910 resultados para Support Decision System
Consolidation of a wsn and minimax method to rapidly neutralise intruders in strategic installations
Resumo:
Due to the sensitive international situation caused by still-recent terrorist attacks, there is a common need to protect the safety of large spaces such as government buildings, airports and power stations. To address this problem, developments in several research fields, such as video and cognitive audio, decision support systems, human interface, computer architecture, communications networks and communications security, should be integrated with the goal of achieving advanced security systems capable of checking all of the specified requirements and spanning the gap that presently exists in the current market. This paper describes the implementation of a decision system for crisis management in infrastructural building security. Specifically, it describes the implementation of a decision system in the management of building intrusions. The positions of the unidentified persons are reported with the help of a Wireless Sensor Network (WSN). The goal is to achieve an intelligent system capable of making the best decision in real time in order to quickly neutralise one or more intruders who threaten strategic installations. It is assumed that the intruders’ behaviour is inferred through sequences of sensors’ activations and their fusion. This article presents a general approach to selecting the optimum operation from the available neutralisation strategies based on a Minimax algorithm. The distances among different scenario elements will be used to measure the risk of the scene, so a path planning technique will be integrated in order to attain a good performance. Different actions to be executed over the elements of the scene such as moving a guard, blocking a door or turning on an alarm will be used to neutralise the crisis. This set of actions executed to stop the crisis is known as the neutralisation strategy. Finally, the system has been tested in simulations of real situations, and the results have been evaluated according to the final state of the intruders. In 86.5% of the cases, the system achieved the capture of the intruders, and in 59.25% of the cases, they were intercepted before they reached their objective.
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This PhD dissertation is framed in the emergent fields of Reverse Logistics and ClosedLoop Supply Chain (CLSC) management. This subarea of supply chain management has gained researchers and practitioners' attention over the last 15 years to become a fully recognized subdiscipline of the Operations Management field. More specifically, among all the activities that are included within the CLSC area, the focus of this dissertation is centered in direct reuse aspects. The main contribution of this dissertation to current knowledge is twofold. First, a framework for the so-called reuse CLSC is developed. This conceptual model is grounded in a set of six case studies conducted by the author in real industrial settings. The model has also been contrasted with existing literature and with academic and professional experts on the topic as well. The framework encompasses four building blocks. In the first block, a typology for reusable articles is put forward, distinguishing between Returnable Transport Items (RTI), Reusable Packaging Materials (RPM), and Reusable Products (RP). In the second block, the common characteristics that render reuse CLSC difficult to manage from a logistical standpoint are identified, namely: fleet shrinkage, significant investment and limited visibility. In the third block, the main problems arising in the management of reuse CLSC are analyzed, such as: (1) define fleet size dimension, (2) control cycle time and promote articles rotation, (3) control return rate and prevent shrinkage, (4) define purchase policies for new articles, (5) plan and control reconditioning activities, and (6) balance inventory between depots. Finally, in the fourth block some solutions to those issues are developed. Firstly, problems (2) and (3) are addressed through the comparative analysis of alternative strategies for controlling cycle time and return rate. Secondly, a methodology for calculating the required fleet size is elaborated (problem (1)). This methodology is valid for different configurations of the physical flows in the reuse CLSC. Likewise, some directions are pointed out for further development of a similar method for defining purchase policies for new articles (problem (4)). The second main contribution of this dissertation is embedded in the solutions part (block 4) of the conceptual framework and comprises a two-level decision problem integrating two mixed integer linear programming (MILP) models that have been formulated and solved to optimality using AIMMS as modeling language, CPLEX as solver and Excel spreadsheet for data introduction and output presentation. The results obtained are analyzed in order to measure in a client-supplier system the economic impact of two alternative control strategies (recovery policies) in the context of reuse. In addition, the models support decision-making regarding the selection of the appropriate recovery policy against the characteristics of demand pattern and the structure of the relevant costs in the system. The triangulation of methods used in this thesis has enabled to address the same research topic with different approaches and thus, the robustness of the results obtained is strengthened.
