The Kogut and Singh (1988) index is the most widely used construct to measure cultural distance in international business and management research. We show that this index is incorrectly specified and captures the squared cultural distance. This inaccuracy is problematic because it means that the empirical findings on the effects of cultural distance presented in different strands of international business research are likely to be misleading. We specify the correct form of the distance measure based on the Euclidean distance formula and demonstrate the implications of using the incorrectly specified Kogut and Singh (1988) index.

Cette thèse est consacrée à l'analyse de l'association de codes LDPC non-binaires (LDPC-NB) à des modulations d’ordre élevé. Cette association vise à améliorer l’efficacité spectrale pour les futurs systèmes de communication sans fil. Notre approche a consisté à tirer au maximum profit de l'association directe des symboles d’un code LDPC-NB sur un corps de Galois avec une constellation de même cardinalité. Notre première contribution concerne la diversité spatiale obtenue dans un canal de Rayleigh avec et sans effacement en faisant subir une rotation à la constellation. Nous proposons d’utiliser l'information mutuelle comme paramètre d’optimisation de l’angle de rotation, et ce pour les modulations de type « BICM » et les modulations codées. Cette étude permet de mettre en évidence les avantages de la modulation codée par rapport à la modulation BICM de l’état de l’art. Par simulation de Monte-Carlo, nous montrons que les gains de codage théoriques se retrouvent dans les systèmes pratiques. Notre deuxième contribution consiste à concevoir conjointement l'étiquetage des points de constellation et le choix des coefficients d'une équation de parité en fonction de la distance euclidienne, et non plus de la distance de Hamming. Une méthode d’optimisation est proposée. Les codes ainsi construits offrent des gains de performance de 0.2 dB et ce, sans ajout de complexité. / This thesis is devoted to the analysis of the association of non-binary LDPC codes (NB-LDPC) with high-order modulations. This association aims to improve the spectral efficiency of future wireless communication systems. Our approach tries to take maximum advantage of the straight association between NB-LDPC codes over a Galois Field with modulation constellations of the same cardinality. We first investigate the optimization of the signal space diversity technique obtained with the Rayleigh channel (with and without erasure) thanks to the rotation of the constellation. To optimize the rotation angle, the mutual information analysis is performed for both coded modulation (CM) and bit-interleaved coded modulation (BICM) schemes. The study shows the advantages of coded modulations over the state-of-the-art BCIM modulations. Using Monte Carlo simulation, we show that the theoretical gains translate into actual gains in practical systems. In the second part of the thesis, we propose to perform a joint optimization of constellation labeling and parity-check coefficient choice, based on the Euclidian distance instead of the Hamming distance. An optimization method is proposed. Using the optimized matrices, a gain of 0.2 dB in performance is obtained with no additional complexity.

Com base em exames como a videolaringoscopia, que é considerado um procedimento médico invasivo e desconfortável, diagnósticos têmsido realizados visando detectar patologias na laringe. Geralmente, esse tipo de exame é realizado somente com solicitação médica e quando alterações na fala já são marcantes, ou há sensação de dor. Nessa fase, muitas vezes a doença está em grau avançado, dificultando o seu tratamento. Com o objetivo de realizar um pré-diagnóstico computacional de tais patologias, este trabalho apresenta uma técnica não invasiva na qual são testados e comparados três classificadores: a Distância Euclidiana, a Rede Neural RBF com o kernel Gaussiano e a Rede Neural RBF com o kernel Gaussiano modificado. Testes realizados com uma base de dados de vozes normais e aquelas afetadas por diversas patologias demonstram a eficácia da técnica proposta, que pode, inclusive, ser implementada em tempo-real. / Based on examinations such as laryngoscopy, which is considered an invasive and uncomfortable procedure, diagnosis have been performed aiming at the detection of larynx pathologies. Usually, this type of test is carried out upon medical request and when the speech changes are notable or are causing pain. At this point, the disease is possibly at an advanced degree, complicating its treatment. In order to perform a computational pre-diagnosis of such conditions, this work proposes a noninvasive technique in which three classifiers are tested and compared: the Euclidean distance, the RBF Neural Network with the Gaussian kernel and RBF Neural Network with a modified Gaussian kernel. Tests carried out with a database of normal voices and those affected by various pathologies demonstrate the effectiveness of the technique that may even be implemented to work in real time.

Com base em exames como a videolaringoscopia, que é considerado um procedimento médico invasivo e desconfortável, diagnósticos têmsido realizados visando detectar patologias na laringe. Geralmente, esse tipo de exame é realizado somente com solicitação médica e quando alterações na fala já são marcantes, ou há sensação de dor. Nessa fase, muitas vezes a doença está em grau avançado, dificultando o seu tratamento. Com o objetivo de realizar um pré-diagnóstico computacional de tais patologias, este trabalho apresenta uma técnica não invasiva na qual são testados e comparados três classificadores: a Distância Euclidiana, a Rede Neural RBF com o kernel Gaussiano e a Rede Neural RBF com o kernel Gaussiano modificado. Testes realizados com uma base de dados de vozes normais e aquelas afetadas por diversas patologias demonstram a eficácia da técnica proposta, que pode, inclusive, ser implementada em tempo-real. / Based on examinations such as laryngoscopy, which is considered an invasive and uncomfortable procedure, diagnosis have been performed aiming at the detection of larynx pathologies. Usually, this type of test is carried out upon medical request and when the speech changes are notable or are causing pain. At this point, the disease is possibly at an advanced degree, complicating its treatment. In order to perform a computational pre-diagnosis of such conditions, this work proposes a noninvasive technique in which three classifiers are tested and compared: the Euclidean distance, the RBF Neural Network with the Gaussian kernel and RBF Neural Network with a modified Gaussian kernel. Tests carried out with a database of normal voices and those affected by various pathologies demonstrate the effectiveness of the technique that may even be implemented to work in real time.

The sexual exploitation of children remains a very serious problem and is rapidly increasing globally through the use of the Internet. This work focuses on the current methods employed by criminals to generate and distribute child pornography, the methods used by law enforcement agencies to deter them, and the drawbacks of currently used methods, as well as the surrounding legal and privacy issues. A proven method to detect the transmission of illicit images at the network layer is presented within this paper. With this research, it is now possible to actively filter illicit pornographic images as they are transmitted over the network layer in real-time. It is shown that a Stochastic Learning Weak Estimator learning algorithm and a Maximum Likelihood Estimator learning algorithm can be applied against Linear Classifiers to identify and filter illicit pornographic images. In this thesis, these two learning algorithms were combined with algorithms such as the Non-negative Vector Similarity Coefficient-based Distance algorithm, Euclidian Distance, and Weighted Euclidian Distance. Based upon this research, a prototype was developed using the abovementioned system, capable of performing classification on both compressed and uncompressed images. Experimental results showed that classification accuracies and the overhead of network-based approaches did have a significant effect on routing devices. All images used in our experiments were legal. No actual child pornography images were ever collected, seen, sought, or used.

This master’s thesis is engaged in usage of cluster analysis for ECG signal to separate normal QRS complexes from abnormal ones. For this, it is used two algorithms created in professional computing interface MATLAB. The outputs from this master’s thesis are dendrograms, which divide QRS complexes into abnormal and normal clusters, and Pearson correlation coefficients.