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Journal articles on the topic 'Response Time'

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Published: 4 June 2021
Last updated: 31 July 2024

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1

LEMESHKO, Andrii, Аrtem ANTONENKO, Oleksii DOBROVOLSKYI, and Viacheslav ZAVADSKYI. "APACHE WEB SERVER RESPONSE TIME OPTIMIZATION." Herald of Khmelnytskyi National University. Technical sciences 319, no. 2 (April 27, 2023): 189–201. http://dx.doi.org/10.31891/2307-5732-2023-319-1-189-201.

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This article explores approaches to online optimization of the Apache web server, focusing on the MaxClients parameter (which controls the maximum number of workers). Using both empirical and analytical methods, we show that MaxClients has a concave-upward effect on response time, and hence hill-climbing techniques can be used to determine the optimal value of MaxClients. We investigate two optimizers that use hill climbing—one based on Newton’s method and one based on fuzzy control. A third technique is a heuristic that exploits the relationship between bottleneck utilization and response time minimization. In all cases, online optimization reduces the response time by a factor of 10 or more compared to the static default value. The trade-offs between online schemes are as follows. Newton’s method is well known but does not provide consistent results for highly variable data such as response times. Fuzzy control is more reliable but converges slowly. The heuristic works well in our prototype system, but it can be difficult to generalize because it requires knowledge of resource bottlenecks and the ability to measure their use. This topic is relevant in the context of a rapidly growing number of web applications and high requirements for the performance and efficiency of web servers. This topic explores how to improve the speed and response time of the Apache web server using various techniques and settings, such as optimizing server settings, using caching, data compression, optimizing request routing, and more. The purpose of this research is to improve the performance and response speed of the Apache web server, which can be useful for developers and administrators of web applications and services. The speed and response time of web servers are critical factors in meeting user needs and achieving business goals for web applications and services. Apache is one of the most widely used web servers in the world, so optimizing the response time of the Apache server is an important task for many developers and administrators of web applications and services. This study will examine various approaches and techniques for optimizing the response time of the Apache web server, including configuring server parameters, using caching, data compression, optimizing request routing, and others. The results of the study can be useful for developers and administrators of web applications and services that deal with the use of the Apache web server. Optimizing Apache server response time can significantly improve the performance and efficiency of web applications and services, which in turn can lead to user satisfaction and business goals.
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2

Bauer, Connie L. "Direct response advertising:Forecasting responses over time." Journal of Direct Marketing 1, no. 4 (1987): 38–50. http://dx.doi.org/10.1002/dir.4000010407.

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3

Zeng, Xinyu, and Olha Lysa. "RESPONSE TIME IN INERTIAL MEASUREMENT UNIT CONTROL ALGORITHMS." Measuring Equipment and Metrology 85, no. 2 (2024): 5–8. http://dx.doi.org/10.23939/istcmtm2024.02.005.

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The Inertial Measurement Unit (IMU) [1] is a cornerstone technology in various fields, ranging from aerospace to consumer electronics, where accurate motion tracking is paramount. Central to the effectiveness of an IMU is the quality of data processing, particularly in the context of filtering techniques. This study compares two filtering methods: Complementary Filters and Kalman Filters, in their application to IMU data processing. Complementary Filters, known for their simplicity and efficiency, contrast with the more complex but potentially more accurate Kalman Filters. Our investigation delves into the underpinnings of each filter, followed by a practical analysis of their performance in real-world IMU applications. We comprehensively compare these filters in terms of accuracy, computational efficiency, and ease of implementation. This research offers valuable insights for practitioners and researchers in selecting the most suitable filtering approach for specific IMU-based applications, enhancing the overall quality of motion sensing and analysis.
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4

Zhu, Ming, Xiaoliu Cui, and Guodong Fan. "Modeling and Verification of Response Time of QoS-aware Web Service Composition by Timed CSP." Journal of Ubiquitous Systems and Pervasive Networks 11, no. 1 (May 1, 2019): 01–09. http://dx.doi.org/10.5383/juspn.11.01.001.

