Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Leilões eletrônicos reversos multiatributo : uma abordagem de decisão multicritério como instrumento de agregação de valor aos processos de compras do setor público brasileiro

Leilões são instituições seculares utilizadas nas relações comerciais entre indivíduos e organizações. Provêem maior flexibilidade aos processos de determinação de preços e alocação de bens, aumentando o espaço para negociações entre compradores e vendedores. Na Internet, têm sido empregados, de maneira crescente, em atividades de comércio eletrônico B2B e G2B, em sua maioria, através da modalidade de leilão reverso. No entanto, seu aspecto unidimensional reduz as negociações à variável preço, produzindo, muitas vezes, resultados aquém do desejado. No caso brasileiro, o Governo Federal instituiu o Portal Comprasnet, através do qual, as organizações públicas adquirem bens e serviços de fornecedores cadastrados. Dentre as modalidades de licitação disponíveis, destaca-se o Pregão Eletrônico, um mecanismo de leilão eletrônico reverso baseado no atributo preço, através do qual, fornecedores submetem lances decrescentes, na disputa por contratos do setor público. No presente trabalho, o autor propõe uma abordagem de decisão multicritério, baseada na Teoria da Utilidade Multiatributo, como uma alternativa para a adoção de leilões reversos baseados em múltiplos atributos e, consequentemente, para uma maior agregação de valor pelas organizações compradoras do setor público brasileiro.

Gestão do conhecimento e criação de valor: um estudo exploratório em empresas brasileiras

Nos últimos dez anos a gestão do conhecimento tem crescido em importância tanto no meio acadêmico como empresarial. Ainda que alguns permaneçam céticos, sua relevância para a competitividade das organizações tem se tornado cada vez mais um ponto de concordância nos dois ambientes, como uma resposta aos desafios sociais e econômicos impostos. Estes desafios impulsionam a gestão do conhecimento vista como uma disciplina interdisciplinar focada nos agentes e no seu ambiente, e no processo de criação, mapeamento e transferência do conhecimento, com o objetivo final de gerar vantagens competitivas sustentáveis. Apesar de muitos estudos específicos, ainda são poucos os trabalhos que buscam avaliar a adoção da gestão do conhecimento como abordagem ampla, quase como um novo paradigma gerencial adaptado à nova realidade econômica vigente, assim como são poucos os estudos que buscam avaliar o impacto na criação de valor de estratégias focadas no conhecimento. Este trabalho visa preencher essa lacuna, avaliando a adoção de práticas, conceitos e atitudes vinculadas à gestão do conhecimento em empresas de grande e pequeno porte criadoras de valor, através de estudos de caso. Para isso, o trabalho partiu de uma ampla revisão da literatura em torno do tema para definir um conjunto de práticas associadas ao conceito de gestão do conhecimento, dividido em seis dimensões: estratégia, estrutura, tecnologia da informação, cultura e pessoas, sistemas de suporte e processos. A partir deste levantamento, instrumentos distintos – questionário e roteiro de entrevista - foram elaborados para estudar as grandes e pequenas empresas. A pesquisa de campo só foi realizada após a validação do instrumento por especialistas na área, que avaliaram cada item com relação a sua total, parcial ou marginal associação ao conceito de gestão do conhecimento. Os resultados mostram que, independente do tamanho, as empresas criadoras de valor adotam muitas das práticas associadas a gestão do conhecimento em cinco das seis dimensões estudadas. Além destes indícios, o trabalho também contribui ao deixar um rol de mais de duzentos e trinta itens validados com relação ao conceito de gestão do conhecimento, que podem ser testados e aperfeiçoados.

Aplicação de redes neurais na classificação de rentabilidade futura de empresas

Este trabalho tem por motivação evidenciar a eficiência de redes neurais na classificação de rentabilidade futura de empresas, e desta forma, prover suporte para o desenvolvimento de sistemas de apoio a tomada de decisão de investimentos. Para serem comparados com o modelo de redes neurais, foram escolhidos o modelo clássico de regressão linear múltipla, como referência mínima, e o de regressão logística ordenada, como marca comparativa de desempenho (benchmark). Neste texto, extraímos dados financeiros e contábeis das 1000 melhores empresas listadas, anualmente, entre 1996 e 2006, na publicação Melhores e Maiores – Exame (Editora Abril). Os três modelos foram construídos tendo como base as informações das empresas entre 1996 e 2005. Dadas as informações de 2005 para estimar a classificação das empresas em 2006, os resultados dos três modelos foram comparados com as classificações observadas em 2006, e o modelo de redes neurais gerou o melhor resultado.

