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Artigos de revistas sobre o tema "Human information processing"

Autor: Grafiati

Publicado: 4 de junho de 2021

Última modificação: 25 de julho de 2025

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1

CALLISTA ROY, SISTER. "Human Information Processing." Annual Review of Nursing Research 6, no. 1 (1988): 237–62. http://dx.doi.org/10.1891/0739-6686.6.1.237.

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2

Callaway, Enoch, Roy Halliday, Hilary Naylor, Lovelle Yano, and Karen Herzig. "Drugs and Human Information Processing." Neuropsychopharmacology 10, no. 1 (1994): 9–19. http://dx.doi.org/10.1038/npp.1994.2.

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3

Velmans, Max. "Is human information processing conscious?" Behavioral and Brain Sciences 14, no. 4 (1991): 651–69. http://dx.doi.org/10.1017/s0140525x00071776.

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AbstractInvestigations of the function of consciousness in human information processing have focused mainly on two questions: (1) Where does consciousness enter into the information processing sequence, and (2) how does conscious processing differ from preconscious and unconscious processing? Input analysis is thought to be initially “preconscious” and “pre-attentive” - fast, involuntary, and automatic. This is followed by “conscious,” “focal-attentive” analysis, which is relatively slow, voluntary, and flexible. It is thought that simple, familiar stimuli can be identified preconsciously, but

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4

Petrie, Rachel X. A., and Ian J. Deary. "Smoking and human information processing." Psychopharmacology 99, no. 3 (1989): 393–96. http://dx.doi.org/10.1007/bf00445565.

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5

Spangenberg, J. F. A., and F. J. N. Nijhuis. "Human information processing in science." Scientometrics 18, no. 5-6 (1990): 389–407. http://dx.doi.org/10.1007/bf02020153.

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6

Rogers, Tracy. "Human information processing under stress." Journal of Emergency Management 21, no. 2 (2023): 141–54. http://dx.doi.org/10.5055/jem.0756.

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This article is a review of literature focused on how human beings process information under stress. Three major theories on information processing are reviewed: cue utilization theory, attentional control theory, and working memory capacity theory. Different conditions that can cause an individual to feel stress are examined, how stress affects information processing, ways which stress may be beneficial, and different ways to mitigate stress, so they may process information more accurately and efficiently. Throughout the article, examples of how stress can affect incident commanders respondin

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7

Ishii, Hiroshi. "The Dawn of Kansei Information Processing. Human Interface and 'Kansei' Information Processing." Journal of the Institute of Image Information and Television Engineers 52, no. 1 (1998): 56–59. http://dx.doi.org/10.3169/itej.52.56.

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8

Lynn, Christopher W., Lia Papadopoulos, Ari E. Kahn, and Danielle S. Bassett. "Human information processing in complex networks." Nature Physics 16, no. 9 (2020): 965–73. http://dx.doi.org/10.1038/s41567-020-0924-7.

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9

PAAS, FRED G. W. C., and JOS J. ADAM. "Human information processing during physical exercise." Ergonomics 34, no. 11 (1991): 1385–97. http://dx.doi.org/10.1080/00140139108964879.

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10

Robertson, Ivan T. "Human information-processing strategies and style." Behaviour & Information Technology 4, no. 1 (1985): 19–29. http://dx.doi.org/10.1080/01449298508901784.

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11

Fedzechkina, Maryia, Becky Chu, and T. Florian Jaeger. "Human Information Processing Shapes Language Change." Psychological Science 29, no. 1 (2017): 72–82. http://dx.doi.org/10.1177/0956797617728726.

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Human languages exhibit both striking diversity and abstract commonalities. Whether these commonalities are shaped by potentially universal principles of human information processing has been of central interest in the language and psychological sciences. Research has identified one such abstract property in the domain of word order: Although sentence word-order preferences vary across languages, the superficially different orders result in short grammatical dependencies between words. Because dependencies are easier to process when they are short rather than long, these findings raise the pos

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12

Callaway, Enoch. "The Biology of Human Information Processing." Journal of Psychoactive Drugs 18, no. 4 (1986): 315–18. http://dx.doi.org/10.1080/02791072.1986.10472363.

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13

Rugg, Michael D. "Psychophysiological approaches to human information processing." Biological Psychology 22, no. 2 (1986): 208–9. http://dx.doi.org/10.1016/0301-0511(86)90073-6.

