<p>In an optimal power control scheme for a Code Division Multiple Access (CDMA) system all mobile stations signals should arrive to the base station at equal power. If not, stronger singals may cause too much interference and block out weaker ones. Commonly used power control schemes utilizes the Signal to Interference Ratio (SIR) to design a Power Control Command (PCC) to adjust the transmit power of the mobile station. A significant problem within the conventional methods is the slow SIR recovery due to deep channel fades. Conventional methods base the PCC on the previous channel state when in fact, the channel state may have significantly changed when transmission occurs. These channel changes may cause the SIR to drop or rise drastically and lead to uncontrollable Multi Access Interference (MAI) resulting in power escalation and making the system unstable. In order to overcome power escalation and improve the recovery from deep fades a novel power control method has been developed. Based on Linear Quadratic Control and Kalman filtering for channel prediction this method designs the PCC based on the coming channel state instead of the current. This optimizes the PCC for the channel state where transmission occurs. Simulations show that this control scheme outperforms previous methods by making the impacts of the deep fades less severe on the SIR and also improves the overall SIR behaviour.</p>

In an optimal power control scheme for a Code Division Multiple Access (CDMA) system all mobile stations signals should arrive to the base station at equal power. If not, stronger singals may cause too much interference and block out weaker ones. Commonly used power control schemes utilizes the Signal to Interference Ratio (SIR) to design a Power Control Command (PCC) to adjust the transmit power of the mobile station. A significant problem within the conventional methods is the slow SIR recovery due to deep channel fades. Conventional methods base the PCC on the previous channel state when in fact, the channel state may have significantly changed when transmission occurs. These channel changes may cause the SIR to drop or rise drastically and lead to uncontrollable Multi Access Interference (MAI) resulting in power escalation and making the system unstable. In order to overcome power escalation and improve the recovery from deep fades a novel power control method has been developed. Based on Linear Quadratic Control and Kalman filtering for channel prediction this method designs the PCC based on the coming channel state instead of the current. This optimizes the PCC for the channel state where transmission occurs. Simulations show that this control scheme outperforms previous methods by making the impacts of the deep fades less severe on the SIR and also improves the overall SIR behaviour.

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / We investigate pulse position modulation (PPM) and multipulse PPM (MPPM) for free space op- tical channels using bit interleaved coded modulation with iterative decoding. Data bits are first encoded by using a non recursive convolutional code and the coded bits after an interleaver are modulated before transmission. Iterative decoding is performed at the receiver. Optimized mapping is designed for MPPM. A genetic algorithm is used to find the optimized mapping for MPPM. Our simulation results show that a significant improvement in the error performance can be achieved by using optimized mapping and iterative decoding at the receiver.

In this paper, we investigate an adaptive decode-and-forward (DF) cooperative diversity scheme based on bit interleaved coded modulation with iterative decoding (BICM-ID). Data bits are first encoded by using a convolutional code and the coded bits after an interleaver are modulated before transmission. Iterative decoding is used at the receiver. Optimized constellation mapping is designed jointly for the source and the relay using a genetic algorithm. A novel error performance analysis for the adaptive DF scheme using BICM-ID is proposed. The simulation results agree well with the analytical results at high signal-to-noise ratio (SNR). More than 5.8 dB gain in terms of SNR over the existing mappings is achieved with proposed mappings.

