Formulações e algoritmos para o problema das p-medianas heterogêneo livre de penalidade

This work presents a new model for the Heterogeneous p-median Problem (HPM), proposed to recover the hidden category structures present in the data provided by a sorting task procedure, a popular approach to understand heterogeneous individual’s perception of products and brands. This new model is named as the Penalty-free Heterogeneous p-median Problem (PFHPM), a single-objective version of the original problem, the HPM. The main parameter in the HPM is also eliminated, the penalty factor. It is responsible for the weighting of the objective function terms. The adjusting of this parameter controls the way that the model recovers the hidden category structures present in data, and depends on a broad knowledge of the problem. Additionally, two complementary formulations for the PFHPM are shown, both mixed integer linear programming problems. From these additional formulations lower-bounds were obtained for the PFHPM. These values were used to validate a specialized Variable Neighborhood Search (VNS) algorithm, proposed to solve the PFHPM. This algorithm provided good quality solutions for the PFHPM, solving artificial generated instances from a Monte Carlo Simulation and real data instances, even with limited computational resources. Statistical analyses presented in this work suggest that the new algorithm and model, the PFHPM, can recover more accurately the original category structures related to heterogeneous individual’s perceptions than the original model and algorithm, the HPM. Finally, an illustrative application of the PFHPM is presented, as well as some insights about some new possibilities for it, extending the new model to fuzzy environments

Comportamento de compra por impulso em shopping centers: pesquisa com consumidores de Brasília-DF e Natal-RN

ARAUJO, G. P. ; RAMOS, A. S. M. . Comportamento de Compra por Impulso em Shopping Centers: pesquisa com Consumidores de Brasília-DF e Natal-RN. REAd. Revista Eletrônica de Administração (Porto Alegre. Online) , v. 16, p. 343-364, 2010.

Análise fractal da vasculatura retínica: métodos de segmentação e de cálculo dimensional

Embora tenha sido proposto que a vasculatura retínica apresenta estrutura fractal, nenhuma padronização do método de segmentação ou do método de cálculo das dimensões fractais foi realizada. Este estudo objetivou determinar se a estimação das dimensões fractais da vasculatura retínica é dependente dos métodos de segmentação vascular e dos métodos de cálculo de dimensão. Métodos: Dez imagens retinográficas foram segmentadas para extrair suas árvores vasculares por quatro métodos computacionais (“multithreshold”, “scale-space”, “pixel classification” e “ridge based detection”). Suas dimensões fractais de “informação”, de “massa-raio” e “por contagem de caixas” foram então calculadas e comparadas com as dimensões das mesmas árvores vasculares, quando obtidas pela segmentação manual (padrão áureo). Resultados: As médias das dimensões fractais variaram através dos grupos de diferentes métodos de segmentação, de 1,39 a 1,47 para a dimensão por contagem de caixas, de 1,47 a 1,52 para a dimensão de informação e de 1,48 a 1,57 para a dimensão de massa-raio. A utilização de diferentes métodos computacionais de segmentação vascular, bem como de diferentes métodos de cálculo de dimensão, introduziu diferença estatisticamente significativa nos valores das dimensões fractais das árvores vasculares. Conclusão: A estimação das dimensões fractais da vasculatura retínica foi dependente tanto dos métodos de segmentação vascular, quanto dos métodos de cálculo de dimensão utilizados

Os efeitos das reclamações online na lealdade dos consumidores: um estudo experimental

