Ultra high frequency (UHF) radio frequency identification (RFID) systems suffer from issues that limit their widespread deployment and limit the number of applications where they can be used. These limitations are: lack of a well defined read zone, interference, and environment sensitivity. To overcome these limitations a novel receiver device is introduced into the system. The use of such device or devices mitigates the issues by enabling more "anchor points" in the system. Two such devices exist in industry and academia: the Astraion Sensatag and the Gen2 Listener. The drawbacks of the Sensatag is that it offers poor performance in capturing tag signals. The Gen2 Listener is based on the expensive software defined radio hardware. The purpose of the thesis was to develop a receiver that will enable several new RFID applications that are not available with current RFID systems. The receiver, named ARR (Augmented RFID Receiver), receives tag and reader signals, which are decoded by an FPGA and the results are reported through Ethernet. This device is central to the augmented RFID system. To show the suitability of such an approach, the performance of the implementation was compared to the other two outlined solutions. A comparison of the read rate and range of the implementations were the defining factors. The analysis showed that the ARR is capable of receiving tag signals with a read rate of 50% for passive and 66% for semi-passive tags at a one meter distance and is capable of receiving tag signals at a maximum of 3.25 meters for passive and 5.5 meters for semi- passive tags, with the reader being within 8 meters of the ARR. Two applications were implemented to showcase the ARR: an RFID portal and protocol analyzer.

We consider asynchronous multiprocessors where processes communicate only by reading or writing shared memory. We show how to implement consensus, all comparison primitives (such as CAS and TAS), and load-linked/store-conditional using only a constant number of remote memory references (RMRs), in both the cache-coherent and the distributed-shared-memory models of such multiprocessors. Our implementations are blocking, rather than wait-free: they ensure progress provided all processes that invoke the implemented primitive are live. Our results imply that any algorithm using read and write operations, comparison primitives and load-linked/store-conditional, can be simulated by an algorithm that uses read and write operations only, with at most a constant-factor increase in RMR complexity.

Two studies were designed to characterize the effects of a non-steroidal aromatase inhibitor, letrozole, on ovarian function in cattle. The specific objective was to test the hypothesis that letrozole will arrest dominant follicle growth resulting in emergence of a new follicular wave at a predictable interval post-treatment. In a first experiment, postpubertal beef heifers were assigned randomly to four treatment groups and given phosphate-buffered saline (controls; n=10), or letrozole at a dose of 500 (n=9), 250 (n=10), or 125 (n=10) µg/kg intravenously 4 days after follicular ablation (~2.5 days after wave emergence). In a second study, postpubertal beef heifers were assigned randomly to four treatment groups. One group received no treatment (control; n=17) and the other groups (n=9-10) were given 85 µg/kg of letrozole per day (250 µg/kg total dose), from Days 1 to 3, Days 3 to 5, or Days 5 to 7 (Day 0 = pre-treatment ovulation,) corresponding to the periods before, during and after selection of the dominant follicle, respectively. Follicular dynamics were monitored ultrasonically and blood samples were collected for endocrine assays. Follicle diameter profiles and plasma LH, FSH, and estradiol concentrations were analyzed. Additionally, during the second trial, CL diameter profiles and plasma progesterone concentrations were measured. In both studies, the diameter profile of the dominant follicle was larger in heifers treated with letrozole than in control heifers (P<0.05) and the intervals to new wave emergence and onset of regression of the extant dominant follicle were longer (P<0.05) in heifers treated with letrozole than in controls, regardless of the dose (high, medium, or low; single vs multiple) and the stage of the follicle wave in which treatments were initiated. Furthermore, during the second experiment, the mean CL diameter was larger in letrozole-treated heifers, although there were no differences in plasma progesterone concentrations between treated and control animals. The effects on dominant follicle and CL diameter profiles appeared to be the result of the significantly increased plasma LH concentrations observed in letrozole-treated animals during both treatment approaches (single vs multiple dose). Incomplete and inconsistent inhibition of estradiol production and the lack of a surge on FSH observed in both experiments may be a result of insufficient circulating levels of letrozole during the treatment period. In summary, a single or multiple dose of letrozole did not induce regression of the extant dominant follicle, nor did it directly affect FSH release. Conversely, letrozole extended the lifespan of the dominant follicle, in association with increased endogenous levels of LH, thereby delaying the next FSH surge and subsequent follicular wave emergence. Results suggest that letrozole has potential as a non-steroidal method for controlling ovarian function in cattle, but further studies are warranted to clarify dosage and timing of treatment to predictably affect follicular wave dynamics in cattle.