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14

Wilkinson, Thomas M. "Human Information Processing, Health Information Technology, and Medical Outcomes." JAMA 302, no. 13 (2009): 1417. http://dx.doi.org/10.1001/jama.2009.1417.

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15

Ramsey, N. F. "Neurophysiological factors in human information processing capacity." Brain 127, no. 3 (2003): 517–25. http://dx.doi.org/10.1093/brain/awh060.

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16

Jayles, Bertrand, Ramón Escobedo, Roberto Pasqua, et al. "Collective information processing in human phase separation." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1807 (2020): 20190801. http://dx.doi.org/10.1098/rstb.2019.0801.

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In our digital societies, individuals massively interact through digital interfaces whose impact on collective dynamics can be important. In particular, the combination of social media filters and recommender systems can lead to the emergence of polarized and fragmented groups. In some social contexts, such segregation processes of human groups have been shown to share similarities with phase separation phenomena in physics. Here, we study the impact of information filtering on collective segregation behaviour of human groups. We report a series of experiments where groups of 22 subjects have

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17

Spivey, Michael J. "Redesigning our theories of human information processing." Discourse, Cognition and Communication 15, no. 3 (2007): 261–65. http://dx.doi.org/10.1075/idj.15.3.08spi.

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18

KITAGAWA, NORIMICHI, and CHARLES SPENCE. "Audiotactile multisensory interactions in human information processing." Japanese Psychological Research 48, no. 3 (2006): 158–73. http://dx.doi.org/10.1111/j.1468-5884.2006.00317.x.

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19

Dickhaut, John, Vernon Smith, Baohua Xin, and Aldo Rustichini. "Human economic choice as costly information processing." Journal of Economic Behavior & Organization 94 (October 2013): 206–21. http://dx.doi.org/10.1016/j.jebo.2013.08.001.

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20

Sanders, Andries F. "Human information processing: Measures, mechanisms and models." Acta Psychologica 76, no. 2 (1991): 199–200. http://dx.doi.org/10.1016/0001-6918(91)90048-5.

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21

Ren, Fuji. "Affective Information Processing and Recognizing Human Emotion." Electronic Notes in Theoretical Computer Science 225 (January 2009): 39–50. http://dx.doi.org/10.1016/j.entcs.2008.12.065.

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22

Duncan, James R. "Human Information Processing, Health Information Technology, and Medical Outcomes—Reply." JAMA 302, no. 13 (2009): 1417. http://dx.doi.org/10.1001/jama.2009.1418.

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23

Alvandi, Ebrahim Oshni. "Emotions and Information Processing." International Journal of Synthetic Emotions 2, no. 1 (2011): 1–14. http://dx.doi.org/10.4018/jse.2011010101.

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An animate system standing in nature and trying to investigate its surroundings for different purposes does a type of cognitive processing. Emotions as mental states are leading human cognitive features that attract life by interactions processed in the world. This paper examines how this cognitive feature process works. By researching history and theories related to emotions and their generation, it becomes clear that information processing is discussed as a tool for their processes. Three different styles of information processing are evaluated for emotional processes. The pragmatic notion o

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24

Rikani, Azadeh A., Zia Choudhry, Adnan Maqsood Choudhry, Nasir Rizvi, and Huma Ikram. "Spatial information processing by the human visual system." El Mednifico Journal 2, no. 3 (2014): 309. http://dx.doi.org/10.18035/emj.v2i3.156.

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25

Lynn, Christopher W., Lia Papadopoulos, Ari E. Kahn, and Danielle S. Bassett. "Author Correction: Human information processing in complex networks." Nature Physics 16, no. 12 (2020): 1238. http://dx.doi.org/10.1038/s41567-020-0985-7.

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26

Driver, Michael J., Katarina Svensson, Roy P. Amato, and Larry E. Pate. "A Human-Information-Processing Approach to Strategic Change." International Studies of Management & Organization 26, no. 1 (1996): 41–58. http://dx.doi.org/10.1080/00208825.1996.11656673.

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27

No authorship indicated. "Review of Eye Movements and Human Information Processing." Contemporary Psychology: A Journal of Reviews 31, no. 10 (1986): 820. http://dx.doi.org/10.1037/024205.

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28

Lounasmaa, O. V., M. Hamalainen, R. Hari, and R. Salmelin. "Information processing in the human brain: magnetoencephalographic approach." Proceedings of the National Academy of Sciences 93, no. 17 (1996): 8809–15. http://dx.doi.org/10.1073/pnas.93.17.8809.

