Sveriges riksdag har beslutat att de nationella nettoutsläppen av växthusgaser år 2045 ska varanoll samt reduceras med 70 % till år 2030. Vägfordon som transporterar gods stod år 2017 förungefär 30 % av transportsektorns totala nationella utsläpp. Syftet med studien är att belysahur en omställning från fossila till fossilfria godstransporter på land kan ske i Sverige till år2045 samtidigt som näringslivets behov av godstransporter tillgodoses. Angreppssättet är attgenom backcasting formulera två framtidsscenarier - scenario A innebär stor satsning på järnväg,scenario B innebär stor satsning på elväg - för att påvisa vilka åtgärder som krävs samt när ochgenom Multi-Level Perspective (MLP) analysera hur de två transportslagen kan utvecklas tillden dominanta regimen i respektive framtidsbild. Studien visade att utsläppsreduktionen går snabbare i scenario B vilket då innebär lägreackumulerade utsläpp samt att den monetära kostnaden för scenario A är dubbelt så stor somkostnaden för scenario B. Ett antal hinder, barriärer och möjligheter identifierades och analyseradesför de båda scenarierna. De aktörer som identifierades var politiska och lagstiftandeinstanser, transportköpare, transportörer, aktörer inom forskning och teknikutveckling, intresseochpåverkansorganisationer, konstruktions- och underhållsentreprenörer samt drivmedelsproducenteroch distributörer. De två förstnämnda bedömdes ha störst inflytande. För elvägar måstenischaktörerna lyckas skapa tillräckligt med intresse för att öka momentumet och ta elvägartill regimnivån. För järnvägen måste aktörerna får upp momentumet inom regimen med interninnovation för att kunna konkurrera med vägtransporter. Sammanfattningsvis visar studien på att en implementering av elväg kan vara bättre påkort sikt och järnväg bättre på längre sikt. Klimatmålet om netto-nollutsläpp till år 2045 kannås samtidigt som näringslivets behov av godstransporter tillgodoses, men konstruktionen avinfrastruktur måste påbörjas snart för att överflyttningen och omställningen ska hinna ske. Föratt nå 2030-målet verkar en ökad inblandning av biodrivmedel i vägfordon utgöra den störstamöjligheten, dock måste de sedan fasas ut för att ersättas av järnväg och elväg. / The Swedish Parliament has decided that the national net emissions of greenhouse gases by 2045should be zero and reduced by 70 % by 2030. In 2017, road freight vehicles were responsible forabout 30 % of the transport sector’s total national emissions. The purpose of the study is tohighlight how a transition from fossil to fossil-free freight transport on land can happen in Swedenuntil 2045, whilst meeting the country’s need for freight transport. The approach is to formulate,through backcasting, two possible scenarios of the future where the targets are met - scenario Ainvolves a large investment in railways, scenario B involves a large investment in electric roadsystems (ERS) - to demonstrate what measures are required and when, and through Multi-LevelPerspective (MLP) analyse how the two modes of transport can be developed into the dominantregime in each scenario. The study showed that the reduction rate of emissions is faster in scenario B, which thenmeans lesser accumulated emissions and that the monetary cost for scenario A is twice as highas the cost for scenario B. Also, a number of obstacles, barriers and opportunities were identifiedand analysed for the two scenarios. The actors that were assessed to possess the greatest influencewere political and legislative actors, and transport buyers. Regarding ERS, niche actors mustsucceed in creating enough interest to increase momentum and take ERS to the regime level.Regarding railway, the actors must increase the momentum within the regime with internalinnovation to be able to compete with road freight transport. In conclusion, the study shows that an implementation of ERS can be favourable in the shortterm and rail freight better in the longer term. The climate target of net zero emissions by 2045can be reached whilst the country’s need for freight transport is met, but the construction ofinfrastructure must begin as soon as possible for the transfer of goods and transformation ofthe system to take place. Moreover, the study argues that in order to reach the 2030 target,an increased use of biofuels in road vehicles seems to be the most promising solution. However,biofuels must then be phased out in order to be replaced by railway and ERS.