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5

Kodratoff, Y., and J. A. Campbell. "Response time." Artificial Intelligence Review 2, no. 1 (1988): 1–2. http://dx.doi.org/10.1007/bf00139622.

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6

Deanna K. Kreisel. "Response: Queering Time." Victorian Studies 60, no. 2 (2018): 236. http://dx.doi.org/10.2979/victorianstudies.60.2.09.

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7

Corominas, Albert, Wieslaw Kubiak, and Natalia Moreno Palli. "Response time variability." Journal of Scheduling 10, no. 2 (January 25, 2007): 97–110. http://dx.doi.org/10.1007/s10951-006-0002-8.

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8

Silverman, R. A. ""Vertical Response Time": The Hidden Component of Ambulance Response Time." Academic Emergency Medicine 12, Supplement 1 (May 1, 2005): 142. http://dx.doi.org/10.1197/j.aem.2005.03.399.

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9

Scherbaum, Stefan, and Maja Dshemuchadse. "Higher response time increases theta energy, conflict increases response time." Clinical Neurophysiology 124, no. 7 (July 2013): 1477–79. http://dx.doi.org/10.1016/j.clinph.2012.12.007.

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10

Vuorinen, Mari, Pentti Varpasuo, and Jukka Kahkonen. "ICONE19-43207 Reaction-time response of a large commercial aircraft." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2011.19 (2011): _ICONE1943. http://dx.doi.org/10.1299/jsmeicone.2011.19._icone1943_81.

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11

Hanson, John, and Leonard Green. "Time and response matching with topographically different responses." Animal Learning & Behavior 14, no. 4 (December 1986): 435–42. http://dx.doi.org/10.3758/bf03200091.

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12

Gondan, Matthias. "Incorrect responses in the response time interaction contrast." Journal of Mathematical Psychology 92 (October 2019): 102249. http://dx.doi.org/10.1016/j.jmp.2019.01.006.

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13

NAGAOKA, Keizo, and Maomi UENO. "ITEM RESPONSE THEORY FOR ITEM RESPONSE TIME." Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 18, no. 2 (1991): 1–8. http://dx.doi.org/10.2333/jbhmk.18.2_1.

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14

RATCLIFF, R. "Modeling response signal and response time data☆." Cognitive Psychology 53, no. 3 (November 2006): 195–237. http://dx.doi.org/10.1016/j.cogpsych.2005.10.002.

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15

Joseph, M. "Finding Response Times in a Real-Time System." Computer Journal 29, no. 5 (May 1, 1986): 390–95. http://dx.doi.org/10.1093/comjnl/29.5.390.

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16

Knippa, Sara, and Jennifer Popies. "Response to the Time." Critical Care Nurse 40, no. 5 (October 1, 2020): 67–71. http://dx.doi.org/10.4037/ccn2020624.

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17

Brewer, Gene A. "Analyzing Response Time Distributions." Zeitschrift für Psychologie 219, no. 2 (January 2011): 117–24. http://dx.doi.org/10.1027/2151-2604/a000056.

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The analysis of response times from prospective memory experiments has resulted in multiple theoretical propositions about the role of attention in prospective memory. Extant theories of prospective memory are in good agreement that attention is necessary for detecting intention-related cues. However, these theories were primarily formulated to describe differences in mean reaction times across experimental conditions. While this approach has been fruitful for establishing a fundamental relation between attention and prospective memory, reaction time modeling techniques can be applied to prospective memory data to better constrain theorizing. In the current work, the ex-Gaussian distribution is fit to data from a prospective memory task. The results from this analysis suggest that modeling reaction time data has the potential for clarifying our understanding of the role of attention in prospective memory.
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18

Evans, Denis J., and Gary P. Morriss. "Time-dependent response theory." Molecular Physics 64, no. 3 (June 20, 1988): 521–34. http://dx.doi.org/10.1080/00268978800100373.

