This study focuses on developing and evaluating efficient and effective parameter calibration and uncertainty methods for hydrologic modeling. Five single objective optimization algorithms and six multi-objective optimization algorithms were tested for automatic parameter calibration of the SWAT model. A new multi-objective optimization method (Multi-objective Particle Swarm and Optimization & Genetic Algorithms) that combines the strengths of different optimization algorithms was proposed. Based on the evaluation of the performances of different algorithms on three test cases, the new method consistently performed better than or close to the other algorithms. In order to save efforts of running the computationally intensive SWAT model, support vector machine (SVM) was used as a surrogate to approximate the behavior of SWAT. It was illustrated that combining SVM with Particle Swarm and Optimization can save efforts for parameter calibration of SWAT. Further, SVM was used as a surrogate to implement parameter uncertainty analysis fo SWAT. The results show that SVM helped save more than 50% of runs of the computationally intensive SWAT model The effect of model structure on the uncertainty estimation of streamflow simulation was examined through applying SWAT and Neural Network models. The 95% uncertainty intervals estimated by SWAT only include 20% of the observed data, while Neural Networks include more than 70%. This indicates the model structure is an important source of uncertainty of hydrologic modeling and needs to be evaluated carefully. Further exploitation of the effect of different treatments of the uncertainties of model structures on hydrologic modeling was conducted through applying four types of Bayesian Neural Networks. By considering uncertainty associated with model structure, the Bayesian Neural Networks can provide more reasonable quantification of the uncertainty of streamflow simulation. This study stresses the need for improving understanding and quantifying methods of different uncertainty sources for effective estimation of uncertainty of hydrologic simulation.

NP-hard problems have numerous applications in various fields such as networks, computer systems, circuit design, etc. However, no efficient algorithms have been found for NP-hard problems. It has been commonly believed that no efficient algorithms for NP-hard problems exist, i.e., that P6=NP. Recently, it has been observed that there are parameters much smaller than input sizes in many instances of NP-hard problems in the real world. In the last twenty years, researchers have been interested in developing efficient algorithms, i.e., fixed-parameter tractable algorithms, for those instances with small parameters. Fixed-parameter tractable algorithms can practically find exact solutions to problem instances with small parameters, though those problems are considered intractable in traditional computational theory. In this dissertation, we propose a new approach of algorithm design and analysis: discovering better measures for problems. In particular we use two measures instead of the traditional single measure?input size to design algorithms and analyze their time complexity. For several classical NP-hard problems, we present improved algorithms designed and analyzed with this new approach, First we show that the new approach is extremely powerful for designing fixedparameter tractable algorithms by presenting improved fixed-parameter tractable algorithms for the 3D-matching and 3D-packing problems, the multiway cut problem, the feedback vertex set problems on both directed and undirected graph and the max-leaf problems on both directed and undirected graphs. Most of our algorithms are practical for problem instances with small parameters. Moreover, we show that this new approach is also good for designing exact algorithms (with no parameters) for NP-hard problems by presenting an improved exact algorithm for the well-known satisfiability problem. Our results demonstrate the power of this new approach to algorithm design and analysis for NP-hard problems. In the end, we discuss possible future directions on this new approach and other approaches to algorithm design and analysis.

This thesis presents an approach for identifying critical model parameters in dynamic air-conditioning systems using limited sensor information. The expansion valve model and the compressor model parameters play a crucial role in the system model's accuracy. In the past, these parameters have been estimated using a mass flow meter; however, this is an expensive devise and at times, impractical. In response to these constraints, a novel method to estimate the unknown parameters of the expansion valve model and the compressor model is developed. A gray box model obtained by augmenting the expansion valve model, the evaporator model, and the compressor model is used. Two numerical search algorithms, nonlinear least squares and Simplex search, are used to estimate the parameters of the expansion valve model and the compressor model. This parameter estimation is done by minimizing the error between the model output and the experimental systems output. Results demonstrate that the nonlinear least squares algorithm was more robust for this estimation problem than the Simplex search algorithm. In this thesis, two types of expansion valves, the Electronic Expansion Valve and the Thermostatic Expansion Valve, are considered. The Electronic Expansion Valve model is a static model due to its dynamics being much faster than the systems dynamics; the Thermostatic expansion valve model, however, is a dynamic one. The parameter estimation algorithm developed is validated on two different experimental systems to confirm the practicality of its approach. Knowing the model parameters accurately can lead to a better model for control and fault detection applications. In addition to parameter estimation, this thesis also provides and validates a simple usable mathematical model for the Thermostatic expansion valve.