Resumo:
No Brasil, a construção bem como as mudanças nos mais de vinte anos do Sistema Único de Saúde (SUS) tem demandado um crescente interesse em estratégias que valorizem o uso da informação em saúde. Cada vez mais as incertezas entre a complexidade deste sistema e as intervenções necessárias para atender os seus preceitos e as necessidades da população precisam de respostas ágeis e efetivas. A efetividade dos serviços e a equidade em sua prestação são cruciais na atenção à saúde e mostram-se como desafio frente à dificuldade de avaliação dos resultados das ações pela demora no impacto nos indicadores epidemiológicos clássicos. O monitoramento é uma prática que pode ser destacada pela agilidade nas respostas, porém é nítido o quanto a discussão sobre o assunto é pouco estabelecida na literatura disponível. Se apresenta como uma prática interativa e proativa que utiliza informações disponíveis com o potencial de organizar e divulgar rapidamente as descobertas feitas, gerar um aprendizado organizacional e apoiar o processo decisório. A proposta deste estudo considerou o Painel de Monitoramento da Secretaria Municipal da Saúde de São Paulo como ponto de partida para pesquisar sobre as potencialidades do monitoramento na gestão. Uma pesquisa de métodos mistos foi a opção metodológica para este trabalho que buscou aprofundar o marco referencial teórico sobre monitoramento, descrever e analisar criticamente as referências técnicas utilizadas para a construção da proposta e realizar um estudo de caso único em território descentralizado do município de São Paulo sobre a rotina local na sua utilização e com isso analisar as potencialidades e os alcances desta experiência na gestão municipal. Concluiu-se que o monitoramento por meio de indicadores selecionados a partir de dados secundários é uma estratégia oportuna de acompanhar a tendência de determinadas ações possibilitando assim a emissão de juízo de valor e tomada de decisão com rapidez. O aplicativo propicia aos gestores e técnicos informações relevantes que apoiam o processo decisório, além de possibilitar a sua utilização em diferentes contextos da gestão e portes territoriais. Por outro lado, a prática cotidiana é pautada por prioridades normativas, onde a precisão do registro, a coerência das fontes e a quantidade apontada sobrepõem-se à informação em si, o seu significado e as ações necessárias para o enfrentamento dos problemas. O uso da informação é cultura em construção e o Painel de Monitoramento traz a possibilidade de organizar, qualificar e difundir dados secundários dos diferentes sistemas de informação do Sistema Único de Saúde (SUS). Além disso, tem contribuído também no papel de fomentar as discussões sobre os diferentes temas que envolvem as prioridades de uma gestão em todos os níveis do sistema de saúde do município de São Paulo.
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This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.
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There are limitations in recent research undertaken on attribute reduction in incomplete decision systems. In this paper, we propose a distance-based method for attribute reduction in an incomplete decision system. In addition, we prove theoretically that our method is more effective than some other methods.
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A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table. In this paper, we propose methods for attribute reduction in static incomplete decision systems and dynamic incomplete decision systems with dynamically-increasing and decreasing conditional attributes. Our methods use generalized discernibility matrix and function in tolerance-based rough sets.
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From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.
Resumo:
Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.
Resumo:
The processing of spatial and mnemonic information is believed to depend on hippocampal theta oscillations (5–12 Hz). However, in rats both the power and the frequency of the theta rhythm are modulated by locomotor activity, which is a major confounding factor when estimating its cognitive correlates. Previous studies have suggested that hippocampal theta oscillations support decision-making processes. In this study, we investigated to what extent spatial decision making modulates hippocampal theta oscillations when controlling for variations in locomotion speed. We recorded local field potentials from the CA1 region of rats while animals had to choose one arm to enter for reward (goal) in a four-arm radial maze. We observed prominent theta oscillations during the decision-making period of the task, which occurred in the center of the maze before animals deliberately ran through an arm toward goal location. In speed-controlled analyses, theta power and frequency were higher during the decision period when compared to either an intertrial delay period (also at the maze center), or to the period of running toward goal location. In addition, theta activity was higher during decision periods preceding correct choices than during decision periods preceding incorrect choices. Altogether, our data support a cognitive function for the hippocampal theta rhythm in spatial decision making
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Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging because of reinforcing feedbacks between multiple drivers. We conducted semistructured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. The “Hands-off” scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production under drought conditions. The “Fire management” scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared with the “Fire suppression” scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a “boundary object” to facilitate collaboration and integration of different perceptions of fire in the region. This approach also has the potential to inform decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.
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Universities are institutions that generate and manipulate large amounts of data as a result of the multiple functions they perform, of the amount of involved professionals and students they attend. Information gathered from these data is used, for example, for operational activities and to support decision-making by managers. To assist managers in accomplishing their tasks, the Information Systems (IS) are presented as tools that offer features aiming to improve the performance of its users, assist with routine tasks and provide support to decision-making. The purpose of this research is to evaluate the influence of the users features and of the task in the success of IS. The study is of a descriptive-exploratory nature, therefore, the constructs used to define the conceptual model of the research are known and previously validated. However, individual features of users and of the task are IS success antecedents. In order to test the influence of these antecedents, it was developed a decision support IS that uses the Multicriteria Decision Aid Constructivist (MCDA-C) methodology with the participation and involvement of users. The sample consisted of managers and former managers of UTFPR Campus Pato Branco who work or have worked in teaching activities, research, extension and management. For data collection an experiment was conducted in the computer lab of the Campus Pato Branco in order to verify the hypotheses of the research. The experiment consisted of performing a distribution task of teaching positions between the academic departments using the IS developed. The task involved decision-making related to management activities. The data that fed the system used were real, from the Campus itself. A questionnaire was answered by the participants of the experiment in order to obtain data to verify the research hypotheses. The results obtained from the data analysis partially confirmed the influence of the individual features in IS success and fully confirmed the influence of task features. The data collected failed to support significant ratio between the individual features and the individual impact. For many of the participants the first contact with the IS was during the experiment, which indicates the lack of experience with the system. Regarding the success of IS, the data revealed that there is no significance in the relationship between Information Quality (IQ) and Individual Impact (II). It is noteworthy that the IS used in the experiment is to support decision-making and the information provided by this system are strictly quantitative, which may have caused some conflict in the analysis of the criteria involved in the decision-making process. This is because the criteria of teaching, research, extension and management are interconnected such that one reflects on another. Thus, the opinion of the managers does not depend exclusively on quantitative data, but also of knowledge and value judgment that each manager has about the problem to be solved.