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29

Truta, Meda, and Mihai Popescu. "Intelligent Control System Based on Human Information Processing." IFAC Proceedings Volumes 34, no. 3 (2001): 117–20. http://dx.doi.org/10.1016/s1474-6670(17)34336-7.

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30

Howes, Andrew, Richard L. Lewis, and Satinder Singh. "Utility Maximization and Bounds on Human Information Processing." Topics in Cognitive Science 6, no. 2 (2014): 198–203. http://dx.doi.org/10.1111/tops.12089.

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31

Seo, Chang-Jin. "Artificial Vision System using Human Visual Information Processing." Journal of Digital Convergence 12, no. 11 (2014): 349–55. http://dx.doi.org/10.14400/jdc.2014.12.11.349.

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32

Coles, MichaelG H. "Psychophysiology and contemporary models of human information processing." Biological Psychology 20, no. 3 (1985): 189–90. http://dx.doi.org/10.1016/0301-0511(85)90066-3.

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33

Ramanujan, S., and RB Cooper. "A human information processing perspective on software maintenance." Omega 22, no. 2 (1994): 185–203. http://dx.doi.org/10.1016/0305-0483(94)90078-7.

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34

Nagy, Peter, Istvan Pinter, and Mihely Bagany. "Phasetransition-like Changes in Human Visual Information Processing." JUCS - Journal of Universal Computer Science 12, no. (9) (2006): 1345–57. https://doi.org/10.3217/jucs-012-09-1345.

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35

Czigler, István, Gergely Csibra, and Ágnes Ambró. "Age and Information Processing." European Psychologist 2, no. 3 (1997): 247–57. http://dx.doi.org/10.1027/1016-9040.2.3.247.

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This paper reviews our recent studies on the effects of aging on human information processing. In these studies the event-related potentials of the brain (ERPs) recorded in visual discrimination tasks were compared in younger and older groups of subjects in four experiments. We obtained a slight age-related delay of the NA component of the ERP. This component is a correlate of elementary pattern-identification processes. Obvious latency differences appeared on the anterior positivity, selection negativity, and N2b components in tasks where the target stimuli were defined by two stimulus charac

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36

Yang, C. Y. David, and Jon D. Fricker. "Using Human Information Processing Principles to Design Advanced Traveler Information Systems." Transportation Research Record: Journal of the Transportation Research Board 1759, no. 1 (2001): 1–8. http://dx.doi.org/10.3141/1759-01.

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37

Chakarov, Vihren E., Krassimir T. Atanassov, and Anthony G. Shannon. "Generalized Net Model of Auditory Information Processing." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 5 (2007): 452–56. http://dx.doi.org/10.20965/jaciii.2007.p0452.

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In a series of papers we have described the human body, its separate systems, and their behavior using Generalized Nets (GNs). Here we construct a GN-model that represents auditory information processing - the first on our research on the structure and behavior of the human nervous system.

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38

Jackson, Russell E., and Dustin P. Calvillo. "Evolutionary Relevance Facilitates Visual Information Processing." Evolutionary Psychology 11, no. 5 (2013): 147470491301100. http://dx.doi.org/10.1177/147470491301100506.

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Visual search of the environment is a fundamental human behavior that perceptual load affects powerfully. Previously investigated means for overcoming the inhibitions of high perceptual load, however, generalize poorly to real-world human behavior. We hypothesized that humans would process evolutionarily relevant stimuli more efficiently than evolutionarily novel stimuli, and evolutionary relevance would mitigate the repercussions of high perceptual load during visual search. Animacy is a significant component to evolutionary relevance of visual stimuli because perceiving animate entities is t

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39

Fagan, Joseph, and Robert E. Ployhart. "The information processing foundations of human capital resources: Leveraging insights from information processing approaches to intelligence." Human Resource Management Review 25, no. 1 (2015): 4–11. http://dx.doi.org/10.1016/j.hrmr.2014.09.003.

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40

Diamant, Emanuel. "Modeling human-like intelligent image processing: An information processing perspective and approach." Signal Processing: Image Communication 22, no. 6 (2007): 583–90. http://dx.doi.org/10.1016/j.image.2007.05.007.

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41

Burgin, Mark, Eugene Eberbach, and Rao Mikkilineni. "Processing Information in the Clouds." Proceedings 47, no. 1 (2020): 25. http://dx.doi.org/10.3390/proceedings2020047025.