För onlinespel är fuskande spelare ett problem som påverkar både övriga spelare och spelföretagen. Det är därför intressant att ta fram en metod som upptäcker fusk. Detta arbete fokuserar på att upptäcka aimbotfusk inom CS:GO med hjälp av artificiellt neuralt nätverk. Arbetet jämför hur väl ett så kallat MLP kan detektera fusk då informationen representeras i tidsserier eller som frekvensdata. Olika konfigurationer jämförs i syfte att hitta bästa möjliga kombinationen för ett MLP. Resultaten visar att frekvensdata är ett mycket bra sätt att upptäcka aimbotfusk. Förhoppningen är att metoden kan utvecklas för att användas även för att upptäcka andra typer av fusk i onlinespel. / <p>Det finns övrigt digitalt material (t.ex. film-, bild- eller ljudfiler) eller modeller/artefakter tillhörande examensarbetet som ska skickas till arkivet.</p>

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A dor neuropática atinge cerca de 6 a 10% da população global e estima-se o seu aumento nos próximos anos. Essa síndrome não tem cura e afeta consideravelmente a qualidade de vida das pessoas por ela acometidas. Os medicamentos utilizados atualmente para o seu tratamento, como antidepressivos, anticonvulsivantes, opióides, dentre outros, não proporcionam um resultado satisfatório pelo fato de não reduzirem consideravelmente os sintomas e/ou por terem muitos efeitos colaterais. Pesquisas recentes mostram que o receptor sigma-1 pode ser utilizado no tratamento da dor neuropática. Verificou-se na literatura uma nova série de pirimidinas que são capazes de se ligar ao receptor sigma-1, atuando como seus antagonistas, sendo potenciais alvos para a produção de fármacos que podem ser utilizados no tratamento da dor neuropática. Então, estudos de Relações Quantitativas Estrutura-Atividade (QSAR) foram realizados utilizando os métodos de Mínimos Quadrados Parciais (PLS) e Redes Neurais Artificiais (ANN) para prever a atividade biológica dessa série de pirimidinas. Os resultados obtidos se mostraram satisfatórios tanto para o método de PLS (r2 = 0,877, q2 = 0,800 e r2teste = 0,738), quanto para o método de ANN (r2trein = 0,734, r2val = 0,753 e r2teste = 0,676), mostrando que o conjunto de compostos antagonistas do receptor Sigma-1 pode ser descrito tanto de forma linear quanto de forma não-linear. / Neuropathic pain affects about 6 to 10% of the global population and it is estimated to increase in the coming years. This syndrome has no cure and considerably affects the life quality of people affected by it. Medications currently used for its treatment, such as antidepressants, anticonvulsants, opioids, among others, do not provide a satisfactory result because they do not significantly reduce the symptoms and/or have many side effects. Recent research shows that the sigma-1 receptor can be used in the treatment of the neuropathic pain. A new series of pyrimidines have been found in the literature, which are capable of binding to the sigma-1 receptor, acting as its antagonists, and have been synthesized as potential targets that can be used in the treatment of the neuropathic pain. Therefore, Quantitative Structure-Activity Relationships (QSAR) were performed using Partial Least Squares (PLS) and Artificial Neural Networks (ANN) methods to predict the biological activity of this series of pyrimidines. Through the mathematical models obtained by PLS (r2 = 0.877, q2 = 0.800 and r2test = 0.738) and ANN (r2trein = 0.734, r2val = 0.753 and r2test = 0.676) methods, it was showed that they were able to predict the biological activity of the studied pyrimidines.

