A large number and variety of genome-wide genomics and proteomics datasets are now available for model organisms. Each dataset on its own presents a distinct but noisy view of cellular state. However, collectively, these datasets embody a more comprehensive view of cell function. This motivates the prediction of function for uncharacterized genes by combining multiple datasets, in order to exploit the associations between such genes and genes of known function--all in a query-specific fashion. Commonly, heterogeneous datasets are represented as networks in order to facilitate their combination. Here, I show that it is possible to accurately predict gene function in seconds by combining multiple large-scale networks. This facilitates function prediction on-demand, allowing users to take advantage of the persistent improvement and proliferation of genomics and proteomics datasets and continuously make up-to-date predictions for large genomes such as humans. Our algorithm, GeneMANIA, uses constrained linear regression to combine multiple association networks and uses label propagation to make predictions from the combined network. I introduce extensions that result in improved predictions when the number of labeled examples for training is limited, or when an ontological structure describing a hierarchy of gene function categorization scheme is available. Further, motivated by our empirical observations on predicting node labels for general networks, I propose a new label propagation algorithm that exploits common properties of real-world networks to increase both the speed and accuracy of our predictions.

A large number and variety of genome-wide genomics and proteomics datasets are now available for model organisms. Each dataset on its own presents a distinct but noisy view of cellular state. However, collectively, these datasets embody a more comprehensive view of cell function. This motivates the prediction of function for uncharacterized genes by combining multiple datasets, in order to exploit the associations between such genes and genes of known function--all in a query-specific fashion. Commonly, heterogeneous datasets are represented as networks in order to facilitate their combination. Here, I show that it is possible to accurately predict gene function in seconds by combining multiple large-scale networks. This facilitates function prediction on-demand, allowing users to take advantage of the persistent improvement and proliferation of genomics and proteomics datasets and continuously make up-to-date predictions for large genomes such as humans. Our algorithm, GeneMANIA, uses constrained linear regression to combine multiple association networks and uses label propagation to make predictions from the combined network. I introduce extensions that result in improved predictions when the number of labeled examples for training is limited, or when an ontological structure describing a hierarchy of gene function categorization scheme is available. Further, motivated by our empirical observations on predicting node labels for general networks, I propose a new label propagation algorithm that exploits common properties of real-world networks to increase both the speed and accuracy of our predictions.

One of the challenges of distributed cooperative orthogonal frequency division multiplexing systems is that the multiple carrier frequency offsets (CFOs) simultaneously present at the receiver. According to our knowledge up to now, even the CFOs are known at the receiver, the way to perfectly eliminate the effect of CFOs is still an open problem. This thesis proposes a scheme to mitigate the effect due to multiple CFOs by using the concept of intercarrier interference self-cancellation in transitional OFDM systems, a scheme where the data are simultaneously modulated on symmetric subcarriers between two transmit antennas. Before processing FFT, two values related to CFOs are used to adjust the time-domain signal resulting in better signal-to-interference ratio in even and odd subcarriers respectively. After that, the data are combined by applying maximum ratio combining and then decoded. Simulation results are given to demonstrate the effectiveness of the proposed scheme as compared to previous scheme.

Synthetic hexaploid wheats, created from a durum (Triticum durum) cross to Aegilops tauschii Coss. (McFadden and Sears, 1946), proved to be an efficient and beneficial source of new genes for common bread wheat (Triticum aestivum L). The purpose of this research was to evaluate the potential and performance of synthetic wheat in Texas. Ten elite primary synthetics from the International Maize and Wheat Improvement Center (CIMMYT), screened for desirable traits, were backcrossed to two Texas cultivars, TAM 111 and TAM 112. Populations were bulked and modified bulked to advance generations. Agronomic traits related to yield were determined on the F4 and F5 Improvement was observed in South Texas and the Blacklands, which have more disease pressure and fewer intermittent dry spells than another two locations at Chillicothe and Bushland in Texas Rolling and High Plains, respectively. Selected bulks were not superior to non-selected bulks. Head number per unit area had the highest correlation with yield and seed weight was the most heritable trait. Synthetic lines combined better with TAM 111 than TAM 112 in high yielding environments. populations across five Texas locations. Similar to crosses with spring wheat, synthetics contributed to yield through an increase in seed weight. Synthetic populations that produced higher grain yield than both TAM 111 and TAM 112 were able to maintain their large seed size and weight while improving their seed per head and head number traits. Poorer performance in environments with harsh winters could be due to a lack of winter-hardiness in the primary synthetics. This clearly demonstrates that improving yield, through utilization of common wheat by synthetic crosses, could result from selecting for larger seed per head and heads per unit area in lines driven from these populations. Introgression of new genes through synthetic backcrosses could contribute to the improvement of wheat in particular regions of Texas. Primary synthetics and recurrent parents combining for superior hybrids were identified.

