This master's thesis deals with timing effects in complex on chip systems. It is written in cooperation with the research and development centre of Infineon Technologies. One primary goal of all integrated circuit designers is to make the chips as small as possible. In deep sub micron designs timing effects like crosstalk have severe impact on the functionality of the chip. Therefore, accurate timing analyses must be made before the chip is ready for manufacturing. Otherwise the production yield can be reduced drastically. A case study on timing analysis with the 0.13 µm technology is made on the bus system of the device S-GOLD. The computer-based program PrimeTime is used to carry out the timing analysis. During the evolution of 0.13 µm technology three design packages have been developed to characterize the timing. Two releases of SGOLD have been designed based on the first and the second design package. The different design packages were compared, with and without pin capacitance variations, on chip variations and crosstalk. Furthermore the two releases are compared. The result from the analysis tool may not correlate well with what you see on the manufactured chips. In order to investigate the correlation, some tests were finally performed on an evaluation board. The results from the timing analysis are as expected. The second netlist version is better optimized than the first one. Design package three is most pessimistic among the three design packages. Design package one is most optimistic and does not match the real performance. Both design package two and three fit to the real performance well. Among the three design packages, design package three fits the real performance best.

Establishing a valid, reliable, and objective method for determining the number of functioning motor units in a muscle is important clinically, as it would provide a quantitative means of documenting changes in neuromuscular health over time. This thesis addressed the reliability of motor unit number estimates (MUNEs) derived using decomposition-based quantitative electromyography (DQEMG) from the extensor digitorum brevis (EDB) and abductor hallucis (AH) muscles. Additionally, the effect of the mean surface motor unit potential (SMUP) parameter averaging method (arithmetic/ensemble), the size-related parameter used to calculate MUNE (amplitude/area), and the type of SMUP marker editing (automatic/manual) was investigated in terms of MUNE values. Two separate analyses on a single data set collected from twenty healthy subjects on two occasions were conducted. MUNEs were calculated by dividing a size-related parameter (amplitude/area) of the compound muscle action potential (CMAP) by the same size-related parameter of a representative mean SMUP. First, paired t-tests investigated differences in MUNEs calculated using arithmetic and ensemble averaged SMUP parameters. Within- and between-day reliability of the two measurements was established using intra-class correlation coefficients (ICCs), coefficients of variation (CV), mean absolute differences (MAD), and Bland Altman limits of agreement (LOA). Second, MUNEs (using both parameters) derived from automated and manually edited SMUPs were compared. The effect of the size-related parameter and editing type was identified using a two-factor, repeated measures analysis of variance. Reliability was determined as described above. Arithmetic averaged SMUP parameters produced smaller MUNEs than those derived from ensemble averaging (p<0.001). SMUP area produced higher MUNEs than SMUP amplitude (p<0.05), except when using arithmetic averaged parameters in AH. Interaction effects between editing type and size parameter were present in both muscles (F>6.68, p<0.001). Between-day MUNEs had lower CVs and MADs, higher ICCs, and narrower LOAs than within-day MUNEs. MUNEs derived from arithmetic averaged SMUP parameters showed the highest reliability (ICCs>0.91). MUNEs calculated from automated SMUP marker placements were highly correlated (r>0.86) and displayed comparable reliabilities to those derived from manual marker placement (ICCs>0.90). To optimize the reproducibility of MUNEs calculated using DQEMG, while minimizing processing time, between-day automated estimates using arithmetic averaged SMUP amplitude is recommended. / Thesis (Master, Rehabilitation Science) -- Queen's University, 2012-08-30 08:32:06.141

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.

