This paper describes basic methods used for optical character recognition. It explains all procedures of recognition from adjustment of picture, processing, feature extracting to matching algorithms. It compares methods and algorithms for character recognition obtained graphically distorted or else modified image so-called „captcha“, used in present. Further it compares method based on invariant moments and neural network as final classifier and method based on correlation between normals and recognized characters.

There are a number of factors that influence crop yield, two of which are soil moisture and fertility.

Ao se realizar estudo em qualquer área do conhecimento, quanto mais dados se dispuser, maior a dificuldade de se extrair conhecimento útil deste banco de dados. A finalidade deste trabalho é apresentar algumas ferramentas ditas inteligentes, de extração de conhecimento destes grandes repositórios de dados. Apesar de ter várias conotações, neste trabalho, irá se entender extração de conhecimento dos repositórios de dados a ocorrência combinada de alguns dados com freqüência e confiabilidade que se consideram interessantes, ou seja, na medida e que determinado dado ou conjunto de dados aparece no repositório de dados, em freqüência considerada razoável, outro dado ou conjunto de dados irá aparecer. Executada sobre repositórios de dados referentes a informações georreferenciadas dos alunos da UERJ (Universidade do Estado do Rio de Janeiro), irá se analisar os resultados de duas ferramentas de extração de dados, bem como apresentar possibilidades de otimização computacional destas ferramentas. / Comparative Study of Techniques for Extracting knowledge from large data repositories. When conducting the study in any field of knowledge, the more data is available, the greater the difficulty in extracting useful knowledge from this database. The purpose of this paper is to present some tools called intelligent, knowledge extraction of these large data repositories. Although many connotations, this work will understand knowledge extraction from data repositories on the combined occurrence of some data with frequency and reliability that are considered interesting, ie, the extent and specific data or data set appears in the data, at a rate deemed reasonable, other data or data set will appear. Runs on repositories of data on georeferenced data of students UERJ (Universidade do Estado do Rio de Janeiro), will analyze the results of two tools to extract data and present opportunities for optimization of these computational tools.

Ao se realizar estudo em qualquer área do conhecimento, quanto mais dados se dispuser, maior a dificuldade de se extrair conhecimento útil deste banco de dados. A finalidade deste trabalho é apresentar algumas ferramentas ditas inteligentes, de extração de conhecimento destes grandes repositórios de dados. Apesar de ter várias conotações, neste trabalho, irá se entender extração de conhecimento dos repositórios de dados a ocorrência combinada de alguns dados com freqüência e confiabilidade que se consideram interessantes, ou seja, na medida e que determinado dado ou conjunto de dados aparece no repositório de dados, em freqüência considerada razoável, outro dado ou conjunto de dados irá aparecer. Executada sobre repositórios de dados referentes a informações georreferenciadas dos alunos da UERJ (Universidade do Estado do Rio de Janeiro), irá se analisar os resultados de duas ferramentas de extração de dados, bem como apresentar possibilidades de otimização computacional destas ferramentas. / Comparative Study of Techniques for Extracting knowledge from large data repositories. When conducting the study in any field of knowledge, the more data is available, the greater the difficulty in extracting useful knowledge from this database. The purpose of this paper is to present some tools called intelligent, knowledge extraction of these large data repositories. Although many connotations, this work will understand knowledge extraction from data repositories on the combined occurrence of some data with frequency and reliability that are considered interesting, ie, the extent and specific data or data set appears in the data, at a rate deemed reasonable, other data or data set will appear. Runs on repositories of data on georeferenced data of students UERJ (Universidade do Estado do Rio de Janeiro), will analyze the results of two tools to extract data and present opportunities for optimization of these computational tools.

