942 resultados para Markov decision processes


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In Smart Grids, a variety of new applications are available to users of the electrical system (from consumers to the electric system operators and market operators). Some applications such as the SCADA systems, which control generators or substations, have consequences, for example, with a communication delay. The result of a failure to deliver a control message due to noncompliance of the time constraint can be catastrophic. On the other hand, applications such as smart metering of consumption have fewer restrictions. Since each type of application has different quality of service requirements (importance, delay, and amount of data to transmit) to transmit its messages, the policy to control and share the resources of the data communication network must consider them. In this paper Markov Decision Process Theory is employed to determine optimal policies to explore as much as possible the availability of throughput in order to transmit all kinds of messages, considering the quality of service requirements defined to each kind of message. First a non-preemptive model is formulated and after that a preemptive model is derived. Numerical results are used to compare FIFO, non-preemptive and preemptive policies.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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A tarefa de projetar um sistema de educação a distância (SEAD) é um processo complexo devido ao número de componentes envolvidos, às diferentes visões e abordagens quanto à sua eficácia, aos valores em disputa, aos interesses em jogo e às decisões urgentes. Este trabalho, partindo da experiência constante de livros e artigos dos autores, faz um recorte na tese de doutoramento de um deles a fim de descrever a importância da análise de incertezas em programas de educação a distância, o que se acredita levar à redução da probabilidade de ocorrência de eventos indesejáveis e/ou inesperados em várias situações caracterizadas por ambientes complexos. Descreve-se a trajetória da incerteza na perspectiva da ciência e apresenta-se um referencial teórico para dar suporte à temática do planejamento de SEADs. São citadas, também, as formas como as incertezas podem incidir nos processos decisórios e de implantação de SEADs, tomando por base uma pesquisa realizada no estado do Pará. Estratégias foram especificadas na perspectiva de melhorar a articulação entre as iniciativas das diversas áreas, de modo a potencializar a participação dos diferentes atores e reforçar o papel da educação a distância como política pública para a inclusão social. Nas considerações finais, reforça-se a adaptabilidade da investigação para outras situações. O trabalho pretende ser uma contribuição na indicação de diretrizes estratégicas para subsidiar a implantação de SEADs.

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The demand for "welfare friendly" products increases as public conscience and perception on livestock production systems grow. The public and policy-makers demand scientific information for education and to guide decision processes. This paper describes some of the last decade contributions made by scientists on the technical, economical and market areas of farm animal welfare. Articles on animal welfare were compiled on the following themes: 1) consumer behavior, 2) technical and economical viability, 3) public regulation, and 4) private certification policies. Most studies on the economic evaluation of systems that promote animal welfare involved species destined to produce export items, such as eggs, beef and pork. Few studies were found on broilers, dairy cows and fish, and data regarding other species, such as horses, sheep and goats were not found. Scientists understand that farm animal welfare is not only a matter of ethics, but also an essential tool to gain and maintain markets. However, it is unfortunate that little attention is paid to species that are not economically important for exports. Studies that emphasize on more humane ways to raise animals and that provide economic incentives to the producer are needed. An integrated multidisciplinary approach is necessary to highlight the benefits of introducing animal welfare techniques to existing production systems.

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Background Cost-effectiveness studies have been increasingly part of decision processes for incorporating new vaccines into the Brazilian National Immunisation Program. This study aimed to evaluate the cost-effectiveness of 10-valent pneumococcal conjugate vaccine (PCV10) in the universal childhood immunisation programme in Brazil. Methods A decision-tree analytical model based on the ProVac Initiative pneumococcus model was used, following 25 successive cohorts from birth until 5 years of age. Two strategies were compared: (1) status quo and (2) universal childhood immunisation programme with PCV10. Epidemiological and cost estimates for pneumococcal disease were based on National Health Information Systems and literature. A 'top-down' costing approach was employed. Costs are reported in 2004 Brazilian reals. Costs and benefits were discounted at 3%. Results 25 years after implementing the PCV10 immunisation programme, 10 226 deaths, 360 657 disability-adjusted life years (DALYs), 433 808 hospitalisations and 5 117 109 outpatient visits would be avoided. The cost of the immunisation programme would be R$10 674 478 765, and the expected savings on direct medical costs and family costs would be R$1 036 958 639 and R$209 919 404, respectively. This resulted in an incremental cost-effectiveness ratio of R$778 145/death avoided and R$22 066/DALY avoided from the society perspective. Conclusion The PCV10 universal infant immunisation programme is a cost-effective intervention (1-3 GDP per capita/DALY avoided). Owing to the uncertain burden of disease data, as well as unclear long-term vaccine effects, surveillance systems to monitor the long-term effects of this programme will be essential.

