816 resultados para Task allocation


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Cost allocation is an inescapable problem in nearly every organization and in nearly every facet of accounting. Within large corporations there are several different types of units, like profit-making business units and non-profit service units. In order to evaluate the performance of the business units and to fund the operations of service units, the expenses of service production need to be allocated to the business units benefiting from the services.The objective of this thesis was to find good and fair allocating factors for the costs of corporate wide IT services. In order to reach this objective, the cost allocation process was studied in general and an overview of cost structure was established. All possible cost driver candidates were mapped and their good and bad properties were weighed. The cost allocation problem was handled separately according to organizational division of corporate IT department: infrastructure, administrative systems, sales system and e-business. The emphasis was on two largest cost groups: infrastructure costs and sales system costs. As a result of the study an allocation model is presented. It contains categorization of the costs, selected cost drivers and cost distributions for the current year.

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This paper analyses the effects of manipulating the cognitive complexity of L2 oral tasks on language production. It specifically focuses on self-repairs, which are taken as a measure of accuracy since they denote both attention to form and an attempt at being accurate. By means of a repeated measures de- sign, 42 lower-intermediate students were asked to perform three different tasks types (a narrative, and instruction-giving task, and a decision-making task) for which two degrees of cognitive complexity were established. The narrative task was manipulated along +/− Here-and-Now, an instruction-giving task ma- nipulated along +/− elements, and the decision-making task which is manipu- lated along +/− reasoning demands. Repeated measures ANOVAs are used for the calculation of differences between degrees of complexity and among task types. One-way ANOVA are used to detect potential differences between low- proficiency and high-proficiency participants. Results show an overall effect of Task Complexity on self-repairs behavior across task types, with different be- haviors existing among the three task types. No differences are found between the self-repair behavior between low and high proficiency groups. Results are discussed in the light of theories of cognition and L2 performance (Robin- son 2001a, 2001b, 2003, 2005, 2007), L1 and L2 language production models (Levelt 1989, 1993; Kormos 2000, 2006), and attention during L2 performance (Skehan 1998; Robinson, 2002).

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This research examines the impacts of the Swiss reform of the allocation of tasks which was accepted in 2004 and implemented in 2008 to "re-assign" the responsibilities between the federal government and the cantons. The public tasks were redistributed, according to the leading and fundamental principle of subsidiarity. Seven tasks came under exclusive federal responsibility; ten came under the control of the cantons; and twenty-two "common tasks" were allocated to both the Confederation and the cantons. For these common tasks it wasn't possible to separate the management and the implementation. In order to deal with nineteen of them, the reform introduced the conventions-programs (CPs), which are public law contracts signed by the Confederation with each canton. These CPs are generally valid for periods of four years (2008-11, 2012-15 and 2016-19, respectively). The third period is currently being prepared. By using the principal-agent theory I examine how contracts can improve political relations between a principal (Confederation) and an agent (canton). I also provide a first qualitative analysis by examining the impacts of these contracts on the vertical cooperation and on the implication of different actors by focusing my study on five CPs - protection of cultural heritage and conservation of historic monuments, encouragement of the integration of foreigners, economic development, protection against noise and protection of the nature and landscape - applied in five cantons, which represents twenty-five cases studies.

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The research on emotional intelligence (EI) has focused mainly on testing the incremental validity of EI with respect to general intelligence and personality; less attention has been devoted to investigating the potential interaction effects. In a self-presentation task that required participants to obtain positive evaluations from others, individuals low in IQ but high in EI performed as well as the high IQ individuals. In addition, the low emotionality individuals performed significantly higher when also high in EI. The results extend the previous findings on the compensatory effect of EI on low IQ to the domain of interpersonal effectiveness and shed light on the effective functioning of personality traits when interpreted with the interaction of EI. Overall this study suggests that the role of EI in predicting performance might have been overlooked by checking solely for main effects and illustrates new venues for understanding the contribution of EI in explaining emotion-laden performance.

