This work focuses on automatic translation of code written in Ruby programming language into Python 3. First part investigates principles of computer programming languages translation as is described in the literature. Second part compares elements of these two programming languages and suggests ways how these elements can be translated. Based on this theory I developed Ruby-to-Python translator. Its working is demonstrated on the translation of the Prawn library for generating PDF files.

A maioria dos artigos científicos estão disponíveis no formato PDF. Este padrão permite a geracão de metadados que são inclusos dentro do documento. Porém, muitos autores não definem esta informação, fazendo esse recurso inseguro ou incompleto. Este fato tem motivado pesquisa que busca extrair metadados automaticamente. A extração automática de metadados foi classificada como uma das tarefas mais desafiadoras na área de engenharia de documentos. Este trabalho propõe Artic, um método para extração de metadados de artigos científicos que aplica um modelo probabilístico em duas camadas baseado em Conditional Random Fields. A primeira camada visa identificar as secões principais com possíveis metadados. Já a segunda camada identifica, para cada secão, o metadado correspondente. Dado um PDF contendo um artigo científico, Artic extrai título, nome dos autores, emails, afiliações e informações sobre a conferência onde o paper foi publicado. Os experimentos usaram 100 artigos de conferências variadas. Os resultados superaram a solução estado-da-arte usada como baseline, atingindo uma precisão acima de 99%. / Most scientific articles are available in PDF format. The PDF standard allows the generation of metadata that is included within the document. However, many authors do not define this information, making this feature unreliable or incomplete. This fact has been motivating research which aims to extract metadata automatically. Automatic metadata extraction has been identified as one of the most challenging tasks in document engineering. This work proposes Artic, a method for metadata extraction from scientific papers which employs a two-layer probabilistic framework based on Conditional Random Fields. The first layer aims at identifying the main sections with metadata information, and the second layer finds, for each section, the corresponding metadata. Given a PDF file containing a scientific paper, Artic extracts the title, author names, emails, affiliations, and venue information. We report on experiments using 100 real papers from a variety of publishers. Our results outperformed the state-of-the-art system used as the baseline, achieving a precision of over 99%.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-02-17T22:02:01Z No. of bitstreams: 1 JoilsonBatistaDeAlmeidaRego_TESE.pdf: 1273840 bytes, checksum: 2e1a41026f6aec413ecef974064af22d (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-02-18T00:03:07Z (GMT) No. of bitstreams: 1 JoilsonBatistaDeAlmeidaRego_TESE.pdf: 1273840 bytes, checksum: 2e1a41026f6aec413ecef974064af22d (MD5) / Made available in DSpace on 2016-02-18T00:03:07Z (GMT). No. of bitstreams: 1 JoilsonBatistaDeAlmeidaRego_TESE.pdf: 1273840 bytes, checksum: 2e1a41026f6aec413ecef974064af22d (MD5) Previous issue date: 2014-08-08 / O presente trabalho usa uma medida de similaridade denominada correntropia no desenvolvimento de um novo m?todo para estimar uma rela??o linear entre as vari?veis e suas amostras. O objetivo ? estender o conceito de correntropia a partir de duas vari?veis para quaisquer dois vetores (mesmo com diferentes dimens?es), utilizando conceitos estat?sticos. Atrav?s das extens?es multidimensionais que ser?o apresentadas, o problema de regress?o ou identifica??o de sistemas pode ser formulado de uma maneira diferente, buscando retas e hiperplanos que possuem a m?xima densidade de probabilidade dos dados desejados. Experimentos mostraram que o novo algoritmo tem uma boa atualiza??o de ponto fixo e robustez a ru?dos impulsivos. / This present work uses a generalized similarity measure called correntropy to develop a new method to estimate a linear relation between variables given their samples. Towards this goal, the concept of correntropy is extended from two variables to any two vectors (even with different dimensions) using a statistical framework. With this multidimensionals extensions of Correntropy the regression problem can be formulated in a different manner by seeking the hyperplane that has maximum probability density with the target data. Experiments show that the new algorithm has a nice fixed point update for the parameters and robust performs in the presence of outlier noise.