Análise dos indicadores de qualidade versus taxa de abandono utilizando método de regressão múltipla para serviço de banda larga

Telecommunication is one of the most dynamic and strategic areas in the world. Many technological innovations has modified the way information is exchanged. Information and knowledge are now shared in networks. Broadband Internet is the new way of sharing contents and information. This dissertation deals with performance indicators related to maintenance services of telecommunications networks and uses models of multivariate regression to estimate churn, which is the loss of customers to other companies. In a competitive environment, telecommunications companies have devised strategies to minimize the loss of customers. Loosing customers presents a higher cost than obtaining new ones. Corporations have plenty of data stored in a diversity of databases. Usually the data are not explored properly. This work uses the Knowledge Discovery in Databases (KDD) to establish rules and new models to explain how churn, as a dependent variable, are related to a diversity of service indicators, such as time to deploy the service (in hours), time to repair (in hours), and so on. Extraction of meaningful knowledge is, in many cases, a challenge. Models were tested and statistically analyzed. The work also shows results that allows the analysis and identification of which quality services indicators influence the churn. Actions are also proposed to solve, at least in part, this problem

Análise de desempenho de vendas em telecomunicações utilizando técnicas de mineração de dados

Nowadays, telecommunications is one of the most dynamic and strategic areas in the world. Organizations are always seeking to find new management practices within an ever increasing competitive environment where resources are getting scarce. In this scenario, data obtained from business and corporate processes have even greater importance, although this data is not yet adequately explored. Knowledge Discovery in Databases (KDD) appears then, as an option to allow the study of complex problems in different areas of management. This work proposes both a systematization of KDD activities using concepts from different methodologies, such as CRISP-DM, SEMMA and FAYYAD approaches and a study concerning the viability of multivariate regression analysis models to explain corporative telecommunications sales using performance indicators. Thus, statistical methods were outlined to analyze the effects of such indicators on the behavior of business productivity. According to business and standard statistical analysis, equations were defined and fit to their respective determination coefficients. Tests of hypotheses were also conducted on parameters with the purpose of validating the regression models. The results show that there is a relationship between these development indicators and the amount of sales

Sistema Especialista para Supressão Online de Alarmes em Processos Industriais

Operating industrial processes is becoming more complex each day, and one of the factors that contribute to this growth in complexity is the integration of new technologies and smart solutions employed in the industry, such as the decision support systems. In this regard, this dissertation aims to develop a decision support system based on an computational tool called expert system. The main goal is to turn operation more reliable and secure while maximizing the amount of relevant information to each situation by using an expert system based on rules designed for a particular area of expertise. For the modeling of such rules has been proposed a high-level environment, which allows the creation and manipulation of rules in an easier way through visual programming. Despite its wide range of possible applications, this dissertation focuses only in the context of real-time filtering of alarms during the operation, properly validated in a case study based on a real scenario occurred in an industrial plant of an oil and gas refinery

Resolução espacial da Grade Ionosférica e do Give

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sistemas computacionais espaço-temporais para toma de decisão em questões ambientais relacionadas à indústria de petróleo e gás