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Cloud computing makes the necessary resources available to the appropriate computation to improve scaling, resiliency, and the efficiency of computations. This makes cloud computing a new paradigm for computation by upgrading its artificial intelligence (AI) to a higher order. To explore cloud computing using theoretical tools, we use cloud automata as a new model for computation. Higher-level AI requires infusing features of the human brain into AI systems such as incremental learning all the time. Consequently, we propose computational models that exhibit incremental learning without stoppin

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42

Burgin, Mark, Eugene Eberbach, and Rao Mikkilineni. "Processing Information in the Clouds." Proceedings 47, no. 1 (2020): 25. http://dx.doi.org/10.3390/proceedings47010025.

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Cloud computing makes the necessary resources available to the appropriate computation to improve scaling, resiliency, and the efficiency of computations. This makes cloud computing a new paradigm for computation by upgrading its artificial intelligence (AI) to a higher order. To explore cloud computing using theoretical tools, we use cloud automata as a new model for computation. Higher-level AI requires infusing features of the human brain into AI systems such as incremental learning all the time. Consequently, we propose computational models that exhibit incremental learning without stoppin

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43

Vaghely, Ivan P., Pierre-André Julien, and André Cyr. "Information transformation: Some missing links." Human Systems Management 26, no. 3 (2007): 157–72. http://dx.doi.org/10.3233/hsm-2007-26302.

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Using grounded theory along with participant observation and interviews the authors explore how individuals in organizations process information. They build a model of human information processing which links the cognitivist-constructionist perspective to an algorithmic-heuristic continuum. They test this model using non-parametric procedures and find interesting results showing links to efficient information processing outcomes such as contributions to decision-making, knowledge-creation and innovation. They also identify some elements of best practice by efficient human information processin

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44

Venturino, Michael. "Timesharing, Cognition, and Human Performance in Complex Information Systems." Proceedings of the Human Factors Society Annual Meeting 30, no. 9 (1986): 880–81. http://dx.doi.org/10.1177/154193128603000906.

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Applications of advanced technology to modern systems have resulted in the requirement for the human operator to process large volumes of information at rapid rates. Such systems may impose substantial attentional and timesharing requirements on the operator, often exceeding human information processing capabilities. Consequently, there is a critical need to investigate and understand the human information processing system in order to identify generalizable, empirically derived principles of human timesharing capabilities. Of particular interest are current theoretical approaches to human att

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45

Massaro, Dominic W., and Donald A. Norman. "Memory and Attention: An Introduction to Human Information Processing." American Journal of Psychology 107, no. 4 (1994): 597. http://dx.doi.org/10.2307/1423002.

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46

Hatamoto, K., M. Nagamachi, K. Ito, and T. Tsuji. "Human visual information processing on formation of subjective contours." Japanese journal of ergonomics 25, Supplement (1989): 112–13. http://dx.doi.org/10.5100/jje.25.supplement_112.

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47

Godlewska, Magdalena. "Smart Document-Centric Processing of Human Oriented Information Flows." Computing and Informatics 37, no. 3 (2018): 673–92. http://dx.doi.org/10.4149/cai_2018_3_673.

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48

Rappelsberger, P., N. Vath, S. Weiss, et al. "EEG Frequency and Phase Coupling during Human Information Processing." Methods of Information in Medicine 40, no. 02 (2001): 106–11. http://dx.doi.org/10.1055/s-0038-1634470.

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AbstractNeuronal activity during information processing is represented by oscillations within local or widespread neuronal networks. These oscillations may be recorded by the EEG (electroencephalogram). The oscillatory interaction between neuronal ensembles may be at one single frequency or at different frequencies due to non-linear coupling. The investigation of momentary coherence and phase enables the examination of synchronized oscillatory network activity during fast-changing cognitive processes. On this basis information transfer from occipital areas towards frontal areas could be descri

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49

Foss, Donald J. "Review of Human Information Processing: Measures, Mechanisms, and Models." Contemporary Psychology: A Journal of Reviews 36, no. 3 (1991): 263. http://dx.doi.org/10.1037/029570.

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50

Sobol, M. G., and G. Klein. "New graphics as computerized displays for human information processing." IEEE Transactions on Systems, Man, and Cybernetics 19, no. 4 (1989): 893–98. http://dx.doi.org/10.1109/21.35357.

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