Decision Analysis for the Evaluation of Risk in Nuclear Waste Management

The implementation of a nuclear waste management technology raises several issues concerning the regulation of social risk. The most basic of those issues are how to regulate a technology when the uncertainties in social consequences are important, and how to incorporate the relevant social values in the regulations. This paper presents a decision analytic approach to resolving these issues, based on the development of radiological risk evaluation indices. While it is essentially a case study, describing work carried out for the U.S. Nuclear Regulatory Commission, this case is used to discuss the more general issues involved. We begin by discussing the need for risk evaluation to provide a clear and defensible basis for regulating technologies involving social risk. We then present an overview of the problem of evaluating the risk of nuclear waste management, and an overview of our approach. That is followed by a development of risk evaluation indices for the regulation of nuclear waste management. The indices developed are expected utilities, based on preferences elicited from groups of people. The use of the indices developed is illustrated in a hypothetical example. Finally, components of the analysis requiring further development are identified and discussed, and the usefulness of the methodology evaluated

Quantum dot emission from site-controlled ngan/gan micropyramid arrays

InxGa1−xN quantum dots have been fabricated by the selective growth of GaN micropyramid arrays topped with InGaN/GaN quantum wells. The spatially, spectrally, and time-resolved emission properties of these structures were measured using cathodoluminescence hyperspectral imaging and low-temperature microphotoluminescence spectroscopy. The presence of InGaN quantum dots was confirmed directly by the observation of sharp peaks in the emission spectrum at the pyramid apices. These luminescence peaks exhibit decay lifetimes of approximately 0.5 ns, with linewidths down to 650 me

Sensing Subjective Well-being from Social Media

Subjective Well-being(SWB), which refers to how people experience the quality of their lives, is of great use to public policy-makers as well as economic, sociological research, etc. Traditionally, the measurement of SWB relies on time-consuming and costly self-report questionnaires. Nowadays, people are motivated to share their experiences and feelings on social media, so we propose to sense SWB from the vast user generated data on social media. By utilizing 1785 users' social media data with SWB labels, we train machine learning models that are able to "sense" individual SWB from users' social media. Our model, which attains the state-by-art prediction accuracy, can then be used to identify SWB of large population of social media users in time with very low cost.Comment: 12 pages, 1 figures, 2 tables, 10th International Conference, AMT 2014, Warsaw, Poland, August 11-14, 2014. Proceeding

High-Efficiency Neutron Detectors

This research was sponsored by the National Science Foundation Grant NSF PHY 87-1440

Energy Dependence of Cross Sections for Stretched States Excited in (p,n) Reactions

This research was sponsored by the National Science Foundation Grant NSF PHY 87-1440

High-Spin States Excited Via (p,n) Reactions

This work was supported by the National Science Foundation Grant NSF PHY 81-14339 and by Indiana Universit

Stretched State Excitations in the 26-Mg(p,n)26-Al Reaction at 134 MeV

This research was sponsored by the National Science Foundation Grant NSF PHY 87-1440

Performance of Large-Volume, Mean-Timed Neutron Detectors

This work was supported by the National Science Foundation Grants NSF PHY 78-22774 A03, NSF PHY 81-14339, and by Indiana Universit

High-Spin "Stretched" States Excited in (p,n) Reactions

This work was supported by the National Science Foundation Grant NSF PHY 78-22774 A02 & A03 and by Indiana Universit

Performance of Large-Volume Mean-Timed Neutron Detectors

Supported by the National Science Foundation and Indiana Universit