A dor neuropática atinge cerca de 6 a 10% da população global e estima-se o seu aumento nos próximos anos. Essa síndrome não tem cura e afeta consideravelmente a qualidade de vida das pessoas por ela acometidas. Os medicamentos utilizados atualmente para o seu tratamento, como antidepressivos, anticonvulsivantes, opióides, dentre outros, não proporcionam um resultado satisfatório pelo fato de não reduzirem consideravelmente os sintomas e/ou por terem muitos efeitos colaterais. Pesquisas recentes mostram que o receptor sigma-1 pode ser utilizado no tratamento da dor neuropática. Verificou-se na literatura uma nova série de pirimidinas que são capazes de se ligar ao receptor sigma-1, atuando como seus antagonistas, sendo potenciais alvos para a produção de fármacos que podem ser utilizados no tratamento da dor neuropática. Então, estudos de Relações Quantitativas Estrutura-Atividade (QSAR) foram realizados utilizando os métodos de Mínimos Quadrados Parciais (PLS) e Redes Neurais Artificiais (ANN) para prever a atividade biológica dessa série de pirimidinas. Os resultados obtidos se mostraram satisfatórios tanto para o método de PLS (r2 = 0,877, q2 = 0,800 e r2teste = 0,738), quanto para o método de ANN (r2trein = 0,734, r2val = 0,753 e r2teste = 0,676), mostrando que o conjunto de compostos antagonistas do receptor Sigma-1 pode ser descrito tanto de forma linear quanto de forma não-linear. / Neuropathic pain affects about 6 to 10% of the global population and it is estimated to increase in the coming years. This syndrome has no cure and considerably affects the life quality of people affected by it. Medications currently used for its treatment, such as antidepressants, anticonvulsants, opioids, among others, do not provide a satisfactory result because they do not significantly reduce the symptoms and/or have many side effects. Recent research shows that the sigma-1 receptor can be used in the treatment of the neuropathic pain. A new series of pyrimidines have been found in the literature, which are capable of binding to the sigma-1 receptor, acting as its antagonists, and have been synthesized as potential targets that can be used in the treatment of the neuropathic pain. Therefore, Quantitative Structure-Activity Relationships (QSAR) were performed using Partial Least Squares (PLS) and Artificial Neural Networks (ANN) methods to predict the biological activity of this series of pyrimidines. Through the mathematical models obtained by PLS (r2 = 0.877, q2 = 0.800 and r2test = 0.738) and ANN (r2trein = 0.734, r2val = 0.753 and r2test = 0.676) methods, it was showed that they were able to predict the biological activity of the studied pyrimidines.

Chez les trypanosomatidés, on observe un double cycle cellulaire : karyokinèse et cytodiérèse sont synchronisées mais indépendantes. La membrane nucléaire persiste au cours de la mitose dite fermée. Les modalités de réplication de l'ADN et de sa régulation, de même que plusieurs étapes de la ségrégation des chromosomes, restent non élucidées : le kinétochore est composé de protéines très atypiques (KKTs), et il existe un déficit du nombre de kinétochores par rapport au nombre de chromosomes. D'autre part, la constitution des pôles du fuseau mitotique associés à la membrane nucléaire est totalement inconnue. Les nucléoporines sont des protéines conservées au cours de l'évolution, principalement impliquées dans la constitution des pores nucléaires et le trafic entre le noyau et le cytoplasme, mais également de plus en plus considérées comme des acteurs importants de la dynamique chromatinienne. En utilisant des vecteurs d'expression protéique sous forme fusionnée à la GFP, nous avons déterminé la localisation subcellulaire de 15 nucléoporines chez Leishmania major. Si la plupart de ces nucléoporines se localisent à la membrane nucléaire, plusieurs d'entre elles ont des localisations secondaires qui peuvent être prédominantes. Ainsi la nucléoporine Mlp2 est préférentiellement localisée au niveau du kinétochore et, en fin de mitose, à l'extrémité du fuseau mitotique chez les deux parasites Leishmania major et Trypanosoma brucei. En accord avec la localisation de TbMlp2 au kinétochore chez T. brucei, où les centromères sont identifiés, nous avons fréquemment détecté TbMlp2 à proximité des séquences centromériques, elles-mêmes détectées par FISH en périphérie du nucléole. Egalement grâce à la technique de FISH, nous montrons que l'inhibition de l'expression de TbMlp2 par ARN-interférence perturbe la distribution des chromosomes au cours de la mitose, conduisant à une aneuploïdie. Paradoxalement, cette inhibition n'a aucun effet sur la croissance des cellules. Nous présentons également le cas singulier de Mlp1, dont la localisation chez T. brucei dépend du site d'intégration choisi. Cette localisation sera discutée à la lumière des phénotypes observés lors de l'inhibition de son expression. / Trypanosomatid parasites exhibit two independent though coordinated (nuclear and mitochondrial) cell cycles, and a closed mitosis, of which many constituents and processes are unknown. In particular, most steps of the chromosome segregation remain elusive: the kinetochore is composed of atypical proteins called KKT and the number of kinetochores is deficient in relation to the number of chromosomes. Moreover, the constitution of the nuclear membrane-associated mitotic spindle poles is unknown. Nucleoporins are evolutionary conserved proteins mainly involved in the constitution of the nuclear pores and trafficking between the nucleus and cytoplasm, but are also increasingly viewed as main actors in chromatin dynamics. Using GFP-fused proteins, we determined the cellular localization of the 15 nucleoporins in Leishmania major. If most of these nucleoporins localized at the nuclear membrane, some of them exhibited secondary locations which are predominant in a few cases. Thus, the nucleoporin Mlp2 localized preferentially at the kinetochore and, at the end of mitosis, at the mitotic spindle poles in both parasites Leishmania major and Trypanosoma brucei. Consistent with the localisation of TbMlp2 to the kinetochore in T. brucei, where centromeres are identified, TbMlp2 was frequently detected in the vicinity of the centromeric sequences in the periphery of the nucleolus. The use of FISH allowed us to show that RNAi knockdowns of TbMlp2 disturbed the distribution of chromosomes during mitosis, leading to aneuploidy. Paradoxically RNAi knockdowns of TbMlp2 had no effect on cell growth. We will also present the singular case of Mlp1 whose location is dependent on the integration site in T. brucei. This location will be discussed in the light of the phenotypes observed after inhibition of its expression.