Yes / Developing medical devices that resist bacterial attachment and subsequent biofilm formation is highly desirable. In this paper, we report the optimization of the molecular structure and thus material properties of a range of (meth)acrylate copolymers which contain monomers reported to deliver bacterial resistance to surfaces. This optimization allows such monomers to be employed within novel coatings to reduce bacterial attachment to silicone urinary catheters. We show that the flexibility of copolymers can be tuned to match that of the silicone catheter substrate, by copolymerizing these polymers with a lower Tg monomer such that it passes the flexing fatigue tests as coatings upon catheters, that the homopolymers failed. Furthermore, the Tg values of the copolymers are shown to be readily estimated by the Fox equation. The bacterial resistance performance of these copolymers were typically found to be better than the neat silicone or a commercial silver containing hydrogel surface, when the monomer feed contained only 25 v% of the “hit” monomer. The method of initiation (either photo or thermal) was shown not to affect the bacterial resistance of the copolymers. Optimized synthesis conditions to ensure that the correct copolymer composition and to prevent the onset of gelation are detailed. / Impact Accelerators Account at the University of Nottingham; Camstent Ltd; The Wellcome Trust (ref 085245 and 103882)

O desenvolvimento de novas técnicas capazes de produzir modelos de predição com erros de generalização relativamente baixos é uma constante em aprendizado de máquina e áreas correlatas. Nesse sentido, a composição de um conjunto de modelos no denominado ensemble merece destaque por seu potencial teórico e empírico de minimizar o erro de generalização. Diversos métodos para construção de ensembles de modelos são encontrados na literatura. Dentre esses, o método baseado em rotação (RB) tem apresentado desempenho superior a outros clássicos. O método RB utiliza a técnica de extração de características da análise de componentes principais (PCA) como estratégia de rotação para provocar acurácia e diversidade entre os modelos componentes. Contudo, essa estratégia não assegura que a direção resultante será apropriada para a técnica de aprendizado supervisionado (SLT) escolhida. Adicionalmente, o método RB não é adequado com SLTs invariantes à rotação e não foi amplamente validado com outras estáveis. Esses aspectos tornam-no inadequado e/ou restrito a algumas SLTs. Nesta tese, é proposta uma nova abordagem de extração baseada na concatenação de rotação e projeção otimizadas em prol da SLT (denominada roto-projeção otimizada). A abordagem utiliza uma metaheurística para otimizar os parâmetros da transformação de roto-projeção e minimizar o erro da técnica diretora da otimização. Mais enfaticamente, propõe-se a roto-projeção otimizada como parte fundamental de um novo método de ensembles, denominado ensemble baseado em roto-projeção otimizada (ORPE). Os resultados obtidos mostram que a roto-projeção otimizada pode reduzir a dimensionalidade e a complexidade dos dados e do modelo, além de aumentar o desempenho da SLT utilizada posteriormente. O método ORPE superou, com relevância estatística, o RB e outros com SLTs estáveis e instáveis em bases de classificação e regressão de domínio público e privado. O ORPE mostrou-se irrestrito e altamente eficaz assumindo a primeira posição em todos os ranqueamentos de dominância realizados / The development of new techniques capable of inducing predictive models with low generalization errors has been a constant in machine learning and other related areas. In this context, the composition of an ensemble of models should be highlighted due to its theoretical and empirical potential to minimize the generalization error. Several methods for building ensembles are found in the literature. Among them, the rotation-based (RB) has become known for outperforming other traditional methods. RB method applies the principal components analysis (PCA) for feature extraction as a rotation strategy to provide diversity and accuracy among base models. However, this strategy does not ensure that the resulting direction is appropriate for the supervised learning technique (SLT). Moreover, the RB method is not suitable for rotation-invariant SLTs and also it has not been evaluated with stable ones, which makes RB inappropriate and/or restricted to the use with only some SLTs. This thesis proposes a new approach for feature extraction based on concatenation of rotation and projection optimized for the SLT (called optimized roto-projection). The approach uses a metaheuristic to optimize the parameters from the roto-projection transformation, minimizing the error of the director technique of the optimization process. More emphatically, it is proposed the optimized roto-projection as a fundamental part of a new ensemble method, called optimized roto-projection ensemble (ORPE). The results show that the optimized roto-projection can reduce the dimensionality and the complexities of the data and model. Moreover, optimized roto-projection can increase the performance of the SLT subsequently applied. The ORPE outperformed, with statistical significance, RB and others using stable and unstable SLTs for classification and regression with databases from public and private domains. The ORPE method was unrestricted and highly effective holding the first position in every dominance rankings