Submitted by Henry Silva Vieira (henry@icomp.ufam.edu.br) on 2018-10-15T15:55:24Z No. of bitstreams: 3 tese-henry-vieira.pdf: 1191114 bytes, checksum: b10400a0fae82d5f844e9bb1c5ec4519 (MD5) folha-de-aprovacao.pdf: 315239 bytes, checksum: b497a7ed9186152c12bd92a9cc4c206e (MD5) ata-de-defesa.pdf: 482952 bytes, checksum: 62340b99b961e7b1d17cdbf1ae2621a2 (MD5) / Approved for entry into archive by Secretaria PPGI (secretariappgi@icomp.ufam.edu.br) on 2018-10-15T18:52:47Z (GMT) No. of bitstreams: 3 tese-henry-vieira.pdf: 1191114 bytes, checksum: b10400a0fae82d5f844e9bb1c5ec4519 (MD5) folha-de-aprovacao.pdf: 315239 bytes, checksum: b497a7ed9186152c12bd92a9cc4c206e (MD5) ata-de-defesa.pdf: 482952 bytes, checksum: 62340b99b961e7b1d17cdbf1ae2621a2 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-10-16T17:41:31Z (GMT) No. of bitstreams: 3 tese-henry-vieira.pdf: 1191114 bytes, checksum: b10400a0fae82d5f844e9bb1c5ec4519 (MD5) folha-de-aprovacao.pdf: 315239 bytes, checksum: b497a7ed9186152c12bd92a9cc4c206e (MD5) ata-de-defesa.pdf: 482952 bytes, checksum: 62340b99b961e7b1d17cdbf1ae2621a2 (MD5) / Made available in DSpace on 2018-10-16T17:41:31Z (GMT). No. of bitstreams: 3 tese-henry-vieira.pdf: 1191114 bytes, checksum: b10400a0fae82d5f844e9bb1c5ec4519 (MD5) folha-de-aprovacao.pdf: 315239 bytes, checksum: b497a7ed9186152c12bd92a9cc4c206e (MD5) ata-de-defesa.pdf: 482952 bytes, checksum: 62340b99b961e7b1d17cdbf1ae2621a2 (MD5) Previous issue date: 2018-09-25 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / FAPEAM - Fundação de Amparo à Pesquisa do Estado do Amazonas / A mídia social online tornou-se uma parte essencial de nossa vida diária. Por meio dessas mídias, os usuários trocam informações que geram usando diversos mecanismos de comunicação. Nesse contexto, mais e mais usuários transmitem e confiam em informações publicadas por outros usuários sobre uma grande variedade de tópicos, incluindo opiniões e informações sobre produtos. A extração e o processamento automáticos de informações geradas pelo usuário nas mídias sociais podem fornecer informações e conhecimento relevantes para uma variedade de aplicativos interessantes. Em particular, uma das técnicas de análise de conteúdo mais aplicadas às mídias sociais é a de mineração de opinião. Uma das tarefas básicas associadas à mineração de opinião é extrair e categorizar as entidades de destino, ou seja, identificar as menções de entidade no texto e vincular essas menções de entidade a entidades do mundo real sobre as quais as opiniões são feitas. Em nosso trabalho, nos concentramos em entidades-alvo de um tipo específico e atualmente relevante: produtos eletrônicos de consumo. Tais produtos são o principal assunto de opiniões postadas pelos usuários em várias postagens em fóruns de discussão e sites de varejo na Web. Neste trabalho, estamos interessados ​​em usar o conteúdo textual não estruturado gerado por usuários de mídia social para permitir continuamente enriquecer o conhecimento sobre produtos representados em catálogos de produtos. Portanto, a tarefa que abordamos aqui é como reconhecer e vincular menções a produtos em conteúdo textual gerado pelo usuário para o produto, de um catálogo, ao qual eles se referem. Afirmamos que duas sub-tarefas básicas surgem: primeiro, a extração de entidades alvo mencionada em conteúdo textual não-estruturado; segundo, a desambiguação de entidades extraídas, isto é, ligação menções extraídas à sua contraparte do mundo real. Neste trabalho, desenvolvemos métodos para abordar essas duas subtarefas. Esta tese detalha essas tarefas, discute nossas ideias para os métodos que desenvolvemos e apresenta nossas contribuições e resultados para esse objetivo. / Online social media has grown into an essential part of our daily life. Through these media, users exchange information that they generate by using many different communication mechanisms. In this context, more and more users pass on and trust information published by other users on a large variety of topics, including opinion and information about products. Automatically extracting and processing user-generated information in social media can provide relevant information and knowledge to a variety of interesting applications. In particular, one of the content analysis techniques most often applied to social media is that of opinion mining. One of the basic tasks associated with opinion mining is extracting and categorizing target entities, i.e., identifying entity mentions in text, and linking these entity mentions to unique real world entities about which the opinions are made. In our work, we focus on target entities of a specific, and currently relevant, type: consumer electronic products. Such products are the main subject of opinions posted by users on a number of posts in discussion forums and retail sites over the Web. In this work, we are interested in using the unstructured textual content generated by social media users to continuously allow enriching the knowledge about products represented in product catalogs. Therefore, the task we address here is how to recognize and link mentions to products in user generated textual content to the product, from a catalog, they refer to. We claim that two basic sub-tasks arise: first, extraction of target entities mentions from unstructured textual content; second, disambiguation of extracted entities, i.e., linking extracted mentions to their real world counterpart. In this work, we developed methods to address these two sub-tasks. This thesis details these tasks, discusses our ideas for the methods we developed, and presents our contributions and results towards this goal. / Não tive dificuldades, tudo funcionou corretamente.