Master of Science / Department of Diagnostic Medicine/Pathobiology / Weiping Zhang / Enterotoxigenic Escherichia coli (ETEC) strains are the most common bacterial cause of diarrhea. ETEC bacterial adherence to the small intestinal epithelial cells and delivery of enterotoxins cause diarrhea in children living in developing countries and international travelers. Currently, there are no vaccines licensed for ETEC associated children’s diarrhea and travelers’ diarrhea. Recently, toxoid fusion 3xSTa[subscript N12S]-mnLT[subscript R192G/L211A] (toxoid fusion), adhesin MEFA (multiepitope fusion antigen) CFA/I/II/IV (CFA MEFA), and toxoid-adhesin MEFA CFA/I/II/IV-3xSTa[subscript N12S]-mnLT[subscript R192G/L211A] (CFA-toxoid MEFA) are demonstrated to induce neutralizing antitoxin and/or anti-adhesin antibodies in intraperitoneal (IP) or subcutaneous (SC) immunized mice, suggesting these antigens are potential candidates for ETEC subunit vaccines. However, these antigens have not been examined for immunogenicity using intradermal (ID) or intramuscular (IM) routes, the routes perhaps are more suitable for human vaccine administration. In this study, toxoid fusion 3xST[subscript aN12S]-mnLT[subscript R192G/L211A], CFA/I/II/IV MEFA, alone or combined, or toxoid-adhesin MEFA CFA-3xSTa[subscript N12S]-mnLT[subscript R192G/L211A] were ID or IM immunized to mice (8 mice per group) induced antigen-specific antibodies were titrated, and antibody neutralization activities were assessed in vitro. Data showed that mice ID or IM immunized with the toxoid fusion 3xSTa[subscript N12S]-mnLT[subscript R192G/L211A] antigen developed anti-LT and anti-STa antibodies and mice immunized with the CFA/I/II/IV MEFA developed antibody responses to all seven adhesins (CFA/I, CS1-CS6). In addition, mice co-administered ID or IM with toxoid fusion 3xSTa[subscript N12S]-mnLT[subscript R192G/L211A] and CFA/I/II/IV MEFA, or with toxoid-adhesin MEFA CFA-3xSTa[subscript N12S]-mnLT[subscript R192G/L211A] developed antibodies to both toxins and all seven adhesins. Antibody neutralization studies of the serum samples of the immunized mice showed that the induced antibodies neutralized enterotoxicity of LT and STa and/or inhibited adherence of ETEC or E. coli bacteria producing any of these seven adhesins. These data confirmed immunogenicity of these ETEC subunit vaccine target antigens and provide useful information for vaccine development against ETEC diarrhea.

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.

The significance of urban areas for military operations is increasing due to the proliferation of cities and the amount of people living in them; armed forces must, to a higher degree, fight in these urban areas in the future. This essay highlights that, despite the increasing importance of urban areas for armed forces, there is a lack of developed theory regarding how armed forces fight in urban areas and how tactics, techniques, and procedures result in casualties. Using previous research on urban warfare, this essay posits three hypotheses and applies these on exercises from the Swedish Armed Forces’ training area for military operations in urban terrain.        The results show that mortars are responsible for a large number of the casualties incurred during the exercises. When exercises involve vehicles the combat ranges, at which casualties are suffered, are longer in comparison to exercises without vehicles. A small percentage of casualties are suffered in close-quarters combat. Finally, the essay elaborates on the meaning of the results and offer some possible explanations that also are suitable for further research. It concludes that further research is warranted, especially regarding close-quarters combat and the use of hand grenades.

Symbolic dynamics is a current interest in the area of anomaly detection, especially in mechanical systems.  Symbolic dynamics reduces the overall dimensionality of system responses while maintaining a high level of robustness to noise.  Rolling element bearings are particularly common mechanical components where anomaly detection is of high importance.  Harsh operating conditions and manufacturing imperfections increase vibration innately reducing component life and increasing downtime and costly repairs.  This thesis presents a novel way to detect bearing vibrational anomalies through Symbolic Aggregate Approximation (SAX) in the two-dimensional time-frequency domain.  SAX reduces computational requirements by partitioning high-dimensional sensor data into discrete states.  This analysis specifically suits bearing vibration data in the time-frequency domain, as the distribution of data does not greatly change between normal and faulty conditions. Under ground truth synthetically-generated experiments, two-dimensional SAX in conjunction with Markov model feature extraction is successful in detecting anomalies (> 99%) using short time spans (< 0.1 seconds) of data in the time-frequency domain with low false alarms (< 8%).  Analysis of real-world datasets validates the performance over the commonly used one-dimensional symbolic analysis by detecting 100% of experimental anomalous vibration with 0 false alarms in all fault types using less than 1 second of data for the basis of 'normality'. Two-dimensional SAX also demonstrates the ability to detect anomalies in predicative monitoring environments earlier than previous methods, even in low Signal-to-Noise ratios. / Master of Science

