Structural adjustment and labor in Jamaica and the Dominican Republic

Statement of the problem. It seeks to examine whether structural adjustment in Jamaica produced the desired developmental effects for labor--both organized and non-unionized--and if there is any significant difference in the Dominican Republic, which did not undergo that economic transformation. The research hypothesis is; "Structural Adjustment leads to Marginalization of labor."^ Methodology used. The methodology is mostly a straight cross-sectional analysis using data sets and publications from the UN, ILO, World Bank and IDB, as well as local statistical sources. The dissertation is primarily an historical to contemporary analysis of the Jamaican experience under structural adjustment, as it related to labor. To a greater extent it involves a straight cross-national comparison on the historical experiences of each country and a discussion of the relative similarities and differences between them, and the impact these features had on labor.^ Summary of findings. In the end, the question is asked as to whether internal factors are important in the relative success or failure of development strategies. From the data there is some indication that under structural adjustment there has been limited economic benefits for labor in Jamaica while labor standards have not improved. In the Dominican Republic the economic performance has been similar but the labor standards have improved significantly. This thus leads to the conclusion that structural adjustment may have been a factor in the resistance to labor's empowerment.^ Nevertheless, the study also shows that there may have been a causal role which local power relations had. The suggestion from the study is that in analyzing the phenomenon, attention must be paid to internal as well as external dynamics and variables. ^

Big city days: Race and labor in early Miami, 1914--1925

The purpose of this study was to recast Miami's social history during the first three decades of the twentieth century through an examination of working class life. The thesis attempts to fill a gap in the literature while also expanding on the advances made in race and class studies of the United States. Through an analysis of local newspapers, minutes of a carpenter's union, and other archival sources, the thesis demonstrates how white workers obtained a virtual monopoly in skilled jobs over black workers, particularly in the construction industry, and exacted economic pressure on business through the threat of work stoppages. Driven by the concern to maintain smooth and steady growth amidst a vibrant tourist economy, business reluctantly worked with labor to maintain harmonious market conditions. Blacks, however, were able to gain certain privileges in the labor market through challenging the rigid system of segregation and notions of what constituted skilled labor. The findings demonstrate that Miami's labor unions shaped the city's social, cultural, and political landscape but the extent of their power was limited by booster discourse and the city's dependence on tourism. ^

Freeway travel time estimation and prediction using dynamic neural networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. ^ This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.^

Three essays on entrepreneurial entry, serial entrepreneurship, and labor turnover

This study explores two important aspects of entrepreneurship — liquidity constraints and serial entrepreneurs, with an additional analysis of occupational choice among wage workers. In the first essay, I revisit the question of whether entrepreneurs face liquidity constraints in business formation. The principle challenge is that wealth is correlated with unobserved ability, and adequate instruments are often difficult to identify. This paper uses the son's birth order as an instrument for household wealth. I exploit the data available in the Korean Labor and Income Panel Study, and find evidence of liquidity constraints associated with self-employment in South Korea. The second essay develops and tests a model that explains entry into serial entrepreneurship and the performance of serial entrepreneurs as the result of selection on innate ability. The model supposes that agents establish businesses with imperfect information about their entrepreneurial ability and the profitability of business ideas. Agents continually observe signals with which they update their beliefs, and this process eventually determines their next business choice. Selection on ability induces a positive correlation between entrepreneurial experience (measured by previous business earnings and founding experience) and serial business formation, as well as its subsequent performance. The predictions in the model are tested using panel data from the NLSY79. The analysis permits a distinction to be made between selection on innate ability and learning by doing. Motivated by previous empirical findings that white-collar workers had higher turnover rates than blue-collar workers during firm expansion, the third essay further examines job turnover among workers with or without specific skills. I present a search-matching model, which predicts that when firm growth is driven by technological advance, workers whose skills are specific to the obsolete technology show a higher tendency to separate from their jobs. This hypothesis is tested with data from the PSID. I find supportive evidence that in the context of technological change, having an occupation requiring specific skills, such as computer specialists or engineers, increases the odds of job separation by nearly eight percent. ^

Mitigating congestion by integrating time forecasting and realtime information aggregation in cellular networks

An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.

An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.