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19

Raatikainen, K. E. E. "Approximating response time distributions." ACM SIGMETRICS Performance Evaluation Review 17, no. 1 (April 1989): 190–99. http://dx.doi.org/10.1145/75372.75393.

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20

SCHUMAN, HOWARD, and JACQUELINE SCOTT. "Response Effects Over Time:." Sociological Methods & Research 17, no. 4 (May 1989): 398–408. http://dx.doi.org/10.1177/0049124189017004005.

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21

Valente, Thomas W., Leanne Dougherty, and Emily Stammer. "Response Bias over Time." Field Methods 29, no. 4 (June 2, 2017): 303–16. http://dx.doi.org/10.1177/1525822x17703718.

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This study investigates potential bias that may arise when surveys include question items for which multiple units are elicited. Examples of such items include questions about experiences with multiple health centers, comparison of different products, or the solicitation of egocentric network data. The larger the number of items asked about each named individual or location, the greater potential interviewer and respondent burden accrues to the naming of more names. Interviewers may be inclined to limit the number of names elicited to reduce the amount of time required to complete the interviews. We tested whether such bias occurred from data collected in northwest Ghana by contrasting group learning with individual learning. The results provided mixed evidence for both group and individual learning and stress the need to take actions such as increased training, change in incentives, and/or monitoring responses to guard against such results.
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22

Johansen, Anders. "Response time of internauts." Physica A: Statistical Mechanics and its Applications 296, no. 3-4 (July 2001): 539–46. http://dx.doi.org/10.1016/s0378-4371(01)00202-3.

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23

Schwarz, R., M. Fernandes, A. Fantoni, M. Vieira, P. Ferreira, and P. Sanguino. "Photocarrier response time scanner." Journal of Non-Crystalline Solids 299-302 (April 2002): 1261–66. http://dx.doi.org/10.1016/s0022-3093(01)01147-4.

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24

Echenique, Federico, and Kota Saito. "Response time and utility." Journal of Economic Behavior & Organization 139 (July 2017): 49–59. http://dx.doi.org/10.1016/j.jebo.2017.04.008.

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25

Bavaria, Joseph E. "RESPONSE: It Is Time." Journal of the American College of Cardiology 76, no. 21 (November 2020): 2568. http://dx.doi.org/10.1016/j.jacc.2020.10.016.

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26

Melvin, Thomas M., Keith R. Briffa, Kurt Nicolussi, and Michael Grabner. "Time-varying-response smoothing." Dendrochronologia 25, no. 1 (May 2007): 65–69. http://dx.doi.org/10.1016/j.dendro.2007.01.004.

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27

García-Villoria, Alberto, and Rafael Pastor. "Minimising maximum response time." Computers & Operations Research 40, no. 10 (October 2013): 2314–21. http://dx.doi.org/10.1016/j.cor.2013.03.014.

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28

Cohen, Michael X., and Roland Nigbur. "Reply to “Higher response time increases theta energy, conflict increases response time”." Clinical Neurophysiology 124, no. 7 (July 2013): 1479–81. http://dx.doi.org/10.1016/j.clinph.2013.03.013.

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29

Ando, Shin, and Einoshin Suzuki. "Minimizing response time in time series classification." Knowledge and Information Systems 46, no. 2 (March 1, 2015): 449–76. http://dx.doi.org/10.1007/s10115-015-0826-7.

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30

Bradley, Steven, William Henderson, and David Kendall. "Using Timed Automata for Response Time Analysis of Distributed Real-Time Systems." IFAC Proceedings Volumes 32, no. 1 (May 1999): 209–14. http://dx.doi.org/10.1016/s1474-6670(17)39989-5.

