Lin, Zhenjiang. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 161-185). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Lai, Tsz Wai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 193-207). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Contributions --- p.2 / Chapter 1.3 --- Organization --- p.2 / Chapter 2 --- Literature Review --- p.4 / Chapter 2.1 --- Taxonomy --- p.4 / Chapter 2.2 --- Design of Infrastructure --- p.6 / Chapter 2.2.1 --- Facility Location Models --- p.7 / Chapter 2.2.1.1 --- Random Breakdowns --- p.7 / Chapter 2.2.1.2 --- Deliberate Attacks --- p.8 / Chapter 2.2.2 --- Network Design Models --- p.9 / Chapter 2.3 --- Protection of Existing Components --- p.10 / Chapter 2.3.1 --- Interdiction Models --- p.11 / Chapter 2.3.2 --- Facility Location Models --- p.12 / Chapter 2.3.2.1 --- Random Breakdowns --- p.12 / Chapter 2.3.2.2 --- Deliberate Attacks --- p.12 / Chapter 2.3.3 --- Network Design Models --- p.14 / Chapter 3 --- Identifying Critical Facilities: Median Problem --- p.16 / Chapter 3.1 --- Introduction --- p.16 / Chapter 3.2 --- Problem Formulation --- p.18 / Chapter 3.2.1 --- The p-Median Problem --- p.18 / Chapter 3.2.1.1 --- A Toy Example --- p.19 / Chapter 3.2.1.2 --- Problem Definition --- p.21 / Chapter 3.2.1.3 --- Mathematical Model --- p.22 / Chapter 3.2.2 --- The r-Interdiction Median Problem --- p.24 / Chapter 3.2.2.1 --- The Toy Example --- p.24 / Chapter 3.2.2.2 --- Problem Definition --- p.27 / Chapter 3.2.2.3 --- Mathematical Model --- p.28 / Chapter 3.2.3 --- The r-Interdiction Median Problem with Fortification --- p.29 / Chapter 3.2.3.1 --- The Toy Example --- p.30 / Chapter 3.2.3.2 --- Problem Definition --- p.32 / Chapter 3.2.3.3 --- Mathematical Model --- p.33 / Chapter 3.2.4 --- The r-Interdiction Median Problem with Fortification (Bilevel Formulation) --- p.35 / Chapter 3.2.4.1 --- Mathematical Model --- p.36 / Chapter 3.3 --- Solution Methodologies --- p.38 / Chapter 3.3.1 --- Model Reduction --- p.38 / Chapter 3.3.2 --- Variable Consolidation --- p.40 / Chapter 3.3.3 --- Implicit Enumeration --- p.45 / Chapter 3.4 --- Results and Discussion --- p.48 / Chapter 3.4.1 --- Data Sets --- p.48 / Chapter 3.4.1.1 --- Swain --- p.48 / Chapter 3.4.1.2 --- London --- p.49 / Chapter 3.4.1.3 --- Alberta --- p.49 / Chapter 3.4.2 --- Computational Study --- p.50 / Chapter 3.4.2.1 --- The p-Median Problem --- p.50 / Chapter 3.4.2.2 --- The r-Interdiction Median Problem --- p.58 / Chapter 3.4.2.3 --- The r-Interdiction Median Problem with Fortification --- p.63 / Chapter 3.4.2.4 --- The r-Interdiction Median Problem with Fortification (Bilevel Formulation) --- p.68 / Chapter 3.5 --- Summary --- p.76 / Chapter 4 --- Hybrid Approaches --- p.79 / Chapter 4.1 --- Framework --- p.80 / Chapter 4.2 --- Tabu Assisted Heuristic Search --- p.81 / Chapter 4.2.1 --- A Tabu Assisted Heuristic Search Construct --- p.83 / Chapter 4.2.1.1 --- Search Space --- p.84 / Chapter 4.2.1.2 --- Initial Trial Solution --- p.85 / Chapter 4.2.1.3 --- Neighborhood Structure --- p.85 / Chapter 4.2.1.4 --- Local Search Procedure --- p.86 / Chapter 4.2.1.5 --- Form of Tabu Moves --- p.88 / Chapter 4.2.1.6 --- Addition of a Tabu Move --- p.88 / Chapter 4.2.1.7 --- Maximum Size of Tabu List --- p.89 / Chapter 4.2.1.8 --- Termination Criterion --- p.89 / Chapter 4.3 --- Hybrid Simulated Annealing