Maize is susceptible to biotic and abiotic stresses. The most important abiotic stresses in Africa are drought and low soil fertility. Aflatoxin contamination is a potential problem in areas facing drought and low soil fertility. Three studies were conducted to evaluate maize germplasm for tolerance to stress. In the first study, fifteen maize inbred lines crossed in a diallel were evaluated under drought, low N stress, and well-watered conditions at six locations in three countries to estimate general (GCA) and specific combining ability (SCA), investigate genotype x environment interaction, and estimate genetic diversity and its relationship with grain yield and heterosis. GCA effects were not significant for grain yield across environments. Lines with good GCA effect for grain yield were P501 and CML258 across stresses. Lines CML339, CML341, and SPLC7-F had good GCA effects for anthesis silking interval across stresses. Additive genetic effects were more important for grain yield under drought and well-watered conditions. Heterosis estimates were highest in stress environments. Clustering based on genetic distance calculated using marker data from AFLP, RFLP, and SSRs grouped lines according to origin. Genetic distance was positively correlated with grain yield and specific combining ability. In the second study, synthetic hybrids were evaluated at seven locations in three countries to estimate GCA and SCA effects under low N stress and optimal conditions and investigate genotype x environment interaction. GCA effects were significant for all traits across low N stress and optimal conditions. The highest yielding synthetic hybrids involved synthetics developed from stress tolerant lines. Synthetics 99SADVIA-# and SYNA00F2 had good GCA for grain yield across low N stress conditions. Heterosis was highly correlated with grain yield. Optimal environments explained more variation than stress environments. The third study evaluated the agronomic performance and aflatoxin accumulation of single and three-way cross white maize hybrids at five locations in Texas. Inbreds CML343, Tx601W, and Tx110 showed positive GCA effects for grain yield. Significant GCA effects for reduced aflatoxin concentration were observed in lines CML269, CML270, and CML78 across locations. Differences in performance between single and three-way crosses hybrids were dependent mostly on the inbred lines.

The explosive growth of the wireless market has increased the demand for low-cost, highly-integrated CMOS wireless transceivers. However, the implementation of CMOS RF power amplifiers remains a formidable challenge. The objective of this research is to demonstrate the feasibility of CMOS RF power amplifiers by compensating for the RF performance disadvantages of CMOS technology. This dissertation proposes a parallel-combining transformer (PCT) as an impedance-matching and output-combining network. The results of a comprehensive analysis show that the PCT is a suitable solution for watt-level output power generation in cellular applications. To achieve high output power and high efficiency, the work presented here entailed the design of a class-E switching power amplifier in a 0.18-μm CMOS technology for GSM applications and, with the suggested power amplifier design technique, successfully demonstrated a fully-integrated RF front-end consisting of a power amplifier and an antenna switch. This dissertation also proposed an efficiency enhancement technique at power back-off. In an effort to save current in the power back-off while satisfying the EVM requirements, a class-AB linear power amplifier was implemented in a 0.18-μm CMOS technology for WLAN and WiMAX applications using a PCT as well as an operation class shift between class-A and class-B. Thus, the research in this dissertation provides low-cost CMOS RF power amplifier solutions for commercial products used in mobile wireless communications.

<p>The well-known Dijkstra's algorithm uses weights to determine the shortest path. The focus here is instead on the opposite problem, does there exist weights for a certain set of shortest paths? OSPF (Open Shortest Path First) is one of several possible protocols that determines how routers will send data in a network like the internet. Network operators would however like to have some control of how the traffic is routed, and being able to determine the weights, which would lead to the desired shortest paths to be used, would be a help in this task.The first part of this thesis is a mathematical explanation of the problem with a lot of examples to make it easier to understand. The focus here is on trying to combine several routing patterns into one, so that the result will be fewer, but more fully spanned, routing patterns, and it can e.g. be shown that there can't exist a common set of weights if two routing patterns can't be combined.The second part is a program that can be used to make several tests and changes to a set of routing patterns. It has a polynomial implementation of a function that can combine routing patterns. The examples that I used to combine routing patterns, showed that this will increase the likelihood of finding and significantly speed up the computation of a “valid cycle”.</p> / Egentligen 30p/45hp, men det fanns inte som alternativ.