O desenvolvimento de novas técnicas capazes de produzir modelos de predição com erros de generalização relativamente baixos é uma constante em aprendizado de máquina e áreas correlatas. Nesse sentido, a composição de um conjunto de modelos no denominado ensemble merece destaque por seu potencial teórico e empírico de minimizar o erro de generalização. Diversos métodos para construção de ensembles de modelos são encontrados na literatura. Dentre esses, o método baseado em rotação (RB) tem apresentado desempenho superior a outros clássicos. O método RB utiliza a técnica de extração de características da análise de componentes principais (PCA) como estratégia de rotação para provocar acurácia e diversidade entre os modelos componentes. Contudo, essa estratégia não assegura que a direção resultante será apropriada para a técnica de aprendizado supervisionado (SLT) escolhida. Adicionalmente, o método RB não é adequado com SLTs invariantes à rotação e não foi amplamente validado com outras estáveis. Esses aspectos tornam-no inadequado e/ou restrito a algumas SLTs. Nesta tese, é proposta uma nova abordagem de extração baseada na concatenação de rotação e projeção otimizadas em prol da SLT (denominada roto-projeção otimizada). A abordagem utiliza uma metaheurística para otimizar os parâmetros da transformação de roto-projeção e minimizar o erro da técnica diretora da otimização. Mais enfaticamente, propõe-se a roto-projeção otimizada como parte fundamental de um novo método de ensembles, denominado ensemble baseado em roto-projeção otimizada (ORPE). Os resultados obtidos mostram que a roto-projeção otimizada pode reduzir a dimensionalidade e a complexidade dos dados e do modelo, além de aumentar o desempenho da SLT utilizada posteriormente. O método ORPE superou, com relevância estatística, o RB e outros com SLTs estáveis e instáveis em bases de classificação e regressão de domínio público e privado. O ORPE mostrou-se irrestrito e altamente eficaz assumindo a primeira posição em todos os ranqueamentos de dominância realizados / The development of new techniques capable of inducing predictive models with low generalization errors has been a constant in machine learning and other related areas. In this context, the composition of an ensemble of models should be highlighted due to its theoretical and empirical potential to minimize the generalization error. Several methods for building ensembles are found in the literature. Among them, the rotation-based (RB) has become known for outperforming other traditional methods. RB method applies the principal components analysis (PCA) for feature extraction as a rotation strategy to provide diversity and accuracy among base models. However, this strategy does not ensure that the resulting direction is appropriate for the supervised learning technique (SLT). Moreover, the RB method is not suitable for rotation-invariant SLTs and also it has not been evaluated with stable ones, which makes RB inappropriate and/or restricted to the use with only some SLTs. This thesis proposes a new approach for feature extraction based on concatenation of rotation and projection optimized for the SLT (called optimized roto-projection). The approach uses a metaheuristic to optimize the parameters from the roto-projection transformation, minimizing the error of the director technique of the optimization process. More emphatically, it is proposed the optimized roto-projection as a fundamental part of a new ensemble method, called optimized roto-projection ensemble (ORPE). The results show that the optimized roto-projection can reduce the dimensionality and the complexities of the data and model. Moreover, optimized roto-projection can increase the performance of the SLT subsequently applied. The ORPE outperformed, with statistical significance, RB and others using stable and unstable SLTs for classification and regression with databases from public and private domains. The ORPE method was unrestricted and highly effective holding the first position in every dominance rankings

In Sweden athlete schools, where students are attending in terms of optimizing their athletic careers in correlation with their studies, are a widely spread phenomena over the country and the system is included within the ordinary school system. This study aims to examine how the subject Physical Education and Health (PEH) is taught at athlete schools in comparison to how it is taught in classes with ordinary upper secondary school students. This study is based on interviews with eight teachers from two different Swedish schools. The results show that teachers do adjust their teaching in order to achieve quality teaching to give the athletic students optimized possibilities to improve. The results show different teacher perspectives about what knowledge that is prioritized. Admittedly, the teachers confess having problems with whether they assess these students on their previous skills or if they actually learn new skills during their PEH. Hence, this study serves the purpose of revealing the importance of developing new and individualized strategies on how to form an optimized educational environment and quality teaching for those students.