A maioria dos artigos científicos estão disponíveis no formato PDF. Este padrão permite a geracão de metadados que são inclusos dentro do documento. Porém, muitos autores não definem esta informação, fazendo esse recurso inseguro ou incompleto. Este fato tem motivado pesquisa que busca extrair metadados automaticamente. A extração automática de metadados foi classificada como uma das tarefas mais desafiadoras na área de engenharia de documentos. Este trabalho propõe Artic, um método para extração de metadados de artigos científicos que aplica um modelo probabilístico em duas camadas baseado em Conditional Random Fields. A primeira camada visa identificar as secões principais com possíveis metadados. Já a segunda camada identifica, para cada secão, o metadado correspondente. Dado um PDF contendo um artigo científico, Artic extrai título, nome dos autores, emails, afiliações e informações sobre a conferência onde o paper foi publicado. Os experimentos usaram 100 artigos de conferências variadas. Os resultados superaram a solução estado-da-arte usada como baseline, atingindo uma precisão acima de 99%. / Most scientific articles are available in PDF format. The PDF standard allows the generation of metadata that is included within the document. However, many authors do not define this information, making this feature unreliable or incomplete. This fact has been motivating research which aims to extract metadata automatically. Automatic metadata extraction has been identified as one of the most challenging tasks in document engineering. This work proposes Artic, a method for metadata extraction from scientific papers which employs a two-layer probabilistic framework based on Conditional Random Fields. The first layer aims at identifying the main sections with metadata information, and the second layer finds, for each section, the corresponding metadata. Given a PDF file containing a scientific paper, Artic extracts the title, author names, emails, affiliations, and venue information. We report on experiments using 100 real papers from a variety of publishers. Our results outperformed the state-of-the-art system used as the baseline, achieving a precision of over 99%.

A maioria dos artigos científicos estão disponíveis no formato PDF. Este padrão permite a geracão de metadados que são inclusos dentro do documento. Porém, muitos autores não definem esta informação, fazendo esse recurso inseguro ou incompleto. Este fato tem motivado pesquisa que busca extrair metadados automaticamente. A extração automática de metadados foi classificada como uma das tarefas mais desafiadoras na área de engenharia de documentos. Este trabalho propõe Artic, um método para extração de metadados de artigos científicos que aplica um modelo probabilístico em duas camadas baseado em Conditional Random Fields. A primeira camada visa identificar as secões principais com possíveis metadados. Já a segunda camada identifica, para cada secão, o metadado correspondente. Dado um PDF contendo um artigo científico, Artic extrai título, nome dos autores, emails, afiliações e informações sobre a conferência onde o paper foi publicado. Os experimentos usaram 100 artigos de conferências variadas. Os resultados superaram a solução estado-da-arte usada como baseline, atingindo uma precisão acima de 99%. / Most scientific articles are available in PDF format. The PDF standard allows the generation of metadata that is included within the document. However, many authors do not define this information, making this feature unreliable or incomplete. This fact has been motivating research which aims to extract metadata automatically. Automatic metadata extraction has been identified as one of the most challenging tasks in document engineering. This work proposes Artic, a method for metadata extraction from scientific papers which employs a two-layer probabilistic framework based on Conditional Random Fields. The first layer aims at identifying the main sections with metadata information, and the second layer finds, for each section, the corresponding metadata. Given a PDF file containing a scientific paper, Artic extracts the title, author names, emails, affiliations, and venue information. We report on experiments using 100 real papers from a variety of publishers. Our results outperformed the state-of-the-art system used as the baseline, achieving a precision of over 99%.

The Affective PDF Reader is a PDF Reader combined with affect recognition systems. The aim of the project is to research a way to provide the reader of a PDF with real - time visual feedback while reading the text to influence the reading experience in a positive way. The visual feedback is given in accordance to analyzed emotional states of the person reading the text - this is done by capturing and interpreting affective information with a facial expression recognition system. Further enhancements would also include analysis of voice in the computation as well as gaze tracking software to be able to use the point of gaze when rendering the visualizations.The idea of the Affective PDF Reader mainly arose in admitting that the way we read text on computers, mostly with frozen and dozed off faces, is somehow an unsatisfactory state or moreover a lonesome process and a poor communication. This work is also inspired by the significant progress and efforts in recognizing emotional states from video and audio signals and the new possibilities that arise from.The prototype system was providing visualizations of footprints in different shapes and colours which were controlled by captured facial expressions to enrich the textual content with affective information. The experience showed that visual feedback controlled by utterances of facial expressions can bring another dimension to the reading experience if the visual feedback is done in a frugal and non intrusive way and it showed that the evolvement of the users can be enhanced.

Utskriftsmotorer används för att generera rapporter och dokument i olika format. Uppdragsgivaren Stamford ställer höga krav på dessa genererade utskrifter gällandepositionering av text, bilder och andra objekt som en utskrift kan innehålla. Det är också viktigt för Stamford att versionshanteringen av den utskriftsmotor de använder fungerar på ett så effektivt sätt som möjligt för att minimera arbete och kostnader vid versionsuppdateringar. Målet med denna uppsats är att hitta ett alternativ till den utskriftsmotor som Stamford använder idag, då de inte är nöjda med hur versionshanteringen fungerar med nuvarande utskriftsmotor. Tre stycken utskriftsmotorer har utvärderats och jämförts mot varandra utifrån en kravlista från Stamford. Dessa utskriftsmotorer är PDFInclude, Viper och VpxPrint. Förutom en utvärdering utifrån Stamfords kravlista så har även vissa andra aspekter funnits i åtanke som exempelvis användarvänlighet och utvecklingsmiljö. Denna studie har visat att VpxPrint är den utskriftsmotor som uppfyller flest kravpunkter från Stamfords kravlista men att Viper är den utskriftsmotor som presterar bäst om aspekter somexempelvis användarvänlighet och utvecklingsmiljö tas i åtanke. / Print engines are used to generate reports and other documents in different formats. Stamford sets high standards on some of the generated reports with regard to the positioning of text, pictures and other objects that a report can contain. It is also important that the version control of the print engine Stamford uses works as effectively as possible to minimize work and costs when updating the system. The goal with this thesis is to find an alternative to the print engine that Stamford is currently using since they are not satisfied with the version control of the current system. Three print engines have been evaluated and compared based on a requirement list from Stamford. These three print engines are PDFInclude, Viper and VpxPrint. As well as the requirement list from Stamford, the evaluation has included other aspects such as usability and development environment. This study has shown that VpxPrint is the print engine that fulfills the greatest number of requirements that Stamford has given. However Viper is the print engine that has achieved the best result when aspects such as usability and development environment are included in the evaluation