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This research has been triggered by an emergent trend in customer behavior: customers have rapidly expanded their channel experiences and preferences beyond traditional channels (such as stores) and they expect the company with which they do business to have a presence on all these channels. This evidence has produced an increasing interest in multichannel customer behavior and it has motivated several researchers to study the customers’ channel choices dynamics in multichannel environment. We study how the consumer decision process for channel choice and response to marketing communications evolves for a cohort of new customers. We assume a newly acquired customer’s decisions are described by a “trial” model, but the customer’s choice process evolves to a “post-trial” model as the customer learns his or her preferences and becomes familiar with the firm’s marketing efforts. The trial and post-trial decision processes are each described by different multinomial logit choice models, and the evolution from the trial to post-trial model is determined by a customer-level geometric distribution that captures the time it takes for the customer to make the transition. We utilize data for a major retailer who sells in three channels – retail store, the Internet, and via catalog. The model is estimated using Bayesian methods that allow for cross-customer heterogeneity. This allows us to have distinct parameters estimates for a trial and an after trial stages and to estimate the quickness of this transit at the individual level. The results show for example that the customer decision process indeed does evolve over time. Customers differ in the duration of the trial period and marketing has a different impact on channel choice in the trial and post-trial stages. Furthermore, we show that some people switch channel decision processes while others don’t and we found that several factors have an impact on the probability to switch decision process. Insights from this study can help managers tailor their marketing communication strategy as customers gain channel choice experience. Managers may also have insights on the timing of the direct marketing communications. They can predict the duration of the trial phase at individual level detecting the customers with a quick, long or even absent trial phase. They can even predict if the customer will change or not his decision process over time, and they can influence the switching process using specific marketing tools

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VHB-JOURQUAL represents the official journal ranking of the German Academic Association for Business Research. Since its introduction in 2003, the ranking has become the most influential journal evaluation approach in German-speaking countries, impacting several key managerial decisions of German, Austrian, and Swiss business schools. This article reports the methodological approach of the ranking’s second edition. It also presents the main results and additional analyses on the validity of the rating and the underlying decision processes of the respondents. Selected implications for researchers and higher-education institutions are discussed.

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Although prior research on new venture creation has identified several antecedents that differentiate entrepreneurs from non-entrepreneurs, scholars still have an incomplete understanding of the factors and decision processes that lead an individual to become an entrepreneur. By applying prospect theory, we introduce the reference point as an important antecedent of new venture creation. Testing our research model and hypotheses with entrepreneurs and employees, results show that entrepreneurs set more aspiring reference points and therefore find themselves more often in a perceived loss situation. Results are also robust when testing for entrepreneurial intention of business graduate students. According to prospect theory, the perceived loss triggers more risk-seeking behavior. Summing up, the reference point has a positive effect on new venture creation and differentiates entrepreneurs from nonentrepreneurs. We discuss theoretical and managerial implications of the findings and develop avenues for future research.

