, no. 4 (April 1, 2012): 337–42. http://dx.doi.org/10.5302/j.icros.2012.18.4.337.

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8

Ma, Yifan, Batu Qi, Wenhua Xu, Mingjie Wang, Bowen Du, and Hongfei Fan. "Integrating Real-Time and Non-Real-Time Collaborative Programming." Proceedings of the ACM on Human-Computer Interaction 7, GROUP (December 29, 2022): 1–19. http://dx.doi.org/10.1145/3567563.

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Real-time collaborative programming enables a group of programmers to edit shared source code at the same time, which significantly complements the traditional non-real-time collaborative programming supported by version control systems. However, one critical issue with this emerging technique is the lack of integration with non-real-time collaboration. Specifically, contributions from multiple programmers in a real-time collaboration session cannot be distinguished and accurately recorded in the version control system. In this study, we propose a scheme that integrates real-time and non-real-time collaborative programming with a novel workflow, and contribute enabling techniques to realize such integration. As a proof-of-concept, we have successfully implemented two prototype systems named CoEclipse and CoIDEA, which allow programmers to closely collaborate in a real-time fashion while preserving the work's compatibility with traditional non-real-time collaboration. User evaluation and performance experiments have confirmed the feasibility of the approach and techniques, demonstrated the good system performance, and presented the satisfactory usability of the prototypes.
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9

Czeiszperger, Michael, and Jeff Pressing. "Synthesizer Performance and Real-Time Techniques." Computer Music Journal 18, no. 4 (1994): 100. http://dx.doi.org/10.2307/3681365.

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10

Lippe, Cort, and Jeff Pressing. "Synthesizer Performance and Real-Time Techniques." Notes 51, no. 1 (September 1994): 167. http://dx.doi.org/10.2307/899217.

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11

Kolarik, William J., Jeffrey C. Woldstad, and Shuxia Lu. "Real-Time Human Performance Reliability Assessment." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 22 (July 2000): 843–46. http://dx.doi.org/10.1177/154193120004402290.

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This paper describes a real-time conditional human reliability model constructed to predict the likelihood of human performance metrics exceeding critical boundaries in a future time interval. The model is implemented by collecting real-time data from selected performance measures, modeling and forecasting these measures, and then converting the forecast results into reliability measures. To demonstrate the feasibility of the proposed model, a prototype software package has been developed and tested for a simple movement task.
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12

Franklin, Jim. "Synthesizer performance and real-time techniques." Musicology Australia 16, no. 1 (January 1993): 79–81. http://dx.doi.org/10.1080/08145857.1993.10415235.

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13

Kenny, K. B., and K. J. Lin. "Measuring and analyzing real-time performance." IEEE Software 8, no. 5 (September 1991): 41–49. http://dx.doi.org/10.1109/52.84215.

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14

Wamanacharya, Kiran, and Prashanth V. Joshi. "Performance Analysis of Real-Time System." Indian Journal of Science and Technology 12, no. 29 (August 1, 2019): 1–3. http://dx.doi.org/10.17485/ijst/2019/v12i29/146973.

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15

Eigenfeldt, Arne. "Real-time Composition as Performance Ecosystem." Organised Sound 16, no. 2 (June 28, 2011): 145–53. http://dx.doi.org/10.1017/s1355771811000094.

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This article proposes that real-time composition can be considered a new performance ecosystem. Rather than an extension of electroacoustic instruments that are used within improvisatory environments, real-time composition systems are produced by composers interested in gestural interactions between musical agents, with or without real-time control. They are a subclass of interactive systems, specifically a genre of interactive composition systems that share compositional control between composer and system. Designing the complexity of interactions between agents is a compositional act, and its outcomes are realised during performance – more so than most interactive systems, the new performance ecosystem is compositional in nature.
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16

So, A. TP, and W. SM Suen. "Assessment of real-time traffic performance." Building Services Engineering Research and Technology 23, no. 3 (August 2002): 143–50. http://dx.doi.org/10.1191/0143624402bt037oa.

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17

Goldwasser, Samuel, R. Rleynolds, Ted Bapty, David Baraff, John Summers, David Talton, and Ed Walsh. "Physician's Workstation with Real-Time Performance." IEEE Computer Graphics and Applications 5, no. 12 (1985): 44–57. http://dx.doi.org/10.1109/mcg.1985.276276.

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18

Sharma, et. al., Mridula. "Performance Evaluation of Real-Time Systems." International Journal of Computing and Digital Systems 3, no. 3 (January 1, 2015): 43–52. http://dx.doi.org/10.12785/ijcds/040105.

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19

Pereira, Diogo Augusto, Wagner Ourique de Morais, and Edison Pignaton de Freitas. "NoSQL real-time database performance comparison." International Journal of Parallel, Emergent and Distributed Systems 33, no. 2 (March 30, 2017): 144–56. http://dx.doi.org/10.1080/17445760.2017.1307367.

