An Interactive Computer Program for Assessing and Analyzing Preferences Concerning Multiple Objectives

An interactive computer program designed to facilitate the quantification of a decision maker's preferences for multiple objectives in terms of a multiattribute utility function is described. It is meant to alleviate many of the operational difficulties with current procedures for assessing and using multiattribute utility functions. The package includes commands for structuring the utility function, assessing single-attribute component utility functions of the overall multiattribute utility function, identifying the preference trade-offs between attributes, evaluating alternatives, and performing sensitivity analysis. Suggestions for using the program are included

Evaluating late detection capability against diverse insider adversaries

This paper describes a model for evaluating the late (after-the-fact) detection capability of material control and accountability (MCandA) systems against insider theft or diversion of special nuclear material. Potential insider cover-up strategies to defeat activities providing detection (e.g., inventories) are addressed by the model in a tractable manner. For each potential adversary and detection activity, two probabilities are assessed and used to fit the model. The model then computes the probability of detection for activities occurring periodically over time. The model provides insight into MCandA effectiveness and helps identify areas for safeguards improvement. 4 refs., 4 tabs

Assessing the integrity of local area network materials accountability systems against insider threats

DOE facilities rely increasingly on computerized systems to manage nuclear materials accountability data and to protect against diversion of nuclear materials or other malevolent acts (e.g., hoax due to falsified data) by insider threats. Aspects of modern computerized material accountability (MA) systems including powerful personal computers and applications on networks, mixed security environments, and more users with increased knowledge, skills and abilities help heighten the concern about insider threats to the integrity of the system. In this paper, we describe a methodology for assessing MA applications to help decision makers identify ways of and compare options for preventing or mitigating possible additional risks from the insider threat. We illustrate insights from applying the methodology to local area network materials accountability systems

Structured Assessment Approach: a microcomputer-based insider-vulnerability analysis tool

The Structured Assessment Approach (SAA) was developed to help assess the vulnerability of safeguards systems to insiders in a staged manner. For physical security systems, the SAA identifies possible diversion paths which are not safeguarded under various facility operating conditions and insiders who could defeat the system via direct access, collusion or indirect tampering. For material control and accounting systems, the SAA identifies those who could block the detection of a material loss or diversion via data falsification or equipment tampering. The SAA, originally desinged to run on a mainframe computer, has been converted to run on a personal computer. Many features have been added to simplify and facilitate its use for conducting vulnerability analysis. For example, the SAA input, which is a text-like data file, is easily readable and can provide documentation of facility safeguards and assumptions used for the analysis

The measurement and determinants of skill acquisition in young workers' first job

The article analyses participation in five types of training (formal on-site, formal off-site, informal co-worker training, learning by watching and learning by doing) and self-assessed skill acquisition in young Flemish workers' first job. A skill production function is estimated whereby the simultaneity of participation in the different types of training and skill acquisition is taken into account. The results clearly demonstrate the importance of informal training. Formal training participation is found to be only a fraction of total training participation. Moreover, the determinants of total training participation and skill acquisition differ from those of formal training participation. While some training types are complementary, others are clearly substitutes. Finally, most types of training generate additional skills. Nonetheless, learning by doing is found to be complementary to formal education in the production of both specific and general skills, whereas formal training serves as a substitute

Spatial And Quantitative Approache to Incorporating Stakeholder Values into Total Maximum Daily Loads: Dominguez Channel Case Study Final Report

Under the Federal Clean Water Act (CWA) states are required to develop and implement Total Maximum Daily Loads (TMDLs) for waters that are not achieving water quality standards. A TMDL specifies the maximum amount of a pollutant that a water body can receive, and allocates the pollutant loadings to point and non-point sources. Lawrence Livermore National Laboratory (LLNL) developed a tool to assist in improving the TMDL process. We developed a stakeholder allocation model (SAM) which uses multi-attribute utility theory to quantitatively structure the preferences of the major stakeholder groups. We then applied a Geographic Information System (GIS) to visualize the results. We used the Dominguez Channel Watershed in Los Angeles County, CA as our case study