We consider asynchronous multiprocessors where processes communicate only by reading or writing shared memory. We show how to implement consensus, all comparison primitives (such as CAS and TAS), and load-linked/store-conditional using only a constant number of remote memory references (RMRs), in both the cache-coherent and the distributed-shared-memory models of such multiprocessors. Our implementations are blocking, rather than wait-free: they ensure progress provided all processes that invoke the implemented primitive are live. Our results imply that any algorithm using read and write operations, comparison primitives and load-linked/store-conditional, can be simulated by an algorithm that uses read and write operations only, with at most a constant-factor increase in RMR complexity.

The hippocampus is one of the most intensely studied brain structures and the oscillatory activity of the hippocampal neurons is believed to be involved in learning and memory consolidation. Therefore, studying rhythm generation and modulation in this structure is an important step in understanding its function. In this thesis, these phenomena are studied via mathematical models of networks of hippocampal interneurons. The two types of neural networks considered here are homogenous and heterogenous networks. In homogenous networks, the input current to each neuron is equal, while in heterogenous networks, this assumption is relaxed and there is a specified degree of heterogeneity in the input stimuli. A phase reduction technique is applied to the neural network model of the hippocampal interneurons and attempts are made to understand the implications of heterogeneity to the existence and stability of the synchronized oscillations. The Existence of a critical level of heterogeneity above which the synchronized rhythms are not stable is established, and linear analysis is applied to derive expressions for estimating the perturbations in the network frequency and timing of the neural spikes. The mathematical techniques developed in this thesis are general enough to be applied to models describing other types of neurons not considered here. Possible biological implications include the application of high frequency local stimulation to alleviate the synchronous neural oscillations in pathological conditions such as epilepsy and Parkinson's disease and the possible role of heterogeneity in controlling the rhythm frequency and switching between various cognitive states.

All large-scale digital Integrated Circuits need an appropriate strategy for clocking and synchronization. In large-scale and high-speed System-on-Chips (SoC), the traditional"Globally Synchronous"(GS) approach is not longer viable, due to severe wire delays. Instead new solutions as"Globally Synchronous, Locally Asynchronous"(GALS) approaches have been proposed. We propose to replace the GALS approach with a mesochronous clocking principle. In this work, such an approach together with a circuit solution in 0.18mm CMOS process has been presented. This solution allows clocking frequencies up to 4 GHz.

The hippocampus is one of the most intensely studied brain structures and the oscillatory activity of the hippocampal neurons is believed to be involved in learning and memory consolidation. Therefore, studying rhythm generation and modulation in this structure is an important step in understanding its function. In this thesis, these phenomena are studied via mathematical models of networks of hippocampal interneurons. The two types of neural networks considered here are homogenous and heterogenous networks. In homogenous networks, the input current to each neuron is equal, while in heterogenous networks, this assumption is relaxed and there is a specified degree of heterogeneity in the input stimuli. A phase reduction technique is applied to the neural network model of the hippocampal interneurons and attempts are made to understand the implications of heterogeneity to the existence and stability of the synchronized oscillations. The Existence of a critical level of heterogeneity above which the synchronized rhythms are not stable is established, and linear analysis is applied to derive expressions for estimating the perturbations in the network frequency and timing of the neural spikes. The mathematical techniques developed in this thesis are general enough to be applied to models describing other types of neurons not considered here. Possible biological implications include the application of high frequency local stimulation to alleviate the synchronous neural oscillations in pathological conditions such as epilepsy and Parkinson's disease and the possible role of heterogeneity in controlling the rhythm frequency and switching between various cognitive states.