The area between São Bento do Norte and Macau cities, located in the northern coast of the Rio Grande do Norte State is submitted to intense and constant processes of littoral and aeolian transport, causing erosion, alterations in the sediments balance and modifications in the shoreline. Beyond these natural factors, the human interference is huge in the surroundings, composed by sensitive places, due to the existence of the Guamaré Petroliferous Pole, RN, the greater terrestrial oil producing in Brazil, besides the activities of the salt companies and shrimp farms. This socioeconomic-environmental context justifies the elaboration of strategies of environmental monitoring of that coastal area. In the environmental monitoring of coastal strips, submitted to human impacts, the use of multi-sources and multitemporal data integrated through a Spatio- Temporal Database that allows the multiuser friendly access. The objective was to use the potential of the computational systems as important tools the managers of environmental monitoring. The stored data in the form of a virtual library aid in making decisions from the related results and presented in different formats. This procedure enlarges the use of the data in the preventive attendance, in the planning of future actions and in the definition of new lines of researches on the area, in a multiscale approach. Another activity of this Thesis consisted on the development of a computational system to automate the process to elaborate Oil-Spill Environmental Sensitivity Maps, based on the temporal variations that some coastal ecosystems present in the sensibility to the oil. The maps generated in this way, based on the methodology proposed by the Ministério do Meio Ambiente, supply more updated information about the behavior of the ecosystem, as a support to the operations in case of oil spill. Some parameters, such as the hydrodynamic data, the declivity of the beach face, types of resources in risk (environmental, economical, human or cultural) and use and occupation of the area are some of the essential basic information in the elaboration of the sensitivity maps, which suffer temporal alterations.In this way, the two computational systems developed are considered support systems to the decision, because they provide operational subsidies to the environmental monitoring of the coastal areas, considering the transformations in the behavior of coastal elements resulting from temporal changes related the human and/or natural interference of the environment

Method for estimating railroad track settlements due to dynamic traffic loads

This paper is the result of real-scale physical modeling study designed to simulate the load-deformation characteristics of railroad foundation systems that include the railroad ties, the ballast, and the sub-base layers of a railroad embankment. The study presents comparisons of the application of dynamic loads of 100kN on the rails, and the resulting deformations during a 500,000 cycle testing period for three rail support systems; wood, concrete and steel. The results show that the deformation curve has an exponential shape, with the larger portion of the deformation occurring during the first 50,000 load cycles followed by a tendency to stabilize between 100,000 to 500,000 cycles. These results indicate that the critical phase of deformations of a new railroad is within the first 50,000 cycles of loading, and after that, it slowly attenuates as it approaches a stable value. The paper also presents empirically derived formulations for the estimation of the deformations of the rail supports as a result of rail traffic.

Fuzzy environmental quality index

This paper presents the construction of a fuzzy environmental quality index for decision support in municipal environmental management. Five groups of indicators were selected in order to obtain an equation that best represented reality in terms of environmental quality. The calculation was carried out using fuzzy mathematical concepts, with the aid of the package Fuzzy Logical Toolbox 2.1 for Matlab ® 6.1, which provides functions and some applications of the theory of fuzzy sets. The work seeks to create a method of inference concerning the nature of urban areas that are unsustainable with respect to the environment, an issue that is often relegated to the background during public policy discussions. The development of this index, together with its implementation and dissemination, could improve public awareness of environmental issues, and promote mobilization towards the use of best practices in local development. © 2010 IEEE.

Aprendizado de máquina simbólico e técnicas fractais para caracterizar rejeição em biópsia miocárdica

This work combines symbolic machine learning and multiscale fractal techniques to generate models that characterize cellular rejection in myocardial biopsies and that can base a diagnosis support system. The models express the knowledge by the features threshold, fractal dimension, lacunarity, number of clusters, spatial percolation and percolation probability, all obtained with myocardial biopsies processing. Models were evaluated and the most significant was the one generated by the C4.5 algorithm for the features spatial percolation and number of clusters. The result is relevant and contributes to the specialized literature since it determines a standard diagnosis protocol. © 2013 Springer.

Sistema de informação sobre violência urbana (SiViU) como apoio à tomada de decisão em políticas públicas de cidades médias

Pós-graduação em Geografia - IGCE

Priorização de alternativas para melhoria do transporte aéreo de passageiros no eixo Rio-SP

Este trabalho estuda uma aplicação de um Método Multicritério (AHP do inglês Analytic Hierarchy Process) para analisar os problemas do congestionamento do tráfego aéreo nos aeroportos brasileiros, focando-se na ponte São Paulo-Rio de Janeiro. Primeiramente com um estudo em grupo mediante comparação em pares e posteriormente mediante um estudo individual com ratings. O objetivo deste trabalho será obter a alternativa mais adequada para os interesses do tráfego aéreo de Brasil