Mecanismos de governança corporativa na pequena empresa familiar

Esta dissertação tem como objetivo descrever e analisar como o fenômeno da governança corporativa articula mecanismos de gestão e impacta na dinâmica de uma pequena organização familiar. Para isso, utilizou-se as perspectivas de Fan (2001) e Silva Junior (2006), que tratam da governança corporativa, e de Chandler (1994), para empresas familiares. Através de abordagem qualitativa com ênfase em um estudo de caso, uma triangulação de dados foi realizada, utilizando a entrevista semiestruturada, observação assistemática ou livre e pesquisa de documentos, e a análise dos dados foi realizada por análise de conteúdo. Verificou-se a presença do fenômeno da governança por intermédio da identificação dos fatores de diferenciação, resultando na implantação de mecanismos de governança ao longo do ciclo de vida da organização familiar, o que possibilitou mudanças em seu controle, no seu processo sucessório e na sua profissionalização. Quanto ao controle, foram verificados que os mecanismos de “manutenção do status quo”, “aconselhamento profissional”, “sinergia de interesses”, “regulamentação financeira da sociedade”, “atribuições e responsabilidades”, “alinhamento de interesses do negócio” e “proteção do empreendimento familiar” possibilitaram a modificação e manutenção do controle da empresa com os sócios. Quanto ao eixo da profissionalização, foi verificado que os mecanismos de “regulamentação financeira da sociedade”, “atribuições e responsabilidades”, “alinhamento de interesses do negócio”, “proteção do empreendimento familiar” e “atenção aos interesses dos stakeholders” foram responsáveis por prover as modificações neste quesito e indicar que a empresa caminha no sentido de se profissionalizar. Quanto ao processo sucessório, verificou-se que a terceira geração não tem interesse na empresa, o que podem resultar na contratação de um profissional externo para gerir a mesma, respeitando a questão dos valores familiares e a cultura organizacional ou conduzir à sucessão recursiva. Aparentemente, observou-se que a segunda questão foi mais evidente, visto que a saída do último irmão do negócio culmina com a venda da empresa familiar, gerando duas alternativas: a compra da empresa por um grupo de sócios ou outra empresa não familiar, o que resultaria na “morte” da empresa enquanto empresa familiar; ou a sua compra por outra família ou empresa familiar, preservando sua classificação inicial.

Avaliação assistida informatizada : indicadores do potencial cognitivo de crianças com deficiência

A identificação e a avaliação de crianças com desenvolvimento atípico configuram um processo muito importante para subsidiar as estratégias de ensino voltadas para a promoção do potencial de aprendizagem. O interesse em relação ao prognóstico de crianças com deficiência tem impulsionado o desenvolvimento de novas tecnologias e pesquisas relacionadas à avaliação, prevenção e intervenção. Nesse contexto, torna-se relevante verificar com instrumentos adequados indicadores linguísticos, cognitivos e comportamentais, para assim traçar metas a partir daquilo que as crianças podem aprender. Dessa forma, esta pesquisa teve por objetivo verificar se a avaliação assistida informatizada se apresenta como uma modalidade de diagnóstico mais prescritivo do desenvolvimento cognitivo, quando comparada à avaliação psicométrica, na aplicação em crianças com deficiência. Na modalidade assistida há ajuda do examinador para conduzir a criança a um melhor nível de desempenho cognitivo. Participaram 11 crianças que frequentam uma instituição de atendimento clínico, em saúde, para crianças com deficiência, na Grande Vitória. Na avaliação psicométrica foram utilizados a Escala de Maturidade Mental Colúmbia computadorizada – Colúmbiacomp e o Teste de Vocabulário por Imagens Peabody - TVIPcomp. Na avaliação assistida informatizada foram aplicadas três provas voltadas para as habilidades de classificação e raciocínio analógico: Exclusão de Objetos, Exclusão de Figuras Geométricas e Jogo de Analogia de Figuras, no ambiente informatizado SINDAPSI. Protocolos de registro de fatores afetivo-motivacionais e de operações cognitivas foram utilizados durante as tarefas assistidas. Na avaliação do comportamento, o Child Behavior Checklist – CBCL foi respondido pelas mães. Dados documentais e dos instrumentos foram submetidos à análise estatística descritiva para verificar o desempenho das crianças nas duas formas de avaliação informatizada (psicométrica e assistida). Nos testes psicométricos, 64% das crianças alcançaram índice “abaixo da média” no TVIPcomp, e 55% “médio-inferior” no Colúmbiacomp. Em relação ao perfil de desempenho cognitivo, na Prova de Exclusão de Objetos computadorizada 55% das crianças foram avaliadas como “não-mantenedoras”. Na Prova de Exclusão de Figuras Geométricas computadorizada 55% da amostra foi classificada no perfil “alto-escore”, e no Jogo de Analogias de Figuras computadorizado 45% apresentou o perfil “ganhador”. A amostra demonstrou níveis de dificuldade na realização dos testes,tanto na modalidade psicométrica quanto assistida. Contudo, o desempenho nos testes assistidos foi relativamente melhor, evidenciando que o grupo se beneficiou da mediação,implementada na fase de assistência, para melhorar as habilidades cognitivas. Além disso, a apresentação informatizada dos testes apresentou-se como fator motivador para a realização e persistência nas tarefas.

