894 resultados para Expectation
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We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.
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A case series to study factors related to family expectation regarding schizophrenic patients was conducted in an out-patient setting in the city of S. Paulo, Brazil. Patients diagnosed as presenting schizophrenia by the ICD 9th Edition and having had the disease for more than four years were included in the study. Family Expectation was measured by the difference between the Katz Adjustment Scale (R2 and R3) scores based on the relative's expectation and the socially expected activities of the patient (Discrepancy Score), and social adjustment was given by the DSM-III-R Global Assessment Scale (GAS) . Outcome assessments were made independently, and 44 patients comprised the sample (25 males and 19 females). The Discrepancy mean score was twice as high for males as for females (p < 0.02), and there was an inverse relationship between the discrepancy score and social adjustment (r =-0.46, p < 0.001). Moreover, sex and social adjustment exerted independent effects on the discrepancy score when age, age at onset and number of psychiatric admissions were controlled by means of a multiple regression technique. There was an interaction between sex and social adjustment, the inverse relationship between social adjustment and discrepancy score being more pronounced for males. These findings are discussed in the light of the potential association between the family environment, gender and social adjustment of schizophrenic patients, and the need for further research, i.e. ethnographic accounts of interactions between patient and relatives sharing households particularly in less developed countries.
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A crucial method for investigating patients with coronary artery disease (CAD) is the calculation of the left ventricular ejection fraction (LVEF). It is, consequently, imperative to precisely estimate the value of LVEF--a process that can be done with myocardial perfusion scintigraphy. Therefore, the present study aimed to establish and compare the estimation performance of the quantitative parameters of the reconstruction methods filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM). Methods: A beating-heart phantom with known values of end-diastolic volume, end-systolic volume, and LVEF was used. Quantitative gated SPECT/quantitative perfusion SPECT software was used to obtain these quantitative parameters in a semiautomatic mode. The Butterworth filter was used in FBP, with the cutoff frequencies between 0.2 and 0.8 cycles per pixel combined with the orders of 5, 10, 15, and 20. Sixty-three reconstructions were performed using 2, 4, 6, 8, 10, 12, and 16 OSEM subsets, combined with several iterations: 2, 4, 6, 8, 10, 12, 16, 32, and 64. Results: With FBP, the values of end-diastolic, end-systolic, and the stroke volumes rise as the cutoff frequency increases, whereas the value of LVEF diminishes. This same pattern is verified with the OSEM reconstruction. However, with OSEM there is a more precise estimation of the quantitative parameters, especially with the combinations 2 iterations × 10 subsets and 2 iterations × 12 subsets. Conclusion: The OSEM reconstruction presents better estimations of the quantitative parameters than does FBP. This study recommends the use of 2 iterations with 10 or 12 subsets for OSEM and a cutoff frequency of 0.5 cycles per pixel with the orders 5, 10, or 15 for FBP as the best estimations for the left ventricular volumes and ejection fraction quantification in myocardial perfusion scintigraphy.
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Nota: 18 valores
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We study the screening problem that arises in a framework where, initially, the agent is privately informed about both the expected production cost and the cost variability and, at a later stage, he learns privately the cost realization. The speci c set of relevant incentive constraints, and so the characteristics of the optimal mechanism, depend nely upon the curvature of the principal s marginal surplus function as well as the relative importance of the two initial information problems. Pooling of production levels is optimally induced with respect to the cost variability when the principal's knowledge imperfection about the latter is sufficiently less important than that about the expected cost.
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To assess the preferred methods to quit smoking among current smokers. Cross-sectional, population-based study conducted in Lausanne between 2003 and 2006 including 988 current smokers. Preference was assessed by questionnaire. Evidence-based (EB) methods were nicotine replacement, bupropion, physician or group consultations; non-EB-based methods were acupuncture, hypnosis and autogenic training. EB methods were frequently (physician consultation: 48%, 95% confidence interval (45-51); nicotine replacement therapy: 35% (32-38)) or rarely (bupropion and group consultations: 13% (11-15)) preferred by the participants. Non-EB methods were preferred by a third (acupuncture: 33% (30-36)), a quarter (hypnosis: 26% (23-29)) or a seventh (autogenic training: 13% (11-15)) of responders. On multivariate analysis, women preferred both EB and non-EB methods more frequently than men (odds ratio and 95% confidence interval: 1.46 (1.10-1.93) and 2.26 (1.72-2.96) for any EB and non-EB method, respectively). Preference for non-EB methods was higher among highly educated participants, while no such relationship was found for EB methods. Many smokers are unaware of the full variety of methods to quit smoking. Better information regarding these methods is necessary.