Search --- p.90 / Chapter 4.3.1 --- A Hybrid Simulated Annealing Construct --- p.91 / Chapter 4.3.1.1 --- Random Selection of Immediate Neighbor --- p.92 / Chapter 4.3.1.2 --- Cooling Schedule --- p.93 / Chapter 4.3.1.3 --- Termination Criterion --- p.94 / Chapter 4.4 --- Hybrid Genetic Search Algorithm --- p.95 / Chapter 4.4.1 --- A Hybrid Genetic Search Construct --- p.99 / Chapter 4.4.1.1 --- Search Space --- p.99 / Chapter 4.4.1.2 --- Initial Population --- p.100 / Chapter 4.4.1.3 --- Selection --- p.104 / Chapter 4.4.1.4 --- Crossover --- p.105 / Chapter 4.4.1.5 --- Mutation --- p.106 / Chapter 4.4.1.6 --- New Population --- p.108 / Chapter 4.4.1.7 --- Termination Criterion --- p.109 / Chapter 4.5 --- Further Assessment --- p.109 / Chapter 4.6 --- Computational Study --- p.114 / Chapter 4.6.1 --- Parameter Selection --- p.115 / Chapter 4.6.1.1 --- Tabu Assisted Heuristic Search --- p.115 / Chapter 4.6.1.2 --- Hybrid Simulated Annealing Approach --- p.121 / Chapter 4.6.1.3 --- Hybrid Genetic Search Algorithm --- p.124 / Chapter 4.6.2 --- Expected Performance --- p.128 / Chapter 4.6.2.1 --- Tabu Assisted Heuristic Search --- p.128 / Chapter 4.6.2.2 --- Hybrid Simulated Annealing Approach --- p.138 / Chapter 4.6.2.3 --- Hybrid Genetic Search Algorithm --- p.146 / Chapter 4.6.2.4 --- Overall Comparison --- p.150 / Chapter 4.7 --- Summary --- p.153 / Chapter 5 --- A Special Case of the Median Problems --- p.156 / Chapter 5.1 --- Introduction --- p.157 / Chapter 5.2 --- Problem Formulation --- p.158 / Chapter 5.2.1 --- The r-Interdiction Covering Problem --- p.158 / Chapter 5.2.1.1 --- Problem Definition --- p.159 / Chapter 5.2.1.2 --- Mathematical Model --- p.160 / Chapter 5.2.2 --- The r-Interdiction Covering Problem with Fortification --- p.162 / Chapter 5.2.2.1 --- Problem Definition --- p.163 / Chapter 5.2.2.2 --- Mathematical Model --- p.164 / Chapter 5.2.3 --- The r-Interdiction Covering Problem with Fortification (Bilevel Formulation) --- p.167 / Chapter 5.2.3.1 --- Mathematical Model --- p.168 / Chapter 5.3 --- Theoretical Relationship --- p.170 / Chapter 5.4 --- Solution Methodologies --- p.172 / Chapter 5.5 --- Results and Discussion --- p.175 / Chapter 5.5.1 --- The r-Interdiction Covering Problem --- p.175 / Chapter 5.5.2 --- The r-Interdiction Covering Problem with Fortification --- p.178 / Chapter 5.5.3 --- The r-Interdiction Covering Problem with Fortification (Bilevel Formulation) --- p.182 / Chapter 5.6 --- Summary --- p.187 / Chapter 6 --- Conclusion --- p.189 / Chapter 6.1 --- Summary of Our Work --- p.189 / Chapter 6.2 --- Future Directions --- p.192

最近，幾種以Kodialam等人提出的RFID數量估計算法為基礎的新算法相繼出現。這些新算法不僅考慮到RFID讀器和RFID標簽之聞無線信道的不穩定性和不確定性，而且還可以保證其估算具有一定的準確性。然而，這些RFID數量估計算法的設計和性能評估都是基於一個比較簡化的信道模型。根據這個信道模型，封包在RFID讀器和標簽之聞傳送時遺失的概率是符合獨立分布的。然而，一些實證測量研究指出，在一般的室内環境，人的活動和設備的移動對信道的影響是不可忽視的。這些活動可以引起多普勒效應，從而使信號變成時域相關。因此，在真實的無線信道傳輸中，封包的遺失也是時域相關的。由於不同的RFID數量估計算法具體的設計和實現方法各有不同，封包遺失的時域相關性可能對這些RFID數量估計算法造成不同程度的影響。 / 在本論文中，我們評估了三系列的算法在更真實的時域相關的無線信道下的性能。具體來，我們重點研究和分析了時域相關性在哪些方面影響了現有的RFID數量估計算法的準確性。依據描述真實無線信道特性的實驗數據，我們改進了原來的信道模型，使其概括了RFID讀器和標簽之聞向前信道/向後信道的時域相關性。通過觀察這三系列算法在更真實的時域相關的無線信道下的表現，我們分析了造成估算值和真實值之間差距的原因。同時，提出了一些改善數量估計算法準確性的方法，並且通過模擬試驗證明這些改進可以提高算法在真實無線信道下的準確性。 / Recently, several new RFID counting algorithms have been proposed based on the probabilistic counting schemes introduced by Kodialam et. al.. These existing algorithms took into account the unreliable and non-deterministic nature of the radio communication channels between the RFID reader and the tags,and are capable of providing tag-count estimates that satisfy a desired level of accuracy. However, all algorithms were designed and evaluated based on a simplistic packet loss model. It assumes that the loss probability of a packet between the reader and the tag-set follows an independent, identical distribution. No characterizations of possible temporal correlations of the channels were performed. As presented by some empirical measurements, movements of personnel or equipments in a building can generate Doppler effect, which introduces time correlations to the fading signal. Thus, the realistic packet loss caused by the wireless channels is temporally correlated due to the frequent change of the nearby environment. Depending on specific implementation details of each individual algorithm,temporally correlated packet loss might have significant impact on the tag-set cardinality estimation. / In this thesis, we will evaluate the performance of the aforementioned RFID counting algorithms under a more sophisticated time-correlated channel fading model. In particular, we focus on investigating and analyzing how the temporal correlations would influence the accuracy of these existing counting algorithms. Based on the experimental statistics that characterized the realistic indoor channels, we refine the channel model to describe the time-correlation of the forward and backward channel between the RFID reader and the tags. We also modify the model to support implementations of different communication scenarios. Comparisons of the performance of the existing counting schemes under the simplistic uncorrelated packet loss channel model and the refined correlated channel model are conducted. We also propose extensions for these RFID counting schemes to mitigate the estimation inaccuracy generated by the correlated packet loss. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Deng, Yulin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 99-107). / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background and related work --- p.7 / Chapter 3 --- Modeling time-correlated channels in RFID systems --- p.13 / Chapter 3.1 --- Memoryless channel model --- p.14 / Chapter 3.2 --- Backscattering channel model --- p.16 / Chapter 3.2.1 --- Discussions of channel differences with active tags --- p.18 / Chapter 3.3 --- Difficulties in extending mathematical analysis for Memoryless channel model to time-correlated Backscattering channel model --- p.19 / Chapter 3.4 --- Implementations of Backscattering channel model --- p.20 / Chapter 3.4.1 --- Model the one-way fading channel based on the Clarke and Gans model --- p.20 / Chapter 3.4.2 --- Other implementation aspects of the Twoway Backscattering channel model --- p.25 / Chapter 4 --- Performance evaluation of the First-two-moment implicit approach under time-correlated channels --- p.27 / Chapter 4.1 --- System model --- p.28 / Chapter 4.2 --- Estimator Accuracy --- p.30 / Chapter 4.3 --- Performance evaluation of the First-two-moment implicit RFID counting scheme over time-correlated channels --- p.32 / Chapter 4.3.1 --- Modeling differences --- p.34 / Chapter 4.3.2 --- Coherence time --- p.37 / Chapter 4.3.3 --- Rician fading channel --- p.40 / Chapter 4.3.4 --- Discussions for the case with active tags --- p.42 / Chapter 4.4 --- Correcting estimation errors under time-correlated channels --- p.44 / Chapter 4.4.1 --- Correcting estimation mean --- p.44 / Chapter 4.4.2 --- The impact of time-correlated channels on estimation variance --- p.47 / Chapter 4.5 --- Chapter summary --- p.49 / Chapter 5 --- Performance Evaluation of the Capture-Recapture approach under time-correlated channels --- p.50 / Chapter 5.1 --- System model --- p.51 / Chapter 5.2 --- Different estimation algorithms --- p.53 / Chapter 5.2.1 --- Union-based approach --- p.53 / Chapter 5.2.2 --- The Capture-Recapture approach --- p.55 / Chapter 5.3 --- Performance evaluation of the estimation schemes under time- correlated channels --- p.58 / Chapter 5.3.1 --- Simulation Setup --- p.60 / Chapter 5.3.2 --- Observations and Analysis --- p.65 / Chapter 5.4 --- Extensions of correcting the errors under timecorrelated channels --- p.69 / Chapter 5.5 --- Chapter Summary --- p.72 / Chapter 6 --- Performance evaluation of adaptive RFID counting algorithms under time-correlated channels --- p.74 / Chapter 6.1 --- System Model --- p.75 / Chapter 6.2 --- Adaptive RFID counting Algorithms --- p.76 / Chapter 6.2.1 --- Adaptive Union approach --- p.77 / Chapter 6.2.2 --- Probabilistic Estimation For Lossy Channels (PELOC) --- p.78 / Chapter 6.3 --- Performance evaluation of the adaptive counting algorithms under time-correlated channels --- p.80 / Chapter 6.3.1 --- Simulation Setup --- p.81 / Chapter 6.3.2 --- Observation and analysis --- p.82 / Chapter 6.4 --- Extensions to correct the inaccuracy under timecorrelated channels / Chapter 6.5 --- Chapter Summary --- p.93 / Chapter 7 --- Conclusion and Future work --- p.95 / Bibliography --- p.99

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Typescript. / Digitized by Kansas Correctional Industries

This dissertation is motivated by the problem of uncertainty and sensitivity in business- class models such as the carbon emission abatement policy model featured in this work. Uncertain model inputs are represented by numerical random variables and a computational methodology is developed to numerically compute business-class models as if sharp inputs were given. A new description for correlation of random variables is presented that arises spontaneously within a numerical model. Methods of numerically computing correlated random variables are implemented in software and represented. The major contribution of this work is a methodology for the numerical computation of models under uncertainty that expresses no preference for unlikelihood of model input combinations. The methodology presented here serves a sharp contrast to traditional Monte Carlo methods that implicitly equate likelihood of model input values with importance of results. The new methodology herein shifts the computational burden from likelihood of inputs to resolution of input space.

A number of shortcomings were found after complete derivation of the temperature dependence of equations, and the expressions related to the Early effect in the present Gummel-Poon 2 model, as implemented in the TEKSPICE program. The formulation and application of improved model equations is presented, followed by a detailed comparison of the existing model with the one developed in this work.