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31

Alanazi, Abdulrahman Naif. "The effect of ambulance response time on patient and transfer to hospital." Journal of Medical Science And clinical Research 11, no. 12 (December 2, 2023): 01–05. http://dx.doi.org/10.18535/jmscr/v11i12.01.

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This study investigates the critical relationship between ambulance response time and its impact on patient outcomes during the transfer to the hospital. Timely and efficient ambulance responses are fundamental in emergency medical services, significantly influencing patient morbidity and mortality rates. The research employs a retrospective analysis of ambulance response times and patient transfer data collected over a specific period. Key variables include response time intervals, patient demographics, medical conditions, and outcomes during hospital transfer. Statistical analyses, including regression modeling, are utilized to assess the correlation between response times and patient outcomes, considering potential confounding factors. Preliminary findings indicate a noteworthy association between extended ambulance response times and adverse patient outcomes, emphasizing the urgency of swift emergency medical interventions. This research contributes valuable insights to emergency medical service providers, policymakers, and healthcare professionals, aiming to enhance pre-hospital care strategies and improve overall patient well-being. The implications of these findings extend beyond statistical correlations, emphasizing the imperative need for efficient emergency response systems to optimize patient care and outcomes. Keywords: Ambulance response time, Patient care, Emergency medical service, Hospital.
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32

Sidaway, Ben. "Fractionated Reaction Time in Lower Leg Responses: A Note on Response Programming Time." Research Quarterly for Exercise and Sport 59, no. 3 (September 1988): 248–51. http://dx.doi.org/10.1080/02701367.1988.10605512.

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33

Davison David Fadaraliki, Matsvimbo. "Efficient Load Balancing in Heterogeneous Cloud to Reduce Response Time and Processing Time Using BUSY & AVAILABLE Algorithm." International Journal of Science and Research (IJSR) 12, no. 8 (August 5, 2023): 289–92. http://dx.doi.org/10.21275/sr22223032201.

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34

Cerino, E. S., and R. S. Stawski. "ASSOCIATIONS BETWEEN AFFECT, MEAN RESPONSE TIME, AND RESPONSE TIME INCONSISTENCY AMONG OLDER ADULTS." Innovation in Aging 2, suppl_1 (November 1, 2018): 755. http://dx.doi.org/10.1093/geroni/igy023.2788.

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35

Silvia, Paul J., Katherine N. Cotter, and Alexander P. Christensen. "Time is a Funny Thing: Response Times and Humor Quality in a Creative Joke Production Task." Creativity. Theories – Research - Applications 11, no. 1 (January 1, 2024): 1–17. http://dx.doi.org/10.2478/ctra-2024-0001.

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Abstract Generating creative ideas takes time: the first idea to come to mind is usually obvious, and people need time to shift strategies, enact executive processes, and evaluate and revise an idea. The present research explored the role of time in creative humor production tasks, which give people a prompt and ask them to create a funny response. A sample of 152 young adults completed four joke stems prompts. Their response times were recorded, and the responses were judged for humor quality (funniness) by six independent judges and by the participants themselves. Mixed-effect models found that, at the within-person level, response time’s link to humor quality diverged for judges and participants. The judges’ ratings of funniness predicted longer response times (relatively funnier responses took longer to create), but participants’ self-ratings of their own responses predicted shorter response times (relatively funnier responses were created faster). Controlling for elaboration (quantified via word count of the response) diminished the effect of judge-rated humor but not participant-rated humor. Taken together, the results suggest that the role of time in humor generation is complex: judges may be weighting elaboration more heavily when judging funniness, whereas participants may be weighting metacognitive cues like ease-of-generation when judging their own ideas.
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36

Lee, Yi-Hsuan, and Zhiliang Ying. "A Mixture Cure-Rate Model for Responses and Response Times in Time-Limit Tests." Psychometrika 80, no. 3 (October 4, 2014): 748–75. http://dx.doi.org/10.1007/s11336-014-9419-8.

