SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant, Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). (C) 2003 Published by Elsevier Science B.V.

O plano plurianual municipal no sistema de planejamento e or??amento brasileiro

A partir da perspectiva do New Public Financial Management, o artigo traz os aspectos t??cnicos e pol??ticos que permearam o desenvolvimento do sistema de planejamento e or??amento brasileiro. Considerando os condicionantes dos momentos hist??ricos que interferiram em seu desenvolvimento, s??o identificadas caracter??sticas pol??ticas, t??cnicas e metodol??gicas incidentes no controle financeiro, nas melhorias administrativas, no planejamento e, finalmente, na tend??ncia participativa decorrente da amplia????o de espa??os democr??ticos. Em seguida, s??o apresentados o tratamento constitucional dado ao Plano Plurianual e o aperfei??oamento do sistema de planejamento e or??amento trazido pela Lei de Responsabilidade Fiscal. S??o destacadas, para o caso municipal, as inova????es contidas no Estatuto da Cidade, com reflexos no Plano Plurianual Municipal. Ressalta-se a import??ncia do processo de planejamento e or??amento na execu????o das pol??ticas p??blicas, enfatizando as dificuldades ainda existentes quanto ?? regula????o do sistema de planejamento e or??amento para permitir o imbricamento dessas pol??ticas entre as tr??s esferas federativas.

Desenvolvimento e avaliação da acurácia do sistema de filtração (BacFil 6.0) na detecção de bacilos álcool-ácido resistentes em amostras de lavado broncoalveolar de pacientes com suspeita de tuberculose

A baciloscopia é o principal método diagnóstico da tuberculose (TB) em razão do seu baixo custo, rapidez e facilidade de execução. Porém sua sensibilidade é baixa, principalmente nas formas paucibacilares da doença. Nesse sentido, novas metodologias que resultem no aumento da sensibilidade da baciloscopia tornam-se absolutamente necessárias. Neste estudo, nos propusemos a aprimorar e padronizar o sistema de filtração BacFil e avaliar sua performance e acurácia em amostras paucibacilares (lavado broncoalveolar). Para alcançar esses objetivos desenvolvemos o estudo em duas fases. Na primeira fase, foram realizados ensaios para definir: 1) utilização de membranas brancas para visualização de BAAR corados por Auramina-O; 2) aumento do volume de NALC, utilização de pérolas de vidro no processo de digestão das amostras e mudança no sistema do suporte do pré-filtro; 3) meios de fixação da membrana de filtração na lâmina de microscopia; 4) limite de detecção da técnica; 5) aumento do volume de NaOCl e a influência desse aumento na visualização de BAAR na membrana. Verificou-se que: a membrana de policarbonato branca tem a mesma eficiência da membrana de policarbonato preta na visualização de BAAR fluorescentes; o método modificado utilizando maior concentração de NALC, pérolas de vidro e sistema de pré-filtro baseado em orifícios obteve 98% de passagem das amostras pelo sistema; a melhor forma de fixação da membrana na lâmina foi obtida por intermédio da utilização de fita dupla face; o limite de detecção da técnica de filtração utilizando o sistema BacFil versão 6.0 foi de 2 a 9 BAAR por mililitro de suspensão bacteriana com D.O de 0,250 ± 0,01 a 625nm; o aumento da concentração de NaOCl para 10% ajuda na passagem de um maior volume de amostra pelo sistema, porém ocasiona a diminuição da quantidade BAAR na membrana de filtração após o período necessário para todo o processo. Na segunda fase foi avaliado acurácia da técnica padronizada em 101 amostras de lavado broncoalveolar (LBA) de pacientes com suspeita de TB provenientes do Hospital Universitário Cassiano Antônio de Moraes. Observou-se que a sensibilidade da técnica de filtração (BacFil versão 6.0) foi de 76% e especificidade de 95%. A sensibilidade obtida foi significativamente maior do que a observada na baciloscopia após centrifugação que foi de 59% (p = 0,001). No entanto, constatou-se uma diminuição de especificidade na técnica de filtração (95%) em relação a técnica de 8 centrifugação (99%). Concluímos que as modificações realizadas nos sistema de filtração permitiu sanar os problemas técnicos apresentados nas versões anteriores e aumentar a sensibilidade da baciloscopia de amostras paucibacilares (lavado broncoalveolar) para o diagnóstico da TB pulmonar.