Radial Distortion Self-Calibration

In cameras with radial distortion, straight lines in space are in general mapped to curves in the image. Although epipolar geometry also gets distorted, there is a set of special epipolar lines that remain straight, namely those that go through the distortion center. By finding these straight epipolar lines in camera pairs we can obtain constraints on the distortion center(s) without any calibration object or plumbline assumptions in the scene. Although this holds for all radial distortion models we conceptually prove this idea using the division distortion model and the radial fundamental matrix which allow for a very simple closed form solution of the distortion center from two views (same distortion) or three views (different distortions). The non-iterative nature of our approach makes it immune to local minima and allows finding the distortion center also for cropped images or those where no good prior exists. Besides this, we give comprehensive relations between different undistortion models and discuss advantages and drawbacks.

Effect of N and K doses in nutritive solution on growth, production and coffee bean size

An adequate supply of nutrients is essential for obtaining high yields of coffee. The objective of this study was to evaluate the effect of N, K and the N:K ratio on vegetative and reproductive growth of coffee. For this purpose, coffee plants were grown in nutrient solution containing K in the concentrations of 1.08; 2.15; 3.23 and 5.38 mmol L-1 combined with a dose of 6 mmol L-1 N, resulting in the N:K ratios (w/w): 1:0.5; 1:1; 1:1.5 and 1:2.5. The control treatment consisted of the doses 3 and 1.61 mmol L-1 of N and K respectively, resulting in the N:K ratio (w/w) 1.0:1.5. The following variables were evaluated: height, stem diameter, number of nodes of the eighth plagiotrofic branch (index branch), pairs of plagiotrofic branches and number of nodes in the orthotropic branch every three weeks from the beginning of the experiment. Additionally, it was evaluated the chemical composition of processed beans and leaves between the flowering and the rapid expansion stage of the cherry beans, production of cherry beans per plant and classification of beans according to the size. N influenced mainly the characteristics of vegetative growth and K influenced mainly the reproductive growth evaluated by the production. The lowest production resulted in the highest percentages of beans retained on sieves with holes larger than 16/64", while the highest production promoted an increase in the percentage of beans retained on sieves with holes smaller than 16/64".

Comparison of methods for classification of the coefficient of variation in papaya

ABSTRACT The objective of this work was to study the distribution of values of the coefficient of variation (CV) in the experiments of papaya crop (Carica papaya L.) by proposing ranges to guide researchers in their evaluation for different characters in the field. The data used in this study were obtained by bibliographical review in Brazilian journals, dissertations and thesis. This study considered the following characters: diameter of the stalk, insertion height of the first fruit, plant height, number of fruits per plant, fruit biomass, fruit length, equatorial diameter of the fruit, pulp thickness, fruit firmness, soluble solids and internal cavity diameter, from which, value ranges were obtained for the CV values for each character, based on the methodology proposed by Garcia, Costa and by the standard classification of Pimentel-Gomes. The results obtained in this study indicated that ranges of CV values were different among various characters, presenting a large variation, which justifies the necessity of using specific evaluation range for each character. In addition, the use of classification ranges obtained from methodology of Costa is recommended.

Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.

Multi-attribute classification of housing conservation status in urban regeneration actions

Urban regeneration is more and more a “universal issue” and a crucial factor in the new trends of urban planning. It is no longer only an area of study and research; it became part of new urban and housing policies. Urban regeneration involves complex decisions as a consequence of the multiple dimensions of the problems that include special technical requirements, safety concerns, socio-economic, environmental, aesthetic, and political impacts, among others. This multi-dimensional nature of urban regeneration projects and their large capital investments justify the development and use of state-of-the-art decision support methodologies to assist decision makers. This research focuses on the development of a multi-attribute approach for the evaluation of building conservation status in urban regeneration projects, thus supporting decision makers in their analysis of the problem and in the definition of strategies and priorities of intervention. The methods presented can be embedded into a Geographical Information System for visualization of results. A real-world case study was used to test the methodology, whose results are also presented.

