http://www.ideals.illinois.edu:80 The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material. http://hdl.handle.net/2142/14285 Rural Eutopia: Can We Learn from Persistently Prosperous Places? Rahe, Mallory L. rural communities prosperity case study http://hdl.handle.net/2142/14284 Farm-Level Impacts of Alternative Spatial Water Management Policies for the Protection of Instream Flows Palazzo, Amanda Margaret ground water tradable permits abatement water market watershed water use http://hdl.handle.net/2142/14283 Household Adoption of Green Technologies: The Case of Chicago Rain Barrels Freitas, Luiz stormwater site selection technology adoption econometrics economics http://hdl.handle.net/2142/14282 Improving the Accuracy of Outlook Price Forecasts: An Application to Livestock Markets Colino, Evelyn Del Valle The performance and economic value of public outlook forecasts has been of continuing interest to agricultural economists and market participants. This dissertation provide new and powerful evidence on the performance of outlook forecasts relative to futures prices in hog and cattle markets over the last three decades and evaluates numerous time-series models and combinatory procedures as forecasting techniques to improve the predictive accuracy of hog price outlook forecasts. Many of these forecasting techniques have never been applied to livestock markets. Quarterly data from the mid- to late-1970s through 2007 for up to three-quarter ahead is available from four prominent outlook programs: University of Illinois/Purdue University, Iowa State University, University of Missouri, and the Economic Research Service of the U.S. Department of Agriculture (USDA). Overall, results show that in general, futures outperform outlook with some differences statistical significant. However, a combination of futures and outlook forecasts generally provide lower forecast errors than futures alone, and therefore, outlook forecasts of hog and cattle prices provide incremental information relative to futures prices. When compared to numerous time-series models, Iowa’s estimates are in general outperformed with statistical insignificant differences. However, even with the use of simple time-series models, findings from the encompassing tests highlight the efficacy of improving Iowa’s price forecasting performance via composite procedures. Finally, given the potential benefits of forecast combination, numerous combinatory techniques are evaluated in a true out-of-sample context. A true out-of-sample evaluation of composite forecasts is an issue not always carefully considered in the literature. Results show that significant forecast error reductions can be obtained from the combination of outlook, futures and two simple time-series models under most of the methods considered. More interesting, the simple average composite shows an outstanding performance that tends to increase at longer horizons, a result consistent with previous literature. In addition, evidence says that the accuracy of futures prices is stellar at the first horizon, but weaker at distant horizons, suggesting that the value of market forecasts lies primarily in the short-run. price forecast outlook futures time-series forecast combination http://hdl.handle.net/2142/14281 Joint Shear Behavior of Reinforced Concrete Beam-Column Connections subjected to Seismic Lateral Loading Kim, Jaehong LaFave, James M. Beam-column connections have been identified as potentially one of the weaker components of reinforced concrete moment resisting frames subjected to seismic lateral loading. Well-established knowledge of RC joint shear behavior is necessary because severe damage within a joint panel may trigger deterioration of the overall performance of RC beam-column connections or frames. However, despite the importance of understanding RC joint shear behavior, a consensus on the ways in which some parameters affect joint shear strength has not been reached. In addition, there has generally been no accepted behavior model for RC joint shear stress vs. joint shear strain. Therefore, in this research a more systematic understanding of RC joint shear behavior has been achieved by completing the following tasks: construction of an extensive experimental database, characterization of RC joint shear behavior, and development of RC joint shear strength models and proposed joint shear behavior models. An extensive experimental RC beam-column connection database (of 341 subassemblies in total) was constructed and classified by governing failure mode sequence, in-plane geometry, outof- plane geometry, and joint eccentricity. All included subassemblies were made at a minimum of one-third scale, and all used conventional types of reinforcement anchorages. RC joint shear behavior was described as an envelope curve by connecting key points displaying the most distinctive stiffness changes. The first point indicates initiation of diagonal cracking within a joint panel, the second point results from yielding of reinforcement, and the third