Understanding the future of a Large Technical System (LTS) through a sociotechnical analysis is a complex notion. The authors will investigate the phenomenon by studying residential water consumption in Sweden. Although Sweden has great access to raw water, compared to many other countries, it does not justify the fact that consumption patterns have to be unsustainable. To perceive the future, one will need to have knowledge of history. Therefore, this thesis has identified 11 drivers that will affect future residential water consumption. From these 11 drivers, the authors have posed four future scenarios for residential water consumption. The top 3 identified drivers are connected to behaviour and awareness. Thus, implying individuals' responsibility and accountability will be of greater significance for the sustainable development of residential water consumption. For this research, the authors have adopted a framework based on the application of LTS, Multi-Level Perspective (MLP), Scenario building, PESTLE, and Multi-Criteria Analysis (MCA). The authors have conducted a qualitative study, gathering data through a literature study and semi-structured interviews. The 18 interviewees covered a broad spectrum of knowledge, experiences, and general interest in water. By understanding the dynamics of the system and drivers, the authors will be able to present the gathered knowledge to stakeholders for possible strategic decisions. / Att förstå framtiden för ett stort tekniskt system (LTS) genom en socioteknisk analys innebär stor komplexitet. Detta kommer att undersökas genom att studera hushållens vattenförbrukning i Sverige. Även om Sverige har stor tillgång till råvatten, jämfört med många andra länder, berättigar det inte förekommandet av ohållbara konsumtionsmönster. För att öka förståelsen av framtiden måste en ha kunskap om historien. Därför har denna avhandling identifierat 11 drivkrafter som kommer att påverka den framtida hushållens vattenförbrukning. Från dessa 11 drivkrafter har författarna formulerat fyra framtida scenarier för hushållens vattenförbrukning. De tre högst rankade identifierade drivkrafterna är kopplade till beteende och medvetenhet. Detta antyder på att individens enskilda ansvar och skyldigheter är av större betydelse för en hållbar utveckling av hushållens vattenförbrukning. För denna forskning har författarna använt sig av ett teoretiskt ramverk som bygger på tillämpningen av LTS, Multi-Level Perspective (MLP), Scenario building, PESTLE and Multi-Criteria Analysis (MCA). Författarna har genomfört en kvalitativ studie, där insamling av data härstammar från den genomförda litteraturstudien och 18 semi-strukturerade intervjuer. De 18 intervjukandidaterna täckte ett brett spektrum av kunskap, erfarenhet och intresse av vatten. Genom att skapa ett samband och förstå dynamiken i systemet och drivkrafterna, kommer författarna att kunna presentera den samlade kunskapen till intressenter för eventuella strategiska beslut.

