978 resultados para stochastic Hamiltonian problems
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Many interconnected problems involved for the conservation of freshwater fish genetic resources of India are enumerated. Some possible solutions to the problems are also discussed.
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In multisource industrial scenarios (MSIS) coexist NOAA generating activities with other productive sources of airborne particles, such as parallel processes of manufacturing or electrical and diesel machinery. A distinctive characteristic of MSIS is the spatially complex distribution of aerosol sources, as well as their potential differences in dynamics, due to the feasibility of multi-task configuration at a given time. Thus, the background signal is expected to challenge the aerosol analyzers at a probably wide range of concentrations and size distributions, depending of the multisource configuration at a given time. Monitoring and prediction by using statistical analysis of time series captured by on-line particle analyzers in industrial scenarios, have been proven to be feasible in predicting PNC evolution provided a given quality of net signals (difference between signal at source and background). However the analysis and modelling of non-consistent time series, influenced by low levels of SNR (Signal-Noise Ratio) could build a misleading basis for decision making. In this context, this work explores the use of stochastic models based on ARIMA methodology to monitor and predict exposure values (PNC). The study was carried out in a MSIS where an case study focused on the manufacture of perforated tablets of nano-TiO2 by cold pressing was performed
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210 p.
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This paper details some of the problems encountered in culturing black tiger shrimp (Penaeus monodon) the semi-intensive way in India, which include aquatic macrophytes; invasions by molluscs, jellyfish and frogs; predators; fouling organisms; and others.
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Esta tese apresenta um estudo sobre modelagem computacional onde são aplicadas meta-heurísticas de otimização na solução de problemas inversos de transferência radiativa em meios unidimensionais com albedo dependente da variável óptica, e meios unidimensionais de duas camadas onde o problema inverso é tratado como um problema de otimização. O trabalho aplica uma meta-heurística baseada em comportamentos da natureza conhecida como algoritmo dos vagalumes. Inicialmente, foram feitos estudos comparativos de desempenho com dois outros algoritmos estocásticos clássicos. Os resultados encontrados indicaram que a escolha do algoritmo dos vagalumes era apropriada. Em seguida, foram propostas outras estratégias que foram inseridas no algoritmo dos vagalumes canônico. Foi proposto um caso onde se testou e investigou todas as potenciais estratégias. As que apresentaram os melhores resultados foram, então, testadas em mais dois casos distintos. Todos os três casos testados foram em um ambiente de uma camada, com albedo de espalhamento dependente da posição espacial. As estratégias que apresentaram os resultados mais competitivos foram testadas em um meio de duas camadas. Para este novo cenário foram propostos cinco novos casos de testes. Os resultados obtidos, pelas novas variantes do algoritmo dos vagalumes, foram criticamente analisados.
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Over a century of fi shery and oceanographic research conducted along the Atlantic coast of the United States has resulted in many publications using unofficial, and therefore unclear, geographic names for certain study areas. Such improper usage, besides being unscholarly, has and can lead to identification problems for readers unfamiliar with the area. Even worse, the use of electronic data bases and search engines can provide incomplete or confusing references when improper wording is used. The two terms used improperly most often are “Middle Atlantic Bight” and “South Atlantic Bight.” In general, the term “Middle Atlantic Bight” usually refers to an imprecise coastal area off the middle Atlantic states of New York, New Jersey, Delaware, Maryland, and Virginia, and the term “South Atlantic Bight” refers to the area off the southeastern states of North Carolina, South Carolina, Georgia, and Florida’s east coast.