Pulsed parabolic equation model of acoustic transmission (PPEMAT)

Underwater sound is very important in the field of oceanography where it is used for remote sensing in much the same way that radar is used in atmospheric studies. One way to mathematically model sound propagation in the ocean is by using the parabolic-equation method, a technique that allows range dependent environmental parameters. More importantly, this method can model sound transmission where the source emits either a pure tone or a short pulse of sound. Based on the parabolic approximation method and using the split-step Fourier algorithm, a computer model for underwater sound propagation was designed and implemented. This computer model differs from previous models in its use of the interactive mode, structured programming, modular design, and state-of-the-art graphics displays. In addition, the model maximizes the efficiency of computer time through synchronization of loosely coupled dual processors and the design of a restart capability. Since the model is designed for adaptability and for users with limited computer skills, it is anticipated that it will have many applications in the scientific community.

Essays on the determinants of private investment: The effects of relative price uncertainty and political instability

The objective of this study was to provide empirical evidence on the effects of relative price uncertainty and political instability on private investment. My effort is expressed in a single-equation model using macroeconomic and socio-political data from eight Latin American countries for the period 1970–1996. Relative price uncertainty is measured by the implied volatility of the exchange rate and political instability is measured by using indicators of social unrest and political violence. ^ I found that, after controlling for other variables, relative price uncertainty and political instability are negatively associated with private investment. Macroeconomic and political stability are key ingredients for the achievement of a strong investment response. This highlights the need to develop the state and build a civil society in which citizens can participate in decision-making and express consent without generating social turmoil. At the same time the government needs to implement structural policies along with relative price adjustments to eliminate excess volatility in price movements in order to provide a stable environment for investment. ^

A study of stock market fluctuations and their relation to business conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Fair price and its effect on willingness to purchase

The purpose of the present research is to demonstrate the influence of a fair price (independent of the subjective evaluation of the price magnitude) on buyers' willingness to purchase. The perceived fairness of a price is conceived to have three components: perceived equity, perceived need, and inferred compliance of the seller to the process rules of pricing. These components reflect the Theories of Distributive Justice (as adjusted for conditions of need) and Procedural Justice.^ The effect of the three components of a fair price on willingness to purchase is depicted in a theoretically causal chain model. Based on the Theories of Dissonance and Attribution, conditions of inequity and need activate concerns for Procedural Justice. Under conditions of inequity and need, buyers tend to infer that the seller has not complied with the generally accepted pricing practices, thus violating the social norms of Procedural justice. Inferred violations of Procedural Justice influence the buyer's attitude toward the seller. As predicted by the Theory of Reasoned Action, attitude is then positively related to willingness to purchase.^ The model was tested with a survey-based experiment conducted with 408 respondents. Two levels of both equity and need were manipulated with scenarios, a common research method in studies of Distributive and Procedural Justice. The data were analyzed with a structural equation model using LISREL. Although the effect of the "need" manipulation was insignificant, the results indicated a good fit of the model (Chi-square = 281, Degrees of Freedom = 104, Goodness of Fit Index =.924). The conclusion is that the fairness of a price does have a significant effect on willingness to purchase, independent of the subjective evaluation of the objective price. ^

Differences in treatment and intervention needs of girls arrested for status versus criminal offenses

The purpose of this research was to explore the differences in factors associated with girls' status and criminal arrests. This study used data from six juvenile justice programs in multiple states, which was derived from the Juvenile Assessment and Intervention System (JAIS). The sample of 908 adolescent girls (ages 13-19) was ethnically and racially diverse (41% African American, 32% white, 12% Hispanic, 11% Native American and 4% Other). A structural equation model (SEM) was analyzed which tested the potential effects of adolescent substance use, truancy, suicidal ideation/attempt, self-harm, peer legal trouble, parental criminal history and parental and non-parental abuse on type of offense (status and criminal) and whether any of these relationships varied as a function of race/ethnicity. ^ Complex relationships emerged regarding both status and more serious criminal arrests. One of the most important findings was that distinct and different patterns of factors were associated with status arrests compared to criminal arrests. For example, truancy and parental abuse were directly associated with status offenses, whereas parental criminal history was directly related to criminal arrests. However, both status and criminal arrests shared common associations, including substance use, which signifies that certain variables are influential regarding both non-criminal and more serious crimes. In addition, significant meditating influences were observed which help to explain some underlying mechanisms involved in girls' arrest patterns. Finally, race/ethnicity moderated a key relationship, which has serious implications for treatment. ^ In conclusion, the present study is an important contribution to research regarding girls' delinquency in that it overcomes limitations in the existing literature in four primary areas: (1) it utilizes a large, multi-state, ethnically and racially diverse sample of justice system-involved girls, (2) it examines numerous co-occurring factors influencing delinquency from multiple domains (family, school, peers, etc.) simultaneously, (3) it formally examines race/ethnicity as a moderator of these multivariate relationships, and (4) it looks at status and criminal arrests independently in order to highlight possible differences in the patterning of risk factors associated with each. These findings have important implications for prevention, treatment and interventions with girls involved in the juvenile justice system.^

Achieving zero accidents—A strategic framework for continuous safety improvement in the construction industry

In the U.S., construction accidents remain a significant economic and social problem. Despite recent improvement, the Construction industry, generally, has lagged behind other industries in implementing safety as a total management process for achieving zero accidents and developing a high-performance safety culture. One aspect of this total approach to safety that has frustrated the construction industry the most has been “measurement”, which involves identifying and quantifying the factors that critically influence safe work behaviors. The basic problem attributed is the difficulty in assessing what to measure and how to measure it—particularly the intangible aspects of safety. Without measurement, the notion of continuous improvement is hard to follow. This research was undertaken to develop a strategic framework for the measurement and continuous improvement of total safety in order to achieve and sustain the goal of zero accidents, while improving the quality, productivity and the competitiveness of the construction industry as it moves forward. The research based itself on an integral model of total safety that allowed decomposition of safety into interior and exterior characteristics using a multiattribute analysis technique. Statistical relationships between total safety dimensions and safety performance (measured by safe work behavior) were revealed through a series of latent variables (factors) that describe the total safety environment of a construction organization. A structural equation model (SEM) was estimated for the latent variables to quantify relationships among them and between these total safety determinants and safety performance of a construction organization. The developed SEM constituted a strategic framework for identifying, measuring, and continuously improving safety as a total concern for achieving and sustaining the goal of zero accidents.