Cette étude traite de l’identification de système dynamique non-linéaire. Une architecture multimodèle capable de surmonter certaines difficultés de l’architecture neuronale de type MLP a été étudiée. L’approche multimodèle consiste à représenter un système complexe par un ensemble de modèles de structures simples à validité limitée dans des zones bien définies. A la place de la structure affine des modèles locaux généralement utilisée, cette étude propose une structure polynômiale plus générale, capable de mieux appréhender les non-linéarités locales, réduisant ainsi le nombre de modèles locaux. L’estimation paramétrique d’une telle architecture multimodèle peut se faire suivant une optimisation linéaire, moins coûteuse en temps de calcul que l’estimation paramétrique utilisée dans une architecture neuronale. L’implantation des multimodèles récurrents, avec un algorithme d’estimation paramétrique plus souple que l’algorithme de rétro-propagation du gradient à travers le temps utilisé pour le MLP récurrent a également été effectuée. Cette architecture multimodèle permet de représenter plus facilement des modèles non-linéaires bouclés tels que les modèles NARMAX et NOE. La détermination du nombre de modèles locaux dans une architecture multimodèle nécessite la décomposition (le partitionnement) de l’espace de fonctionnement du système en plusieurs sous-espaces où sont définies les modèles locaux. Des modes de partitionnement flou (basé sur les algorithmes de« fuzzy-c-means », de « Gustafson et Kessel » et du « subtractive clustering ») ont été présentés. L’utilisation de telles méthodes nécessite l’implantation d’une architecture multimodèle où les modèles locaux peuvent être de structures différentes : polynômiales de degrés différents, neuronale ou polynômiale et neuronale. Une architecture multimodèle hétérogène répondant à ses exigences a été proposée, des algorithmes d’identification structurelles et paramétriques ont été présentés. Une étude comparative entre les architectures MLP et multimodèle a été menée. Le principal atout de l’architecture multimodèle par rapport à l’architecture neuronale de type MLP est la simplicité de l’estimation paramétrique. Par ailleurs, l’utilisation dans une architecture multimodèle d’un mode de partitionnement basé sur la classification floue permet de déterminer facilement le nombre de modèles locaux, alors que la détermination du nombre de neurones cachés pour une architecture MLP reste une tâche difficile / This work deals with non linear dynamical system identification. A multiple model architecture which overcomes certain insufficiencies of MLP neural networks is studied. Multiple model approach consists of modeling complex systems by mean of a set of simple local models whose validity are limited in well defined zones. Instead of using conventional affine models, a more general polynomial structure is proposed in this study, enabling to better apprehend local non linearities, reducing thus the number of local models. Models parameters of such a structure are estimated by linear optimization, which reduces computation time with respect to parameter estimation of a neural network architecture. The implementation of recurrent multiple models, with a more convenient learning algorithm than the back propagation through time, used in recurrent MLP models, is also studied. Such implementations facilitate representation of recurrent models like NARMAX and NOE. The determination of the number of local models in a multiple model architecture requires decomposition of system’s feature space into several sub-systems in which local models are defined. Fuzzy partitioning methods (based of « fuzzy-c-means », « Gustafson and Kessel » and « subtractive clustering »algorithms) are presented. The use of such methods requires the implementation of a multiple model architecture where local models can have different structures : polynomial with different degrees, neural or polynomial and neural. A multiple model with a heterogeneous architecture satisfying these requirements is proposed and structural and parametrical identification algorithms are presented. A comparative study between multiple model and MLP architectures is done. The main advantage of the multiple model architecture is the parameter estimation simplicity. In addition, the use of fuzzy partitioning methods in multiple model architecture enables to find easily the number of local models while the determination of hidden neurons in an MLP architecture remains a hard task

Made available in DSpace on 2016-08-10T10:40:42Z (GMT). No. of bitstreams: 1 RAFAEL GOMES LOIOLA.pdf: 2193685 bytes, checksum: 77fe8f4c3a881108732f58c6013d52b5 (MD5) Previous issue date: 2016-03-09 / The demand forecasting is of essential importance for business environments, in a way to serve as a decision making supporting tool during the development of companies strategic planning. This work strived to compare statistics with artificial intelligence methods applied to provisioning on demand issues using temporal series through Box-Jenkins and Artificial Neural Networks Multilayer Perceptron (MLP) methods. Studies were performed to identify and define the main demand forecasting methods. Subsequently, the selected prediction methods for the analysis of the three most relevant products of a metalworking industry were applied in the period 2012 to 2014. The four last periods were used only for performance validation of both methods, through the analysis of forecast errors. Softwares R, Matlab and SPSS supported the data deployment, modeling and analysis. From those models, a step ahead provisioning of