Numerical modeling has become a major tool for managing water quality in surface waterbodies such as rivers, lakes, reservoirs, and estuaries. Since the two-dimensional longitudinal/vertical model CE-QUAL-W2 is a well-known model and it has been applied to thousands of waterbodies around the world successfully, its numerical scheme was adapted to develop a new three-dimensional numerical model for simulating hydrodynamics, temperature, and water quality in surface waterbodies. Finite difference approximations were used to solve the fluid dynamic governing equations of continuity, free water surface, momentums, and mass transport. No coordinate transformations were performed and the z-coordinate system has been used. Higher-order schemes (QUICK, QUICKEST, and ULTIMATE QUICKEST) in addition to the UPWIND scheme were used for the advective temperature and mass transport. A novel numerical approach was used for the numerical formulation of the three-dimensional scheme. This approach forced the numerical solution of the free surface equation to be a tri-diagonal matrix form rather than a more computationally intensive penta-diagonal matrix solution. This new approach was done by linking a method called line-by-line with the free water surface numerical solution. Another new approach was that the three-dimensional numerical scheme involved a simultaneous solution of hydrodynamics, temperature, and water quality at every model time level instead of saving the hydrodynamic results to be used later for water quality simulation. Hence, this scheme allowed feedback between the hydrodynamics and water quality every time step. In addition, various unique numerical algorithms were employed from CE-QUAL-W2 such as the W2 turbulence model, selective withdrawal theory, surface heat fluxes, and water quality sources and sinks, making the three-dimensional model built on well-tested algorithms. To test the model structure and assumptions, an analytical verification was performed by comparing model predictions to known analytical exact solutions test cases. Good agreement was showed by the model for all of these tests. A computation of the volume balance over the simulation period was also incorporated within the model to assess how well the code performed. Sensitivity tests were also made varying bed and wind shear. The model was also applied to three reservoirs in the USA as field case studies: Lake Chaplain in WA, Laurance Lake in OR, and Cooper Creek Reservoir in OR. The model was validated by comparing the model predictions of water levels, velocities, vertical temperature profiles, and dissolved oxygen with field data. Through these real applications, the numerical predictions of the 3D model showed good agreement with field data based on error statistics. The model results of each field case study were discussed separately. In the Lake Chaplain model application, the study was focused on the importance of the higher-order schemes compared to the first-order UPWIND scheme. The model predictions of temperature were determined by using the UPWIND, QUICK, and QUICKEST scheme and compared with field data. The Error statistics of the model predictions compared to field data were an absolute mean error (AME) of 0.065 m for the water level predictions and an overall AME of 1.62 °C, 1.09 °C, and 1.23 °C for the temperature predictions by using the UPWIND, QUICK, and QUICKEST scheme, respectively. In the Laurance Lake model application, a comparison was performed between the present 3D model and the 2D CE-QUAL-W2. Since the 3D model was build based on CE-QUAL-W2, differences between the two models were evaluated. Error statistics between the model predictions of water level and temperature compared to field data showed that both models were in good agreement with field data. However, the 3D model AME (0.30 m for the water level predictions and 0.48 °C for the temperature predictions) was higher than the 2D model (0.03 m for the water level predictions and 0.42 °C for the temperature predictions). Finally, the Cooper Creek Reservoir case study was done to show the model predictions of temperature and dissolved oxygen. In this application, vertical temperature profiles were covered the entire simulation period in order to show how the model transfer heat between stratification and non- stratification conditions. The model showed good agreement with field data (0.12 m AME for the water level predictions, 1.00 °C overall AME for the temperature predictions, and 1.32 g/m3 overall AME for the dissolved oxygen predictions). Finally, comparisons were made between CE-QUAL-W2 and the 3D model. The 2D model generally performed better in the tests cases if the model user is unconcerned about lateral impacts. The 3D model is important to use when lateral currents and variation in the lateral dimension are important.

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