Buried Time Capsule and Plaque

The buried time capsule and plaque. The Annual FIU Student Leadership Summit is held each February on the Biscayne Bay Campus. The Summit is a one-day conference for current student leaders. The Summit offers our students the opportunity to learn from the vast expertise of our faculty and administrators, to share their leadership experiences with each other and to establish a network of support and cooperation within the university. On Feb. 2, 2013, we celebrated the 10th anniversary of holding the Student Leadership Summit. In honor of this occasion, we buried a time capsule containing materials from the day as well as messages from participants to the participants of 2023 when the time capsule is to be opened.

Effects of real -time captioning and sign language interpreting on the learning of college students who are deaf or hard of hearing

College personnel are required to provide accommodations for students who are deaf and hard of hearing (D/HoH), but few empirical studies have been conducted on D/HoH students as they learn under the various accommodation conditions (sign language interpreting, SLI, real-time captioning, RTC, and both). Guided by the experiences of students who are D/HoH at Miami-Dade College (MDC) who requested RTC in addition to SLI as accommodations, the researcher adopted Merten’s transformative-emancipatory theoretical framework that values perceptions and voice of students who are D/HoH. A mixed methods design addressed two research questions: Did student learning differ for each accommodation? What did students experience while learning through accommodations? Participants included 30 students who were D/HoH (60% women). They represented MDC’s majority minority population: 10% White (non-Hispanic), 20% Black (non-Hispanic, including Haitian/Caribbean), 67% Hispanic, and 3% other. Hearing loss, ranged from severe-profound (70%) to mild-moderate (30%). All were able to communicate with American Sign Language: Learning was measured while students who were D/HoH viewed three lectures under three accommodation conditions (SLI, RTC, SLI+RTC). The learning measure was defined as the difference in pre- and post-test scores on tests of the content presented in the lectures. Using repeated measure ANOVA and ANCOVA, confounding variables of fluency in American Sign Language and literacy skills were treated as covariates. Perceptions were obtained through interviews and verbal protocol analysis that were signed, videotaped, transcribed, coded, and examined for common themes and metacognitive strategies. No statistically significant differences were found among the three accommodations on the learning measure. Students who were D/HoH expressed thoughts about five different aspects of their learning while they viewed lectures: (a) comprehending the information, (b) feeling a part of the classroom environment, (c) past experiences with an accommodation, (d) individual preferences for an accommodation, (e) suggestions for improving an accommodation. They exhibited three metacognitive strategies: (a) constructing knowledge, (b) monitoring comprehension, and (c) evaluating information. No patterns were found in the types of metacognitive strategies used for any particular accommodation. The researcher offers recommendations for flexible applications of the standard accommodations used with students who are D/HoH.

Time trends and predictors of initiation for cigarette and waterpipe smoking among Jordanian school children: Irbid, 2008-2011

Smoking prevalence among adolescents in the Middle East remains high while rates of smoking have been declining among adolescents elsewhere. The aims of this research were to (1) describe patterns of cigarette and waterpipe (WP) smoking, (2) identify determinants of WP smoking initiation, and (3) identify determinants of cigarette smoking initiation in a cohort of Jordanian school children. ^ Among this cohort of school children in Irbid, Jordan, (age ≈ 12.6 at baseline) the first aim (N=1,781) described time trends in smoking behavior, age at initiation, and changes in frequency of smoking from 2008–2011 (grades 7–10). The second aim (N=1,243) identified determinants of WP initiation among WP-naïve students; and the third aim (N=1,454) identified determinants of cigarette smoking initiation among cigarette naïve participants. Determinants of initiation were assessed with generalized mixed models. All analyses were stratified by gender. ^ Baseline prevalence of current smoking (cigarettes or WP) for boys and girls was 22.9% and 8.7% respectively. Prevalence of ever- and current- any smoking, cigarette smoking, WP smoking, and dual cigarette/WP smoking was higher in boys than girls each year (p<0.001). At all time points, prevalence of WP smoking was higher than that of cigarette smoking (p<0.001) for both boys and girls. WP initiation was documented in 39% of boys and 28% of girls. Cigarette initiation was documented in 37% of boys and 24% of girls. Determinants of WP initiation included ever-cigarette smoking, low WP refusal self-efficacy, intention to smoke, and having teachers and friends who smoke WP. Determinants of cigarette smoking initiation included ever-WP smoking, low cigarette refusal self-efficacy, intention to start smoking cigarettes, and having friends and family who smoke.^ These studies reveal intensive smoking patterns at early ages among Jordanian youth in Irbid, characterized by a predominance of WP smoking. WP may be a vehicle for tobacco dependence and subsequent cigarette uptake. The sizeable incidence of WP and cigarette initiation among students of both sexes points to a need for culturally relevant smoking prevention interventions. Gender-specific factors, refusal skills, and smoking cessation of both WP and cigarettes for youth and their parents/teachers would be important components of such initiatives. ^

