Temporal changes in immigration stress, adaptation, and the factors contributing to the immigration -adaptation process in newly immigrant parents

The adaptation process to a new land can be an arduous transition for families who migrate from their countries in an attempt to evade negative life conditions. Family-based immigration has been the cornerstone of immigration policy for the U.S. However, there has been a relative lack of attention given in immigration studies to the impact of immigration particularly on parents. Furthermore, little is known about their adjustment to their post-migration circumstances, particularly the initial phase of migration, where the psychological impact of immigration tends to be concentrated. It is even rarer that investigators have addressed longitudinally the dynamic process of parents' adaptation to a new ecology, which can shed a great deal of light on its mechanisms. In this dissertation, changes over time in levels of stress, adjustment (affect balance and life satisfaction), and the factors (social support, economic hardship, and discrimination) contributing to stress and adjustment were examined in newly immigrant parents from Argentina, Colombia, Cuba, Haiti, and the West Indies. Moderating effects of gender and country-of-origin were examined as well. This study also aimed to investigate to what extent the contributing factors impacted stress and adjustment, not only concurrently, but also over the first three years of post-migration. Analysis of variance results showed that both affect balance and social support increased whereas life satisfaction decreased over time. There was no significant change in stress, however. Both gender and group effects were also observed. Mothers experienced higher stress whereas fathers experienced higher discrimination. Among groups, Haitians appeared at the greatest risk in terms of stress, discrimination, and economic hardship. A structural equation modeling analysis showed that the relative importance of contributing factors changed over time in the process of immigrants' adaptation. Yet, social support emerged as a powerful protective factor in that its effects carried over time, and discrimination was a primary mediator through which other predictors were related to stress and adjustment. These findings shed light on the "hows and whys" of the immigration-adaptation process, by demonstrating the significance of specific conditions of life change to psychological outcomes as newly immigrant parents adapt to their post-migration ecology.

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^