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Relevant bibliographies by topics / Information processing speed

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Academic literature on the topic 'Information processing speed'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Information processing speed"

1

Kail, Robert. "Speed of Information Processing." Journal of School Psychology 38, no. 1 (2000): 51–61. http://dx.doi.org/10.1016/s0022-4405(99)00036-9.

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Walker, Lisa A. S., Amy Cheng, Jason Berard, Lindsay I. Berrigan, Laura M. Rees, and Mark S. Freedman. "Tests of Information Processing Speed." International Journal of MS Care 14, no. 2 (2012): 92–99. http://dx.doi.org/10.7224/1537-2073-14.2.92.

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Reduction in information processing speed (IPS) is a key deficit in multiple sclerosis (MS). The Paced Auditory Serial Addition Test (PASAT), Symbol Digit Modalities Test (SDMT), and Computerized Test of Information Processing (CTIP) are used to measure IPS. Both the PASAT and SDMT are sensitive to deficits in IPS. The CTIP, a newer task, also shows promise. The PASAT has several limitations, and it is often perceived negatively by patients. Yet little supporting quantitative evidence of such perceptions has been presented. Therefore, in this study, subjective ratings of likeability, difficulty, and appropriateness of the PASAT, CTIP, and SDMT were obtained. Ratings were compared between MS patients and healthy controls. It was hypothesized that ratings of the PASAT would differ significantly from those of the SDMT and CTIP. The relationship between subjective ratings and objective performance was evaluated. Sixty-nine MS patients and 68 matched controls rated the three tests in terms of likeability, difficulty, and appropriateness for capturing cognitive deficits often associated with MS using a Likert scale. Both groups rated the PASAT as most difficult and least likeable. The MS group rated the PASAT and SDMT as more appropriate for measuring MS-related deficits than the CTIP. Subjects who performed better on the PASAT were more likely to rate it as easier. Ratings of the SDMT and CTIP did not vary consistently with performance. The findings lend quantitative support to the common belief that the PASAT is perceived as unpleasant. Other tests are available that are similarly sensitive to deficits in IPS and more palatable to the patient.

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Walker, Lisa A. S., Amy Cheng, Jason Berard, Lindsay I. Berrigan, Laura M. Rees, and Mark S. Freedman. "Tests of Information Processing Speed." International Journal of MS Care 15, S1 (2013): 2–11. http://dx.doi.org/10.7224/1537-2073-15.s1.2.

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Rabbitt, Patrick, and Louise Goward. "Age, Information Processing Speed, and Intelligence." Quarterly Journal of Experimental Psychology Section A 47, no. 3 (1994): 741–60. http://dx.doi.org/10.1080/14640749408401135.

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Two parallel, but independent, literatures have grown out of observations that individual differences in information processing speed, as expressed in performance on choice reaction time (C RT) tasks, modestly correlate with individual differences in age and IQ test performance. These associations have prompted theories that individual differences in information processing speed functionally determine individual differences in performance of all cognitive skills by people of different general intellectual ability (Eysenck, 1986; Jensen, 1985) or age (Salthouse, 1982, 1985). The experiments on which this literature has been based suffer from methodological weaknesses, such that comparisons have only been made very early in practice and have only concerned mean latencies for correct responses. An experiment compared 90 volunteers aged from 50 through 79 years who were grouped in terms of their performance on the AH 4 (Heim, 1968) IQ test. It explored the joint and independent effects of individual differences in age and in IQ test score and the effects of practice on mean latencies (C RTs) on the shapes of distributions of correct and incorrect responses and on the limiting speeds with which accurate responses can be made (speed/error trade-off functions). We suggest that a plausible explanation for the results is that individual differences in age and in general ability influence C RTs mainly because they affect the efficiency with which responses can be controlled to maximize speed while maintaining accuracy.

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Fink, Andreas, and Aljoscha C. Neubauer. "Speed of information processing, psychometric intelligence." Personality and Individual Differences 30, no. 6 (2001): 1009–21. http://dx.doi.org/10.1016/s0191-8869(00)00089-1.