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20

Elsobeiey, Mohamed, and Salim Al-Harbi. "Performance of real-time Precise Point Positioning using IGS real-time service." GPS Solutions 20, no. 3 (June 9, 2015): 565–71. http://dx.doi.org/10.1007/s10291-015-0467-z.

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21

Rowe, Robert. "Real Time and Unreal Time: Expression in Distributed Performance." Journal of New Music Research 34, no. 1 (March 2005): 87–95. http://dx.doi.org/10.1080/1080/09298210500124034.

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22

Furht, Borko, J. Parker, and D. Grostick. "Performance of REAL/IX TM -fully preemptive real time UNIX." ACM SIGOPS Operating Systems Review 23, no. 4 (October 1989): 45–52. http://dx.doi.org/10.1145/70730.70738.

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23

Rothstein, Joseph. "Scorpion Systems sYbil Real-Time Performance Software." Computer Music Journal 15, no. 2 (1991): 84. http://dx.doi.org/10.2307/3680926.

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24

Sultan, Juwita Mohd, Izzah Artikah Osmadi, and Zahariah Manap. "Real-time Wi-Fi network performance evaluation." International Journal of Informatics and Communication Technology (IJ-ICT) 11, no. 3 (December 1, 2022): 193. http://dx.doi.org/10.11591/ijict.v11i3.pp193-205.

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<span>The most critical parameters that indicate the Wi-Fi network are throughput, delay, latency, and packet loss since they provide significant benefits, especially to the end-user. This research aims to investigate Wi-Fi performance in an indoor environment for light-of-sight (LOS) and non-light-of-sight (NLOS) conditions. The effect of the surrounding obstacles and distance has also been reported in the paper. The parameters measured are packet loss, the packet sent, the packet received, throughput, and latency. Site measurement is done to obtain real-time and optimum results. The measured parameters are then validated using the EMCO ping monitor 8 software. The comparison results between the measurement and the simulation are well presented in this paper. Additionally, the measurement distance is done up to 30 meters and the results are reported in the paper as well. The results indicate that the throughput value decreases with an increasing distance, where the lowest throughput value is 24.64 Mbps and the highest throughput value is 70.83 Mbps. Next, the maximum latency value from the measurement is 79 ms, while the lowest latency value is 56.09 ms. Finally, this research verified that obstacles and distances are among the contributing factors affecting the throughput and latency performance of the Wi-Fi network.</span>
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25

Cao, Chen, Derek Bradley, Kun Zhou, and Thabo Beeler. "Real-time high-fidelity facial performance capture." ACM Transactions on Graphics 34, no. 4 (July 27, 2015): 1–9. http://dx.doi.org/10.1145/2766943.

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26

Chen, Junping, Haojun Li, Bin Wu, Yize Zhang, Jiexian Wang, and Congwei Hu. "Performance of Real-Time Precise Point Positioning." Marine Geodesy 36, no. 1 (March 1, 2013): 98–108. http://dx.doi.org/10.1080/01490419.2012.699503.

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27

Abbas, Houssam, Rajeev Alur, Konstantinos Mamouras, Rahul Mangharam, and Alena Rodionova. "Real-Time Decision Policies With Predictable Performance." Proceedings of the IEEE 106, no. 9 (September 2018): 1593–615. http://dx.doi.org/10.1109/jproc.2018.2853608.

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28

Cidon, I., I. Gopal, G. Grover, and M. Sidi. "Real-time packet switching: a performance analysis." IEEE Journal on Selected Areas in Communications 6, no. 9 (December 1988): 1576–86. http://dx.doi.org/10.1109/49.12885.

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29

Lehoczky, John P., and Lui Sha. "Performance of real-time bus scheduling algorithms." ACM SIGMETRICS Performance Evaluation Review 14, no. 1 (May 1986): 44–53. http://dx.doi.org/10.1145/317531.317538.

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30

Sastry, Munukutla, and Dao lin Li. "F109 REAL-TIME POWER PLANT PERFORMANCE MONITORING." Proceedings of the International Conference on Power Engineering (ICOPE) 2003.1 (2003): _1–327_—_1–331_. http://dx.doi.org/10.1299/jsmeicope.2003.1._1-327_.

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31

Shaffer, Eric, and Daniel A. Reed. "Real-time immersive performance visualization and steering." ACM SIGGRAPH Computer Graphics 34, no. 2 (May 2000): 11–14. http://dx.doi.org/10.1145/351440.351443.

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32

Johnson, Bridget. "Emerging Technologies for Real-Time Diffusion Performance." Leonardo Music Journal 24 (December 2014): 13–15. http://dx.doi.org/10.1162/lmj_a_00188.