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Paradoxically, high-growth, high-investment developing countries tend to experience capital outflows. This paper shows that this allocation puzzle can be explained simply by introducing uninsurable idiosyncratic investment risk in the neoclassical growth model with international trade in bonds, and by taking into account not only TFP catch-up, but also the capital wedge, that is, the distortions on the return to capital. The model fits the two following facts, documented on a sample of 67 countries between 1980 and 2003: (i) TFP growth is positively correlated with capital outflows in a sample including creditor countries; (ii) the long-run level of capital per efficient unit of labor is positively correlated with capital outflows. Consistently, we show that the capital flows predicted by the model are positively correlated with the actual ones in this sample once the capital wedge is accounted for. The fact that Asia dominates global imbalances can be explained by its relatively low capital wedge.

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The Commission on Classification and Terminology and the Commission on Epidemiology of the International League Against Epilepsy (ILAE) have charged a Task Force to revise concepts, definition, and classification of status epilepticus (SE). The proposed new definition of SE is as follows: Status epilepticus is a condition resulting either from the failure of the mechanisms responsible for seizure termination or from the initiation of mechanisms, which lead to abnormally, prolonged seizures (after time point t1 ). It is a condition, which can have long-term consequences (after time point t2 ), including neuronal death, neuronal injury, and alteration of neuronal networks, depending on the type and duration of seizures. This definition is conceptual, with two operational dimensions: the first is the length of the seizure and the time point (t1 ) beyond which the seizure should be regarded as "continuous seizure activity." The second time point (t2 ) is the time of ongoing seizure activity after which there is a risk of long-term consequences. In the case of convulsive (tonic-clonic) SE, both time points (t1 at 5 min and t2 at 30 min) are based on animal experiments and clinical research. This evidence is incomplete, and there is furthermore considerable variation, so these time points should be considered as the best estimates currently available. Data are not yet available for other forms of SE, but as knowledge and understanding increase, time points can be defined for specific forms of SE based on scientific evidence and incorporated into the definition, without changing the underlying concepts. A new diagnostic classification system of SE is proposed, which will provide a framework for clinical diagnosis, investigation, and therapeutic approaches for each patient. There are four axes: (1) semiology; (2) etiology; (3) electroencephalography (EEG) correlates; and (4) age. Axis 1 (semiology) lists different forms of SE divided into those with prominent motor systems, those without prominent motor systems, and currently indeterminate conditions (such as acute confusional states with epileptiform EEG patterns). Axis 2 (etiology) is divided into subcategories of known and unknown causes. Axis 3 (EEG correlates) adopts the latest recommendations by consensus panels to use the following descriptors for the EEG: name of pattern, morphology, location, time-related features, modulation, and effect of intervention. Finally, axis 4 divides age groups into neonatal, infancy, childhood, adolescent and adulthood, and elderly.

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How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.

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Globalisation and technological advances have made possible to offshore specific productive tasks (that do not require physical proximity to the actual location of the work unit) to foreign countries where these are usually performed at lower costs. We analyse the effect of task trade (i.e. task offshorability) on Spanish regional and national employment levels correlating a newly built index of task-delocalisation index to key variables such as the region’s wealth, the worker’s age and level of education, the importance of the service sector and the technological level of the economic activities undertaken in that particular geographical area. We conclude that approximately 25 per cent of Spanish occupations are potentially affected by task trade / offshoring and that this is likely to benefit Spanish economy (and the performance of specific regions, categories of workers and sectors) being Spain a potential recipient of tasks offshored from abroad. Also we obtain that Spain’s trade in tasks correlates strongly with the above variables, presenting significant regional differences.

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OBJECTIVE: To develop disease-specific recommendations for the diagnosis and management of eosinophilic granulomatosis with polyangiitis (Churg-Strauss syndrome) (EGPA). METHODS: The EGPA Consensus Task Force experts comprised 8 pulmonologists, 6 internists, 4 rheumatologists, 3 nephrologists, 1 pathologist and 1 allergist from 5 European countries and the USA. Using a modified Delphi process, a list of 40 questions was elaborated by 2 members and sent to all participants prior to the meeting. Concurrently, an extensive literature search was undertaken with publications assigned with a level of evidence according to accepted criteria. Drafts of the recommendations were circulated for review to all members until final consensus was reached. RESULTS: Twenty-two recommendations concerning the diagnosis, initial evaluation, treatment and monitoring of EGPA patients were established. The relevant published information on EGPA, antineutrophil-cytoplasm antibody-associated vasculitides, hypereosinophilic syndromes and eosinophilic asthma supporting these recommendations was also reviewed. DISCUSSION: These recommendations aim to give physicians tools for effective and individual management of EGPA patients, and to provide guidance for further targeted research.

