FUSÕES E AQUISIÇÕES: UMA EXPERIÊNCIA DE INTEGRAÇÃO COM SUCESSO

Esta dissertação apresenta um estudo exploratório que tem como objetivo analisar o caso de uma experiência de integração com sucesso de uma fusão de duas empresas com estruturas organizacionais diferentes, tomando como referência a experiência internacional diante da escassez de estudos sistemáticos sobre a integração de fusões e aquisições no Brasil. O estudo se propõe a investigar como foi processada a integração entre as duas empresas buscando analisar os fatores que ocasionaram o sucesso dessa fusão. A metodologia adotada consiste na pesquisa bibliográfica e documental com observação participativa. Os dados foram obtidos por meio de documentos públicos sobre a empresa, que serviram de apoio à pesquisa realizada. Para objeto de pesquisa foi selecionada a empresa SmithKline Beecham, por ser uma empresa global com fabricas no Brasil. Os resultados obtidos apontaram que a integração da empresa foi feita com sucesso, significando que os objetivos estratégicos e de sinergias da fusão, representados por resultados financeiros, de mercado, pesquisa, desenvolvimento e lançamento de novos produtos foram alcançados. A empresa combinada, depois de terminado o processo de integração, apresentava resultados superiores do que quando as duas atuavam separadamente, comprovando que os mecanismos utilizados na integração das duas empresas funcionaram com eficácia. Entretanto, recomendamos que outros estudos como este sejam organizados na busca de novos aspectos que possam servir de suporte às decisões dos empresários quanto à adoção da abordagem estratégica das fusões e aquisições.(AU)

FUSÕES E AQUISIÇÕES: UMA EXPERIÊNCIA DE INTEGRAÇÃO COM SUCESSO

Esta dissertação apresenta um estudo exploratório que tem como objetivo analisar o caso de uma experiência de integração com sucesso de uma fusão de duas empresas com estruturas organizacionais diferentes, tomando como referência a experiência internacional diante da escassez de estudos sistemáticos sobre a integração de fusões e aquisições no Brasil. O estudo se propõe a investigar como foi processada a integração entre as duas empresas buscando analisar os fatores que ocasionaram o sucesso dessa fusão. A metodologia adotada consiste na pesquisa bibliográfica e documental com observação participativa. Os dados foram obtidos por meio de documentos públicos sobre a empresa, que serviram de apoio à pesquisa realizada. Para objeto de pesquisa foi selecionada a empresa SmithKline Beecham, por ser uma empresa global com fabricas no Brasil. Os resultados obtidos apontaram que a integração da empresa foi feita com sucesso, significando que os objetivos estratégicos e de sinergias da fusão, representados por resultados financeiros, de mercado, pesquisa, desenvolvimento e lançamento de novos produtos foram alcançados. A empresa combinada, depois de terminado o processo de integração, apresentava resultados superiores do que quando as duas atuavam separadamente, comprovando que os mecanismos utilizados na integração das duas empresas funcionaram com eficácia. Entretanto, recomendamos que outros estudos como este sejam organizados na busca de novos aspectos que possam servir de suporte às decisões dos empresários quanto à adoção da abordagem estratégica das fusões e aquisições.(AU)

Memory-enhancing effects of secreted forms of the β-amyloid precursor protein in normal and amnestic mice

When administered intracerebroventricularly to mice performing various learning tasks involving either short-term or long-term memory, secreted forms of the β-amyloid precursor protein (APPs751 and APPs695) have potent memory-enhancing effects and block learning deficits induced by scopolamine. The memory-enhancing effects of APPs were observed over a wide range of extremely low doses (0.05-5,000 pg intracerebroventricularly), blocked by anti-APPs antisera, and observed when APPs was administered either after the first training session in a visual discrimination or a lever-press learning task or before the acquisition trial in an object recognition task. APPs had no effect on motor performance or exploratory activity. APPs695 and APPs751 were equally effective in the object recognition task, suggesting that the memory-enhancing effect of APPs does not require the Kunitz protease inhibitor domain. These data suggest an important role for APPss on memory processes.

