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Articles 1 - 9 of 9
Full-Text Articles in Life Sciences
Tracing God's Hand In Redemption: Exploring Evidence Of The Imago Dei In Human Molecular Biology, James Don Johansen
Tracing God's Hand In Redemption: Exploring Evidence Of The Imago Dei In Human Molecular Biology, James Don Johansen
Doctoral Dissertations and Projects
This interdisciplinary dissertation examines how Imago Dei and the impacts and redemption of sin may be observable in molecular biology. It introduces the idea of biological redemption, where, in support of our Imago Dei mission and calling, our bodies can respond to environmental and spiritual factors with biological redemptive adaptations. This project does both theological and scientific assessment. It explores how God is engaged with individuals in community via spiritual social networks, where Christian communities act as an ecosystem in which individuals can thrive and undergo spiritual formation, living out Christian spiritual practices. The main question this dissertation addresses is: …
In Search Of Safety, Negotiating Everyday Forms Of Risk: Sex Work, Criminalization, And Hiv/Aids In The Slums Of Kampala, Serena Cruz
FIU Electronic Theses and Dissertations
This dissertation offers an in-depth descriptive account of how women manage daily risks associated with sex work, criminalization, and HIV/AIDS. Primary data collection took place within two slums in Kampala, Uganda over the course of fourteen months. The emphasis was on ethnographic methodologies involving participant observation and informal and unstructured interviewing. Insights then informed document analysis of international and national policies concerning HIV prevention and treatment strategies in the context of Uganda. The dissertation finds social networks and social capital provide the basis for community formation in the sex trade. It holds that these interpersonal processes are necessary components for …
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Kno.e.sis Publications
We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user behavioral patterns with respect to specific trending topics on Twitter. Going beyond previous efforts that have analyzed driving factors in whether and when a user will publish topic-relevant tweets, here we seek to predict the strength of content generation which allows more accurate understanding of Twitter users' behavior and more effective utilization of the online social network for diffusing information. Unlike traditional approaches, we consider multiple dimensions into one regression-based prediction framework covering network structure, user interaction, content characteristics and past activity. Experimental results on three large Twitter …
Trust Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Trust Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Trust relationships occur naturally in many diverse contexts such as collaborative systems, e-commerce, interpersonal interactions, social networks, semantic sensor web, etc. As collaborating agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update become critical. There is a need to find online substitutes for traditional (direct or face-to-face) cues to derive measures of trust, and create efficient and secure system for managing trust, to support decision-making. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its semantics …
Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
Trust is an amorphous concept that is becoming Increasingly important in many domains, such as P2P networks, E-commerce, social networks, and sensor networks. While we all have an intuitive notion of trust, the literature is scattered with a wide assortment of differing definitions and descriptions; often these descriptions are highly dependent on a single domain or application of interest. In addition, they often discuss orthogonal aspects of trust while continuing to use the general term “trust”. In order to make sense of the situation, we have developed an ontology of trust that integrates and relates its various aspects into a …
Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Trust and reputation are becoming increasingly important in diverse areas such as search, e-commerce, social media, semantic sensor networks, etc. We review past work and explore future research issues relevant to trust in social/sensor networks and interactions. We advocate a balanced, iterative approach to trust that marries both theory and practice. On the theoretical side, we investigate models of trust to analyze and specify the nature of trust and trust computation. On the practical side, we propose to uncover aspects that provide a basis for trust formation and techniques to extract trust information from concrete social/sensor networks and interactions. We …
Artist Ranking Through Analysis Of On-Line Community Comments, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Christine Robson, Nachiketa Sahoo
Artist Ranking Through Analysis Of On-Line Community Comments, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Christine Robson, Nachiketa Sahoo
Kno.e.sis Publications
We describe an approach to measure the popularity of music tracks, albums and artists by analyzing the comments of music listeners in social networking online communities such as MySpace. This measure of popularity appears to be more accurate than the traditional measure based on album sales figures, as demonstrated by our focus group study. We faced many challenges in our attempt to generate a popularity ranking from the user comments on social networking sites, e.g., broken English sentences, comment spam, etc. We discuss the steps we took to overcome these challenges and describe an end to end system for generating …
Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang
Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang
Kno.e.sis Publications
In this work, we investigate techniques to monitize user activity on public forums, marketplaces and groups on social network sites. Our approach involves (a) identifying the monetization potential of user posts and (b) eliminating o- topic content in monetizable posts to use the most relevant keywords for advertising. Our first user study involving 30 users and data from MySpace and Facebook, shows that 52% of ad impressions shown after using our system were more targeted compared to the 30% relevant impressions generated without using our system. A second smaller study suggests that profile ads that are based on user activity …
Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth
Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth
Kno.e.sis Publications
Social networking, distributed problem solving and human computation have gained high visibility. Wikipedia is a well established service that incorporates aspects of these three fields of research. For this reason it is a good object of study for determining quality of solutions in a social setting that is open, completely distributed, bottom up and not peer reviewed by certified experts. In particular, this paper aims at identifying semantic convergence of Wikipedia articles; the notion that the content of an article stays stable regardless of continuing edits. This could lead to an automatic recommendation of good article tags but also add …