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37

Oh, H. R., W. H. Chung, and M. Kim. "Transformation of timed Petri nets for response time estimation." IEE Proceedings E Computers and Digital Techniques 137, no. 1 (1990): 74. http://dx.doi.org/10.1049/ip-e.1990.0007.

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38

Viščor, Petr, and N. B. Olsen. "Frequency and time response in relaxation time semiconductors." Journal of Non-Crystalline Solids 90, no. 1-3 (February 1987): 25–28. http://dx.doi.org/10.1016/s0022-3093(87)80377-0.

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39

Kirby, N. H., and J. McConaghy. "Responding time: A response equivalent to inspection time." Personality and Individual Differences 7, no. 5 (January 1986): 687–94. http://dx.doi.org/10.1016/0191-8869(86)90038-3.

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40

Ferrando, Pere J., and Urbano Lorenzo-Seva. "A Measurement Model for Likert Responses That Incorporates Response Time." Multivariate Behavioral Research 42, no. 4 (December 28, 2007): 675–706. http://dx.doi.org/10.1080/00273170701710247.

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41

Soland, James, Steven L. Wise, and Lingyun Gao. "Identifying Disengaged Survey Responses: New Evidence Using Response Time Metadata." Applied Measurement in Education 32, no. 2 (March 13, 2019): 151–65. http://dx.doi.org/10.1080/08957347.2019.1577244.

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42

MONTARE, ALBERTO. "CONDITIONING THE REACTION TIME RESPONSE." Perceptual and Motor Skills 71, no. 6 (1990): 509. http://dx.doi.org/10.2466/pms.71.6.509-510.

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43

Yu, Hai Xi, Feng Lin, Hui Cai, and Jian Wen Shao. "Development of Response Time Tester." Applied Mechanics and Materials 602-605 (August 2014): 2366–69. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2366.

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In order to solve the difficult problem of the transmission-type smoke meter response time, which needs to be settled urgently, response time testers have been developed, according to China's metrological verification regulation JJG 976-2010《Calibration procedures of transmission-type smoke meter》. The tester integrated several communication protocols of transmission-type smoke meter manufacturers, takes measurements at every 20ms, draws absorptance N curves in real time and displays the final response time in man-machine interface. The measuring range of the tester is (600~2000) ms, and the error is ±20ms. It is very convenient, fast, and accurate to verify for transmission–type smoke meter and traffic analyzer.
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44

Montare, Alberto. "Conditioning the Reaction Time Response." Perceptual and Motor Skills 71, no. 2 (October 1990): 509–10. http://dx.doi.org/10.2466/pms.1990.71.2.509.

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45

Friedman, Franklin D. "Response on Published Waiting Time." Annals of Emergency Medicine 79, no. 3 (March 2022): 317. http://dx.doi.org/10.1016/j.annemergmed.2021.11.005.

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46

Farago, Claire. "Response: Time Out of Joint." Art Bulletin 87, no. 3 (September 2005): 424–29. http://dx.doi.org/10.1080/00043079.2005.10786252.

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47

Thomsen, Volker. "Response time of a thermometer." Physics Teacher 36, no. 9 (December 1998): 540–41. http://dx.doi.org/10.1119/1.880128.

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48

Dinshaw, Carolyn. "Response Time: Linear, Nonlinear, Queer." Studies in Gender and Sexuality 16, no. 1 (January 2, 2015): 40–43. http://dx.doi.org/10.1080/15240657.2015.1005494.

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49

Culler, J. ""Feminism in Time": A Response." Modern Language Quarterly 65, no. 1 (March 1, 2004): 177–94. http://dx.doi.org/10.1215/00267929-65-1-177.

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50

Avigad, Gideon, Alex Goldvard, and Shaul Salomon. "Time-response-based evolutionary optimization." Engineering Optimization 47, no. 4 (April 22, 2014): 533–49. http://dx.doi.org/10.1080/0305215x.2014.905552.

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