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Intelligence and parallel versus sequential organization of information processing in analogical reasoning

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Orzechowski J., Nęcka E.
Psychological Studies
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2011
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vol. 49
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issue 5
41-53
EN
The construct of the organization of information processing (OIP) has been adopted as a possible cognitive mechanism responsible for human intelligent functioning. Participants (N = 77) were asked to solve an analogical reasoning task, a test of divided attention, a working memory capacity test, and Raven’s Advanced Progressive Matrices as a standard test of general fl uid intelligence. On the basis of the chronometric analysis of their performance in the analogy task, participants were divided into those preferring to use parallel or sequential modes of organization of information processing. It appeared that intelligent people using the parallel mode of processing obtained the best results in the analogical reasoning test. Other subgroups did not differ substantially from one another. It also appeared that intelligent people using the parallel mode of processing performed equally well regardless of their attentional resources and working memory capacity, whereas people using the sequential mode of processing were much more dependent on these basic cognitive limitations. A compensatory mechanism is suggested in order to account for this data: the parallel mode of processing probably helps to compensate for defi cient attention or impaired working memory, whereas the sequential mode cannot act in a compensatory way.
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Big Data – definicje, wyzwania i technologie informatyczne

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Tabakow M., Korczak J., Franczyk B.
Informatyka Ekonomiczna
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2014
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issue 1(31)
138-153
XX
Big Data as a complex IT issues, is one of the most important challenges of the modern digital world. At the present time, the continuous inflow of a large amount of information from different sources, and thus with different characteristics, requires the introduction of new data analysis techniques and technology. In particular, Big Data requires the use of parallel processing and the departure from the classical scheme of data storage. Thus, in this paper we review the basic issues related to the theme of Big Data: different definitions of „Big Data” research and technological problems and challenges in terms of data volume, their diversity, the reduction of the dimension of data quality and inference capabilities. We also consider the future direction of work in the field of exploration of the possibilities of Big Data in various areas of management.
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