A dynamic model of the U.S. cotton market with rational expectations

This study presents a dynamic rational expectations model for the U.S. cotton market. The dynamic decision rules are derived from the cotton farmer and miller optimization problems; and the equilibrium movements of prices, production, land allocation, and mill consumption are solved analytically. The dynamic element in the cotton farmer and miller problems come from the cost functions. In the cotton cost function a sequential adjustment cost is used while a quadratic cost function is used in the cotton yarns cost function. These optimal decision rules are derived as functions of past values of these decision variables, expectations of future product prices, and other exogenous variables. Assuming rational expectations and knowing the orders of the Markov-processes for the relevant state variables and the disturbances, closed-form regression equations representing decision rules and stochastic processes are obtained. Then, the VAR approach and Granger-causality test are used to obtain information which help to forecast the relevant state variables at the first stage of estimation. With the specific assumption on the errors, a dynamic mill demand for cotton is estimated by using the method of nonlinear least squares and tested by using the likelihood ratio. The empirical results provide some support for the specific model. Furthermore, the empirical model provides a framework for policy evaluation

Voice-related Experiences of Nonbinary Individuals (VENI) Development and Content Validity

Transgender individuals may seek a variety of gender-affirming health and educational services, including voice modification from speech-language pathologists. Measuring the client\u27s self-perception of their communication experiences is crucial for providing client-centered services and measuring outcomes. However, there is currently no validated assessment tool for the nonbinary population, a part of the transgender population. This study explores the voice-related concerns and experiences among the nonbinary population to create a valid measure of their self-perception of voice. Ten nonbinary individuals were surveyed about their voice-related concerns and experiences. A thematic analysis of the responses led to the development of the questionnaire, titled the Voice-related Experiences of Nonbinary Individuals. The questionnaire was systematically evaluated for its content validity by a panel of speech-language pathologist experts in transgender voice services. Outcomes of this analysis supported the measure\u27s content validity and motivated further revisions. This is the first assessment tool that measures self-perception of voice and voice-related experiences for nonbinary individuals. Initial psychometric testing supported its content validity and further research is needed for large-scale testing of validity and reliability

A Run-Time Decision Procedure for Responsive Computing Systems

A responsive computing system is a hybrid of real-time, distributed and fault-tolerant systems. In such a system, severe consequences will occur if the logical and physical specifications of the system are not met. In this paper, we present a logic, Interval Temporal Logic (ITL), to specify responsive systems and give decision procedures to verify properties of the system at run-time as follows. First, we collect, during execution, events occurring in the system to represent a distributed computation. Next, we specify properties of the system using ITL formulas. Finally, we apply the decision procedures to determine satisfaction of the formulas. Thus, we can verify properties of the system at run-time using these decision procedures

Operational Evaluation of Responsiveness Properties

In this paper, a new technique for ensuring run-time satisfaction of properties-specifically responsiveness property, a subset of liveness property, in responsive systems, is presented. Since whether the run-time behavior of a system is satisfied depends on the execution (operational) environment, we develop a translation which takes into account the constraints in the operational environment, and generates histories for each process in the system. Thus, every process can utilize its history to operationally evaluate the system behavior and signal errors if its history is violated. Therefore, this technique provides software safety, handles error-detection, and ensures run-time satisfaction of responsiveness property in the operational environment. To illustrate this approach a train set example is presented

Constructing an Interval Temporal Logic for Real-Time Systems

A real-time system is one that involves control of one or more physical devices with essential timing requirements. Examples of these systems are command and control systems, process control systems, flight control systems, and the space shuttle avionics systems. The characteristics of these systems are that severe consequences will occur if the logical and physical timing specifications of the systems are not met. Formal specification and verification are among the techniques to achieve reliable software for real-time systems, in which testing may be impossible or too dangerous to perform. This paper presents a modal logic, Interval Temporal , built upon a classical predicate logic In this logic system, we consider formulas that can be used to reason about timing properties of systems, in particular, responsiveness assertions. A responsiveness assertion describes constraints that a program must satisfy within an interval. Thus, it can be utilized to characterize behaviors of life-critical systems. We assume that a program P can be identified with a theory, a collection of formulas characterizing sequences of states of P with arbitrary initial states. In the following, we describe syntax and semantics of the logic, present a proof rule for responsiveness assertions, and show soundness and relative completeness of responsiveness assertions that we consider. There are other approaches to build temporal logics for real-time systems, which are included in bibliography