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Apresenta-se, neste trabalho, o desenvolvimento de um modelo bioinspirado a partir do circuito neural de insetos. Este modelo é obtido através da análise de primeira ordem dada pelo STA (Spike Triggered Average) e pela transferência de informação entre os sinais neurais. São aplicadas técnicas baseadas na identificação dos atrasos de tempo da máxima coerência da informação. Utilizam-se, para esta finalidade, os conceitos da teoria de informação: a DMI (Delayed Mutual Information) e a TE (Transfer Entropy). Essas duas abordagens têm aplicação em transferência de informação, cada uma com suas particularidades. A DMI é uma ferramenta mais simples do que a TE, do ponto de vista computacional, pois depende da análise estatística de funções densidades de probabilidades de segunda ordem, enquanto que a TE, de funções de terceira ordem. Dependendo dos recursos computacionais disponíveis, este é um fator que deve ser levado em consideração. Os resultados de atraso da informação são muito bem identificados pela DMI. No entanto, a DMI falha em distinguir a direção do fluxo de informação, quando se tem sistemas com transferência de informação indireta e com sobreposição da informação. Nesses casos, a TE é a ferramenta mais indicada para a determinação da direção do fluxo de informação, devido à dependência condicional imposta pelo histórico comum entre os sinais analisados. Em circuitos neurais, estas questões ocorrem em diversos casos. No gânglio metatorácico de insetos, os interneurônios locais possuem diferentes padrões de caminhos com sobreposição da informação, pois recebem sinais de diferentes neurônios sensores para o movimento das membros locomotores desses animais. O principal objetivo deste trabalho é propor um modelo do circuito neural do inseto, para mapear como os sinais neurais se comportam, quando sujeitos a um conjunto de movimentos aleatórios impostos no membro do inseto. As respostas neurais são reflexos provocados pelo estímulo táctil, que gera o movimento na junção femorotibial do membro posterior. Nestes circuitos neurais, os sinais neurais são processados por interneurônios locais dos tipos spiking e nonspiking que operam em paralelo para processar a informação vinda dos neurônios sensores. Esses interneurônios recebem sinais de entrada de mecanorreceptores do membro posterior e da junção motora dos insetos. A principal característica dos interneurônios locais é a sua capacidade de se comunicar com outros neurônios, tendo ou não a presença de impulsos nervosos (spiking e nonspiking). Assim, forma-se um circuito neural com sinais de entradas (neurônios sensores) e saídas (neurônios motores). Neste trabalho, os algoritmos propostos analisam desde a geração aleatória dos movimentos mecânicos e os estímulos nos neurônios sensores que chegam até o gânglio metatorácico, incluindo suas respostas nos neurônios motores. São implementados os algoritmos e seus respectivos pseudocódigos para a DMI e para a TE. É utilizada a técnica de Surrogate Data para inferir as medidas de significância estatística em relação à máxima coerência de informação entre os sinais neurais. Os resultados a partir dos Surrogate Data são utilizados para a compensação dos erros de desvio das medidas de transferência de informação. Um algoritmo, baseado na IAAFT (Iterative Amplitude Adjusted Fourier Transform), gera os dados substitutos, com mesmo espectro de potência e diferentes distribuições dos sinais originais. Os resultados da DMI e da TE com os Surrogate Data fornecem os valores das linhas de base quando ocorre a mínima transferência de informação. Além disso, foram utilizados dados simulados, para uma discussão sobre os efeitos dos tamanhos das amostras e as forças de associação da informação. Os sinais neurais coletados estão disponíveis em um banco de dados com diversos experimentos no gânglio metatorácico dos gafanhotos. No entanto, cada experimento possui poucos sinais coletados simultaneamente; assim, para diferentes experimentos, os sinais ficam sujeitos às variações de tamanho de amostras, além de ruídos que interferem nas medidas absolutas de transferência de informação. Para se mapear essas conexões neurais, foi utilizada a metodologia baseada na normalização e compensação dos erros de desvio para os cálculos da transferência de informação. As normalizações das medidas utilizam as entropias totais do sistema. Para a DMI, utiliza-se a média geométrica das entropias de X e Y , para a TE aplica-se a CMI (Conditional Mutual Information) para a sua normalização. Após a aplicação dessas abordagens, baseadas no STA e na transferência de informação, apresenta-se o modelo estrutural do circuito neural do sistema neuromotor de gafanhotos. São apresentados os resultados com o STA e a DMI para os neurônios sensores, dos quais são levantadas algumas hipóteses sobre o funcionamento desta parte do FeCO (Femoral Chordotonal Organ). Para cada tipo de neurônio foram identificados múltiplos caminhos no circuito neural, através dos tempos de atraso e dos valores de máxima