Social support, risk, and adjustment of immigrant preadolescents

The current study was designed to explore the salience of social support, immigrant status, and risk in middle childhood and early adolescence across two time periods as indicated by measures of school adjustment and well-being. Participants included 691 children of public elementary schools in grades 4 and 6 who were interviewed in 1997 (Time 1) and reinterviewed two years later (Time 2); 539 were U.S.-born, and 152 were foreign-born. ^ Repeated measures multivariate analyses of variance (MANOVA's) were conducted to assess the effects of immigrant status and risk on total support, well-being, and school adjustment from Time 1 to Time 2. Follow-up analyses, including Student-Newman-Keuls post hoc tests, were used to test the significance of the differences among the means of support categories (low and high), immigrant status (U.S. born and non-U.S. born), risk (low and high) and time (time 1 and time 2). ^ Results showed that immigrant participants in the high risk group reported significantly lower levels of support than their peers. Further, children of low risk at Time 2 indicated the highest levels of support. Second, immigrant preadolescents, preadolescents who reported low levels of social support, and preadolescents of the high risk reported lower levels of emotional well-being. There was also an interaction of support by risk by time, indicating that children who are at risk and had low levels of social support reported more emotional problems at Time 1. Finally, preadolescents who are at risk and preadolescents who reported lower levels of support were more likely to show school adaptation problems. Findings from this study highlight the importance of a multivariable approach to the study of support, emotional adjustment, and academic adjustment of immigrant preadolescents. ^

Bringing ESL Students to Literacy and Social Integration: Barriers and Strategies

In this paper, the author explores the barriers that students of English as a Second Language (ESL) face in coming fully literate in English and fully integrated into American society. The barriers cited include inadequate training of reading specialists to work with ESL students, turf wars between reading specialists and ESL teachers, inadequate preparation of students for high school and higher education, as well as a lack of academic research on developing reading skills in ESL students. Strategies for overcoming these barriers include improvement in teacher training, understanding of the student population and students’ first language (L1), and promoting success in literacy.

Social Learning Theory and Prison Work Release Programs

The authors’ review of literature about Bandura’s (1977) social learning theory and self-efficacy leads to implications on how this theory can positively affect prison work release programs and inmate post-release outcomes. Additionally, several causes of deviant behavior have been explained by social learning theory concepts.

Mining the online social network data: Influence, summarization, and organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Mining the Online Social Network Data: Influence, Summarization, and Organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Solving the mystery of Guanxi-a sociological explanation of social exchange and social networking in Guanxi practice

Guanxi, loosely defined as "inter-personal relations" or "personal connections," is one of the key socio-cultural concepts in understanding Chinese society. This thesis presented a theoretical examination of the Chinese socio-cultural concept of guanxi. By using a broad survey of the available literature, this thesis established the following points: Social structures shape and define the development of guanxi practice in Chinese society. Guanxi relationships are based on the social exchange of gifts and favors in dyadic or multi-stranded social networks. While following the general rules of reciprocity found in social exchange, guanxi exchange is also governed by the internalized social norms such as mianzi (face) and renqing (humanized obligation underpinned by human sentiment). Guanxi relationships are also network-oriented, featuring ties based on familiarity and mutual trust, and characterized by an interplay between expressiveness and instrumentalism.

Hybrid Power System Intelligent Operation and Protection Involving Distributed Architectures and Pulsed Loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.