In an environment of constant change, technological developments, market competition and more informed consumers, the search for a lasting relationship through the conquest of loyalty has become the objective of companies. However, several authors suggest that this loyalty can be affected by negative comments available on the internet. Therefore, this dissertation has as objective to examine if the complaints are available on the internet impact the loyalty to a brand of mobile phone. The research used as the basis the Expanded NCSB model suggest by Johnson et al. (2001), studying five prominent drives of loyalty: image/brand reputation, affective commitment, calculative commitment, perceived value and trust, beyond the satisfaction construct as moderator variable. The research method adopted was the experimental design which included 285 undergraduate students, with the trial which included 285 undergraduate students, with the field study of the mobile industry, specifically, the brands of cell phones. The research approach was quantitative and methods were descriptive statistics, factor analysis, cluster analysis, linear regression and non-parametric test of Wilcoxon for data analysis. Of the 16 hypothesis stemmed from the research model proposed, 12 were confirmed. The results showed that the complaint available on the internet, here represented by the available on the site Reclame Aqui, may impact consumer perceptions about brand loyalty, as well as its antecedents, being that these complaints can affect all the consumers, regardless of historical satisfaction with the brand. It also noted the positive relationship between the independent variables trust, image/brand reputation, perceived value, affective commitment and calculative commitment and the dependent variable - loyalty, even when considering the data obtained after exposure to the complaint. However, no unanimous conclusion that the relationship between these variables was strongest in the group with satisfactory experience. At the first moment of the research, the trust was the most important variable for the formation of loyalty. However, after exposure to treatment, the image/brand reputation, was more relevant. Contributions of the study, limitations and recommendations for future researches are approached in the present investigation

Fatores da qualidade e satisfação na compra pela internet e sua influência na fidelidade dos consumidores

A presente pesquisa objetivou estudar as relações entre os fatores intervenientes para a satisfação no processo de compras baseadas na Internet e sua influência na fidelidade online (e-loyalty), na visão dos consumidores de varejo virtual. Para tanto, foi utilizado como instrumento de coleta de dados um questionário baseado em fatores de qualidade e fidelidade oriundos dos serviços convencionais, que foi adaptado para a realidade dos serviços digitais. A pesquisa caracteriza-se como exploratória, de natureza quantiqualitativa. A análise quantitativa descreveu e testou a relação de variáveis de qualidade do site e de preço dos produtos do site com as variáveis de satisfação. Neste caso, foram utilizadas técnicas estatísticas como distribuição de freqüência, médias e desvio-padrão e correlação de postos de Spearman. Já na abordagem qualitativa, foi empregada a análise de conteúdo para uma questão aberta relacionada com a identificação dos fatores que levam a fidelidade digital. A pesquisa de campo foi feita com uma amostra de 44 alunos de pós-graduação em nível de Especialização da Universidade Federal do Rio Grande do Norte. Os resultados da análise quantitativa evidenciaram que a qualidade está ligada à satisfação dos clientes em vários fatores, mas o preço não influencia muito na satisfação. Na análise qualitativa, a segurança do website e os preços oferecidos são fatores que potencialmente fidelizam os clientes digitais, segundo a perspectiva dos entrevistados. O fator segurança e confiança no website foi considerado o mais crítico para a fidelidade dos clientes que compram pela Internet

Gestão da satisfação e da fidelidade de consumidores :um estudo dos fatores que afetam a satisfação e a fidelidade no mercado de turismo

The corporative strategies have been systematically changing since the middle of the 90´s by including measurement of satisfaction and loyalty of the consumers in their organization. strategies. This essay presents a study on the factors that influence on the satisfaction and loyalty of the consumers, and is based on national models of satisfaction rates. For this essay, the new Norwegian model was used. During the period of 01/06/03 until 02/14/03, a field research was developed and applied to 230 tourists visiting the city of Natal/RN

A influência do marketing ambiental na decisão de compra dos consumidores de produtos orgânicos

The search of the man for more comfort and one better quality of life led to an increment of the production of goods and services, that results, almost always, in aggressions to the nature and to a reduction of this same quality of life. The concern with the ambient problems appears as an important element regarding the material and economic growth and of the quality of life. With this scene a new question, the Ambient Marketing appears. Although the marketing concept to be well ample, the companies use the term ambient marketing to make reference what in fact, many times, are a more specific activity of ambient communication. The ambient communication is a new form to communicate used for the companies with the objective to get advantages of its competitors ahead, since the competitiveness by means of the o price, the stated period and the quality if becomes extremely incited. In view of the current competitive market, where the organizations need distinguishing to get greater have detached front to the competition, and the fact of the society to be each time more worried about the environment and the impacts that the companies cause it, the ambient communication has been used as form to convince its customers. Of this form, she evaluated herself, through a exploratory research and qualitative, the influence of the use of the ambient communication in the decision of purchase and of that she forms the companies when using of this communication can add value to its product. The results had indicated that 77% of the interviewed ones had heard to say on marketing or ambient communication and that the television is main the media for this knowledge, a time that 90.9% of the respondents had affirmed to have seen propagandas of directed products of consumption to the ambient question in this way. In fact, the concern with the environment demonstrated for the companies has its impact, therefore 84% of the respondents had told if to sensetize with this fact. However, only a lesser number of people, 70.5% answered that this concern really influences in its decision of purchase

