Community-based older adults' perceptions of factors that influence successful aging in place

The purpose of this study was to obtain an understanding of older adults' perceptions of independence and the factors that allow them to remain living independently in the community. A questionnaire was mailed to a random sample of 500 community-based older adults. One hundred seventy eight questionnaires were returned (36%). Respondents were asked questions related to independence, self-health rating, functional difficulties, and social supports. Most respondents indicated Mental Health (97%), Physical Health (97%), Control of choices (97%), and Social Support Systems (93%) contributed to maintaining independence in the community. Age, education, fewer chronic health conditions, and a higher self-health rating were found to be significant predictors of actual independence. Family members were identified as the primary source of assistance with advice on major life decisions and financial matters. Findings indicate age, education, health status and the social support of family and friends all play an important role for older adults to live independently in the community. Occupational therapy could be instrumental in extending the health, highest level of independent functioning, and the number of years older adults remain living in the community.

Social construction of Geographic Information Systems. (Volumes I and II)

Geographic Information Systems (GIS) is an emerging information technology (IT) which promises to have large scale influences in how spatially distributed resources are managed. It has had applications in the management of issues as diverse as recovering from the disaster of Hurricane Andrew to aiding military operations in Desert Storm. Implementation of GIS systems is an important issue because there are high cost and time involvement in setting them up. An important component of the implementation problem is the "meaning" different groups of people who are influencing the implementation give to the technology. The research was based on the theory of (theoretical stance to the problem was based on the) "Social Construction of Knowledge" systems which assumes knowledge systems are subject to sociological analysis both in usage and in content. An interpretive research approach was adopted to inductively derive a model which explains how the "meanings" of a GIS are socially constructed. The research design entailed a comparative case analysis over two county sites which were using the same GIS for a variety of purposes. A total of 75 in-depth interviews were conducted to elicit interpretations of GIS. Results indicate that differences in how geographers and data-processors view the technology lead to different implementation patterns in the two sites.

Theoretical and applied evaluations of facial composite systems

Police often use facial composites during their investigations, yet research suggests that facial composites are generally not effective. The present research included two experiments on facial composites. The first experiment was designed to test the usefulness of the encoding specificity principle for determining when facial composites will be effective. Instructions were used to encourage holistic or featural cues at encoding. The method used to construct facial composites was manipulated to encourage holistic or featural cues at retrieval. The encoding specificity principle suggests that an interaction effect should occur. If the same cues are used at encoding and retrieval, better composites should be constructed than when the cues are not the same. However, neither the expected interaction nor the main effects for encoding and retrieval were significant. The second study was conducted to assess the effectiveness of composites generated by two different facial composite construction systems, E-Fit and Mac-A-Mug Pro. These systems differ in that the E-Fit system uses more sophisticated methods of composite construction and may construct better quality facial composites. A comparison of E-Fit and Mac-A-Mug Pro composites demonstrated that E-Fit composites were of better quality than Mac-A-Mug Pro composites. However, neither E-Fit nor Mac-A-Mug Pro composites were useful for identifying the target person from a photograph lineup. Further, lineup performance was at floor level such that both E-Fit and Mac-A-Mug Pro composites were no more useful than a verbal description. Possible limitations of the studies are discussed, as well as suggestions for future research. ^

Evaluating the Appropriateness of Project Delivery Systems for Different Trenchless Methods

Trenchless methods have been considered to be a viable solution for pipeline projects in urban areas. Their applicability in pipeline projects is expected to increase with the rapid advancements in technology and emerging concerns regarding social costs related to trenching methods. Selecting appropriate project delivery system (PDS) is a key to the success of trenchless projects. To ensure success of the project, the selected project delivery should be tailored to trenchless project specific characteristics and owner needs, since the effectiveness of project delivery systems differs based on different project characteristics and owners requirements. Since different trenchless methods have specific characteristics such rate of installation, lengths of installation, and accuracy, the same project delivery systems may not be equally effective for different methods. The intent of this paper is to evaluate the appropriateness of different PDS for different trenchless methods. PDS are examined through a structured decision-making process called Fuzzy Delivery System Selection Model (FDSSM). The process of incorporating the impacts of: (a) the characteristics of trenchless projects and (b) owners’ needs in the FDSSM is performed by collecting data using questionnaires deployed to professionals involved in the trenchless industry in order to determine the importance of delivery systems selection attributes for different trenchless methods, and then analyzing this data. The sensitivity of PDS rankings with respect to trenchless methods is considered in order to evaluate whether similar project delivery systems are equally effective in different trenchless methods. The effectiveness of PDS with respect to attributes is defined as follows: a project delivery system is most effective with respect to an attribute (e.g., ability to control growth in costs ) if there is no project delivery system that is more effective than that PDS. The results of this study may assist trenchless project owners to select the appropriate PDS for the trenchless method selected.

Assessment of policies for innovative financing in infrastructure systems

Infrastructure systems are drivers of the economy in the nation. A dollar spent on infrastructure development yields roughly double the initial spending in ultimate economic output in the short term; and over a twenty-year period, and generalized ‘public investment’ produces an aggregated $3.21 of economic activity per $1.00 spent [1]. Thus, formulation of policies pertaining to infrastructure investment and development is of significance affecting the social and economic wellbeing of the nation. The aim of this policy brief is to evaluate innovative financing in infrastructure systems from two different perspectives: (1) through consideration of the current condition of infrastructure in the U.S., the current trends in public spending, and the emerging innovative financing tools; (2) through evaluation of the roles and interactions of different agencies in the creation and the diffusion of innovative financing tools. Then using the example of transportation financing, the policy brief provides an assessment of policy landscapes which could lead to the closure of infrastructure financing gap in the U.S and proposes strategies for citizen involvement to gain public support of innovative financing.

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.