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The Andalusian Public Health System Virtual Library (Biblioteca Virtual del Sistema Sanitario Público de Andalucía, BV-SSPA) provides access to health information resources and services to healthcare professionals through its Website. This virtual environment demands higher users’ knowledge in order to satisfy of the need of information of our users, as digital natives as digital immigrants, improving at the same time the communication with all of them. 1. To collect clients' views and expectations according to their nature of digital natives and immigrants. 2. To know our online reputation. A Collecting User Expectation Questionnaire will be built, taking into account the segmentation of the BV-SSPA users’ professional groups of the Andalusian Public Health System. A pilot test will be run to check the survey dimensions and items about practices, attitudes and knowledge of our users. Two Quality Function Deployment (QFD) matrices will enable the BV-SSPA services to be targeted to our digital natives or digital immigrants, according to their nature, finding the best way to satisfy their information needs. We provide feedback on BV-SSPA: users can have the opportunity to post feedback about the site via the 'Contact us' section and comment about their experience. And Web 2.0 is a shop window, providing the opportunity to show the comments; and through time, our online reputation will be built, but the BV-SSPA must manage its own personal branding. Web 2.0 tools are a driver of improvement, because they provide a key source of insight into people's attitudes. Besides, the BV-SSPA digital identity will be analyzed through indicators like major search engine referrals breakdown, top referring sites (non search engines), or top search engine referral phrases, among others. Definition of digital native and digital immigrant profiles of the BV-SSPA, and their difference, will be explained by their expectations. The design of the two QFD matrices will illustrate in just one graph the requirements of both groups for tackling digital abilities and inequalities. The BV-SSPA could deliver information and services through alternative channels. On the other hand, we are developing a strategy to identify, to measure and to manage a digital identity through communication with the user and to find out our online reputation. With the use of different tools from quantitative and qualitative methodology, and the opportunities offered by Web 2.0 tools, the BV-SSPA will know the expectations of their users as a first step to satisfy their necessities. Personalization is pivotal to the success of the Site, delivering tailored content to individuals based on their recorded preferences. The valuable user research can be used during new product development and redesign. Besides positive interaction let us build trust, show authenticity, and foster loyalty: we improve with effort, communication and show.
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A crucial method for investigating patients with coronary artery disease (CAD) is the calculation of the left ventricular ejection fraction (LVEF). It is, consequently, imperative to precisely estimate the value of LVEF--a process that can be done with myocardial perfusion scintigraphy. Therefore, the present study aimed to establish and compare the estimation performance of the quantitative parameters of the reconstruction methods filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM). METHODS: A beating-heart phantom with known values of end-diastolic volume, end-systolic volume, and LVEF was used. Quantitative gated SPECT/quantitative perfusion SPECT software was used to obtain these quantitative parameters in a semiautomatic mode. The Butterworth filter was used in FBP, with the cutoff frequencies between 0.2 and 0.8 cycles per pixel combined with the orders of 5, 10, 15, and 20. Sixty-three reconstructions were performed using 2, 4, 6, 8, 10, 12, and 16 OSEM subsets, combined with several iterations: 2, 4, 6, 8, 10, 12, 16, 32, and 64. RESULTS: With FBP, the values of end-diastolic, end-systolic, and the stroke volumes rise as the cutoff frequency increases, whereas the value of LVEF diminishes. This same pattern is verified with the OSEM reconstruction. However, with OSEM there is a more precise estimation of the quantitative parameters, especially with the combinations 2 iterations × 10 subsets and 2 iterations × 12 subsets. CONCLUSION: The OSEM reconstruction presents better estimations of the quantitative parameters than does FBP. This study recommends the use of 2 iterations with 10 or 12 subsets for OSEM and a cutoff frequency of 0.5 cycles per pixel with the orders 5, 10, or 15 for FBP as the best estimations for the left ventricular volumes and ejection fraction quantification in myocardial perfusion scintigraphy.
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The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.