Two studies were designed to characterize the effects of a non-steroidal aromatase inhibitor, letrozole, on ovarian function in cattle. The specific objective was to test the hypothesis that letrozole will arrest dominant follicle growth resulting in emergence of a new follicular wave at a predictable interval post-treatment. In a first experiment, postpubertal beef heifers were assigned randomly to four treatment groups and given phosphate-buffered saline (controls; n=10), or letrozole at a dose of 500 (n=9), 250 (n=10), or 125 (n=10) µg/kg intravenously 4 days after follicular ablation (~2.5 days after wave emergence). In a second study, postpubertal beef heifers were assigned randomly to four treatment groups. One group received no treatment (control; n=17) and the other groups (n=9-10) were given 85 µg/kg of letrozole per day (250 µg/kg total dose), from Days 1 to 3, Days 3 to 5, or Days 5 to 7 (Day 0 = pre-treatment ovulation,) corresponding to the periods before, during and after selection of the dominant follicle, respectively. Follicular dynamics were monitored ultrasonically and blood samples were collected for endocrine assays. Follicle diameter profiles and plasma LH, FSH, and estradiol concentrations were analyzed. Additionally, during the second trial, CL diameter profiles and plasma progesterone concentrations were measured. In both studies, the diameter profile of the dominant follicle was larger in heifers treated with letrozole than in control heifers (P<0.05) and the intervals to new wave emergence and onset of regression of the extant dominant follicle were longer (P<0.05) in heifers treated with letrozole than in controls, regardless of the dose (high, medium, or low; single vs multiple) and the stage of the follicle wave in which treatments were initiated. Furthermore, during the second experiment, the mean CL diameter was larger in letrozole-treated heifers, although there were no differences in plasma progesterone concentrations between treated and control animals. The effects on dominant follicle and CL diameter profiles appeared to be the result of the significantly increased plasma LH concentrations observed in letrozole-treated animals during both treatment approaches (single vs multiple dose). Incomplete and inconsistent inhibition of estradiol production and the lack of a surge on FSH observed in both experiments may be a result of insufficient circulating levels of letrozole during the treatment period. In summary, a single or multiple dose of letrozole did not induce regression of the extant dominant follicle, nor did it directly affect FSH release. Conversely, letrozole extended the lifespan of the dominant follicle, in association with increased endogenous levels of LH, thereby delaying the next FSH surge and subsequent follicular wave emergence. Results suggest that letrozole has potential as a non-steroidal method for controlling ovarian function in cattle, but further studies are warranted to clarify dosage and timing of treatment to predictably affect follicular wave dynamics in cattle.

The detection for phase locking in a forced oscillator with dual attractors and ill-defined phase structure is hard until a quantitative approach was constructed for detecting phase locking via stroboscopic method. We study the route to weak phase locking in a chaotic system ¡§Chua oscillator¡¨ with complex attractor structure by analyzing the stroboscopic points. The onset of weak phase locking detected by using this statistical approach and the critical coupling strength calculated by conditional Lyapunov exponent are matched well. Detailed structure of phase locking intensity is described by the Arnold tongue diagram. Moreover, we apply this approach on three hyper-chaotic systems with multi-scroll attractor, including hyper-chaotic Rössler system, hyper-chaotic Lorenz system, and modified MCK oscillator. The weak phase locking between hyper-chaotic system and a periodic or a chaotic driving force is observable following the condition of stroboscopic point concentration.

Synchronization of two identical chaotic systems with matched and mismatched perturbations by utilizing adaptive sliding mode control (ASMC) technique is presented in this thesis. The sliding surface function is designed based on Lyapunov stability theorem and linear matrix inequality (LMI) optimization technique. Adaptive mechanisms embedded in the proposed control scheme are used to adapt the unknown upper bounds of the perturbations. The designed tracking controller can not only suppress the mismatched perturbations when the controlled dynamics (master-slave) are in the sliding mode, but also drive the trajectories of synchronization errors into a small bounded region whose size can be adjusted through the designed parameters. The stability of overall controlled synchronization systems is guaranteed. Application of proposed chaotic synchronization technique to secure communication as well as several numerical examples are given to demonstrate the feasibility of the proposed design technique.