905 resultados para Expectation Maximization


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The objective of this study is to determine the impact of expectation associated with placebo and caffeine ingestion. We used a three-armed, randomized, double-blind design. Two three-armed experiments varying instruction (true, false, control) investigated the role of expectations of changes in arousal (blood pressure, heart rate), subjective well-being, and reaction time (RT). In Experiment 1 (N = 45), decaffeinated coffee was administered, and expectations were produced in one group by making them believe they had ingested caffeinated coffee. In Experiment 2 (N = 45), caffeinated orange juice was given in both experimental groups, but only one was informed about the true content. In Experiment 1, a significant effect for subjective alertness was found in the placebo treatment compared to the control group. However, for RT and well-being no significant effects were found. In Experiment 2, no significant expectancy effects were found. Caffeine produced large effects for blood pressure in both treatments compared to the control group, but the effects were larger for the false information group. For subjective well-being (alertness, calmness), considerable but nonsignificant changes were found for correctly informed participants, indicating possible additivity of pharmacologic effect and expectations. The results tentatively indicate that placebo and expectancy effects primarily show through introspection.

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Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

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This paper examines whether Swiss firms maximize shareholder value. To find out, we survey the goals of 313 listed and unlisted firms. We then examine whether managers’ decisions are consistent with their goals and analyze whether performance corresponds to intentions. Our results show that most managers pursue conflicting targets. Many also declare that they do not maximize shareholder value. And those who claim they do sometimes rely on investment criteria that are inconsistent with that target. Finally, we find that share-price performance is marginally better when managers claim to maximize shareholder value, particularly when stock prices have fallen.

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Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

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Volunteer research in sports clubs has paid hardly any attention to the individual expectations even though matching conditions to the specific volunteer’s expectations represents a major management challenge. This article presents a person-oriented approach to the expectation profiles of volunteers that delivers the basis for identifying different volunteer segments. The approach assumes explicitly that volunteers in sports clubs develop specific expectations regarding their working conditions. These expectations were determined in a sample of 441 members of 45 selected sports clubs. Proximately, a cluster analysis revealed that volunteers vary in their expectations regarding voluntary work. Four different types of volunteers could be identified: (1) recognition seekers, (2) material incentive seekers, (3) participation and communication seekers, and (4) support seekers. These “expectation-based volunteer types” could also be characterized in socioeconomic, membershiprelated, and volunteer-work-related terms. These types could serve as a basis for designing specific voluntary work conditions in sports clubs.

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Mental imagery and perception are thought to rely on similar neural circuits, and many recent behavioral studies have attempted to demonstrate interactions between actual physical stimulation and sensory imagery in the corresponding sensory modality. However, there has been a lack of theoretical understanding of the nature of these interactions, and both interferential and facilitatory effects have been found. Facilitatory effects appear strikingly similar to those that arise due to experimental manipulations of expectation. Using a self-motion discrimination task, we try to disentangle the effects of mental imagery from those of expectation by using a hierarchical drift diffusion model to investigate both choice data and response times. Manipulations of expectation are reasonably well understood in terms of their selective influence on parameters of the drift diffusion model, and in this study, we make the first attempt to similarly characterize the effects of mental imagery. We investigate mental imagery within the computational framework of control theory and state estimation. • Mental imagery and perception are thought to rely on similar neural circuits; however, on more theoretical grounds, imagery seems to be closely related to the output of forward models (sensory predictions). • We reanalyzed data from a study of imagined self-motion. • Bayesian modeling of response times may allow us to disentangle the effects of mental imagery on behavior from other cognitive (top-down) effects, such as expectation.

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Determining the profit maximizing input-output bundle of a firm requires data on prices. This paper shows how endogenously determined shadow prices can be used in place of actual prices to obtain the optimal input-output bundle where the firm.s shadow profit is maximized. This approach amounts to an application of the Weak Axiom of Profit Maximization (WAPM) formulated by Varian (1984) based on shadow prices rather than actual prices. At these prices the shadow profit of a firm is zero. Thus, the maximum profit that could have been attained at some other input-output bundle is a measure of the inefficiency of the firm. Because the benchmark input-output bundle is always an observed bundle from the data, it can be determined without having to solve any elaborate programming problem. An empirical application to U.S. airlines data illustrates the proposed methodology.

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This study explored the relationship of attitudes, needs, and health services utilization patterns of elderly veterans who were identified and categorized by their expectation for and receipt of sick-role legitimation. Three prescription types (new, change, renewal) were defined as the operational variables. A population of 676 ambulatory, chronically ill (average age 60 years) veterans were sent a questionnaire (74% response rate). In addition, retrospective medical and prescription record review was performed for a 45% sample of respondents. The results were analyzed using discriminant function and regression analysis. Fewer than 20% of the veterans responding expected to receive more prescriptions than were presently prescribed, whereas over 80% expected refill authorizations. Distinct attitudinal, need, and utilization patterns were identified. ^

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This paper proposes a quiet zone probing approach which deals with low dynamic range quiet zone acquisitions. Lack of dynamic range is a feature of millimeter and sub-millimeter wavelength technologies. It is consequence of the gradually smaller power generated by the instrumentation, that follows a f^α law with frequency, being α≥1 variable depending on the signal source’s technology. The proposed approach is based on an optimal data reduction scenario which redounds in a maximum signal to noise ratio increase for the signal pattern, with minimum information losses. After theoretical formulation, practical applications of the technique are proposed.

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Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If data is to be sent to a far-away base station, collaborative beamforming by the sensors may help to dis- tribute the load among the nodes and reduce fast battery depletion. However, collaborative beamforming techniques are far from opti- mality and in many cases may be wasting more power than required. In this contribution we consider the issue of energy efficiency in beamforming applications. Using a convex optimization framework, we propose the design of a virtual beamformer that maximizes the network's lifetime while satisfying a pre-specified Quality of Service (QoS) requirement. A distributed consensus-based algorithm for the computation of the optimal beamformer is also provided

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Voters try to avoid wasting their votes even in PR systems. In this paper we make a case that this type of strategic voting can be observed and predicted even in PR systems. Contrary to the literature we do not see weak institutional incentive structures as indicative of a hopeless endeavor for studying strategic voting. The crucial question for strategic voting is how institutional incentives constrain an individual’s decision-making process. Based on expected utility maximization we put forward a micro-logic of an individual’s expectation formation process driven by institutional and dispositional incentives. All well-known institutional incentives to vote strategically that get channelled through the district magnitude are moderated by dispositional factors in order to become relevant for voting decisions. Employing data from Finland – because of its electoral system a particularly hard testing ground - we find considerable evidence for observable implications of our theory.

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A chapter supplementary to the author's Choice and Chance.

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Mode of access: Internet.