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It is very well known that the first succesful valuation of a stock option was done by solving a deterministic partial differential equation (PDE) of the parabolic type with some complementary conditions specific for the option. In this approach, the randomness in the option value process is eliminated through a no-arbitrage argument. An alternative approach is to construct a replicating portfolio for the option. From this viewpoint the payoff function for the option is a random process which, under a new probabilistic measure, turns out to be of a special type, a martingale. Accordingly, the value of the replicating portfolio (equivalently, of the option) is calculated as an expectation, with respect to this new measure, of the discounted value of the payoff function. Since the expectation is, by definition, an integral, its calculation can be made simpler by resorting to powerful methods already available in the theory of analytic functions. In this paper we use precisely two of those techniques to find the well-known value of a European call
Resumo:
It is very well known that the first succesful valuation of a stock option was done by solving a deterministic partial differential equation (PDE) of the parabolic type with some complementary conditions specific for the option. In this approach, the randomness in the option value process is eliminated through a no-arbitrage argument. An alternative approach is to construct a replicating portfolio for the option. From this viewpoint the payoff function for the option is a random process which, under a new probabilistic measure, turns out to be of a special type, a martingale. Accordingly, the value of the replicating portfolio (equivalently, of the option) is calculated as an expectation, with respect to this new measure, of the discounted value of the payoff function. Since the expectation is, by definition, an integral, its calculation can be made simpler by resorting to powerful methods already available in the theory of analytic functions. In this paper we use precisely two of those techniques to find the well-known value of a European call
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BACKGROUND: We assessed expectations to improve cardiovascular disease risk factors (CVD-RF) in participants to a health promotion program. PARTICIPANTS AND METHODS: Blood pressure (BP), blood glucose (BG), blood total cholesterol (TC), body mass index (BMI), and self-reported smoking were assessed in 1,598 volunteers from the general public (men: 40%; mean age: 56.7 +/- 12.7 years) participating in a mobile health promotion program in the Vaud canton, Switzerland. Participants were asked about their expectation to have their CVD-RF improved at a next visit scheduled 2-3 years later. RESULTS: Expectation for improved control was found in 90% of participants with elevated BP, 91% with elevated BG, 45% with elevated TC, 44% who were overweight, and 35% who were smoking. Expectation for TC improvement was reported more often by men, persons with high level of TC, and persons who had consulted a doctor in the past 12 months. Expectations to lose weight and to quit smoking were found more often in younger persons than the older ones. CONCLUSION: Volunteers from the general population participating in a health promotion program expected improved control more often for hypertension and dysglycemia than for dyslipidemia, overweight and smoking.
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Tämä työ on tehty kansainväliselle metsäteollisuusyritykselle. Työn lähtökohtana oli tarve tutkia yrityksen mahdollisuuksia laajentaa toimintaansa uudelle markkinasegmentille, eläinruokapakkausmarkkinoille. Johtuen maailmanlaajuisesta eläinruoankulutuksen kasvusta, eläinruokapakkaukset ovat yritykselle mielenkiintoinen uusi markkina-alue. Onnistunut markkinoilletulo vaatii asiakastarpeiden ja -odotusten huomioimista tuotekehitys- ja markkinastrategian muodostamisessa. Tämän työn tavoitteena oli selvittää asiakkaiden odotuksia eläinruokapakkauksille, sekä mallintaa alalla vallitsevia ostoprosesseja. Asiakastarvetutkimus suunniteltiin perustuen kirjallisuuteen ja alustaviin markkina- ja asiakasanalyyseihin. Alustavat analyysit ovat tarpeellisia lähtötilanteen ja trendien selvittämiseksi. Itse tutkimus toteutettiin semi-konstruktoituna teemahaastatteluna. Haastateltavat edustivat USA:n ja Euroopan johtavia eläinruokavalmistajia ja pakkausten jatkojalostajia. Työn tuloksena saatiin yksityiskohtaista tietoa asiakkaiden odotuksista eläinruokapakkauksille, paperin ominaisuuksille ja paperitoimittajille. Lisäksi mallinnettiin ostoprosesseja paperitoimittajien, pakkausten jalostajien ja eläinruokavalmistajien välillä. Tulosten perusteella on analysoitu yrityksen mahdollisuuksia menestyä uudella markkinasegmentillä. Lisäksi työssä annettiin ehdotuksia tuotekehitys- ja markkinastrategian muodostamiseen.