Comparative evaluation of underlying causes of death processed by the Automated Classification of Medical Entities and the Underlying Cause of Death Selection Systems

INTRODUCTION: The correct identification of the underlying cause of death and its precise assignment to a code from the International Classification of Diseases are important issues to achieve accurate and universally comparable mortality statistics These factors, among other ones, led to the development of computer software programs in order to automatically identify the underlying cause of death. OBJECTIVE: This work was conceived to compare the underlying causes of death processed respectively by the Automated Classification of Medical Entities (ACME) and the "Sistema de Seleção de Causa Básica de Morte" (SCB) programs. MATERIAL AND METHOD: The comparative evaluation of the underlying causes of death processed respectively by ACME and SCB systems was performed using the input data file for the ACME system that included deaths which occurred in the State of S. Paulo from June to December 1993, totalling 129,104 records of the corresponding death certificates. The differences between underlying causes selected by ACME and SCB systems verified in the month of June, when considered as SCB errors, were used to correct and improve SCB processing logic and its decision tables. RESULTS: The processing of the underlying causes of death by the ACME and SCB systems resulted in 3,278 differences, that were analysed and ascribed to lack of answer to dialogue boxes during processing, to deaths due to human immunodeficiency virus [HIV] disease for which there was no specific provision in any of the systems, to coding and/or keying errors and to actual problems. The detailed analysis of these latter disclosed that the majority of the underlying causes of death processed by the SCB system were correct and that different interpretations were given to the mortality coding rules by each system, that some particular problems could not be explained with the available documentation and that a smaller proportion of problems were identified as SCB errors. CONCLUSION: These results, disclosing a very low and insignificant number of actual problems, guarantees the use of the version of the SCB system for the Ninth Revision of the International Classification of Diseases and assures the continuity of the work which is being undertaken for the Tenth Revision version.

Towards an efficient and robust foot classification from pedobarographic images

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Integrated vehicle classification system

This paper presents an integrated system for vehicle classification. This system aims to classify vehicles using different approaches: 1) based on the height of the first axle and_the number of axles; 2) based on volumetric measurements and; 3) based on features extracted from the captured image of the vehicle. The system uses a laser sensor for measurements and a set of image analysis algorithms to compute some visual features. By combining different classification methods, it is shown that the system improves its accuracy and robustness, enabling its usage in more difficult environments satisfying the proposed requirements established by the Portuguese motorway contractor BRISA.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Materiais estruturados: qual o seu papel na aprendizágem dos primeiros números?

Dissertação apresentada para obtenção do grau de Mestre em Educação Matemática na Educação Pré-Escolar e no 1.º e 2.º Ciclos do Ensino Básico

Identificação e análise de movimento humano com ultrassons

Faz-se nesta dissertação a análise do movimento humano utilizando sinais de ultrassons refletidos pelos diversos membros do corpo humano, designados por assinaturas de ultrassons. Estas assinaturas são confrontadas com os sinais gerados pelo contato dos membros inferiores do ser humano com o chão, recolhidos de forma passiva. O método seguido teve por base o estudo das assinaturas de Doppler e micro-Doppler. Estas assinaturas são obtidas através do processamento dos ecos de ultrassons recolhidos, com recurso à Short-Time Fourier Transform e apresentadas sobre a forma de espectrograma, onde se podem identificar os desvios de frequência causados pelo movimento das diferentes partes do corpo humano. É proposto um algoritmo inovador que, embora possua algumas limitações, é capaz de isolar e extrair de forma automática algumas das curvas e parâmetros característicos dos membros envolvidos no movimento humano. O algoritmo desenvolvido consegue analisar as assinaturas de micro-Doppler do movimento humano, estimando diversos parâmetros tais como o número de passadas realizadas, a cadência da passada, o comprimento da passada, a velocidade a que o ser humano se desloca e a distância percorrida. Por forma a desenvolver, no futuro, um classificador capaz de distinguir entre humanos e outros animais, são também recolhidas e analisadas assinaturas de ultrassons refletidas por dois animais quadrúpedes, um canino e um equídeo. São ainda estudadas as principais características que permitem classificar o tipo de animal que originou a assinatura de ultrassons. Com este estudo mostra-se ser possível a análise de movimento humano por ultrassons, havendo características nas assinaturas recolhidas que permitem a classificação do movimento como humano ou não humano. Do trabalho desenvolvido resultou ainda uma base de dados de assinaturas de ultrassons de humanos e animais que permitirá suportar trabalho de investigação e desenvolvimento futuro.