Structural health monitoring (SHM) is an emerging field in civil engineering in recent years. The main objectives of the SHM are to identify structural integrity issues at early stage and improve the structural safety through measuring and analyzing structural behaviors. Sensing systems for SHM can be used to identify applied vehicle loads for bridge structures. Bridge weigh-in-motion (BWIM) is one type of such vehicle load identification. As a tool to monitor the vehicle weight moving on the bridges, BWIM uses the structural responses induced by moving vehicle on the bridge to back-calculate vehicle information. In this thesis, optimized BWIM systems using multimetric measurements will be investigated. In Chapter 1, the concept and background of BWIM systems will be introduced. The objective of this research will be also demonstrated in this chapter. Chapter 2 is the literature review section. In Chapter 3, the finite element bridge model adopted for this study will be described. In this section, the moving-load time history analysis, sectional properties for bridge members, and other structural parameters of bridge model will be introduced. The methodology of BWIM systems used in this study will be demonstrated in Chapter 4. In Chapter 5, optimized sensor locations for BWIM using normal and shear strain measurements and acceleration measurement will be discussed for the case without measurement noise. In Chapter 6, sensor location optimization for the case considering measurement noises will be investigated. A new acceleration-based BWIM method is proposed in this section. Non-drift displacement reconstruction technique using acceleration measurement and FIR filtering is applied for BWIM. Finally, Chapter 7 is the conclusion part of this thesis.

Resumo: Um processo muito utilizado na indústria metal-mecânica em geral para fabricação de componentes de responsabilidade é a operação de retificação cilíndrica interna de precisão, este processo é utilizado, por exemplo, na fabricação de anéis de rolamento e outros componentes. Atualmente a evolução das máquinas permitiu o aprimoramento deste processo no que diz respeito ao posicionamento e à rigidez do sistema máquina-peça-ferramenta, porém ainda são enfrentados grandes problemas quanto à lubrificação e refrigeração, principalmente no que diz respeito à utilização de fluidos de corte. Este trabalho visa o estudo do comportamento da operação de retificação cilíndrica interna de mergulho a alta velocidade, no processo de acabamento de um aço endurecido SAE 52100, utilizando-se um rebolo convencional e dois métodos de refrigeração: o método de refrigeração convencional e com um bocal modificado. O motivo para o emprego de um bocal modificado reside no fato de se encontrar uma alternativa viável para uma possível substituição do método convencional que consome grande quantidade de fluido, já que estes têm se tornando nas últimas décadas um grande problema para as indústrias, devido aos enormes dados ambientais e humanos que causam. Para efetivar a comparação entre os métodos de refrigeração foram analisados os dados a respeito da rugosidade, erros de circularidade e desgaste diametral do rebolo, além de análise de microdureza e MEV das amostras retificadas para os métodos de refrigeração citados anteriormente. Analisando os resultados a quebra de barreira aerodinâmica e a melhor eficiência da penetração do fluido de corte na região de contato entre o rebolo e a peça foi maior quando se utilizou o bocal modificado com vazão de 21 1/min (25 m/s); os resultados de rugosidade, erro de circularidade e desgaste do rebolo foram sempre... (Resumo completo, clicar acesso eletrÔnico abaixo) / Abstract: Precision internal plunge grinding is a process much used in the mechanical industry in general / Orientador: Eduardo Carlos Bianchi / Coorientador: Paulo Roberto de Aguiar / Banca: Carlos Elias da Silva Junior / Banca: Carlos Alberto Soufen / Mestre