Lightness constancy in primary visual cortex

When the illumination of a visual scene changes, the quantity of light reflected from objects is altered. Despite this, the perceived lightness of the objects generally remains constant. This perceptual lightness constancy is thought to be important behaviorally for object recognition. Here we show that interactions from outside the classical receptive fields of neurons in primary visual cortex modulate neural responses in a way that makes them immune to changes in illumination, as is perception. This finding is consistent with the hypothesis that the responses of neurons in primary visual cortex carry information about surface lightness in addition to information about form. It also suggests that lightness constancy, which is sometimes thought to involve “higher-level” processes, is manifest at the first stage of visual cortical processing.

Constellations and the unsupervised learning of graphs

In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an EM central clustering algorithm which builds prototypical graphs on the basis of fast matching with graph transformations. Our experiments, both with random graphs and in realistic situations (visual localization), show that our prototypes improve the set median graphs and also the prototypes derived from our previous incremental method. We also discuss how the method scales with a growing number of images.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

Real-time 3D semi-local surface patch extraction using GPGPU

Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Fractal analysis of pyramidal cells in the visual cortex of the galago (Otolemur garnetti): Regional variation in dendritic branching patterns between visual areas

Previously it has been shown that the branching pattern of pyramidal cells varies markedly between different cortical areas in simian primates. These differences are thought to influence the functional complexity of the cells. In particular, there is a progressive increase in the fractal dimension of pyramidal cells with anterior progression through cortical areas in the occipitotemporal (OT) visual stream, including the primary visual area (V1), the second visual area (V2), the dorsolateral area (DL, corresponding to the fourth visual area) and inferotemporal cortex (IT). However, there are as yet no data on the fractal dimension of these neurons in prosimian primates. Here we focused on the nocturnal prosimian galago (Otolemur garnetti). The fractal dimension (D), and aspect ratio (a measure of branching symmetry), was determined for I I I layer III pyramidal cells in V1, V2, DL and IT. We found, as in simian primates, that the fractal dimension of neurons increased with anterior progression from V1 through V2, DL, and IT. Two important conclusions can be drawn from these results: (1) the trend for increasing branching complexity with anterior progression through OT areas was likely to be present in a common primate ancestor, and (2) specialization in neuron structure more likely facilitates object recognition than spectral processing.

Stability criteria for unsupervised temporal association networks

A biologically realizable, unsupervised learning rule is described for the online extraction of object features, suitable for solving a range of object recognition tasks. Alterations to the basic learning rule are proposed which allow the rule to better suit the parameters of a given input space. One negative consequence of such modifications is the potential for learning instability. The criteria for such instability are modeled using digital filtering techniques and predicted regions of stability and instability tested. The result is a family of learning rules which can be tailored to the specific environment, improving both convergence times and accuracy over the standard learning rule, while simultaneously insuring learning stability.

The correspondence framework for 3D surface matching algorithms

Beyond the inherent technical challenges, current research into the three dimensional surface correspondence problem is hampered by a lack of uniform terminology, an abundance of application specific algorithms, and the absence of a consistent model for comparing existing approaches and developing new ones. This paper addresses these challenges by presenting a framework for analysing, comparing, developing, and implementing surface correspondence algorithms. The framework uses five distinct stages to establish correspondence between surfaces. It is general, encompassing a wide variety of existing techniques, and flexible, facilitating the synthesis of new correspondence algorithms. This paper presents a review of existing surface correspondence algorithms, and shows how they fit into the correspondence framework. It also shows how the framework can be used to analyse and compare existing algorithms and develop new algorithms using the framework's modular structure. Six algorithms, four existing and two new, are implemented using the framework. Each implemented algorithm is used to match a number of surface pairs. Results demonstrate that the correspondence framework implementations are faithful implementations of existing algorithms, and that powerful new surface correspondence algorithms can be created. (C) 2004 Elsevier Inc. All rights reserved.