sales of a metal mechanic industry was performed, followed by the comparison of the errors of each method based on root mean squared error, RMSE, and mean absolute percentage error, MAPE, to identify the most satisfactory and adequate provisioning method. The results indicated that the performance of the forecasts using the statistical method of Box-Jenkins in Products 1 and 3 were higher than the application of the MLP neural network models. While, for Product 2 the method of neural networks achieved better results. In the statistics analysis, one could verify that the series present some behavior patterns associated to seasonality and oscillations, being possible to observe that both methods show satisfactory results for each data characteristics of the temporal series. / A previsão de demanda é de essencial importância em ambientes organizacionais, de forma a servir como ferramenta de apoio a tomada de decisão durante o desenvolvimento do planejamento estratégico das empresas. Este trabalho teve como principal objetivo comparar modelos estatísticos e de inteligência artificial para problemas de previsão de demanda utilizando séries temporais por meio dos métodos de Box-Jenkins e rede neural artificial Multilayer Perceptron (MLP). Realizou-se o estudo para identificação e definição dos principais métodos de previsão de demanda. Posteriormente, aplicaram-se os métodos de previsão selecionados para a análise dos três produtos mais relevantes de uma indústria metal mecânica, no período de 2012 até 2014. Os quatro últimos períodos da série foram utilizados apenas para validação de desempenho de ambos os métodos propostos através das análises dos erros de previsão. Os softwares R, Matlab e SPSS apoiaram a aplicação, modelagem e análise dos dados. A partir dos modelos, realizou-se a previsão um passo a frente das vendas de uma indústria metal mecânica e posteriormente fez-se o comparativo de seus resultados através das medidas de erros referentes à raiz quadrada do erro quadrático médio, RMSE, e o erro percentual absoluto médio, MAPE, para identificar o modelo mais satisfatório e adequado para a predição. Os resultados indicaram que o desempenho das previsões utilizando o método estatístico de Box-Jenkins nos Produtos 1 e 3 foram superiores à aplicação dos modelos de rede neural MLP. Enquanto que para o Produto 2, o método de redes neurais alcançou melhores resultados. Nas análises estatísticas verificou-se que as séries apresentam padrões de comportamento referente à sazonalidade e oscilações, sendo possível observar que ambos os métodos apresentam resultados satisfatórios para cada característica de dados das séries temporais estudadas.

A tarefa de encontrar faces em imagens é extremamente complexa, pois pode ocorrer variação de luminosidade, fundos extremamente complexos e objetos que podem se sobrepor parcialmente à face que será localizada, entre outros problemas. Com o avanço na área de visão computacional técnicas mais recentes de processamento de imagens e inteligência artificial têm sido combinadas para desenvolver algoritmos mais eficientes para a tarefa de detecção de faces. Este trabalho apresenta uma metodologia de visão computacional que utiliza redes neurais MLP (Perceptron Multicamadas) para segmentar a cor da pele e a textura da face, de outros objetos presentes em uma imagem de fundo complexo. A imagem resultante é dividida em regiões, e para cada região são extraídas características que são aplicadas em outra rede neural MLP para identificar se naquela região contem face ou não. Para avaliação do software implementado foram utilizados dois banco de imagens, um com imagens padronizadas (Banco AR) e outro banco com imagens adquiridas na Internet contendo faces com diferentes tons de pele e fundo complexo. Os resultados finais obtidos foram de 83% de faces detectadas para o banco de imagens da Internet e 88% para o Banco AR, evidenciando melhores resultados para as imagens deste banco, pelo fato de serem padronizadas, não conterem faces inclinadas e fundo complexo. A etapa de segmentação apesar de reduzir a quantidade de informação a ser processada para os demais módulos foi a que contribuiu para o maior número de falsos negativos. / The task of finding faces in images is extremely complex, as there is variation in brightness, backgrounds and highly complex objects that may overlap partially in the face to be found, among other problems. With the advancement in the field of computer vision techniques latest image processing and artificial intelligence have been combined to develop more efficient algorithms for the task of face detection. This work presents a methodology for computer vision using neural networks MLP (Multilayer Perceptron) to segment the skin color and texture of the face, from other objects present in a complex background image. The resulting image is divided into regions and from each region are extracted features that are applied in other MLP neural network to identify whether this region contains the face or not. To evaluate the software two sets of images were used, images with a standard database (AR) and another database with images acquired from the Internet, containing faces with different skin tones and complex background. The final results were 83% of faces detected in the internet database of images and 88% for the database AR. These better results for the database AR is due to the fact that they are standardized, are not rotated and do not contain complex background. The segmentation step, despite reducing the amount of information being processed for the other modules contributed to the higher number of false negatives.