The first part of this thesis proposes a method to synthesize the T- and £S-prototype of band-pass filters using the two reflection zeros and the rolloff rate. According to the characteristics of passive components embedded in different substrates, £S-prototype band-pass filter is suitable for implementation on LTCC substrate, while T-prototype band-pass filter is suitable for implementation on organic substrate. The second part of this thesis employs the £S-prototype to design the LTCC band-pass filters. It has been found that mutual coupling and feedback elements can be used to create the multiple transmission zeros. With these synthesized transmission zeros, the stopband attenuation can be enhanced at several specific frequencies. For demonstration, this thesis implements the LTCC band-pass filters in 2.4 GHz ISM band and 3.5 GHz WiMAX band. The measured results show that insertion loss and return loss in the passband for these LTCC filters is less than 2 dB and more than 10 dB, respectively. In addition, these filters have the additional transmission zeros for enhancing the stopband attenuation. Moreover, miniaturization is also a key issue in implementing these LTCC filters. The 2.4 GHz and 3.5 GHz LTCC filter can meet the standard 1608 size and 2520 size, respectively, which are the smallest compared to the other LTCC filters reported for similar applications in the current literature and commercial media.

Abstract: This thesis is concerned with the acquisition of body signals using a sampling system. A typical application is the recording of the electrocardiogram (ECG). It is proposed to sample the input signal at different rates, depending on the momentary signal content. If the input signal has large voltage variation, it is sampled at a high rate. During periods of small variation, the signal is sampled at a lower frequency to save both memory and power. An analog controller to control the clock rate is proposed and implemented. The analog controller decides the sample frequency (high rate or low rate) depending on the input signal. The analysis of the proposed system is presented in this thesis. Furthermore, a working prototype is implemented using discrete components on a PCB. The measured results show a significant reduction in the average sample frequency and data rate of 50% and 35%, respectively. Finally, the critical analog circuit blocks of the system suitable for integration on chip are proposed and implemented in a 0.35£gm CMOS process. Measured results are reported to confirm the functionality of the blocks.

Human-induced climate change, with its potentially catastrophic impacts on weather patterns, water resources, ecosystems, and agricultural production, is the toughest global problem of modern times. Impeding catastrophic climate change necessitates the widespread deployment of renewable energy technologies for reducing the emissions of heat-trapping gases, especially carbon di-oxide (CO₂). However, the deployment of renewable energy technologies is plagued by various market failures, such as environmental externalities from conventional energy sources, learning-by-doing, innovation spillover effects, and peer effects. In efforts to begin to address these market failures, several governments at all levels—city, state, regional, and national—have instituted various subsidies for promoting the adoption of renewable energy technologies. Public resources are limited and have competing uses. So, it is important to ask: how cost-effective are renewable energy subsidies? Are the subsidies even reaching the intended subjects—the potential adopters of renewable energy technologies? In this empirically-driven dissertation, I analyze these important policy design and evaluation questions with a focus on the solar subsidy programs in California. All programs to incentivize the adoption of renewable energy technologies run into the same key question: what is the optimal (maximum capacity inducing) rebate schedule in the face of volatile product prices and the need for policy certainty? Answering this question requires careful attention to both supply-side (learning-by-doing) and demand-side (peer effects) market dynamics. I use dynamic programming to analyze the effectiveness of the largest state-level solar photovoltaic (PV) subsidy program in the U.S. – the California Solar Initiative (CSI) – in maximizing the cumulative PV installation in California under a budget constraint. I find that previous studies overestimated learning-by-doing in the solar industry. Consistent with other studies, I also find that peer effects are a significant demand driver in the California solar market. The main implication of this empirical finding in the dynamic optimization context is that it forces the optimal solution towards higher subsidies in earlier years of the program, and, hence, leads to a lower program duration (for the same budget). In particular, I find that the optimal rebate schedule would start not at $2.5/W as it actually did in CSI, but instead at $4.2/W; the effective policy period would be only three years instead of the realized period of six years. This optimal (i.e., most cost effective) solution results in total PV adoption of 32.2 MW (8.1%) higher than that installed under CSI, using the same budget. Furthermore, I find that the optimal rebate schedule starts to look like the actual CSI in a ‘policy certainty’ scenario where the variation of periodic subsidy-level changes is constrained. Finally, introduction of stochastic learning-by-doing as a way to better capture the dynamic nature of learning in markets for new products does not yield significantly different results compared to the deterministic case. Another, still-unanswered, redistribution question related to the CSI program is: to what degree have the direct PV incentives in California been passed through from installers to consumers? I address this question by carefully examining the residential PV market in California by applying multiple methods. Specifically, I apply a structural-modeling approach, a reduced-form regression analysis, and regression discontinuity designs to estimate the incentive pass-through rate in California’s solar program. The results consistently suggest a high average pass-through rate of direct incentives of nearly 100%, though with regional differences among California counties and utilities. While these results could have multiple explanations, they suggest a relatively competitive market and a smoothly operating subsidy program. Combining evidence from the optimal subsidy policy design and the incentive pass-through analysis, this dissertation lends credibility to the cost-effectiveness of CSI given CSI’s design goal of providing policy certainty and also finds a near-perfect incidence in CSI. Long-term credible commitment as reflected through CSI’s capacity-triggered step changes in rebates along with policy and data transparency are important factors for CSI’s smooth and cost-effective functioning. Though CSI has now wound down because final solar capacity targets have been reached, the historical performance of CSI is relevant not only as an ex-post analysis in California, but potentially has broader policy implications for other solar incentive programs both nationally and internationally. / text

