Implementação de um modelo de erosão para a simulação de carreiras dos Oficiais da Marinha Portuguesa

Em outubro de 2012, a Direção de Análise e Gestão da Informação (DAGI), em colaboração com a Superintendência do Pessoal (SP) e Direção do Pessoal (DP), iniciou o desenvolvimento de um protótipo de simulador, que designou por “Protótipo Fluxo de Carreiras”. Este simulador permite parametrizar diversos fatores que condicionam o desenvolvimento de carreira dos militares e que estão associados a mecanismos reguladores de carreira que se encontram vertidos no Estatuto dos Militares das Forças Armadas (EMFAR). Para cada ano do período de simulação, a situação de cada militar de uma determinada classe é atualizada e são verificadas as condições para a ocorrência de promoções e passagens à reserva. O evento “passagem à reserva” de um militar pode ter origem em regras determinísticas (exemplo: militar atinge a idade limite de passagem à reserva no seu posto) ou em condições estocásticas ou aleatórias (exemplos: óbito, exclusão da promoção, requerer voluntariamente a passagem à reserva, etc.). Estas últimas situações resultam do fenómeno de erosão dos quadros que pode ser observado a partir do histórico de saídas desta natureza. Até 2015, o simulador de carreiras não comtemplava um modelo de erosão, pelo que os resultados disponibilizados (indicadores de fluxo de carreira) dependiam exclusivamente de mecanismos determinísticos. Desta forma estes resultados apresentam uma natureza “pessimista” e com fraca aderência à realidade. O presente trabalho tem como objetivo construir um modelo descritivo da erosãodos militares oficiais da Marinha, tendo por base dados de saídas (excetuando saídas relacionadas com regras determinísticas previstas no EMFAR) no período de 2008 a2015. Para cada classe da categoria de oficiais é estimada uma função de probabilidadecondicional ao tempo de serviço efetivo ou à idade do militar que representa apropensão para um militar sair do quadro antes de ser verificada uma condição determinística. Estas funções foram integradas no simulador de carreiras para que os resultados possam reproduzir a componente de erosão. Usando o método de simulação de Monte Carlo é possível obter a distribuição dos indicadores de fluxo de carreira. Porfim, objetiva-se realizar uma comparação entre uma simulação com fatores estocásticos (com erosão) e uma simulação considerando apenas fatores determinísticos (semerosão). Este trabalho visa refletir o panorama atual da erosão de pessoal na Marinha, permitindo assim melhorar a qualidade das previsões de efetivos ao longo do tempo bem como aumentar a capacidade de intervenção e resposta na identificação e correção antecipada de possíveis estruturações.

Value at Risk (VaR) en empresas del sector real en Colombia: caso, Bogotá ELEKTRIKA

La estimación y gestión del riesgo con la evolución del mercado ha tomado gran relevancia, principalmente en el sector financiero y de capitales, no obstante las variables macroeconómicas que afectan el riesgo en el tiempo son cada vez más volátiles y generan un mayor nivel de incertidumbre; se puede presentar en igual medida o con un mayor impacto en empresas del sector real, principalmente en aquellas cuyas condiciones de valoración causan un mayor impacto para los inversionistas, tal es el caso de las Asociaciones Público Privadas, mecanismos de contratación que vinculan al sector privado con el público en el desarrollo de proyectos de mayor nivel, donde se requiere establecer la valoración y cuantificación del riesgo que cada una de las partes está dispuesto a asumir -- Hoy por hoy existen métodos de medición sofisticados que permiten la estimación del Value at Risk (VaR), los cuales han sido desarrollados principalmente por el sistema financiero, sin contar con una aplicación en el sector real -- Es por eso que surge la necesidad de esta investigación para obtener una metodología que permita estimar el VaR bajo los conceptos teóricos de economía, estadística y simulación

Reporte financiero Burkenroad / Latinoamérica – Colombia ISAGEN S.A. E.S.P.

Isagen es una empresa que posee cerca del 20% de participación del mercado nacional de generación de energía, las proyecciones del crecimiento de la demanda de energía para los próximos tres años, según UPME, oscilan entre un 2.0% y un 4.8%, por esta razón Isagen ha realizado importantes proyectos de crecimiento y ampliación de su capacidad, como la hidroeléctrica de Sogamoso recientemente, y ahora han iniciado con un proyecto de similares magnitudes como lo es Cañafisto, con la que ampliará su capacidad en 5.740 GW / año, y consideramos que aunque en el corto plazo los flujos de caja estarán ajustados por la alta inversión que este megaproyecto demanda, las condiciones y los fundamentales de Isagen soportan un precio mayor

Avaliação econômica e de risco em sistema de produção de soja na região de Santarém, estado do Pará.