Turning configural processing upside down: Part and whole body postures

Like faces, body postures are susceptible to an inversion effect in untrained viewers. The inversion effect may be indicative of configural processing, but what kind of configural processing is used for the recognition of body postures must be specified. The information available in the body stimulus was manipulated. The presence and magnitude of inversion effects were compared for body parts, scrambled bodies, and body halves relative to whole bodies and to corresponding conditions for faces and houses. Results suggest that configural body posture recognition relies on the structural hierarchy of body parts, not the parts themselves or a complete template match. Configural recognition of body postures based on information about the structural hierarchy of parts defines an important point on the configural processing continuum, between recognition based on first-order spatial relations and recognition based on holistic undifferentiated template matching.

A global vision system for a robot soccer team

This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system acheives a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.

FUSÕES E AQUISIÇÕES: UMA EXPERIÊNCIA DE INTEGRAÇÃO COM SUCESSO

Esta dissertação apresenta um estudo exploratório que tem como objetivo analisar o caso de uma experiência de integração com sucesso de uma fusão de duas empresas com estruturas organizacionais diferentes, tomando como referência a experiência internacional diante da escassez de estudos sistemáticos sobre a integração de fusões e aquisições no Brasil. O estudo se propõe a investigar como foi processada a integração entre as duas empresas buscando analisar os fatores que ocasionaram o sucesso dessa fusão. A metodologia adotada consiste na pesquisa bibliográfica e documental com observação participativa. Os dados foram obtidos por meio de documentos públicos sobre a empresa, que serviram de apoio à pesquisa realizada. Para objeto de pesquisa foi selecionada a empresa SmithKline Beecham, por ser uma empresa global com fabricas no Brasil. Os resultados obtidos apontaram que a integração da empresa foi feita com sucesso, significando que os objetivos estratégicos e de sinergias da fusão, representados por resultados financeiros, de mercado, pesquisa, desenvolvimento e lançamento de novos produtos foram alcançados. A empresa combinada, depois de terminado o processo de integração, apresentava resultados superiores do que quando as duas atuavam separadamente, comprovando que os mecanismos utilizados na integração das duas empresas funcionaram com eficácia. Entretanto, recomendamos que outros estudos como este sejam organizados na busca de novos aspectos que possam servir de suporte às decisões dos empresários quanto à adoção da abordagem estratégica das fusões e aquisições.(AU)

The anatomical and functional correlates of category-specificity

The dramatic effects of brain damage can provide some of the most interesting insights into the nature of normal cognitive performance. In recent years a number of neuropsychological studies have reported a particular form of cognitive impairment where patients have problems recognising objects from one category but remain able to recognise those from others. The most frequent ‘category-specific’ pattern is an impairment identifying living things, compared to nonliving things. The reverse pattern of dissociation, i.e., an impairment recognising and naming nonliving things relative to living things, has been reported albeit much less frequently. The objective of the work carried out in this thesis was to investigate the organising principles and anatomical correlates of stored knowledge for categories of living and nonliving things. Three complementary cognitive neuropsychological research techniques were employed to assess how, and where, this knowledge is represented in the brain: (i) studies of normal (neurologically intact) subjects, (ii) case-studies of neurologically impaired patients with selective deficits in object recognition, and (iii) studies of the anatomical correlates of stored knowledge for living and nonliving things on the brain using magnetoencephalography (MEG). The main empirical findings showed that semantic knowledge about living and nonliving things is principally encoded in terms of sensory and functional features, respectively. In two case-study chapters evidence was found supporting the view that category-specific impairments can arise from damage to a pre-semantic system, rather than the assumption often made that the system involved must be semantic. In the MEG study, rather than finding evidence for the involvement of specific brain areas for different object categories, it appeared that, when subjects named and categorised living and nonliving things, a non-differentiated neural system was involved.