Ensuring the Satisfaction of a Temporal Specification at Run-Time

A responsive computing system is a hybrid of real-time, distributed and fault-tolerant systems. In such a system, severe consequences can occur if the run-time behavior does not conform to the expected behavior or specifications. In this paper, we present a formal approach to ensure satisfaction of the specifications in the operational environment as follows. First we specify behavior of the systems using Interval Temporal Logic (ITL). Next we give algorithms for trace checking of programs in such systems. Finally, we present a fully distributed run-time evaluation system which causally orders the events of the system during its execution and checks this run-time behavior against its ITL specification. The approach is illustrated using a train-set example

E-Government and Lessons from E-Commerce: A Preliminary Study

As businesses become more involved and savvy with electronic commerce (e-commerce), electronic government (e-government) can learn many lessons from them. The tremendous growth in e-commerce will spur many governments to launch comparable e-government services. The recent passage of federal law in the US has institutionalized e-government. Thus, many government bodies will become greatly involved with the Internet and its associated technologies in providing an array of government services that were once confined to brick and mortar operations. However, in deciding which applications will be most effective in serving their constituents and given their limited resources, governments might learn from the practices of businesses. As in the case of business to business (B2B) e-commerce, the exchange of information within and between government agencies will comprise the bulk of interactions or transactions. The results of a preliminary e-commerce survey suggest several areas that may prove to be more effective for e-government Extranet and Intranet applications

Rainfall Reliability Evaluation for Stability of Municipal Solid Waste Landfills on Slope

[[abstract]]A method to assess the reliability for the stability of municipal solid waste (MSW) landfills on slope due to rainfall infiltration is proposed. Parameter studies are first done to explore the influence of factors on the stability of MSW. These factors include rainfall intensity, duration, pattern, and the engineering properties of MSW. Then 100 different combinations of parameters are generated and associated stability analyses of MSW on slope are performed assuming that each parameter is uniform distributed around its reason ranges. In the following, the performance of the stability of MSW is interpreted by the artificial neural network (ANN) trained and verified based on the aforementioned 100 analysis results. The reliability for the stability of MSW landfills on slope is then evaluated and explored for different rainfall parameters by the ANN model with first-order reliability method (FORM) and Monte Carlo simulation (MCS).[[incitationindex]]SCI[[booktype]]紙

On-line, Incremental Visual Scene Understanding for an Indoor Navigating Robot.

An indoor navigating robot must perceive its local environment in order to act. The robot must construct a model that captures critical navigation information from the stream of visual data that it acquires while traveling within the environment. Visual processing must be done on-line and efficiently to keep up with the robot's need. This thesis contributes both representations and algorithms toward solving the problem of modeling the local environment for an indoor navigating robot. Two representations, Planar Semantic Model (PSM) and Action Opportunity Star (AOS), are proposed to capture important navigation information of the local indoor environment. PSM models the geometric structure of the indoor environment in terms of ground plane and walls, and captures rich relationships among the wall segments. AOS is an abstracted representation that reasons about the navigation opportunities at a given pose. Both representations are capable of capturing incomplete knowledge where representations of unknown regions can be incrementally built as observations become available. An on-line generate-and-test framework is presented to construct the PSM from a stream of visual data. The framework includes two key elements, an incremental process of generating structural hypotheses and an on-line hypothesis testing mechanism using a Bayesian filter. Our framework is evaluated in three phases. First, we evaluate the effectiveness of the on-line hypothesis testing mechanism with an initially generated set of hypotheses in simple empty environments. We demonstrate that our method outperforms state-of-the-art methods on geometric reasoning both in terms of accuracy and applicability to a navigating robot. Second, we evaluate the incremental hypothesis generating process and demonstrate the expressive power of our proposed representations. At this phase, we also demonstrate an attention focusing method to efficiently discriminate among the active hypothesized models. Finally, we demonstrate a general metric to test the hypotheses with partial explanations in cluttered environments.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108914/1/gstsai_1.pd