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The European Forum on Epilepsy Research (ERF2013), which took place in Dublin, Ireland, on May 26-29, 2013, was designed to appraise epilepsy research priorities in Europe through consultation with clinical and basic scientists as well as representatives of lay organizations and health care providers. The ultimate goal was to provide a platform to improve the lives of persons with epilepsy by influencing the political agenda of the EU. The Forum highlighted the epidemiologic, medical, and social importance of epilepsy in Europe, and addressed three separate but closely related concepts. First, possibilities were explored as to how the stigma and social burden associated with epilepsy could be reduced through targeted initiatives at EU national and regional levels. Second, ways to ensure optimal standards of care throughout Europe were specifically discussed. Finally, a need for further funding in epilepsy research within the European Horizon 2020 funding programme was communicated to politicians and policymakers participating to the forum. Research topics discussed specifically included (1) epilepsy in the developing brain; (2) novel targets for innovative diagnostics and treatment of epilepsy; (3) what is required for prevention and cure of epilepsy; and (4) epilepsy and comorbidities, with a special focus on aging and mental health. This report provides a summary of recommendations that emerged at ERF2013 about how to (1) strengthen epilepsy research, (2) reduce the treatment gap, and (3) reduce the burden and stigma associated with epilepsy. Half of the 6 million European citizens with epilepsy feel stigmatized and experience social exclusion, stressing the need for funding trans-European awareness campaigns and monitoring their impact on stigma, in line with the global commitment of the European Commission and with the recommendations made in the 2011 Written Declaration on Epilepsy. Epilepsy care has high rates of misdiagnosis and considerable variability in organization and quality across European countries, translating into huge societal cost (0.2% GDP) and stressing the need for cost-effective programs of harmonization and optimization of epilepsy care throughout Europe. There is currently no cure or prevention for epilepsy, and 30% of affected persons are not controlled by current treatments, stressing the need for pursuing research efforts in the field within Horizon 2020. Priorities should include (1) development of innovative biomarkers and therapeutic targets and strategies, from gene and cell-based therapies to technologically advanced surgical treatment; (2) addressing issues raised by pediatric and aging populations, as well as by specific etiologies and comorbidities such as traumatic brain injury (TBI) and cognitive dysfunction, toward more personalized medicine and prevention; and (3) translational studies and clinical trials built upon well-established European consortia.

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The differentiation of workers into morphological subcastes (e.g., soldiers) represents an important evolutionary transition and is thought to improve division of labor in social insects. Soldiers occur in many ant and termite species, where they make up a small proportion of the workforce. A common assumption of worker caste evolution is that soldiers are behavioral specialists. Here, we report the first test of the "rare specialist" hypothesis in a eusocial bee. Colonies of the stingless bee Tetragonisca angustula are defended by a small group of morphologically differentiated soldiers. Contrary to the rare specialist hypothesis, we found that soldiers worked more (+34%-41%) and performed a greater variety of tasks (+23%-34%) than other workers, particularly early in life. Our results suggest a "rare elite" function of soldiers in T. angustula, that is, that they perform a disproportionately large amount of the work. Division of labor was based on a combination of temporal and physical castes, but soldiers transitioned faster from one task to the next. We discuss why the rare specialist assumption might not hold in species with a moderate degree of worker differentiation.

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In this paper we study student interaction in English and Swedish courses at a Finnish university. We focus on language choices made in task-related activities in small group interaction. Our research interests arose from the change in the teaching curriculum, in which content and language courses were integrated at Tampere University of Technology in 2013. Using conversation analysis, we analysed groups of 4-5 students who worked collaboratively on a task via a video conference programme. The results show how language alternation has different functions in 1) situations where students orient to managing the task, e.g., in transitions into task, or where they orient to technical problems, and 2) situations where students accomplish the task. With the results, we aim to show how language alternation can provide interactional opportunities for language learning. The findings will be useful in designing tasks in the future.

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X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

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The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.