983 resultados para decision algorithm


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In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

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This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results

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Nominal Unification is an extension of first-order unification where terms can contain binders and unification is performed modulo α equivalence. Here we prove that the existence of nominal unifiers can be decided in quadratic time. First, we linearly-reduce nominal unification problems to a sequence of freshness and equalities between atoms, modulo a permutation, using ideas as Paterson and Wegman for first-order unification. Second, we prove that solvability of these reduced problems may be checked in quadràtic time. Finally, we point out how using ideas of Brown and Tarjan for unbalanced merging, we could solve these reduced problems more efficiently

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Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.

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The development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.

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BACKGROUND: The relationship between physicians and patients has undergone important changes, and the current emancipation of patients has led to a real partnership in medical decision making. The present study aimed to assess patients' preferences on different aspects of decision making during treatment and potential complications, as well as the amount and type of preoperative information wanted before visceral surgery. METHODS: This was a prospective non-randomized study based on a questionnaire given to 253 consecutive patients scheduled for elective gastrointestinal surgery. RESULTS: In considering surgical complications or treatment in the intensive care unit, 64 % of patients wished to take an active role in any medical decisions. The respective figures for cardiac resuscitation and treatment limitations were 89 and 60 %. As for information, 73, 77, and 47 % of patients wish detailed information, information on a potential ICU hospitalization, and knowledge of cardiac resuscitation, respectively. Elderly and low-educated patients were significantly less interested in shared medical decision making (p = 0.003 and 0.015), and in receiving information (p = 0.03 and 0.05). Similarly, involvement of the family in decision making was significantly less important to elderly and male patients (p = 0.05 and 0.03, respectively). Neither the type of operation (minor or major) nor the severity of disease (malignancies versus non-malignancies) was a significant factor for shared decision making, information, or family involvement. CONCLUSIONS: The vast majority of surgical patients clearly want to get adequate preoperative information about their disease and the planned treatment. They also consider it crucial to be involved in any kind of decision making for treatment and complications. For most patients, the family role is limited to supporting the treating physicians if the patient is unable to participate in decision making.

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OBJECTIVE: We aim to explore how health surrogates of patients with dementia proceed in decision making, which considerations are decisive, and whether family surrogates and professional guardians decide differently. METHODS: We conducted an experimental vignette study using think aloud protocol analysis. Thirty-two family surrogates and professional guardians were asked to decide on two hypothetical case vignettes, concerning a feeding tube placement and a cardiac pacemaker implantation in patients with end-stage dementia. They had to verbalize their thoughts while deciding. Verbalizations were audio-recorded, transcribed, and analyzed according to content analysis. By experimentally changing variables in the vignettes, the impact of these variables on the outcome of decision making was calculated. RESULTS: Although only 25% and 31% of the relatives gave their consent to the feeding tube and pacemaker placement, respectively, 56% and 81% of the professional guardians consented to these life-sustaining measures. Relatives decided intuitively, referred to their own preferences, and focused on the patient's age, state of wellbeing, and suffering. Professional guardians showed a deliberative approach, relied on medical and legal authorities, and emphasized patient autonomy. Situational variables such as the patient's current behavior and the views of health care professionals and family members had higher impacts on decisions than the patient's prior statements or life attitudes. CONCLUSIONS: Both the process and outcome of surrogate decision making depend heavily on whether the surrogate is a relative or not. These findings have implications for the physician-surrogate relationship and legal frameworks regarding surrogacy. Copyright © 2011 John Wiley & Sons, Ltd.

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The Federal Highway Administration (FHWA) approves the selection of the Reconstruction of All or Part of the Interstate (Construction Alternative) as the Preferred Alternative to provide improvements to the interstate system in the Omaha/Council Bluffs metropolitan area, extending across the Missouri River on Interstate 80 to east of the Interstate 480 interchange in Omaha, Nebraska. The study considered long-term, broad-based transportation improvements along Interstate I-29 (I-29), I-80, and I-480, including approximately 18 mainline miles of interstate and 14 interchanges (3 system, 11 service), that would add capacity and correct functional issues along the mainline and interchanges and upgrade the I-80 Missouri River Crossing.

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We study the induced aggregation operators. The analysis begins with a revision of some basic concepts such as the induced ordered weighted averaging (IOWA) operator and the induced ordered weighted geometric (IOWG) operator. We then analyze the problem of decision making with Dempster-Shafer theory of evidence. We suggest the use of induced aggregation operators in decision making with Dempster-Shafer theory. We focus on the aggregation step and examine some of its main properties, including the distinction between descending and ascending orders and different families of induced operators. Finally, we present an illustrative example in which the results obtained using different types of aggregation operators can be seen.

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[spa] Se presenta el operador de media ponderada ordenada generalizada lingüística de 2 tuplas inducida (2-TILGOWA). Es un nuevo operador de agregación que extiende los anteriores modelos a través de utilizar medias generalizadas, variables de ordenación inducidas e información lingüística representada mediante el modelo de las 2 tuplas lingüísticas. Su principal ventaja se encuentra en la posibilidad de incluir a un gran número de operadores de agregación lingüísticos como casos particulares. Por eso, el análisis puede ser visto desde diferentes perspectivas de forma que se obtiene una visión más completa del problema considerado y seleccionar la alternativa que parece estar en mayor concordancia con nuestros intereses o creencias. A continuación se desarrolla una generalización mayor a través de utilizar medias cuasi-aritméticas, obteniéndose el operador Quasi-2-TILOWA. El trabajo finaliza analizando la aplicabilidad del nuevo modelo en un problema de toma de decisiones sobre gestión de la producción.

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[spa] El índice del máximo y el mínimo nivel es una técnica muy útil, especialmente para toma de decisiones, que usa la distancia de Hamming y el coeficiente de adecuación en el mismo problema. En este trabajo, se propone una generalización a través de utilizar medias generalizadas y cuasi aritméticas. A estos operadores de agregación, se les denominará el índice del máximo y el mínimo nivel medio ponderado ordenado generalizado (GOWAIMAM) y cuasi aritmético (Quasi-OWAIMAM). Estos nuevos operadores generalizan una amplia gama de casos particulares como el índice del máximo y el mínimo nivel generalizado (GIMAM), el OWAIMAM, y otros. También se desarrolla una aplicación en la toma de decisiones sobre selección de productos.

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We study the induced aggregation operators. The analysis begins with a revision of some basic concepts such as the induced ordered weighted averaging (IOWA) operator and the induced ordered weighted geometric (IOWG) operator. We then analyze the problem of decision making with Dempster-Shafer theory of evidence. We suggest the use of induced aggregation operators in decision making with Dempster-Shafer theory. We focus on the aggregation step and examine some of its main properties, including the distinction between descending and ascending orders and different families of induced operators. Finally, we present an illustrative example in which the results obtained using different types of aggregation operators can be seen.