The purpose of the present study was to examine the invariance of the factor structure and item response model parameter estimates obtained from a set of 27 items selected from the 2002 and 2003 forms of Your First College Year (YFCY). The first major research question of the present study was: How similar/invariant are the factor structures obtained from two datasets (i.e., identical items, different people)? The first research question was addressed in two parts: (1) Exploring factor structures using the YFCY02 dataset; and (2) Assessing factorial invariance using the YFCY02 and YFCY03 datasets. After using exploratory and confirmatory and factor analysis for ordered data, a four-factor model using 20 items was selected based on acceptable model fit for the YFCY02 and YFCY03 datasets. The four factors (constructs) obtained from the final model were: Overall Satisfaction, Social Agency, Social Self Concept, and Academic Skills. To assess factorial invariance, partial and full factorial invariance were examined. The four-factor model fit both datasets equally well, meeting the criteria for partial and full measurement invariance. The second major research question of the present study was: How similar/invariant are person and item parameter estimates obtained from two different datasets (i.e., identical items, different people) for the homogenous graded response model (Samejima, 1969) and the partial credit model (Masters, 1982)? To evaluate measurement invariance using IRT methods, the item discrimination and item difficulty parameters obtained from the GRM need to be equivalent across datasets. The YFCY02 and YFCY03 GRM item discrimination parameters (slope) correlation was 0.828. The YFCY02 and YFCY03 GRM item difficulty parameters (location) correlation was 0.716. The correlations and scatter plots indicated that the item discrimination parameter estimates were more invariant than the item difficulty parameter estimates across the YFCY02 and YFCY03 datasets.

In real-time, two way video communications, how to minimize the end-to-end delay for transmitting video data is very important. Since the delay produced by bits accumulated in the encoder buffer must be very small, we need an improved rate control to encode the video with high quality and maintain low buffer fullness. One approach to reduce the buffer fullness is to skip the encoding frames, but the frame-skipping will produce undesirable motion discontinuity in the encoded video sequence. In this thesis, we study the impact of low delay constraint in H.264 rate control and its improvements. The drawback of the H.264 rate control is it cannot handle the frame-skipping mechanism well. To modify this, we control the quantization parameter of each I-frame to avoid the buffer overflow and frame-skipping. Since encoding the I-frame by different quantization parameter will generate different rate and distortion for a group of pictures (GOP), we use Lagrangian optimization to find the tradeoff between rate and distortion for a GOP. By the estimation models of rate and distortion for a GOP, calculate the Lagrangian cost for each possible quantization parameter of I-frame, the quantization parameter with minimum Lagrangian cost will be our choice for I-frame. Simulation results show that our proposed rate control encode the video sequence with less skipped frames and with higher PSNR compared to H.264 rate control under low delay constraint.

Coastal erosion is, more than ever, a global problem. By adopting a high-efficient, cost effective and reliable numerical model, it would help predict and manage erosion, as well as alleviate many coastal problems. This thesis reports the results of a though out investigation on the popular one dimension long-term shoreline change model--- GENESIS, analyze its suitability, sensitivity and technical difficulties likely to encounter while using the model, with the aim to predict the effect of coastal structure on shoreline changes. Prior to perform a modeling task, this report provides constructive recommendation on the setting of the length of shoreline to be covered in the modeling, boundary conditions, grid space, transport parameters K1 and K2 and revision of wave angle, followed by verification using results of several physical scale models, in order to enhance the reliability of the modeling and the parameters employed. Finally, reasonable ranges of K values are proposed. For modeling shoreline changes induced by a detached breakwater with normal incident waves, an empirical equation is proposed to determine the K ratio(K2/K1), which offer a useful guide in achieving the results with in a tolerance limits of 12%~-7%. When consider oblique wave incident to single detached breakwater, K1=0.6 is used and the ratio of K2/K1 ≈ 0.25~0.5. For modeling the effect of a single groin, the present study suggests K1=0.6 and K2/K1 ≈ 1~2. On the basis of these principles for setting the K values, the results are then applied to model the shoreline changes due to the installation of detached breakwater and groin. From the results of this study, for normal wave incident to single detached breakwater, it shows that for a small ratio of the offshore distance to the length of the breakwater S/B or a larger wave height, the salient dimension will increase and wave period has almost no effect on the results produced; for small S/B ratio, the maximum downcoast retreat increase, and its quantity is almost not affected by the wave conditions imposed. For oblique wave incident to single detached breakwater, it shows that for a larger wave angle, a small S/B or a larger wave height, the salient dimension will increase and wave period has almost no effect on the results produced; for larger wave angle or small S/B ratio, the maximum downcoast retreat increase, and its quantity is almost not affected by the wave height and wave period. For modeling the effect of a single groin, it shows that for larger wave angle or length of groin, the maximum downcoast retreat increase, and its quantity is almost not affected by the wave height and wave period.