Of the structured data published on the web, for instance as datasets on Open Data Platforms such as data.gov, but also in the form of HTML tables on the general web, only a small part is in a relational form. Instead the data is intermingled with formatting, layout and textual metadata, i.e., it is contained in partially structured documents. This makes transformation into a true relational form necessary, which is a precondition for most forms of data analysis and data integration. Studying data.gov as an example source for partially structured documents, we present a classification of typical normalization problems. We then present the DeExcelerator, which is a framework for extracting relations from partially structured documents such as spreadsheets and HTML tables.

Thesis (PhD)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: The design, development and evaluation of a novel wave energy converter (WEC) device, called the ShoreSWEC, in a South African port development is presented. Based on the device requirements, site selection criteria were specified and applied to identify a suitable deployment location. A wave modeling procedure was developed to determine the operational wave conditions and available wave power resource at the selected location. The site was found to have a low mean annual average resource of approximately 2.3 kilowatt per meter wave crest (kW/m) due to its relatively sheltered location. The wave model was further used to determine design storm conditions and a structural stability analysis of the device was conducted. Experimental tests were performed to evaluate the hydrodynamic conversion efficiency of a single chamber of the device at its most conservative orientation, under a variety of wave energy conditions. The effect of a floor incline and an additional chamber on the performance of the system was investigated. The incline improved efficiency for low wave heights, making it ideal for the low wave power resource conditions of the site, whilst the multi-chamber system experienced increased performance at high wave periods. A comparison between the ShoreSWEC and a conventional oscillating water column (OWC) WEC showed that the OWC extracted 72% more energy, highlighting the sensitivity of performance on device orientation. A three-dimensional (3D) numerical model of the experimental setup was developed. The numerical model provided comparable water surface elevations inside the flume and chamber, yet predicted significantly higher internal chamber pressures and overall efficiency. The electricity generation potential of a 10 chamber ShoreSWEC at the specified location, approximated from the experimental results and 11 years of hindcast wave data, was found to be 6 kW on average for a 15 kW capacity system. Results of this study highlighted the need for greater understanding of the hydrodynamic characteristics of a full length device. Experimental tests in a 3D wave basin on a scaled full length ShoreSWEC model are therefore recommended. Once conducted, South Africa will be one step closer to the deployment of the full scale SWEC device. / AFRIKAANSE OPSOMMING: Die ontwerp, ontwikkeling en evaluasie van ‘n unieke golfenergieomsetter (GEO), genaamd die ShoreSWEC, in ‘n Suid-Afrikaanse haweontwikkeling word aangebied. Terrein evaluasie kriteria, gebaseer op die omsettervereistes, is ontwikkel en toegepas om die mees belowende terrein te identifiseer. ‘n Golfmodeleringsprosedure is ontwikkel om die operasionele golfkondisies en beskikbare golfdrywinghulpbron te bepaal. Daar is gevind dat die terrein ‘n lae gemiddelde golfdrywing van bykans 2.3 kilowat per meter golfkruin het as gevolg van die beskutte ligging. Die golfmodel is verder gebruik om ontwerpstormkondisies te bepaal en ‘n stabiliteitsanalise was op die toestel struktuur uitgevoer. Eksperimentele toetse van verskeie golfenergie kondisies is gedoen om die hidrodinamiese omsettingseffektiwiteit van ‘n enkel kamer van die toestel te bepaal teen sy konserwatiefste orientasie. Die effek van ‘n vloerhelling en ‘n addisionele kamer op die uitsette van die sisteem is ondersoek. Die helling het effektiwiteit verbeter vir lae golfhoogtes wat dit ideaal maak vir die lae hulpbron by die terrein, terwyl die veelvoudige-kamer-sisteem beter gevaar het by hoë golfperiodes. ‘n Vergelyking tussen die ShoreSWEC en ‘n konvensionele ossilerende waterkolom (OWK) GEO het gewys dat die OWK 72% meer energie onttrek. Dit beklemtoon die sisteem se sensitiwiteit vir die inkomende golfrigting. ‘n Drie-dimensionele (3D) numeriese model van die eksperimentele opstelling is ontwikkel. Die numeriese model het aansienlik hoër drukke binne die kamer, en gevolglik algehele effektiwiteit, voorspel as die eksperimentele toetse. Die elektriese opwekkingskapasiteit van ‘n 10 kamer ShoreSWEC by die terrein, gebaseer op die eksperimentele resultate en 11 jaar se golfdata, is bereken as 6 kW gemiddeld vir ‘n 15 kW kapasiteit stelsel. Die bevindinge van hierdie studie het die behoefte aan ‘n beter begrip van die hidrodinamiese eienskappe van ‘n vollengte sisteem beklemtoon. Eksperimentele toetse in ‘n 3D golfbak op ‘n geskaleerde vollengte ShoreSWEC model word dus aanbeveel. Sodra dit voltooi is, sal Suid-Afrika een stap nader wees aan die ontplooiing van ‘n volskaalse SWEC toestel.