coerência da informação. Nos interneurônios spiking obtiveram-se dois padrões de caminhos, enquanto que para os interneurônios nonspiking identificaram-se três padrões distintos. Esses resultados são obtidos computacionalmente e condizem com que é esperado a partir dos modelos biológicos descritos em Burrows (1996). / Herein, we present the development of a bioinspired model by the neural circuit of insects. This model is obtained by analyzing the first order from STA (Spike Triggered Average) and the transfer of information among neural signals. Techniques are applied based on the identification of the time delays of the information maximum coherence. For this purpose we use the concepts of the theory of information: DMI (Delayed Mutual Information) and TE (Transfer Entropy). These two approaches have applications on information transfer and each one has peculiarities. The DMI is a simpler tool than the TE, from the computational point of view. Therefore, DMI depends on the statistical analysis of second order probability density functions, whereas the TE depends on third order functions. If computational resources are a problem, those questions can be taken into consideration. The results of the information delay are very effective for DMI. However, DMI fails to distinguish the direction of the information flow when we have systems subjected to indirect information transfer and superposition of the information. In these cases, the TE is the most appropriate tool for determining the direction of the information flow, due to the conditional dependence imposed by a common history among the signals. In neural circuits, those issues occur in many cases. For example, in metathoracic ganglion of insects, the local interneurons have different pathways with superposition of the information. Therefore, the interneurons receive signals from different sensory neurons for moving the animals legs . The main objective of this work is propose a model of the neural circuit from an insect. Additionally, we map the neural signals when the hind leg is subjected to a set of movements. Neural responses are reflexes caused by tactile stimulus, which generates the movement of femoro-tibial joint of the hind leg. In these neural circuits, the signals are processed by neural spiking and nonspiking local interneurons. These types of neurons operate in parallel processing of the information from the sensory neurons. Interneurons receive input signals from mechanoreceptors by the leg and the insect knees. The main feature of local interneurons is their ability to communicate with others neurons. It can occur with or without of the presence of impulses (spiking and nonspiking). Thus, they form a neural circuit with input signals (sensory neurons) and outputs (motor neurons). The proposed algorithms analyze the random generation of movements and mechanical stimuli in sensory neurons. Which are processing in the metathoracic ganglion, including their responses in the motor neurons. The algorithms and the pseudo-code are implemented for TE and DMI. The technique of Surrogate Data is applied to infer the measures of statistical significance related to the information maximum coherence among neural signals. The results of the Surrogate Data are used for bias error compensation from information transfer. An algorithm, based on IAAFT (Iterative Amplitude Adjusted Fourier Transform), generates Surrogate Data with the same power spectrum and different distributions of the original signals. The results of the surrogate data, for DMI and TE, achieve the values of baselines when there are minimum information transfer. Additionally, we used simulated data to discuss the effects of sample sizes and different strengths of information connectivity. The collected neural signals are available from one database based on several experiments of the locusts metathoracic ganglion. However, each experiment has few simultaneously collected signals and the signals are subjected of variations in sample size and absolute measurements noisy of information transfer. We used a methodology based on normalization and compensation of the bias errors for computing the information transfer. The normalization of the measures uses the total entropy of the system. For the DMI, we applied the geometric mean of X and Y . Whereas, for the TE is computed the CMI (Conditional Mutual Information) for the normalization. We present the neural circuit structural model of the locusts neuromotor system, from those approaches based on STA and the information transfer. Some results are presented from STA and DMI for sensory neurones. Then, we achieve some new hypothesis about the neurophisiology function of FeCO. For each type of neuron, we identify multiple pathways in neural circuit through the time delay and the information maximum coherence. The spiking interneurons areyielded by two pathways, whereas the nonspiking interneurons has revealed three distinct patterns. These results are obtained computationally and are consistent with biological models described in Burrows (1996).