Taguchi methods is also called quality engineering. It is a systematic methodology for product design(modify) and process design(improvement) with the most of saving cost and time, in order to satisfy customer requirement. Taguchi¡¦s parameter design is also known as robust design, which has the merits of low cost and high efficiency, and can achieve the activities of product quality design, management and improvement, consequently to reinforce the competitive ability of business. It is a worthy research course to study how to effectively apply parameter design, to shorten time spending on research, early to promote product having low cost and high quality on sale and to reinforce competitive advantage. However, the parameter design optimization problems are difficult in practical application owing to (1)complex and nonlinear relationships exist among the system¡¦s inputs, outputs and parameters and (2)interactions may occur among parameters. (3)In Taguchi¡¦s two-phase optimization procedure, the adjustment factor cannot be guaranteed to exist in practice. (4)For some reasons, the data may become lost or were never available. For these incomplete data, the Taguchi¡¦s method cannot treat them well. Neural networks have learning capacity fault tolerance and model-free characteristics. These characteristics support the neural networks as a competitive tool in processing multivariable input-output implementation. The successful field including diagnostics, robotics, scheduling, decision-marking, predicition, etc. In the process of searching optimization, genetic algorithm can avoid local optimization. So that it may enhance the possibility of global optimization. This study had drawn out the key parameters from the spheroidizing theory, and L18, L9 orthogonal experimental array were applied to determine the optimal operation parameters by Signal/Noise analysis. The conclusions are summarized as follows: 1. The spheroidizing of AISI 3130 used to be the highest unqualified product, and required for the second annealing treatment. The operational record before improvement showed 83 tons of the 3130 steel were required for the second treatment. The optimal operation parameters had been defined by L18(61¡Ñ35) orthogonal experimental array. The control parameters of the annealing temperature was at B2

This research analyzed the weather information (temperature, wind velocity, visibility, and total cloudiness) from the Taipei and the Kaohsiung Weather Station of Central Weather Bureau, and air pollution from the Air Quality Monitoring Station of Environmental Protection Administration, Executive Yuan ( Shihlin, Shihlin, Jhongshan, Wanhua, Guting, Songshan¡A), Nanzih, Zuoying, Cianjin, and Siaogan ) to evaluate the feasibility of using visibility as the ambient air quality index by statistical analysis¡C In regard to the visibility in Taipei metropolis, the visibility between 1983~1992 showed a steady status between 5~11 kilometers. The visibility after 1993 has increased gradually between 6~16 kilometers, which indicated that the visual air quality has been improved year by year in Taipei metropolis. In regard to the visibility in Kaohsiung metropolis, the index has a trend of decreasing year by year from 10~24 kilometers to 2~12 kilometers, and the decrease was particularly obvious after 1993. Analyzing the air quality index greater than 100 in the metropolis, the visibility is categorized as the level of "poor", which means that the visibility is within 3 kilometers. When the air quality index ranges between 76~100, the visibility is categorized as the level of median, which means the visibility is within 4 kilometers. When the air quality index ranges between 50~75, the visibility is categorized as the level of "good", which means the visibility is within 7 kilometers. When the air quality index ranges between 20~49, the visibility is categorized as the level of "excellent", which means the visibility is beyond 7 kilometers.

Differential signaling is suitable for high speed signal transmission due to lower noise induction and higher common-mode noise rejection compared to its single-ended signaling counterpart. However, for a high performance differential transmission-line pair, excellent symmetry and appropriate design for substrate layer stack-up is necessary. Especially for a practical IC package substrate, differential transmission-line pair is inevitable for asymmetry because of considering the locations of IC pads and solderballs. Furthermore, different differential transmission-line pair architectures are also demanded in consideration of limited substrate floorplan space and substrate layer stack-up structures. In this thesis, several differential pairs have been implemented on the conventional 4-layer laminate package substrate. The consequent high frequency performances are measured using vector network analyzer and then compared by converting into mixed-mode S-parameters.

Saturated reluctance identification of induction motor can be implemented by additional sensor, finite-element method, spectrum analysis, or step voltage test in the research accounts. But it is not easy to implement in the field evaluation when we need to build up the power system model, because of the factory parameter absent, expansive cost, extra sensor installation, or variable voltage and frequency. To be concerned with practicality, it is always inconvenient to build up simulation for the end user. The linear model of motor can¡¦t provide the simulation answer accurately when models run into saturated during power system transient. Accordingly, this thesis discuss two paragraphs as following: First, This thesis introduces a simple and practical method base on the manufacturer instruction manual to estimate the saturated reluctance of high / medium voltage induction motor in modeling. And we can analyze the motor dynamic characteristic by using the induction motor d-q-0 model directly, in place of traditional mathematical power equations. Moreover, we can evaluate the motor-generation reaction because of the rotor inertia due to loss of voltage. To identify the discrepancy between numeral situations what the line capacitor existed or not. Besides, we can explain the existing voltage after power system break down by comparing the simulation result with recorder chart.