point corresponds to maximum response. An RC joint shear strength model was then developed using the experimental database in conjunction with the Bayesian parameter estimation method. A simple and unified joint shear deformation model (at maximum response) was also developed, following the same procedure used to develop the simple and unified joint shear strength model. Full RC joint shear behavior models were constructed by employing the Bayesian method at each key point and also by adjusting the simple and unified joint shear strength and deformation models for maximum response. Finally, the Parra-Montesinos and Wight model was modified to improve its reliability by updating the key relation between principal strain ratio and joint shear deformation. reinforced concrete connections joint shear failure experimental database earthquake loading Bayesian parameter estimation structural behavior prediction models http://hdl.handle.net/2142/14280 Decentralized Strategies for Monitoring Structures using Wireless Smart Sensor Networks Sim, Sung-Han Spencer, Jr., Billie F. Driven by the needs to address problems with our rapidly aging civil infrastructure, structural health monitoring (SHM) has arisen as an important tool to improve maintenance and operation. Introduced as a promising alternative to the traditional wired sensors, wireless smart sensors offer unique features (low cost, wireless communication, onboard computation, and small size) that enable deployment of dense array of sensors essential for assessing structural damage. The centralized data collection approach, which the wired sensor system commonly employs, is not suitable to wireless smart sensor networks (WSSNs) due to limitations in the wireless communication; decentralized data aggregation and processing is required in the WSSNs. Rather than collecting uncondensed raw sensor data at a centralized location, in-network data processing, made possible by the onboard computational capability of smart sensors, is utilized to condense the raw data and extract meaningful information. By transferring only the condensed data to the centralized location, data communication over the wireless links can be greatly reduced. Decentralized data aggregation approaches can be placed in two broad categories: (a) independent processing (each node processes sensor data independently), and (b) coordinated processing (sensor nodes collaborate to process sensor data by sharing information). This report outlines the implementation of both decentralized data aggregation approaches for the WSSNs employing Crossbow’s Imote2 smart sensor platform. Design considerations for developing WSSN applications are described herein, including network-wide flow and timing, fault-tolerant feature, and network topology to account for the decentralized data aggregation. WSSN applications introduced in this report can be downloaded at the Illinois SHM Project website (http://shm.cs.uiuc.edu). structural health monitoring wireless smart sensor wireless smart sensor network decentralized processing ISHMP Services Toolsuite Imote2 http://hdl.handle.net/2142/14279 Water Demand in the Chicago Metropolitan Area Mieno, Taro Illinois faces a legally de ned quota for the amount of water that it is allowed to pump from Lake Michigan. Separately, in Northeastern Illinois, the ground water level has fallen due to pumping pressure. Together, these constraints on water supply could limit economic and population growth in the Chicago Metropolitan area. There are two alternatives to meet the area's growing demand: pumping water from distant sources, or using the available water more e ciently. The former will require huge investments in infrastructure, while the latter could postpone or circumvent those investments. In light of these facts, curbing water demand, rather than expanding water supply, seems like a promising option. The objective of study is to understand water demand in the Chicago area by examining the e ects of water price, weather conditions, and socio-demographic characteristics on water use in Chicago Metropolitan Area. Economic theory tells us that water demand should be responsive to water price. For policy makers, consumer responsiveness to water price changes will be invaluable information when considering long term strategies to ensure the e cient and conservative use of Chicago's water resource. water demand price elasticity http://hdl.handle.net/2142/14278 Evaluating Sampling Biases in Policy Analysis of Environmental Markets Li, Hongshuang sampling strategies sampling biases water permit market Monte Carlo http://hdl.handle.net/2142/14277 Live and Feeder Cattle Options Markets: Returns, Risk, and Volatility Forecasting Brittain, Lee options live cattle feeder cattle returns risk volatility forecasting http://hdl.handle.net/2142/14276 Exact Solutions of Some Dynamic Problems of Indentation And Transient Loadings of an Elastic Half Space Thompson, J.C. Robinson, A.R. Impact Potential theory (Mathematics) Wave equation Boundary value problems