Les travaux réalisés dans cette thèse traitent de la gestion des données dans les réseaux inter-véhiculaires (VANETs). Ces derniers sont constitués d’un ensemble d’objets mobiles qui communiquent entre eux à l’aide de réseaux sans fil de type IEEE 802.11, Bluetooth, ou Ultra Wide Band (UWB). Avec de tels mécanismes de communication, un véhicule peut recevoir des informations de ses voisins proches ou d’autres plus distants, grâce aux techniques de multi-sauts qui exploitent dans ce cas des objets intermédiaires comme relais. De nombreuses informations peuvent être échangées dans le contexte des «VANETs», notamment pour alerter les conducteurs lorsqu’un événement survient (accident, freinage d’urgence, véhicule quittant une place de stationnement et souhaitant en informer les autres, etc.). Au fur et à mesure de leurs déplacements, les véhicules sont ensuite « contaminés » par les informations transmises par d’autres. Dans ce travail, nous voulons exploiter les données de manière sensiblement différente par rapport aux travaux existants. Ces derniers visent en effet à utiliser les données échangées pour produire des alertes aux conducteurs. Une fois ces données utilisées, elles deviennent obsolètes et sont détruites. Dans ce travail, nous cherchons à générer dynamiquement à partir des données collectées par les véhicules au cours de leur trajet, un résumé (ou agrégat) qui fourni des informations aux conducteurs, y compris lorsqu’aucun véhicule communicant ne se trouve pas à proximité. Pour ce faire, nous proposons tout d’abord une structure d’agrégation spatio-temporelle permettant à un véhicule de résumer l’ensemble des événements observés. Ensuite, nous définissons un protocole d’échange des résumés entre véhicules sans l’intermédiaire d’une infrastructure, permettant à un véhicule d’améliorer sa base de connaissances locale par échange avec ses voisins. Enfin, nous définissons nos stratégies d’exploitation de résumé afin d’aider le conducteur dans la prise de décision. Nous avons validé l’ensemble de nos propositions en utilisant le simulateur « VESPA » en l’étendant pour prendre en compte la notion de résumés. Les résultats de simulation montrent que notre approche permet effectivement d’aider les conducteurs à prendre de bonnes décisions, sans avoir besoin de recourir à une infrastructure centralisatrice / The works in this thesis focus on data management in inter-vehicular networks (VANETs). These networks consist of a set of moving objects that communicate with wireless networks IEEE 802.11, Bluetooth, or Ultra Wide Band (UWB). With such communication mechanisms, a vehicle may receive information from its close neighbors or other more remote, thanks to multi-jump techniques that operate in this case intermediate objects as relays. A lot of information can be exchanged in the context of « VANETs », especially to alert drivers when an event occurs (accident, emergency braking, vehicle leaving a parking place and want to inform others, etc.). In their move vehicles are then « contaminated » by the information provided by others. In this work, we use the data substantially different from the existing work. These are, in fact, use the data exchanged to produce alerts drivers. Once these data are used, they become obsolete and are destroyed. In this work, we seek to generate dynamically from data collected by vehicles in their path, a summary (or aggregate) which provides information to drivers, including when no communicating vehicle is nearby. To do this, we first propose a spatio-temporal aggregation structure enabling a vehicle to summarize all the observed events. Next, we define a protocol for exchanging summaries between vehicles without the mediation of an infrastructure, allowing a vehicle to improve its local knowledge base by exchange with its neighbors. Finally, we define our operating strategies of the summary to assist the driver in making decision. We validated all of our proposals using the «VESPA» simulator by extending it to take into account the concept of summaries. Simulation results show that our approach can effectively help drivers make good decisions without the need to use a centralized infrastructure