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Hart, Robert P., Joseph A. Kwentus, Robert T. Leshner, and Robert Frazier. "Information processing speed in Friedreich's ataxia." Annals of Neurology 17, no. 6 (1985): 612–14. http://dx.doi.org/10.1002/ana.410170615.

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Brand, Chris. "Speed of information-processing and intelligence." Personality and Individual Differences 11, no. 5 (1990): 535–37. http://dx.doi.org/10.1016/0191-8869(90)90068-3.

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Kirby, N. H., and T. Nettelbeck. "Speed of information processing and age." Personality and Individual Differences 12, no. 2 (1991): 183–88. http://dx.doi.org/10.1016/0191-8869(91)90101-g.

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Friedman, Howard, Harvey A. Taub, Joseph F. Sturr, Katherine L. Church, and Richard A. Monty. "Hypnotizability and Speed of Visual Information Processing." International Journal of Clinical and Experimental Hypnosis 34, no. 3 (1986): 234–41. http://dx.doi.org/10.1080/00207148608406988.

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Gerritsen, Marleen J. J., Ina J. Berg, Betto G. Deelman, Annemarie C. Visser-Keizer, and Betty Meyboom-de Jong. "Speed of Information Processing After Unilateral Stroke." Journal of Clinical and Experimental Neuropsychology 25, no. 1 (2003): 1–13. http://dx.doi.org/10.1076/jcen.25.1.1.13622.

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Dissertations / Theses on the topic "Information processing speed"

1

Bennett, Susan Nicole. "Speed of information processing and mental retardation /." Title page, contents and abstract only, 1999. http://web4.library.adelaide.edu.au/theses/09ARPS/09arpsb472.pdf.

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Torrens-Burton, Anna. "Information processing speed in ageing : is it task dependent?" Thesis, Swansea University, 2018. https://cronfa.swan.ac.uk/Record/cronfa40835.

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Evidence indicates that information processing speed slows as age increases and disproportionately so with impaired cognition and various neurodegenerative diseases such as Alzheimer’s disease. The new DSM-5 criteria for neuro-cognitive disorders state that measuring information processing speed associated with attentional function should be included within dementia diagnosis. However, what is not clarified is that outcome variability can occur, in part, as a result of methodological factors i.e. type of attention-related test/ attentional function and by person-related factors such as sex and education. In addition, there appears to be a dichotomy between the types of tests used within research studies and clinical settings which should be addressed [Haworth et al, 2016].The aim of the research presented in this thesis was to investigate how using different tests of attentional function in similar groups of young and older adults may affect the outcome measure of information processing speed (RT) and its variability (IIV). Part of this aim was to determine whether the number of trials may influence performance i.e. RT, IIV and accuracy (number of errors). Another aim was to determine whether result outcome is affected similarly across tests by a variety of person-related factors i.e. sex, education, objective cognitive measures and particularly previously un-tested factors of subjective memory function and perceived test difficulty which may help determine whether subjective feelings are associated with slower and more variable information processing speed and may influence study outcome. The first study [Chapter 2] comprised of a visual search test commonly used in research as a sensitive measure of ageing upon RT and IIV and attentional shifting, yet not examined particularly in relation to subjective memory function and perceived test difficulty. Results indicated that information processing speed was significantly slowed in older compared to younger adults and attentional shifting was poorer in older adults. There was no relationship with subjective memory function whereas the influence of sex, education and perceived test difficulty were dependent on the condition and age. In the second, larger study including the Trail Making Test (TMT), Simple reaction time (RT) test, Choice RT test and Multi-Item Localization test (MILO) [Chapters 3- 5], the results indicated that in all tests older adults were significantly slower and more variable than young adults at group level. Person-related factors were influential depending on the test used. Subjective memory function and education were only influential within conditions of the MILO and perceived test difficulty influential in Trails B and Choice RT. Large effect sizes in visual search, MILO and the Choice RT suggested they were most sensitive to ageing effects. In conclusion, we speculate which attentional tests may be more useful in research and than those already used in clinical settings i.e. TMT and highlight the need to take into consideration different factors depending on the attentional test used so as not to misinterpret normal levels of information processing speed in ostensibly healthy aging.

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Stokes, Tonya Lee. "The relations among speed of information processing, intelligence, and strategy use." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ29194.pdf.

