TOWARD INTELLIGENT DECISION SUPPORT SYSTEMS: SURVEY, ASSESSMENT AND DIRECTION

A survey of relevant literature serves as the basis for an assessment of research on integration of decision support systems and artificial intelligence. The analysis identifies the need for a unifying framework with which to direct such research. The characteristics required for such a framework are highlighted and shown to be well-suited to the artificial intelligence concept of deep knowledge. A deep knowledge architecture for intelligent decision support systems is presented and proposed as a basis for integration of the two disciplines

NEURAL NETWORKS IN FORECASTING AND DECISION MAKING

Neural networks (NN) have been widely touted as solving many forecasting and decision modeling problems. For example, they are argued to be able to model easily any type of parametric or non-parametric process and also automatically and optimally transform the input data. Also, they are easy to embed in information systems and they can learn how to perform simple forecasting and decision making tasks without human input. Our research-in-progress evaluates these claims. We will spend the first half of the session reviewing our work comparing neural networks to classical techniques in time series forecasting, regression-based causal forecasting, and regression-based decision models. In tile second half of the session, we will discuss the art and science of building these models. In Hill, O\u27Connor and Remus (1992), time series forecasts based on neural networks were compared with forecasts from six statistical time series methods (including exponential smoothing and Box-Jenkins) and two judgment-based methods; we did this for 111 real financial time series. The classical methods were all estimated by experts. Across all series, the neural networks did better than or as good as statistical and judgment methods. In Marquez et al. (forthcoming), data representing three common bivariate functional forms used in causal forecasting (linear, log-linear, and reciprocal) were generated and the performance of the neural network models was compared against the true regression model across differing functional forms, sample sizes, and noise levels. The results showed that neural network models perform within 2% of the mean absolute percentage error (MAPE); this is very good performance in the real world. This work is continuing as Marquez studies issues such as the vulnerability of neural networks and regression to multicolinearity, outliers, and other data problems. In Remus and Hill (forthcoming), tile production scheduling decisions as modeled by neural networks and regression-based decision rules for sixty-two decision makers were compared. Neural network models performed as well as but not better than those using the linear regression models. In Hill and Remus (forthcoming), the above research was continued and composite neural network models were estimated. The neural networks performed better than both the classical models and neural networks from the earlier study. The coinposite neural network also performed at least as well as classical composite models

Telling the tale of the first stars

HE 0107-5240 is a star in more than once sense of the word. Chemically, it is the most primitive object yet discovered, and it is at the centre of debate about the origins of the first elements in the Universe.Comment: 3 pages, 0 figures, published in Nature "News and Views," Apr. 24, 200

Effects of Perceiver / Target Gender and Social Networking Presence on Web-based Impression Formation

As the Web has expanded in its use and utility it has fundamentally changed the way in which individuals gather and use information. This paper suggests that those changes give rise to tangible and significant effects in the impressions people form of others using Web-based information. This study explores the impacts of perceiver gender, target gender, and social networking presence on subjects’ perceptions of potential teammates otherwise unknown to them as revealed by ratings they assign based only on search engine results. Experiments reveal differences in how male and female perceivers view others’ social networking activity in general and suggest that how the perceiver gender matches, or differs, from the gender of the target affects how social networking presence plays into impression formation. Findings hold implications for professionals, academics and individuals concerned with the role that Web-based information plays in impression formation and how inherent gender-based biases may affect power and politics in the workplace and beyond

Potential Sinks for Geologic Storage of CO2 Generated in the Carolinas

This document summarizes a scoping study of the current state of knowledge of carbon storage options for our geographic area. The focus is on one aspect of carbon capture and storage—identification of deep saline aquifers in which carbon dioxide (CO2 ) generated in the Carolinas might be stored. The study does not address other aspects of CO2 storage projects, such as capture and compression of the gas, well construction and development, or injection. Transport of CO2 is touched upon in this study but has not been fully addressed. The information contained in this document is primarily from review of published geologic literature and unpublished data. No field data collection has been completed as part of this study. Further work will be necessary to increase confidence in the suitability of the potential CO2 storage sites identified in this report. This study does not address the regulatory, environmental, or public policy issues associated with carbon storage, which are under development at this time.Duke Energy, Progress Energy, Santee Cooper Power, South Carolina Electric and Gas, Electric Power Research Institute (EPRI), Southern States Energy Board (SSEB)Bureau of Economic Geolog