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The Multicriteria decision analysis is a tool to support decision-making in the identification of areas with the utmost beekeeping potential. This paper design a GIS multicriteria approach to assess the beekeeping potential. The development of a conceptual model structure requires the participation of stakeholders and experts in that process. The spatial Multicriteria Decision Analysis (MCDA) allowed defining the potential beekeeping map. The resulting maps can be used by the beekeepers associations to easily select the more suitable areas for the apiaries location or relocation and avoid prohibited areas by legal requirements.
Resumo:
The processing of spatial and mnemonic information is believed to depend on hippocampal theta oscillations (5–12 Hz). However, in rats both the power and the frequency of the theta rhythm are modulated by locomotor activity, which is a major confounding factor when estimating its cognitive correlates. Previous studies have suggested that hippocampal theta oscillations support decision-making processes. In this study, we investigated to what extent spatial decision making modulates hippocampal theta oscillations when controlling for variations in locomotion speed. We recorded local field potentials from the CA1 region of rats while animals had to choose one arm to enter for reward (goal) in a four-arm radial maze. We observed prominent theta oscillations during the decision-making period of the task, which occurred in the center of the maze before animals deliberately ran through an arm toward goal location. In speed-controlled analyses, theta power and frequency were higher during the decision period when compared to either an intertrial delay period (also at the maze center), or to the period of running toward goal location. In addition, theta activity was higher during decision periods preceding correct choices than during decision periods preceding incorrect choices. Altogether, our data support a cognitive function for the hippocampal theta rhythm in spatial decision making
Resumo:
O Empreendimento de Fins Múltiplos de Alqueva (EFMA) é um projecto estruturante centrado na barragem do Alqueva, que pretende garantir o recurso Água na região e com isso viabilizar uma série de infra-estruturas que contribuirão para o desenvolvimento, em termos económicos e sociais, de uma das regiões mais desfavorecidas da Europa. O EFMA é constituído pelo "Reservatório Mãe" e por um conjunto de outras albufeiras de menor dimensão, interligados por uma rede com cerca de dois mil quilómetros de canais e condutas e mais de meia centena de estações de bombagem, contemplando os seguintes usos da água: - Abastecimento público. - Fornecimento de água para o desenvolvimento de actividades agrícolas e agro-industriais; - Produção de energia; Este trabalho tem por objectivo avaliar a adequabilidade da qualidade da água para o uso rega na origem e produzir informação adequada de suporte à decisão. Os resultados obtidos permitem afirmar que de um modo geral a qualidade da água captada no sistema Alqueva- Pedrógão é adequada para o uso rega, apesar de se verificar uma persistente contaminação de coliformes fecais. ABSTRACT; The Multipurpose Alqueva Project (EFMA- Empreendimento de Fins Múltiplos de Alqueva) is a groundwork project centred in Alqueva dam and its reservoir, which intends to guarantee a strategic water reserve in the region, and therefore making possible a series of associated infrastructures, contributing for the potential development of the region, in economic and social terms, in one of the most poorest regions of Europe. The EFMA includes a "Main Reservoir" and set of other dams with lesser dimension, connected by a several canals and pipelines about two thousand kilometers long (including Primary and Secondary Network), and about 50 pumping stations, with the goal of attaining the following main objectives: - Water supply for the development of agricultural and agro-industrial activities; - Production of energy; - Public Water Supply. This study intends to evaluate the suitability of water quality in the origin for irrigation use and to achieve adequate information for support decision. The results have revealed that the quality of water abstracted in the Alqueva - Pedrógão System is suitable for irrigation, although the persistent contamination of fecal coliforms.
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Animal welfare issues have received much attention not only to supply farmed animal requirements, but also to ethical and cultural public concerns. Daily collected information, as well as the systematic follow-up of production stages, produces important statistical data for production assessment and control, as well as for improvement possibilities. In this scenario, this research study analyzed behavioral, production, and environmental data using Main Component Multivariable Analysis, which correlated observed behaviors, recorded using video cameras and electronic identification, with performance parameters of female broiler breeders. The aim was to start building a system to support decision-making in broiler breeder housing, based on bird behavioral parameters. Birds were housed in an environmental chamber, with three pens with different controlled environments. Bird sensitivity to environmental conditions were indicated by their behaviors, stressing the importance of behavioral observations for modern poultry management. A strong association between performance parameters and the behavior at the nest, suggesting that this behavior may be used to predict productivity. The behaviors of ruffling feathers, opening wings, preening, and at the drinker were negatively correlated with environmental temperature, suggesting that the increase of in the frequency of these behaviors indicate improvement of thermal welfare.