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Redick, Thomas Scott. "Working Memory Capacity, Perceptual Speed, and Fluid Intelligence: An Eye Movement Analysis." Thesis, Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-11202006-143305/.

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Byrne, Michael Dwyer. "A computational theory of working memory : speed, parallelism, activation, and noise." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/29797.

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Uhland, Gary A. "Beyond difference scores : testing models of speed of information-processing using confirmatory factor analysis." PDXScholar, 1988. https://pdxscholar.library.pdx.edu/open_access_etds/3845.

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This study has two parts: Part I discusses the limitations of difference scores and exploratory factor analysis for representing speed of information-processing stages in the context of a reanalysis of a study by Vernon (1983). Vernon interpreted the differences between objectively measured reaction times on various simple cognitive tasks as components of speed of information processing. Correlations were calculated among these differences and subjected to exploratory factor analysis. The factors obtained from this analysis were interpreted by Vernon in terms of short-term and long-term memory processing constructs. The use of difference scores, however, implies an additive model allowance for random error, which correlations between these differences. that does not make leads to spurious The application of exploratory factor analysis to among these differences compounds uncover latent variables the problem because it admits many alternative interpretations which cannot be tested against one another for goodness-of-fit to the data. Confirmatory factor analysis addresses these problems. This thesis demonstrates that the correlations between the difference scores can be accounted for in terms of factors obtained from factor analysis of the original reaction time data. These factors lead to an alternative interpretation of the results which is contrasted with Vernon's interpretation. Part II of this study illustrates the use of confirmatory factor analysis with this kind of data. An attempt to test the assumptions of Vernon's difference score model with confirmatory factor analysis did not succeed because the implied model was too constrained for the statistical program we were using; consequently, the program could not find a starting solution. In order to demonstrate how confirmatory factor analysis can be used to test models of speed of cognitive processing, Part II partially replicates a study by Lansman, Donaldson, Hunt, & Yantis (1982). This research analyzed a simple cognitive reaction time task that was examined in detail by Vernon. Donaldson (1983) used the Lansman et al. data to compare difference scores and part correlational techniques with a general approach based on analysis of covariance structures to demonstrate how the components of cognitive processes can be explicated using confirmatory factor analysis.

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Manglani, Heena R. "A neural network analysis of sedentary behavior and information processing speed in multiple sclerosis." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu15253688510945.

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Luciano, Michelle. "An information processing approach to the genetic study of psychometric intelligence : links between processing speed, working memory and IQ /." [St. Lucia, Qld.], 2001. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16373.pdf.

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Ross, Lesley Anne. "Does speed of processing training impact driving mobility in older adults? /." Birmingham, Ala. : University of Alabama at Birmingham, 2007. https://www.mhsl.uab.edu/dt/2009r/ross.pdf.

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Thesis (Ph. D.)--University of Alabama at Birmingham, 2007.<br>Title from PDF of title page (viewed Oct. 13, 2009). Additional advisors: Jerri D. Edwards, David L. Roth, David E. Vance, Virginia G. Wadley. Includes bibliographical references (p. 36-44).

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Wilson, Hanna Jade. "The effects of glucose on memory, attention and speed of information processing in healthy, young adults /." Title page, table of contents and abstract only, 2003. http://web4.library.adelaide.edu.au/theses/09SSPS/09sspsw7462.pdf.

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Books on the topic "Information processing speed"

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Kyllonen, Patrick C. Dimensions of information processing speed. Air Force Human Resources Laboratory, Air Force Systems Command, 1985.

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Tovée, Martin J. The speed of thought: Information processing in the cerebral cortex. Springer, 1998.

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Stokes, Tonya Lee. The relations among speed of information processing, intelligence, and strategy use. National Library of Canada = Bibliothèque nationale du Canada, 1999.

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Souleyrette, Reginald R. High speed computing to facilitate real time analysis of transportation planning alternatives: Final report. Midwest Transportation Center, Iowa State University, 1995.

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Chao gao mi du chao kuai su guang xin xi cun chu: Super-density and super-speed optical data storage. Liaoning ke xue ji shu chu ban she, 2010.

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Mason, Heather Labon. The development and standardisation of the Speed of Tactile Information Processing Test (STIP) for use with children and young people who are blind. University of Birmingham, 1996.

