Made available in DSpace on 2014-06-11T19:22:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-12-02Bitstream added on 2014-06-13T19:48:52Z : No. of bitstreams: 1 freitas_lps_me_ilha.pdf: 463364 bytes, checksum: 35c3a3450e5ec638595c65e3a7508c09 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Neste trabalho descreve-se o desenvolvimento de duas redes neurais que identificam e classificam dados da distribuição do peso corporal na região plantar de pessoas normais e hemiplégicas. Esses dados são experimentais e foram obtidos através da utilização de uma plataforma de força contendo 48 sensores. As arquiteturas utilizadas para esta aplicação foram as redes neurais MLP (Multilayer Perceptron) com o algoritmo retropropagação (backpropagation), e ARTMAP Nebulosa. A escolha de tais arquiteturas se deve ao treinamento (supervisionado) o qual associa de forma direta a distribuição de força plantar com os respectivos pacientes (normais e hemiplégicos). Ambas as arquiteturas, MLP e ARTMAP Nebulosa, conseguiram fazer a discriminação entre quase todas as pessoas normais e hemiplégicos. A rede neural ARTMAP Nebulosa possui a vantagem de efetuar a classificação de forma rápida e eficiente. Esta aplicação é importante nas áreas de Podologia, Posturologia e Podoposturologia, pois propicia ao profissional de saúde uma nova metodologia de diagnóstico / This work describes the development of two neural networks that identify and classify data distribution of plantar body weight of normal or hemiplegic individuals. The architectures used for this application were, respectively, MLP neural networks (Multilayer Perceptron) with backpropagation algorithm, and Fuzzy ARTMAP. The choice of such architectures was due to the training (supervised training) which directly associates the distribution of plantar force with the patients (normal or hemiplegic). The input data used for training and diagnosis of the neural networks were obtained from a force plate, with 48 sensors, containing measurements of the weight distribution on the plantar region (right and left) of normal or hemiplegic patients. Both architectures, MLP and Fuzzy ARTMAP, were able to discriminate almost all normal and hemiplegic patients. The Fuzzy ARTMAP neural network was more efficient than MLP neural network in the classification of the patients. This application is important in areas of Podiatry, Posturology and Podoposturology because it can help the health care professionals

Orientador: Marcelo Carvalho Minhoto Teixeira / Banca: Aparecido Augusto de Carvalho / Banca: Márcio Roberto Covacic / Resumo: Neste trabalho descreve-se o desenvolvimento de duas redes neurais que identificam e classificam dados da distribuição do peso corporal na região plantar de pessoas normais e hemiplégicas. Esses dados são experimentais e foram obtidos através da utilização de uma plataforma de força contendo 48 sensores. As arquiteturas utilizadas para esta aplicação foram as redes neurais MLP (Multilayer Perceptron) com o algoritmo retropropagação (backpropagation), e ARTMAP Nebulosa. A escolha de tais arquiteturas se deve ao treinamento (supervisionado) o qual associa de forma direta a distribuição de força plantar com os respectivos pacientes (normais e hemiplégicos). Ambas as arquiteturas, MLP e ARTMAP Nebulosa, conseguiram fazer a discriminação entre quase todas as pessoas normais e hemiplégicos. A rede neural ARTMAP Nebulosa possui a vantagem de efetuar a classificação de forma rápida e eficiente. Esta aplicação é importante nas áreas de Podologia, Posturologia e Podoposturologia, pois propicia ao profissional de saúde uma nova metodologia de diagnóstico / Abstract: This work describes the development of two neural networks that identify and classify data distribution of plantar body weight of normal or hemiplegic individuals. The architectures used for this application were, respectively, MLP neural networks (Multilayer Perceptron) with backpropagation algorithm, and Fuzzy ARTMAP. The choice of such architectures was due to the training (supervised training) which directly associates the distribution of plantar force with the patients (normal or hemiplegic). The input data used for training and diagnosis of the neural networks were obtained from a force plate, with 48 sensors, containing measurements of the weight distribution on the plantar region (right and left) of normal or hemiplegic patients. Both architectures, MLP and Fuzzy ARTMAP, were able to discriminate almost all normal and hemiplegic patients. The Fuzzy ARTMAP neural network was more efficient than MLP neural network in the classification of the patients. This application is important in areas of Podiatry, Posturology and Podoposturology because it can help the health care professionals / Mestre