Time, Cost, and Environmental Impact Analysis for Sustainable Design at Multiple Building Levels

Construction projects are complex endeavors that require the involvement of different professional disciplines in order to meet various project objectives that are often conflicting. The level of complexity and the multi-objective nature of construction projects lend themselves to collaborative design and construction such as integrated project delivery (IPD), in which relevant disciplines work together during project conception, design and construction. Traditionally, the main objectives of construction projects have been to build in the least amount of time with the lowest cost possible, thus the inherent and well-established relationship between cost and time has been the focus of many studies. The importance of being able to effectively model relationships among multiple objectives in building construction has been emphasized in a wide range of research. In general, the trade-off relationship between time and cost is well understood and there is ample research on the subject. However, despite sustainable building designs, relationships between time and environmental impact, as well as cost and environmental impact, have not been fully investigated. The objectives of this research were mainly to analyze and identify relationships of time, cost, and environmental impact, in terms of CO2 emissions, at different levels of a building: material level, component level, and building level, at the pre-use phase, including manufacturing and construction, and the relationships of life cycle cost and life cycle CO2 emissions at the usage phase. Additionally, this research aimed to develop a robust simulation-based multi-objective decision-support tool, called SimulEICon, which took construction data uncertainty into account, and was capable of incorporating life cycle assessment information to the decision-making process. The findings of this research supported the trade-off relationship between time and cost at different building levels. Moreover, the time and CO2 emissions relationship presented trade-off behavior at the pre-use phase. The results of the relationship between cost and CO2 emissions were interestingly proportional at the pre-use phase. The same pattern continually presented after the construction to the usage phase. Understanding the relationships between those objectives is a key in successfully planning and designing environmentally sustainable construction projects.

Freeway Travel Time Estimation and Prediction Using Dynamic Neural Networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

Organized labor and U.S. foreign policy: The Solidarity Center in historical context

During the Cold War the foreign policy of the American Federation of Labor and Congress of Industrial Organizations (AFL-CIO), was heavily criticized by scholars and activists for following the lead of the U.S. state in its overseas operations. In a wide range of states, the AFL-CIO worked to destabilize governments selected by the U.S. state for regime change, while in others the Federation helped stabilize client regimes of the U.S. state. In 1997 the four regional organizations that previously carried out AFL-CIO foreign policy were consolidated into the American Center for International Labor Solidarity (Solidarity Center). My dissertation is an attempt to analyze whether the foreign policy of the AFL-CIO in the Solidarity Center era is marked by continuity or change with past practices. At the same time, this study will attempt to add to the debate over the role of non-governmental organizations (NGOs) in the post-Cold War era, and its implications for future study. Using the qualitative "process-tracing" detailed by of Alexander George and Andrew Bennett (2005) my study examines a wide array of primary and secondary sources, including documents from the NED and AFL-CIO, in order to analyze the relationship between the Solidarity Center and the U.S. state from 2002-2009. Furthermore, after analyzing broad trends of NED grants to the Solidarity Center, this study examines three dissimilar case studies including Venezuela, Haiti, and Iraq and the Middle East and North African (MENA) region to further explore the connections between U.S. foreign policy goals and the Solidarity Center operations. The study concludes that the evidence indicates continuity with past AFL-CIO foreign policy practices whereby the Solidarity Center follows the lead of the U.S. state. It has been found that the patterns of NED funding indicate that the Solidarity Center closely tailors its operations abroad in areas of importance to the U.S. state, that it is heavily reliant on state funding via the NED for its operations, and that the Solidarity Center works closely with U.S. allies and coalitions in these regions. Finally, this study argues for the relevance of "top-down" NGO creation and direction in the post-Cold War era.