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Grigor'ev, Anatoliy, Evgeniy Isaev, and Pavel Tarasov. Transfer, storage and processing of large volumes of scientific data. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1073525.

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The textbook examines large scientific projects and the amount of data generated by them, and provides an overview of scientific computer networks that allow high-speed transmission of large amounts of data for these projects. The article considers the computing systems offered by the leading manufacturers of computer equipment for processing large amounts of data and providing both the possibilities of storing large amounts of data, including distributed data, and the means of analytics and parallel data processing in real time. Special attention is paid to the security of the transmitted scientific information. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students of technical specialties of bachelor's degree, master's degree, specialty, studying in the areas of "Applied Mathematics and Computer Science", "Business Computer Science" and "Computer Science and Computer Engineering".

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Evans, Robert. Art, science and informatics: Visualisation of large, complex data sets in high-speed measurement of the microstructure of wood. University of British Columbia, 2002.

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1956-, DeLuca John, and Kalmar Jessica, eds. Information processing speed in clinical applications. Taylor & Francis, 2007.

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A, Vernon Philip, ed. Speed of information-processing and intelligence. Ablex Pub. Corp., 1987.

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Book chapters on the topic "Information processing speed"

1

Sweet, Lawrence H. "Information Processing Speed." In Encyclopedia of Clinical Neuropsychology. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_1321.

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First, Michael B., Elizabeth Spencer, Elizabeth Spencer, et al. "Information Processing Speed." In Encyclopedia of Autism Spectrum Disorders. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_346.

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Sweet, Lawrence H. "Information Processing Speed." In Encyclopedia of Clinical Neuropsychology. Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_1321.

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Sweet, Lawrence H. "Information Processing Speed." In Encyclopedia of Clinical Neuropsychology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_1321-2.

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Kuschner, Emily S., and Gregory L. Wallace. "Information Processing Speed." In Encyclopedia of Autism Spectrum Disorders. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-91280-6_346.

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Lu, Haiyan, Jiani Heng, and Chen Wang. "An AI-Based Hybrid Forecasting Model for Wind Speed Forecasting." In Neural Information Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70093-9_23.

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Park, Moon-sung, Il-sook Kim, Eun-kyung Cho, and Young-hee Kwon. "High Speed Extraction Model of ROI for Automatic Logistics System." In Neural Information Processing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30499-9_108.

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Hu, Rukun, and Ping Guo. "Speed Up Spatial Pyramid Matching Using Sparse Coding with Affinity Propagation Algorithm." In Neural Information Processing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24965-5_53.

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Hasegawa, Ryohei P., and Yoshiko Nakamura. "An Attempt of Speed-up of Neurocommunicator, an EEG-Based Communication Aid." In Neural Information Processing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46687-3_28.

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Pan, Hongxia, Mingzhi Pan, Runpeng Zhao, and Haifeng Ren. "Fault Diagnosis of a High-Speed Automaton Based on Structure Vibration Response Analysis." In Neural Information Processing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34475-6_68.

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Conference papers on the topic "Information processing speed"

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Wei, Cui, Li Xingguang, Li Guiying, and Chen Dianren. "High-speed Information Acquisition and Processing Using FPGA." In 2009 Third International Symposium on Intelligent Information Technology Application. IEEE, 2009. http://dx.doi.org/10.1109/iita.2009.431.

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Bykovsky, Yuri A., Anatoly A. Markilov, Vladislav G. Rodin, et al. "Optical information processing systems with various structure incoherent radiation." In Twenty-Third International Congress on High-Speed Photography and Photonics, edited by Valentina P. Degtyareva, Mikhail A. Monastyrski, Mikhail Y. Schelev, and Alexander V. Smirnov. SPIE, 1999. http://dx.doi.org/10.1117/12.350525.

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Zhu, Yun, Zihua Weng, Yuanqing Huang, and Zhimin Chen. "A novel high-speed magneto-optic switch design and analysis." In ICO20:Optical Information Processing, edited by Yunlong Sheng, Songlin Zhuang, and Yimo Zhang. SPIE, 2006. http://dx.doi.org/10.1117/12.668191.