Técnicas de computação natural para segmentação de imagens médicas

Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth

Desenvolvimento de antenas de microfita com aberturas nos patches condutores através do método da segmentação

Microstrip antennas are widely used in modern telecommunication systems. This is particularly due to the great variety of geometries and because they are easily built and integrated to other high frequency devices and circuits. This work presents a study of the properties of the microstrip antenna with an aperture impressed in the conducting patch. Besides, the analysis is performed for isotropic and anisotropic dielectric substrates. The Multiport Network Model MNM is used in combination with the Segmentation Method and the Greens function technique in the analysis of the considered microstrip antenna geometries. The numerical analysis is performed by using the boundary value problem solution, by considering separately the impedance matrix of the structure segments. The analysis for the complete structure is implemented by choosing properly the number and location of the neighboor element ports. The numerial analysis is performed for the following antenna geometries: resonant cavity, microstrip rectangular patch antenna, and microstrip rectangular patch antenna with aperture. The analysis is firstly developed for microstrip antennas on isotropic substrates, and then extended to the case of microstrip antennas on anisotropic substrates by using a Mapping Method. The experimental work is described and related to the development of several prototypes of rectangular microstrip patch antennas wtih and without rectangular apertures. A good agreement was observed between the simulated and measured results. Thereafter, a good agreement was also observed between the results of this work and those shown in literature for microstrip antennas on isotropic substrates. Furthermore, results are proposed for rectangular microstrip patch antennas wtih rectangular apertures in the conducting patch

Paralelização em GPU da segmentação vascular com extração de Centerlines por Height Ridges

The vascular segmentation is important in diagnosing vascular diseases like stroke and is hampered by noise in the image and very thin vessels that can pass unnoticed. One way to accomplish the segmentation is extracting the centerline of the vessel with height ridges, which uses the intensity as features for segmentation. This process can take from seconds to minutes, depending on the current technology employed. In order to accelerate the segmentation method proposed by Aylward [Aylward & Bullitt 2002] we have adapted it to run in parallel using CUDA architecture. The performance of the segmentation method running on GPU is compared to both the same method running on CPU and the original Aylward s method running also in CPU. The improvemente of the new method over the original one is twofold: the starting point for the segmentation process is not a single point in the blood vessel but a volume, thereby making it easier for the user to segment a region of interest, and; the overall gain method was 873 times faster running on GPU and 150 times more fast running on the CPU than the original CPU in Aylward

Segmentação Fuzzy de Texturas e Vídeos

The segmentation of an image aims to subdivide it into constituent regions or objects that have some relevant semantic content. This subdivision can also be applied to videos. However, in these cases, the objects appear in various frames that compose the videos. The task of segmenting an image becomes more complex when they are composed of objects that are defined by textural features, where the color information alone is not a good descriptor of the image. Fuzzy Segmentation is a region-growing segmentation algorithm that uses affinity functions in order to assign to each element in an image a grade of membership for each object (between 0 and 1). This work presents a modification of the Fuzzy Segmentation algorithm, for the purpose of improving the temporal and spatial complexity. The algorithm was adapted to segmenting color videos, treating them as 3D volume. In order to perform segmentation in videos, conventional color model or a hybrid model obtained by a method for choosing the best channels were used. The Fuzzy Segmentation algorithm was also applied to texture segmentation by using adaptive affinity functions defined for each object texture. Two types of affinity functions were used, one defined using the normal (or Gaussian) probability distribution and the other using the Skew Divergence. This latter, a Kullback-Leibler Divergence variation, is a measure of the difference between two probability distributions. Finally, the algorithm was tested in somes videos and also in texture mosaic images composed by images of the Brodatz album

