Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study was applied to the Bacchiglione catchment, located in Italy. The first methodological step was to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model were implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge were generated, as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location were assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that, overall, the assimilation of uncertain observations can improve the hydrologic model performance. In particular, it was found that the model structure is an important factor, of difficult characterization, since can induce different forecasts in terms of outflow discharge. This study is partly supported by the FP7 EU Project WeSenseIt.

Effective Data Management Enables Intelligent Utility Management

Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to manage data from smart water meters to the collaboration of data across third party corporations. This paper focuses on practical, utility successes in the water industry where utility managers are leveraging instantaneous access to data from proven, commercial off-the-shelf ODMS solutions to enable better real-time decision making. Successes include saving $650,000 / year in water loss control, safeguarding water quality, saving millions of dollars in energy management and asset management. Immediate opportunities exist to integrate the research being done in academia with these ODMS solutions in the field and to leverage these successes to utilities around the world.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.

Newly Automated System For Integrated Assessment Of The Conditions Of Underwater Gas Pipelines

An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.

Museus federais : a aplicação de modernas técnicas de gestão para lidar com as ameaças ao seu desempenho

Os museus federais, de um modo geral, nas duas últimas décadas, têm apresentado resultados satisfatórios no desempenho de sua missão básica - preservação e difusão do acervo que detêm - sem, necessariamente, contar para isso com apoio e recursos governamentais expressivos. Ao contrário, integrantes de uma área de governo sabidamente desfavorecida de recursos orçamentários, bem como de interesse político, desprovida, ainda, de quadros altamente qualificados, desenvolveram soluções próprias e um estilo peculiar de gestão para lidar com essas dificuldades crônicas. Tais soluções gerenciais (Associações de Amigos, criatividade, abnegação, flexibilidade, intensa participação etc.), alinhadas com um modo orgânico de funcionamento e adequadas até então, acobertam, de uma maneira sutil e arriscada, um quase absoluto despreparo profissional para a implementação de sistemas de controle gerencial orientados para resultados - gestão estratégica, programação e orçamentação, controle de qualidade, capacitação técnica e gerencial, indicadores de resultados e avaliação de programas etc. A crescente concorrência de outros meios de entretenimento e lazer, o aperto no controle do déficit público e a conseqüente pressão no sentido da publicização dessas atividades (fortes candidatas a virarem organizações sociais), somados ao esperado crescimento da cobrança social pela accountabilíty de seus dirigentes formam um cenário nada promissor para essas instituições, até então, imunes aos escândalos ou, pelo menos, a uma avaliação menos favorável pela população e demais stakeholders. O julgamento ainda vigente em grande parte de sua elite técnica de que não existe inteligência no mundo da administração, um mal necessário e de convívio difícil com as artes, reforça o belo desafio a ser enfrentado nos próximos anos pelos dirigentes dessas instituições.

Using an animated pedagogical agent to interact affectively with the student

This work proposes an animated pedagogical agent that has the role of providing emotional support to the student: motivating and encouraging him, making him believe in his self-ability, and promoting a positive mood in him, which fosters learning. This careful support of the agent, its affective tactics, is expressed through emotional behaviour and encouragement messages of the lifelike character. Due to human social tendency of anthropomorphising software, we believe that a software agent can accomplish this affective role. In order to choose the adequate affective tactics, the agent should also know the student’s emotions. The proposed agent recognises the student’s emotions: joy/distress, satisfaction/disappointment, anger/gratitude, and shame, from the student’s observable behaviour, i. e. his actions in the interface of the educational system. The inference of emotions is psychologically grounded on the cognitive theory of emotions. More specifically, we use the OCC model which is based on the cognitive approach of emotion and can be computationally implemented. Due to the dynamic nature of the student’s affective information, we adopted a BDI approach to implement the affective user model and the affective diagnosis. Besides, in our work we profit from the reasoning capacity of the BDI approach in order for the agent to deduce the student’s appraisal, which allows it to infer the student’s emotions. As a case study, the proposed agent is implemented as the Mediating Agent of MACES: an educational collaborative environment modelled as a multi-agent system and pedagogically based on the sociocultural theory of Vygotsky.

Valorização de beleza e inteligência por adolescentes de diferentes classes sociais

Participaram do estudo 180 adolescentes (90M e 90F) com idades variando entre 15 e 17 anos, alunos do ensino médio, pertencentes a diferentes classes sociais. Foram comparados gêneros e classes sócio-econômicas a respeito dos valores de beleza e de inteligência que adolescentes atribuem a si próprios e, numa situação hipotética e de forma mutuamente exclusiva, qual desses atributos foram mais valorizados para si mesmos e para possíveis parceiros. Os resultados mostraram que os rapazes de classe alta atribuíram-se maiores notas de inteligência. Adolescentes de ambos sexos pertencentes à classe baixa gostariam de possuir um maior nível de inteligência em detrimento da beleza, enquanto que adolescentes de classe alta preferem o equilíbrio entre beleza e inteligência. As moças valorizam mais a inteligência em seus parceiros que os rapazes, os quais valorizam mais a beleza em suas parceiras.

A significação na epistemologia genética: contribuições para uma teoria do conhecimento

Pós-graduação em Filosofia - FFC

A Natureza da reorganização do pensamento em um curso a distância sobre tendências em educação matemática

Pós-graduação em Educação Matemática - IGCE

Momentos fracionários e localização dinâmica para o modelo de Anderson discreto multidimensional

Pós-graduação em Matematica Aplicada e Computacional - FCT

Análise global de sistemas quadráticos e cúbicos com duas circunferências não-concêntricas invariantes

Pós-graduação em Matematica Aplicada e Computacional - FCT

Estabilidade estocástica de sistemas lineares com Saltos Markovianos e Sistemas Lineares com Saltos Semimarkovianos

Pós-graduação em Matematica Aplicada e Computacional - FCT

Inteligência coletiva: um olhar sobre a produção de Pierre Lévy

Collective intelligence is an interdisciplinary subject and it has been explored for many different knowledge areas. As a proposal totally tied to the concept of information and information technologies and communication, it is considered as relevant the discussion about the topic within the scope of Information Science. Therefore, a descriptive and exploratory study was carried out from Pierre Levy's work, identifying the precepts of collective intelligence and its ambiences and implications. The research is documental, focusing on determining the state of the art of the production about collective intelligence, verifying what was produced by Pierre Lévy and by other authors about the subject, in order to point out what possible interventions of Information Science on studies about collective intelligence. The research showed that that in the field of Information Science there is little research on the theoretical level about collective intelligence. Nevertheless, discussions about the representation and organization of collective intelligence in digital environments have been recurrent in the present, thus opening new fields of approach between Information Science and conceptual research and practice in collective intelligence.