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Grigoryeva, Lyudmila, Julie Henriques, Laurent Larger, and Juan-Pablo Ortega. "Time-Delay Reservoir Computers and High-Speed Information Processing Capacity." In 2016 19th IEEE Intl Conference on Computational Science and Engineering (CSE), IEEE 14th Intl Conference on Embedded and Ubiquitous Computing (EUC), and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES). IEEE, 2016. http://dx.doi.org/10.1109/cse-euc-dcabes.2016.230.

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Fu, Lin, Anzhi He, and Zhenhua Li. "Real-time measurement and high-speed identification of highway pavement surface deformation." In ICO20:Optical Information Processing, edited by Yunlong Sheng, Songlin Zhuang, and Yimo Zhang. SPIE, 2006. http://dx.doi.org/10.1117/12.667910.

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Kumar, Subhash. "Modification in Hadoop Framework for Improving Big Data Processing Speed." In Department of Information Science and Technology. Research Publishing Services, 2015. http://dx.doi.org/10.3850/978-981-09-4426-1_036.

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Song, Guoming, Houjun Wang, and Jingfeng Wang. "A high-speed realtime vibration measusement and analysis system based on DSP technology." In ICO20:Optical Information Processing, edited by Yunlong Sheng, Songlin Zhuang, and Yimo Zhang. SPIE, 2006. http://dx.doi.org/10.1117/12.667912.

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Zhang, Daxing, Junfeng Xu, Haihua Li, and Heming Li. "A Novel Image Watermarking Algorithm with Fast Processing Speed." In 2009 International Conference on Information Engineering and Computer Science. IEEE, 2009. http://dx.doi.org/10.1109/iciecs.2009.5362803.

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Jie Sun, Dev V. Gupta, Patrick A. Kelly, and Weibo Gong. "Analog signal processing for ultra high speed data communication." In 2007 6th International Conference on Information, Communications & Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icics.2007.4449836.

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Andreev, A. L., Natalia I. Chernova, Igor N. Kompanets, et al. "Advances in ferroelectric liquid crystals for high-speed spatial-light modulators." In Optical Information Processing: International Conference, edited by Yuri V. Gulyaev and Dennis R. Pape. SPIE, 1994. http://dx.doi.org/10.1117/12.166021.

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Reports on the topic "Information processing speed"

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Uhland, Gary. Beyond difference scores : testing models of speed of information-processing using confirmatory factor analysis. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.5717.

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Bauer, Andrew, James Forsythe, Jayanarayanan Sitaraman, Andrew Wissink, Buvana Jayaraman, and Robert Haehnel. In situ analysis and visualization to enable better workflows with CREATE-AV™ Helios. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40846.

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The CREATE-AV™ Helios CFD simulation code has been used to accurately predict rotorcraft performance under a variety of flight conditions. The Helios package contains a suite of tools that contain almost the entire set of functionality needed for a variety of workflows. These workflows include tools customized to properly specify many in situ analysis and visualization capabilities appropriate for rotorcraft analysis. In situ is the process of computing analysis and visualization information during a simulation run before data is saved to disk. In situ has been referred to with a variety of terms including co-processing, covisualization, coviz, etc. In this paper we describe the customization of the pre-processing GUI and corresponding development of the Helios solver code-base to effectively implement in situ analysis and visualization to reduce file IO and speed up workflows for CFD analysts. We showcase how the workflow enables the wide variety of Helios users to effectively work in post-processing tools they are already familiar with as opposed to forcing them to learn new tools in order post-process in situ data extracts being produced by Helios. These data extracts include various sources of information customized to Helios, such as knowledge about the near- and off-body grids, internal surface extracts with patch information, and volumetric extracts meant for fast post-processing of data. Additionally, we demonstrate how in situ can be used by workflow automation tools to help convey information to the user that would be much more difficult when using full data dumps.

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Federal Information Processing Standards Publication: high speed 25-position interface for data terminal equipment and data circuit-terminating equipment. National Bureau of Standards, 1987. http://dx.doi.org/10.6028/nist.fips.154.

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Federal Information Processing Standards Publication: high speed 25-position interface for data terminal equipment and data circuit-terminating equipment. National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nist.fips.154-1988.

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