855 resultados para job search workshops


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This paper examines whether social support is a boundary-determining criterion in the job strain model of Karasek (1979). The particular focus is the extent to which different sources of social support, work overload and task control influence job satisfaction, depersonalization and supervisor assessments of work performance. Hypotheses are tested using prospective survey data from 80 clerical staff in a university setting. Results revealed 3-way interactions among levels of support (supervisor, co-worker, non-work), perceived task control and work overload on levels of work performance and employee adjustment (self-report). After controlling for levels of negative affect in all analyses, there was evidence that high levels of supervisor support mitigated against the negative effects of high strain jobs on levels of job satisfaction and reduced reported levels of depersonalization. Moreover, high levels of non-work support and co-worker support also mitigated against the negative effects of high strain jobs on levels of work performance. The results are discussed in terms of the importance of social support networks both at, and beyond, the work context.

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Ohman and colleagues provided evidence for preferential processing of pictures depicting fear-relevant animals by showing that pictures of snakes and spiders are found faster among pictures of fiowers and mushrooms than vice versa and that the speed of detecting fear-relevant animals was not affected by set size whereas the speed of detecting fiowers/mushrooms was. Experiment 1 replicated this finding. Experiment 2, however, found similar search advantages when pictures of cats and horses or of wolves and big cats were to be found among pictures of flowers and mushrooms. Moreover, Experiment 3, in a within subject comparison, failed to find faster identification of snakes and spiders than of cats and horses among flowers and mushrooms. The present findings seem to indicate that previous reports of preferential processing of pictures of snakes and spiders in a visual search task may reflect a processing advantage for animal pictures in general rather than fear-relevance.

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The image reconstruction using the EIT (Electrical Impedance Tomography) technique is a nonlinear and ill-posed inverse problem which demands a powerful direct or iterative method. A typical approach for solving the problem is to minimize an error functional using an iterative method. In this case, an initial solution close enough to the global minimum is mandatory to ensure the convergence to the correct minimum in an appropriate time interval. The aim of this paper is to present a new, simple and low cost technique (quadrant-searching) to reduce the search space and consequently to obtain an initial solution of the inverse problem of EIT. This technique calculates the error functional for four different contrast distributions placing a large prospective inclusion in the four quadrants of the domain. Comparing the four values of the error functional it is possible to get conclusions about the internal electric contrast. For this purpose, initially we performed tests to assess the accuracy of the BEM (Boundary Element Method) when applied to the direct problem of the EIT and to verify the behavior of error functional surface in the search space. Finally, numerical tests have been performed to verify the new technique.

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The main focus of this essay is the first American round-the-world scientific voyage, the U. S Exploring Expedition, which took place between 1838 and 1841 and was lead by Lieutenant Charles Wilkes. Here, I discuss the purposes of this expedition in the context of the voyages of circumnavigation accomplished by the various European powers during the same period.

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Chronic beryllium disease (CBD) is clinically similar to other granulomatous diseases such as sarcoidosis. It is often misdiagnosed if a thorough occupational history is not taken. When appropriate, a beryllium lymphocyte proliferation tests (BeLPT) need to be performed. We aimed to search for CBD among currently diagnosed pulmonary sarcoidosis patients and to identify the occupations and exposures in Ontario leading to CBD. Questionnaire items included work history and details of possible exposure to beryllium. Participants who provided a history of previous work with metals underwent BeLPTs and an ELISPOT on the basis of having a higher pretest probability of CBD. Among 121 sarcoid patients enrolled, 87 (72%) reported no known previous metal dust or fume exposure, while 34 (28%) had metal exposure, including 17 (14%) with beryllium exposure at work or home. However, none of these 34 who underwent testing had positive test results. Self-reported exposure to beryllium or metals was relatively common in these patients with clinical sarcoidosis, but CBD was not confirmed using blood assays in this population.

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Using the framework of Communication Accommodation Theory, this study investigated the extent to which job applicants objectively and subjectively altered their accents to converge to or diverge from the speech style of the interviewer Forty-eight male and 48 female job applicants participated in two interviews for a casual research assistant position. In one interview, the interviewer had a broad Australian English accent, and in the other one, the interviewer had a cultivated accent. Applicants showed broader accents with broad-accented interviewers than with cultivated-accented interviewers. Applicants did not converge to the cultivated-accented interviewers, however and male job applicants were more likely than mere females to diverge from the cultivated-accented interviewers. There were also discrepancies between objectively rated changes to applicants' accents and their subjective judgments about the extent of accent accommodation.

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Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.