This work evaluates the capabilities of the RANS and LES techniques for the simulation of high speed reacting flows. These methods are used to gain further insight into the physics encountered and regimes present in supersonic combustion. The target application of this research is the scramjet engine, a propulsion system of great promise for efficient hypersonic flight. In order to conduct this work a new highly parallelised code, PULSAR, is developed. PULSAR is capable of simulating complex chemistry combustion in highly compressible flows, based on a second order upwind method to provide a monotonic solution in the presence of high gradient physics. Through the simulation of a non-reacting supersonic coaxial helium jet the RANS method is shown to be sensitive to constants involved in the modelling process. The LES technique is more computationally demanding but is shown to be much less sensitive to these model parameters. Nevertheless, LES results are shown to be sensitive to the nature of turbulence at the inflow; however this information can be experimentally obtained. The SCHOLAR test case is used to validate the reacting aspects of PULSAR. Comparing RANS results from laminar chemistry and assumed PDF combustion model simulations, the influence of turbulence-chemistry interactions in supersonic combustion is shown to be small. In the presence of reactions, the RANS results are sensitive to inflow turbulence, due to its influence on mixing. From complex chemistry simulations the combustion behaviour is evaluated to sit between the flamelet and distributed reaction regimes. LES results allow an evaluation of the physics involved, with a pair of coherent vortices identified as the dominant influence on mixing for the oblique wall fuel injection method. It is shown that inflow turbulence has a significant impact on the behaviour of these vortices and hence it is vital for turbulence intensities and length scales to be measured by experimentalists, in order for accurate simulations to be possible.

Researchers have shown that by combining multiple input multiple output (MIMO) techniques with CDMA then higher gains in capacity, reliability and data transmission speed can be attained. But a major drawback of MIMO-CDMA systems is multiple access interference (MAI) which can reduce the capacity and increase the bit error rate (BER), so statistical analysis of MAI becomes a very important factor in the performance analysis of these systems. In this thesis, a detailed analysis of MAI is performed for binary phase-shift keying (BPSK) signals with random signature sequence in Raleigh fading environment and closed from expressions for the probability density function of MAI and MAI with noise are derived. Further, probability of error is derived for the maximum Likelihood receiver. These derivations are verified through simulations and are found to reinforce the theoretical results. Since the performance of MIMO suffers significantly from MAI and inter-symbol interference (ISI), equalization is needed to mitigate these effects. It is well known from the theory of constrained optimization that the learning speed of any adaptive filtering algorithm can be increased by adding a constraint to it, as in the case of the normalized least mean squared (NLMS) algorithm. Thus, in this work both linear and non-linear decision feedback (DFE) equalizers for MIMO systems with least mean square (LMS) based constrained stochastic gradient algorithm have been designed. More specifically, an LMS algorithm has been developed , which was equipped with the knowledge of number of users, spreading sequence (SS) length, additive noise variance as well as MAI with noise (new constraint) and is named MIMO-CDMA MAI with noise constrained (MNCLMS) algorithm. Convergence and tracking analysis of the proposed algorithm are carried out in the scenario of interference and noise limited systems, and simulation results are presented to compare the performance of MIMO-CDMA MNCLMS algorithm with other adaptive algorithms.

Nowadays, universal and unrestricted access to documents has become commonplace. In particular, PDF documents can be created quickly and easily, they look the same everywhere and can be read by any device. Whether for the distribution of printed material or forms: PDF documents are used extensively everywhere to provide various contents. With the Act on Equal Opportunities for People with Disabilities and the BITV 2.0, respectively, public bodies are also legally obliged to make digital offerings accessible. On the following pages we would like to give you instructions on how to make your documents accessible to more people. Furthermore, your work should become more effective and efficient in the long term. The instructions focus on Adobe InDesign 16 for Windows and macOS. Of course, you can use the concepts, support and tips presented here regardless of which version of InDesign you are using.