Phase control in microwave circuits is an impotant process. Especially, in certain applications such as phase array antennas, it is the main principle of opeation. In antenna arrays, each array element is fed by an individual oscillator. By controlling the phase of each oscillator, the radiation pattern and the RF power can be combined in space in certain directions. For such applications, phase shifters have been utilized extensively. However, their high costs, difficulties in design and efficiency are impotant disadvantages. More recently, another technique, &quot / Injection Locking&quot / or &quot / Phase Locking&quot / suggests to use a single reference signal injected into each oscilator element. Through this signal, the phase of the individual oscillators can be controlled and set to a desired value. Therefore, power combining in space or known as &quot / Spaial Power Combining&quot / is possible by using &quot / Phase Locking&quot / of individual oscillator elements. In this thesis, this new phase control technique is examined in theory and in application of a 1GHz oscillator system. A reference signal is injected into a voltage controlled oscillator, and the phase progression is obtained by tuning the oscilator&#039 / s free running frequency.

abstract: To establish reliable wireless communication links it is critical to devise schemes to mitigate the effects of the fading channel. In this regard, this dissertation analyzes two types of systems: point-to-point, and multiuser systems. For point-to-point systems with multiple antennas, switch and stay diversity combining offers a substantial complexity reduction for a modest loss in performance as compared to systems that implement selection diversity. For the first time, the design and performance of space-time coded multiple antenna systems that employ switch and stay combining at the receiver is considered. Novel switching algorithms are proposed and upper bounds on the pairwise error probability are derived for different assumptions on channel availability at the receiver. It is proved that full spatial diversity is achieved when the optimal switching threshold is used. Power distribution between training and data codewords is optimized to minimize the loss suffered due to channel estimation error. Further, code design criteria are developed for differential systems. Also, for the special case of two transmit antennas, new codes are designed for the differential scheme. These proposed codes are shown to perform significantly better than existing codes. For multiuser systems, unlike the models analyzed in literature, multiuser diversity is studied when the number of users in the system is random. The error rate is proved to be a completely monotone function of the number of users, while the throughput is shown to have a completely monotone derivative. Using this it is shown that randomization of the number of users always leads to deterioration of performance. Further, using Laplace transform ordering of random variables, a method for comparison of system performance for different user distributions is provided. For Poisson users, the error rates of the fixed and random number of users are shown to asymptotically approach each other for large average number of users. In contrast, for a finite average number of users and high SNR, it is found that randomization of the number of users deteriorates performance significantly. / Dissertation/Thesis / Ph.D. Electrical Engineering 2010

[pt] A presente dissertação tem por objetivo o estudo quantitativo da previsão da demanda de carga elétrica semanal para a região sudeste e em particular, para os Estados do Rio de Janeiro e São Paulo. Foram estudadas para tanto as séries reais dos últimos 7(sete) anos, ou seja, de janeiro de 1991 a novembro de 1997 das concessionárias LIGHT, CERJ, CESP, CPFL e ELETROPAULO. Para o estudo de previsão foi utilizado o conceito in sample, ou seja, parte real dos dados foram separados e mais tarde comparados com os valores previstos experimentalmente para aquela mesma época dos dados reais separados. Desta forma, permitiu-se averiguar qual seria a precisão da previsão, verificando-se os erros entre os valores experimentais e reais. Para os cálculos das previsões, também foi utilizado o conceito de bayesiano de combinação de previsões (outperformance) das duas técnicas a saber: redes neurais artificiais (software Neunet) e o modelo clássico Box & Jenkins (software Autobox). Para se obter o valor combinado das previsões, foi utilizado software matlab que se comportou de maneira adequada para o estudo em questão. Além disso vale acrescentar que o software Neunet foi utilizado, pois possui em seu ambiente a técnica de eliminação de sinapses enquadra-se dentro do conceito de redes neurais multicamadas com retropropagação dos erros. / [en] The goal of this dissertation is to present a quantitative study in time series of weekly electrical charge demand at the southeast region, particulary at Rio de Janeiro and São Paulo. In this work will be analysed the last 7 years, from january 1991 to november of 1997. The next time series were study: LIGHT, CERJ, CESP, CPFL and ELETROPAULO. Aimming to test the model against real data the concept of sample data was utilized in this dissertation. Another concept used in this work was outperformance. Outperformance is a Bayesian concept that involves the combination of two or more techniques in order to enchance the forecasting results. Artificial neural network and Box and Jenkins method are combined in this work. It is also interesting to notice that weight elimination, which is a new ANN technique, proved to be faster then classical back- propagation and yielded better results.