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Introduction: Alcohol-dependency is a common disease with many negative consequences in the daily life. A typical symptom of alcoholic-patients is the persistent and uncontrollable desire to consume alcohol. Inspite of different treatments, alcohol-dependency has a relapse rate of about 85%. This high rate is facilitated by a dysfunction of cognitive control-processes. In order to understand this disease sustaining factor, the present study investigated the neurophysiological correlates of inhibition of alcoholic-patients in a neutral as well as an alcohol-related context. Methods: A total of 18 participants, (9 alcohol-dependent-patients (age range: 27-62 years), 9 healthy controls (age range: 29-60 years)) have been measured with functional magnetic resonance imaging while they participated in an alcohol-specific Go/NoGo-Task. Neurophysiological correlates of inhibition in an alcohol-related as well as a neutral context were compared in both groups. Results: When comparing correct stop-trials in alcohol-related to neutral context, only alcohol-dependent patients showed significant hyperactivation in frontal regions (superior and medial gyrus frontalis, anterior gyrus cinguli, gyrus paracentralis and the gyrus praecentralis). No significant differences were found in any of the behavioral analyses. Discussion: These preliminary results thus indicate that successful inhibition in a drug-related context demands additional resources in patients. Especially the hyperactivation of the anterior gyrus cinguli might be important because of its involvement in decision-processes. In the absent of deficits in behavioral data, this suggests that alcohol-dependent patients need more neuronal activity to achieve the same performance-level like healthy controls.

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The present study investigated how ease of imagery influences source monitoring accuracy. Two experiments were conducted in order to examine how ease of imagery influences the probability of source confusions of perceived and imagined completions of natural symmetric shapes. The stimuli consisted of binary pictures of natural objects, namely symmetric pictures of birds, butterflies, insects, and leaves. The ease of imagery (indicating the similarity of the sources) and the discriminability (indicating the similarity of the items) of each stimulus were estimated in a pretest and included as predictors of the memory performance for these stimuli. It was found that confusion of the sources becomes more likely when the imagery process was relatively easy. However, if the different processes of source monitoring-item memory, source memory and guessing biases-are disentangled, both experiments support the assumption that the effect of decreased source memory for easily imagined stimuli is due to decision processes and misinformation at retrieval rather than encoding processes and memory retention. The data were modeled with a Bayesian hierarchical implementation of the one high threshold source monitoring model.

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This paper outlines an automatic computervision system for the identification of avena sterilis which is a special weed seed growing in cereal crops. The final goal is to reduce the quantity of herbicide to be sprayed as an important and necessary step for precision agriculture. So, only areas where the presence of weeds is important should be sprayed. The main problems for the identification of this kind of weed are its similar spectral signature with respect the crops and also its irregular distribution in the field. It has been designed a new strategy involving two processes: image segmentation and decision making. The image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and weeds. The decision making is based on the SupportVectorMachines and determines if a cell must be sprayed. The main findings of this paper are reflected in the combination of the segmentation and the SupportVectorMachines decision processes. Another important contribution of this approach is the minimum requirements of the system in terms of memory and computation power if compared with other previous works. The performance of the method is illustrated by comparative analysis against some existing strategies.

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This paper describes the architecture of a computer system conceived as an intelligent assistant for public transport management. The goal of the system is to help operators of a control center in making strategic decisions about how to solve problems of a fleet of buses in an urban network. The system uses artificial intelligence techniques to simulate the decision processes. In particular, a complex knowledge model has been designed by using advanced knowledge engineering methods that integrates three main tasks: diagnosis, prediction and planning. Finally, the paper describes two particular applications developed following this architecture for the cities of Torino (Italy) and Vitoria (Spain).

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This paper contributes with a unified formulation that merges previ- ous analysis on the prediction of the performance ( value function ) of certain sequence of actions ( policy ) when an agent operates a Markov decision process with large state-space. When the states are represented by features and the value function is linearly approxi- mated, our analysis reveals a new relationship between two common cost functions used to obtain the optimal approximation. In addition, this analysis allows us to propose an efficient adaptive algorithm that provides an unbiased linear estimate. The performance of the pro- posed algorithm is illustrated by simulation, showing competitive results when compared with the state-of-the-art solutions.

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The SESAR (Single European Sky ATM Research) program is an ambitious re-search and development initiative to design the future European air traffic man-agement (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three stud-ies related to the design of future ATM systems in Europe.