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With the ascendance of the field of new interfaces for musical expression, a new phase of sound diffusion has emerged. Rapid development is taking place across the field, with a focus on gestural interaction and the development of custom performance interfaces. This article discusses how composers and performers embracing technology have broadened the boundaries of spatial performance. A particular focus is placed on performance interfaces built by the author that afford the artist more control over performative gestures. These new works serve as examples of the burgeoning field of diffusion performance interface design.
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33

Halang, W. A., R. Gumzej, and M. Colnarič. "Measuring the Performance of Real Time Systems." IFAC Proceedings Volumes 30, no. 23 (September 1997): 93–98. http://dx.doi.org/10.1016/s1474-6670(17)41398-x.

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34

Nguyen, Stephanie N., and Hiroo Takayama. "Commentary: Measuring the performance in real time." JTCVS Techniques 2 (June 2020): 68–69. http://dx.doi.org/10.1016/j.xjtc.2020.01.026.

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35

Kreimer, Joseph. "Performance of Real-Time Systems in Equilibrium." IFAC Proceedings Volumes 33, no. 11 (June 2000): 1175–80. http://dx.doi.org/10.1016/s1474-6670(17)37521-3.

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36

Paulk, Mark C. "Real-time performance of distributed Ada programs." ACM SIGAda Ada Letters VII, no. 6 (October 1987): 77–78. http://dx.doi.org/10.1145/36792.36809.

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37

WENDLING, PATRICE. "Real-Time Performance Data Improved VTE Prophylaxis." Hospitalist News 2, no. 6 (June 2009): 4. http://dx.doi.org/10.1016/s1875-9122(09)70131-2.

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38

Qin, Biao, and Yunsheng Liu. "High performance distributed real-time commit protocol." Journal of Systems and Software 68, no. 2 (November 2003): 145–52. http://dx.doi.org/10.1016/s0164-1212(02)00145-0.

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39

Fricks, Ricardo M., Antonio Puliafito, and Kishor S. Trivedi. "Performance analysis of distributed real-time databases." Performance Evaluation 35, no. 3-4 (May 1999): 145–69. http://dx.doi.org/10.1016/s0166-5316(99)00008-5.

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40

Lu, S., H. Lu, and W. J. Kolarik. "Multivariate performance reliability prediction in real-time." Reliability Engineering & System Safety 72, no. 1 (April 2001): 39–45. http://dx.doi.org/10.1016/s0951-8320(00)00102-2.

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41

Mousas, Christos, and Christos-Nikolaos Anagnostopoulos. "Real-time performance-driven finger motion synthesis." Computers & Graphics 65 (June 2017): 1–11. http://dx.doi.org/10.1016/j.cag.2017.03.001.

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42

Sankaraiah, S., and C. Eswaran. "Performance optimization of real-time video decoding." Computers & Electrical Engineering 70 (August 2018): 366–79. http://dx.doi.org/10.1016/j.compeleceng.2016.08.022.

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43

Mao, Guoqiang. "A real-time loss performance monitoring scheme." Computer Communications 28, no. 2 (February 2005): 150–61. http://dx.doi.org/10.1016/j.comcom.2004.06.007.

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44

Khatibisepehr, Shima, Biao Huang, Swanand Khare, and Ramesh Kadali. "Real-time Performance Assessment of Inferential Sensors*." IFAC Proceedings Volumes 46, no. 32 (December 2013): 277–82. http://dx.doi.org/10.3182/20131218-3-in-2045.00093.

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45

Akl, Selim G. "Superlinear Performance in Real-Time Parallel Computation." Journal of Supercomputing 29, no. 1 (July 2004): 89–111. http://dx.doi.org/10.1023/b:supe.0000022574.59906.20.

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46

So, ATP, and WSM Suen. "Assessment of real-time lift traffic performance." Building Services Engineering Research and Technology 23, no. 3 (October 1, 2002): 143–50. http://dx.doi.org/10.1191/0143624402br037oa.

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47

Newport, John R. "A performance model for real-time systems." ACM SIGAda Ada Letters XV, no. 2 (March 1995): 59–73. http://dx.doi.org/10.1145/224126.224132.

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48

Clapp, Russell M., Louis Duchesneau, Richard A. Volz, Trevor N. Mudge, and Timothy Schultze. "Toward real-time performance benchmarks for Ada." Communications of the ACM 29, no. 8 (August 1986): 760–78. http://dx.doi.org/10.1145/6424.6428.

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49

Berggren, Hans, Mikael Gustafsson, and Lennart Lindh. "Measuring and analyzing real-time kernel performance." Microprocessing and Microprogramming 35, no. 1-5 (September 1992): 635–40. http://dx.doi.org/10.1016/0165-6074(92)90380-p.

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50

Garcia Nocetti, D. F., and P. J. Fleming. "Performance studies of parallel real-time controllers." IFAC Proceedings Volumes 24, no. 7 (September 1991): 249–54. http://dx.doi.org/10.1016/b978-0-08-041699-1.50046-x.

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