Zugl.: Paderborn, Univ., Diss., 2009

Universiẗat, Diss., 1999--Konstanz.

abstract: The front end of almost all ADCs consists of a Sample and Hold Circuit in order to make sure a constant analog value is digitized at the end of ADC. The design of Track and Hold Circuit (THA) mainly focuses on following parameters: Input frequency, Sampling frequency, dynamic Range, hold pedestal, feed through error. This thesis will discuss the importance of these parameters of a THA to the ADCs and commonly used architectures of THA. A new architecture with SiGe HBT transistors in BiCMOS 130 nm technology is presented here. The proposed topology without complicated circuitry achieves high Spurious Free Dynamic Range(SFDR) and Total Harmonic Distortion (THD).These are important figure of merits for any THA which gives a measure of non-linearity of the circuit. The proposed topology is implemented in IBM8HP 130 nm BiCMOS process combines typical emitter follower switch in bipolar THAs and output steering technique proposed in the previous work. With these techniques and the cascode transistor in the input which is used to isolate the switch from the input during the hold mode, better results have been achieved. The THA is designed to work with maximum input frequency of 250 MHz at sampling frequency of 500 MHz with input currents not more than 5mA achieving an SFDR of 78.49 dB. Simulation and results are presented, illustrating the advantages and trade-offs of the proposed topology. / Dissertation/Thesis / M.S. Electrical Engineering 2012

No description available.

<p>Går det att förutspå framtida aktiepriser genom att undersöka hur priser, på samma aktier, rört sig historisk? För att undersöka detta har vi använt oss av teknisk analys. Denna uppsats undersöker om teknisk analys på stockholmsbörsen kan användas för att uppnå högre avkastning än en s.k. Buy and Hold Strategi. I undersökningen används Relative Strength Index som teknisk analysmetod för att försöka förutspå framtida upp- och nedgångar i aktiepriser på tjugofem av de högst omsatta aktierna på Stockholmsbörsen. I undersökningen kompletteras Relative Strength Index med en Money Management strategi, som är till för att begränsa förlusterna. Undersökningsperioden sträcker sig mellan januari 2001 och juni 2008.</p><p> </p><p>Svaga statistiska resultat, kombinerat med generellt sett lägre avkastningar, säger oss att förutspå framtida upp- och nedgångar på Stockholmsbörsen med hjälp av Relative Strength Index ej är att föredra framför strategin Buy and Hold.</p>

This dissertation consists of three essays evaluating topics in industrial organization. The first essay investigates a market structure or property regime in which a final good exists only by assembling multiple, monopoly-supplied components. In such dynamic settings, any sunk cost results in an outcome of hold-up, also known as tragedy of the anticommons. I design a model showing conditions for which two factors that reduce sunk cost, refunds and complementarities, mitigate hold-up. If the first component purchased has positive stand alone value or the first seller offers a full refund, hold-up is mitigated. My results suggest several policies that can mitigate inefficient outcomes in assembly problems, including legal requirements on full refunds, regulation on the purchasing order of components, and prohibition of price discrimination. The second essay applies Bayesian statistics to single-firm event studies used in securities litigation and antitrust investigations. Inference based on Bayesian analysis does not require an assumption of normality that potentially invalidates standard inference of classical single-firm event studies. I investigate ten events, five from actual securities litigation cases. Various Bayesian models, including replication of the frequentist approach, are examined. A flexible Bayesian model, replacing parametric likelihood functions with the empirical distribution function, also is explored. Our approach suggests an alternative, valid method for inference with easy implementation and interpretation. The third essay, motivated in the context of pharmaceutical advertising, analyzes demand rotations caused by an exogenously determined advertising parameter under Cournot oligopoly competition. We find that firms and consumers prefer extreme levels of advertising, but preferences for which extreme do not necessarily align. However, these differences can be alleviated with few or many firms in the market or cheap or expensive technologies. Therefore, advertising levels, regulated or not, might not serve consumers' best interests unless certain market attributes hold.

No description available.