Dans cette thèse nous proposons de mettre en œuvre des méthodes des mathématiques appliquées et du traitement du signal pour l’étude à partir de spectres infrarouges (IR) de l’évolution des litières végétales au cours du processus de biodégradation. Nous présentons tout d’abord une nouvelle méthode de classification floue fondée sur une optimisation de type non supervisée, basée sur le facteur de covariance qui permet de classer des données IR de forme sphérique ou non sphérique afin d’identifier les méthodes de prétraitement et de choix de gammes spectrales les mieux adaptées. Nous développons des outils mathématiques et des algorithmes innovants permettant de combiner des informations spectrales moyen IR (MIR) et proche IR (MIR) afin d’identifier des marqueurs spectroscopiques discriminants de résidus lignocellulosiques en fonction de leur niveau de dégradation. Pour cela, nous proposons une méthode d'optimisation stochastique basée sur un algorithme génétique avec paramètres adaptés. Nous montrons que l’analyse conjoints des spectres MIR et NIR fusionnés par le produit extérieur permet de mieux discriminer la biomasse lignocellulosique au cours du processus de dégradation qu’un traitement séparé. Nous proposons ensuite une nouvelle approche d’optimisation non linéaire basée sur la sélection d’un vecteur qui met en évidence les poids des bandes spectrales. Enfin, nous développons une méthode de modélisation mathématique basée sur l’extension de l’algorithme AG-PLS en combinant les informations spectrales MIR et NIR par le produit extérieur (OP-AG-PLS). Cette méthode permet d’améliorer les performances de prédiction de l’état de dégradation de la biomasse. / In this thesis we propose to implement methods of applied mathematics and signal processing for the study of the evolution of plant biomass during the biodegradation process. The degradation of plant biomass is identified by FTIR spectroscopy, particularly in the MIR and NIR ranges. We proposed a new unsupervised classification method of Fuzzy C-Means based on the covariance factor to classify the IR data with spherical and not spherical form to identify the pre-treatment methods and the choice of spectral ranges that are the best adapted for our study. We have developed mathematical tools and innovative algorithms to combine these spectral information and identifying infrared spectroscopic markers that are discriminative in the lignocellulosic residues according to their level of degradation. For this, we have proposed a stochastic optimization method based on a genetic algorithm by choosing the appropriate parameters. We have shown that the joint analysis of the MIR and NIR spectra by the outer product (OP) provides better results than the separate analysis for the discrimination of the lignocellulosic biomass during the degradation process. Then, we proposed a new nonlinear optimization approach based on the built of vector which highlights the weight of spectral bands. Finally, we have developed a mathematical modelisation based on the extension of the GA-PLS algorithm combining the MIR and NIR spectral information by outer product (OP-GA-PLS) which significantly improves the prediction performance of the state of degradation of biomass.

This Thesis deals with analysis of the possiblity of password breakthrough for common compression formats and password extraction from self-extraction archives used for malicious software. Structure of compression programs, ciphers and connection between cipher and archives is described. Common and specialized attacks on archives and ciphers are described. Structure of self-extracting archives and password location is used to create extractor of passwords in self-extracting archives.