A soja tem contribuição importante no cenário brasileiro. Sua expansão para fronteira amazônica tem chamado atenção, incluindo o Estado do Pará, particularmente pelos fatores de custo de produção, devido à carência de infraestrutura e mercado de insumos. Neste contexto a análise econômica e de risco dos polos produtores de soja no Pará é importante para elaboração de medidas adequadas para sustentabilidade econômica do investimento. A avaliação econômicofinanceira dos sistemas ocorreu com base na Análise de Custo-Benefício (ACB), utilizando como indicador a Receita Líquida obtida. Foi realizada, uma análise de eficiência que considera o fator risco, tendo sido utilizado o método de simulação monte-carlo, por meio do software @-RISK. De acordo com as estatísticas da receita líquida, o sistema produtivo de soja se mostra com muita variabilidade, de acordo com o desvio padrão, máxima e mínima. De acordo com a porcentagem de risco a soja apresentou nível médio a elevado de risco.

Property cash flow studies : focusing on model consistency and data accuracy

The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.

Whole of life cycle cost analysis in bridge rehabilitation

The report presents a methodology for whole of life cycle cost analysis of alternative treatment options for bridge structures, which require rehabilitation. The methodology has been developed after a review of current methods and establishing that a life cycle analysis based on a probabilistic risk approach has many advantages including the essential ability to consider variability of input parameters. The input parameters for the analysis are identified as initial cost, maintenance, monitoring and repair cost, user cost and failure cost. The methodology utilizes the advanced simulation technique of Monte Carlo simulation to combine a number of probability distributions to establish the distribution of whole of life cycle cost. In performing the simulation, the need for a powerful software package, which would work with spreadsheet program, has been identified. After exploring several products on the market, @RISK software has been selected for the simulation. In conclusion, the report presents a typical decision making scenario considering two alternative treatment options.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean

Phase-type distributions represent the time to absorption for a finite state Markov chain in continuous time, generalising the exponential distribution and providing a flexible and useful modelling tool. We present a new reversible jump Markov chain Monte Carlo scheme for performing a fully Bayesian analysis of the popular Coxian subclass of phase-type models; the convenient Coxian representation involves fewer parameters than a more general phase-type model. The key novelty of our approach is that we model covariate dependence in the mean whilst using the Coxian phase-type model as a very general residual distribution. Such incorporation of covariates into the model has not previously been attempted in the Bayesian literature. A further novelty is that we also propose a reversible jump scheme for investigating structural changes to the model brought about by the introduction of Erlang phases. Our approach addresses more questions of inference than previous Bayesian treatments of this model and is automatic in nature. We analyse an example dataset comprising lengths of hospital stays of a sample of patients collected from two Australian hospitals to produce a model for a patient's expected length of stay which incorporates the effects of several covariates. This leads to interesting conclusions about what contributes to length of hospital stay with implications for hospital planning. We compare our results with an alternative classical analysis of these data.

CTCombine : rotating and combining CT data with an accurate detector model, to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc. The geometric and dosimetric accuracy of CTCombine’s output has been assessed by simulating simple and complex treatments applied to a rotated planar phantom and a rotated humanoid phantom and comparing the resulting virtual EPID images with the images acquired using experimental measurements and independent simulations of equivalent phantoms. It is expected that CTCombine will be useful for Monte Carlo studies of EPID dosimetry as well as other EPID imaging applications.

Reliability driven reconfiguration of rural power distribution systems

This paper presents a reliability-based reconfiguration methodology for power distribution systems. Probabilistic reliability models of the system components are considered and Monte Carlo method is used while evaluating the reliability of the distribution system. The reconfiguration is aimed at maximizing the reliability of the power supplied to the customers. A binary particle swarm optimization (BPSO) algorithm is used as a tool to determine the optimal configuration of the sectionalizing and tie switches in the system. The proposed methodology is applied on a modified IEEE 13-bus distribution system.

HABITAT : a longitudinal multilevel study of physical acitvity change in mid-aged adults

Purpose. To explore the role of the neighborhood environment in supporting walking Design. Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting. The Brisbane City Local Government Area, Australia, 2007. Subjects. Brisbane residents aged 40 to 65 years. Measures. Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis. The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results. After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion. The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.