Os ácidos ribonucleicos (RNAs) podem ser classificados em duas classes principais: codificante e não codificante de proteína. Os codificantes, representados pelos RNAs mensageiros (mRNAs), possuem a informação necessária à síntese proteica. Já os RNAs não codificantes (ncRNAs) não são traduzidos em proteínas, mas estão envolvidos em várias atividades celulares distintas e associados a várias doenças tais como cardiopatias, câncer e desordens psiquiátricas. A descoberta de novos ncRNAs e seus papéis moleculares favorece avanços no conhecimento da biologia molecular e pode também impulsionar o desenvolvimento de novas terapias contra doenças. A identificação de ncRNAs é uma ativa área de pesquisa e um dos correntes métodos é a classificação de sequências transcritas utilizando sistemas de reconhecimento de padrões baseados em suas características. Muitos classificadores têm sido desenvolvidos com este propósito, especialmente nos últimos três anos. Um exemplo é o Coding Potential Calculator (CPC), baseado em Máquinas de Vetores de Suporte (SVM). No entanto, outros algoritmos robustos são também reconhecidos pelo seu potencial em tarefas de classificação, como por exemplo Random Forest (RF). O método mais utilizado para avaliação destas ferramentas tem sido a validação cruzada k-fold. Uma questão não considerada nessa forma de validação é a suposição de que as distribuições de frequências dentro do banco de dados, em termos das classes das sequências e outras variáveis, não se alteram ao longo do tempo. Caso essa premissa não seja verdadeira, métodos tradicionais como a validação cruzada e o hold-out podem subestimar os erros de classificação. Constata-se, portanto, a necessidade de um método de validação que leve em consideração a constante evolução dos bancos de dados ao longo do tempo, para proporcionar uma análise de desempenho mais realista destes classificadores. Neste trabalho comparamos dois métodos de avaliação de classificadores: hold-out temporal e hold-out tradicional (atemporal). Além disso, testamos novos modelos de classificação a partir da combinação de diferentes algoritmos de indução com características de classificadores do estado da arte e um novo conjunto de características. A partir dos testes das hipóteses, observamos que tanto a validação hold-out tradicional quanto a validação hold-out temporal tendem a subestimar os erros de classificação, que a avaliação por validação temporal é mais fidedigna, que classificadores treinados a partir de parâmetros calibrados por validação temporal não melhoram a classificação e que nosso modelo de classificação baseado em Random Forest e treinado com características de classificadores do estado da arte e mais um novo conjunto de características proporcionou uma melhora significativa na discriminação dos RNAs codificantes e não codificantes. Por fim, destacamos o potencial do algoritmo Random Forest e das características utilizadas, diante deste problema de classificação, e sugerimos o uso do método de validação hold-out temporal para a obtenção de estimativas de desempenho mais fidedignas para os classificadores de RNAs codificantes e não codificantes de proteína. / Ribonucleic acids (RNAs) can be classified into two main classes: coding and non-coding of protein. The coding, represented by messenger RNAs (mRNAs), has the necessary information for protein synthesis. Non-coding RNAs (ncRNAs) are not translated into proteins but are involved in several distinct cellular activities associated with various diseases such as heart disease, cancer and psychiatric disorders. The discovery of new ncRNAs and their molecular roles favors advances in the knowledge of molecular biology and may also boost the development of new therapies against diseases. The identification of ncRNAs is an active area of research and one of the current methods is the classification of transcribed sequences using pattern recognition systems based on their characteristics. Many classifiers have been developed for this purpose, especially in the last three years. An example is the Coding Potential Calculator (CPC), based on Supporting Vector Machines (SVM). However, other robust algorithms are also recognized for their potential in classification tasks, such as Random Forest (RF). The most commonly used method for evaluating these tools has been cross-validation k-fold. An issue not considered in this form of validation is the assumption that frequency distributions within the database, in terms of sequence classes and other variables, do not change over time. If this assumption is not true, traditional methods such as cross-validation and hold-out may underestimate classification errors. The need for a validation method that takes into account the constant evolution of databases over time is therefore needed to provide a more realistic performance analysis of these classifiers. In this work we compare two methods of evaluation of classifiers: time hold-out and traditional hold-out (without considering the time). In addition, we tested new classification models from the combination of different induction algorithms with state-ofthe-art classifier characteristics and a new set of characteristics. From the hypothesis tests, we observe that both the traditional hold-out validation and the time hold-out validation tend to underestimate the classification errors, that the time validation evaluation is more reliable, than classifiers trained from parameters calibrated by time validation did not improve classification and that our Random Forest-based classification model trained with state-of-the-art classifier characteristics and a new set of characteristics provided a significant improvement in the discrimination of the coding and non-coding RNAs. Finally, we highlight the potential of the Random Forest algorithm and the characteristics used, in view of this classification problem, and we suggest the use of the time hold-out validation method to obtain more reliable estimates of the protein coding and non-coding RNA classifiers.

Går det att förutspå framtida aktiepriser genom att undersöka hur priser, på samma aktier, rört sig historisk? För att undersöka detta har vi använt oss av teknisk analys. Denna uppsats undersöker om teknisk analys på stockholmsbörsen kan användas för att uppnå högre avkastning än en s.k. Buy and Hold Strategi. I undersökningen används Relative Strength Index som teknisk analysmetod för att försöka förutspå framtida upp- och nedgångar i aktiepriser på tjugofem av de högst omsatta aktierna på Stockholmsbörsen. I undersökningen kompletteras Relative Strength Index med en Money Management strategi, som är till för att begränsa förlusterna. Undersökningsperioden sträcker sig mellan januari 2001 och juni 2008.   Svaga statistiska resultat, kombinerat med generellt sett lägre avkastningar, säger oss att förutspå framtida upp- och nedgångar på Stockholmsbörsen med hjälp av Relative Strength Index ej är att föredra framför strategin Buy and Hold.

In our pilot study investigating Texas Hold ‘em poker, we found that players bluffing (with a losing hand) elicits a similar physiological arousal response (as measured by skin conductance levels) to those in a position of strength and poised to win. Since arousal has been suggested to be a reinforcing factor in problematic gambling behaviour, we sought to replicate the findings of our pilot study in the current investigation. We aimed to extend our previous findings further by: isolating truthful betting (strong betting) to disambiguate deception when players are in positions of strength (i.e. trapping), measuring subjective excitement levels and risk assessments, investigating the physiological arousal responses following wins versus losses, and finally, exploring group differences (i.e. problem gambling status, experience levels). 71 participants played 20 naturalistic rounds of Texas Hold ‘em poker for monetary rewards. We were able to replicate our previous findings that bluffing triggers a physiological arousal (as measured by skin conductance responses) similar to truthful strong betting. Trapping was also found to elicit a skin conductance response similar to both bluffing and strong betting. Measures of subjective excitement revealed a pattern that converged with physiological data. Furthermore, wins were found to be more arousing than losses. Finally, our exploratory analysis of group differences (i.e. problem gambling status, experience) proved to be an insignificant factor with all measures. We conclude that the effect of bluffing on physiological arousal is so powerful that it pervades all participants; which is problematic due to its risky nature and potential to be self-triggered. With its ever increasing popularity and availability, more research on Texas Hold ‘em poker is warranted for treatment implications.