Development of error correction techniques for nitrate-N load estimation models

Excess nutrient loads carried by streams and rivers are a great concern for environmental resource managers. In agricultural regions, excess loads are transported downstream to receiving water bodies, potentially causing algal blooms, which could lead to numerous ecological problems. To better understand nutrient load transport, and to develop appropriate water management plans, it is important to have accurate estimates of annual nutrient loads. This study used a Monte Carlo sub-sampling method and error-corrected statistical models to estimate annual nitrate-N loads from two watersheds in central Illinois. The performance of three load estimation methods (the seven-parameter log-linear model, the ratio estimator, and the flow-weighted averaging estimator) applied at one-, two-, four-, six-, and eight-week sampling frequencies were compared. Five error correction techniques; the existing composite method, and four new error correction techniques developed in this study; were applied to each combination of sampling frequency and load estimation method. On average, the most accurate error reduction technique, (proportional rectangular) resulted in 15% and 30% more accurate load estimates when compared to the most accurate uncorrected load estimation method (ratio estimator) for the two watersheds. Using error correction methods, it is possible to design more cost-effective monitoring plans by achieving the same load estimation accuracy with fewer observations. Finally, the optimum combinations of monitoring threshold and sampling frequency that minimizes the number of samples required to achieve specified levels of accuracy in load estimation were determined. For one- to three-weeks sampling frequencies, combined threshold/fixed-interval monitoring approaches produced the best outcomes, while fixed-interval-only approaches produced the most accurate results for four- to eight-weeks sampling frequencies.

Low-power high-performance SAR ADC design with digital calibration techniques

This dissertation presents the design of three high-performance successive-approximation-register (SAR) analog-to-digital converters (ADCs) using distinct digital background calibration techniques under the framework of a generalized code-domain linear equalizer. These digital calibration techniques effectively and efficiently remove the static mismatch errors in the analog-to-digital (A/D) conversion. They enable aggressive scaling of the capacitive digital-to-analog converter (DAC), which also serves as sampling capacitor, to the kT/C limit. As a result, outstanding conversion linearity, high signal-to-noise ratio (SNR), high conversion speed, robustness, superb energy efficiency, and minimal chip-area are accomplished simultaneously. The first design is a 12-bit 22.5/45-MS/s SAR ADC in 0.13-μm CMOS process. It employs a perturbation-based calibration based on the superposition property of linear systems to digitally correct the capacitor mismatch error in the weighted DAC. With 3.0-mW power dissipation at a 1.2-V power supply and a 22.5-MS/s sample rate, it achieves a 71.1-dB signal-to-noise-plus-distortion ratio (SNDR), and a 94.6-dB spurious free dynamic range (SFDR). At Nyquist frequency, the conversion figure of merit (FoM) is 50.8 fJ/conversion step, the best FoM up to date (2010) for 12-bit ADCs. The SAR ADC core occupies 0.06 mm2, while the estimated area the calibration circuits is 0.03 mm2. The second proposed digital calibration technique is a bit-wise-correlation-based digital calibration. It utilizes the statistical independence of an injected pseudo-random signal and the input signal to correct the DAC mismatch in SAR ADCs. This idea is experimentally verified in a 12-bit 37-MS/s SAR ADC fabricated in 65-nm CMOS implemented by Pingli Huang. This prototype chip achieves a 70.23-dB peak SNDR and an 81.02-dB peak SFDR, while occupying 0.12-mm2 silicon area and dissipating 9.14 mW from a 1.2-V supply with the synthesized digital calibration circuits included. The third work is an 8-bit, 600-MS/s, 10-way time-interleaved SAR ADC array fabricated in 0.13-μm CMOS process. This work employs an adaptive digital equalization approach to calibrate both intra-channel nonlinearities and inter-channel mismatch errors. The prototype chip achieves 47.4-dB SNDR, 63.6-dB SFDR, less than 0.30-LSB differential nonlinearity (DNL), and less than 0.23-LSB integral nonlinearity (INL). The ADC array occupies an active area of 1.35 mm2 and dissipates 30.3 mW, including synthesized digital calibration circuits and an on-chip dual-loop delay-locked loop (DLL) for clock generation and synchronization.