Neural Network method is a technique that is heavily researched and used in applications within the engineering field for various purposes ranging from process control to biomedical applications. The success of Neural Networks (NN) in engineering applications, e.g. object tracking and face recognition has motivated its application to the finance industry. In the financial industry, time series data is used to model economic variables. As a result, finance researchers, portfolio managers and stockbrokers have taken interest in applying NN to model non-linear problems they face in their practice. NN facilitates the approach of predicting stocks due to its ability to accurately and intuitively learn complex patterns and characterizes these patterns as simple equations. In this research, a methodology that uses fractal theory and NN framework to model the stock market behavior is proposed and developed. The time series analysis is carried out using the proposed approach with application to modelling the Dow Jones Average Index’s future directional movement. A methodology to establish self-similarity of time series and long memory effects that result in classifying the time series signal as persistent, random or non-persistent using the rescaled range analysis technique is developed. A linear regression technique is used for the estimation of the required parameters and an incremental online NN algorithm is implemented to predict the directional movement of the stock. An iterative fractal analysis technique is used to select the required signal intervals using the approximated parameters. The selected data is later combined to form a signal of interest and then pass it to the ensemble of classifiers. The classifiers are modelled using a neural network based algorithm. The performance of the final algorithm is measured based on accuracy of predicting the direction of movement and also on the algorithm’s confidence in its decision-making. The improvement within the final algorithm is easily assessed by comparing results from two different models in which the first model is implemented without fractal analysis and the second model is implemented with the aid of a strong fractal analysis technique. The results of the first NN model were published in the Lecture Notes in Computer Science 2006 by Springer. The second NN model incorporated a fractal theory technique. The results from this model shows a great deal of improvement when classifying the next day’s stock direction of movement. A summary of these results were submitted to the Australian Joint Conference on Artificial Intelligence 2006 for publishing. Limitations on the sample size, including problems encountered with the proposed approach are also outlined in the next sections. This document also outlines recommendations that can be implemented as further steps to advance and improve the proposed approach for future work.

The adenovirus major late transcription unit (MLTU) encodes for most of the mRNAs that are translated into the structural proteins of the virus capsid. Transcription from the MLTU is directed by the major late promoter (MLP), which is highly activated during the late phase of infection. This thesis discusses how the adenovirus-encoded L4-22K protein regulates the MLP at both the level of transcription and pre-mRNA splicing. The study shed new light on the complex regulation of the early to late shift of adenoviral gene expression. Here we show that the L4-22K protein has opposing effects on MLP transcription, functioning both as an activator and a repressor protein. The stimulatory effect mainly depends on the direct interaction of the L4-22K protein with the downstream element (DE element) located approximately 100 nucleotides downstream of the transcription initiation site. In addition to the DE element we also show that the promoter-proximal upstream element (UPE) acts as an L4-22K responsive enhancer element in the MLP. Preliminary data suggests that the activation of MLP transcription via DE and UPE differs mechanistically. The transactivation domain of the L4-22K protein is localized to the conserved carboxy-terminus of the protein. Our results also defined a novel low affinity L4-22K binding site, the R1 region, which functions as a repressor element in MLP transcription. At high concentrations L4-22K binds to R1 and recruits the cellular transcription factor Sp1 to a DNA segment covering the major late first leader 5´ splice site that is embedded in the R1 region. Sp1 binding to R1 results in a suppression of L4-22K-mediated activation of MLP transcription. This self-limiting effect on MLP transcription might have a function to fine-tune the MLTU gene expression. Interestingly, the L4-22K protein binds with the same sequence specificity to both the R1 double-stranded DNA and R1 single-stranded RNA (ssRNA). L4-22K binds to the R1 ssRNA with the same polarity as the MLTU nascent RNA. This binding results in the recruitment of U1 snRNA to the major late first leader 5´ splice site. This enhanced U1 snRNA recruitment leads to a suppression of MLP transcription and simultaneously an increase of major late first intron splicing.

No description available.

Denna studie syftar till att undersöka berörda samhällsaktörers inställning till att uppnå klimatneutralitet inom Sverige med bio-CCS som åtgärd. En kvalitativ innehållsanalys av remisser från klimatpolitiska vägvalsutredningens betänkande Vägen till en klimatpositiv framtid genomfördes med ett multi-level perspective för att studera dessa aktörers ståndpunkt. Aktörernas synpunkter identifieras och analyseras för att därefter ställas mot tidigare forskning. Resultatet av studien visar att det finns delade uppfattningar hos aktörerna angående bio-CCS och vad som behövs för att främja tekniken. De största hindren till att implementera bio-CCS som åtgärd anses vara ekonomiska och politiska aspekter, men att det även finns andra faktorer som har en betydande roll för att bio-CCS ska kunna ha ett inflytande till att Sverige ska uppnå klimatneutralitet till 2045. / This study aims to investigate the approach of relevant actors to achieving climate neutrality within Sweden with bio-CCS as a measure. A qualitative content analysis of referrals from the climate policy inquiry report Vägen till en klimatpositiv framtid carried out with a multi-level perspective theory to study the position of these actors. The actors' views are identified and analyzed and compared to previous research. The results show that there are divided opinions among actors regarding bio-CCS and what is needed to promote the technology. The main obstacles to implementing bio-CCS as a measure are considered to be economic and political aspects, other factors also have a significant role in influencing Sweden to achieve climate neutrality by 2045.

