833 resultados para Imagery (Psychology)


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The present study investigated students' behavior across academic departments to establish how personality, demographic, educational, attitudinal, and climate (both psychological and departmental) predicted self-reported cheating behavior at a university, Participants were 107 students from a variety of academic disciplines, The results explain 50.5% of the variability in self-reported cheating behavior in terms of demographic (male, school education qualifications), departmental climate, and individual differences (Lie and Neuroticism scales), We concluded that an expanded theoretical perspective (utilizing a wide range of person and situation variables) explained more variability than would otherwise be explained from any single perspective, and that findings from the literature of integrity at work generalize to educational settings. Finally, we discuss the limitations and implications of this research.

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Rumor research, in general, and its delayed incorporation of the work, of rumor researcher Jamuna Prasad, in particular, exemplify how the intellectual climate of American social psychology discouraged the development of social approaches. In the present paper, we explain his conceptualization of how rumors start and spread, and explore findings from subsequent research supporting or negating his propositions. It is our contention that, although Prasad had identified the basic variables involved in rumor generation and transmission correctly, mainstream social psychological research in the 1940s did not incorporate his contributions. Instead, mirroring the Zeitgeist of American social psychology, rumor research was approached from a predominantly individual level of analysis. In the present paper, the authors have tried to resurrect some of the group-level variables from Prasad's treatment of rumor and to suggest that social psychology adopt a more 'social' approach to rumor.

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Trabalho realizado durante a vigência de bolsa de produtividade em pesquisa/CNPq.

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Forest cover of the Maringá municipality, located in northern Parana State, was mapped in this study. Mapping was carried out by using high-resolution HRC sensor imagery and medium resolution CCD sensor imagery from the CBERS satellite. Images were georeferenced and forest vegetation patches (TOFs - trees outside forests) were classified using two methods of digital classification: reflectance-based or the digital number of each pixel, and object-oriented. The areas of each polygon were calculated, which allowed each polygon to be segregated into size classes. Thematic maps were built from the resulting polygon size classes and summary statistics generated from each size class for each area. It was found that most forest fragments in Maringá were smaller than 500 m². There was also a difference of 58.44% in the amount of vegetation between the high-resolution imagery and medium resolution imagery due to the distinct spatial resolution of the sensors. It was concluded that high-resolution geotechnology is essential to provide reliable information on urban greens and forest cover under highly human-perturbed landscapes.

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OBJECTIVE: To investigate the relevance of subjective criteria adopted by a psychiatry and psychology consultation-liaison service, and their suitability in the evaluation of case registries and objective results. METHODS: Semi-structured interviews were conducted and all supervisors of the university hospital service were interviewed. Routinely collected case registries were also reviewed. Standardized assessment with content analysis for each category was carried out. RESULTS: The results showed distortions in the adopted service focus (doctor-patient relationship) and consultant requests. This focus is more on consulting physician-oriented interventions than on patients. DISCUSSION: Evaluation of the relevance of service criteria could help promoting quality assessment of the services provided, mainly when objective criteria have not yet been established to assure their suitability.

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The paper discusses mental imagery as an important part of information processing performed during interpreting. Mental imagery is examined to see if visual processing used to remember the source text or to facilitate its understanding helps to ‗off-load‘ other cognitive (mainly linguistic) resources in interpreting. The discussion is based on a neurocognitively-oriented depictivist model by Kosslyn (1994). The overview of mental imagery processes and systems is followed by the discussion of imagery used in interpreting. First, imagery development in student interpreters is described on the basis of a note-taking course for would-be consecutive interpreters organized by the author at AMU. The initial part of the course devoted to imagery involves visualizations of geographical, descriptive and narrative texts. The description abounds in authentic examples and presents conclusions for interpreting trainers. Later, imagery as employed by professional interpreters is discussed on the basis of a qualitative survey. General implications of the use of mental imagery for cognitive processing limitations in interpreting are presented in the concluding section.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Roots and rituals.The construction of ethnic identities, Ton Dekker, John Helsloot Carla Wijers editors, p. 267-268; Selected papers of the 6TH SIEF conference on 'Roots & rituals', Amsterdam 20-25 April 1998.

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In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

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Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000.