A Comprehensive Audit of Professional Development for K-12 School Leaders in the Commonwealth of Virginia

The intent of this paper is to provide a mixed-methods audit of professional development provided to K-12 school leadership in Virginia\u27s diverse landscape to include identification of providers, funding, effectiveness, and expectations. In the Commonwealth of Virginia, geographical, political, and socio-economical differences across 132 school divisions cause variability in leaders\u27 experiences with professional development. A mixed-methods approach was used, including a review of current literature, an online survey, virtual interviews, and virtual focus group discussions. This data collection results in a comprehensive audit of professional development provided to school leaders in Virginia\u27s diverse landscape. The study defines effective professional development for school leaders and considers commonalities and disparities of school leaders\u27 experience with professional development, including divisions\u27 commitment to funding, leaders’ access to providers, and leaders’ exposure to traditional and emerging content topics in order to provide recommendations to Virginia Commonwealth University\u27s School of Education as an external provider of professional development for school leaders

Near-Infrared Spectroscopy of Carbon-Enhanced Metal-Poor Stars. I. A SOAR/OSIRIS Pilot Study

We report on an abundance analysis for a pilot study of seven Carbon-Enhanced Metal-Poor (CEMP) stars, based on medium-resolution optical and near-infrared spectroscopy. The optical spectra are used to estimate [Fe/H], [C/Fe], [N/Fe], and [Ba/Fe] for our program stars. The near-infrared spectra, obtained during a limited early science run with the new SOAR 4.1m telescope and the Ohio State Infrared Imager and Spectrograph (OSIRIS), are used to obtain estimates of [O/Fe] and 12C/13C. The chemical abundances of CEMP stars are of importance for understanding the origin of CNO in the early Galaxy, as well as for placing constraints on the operation of the astrophysical s-process in very low-metallicity Asymptotic Giant Branch (AGB) stars. This pilot study includes a few stars with previously measured [Fe/H], [C/Fe], [N/Fe],[O/Fe], 12C/13C, and [Ba/Fe], based on high-resolution optical spectra obtained with large-aperture telescopes. Our analysis demonstrates that we are able to achieve reasonably accurate determinations of these quantities for CEMP stars from moderate-resolution optical and near-infrared spectra. This opens the pathway for the study of significantly larger samples of CEMP stars in the near future. Furthermore, the ability to measure [Ba/Fe] for (at least the cooler) CEMP stars should enable one to separate stars that are likely to be associated with s-process enhancements (the CEMP-s stars) from those that do not exhibit neutron-capture enhancements (the CEMP-no stars).Comment: 27 pages, including 5 tables, 6 figures, accepted for publication in The Astronomical Journa

AMCIS 2008 Panel Report: Aging Content on the Web: Issues, Implications, and Potential Research Opportunities

Since its inception in the early 1990s, the World Wide Web (Web) has grown enormously. According to the “official Google blog” (Google 2008), the Web had 1 trillion (as in 1,000,000,000,000) unique coexisting URL’s as of July 25, 2008. Given the exponential growth of the Web over time, an issue that is likely to gain prominence is that of outdated information. This is especially important to study since many of us rely on the Web to find facts in order to take decisions. For example, for students and researchers, the “date” of a document is important for scholarship and student work. However, getting an accurate date on content is challenging, and furthermore, outdated pages that are not deleted from Web servers will continue to be returned in response to Web searches. The panel, held at the 2008 Americas Conference on Information Systems in Toronto, Canada, identified a number of research issues and opportunities that arise as a result of this phenomenon