Segmentação fuzzy de imagens e vídeos

Image segmentation is the process of subdiving an image into constituent regions or objects that have similar features. In video segmentation, more than subdividing the frames in object that have similar features, there is a consistency requirement among segmentations of successive frames of the video. Fuzzy segmentation is a region growing technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership between 0 and 1 to an object. In this work we present an application that uses a fuzzy segmentation algorithm to identify and select particles in micrographs and an extension of the algorithm to perform video segmentation. Here, we treat a video shot is treated as a three-dimensional volume with different z slices being occupied by different frames of the video shot. The volume is interactively segmented based on selected seed elements, that will determine the affinity functions based on their motion and color properties. The color information can be extracted from a specific color space or from three channels of a set of color models that are selected based on the correlation of the information from all channels. The motion information is provided into the form of dense optical flows maps. Finally, segmentation of real and synthetic videos and their application in a non-photorealistic rendering (NPR) toll are presented

Segmentação fuzzy de imagens coloridas com características texturais: uma aplicação a rochas sedimentares

Image segmentation is the process of labeling pixels on di erent objects, an important step in many image processing systems. This work proposes a clustering method for the segmentation of color digital images with textural features. This is done by reducing the dimensionality of histograms of color images and using the Skew Divergence to calculate the fuzzy a nity functions. This approach is appropriate for segmenting images that have colorful textural features such as geological, dermoscopic and other natural images, as images containing mountains, grass or forests. Furthermore, experimental results of colored texture clustering using images of aquifers' sedimentary porous rocks are presented and analyzed in terms of precision to verify its e ectiveness.

Técnica para segmentação automática de imagens microscópicas de componentes sanguíneos e classificação diferencial de leucócitos baseada em lógica fuzzy

Automatic detection of blood components is an important topic in the field of hematology. The segmentation is an important stage because it allows components to be grouped into common areas and processed separately and leukocyte differential classification enables them to be analyzed separately. With the auto-segmentation and differential classification, this work is contributing to the analysis process of blood components by providing tools that reduce the manual labor and increasing its accuracy and efficiency. Using techniques of digital image processing associated with a generic and automatic fuzzy approach, this work proposes two Fuzzy Inference Systems, defined as I and II, for autosegmentation of blood components and leukocyte differential classification, respectively, in microscopic images smears. Using the Fuzzy Inference System I, the proposed technique performs the segmentation of the image in four regions: the leukocyte’s nucleus and cytoplasm, erythrocyte and plasma area and using the Fuzzy Inference System II and the segmented leukocyte (nucleus and cytoplasm) classify them differentially in five types: basophils, eosinophils, lymphocytes, monocytes and neutrophils. Were used for testing 530 images containing microscopic samples of blood smears with different methods. The images were processed and its accuracy indices and Gold Standards were calculated and compared with the manual results and other results found at literature for the same problems. Regarding segmentation, a technique developed showed percentages of accuracy of 97.31% for leukocytes, 95.39% to erythrocytes and 95.06% for blood plasma. As for the differential classification, the percentage varied between 92.98% and 98.39% for the different leukocyte types. In addition to promoting auto-segmentation and differential classification, the proposed technique also contributes to the definition of new descriptors and the construction of an image database using various processes hematological staining

Segmentação fuzzy de objetos tridimensionais com propriedades texturais

Digital image segmentation is the process of assigning distinct labels to different objects in a digital image, and the fuzzy segmentation algorithm has been used successfully in the segmentation of images from several modalities. However, the traditional fuzzy segmentation algorithm fails to segment objects that are characterized by textures whose patterns cannot be successfully described by simple statistics computed over a very restricted area. In this paper we present an extension of the fuzzy segmentation algorithm that achieves the segmentation of textures by employing adaptive affinity functions as long as we extend the algorithm to tridimensional images. The adaptive affinity functions change the size of the area where they compute the texture descriptors, according to the characteristics of the texture being processed, while three dimensional images can be described as a finite set of two-dimensional images. The algorithm then segments the volume image with an appropriate calculation area for each texture, making it possible to produce good estimates of actual volumes of the target structures of the segmentation process. We will perform experiments with synthetic and real data in applications such as segmentation of medical imaging obtained from magnetic rosonance