Sistemas granulares evolutivos

Orientador: Fernando Antonio Campos GomideTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Recentemente tem-se observado um crescente interesse em abordagens de modelagem computacional para lidar com fluxos de dados do mundo real. Métodos e algoritmos têm sido propostos para obtenção de conhecimento a partir de conjuntos de dados muito grandes e, a princípio, sem valor aparente. Este trabalho apresenta uma plataforma computacional para modelagem granular evolutiva de fluxos de dados incertos. Sistemas granulares evolutivos abrangem uma variedade de abordagens para modelagem on-line inspiradas na forma com que os humanos lidam com a complexidade. Esses sistemas exploram o fluxo de informação em ambiente dinâmico e extrai disso modelos que podem ser linguisticamente entendidos. Particularmente, a granulação da informação é uma técnica natural para dispensar atenção a detalhes desnecessários e enfatizar transparência, interpretabilidade e escalabilidade de sistemas de informação. Dados incertos (granulares) surgem a partir de percepções ou descrições imprecisas do valor de uma variável. De maneira geral, vários fatores podem afetar a escolha da representação dos dados tal que o objeto representativo reflita o significado do conceito que ele está sendo usado para representar. Neste trabalho são considerados dados numéricos, intervalares e fuzzy; e modelos intervalares, fuzzy e neuro-fuzzy. A aprendizagem de sistemas granulares é baseada em algoritmos incrementais que constroem a estrutura do modelo sem conhecimento anterior sobre o processo e adapta os parâmetros do modelo sempre que necessário. Este paradigma de aprendizagem é particularmente importante uma vez que ele evita a reconstrução e o retreinamento do modelo quando o ambiente muda. Exemplos de aplicação em classificação, aproximação de função, predição de séries temporais e controle usando dados sintéticos e reais ilustram a utilidade das abordagens de modelagem granular propostas. O comportamento de fluxos de dados não-estacionários com mudanças graduais e abruptas de regime é também analisado dentro do paradigma de computação granular evolutiva. Realçamos o papel da computação intervalar, fuzzy e neuro-fuzzy em processar dados incertos e prover soluções aproximadas de alta qualidade e sumário de regras de conjuntos de dados de entrada e saída. As abordagens e o paradigma introduzidos constituem uma extensão natural de sistemas inteligentes evolutivos para processamento de dados numéricos a sistemas granulares evolutivos para processamento de dados granularesAbstract: In recent years there has been increasing interest in computational modeling approaches to deal with real-world data streams. Methods and algorithms have been proposed to uncover meaningful knowledge from very large (often unbounded) data sets in principle with no apparent value. This thesis introduces a framework for evolving granular modeling of uncertain data streams. Evolving granular systems comprise an array of online modeling approaches inspired by the way in which humans deal with complexity. These systems explore the information flow in dynamic environments and derive from it models that can be linguistically understood. Particularly, information granulation is a natural technique to dispense unnecessary details and emphasize transparency, interpretability and scalability of information systems. Uncertain (granular) data arise from imprecise perception or description of the value of a variable. Broadly stated, various factors can affect one's choice of data representation such that the representing object conveys the meaning of the concept it is being used to represent. Of particular concern to this work are numerical, interval, and fuzzy types of granular data; and interval, fuzzy, and neurofuzzy modeling frameworks. Learning in evolving granular systems is based on incremental algorithms that build model structure from scratch on a per-sample basis and adapt model parameters whenever necessary. This learning paradigm is meaningful once it avoids redesigning and retraining models all along if the system changes. Application examples in classification, function approximation, time-series prediction and control using real and synthetic data illustrate the usefulness of the granular approaches and framework proposed. The behavior of nonstationary data streams with gradual and abrupt regime shifts is also analyzed in the realm of evolving granular computing. We shed light upon the role of interval, fuzzy, and neurofuzzy computing in processing uncertain data and providing high-quality approximate solutions and rule summary of input-output data sets. The approaches and framework introduced constitute a natural extension of evolving intelligent systems over numeric data streams to evolving granular systems over granular data streamsDoutoradoAutomaçãoDoutor em Engenharia Elétric

Implementation of a business intelligence system in a public institution

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceTechnology is capable to support companies to reach their goals by making use data to take advantages from its analysis. Concerning public institutions, it is meaningful to deliver high-quality services and products to society, and technology may lead the organizations to a more efficient service provision. The purpose of this project is the implementation of a business intelligence system in Consultoria Jurídica da União (CJU) [Consultancy Office], the institution responsible for analyzing bidding processes in Brazil. The solution proposed by this work aims to store the business data and provide an analytical tool to display information in dashboards to provide insights to stakeholders, analyzing data trends and tendencies, preventing future unnecessary events, identifying best practices, to finally improve the public tenders to a better application of public funds and provide better services to society. To reach this project main objective, the technology that surrounds the BI system to be implemented includes the development of a scalable data warehouse to store the organization data and its schema modelling, the extraction-transform-load method to populate the data warehouse tables, and create the analytical tool, named dashboard, to answer the business needs providing the institution information. This business intelligence system intends to improve the legal bidding process in public agencies by making use of technology

Nutrient Removal in Willow Biomass Crops is Impacted Over Multiple Rotations, Timing of Harvest, and Harvesting System

The pressing need to mitigate climate change and find alternative uses for marginal agricultural land have stimulated the establishment of short rotation woody crops (SRWC), like shrub willow, in both North America and Europe. There is limited research on the dynamics of nutrient removal over several rotations in these systems and little is known about the long-term impacts of repeated whole-plant harvesting on soil nutrient concentrations. This study compared nutrient removals among 18 cultivars of willow harvested across three three-year rotations at two sites and changes in the soil nutrient concentrations. Nutrient removal was statistically different among rotations for all studied elements in the following order 2011 ≤ 2017 \u3c 2014. For example, K removal was 7 kg ha-1 year-1 in 2011, 14 kg ha-1 year-1 in 2017, and 20 kg ha-1 year-1 in 2014 at the Belleville site. Additionally, significant effects of site (for N and Ca) and cultivar (all elements) were observed. A significant decrease in soil concentrations among years was observed for total N (1,986 g kg-1 in 2008 and 1,633 g kg-1 in 2017) and P (6.9 g kg-1 in 2008 and 3.4 g kg-1 in 2017) at one site (Belleville) while a significant increase was observed for K (44 g kg-1 in 2008 and 57 g kg-1 in 2017) at the other site (Tully). These results show that shrub willow crops are not negatively impacting extractable nutrient reserves and are capable of recycling nutrients effectively over a 10-year period. Adequate nutrient management guidelines for commercial willow sites should be site specific, consider the selection of cultivars deployed given the high variation in nutrient removal among cultivars, and the soil nutritional status

Amphibia, Anura, Hylidae, Scinax fuscomarginatus: distribution extension

Non

On the role of business incubators to foster entrepreneurship

One of the mostly used instruments to foster entrepreuneurship are business incubators, which aim to support the development of new business ideas in which the incubators help firms to survive and grow during their initial stages. The objective of this paper is to provide the results of the analysis of three case studies about the business incubation process in Portugal, contributing to enhance the knowledge about this subject. The main findings of the paper are the following: the three incubators are focused on stimulating entrepreneurship, new business ideas and innovation, and are concerned in being a facilitator agent of the success of those new projects; however, some differences might be seen among these incubators, namely in terms of criteria used to select the new business ideas or projects, the support services provided to the incubatees, the incubation period, and the type of projects supported