Sistema de gestão e controlo da atribuição de endereçamento de rede

Com a evolução tecnológica, a informática assumiu um papel fulcral na nossa vida actual tanto numa vertente doméstica como para as mais variadíssimas organizações. As redes IP estão disseminadas por todo o lado, escritórios, habitações, estabelecimentos de ensino, espaços comerciais, com as mais diversas topologias e dimensões, que como qualquer recurso devem ser bem geridas. O presente projecto insere-se neste contexto, pretendendo criar um sistema para dar apoio no controlo e gestão de endereçamento IP dados por um servidor DHCP. A problemática central que este projecto pretende tratar é a detecção da configuração forçada de endereços IP por parte dos utilizadores, notificando tais situações aos administradores de rede. O sistema é constituído por vários componentes como Linux, MySQL, ISC DHCP, SNMP, PHP, APACHE e irá interagir com equipamentos de rede que possuam tabelas de endereços para que a informação, nestas encontradas, seja comparada com a informação dos endereços fornecidos pelo servidor DHCP. O sistema dá suporte a uma página web que pretende auxiliar algumas configurações e fornecer informações estatísticas sobre a rede.

Sistema de apoio à criminologia

Este trabalho consiste no desenvolvimento de um Sistema de Apoio à Criminologia – SAC, onde se pretende ajudar os detectives/analistas na prevenção proactiva da criminalidade e na gestão dos seus recursos materiais e humanos, bem como impulsionar estudos sobre a alta incidência de determinados tipos de crime numa dada região. Historicamente, a resolução de crimes tem sido uma prerrogativa da justiça penal e dos seus especialistas e, com o aumento da utilização de sistemas computacionais no sistema judicial para registar todos os dados que dizem respeito a ocorrências de crimes, dados de suspeitos e vítimas, registo criminal de indivíduos e outros dados que fluem dentro da organização, cresce a necessidade de transformar estes dados em informação proveitosa no combate à criminalidade. O SAC tira partido de técnicas de extracção de conhecimento de informação e aplica-as a um conjunto de dados de ocorrências de crimes numa dada região e espaço temporal, bem como a um conjunto de variáveis que influenciam a criminalidade, as quais foram estudadas e identificadas neste trabalho. Este trabalho é constituído por um modelo de extracção de conhecimento de informação e por uma aplicação que permite ao utilizador fornecer um conjunto de dados adequado, garantindo a máxima eficácia do modelo.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

VPPs information needs for effective operation in competitive electricity markets

The large increase of renewable energy sources and Distributed Generation (DG) of electricity gives place to the Virtual Power Producer (VPP) concept. VPPs may turn electricity generation by renewable sources valuable in electricity markets. Information availability and adequate decision-support tools are crucial for achieving VPPs’ goals. This involves information concerning associated producers and market operation. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, focusing mainly in the information requirements for adequate decision making.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Balancing market integration in MASCEM electricity market simulator

With the restructuring of the energy sector in industrialized countries there is an increased complexity in market players’ interactions along with emerging problems and new issues to be addressed. Decision support tools that facilitate the study and understanding of these markets are extremely useful to provide players with competitive advantage. In this context arises MASCEM, a multi-agent simulator for competitive electricity markets. It is essential to reinforce MASCEM with the ability to recreate electricity markets reality in the fullest possible extent, making it able to simulate as many types of markets models and players as possible. This paper presents the development of the Balancing Market in MASCEM. A key module to the study of competitive electricity markets, as it has well defined and distinct characteristics previously implemented.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.

Tourism mobile and recommendation systems - a state of the art

Recommendation systems have been growing in number for the last fifteen years. To evolve and adapt to the demands of the actual society, many paradigms emerged giving birth to even more paradigms and hybrid approaches. Mobile devices have also been under an incredible growth rate in every business area, and there are already lots of mobile based systems to assist tourists. This explosive growth gave birth to different mobile applications, each having their own advantages and disadvantages. Since recommendation and mobile systems might as well be integrated, this work intends to present the current state of the art in tourism mobile and recommendation systems, as well as to state their advantages and disadvantages.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.