Incomplete information games of conflict and collective action

My thesis consists of three essays that investigate strategic interactions between individuals engaging in risky collective action in uncertain environments. The first essay analyzes a broad class of incomplete information coordination games with a wide range of applications in economics and politics. The second essay draws from the general model developed in the first essay to study decisions by individuals of whether to engage in protest/revolution/coup/strike. The final essay explicitly integrates state response to the analysis. The first essay, Coordination Games with Strategic Delegation of Pivotality, exhaustively analyzes a class of binary action, two-player coordination games in which players receive stochastic payoffs only if both players take a ``stochastic-coordination action''. Players receive conditionally-independent noisy private signals about the normally distributed stochastic payoffs. With this structure, each player can exploit the information contained in the other player's action only when he takes the “pivotalizing action”. This feature has two consequences: (1) When the fear of miscoordination is not too large, in order to utilize the other player's information, each player takes the “pivotalizing action” more often than he would based solely on his private information, and (2) best responses feature both strategic complementarities and strategic substitutes, implying that the game is not supermodular nor a typical global game. This class of games has applications in a wide range of economic and political phenomena, including war and peace, protest/revolution/coup/ strike, interest groups lobbying, international trade, and adoption of a new technology. My second essay, Collective Action with Uncertain Payoffs, studies the decision problem of citizens who must decide whether to submit to the status quo or mount a revolution. If they coordinate, they can overthrow the status quo. Otherwise, the status quo is preserved and participants in a failed revolution are punished. Citizens face two types of uncertainty. (a) non-strategic: they are uncertain about the relative payoffs of the status quo and revolution, (b) strategic: they are uncertain about each other's assessments of the relative payoff. I draw on the existing literature and historical evidence to argue that the uncertainty in the payoffs of status quo and revolution is intrinsic in politics. Several counter-intuitive findings emerge: (1) Better communication between citizens can lower the likelihood of revolution. In fact, when the punishment for failed protest is not too harsh and citizens' private knowledge is accurate, then further communication reduces incentives to revolt. (2) Increasing strategic uncertainty can increase the likelihood of revolution attempts, and even the likelihood of successful revolution. In particular, revolt may be more likely when citizens privately obtain information than when they receive information from a common media source. (3) Two dilemmas arise concerning the intensity and frequency of punishment (repression), and the frequency of protest. Punishment Dilemma 1: harsher punishments may increase the probability that punishment is materialized. That is, as the state increases the punishment for dissent, it might also have to punish more dissidents. It is only when the punishment is sufficiently harsh, that harsher punishment reduces the frequency of its application. Punishment Dilemma 1 leads to Punishment Dilemma 2: the frequencies of repression and protest can be positively or negatively correlated depending on the intensity of repression. My third essay, The Repression Puzzle, investigates the relationship between the intensity of grievances and the likelihood of repression. First, I make the observation that the occurrence of state repression is a puzzle. If repression is to succeed, dissidents should not rebel. If it is to fail, the state should concede in order to save the costs of unsuccessful repression. I then propose an explanation for the “repression puzzle” that hinges on information asymmetries between the state and dissidents about the costs of repression to the state, and hence the likelihood of its application by the state. I present a formal model that combines the insights of grievance-based and political process theories to investigate the consequences of this information asymmetry for the dissidents' contentious actions and for the relationship between the magnitude of grievances (formulated here as the extent of inequality) and the likelihood of repression. The main contribution of the paper is to show that this relationship is non-monotone. That is, as the magnitude of grievances increases, the likelihood of repression might decrease. I investigate the relationship between inequality and the likelihood of repression in all country-years from 1981 to 1999. To mitigate specification problem, I estimate the probability of repression using a generalized additive model with thin-plate splines (GAM-TPS). This technique allows for flexible relationship between inequality, the proxy for the costs of repression and revolutions (income per capita), and the likelihood of repression. The empirical evidence support my prediction that the relationship between the magnitude of grievances and the likelihood of repression is non-monotone.