Στην παρούσα διπλωματική ασχοληθήκαμε με την εύρεση του καρδιακού ρυθμού ενός ατόμου με τεχνικές ψηφιακής επεξεργασίας εικόνας στο κοντινό και στο μέσο υπέρυθρο φάσμα. Χρησιμοποιήσαμε μια σειρά από διόδους εκπομπής στο υπέρυθρο φάσμα και μια βιντεοκάμερα με την οποία πήραμε τα προς εξέταση δεδομένα. Στηριζόμαστε στην ιδιότητας της αιμοσφαιρίνης να απορροφά το υπέρυθρο φως ορισμένου μήκους κύματος. Επεξεργαζόμενοι το οπτικό υλικό που προκύπτει από τις μετρήσεις μας με κατάλληλες μεθόδους μπορούμε να πλησιάσουμε στην εύρεση του καρδιακού ρυθμού, μελετώντας τα βιολογικά σήματα και ευρίσκοντας μεθόδους βελτίωσης τους. / -

All-fiber multireflector spectral filters which have potential application in optical communications have been investigated experimentally. These multireflector etalons were produced by aligning equal-length fiber sections with TiO2/SiO2 dielectric mirrors deposited on the end in a silicon v-groove. Fiber sections 1.33mm in length were produced by polishing, with the fibers held in a silicon wafer polishing jig. The fibers were aligned inside the polishing jig using a precision micro positioner. Then four polishing steps with increasingly finer grit were applied to produce high-quality polished end surfaces on each fiber section. Finally, a dielectric mirror was deposited on one end of each fiber section by magnetron sputtering. After characterizing the optical loss, length, and mirror reflectance for each of the fiber sections, sections which were well-matched in length were chosen for assembly of the four-mirror etalon, which had nominal reflectance values of 10%, 50%, 50%, and 10% for the dielectric mirrors. Measured transmittance spectra for a mutireflector spectral filter were compared with calculated spectra. Thermal tuning of the multireflector etalon was also investigated. A 0.34 nm wavelength shift was observed for a 23° C temperature change, in agreement with prediction. increasingly finer grit were applied to produce high-quality polished end surfaces on each fiber section. Finally, a dielectric mirror was deposited on one end of each fiber section by magnetron sputtering. After characterizing the optical loss, length, and mirror reflectance for each of the fiber sections, sections which were well-matched in length were chosen for assembly of the four-mirror etalon, which had nominal reflectance values of 10%, 50%, 50%, and 10% for the dielectric mirrors. Measured transmittance spectra for a mutireflector spectral filter were compared with calculated spectra. Thermal tuning of the multireflector etalon was also investigated. A 0.34 nm wavelength shift was observed for a 23° C temperature change, in agreement with prediction.

The U.S. Army¡¯s Chemical Demilitarization are designed to store, treat and destroy the nation¡¯s aging chemical weapons. It operates Near-Real-Time Monitors and Deport Area Monitoring Systems to detect chemical agent at concentrations before they become dangerous to workers, public health and the environment. CDC recommends that the sampling and analytical methods measure within 25% of the true concentration 95% of the time, and if this criterion is not met the alarm set point or reportable level should be adjusted. Two methods were provided by Army¡¯s Programmatic Laboratory and Monitoring Quality Assurance Plan to evaluate the monitoring systems based on CDC recommendations. This thesis addresses the potential problems associated with these two methods and proposes the Bayesian method in an effort to improve the assessment. Comparison of simulation results indicates that Bayesian method produces a relatively better estimate for verifying monitoring system performance as long as the prior given is correct.

Zugl.: Darmstadt, Techn. Univ., Diss., 2007

Thesis (Ph. D.)--University of Washington, 1996. / Vita. Includes bibliographical references (leaves [202]-219).

Zugl.: Vallendar, WHU - Otto Beisheim School of Management, Diss., 2008

Thesis (Ph. D.)--Carleton University, 1984. / Also available in electronic format on the Internet.