This mixed methods study aims at evaluating the transformative potential of Nationally Appropriate Mitigation Actions (NAMAs). Earlier studies on the subject have outlined a lack of clarity both on the concept of NAMAs and on how developing countries will use it in their climate actions and thus its ability to contribute to transformational change. The mixed method approach used was: quantitative content analysis of Intended Nationally Determined Contribution (INDC) from developing countries referring to NAMAs combined with qualitative thematic analysis of NAMA proposals from eight selected countries. An explanatory sequential design was used which means that the first quantitative phase aimed at giving an initial understanding of NAMAs transformative potential. The purpose with the second phase, the qualitative analysis was then to deepen that understanding, by applying transformation theories. The two phases of analysis was integrated in the discussion section to get a more complete picture of the transformative potential. The result shows that the intent with NAMAs in the INDC consists of great uncertainties. A variety of NAMA designs was found in both phases of the study. In all of the eight more closely studied countries elements of transformation could be identified, which indicates that NAMAs could be designed to have transformative potential.

<p>Merparten av de kommersiella system för mobilkommunikation som finns och byggs i världen idag bygger fortfarande på GSM, antalet abbonnenter är över 2 miljarder. För att utöka funktionaliteten med mobila terminaler har det forskats på att införa positionering i GSM-nätverk. Tjänster som använder abbonnentens positionsinformation kallas Location Based Service och de ger möjlighet att utöka funktionaliteten och spara användaren av tjänsten arbete. </p><p>Rapporten beskriver olika tekniker för positionering och slutsatsen att CGI-TA är den teknik som positioneringen ska byggas på. Denna teknik finns tillgänglig hos de svenska operatörerna idag och för att kommunicera med dem används Mobile Location Protocol 3.0.0. Implementation av positioneringen realiserades i en J2EE-miljö i form av en WebLogic Server 8.1 med hjälp av Enterprise Java Beans och Java Connector Architecture. Prototypen verifierades med hjälp av en emulator till Ericsson Mobile Positioning System som klarar av att hantera Mobile Location Protocol 3.0.0.</p>

Merparten av de kommersiella system för mobilkommunikation som finns och byggs i världen idag bygger fortfarande på GSM, antalet abbonnenter är över 2 miljarder. För att utöka funktionaliteten med mobila terminaler har det forskats på att införa positionering i GSM-nätverk. Tjänster som använder abbonnentens positionsinformation kallas Location Based Service och de ger möjlighet att utöka funktionaliteten och spara användaren av tjänsten arbete. Rapporten beskriver olika tekniker för positionering och slutsatsen att CGI-TA är den teknik som positioneringen ska byggas på. Denna teknik finns tillgänglig hos de svenska operatörerna idag och för att kommunicera med dem används Mobile Location Protocol 3.0.0. Implementation av positioneringen realiserades i en J2EE-miljö i form av en WebLogic Server 8.1 med hjälp av Enterprise Java Beans och Java Connector Architecture. Prototypen verifierades med hjälp av en emulator till Ericsson Mobile Positioning System som klarar av att hantera Mobile Location Protocol 3.0.0.

Made available in DSpace on 2014-06-12T16:00:06Z (GMT). No. of bitstreams: 2 arquivo5998_1.pdf: 1180748 bytes, checksum: e5d0a95fe8d45bdddd6975b365971603 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2007 / Este trabalho propõe uma metodologia para a otimização global de redes neurais MLP. O objetivo é a otimização simultânea de arquiteturas e pesos sinápticos de redes MLP, na tentativa de proporcionar um bom desempenho de classificação para qualquer conjunto de dados. A otimização simultânea de arquiteturas e pesos de redes neurais é uma abordagem interessante para a obtenção de redes eficientes com maior poder de generalização, pois cria um compromisso entre baixa complexidade estrutural do modelo e baixos índices de erro de treinamento. Tal aplicação já foi bastante investigada com a utilização de métodos de busca metaheurística tais como algoritmos genéticos, recozimento simulado, busca tabu e combinações dos mesmos. Outra técnica de busca meta-heurística menos investigada neste contexto é a otimização por enxame de partículas (PSO) que vem recebendo cada vez mais atenção da comunidade científica devido aos bons resultados obtidos ao lidar com problemas de otimização numérica contínua. A metodologia desenvolvida neste trabalho consiste na aplicação de dois algoritmos PSOs, um para a otimização de arquiteturas e outro para o ajuste dos pesos sinápticos de cada arquitetura gerada pelo primeiro PSO. Estes dois processos são intercalados por um número específico de iterações. Este trabalho apresenta resultados da aplicação da metodologia proposta em três conhecidas bases de dados de problemas de classificação de padrões de domínio médico. Nos problemas mais difíceis de classificar, a metodologia apresentada obteve resultados satisfatórios e gerou redes com baixo erro de generalização e baixa complexidade. Tais resultados são relevantes para mostrar que a técnica meta-heurística de otimização por enxames de partículas é uma opção efetiva para o ajuste de pesos e arquiteturas de redes neurais MLP