Spatial and Quantitative Approach to Incorporating Stakeholder Values into Total Maximum Daily Loads: Dominguez Channel Case Study

The Federal Clean Water Act (CWA) Section 303(d)(1)(A) requires each state to identify those waters that are not achieving water quality standards. The result of this assessment is called the 303(d) list. The CWA also requires states to develop and implement Total Maximum Daily Loads (TMDLs) for these waters on the 303(d) list. A TMDL specifies the maximum amount of a pollutant that a water body can receive and still meet water quality standards, and allocates the pollutant loadings to point and non-point sources. Nationwide, over 34,900 segments of waterways have been listed as impaired by the Environmental Protection Agency (EPA 2006). The EPA enlists state agencies and local communities to submit TMDL plans to reduce discharges by specified dates or have them developed by the EPA. The Department of Energy requested Lawrence Livermore National Laboratory (LLNL) to develop appropriate tools to assist in improving the TMDL process. An investigation of this process by LLNL found that plans to reduce discharges were being developed based on a wide range of site investigation methods. Our investigation found that given the resources available to the interested and responsible parties, developing a quantitative stakeholder input process and using visualization tools to display quantitative information could improve the acceptability of TMDL plans. We developed a stakeholder allocation model (SAM) which uses multi-attribute utility theory to quantitatively structure the preferences of the major stakeholder groups. We then applied GIS to display allocation options in maps representing economic activity, community groups, and city agencies. This allows allocation options and stakeholder concerns to be represented in both space and time. The primary goal of this tool is to provide a quantitative and visual display of stakeholder concerns over possible TMDL options

Regional Seismic Discrimination Optimization With and Without Nuclear Test Data: Western U.S. Examples

The western U.S. has abundant natural seismicity, historic nuclear explosion data, and widespread mine blasts, making it a good testing ground to study the performance of regional source-type discrimination techniques. We have assembled and measured a large set of these events to systematically explore how to best optimize discrimination performance. Nuclear explosions can be discriminated from a background of earthquakes using regional phase (Pn, Pg, Sn, Lg) amplitude measures such as high frequency P/S ratios. The discrimination performance is improved if the amplitudes can be corrected for source size and path length effects. We show good results are achieved using earthquakes alone to calibrate for these effects with the MDAC technique (Walter and Taylor, 2001). We show significant further improvement is then possible by combining multiple MDAC amplitude ratios using an optimized weighting technique such as Linear Discriminant Analysis (LDA). However this requires data or models for both earthquakes and explosions. In many areas of the world regional distance nuclear explosion data is lacking, but mine blast data is available. Mine explosions are often designed to fracture and/or move rock, giving them different frequency and amplitude behavior than contained chemical shots, which seismically look like nuclear tests. Here we explore discrimination performance differences between explosion types, the possible disparity in the optimization parameters that would be chosen if only chemical explosions were available and the corresponding effect of that disparity on nuclear explosion discrimination. There are a variety of additional techniques in the literature also having the potential to improve regional high frequency P/S discrimination. We explore two of these here: three-component averaging and maximum phase amplitude measures. Typical discrimination studies use only the vertical component measures and for some historic regional nuclear records these are all that are available. However S-waves are often better recorded on the horizontal components and some studies have shown that using a three-component average or a vertical-P/horizontal-S or other three-component measure can improve discrimination over using the vertical alone (e.g. Kim et al. 1997; Bowers et al 2001). Here we compare the performance of vertical and three-component measures on the western U. S. test set. A complication in regional discrimination is the variation in P and S-wave propagation with region. The dominantly observed regional high frequency S-wave can vary with path between Sn and Lg in a spatially complex way. Since the relative lack of high frequency S-waves is the signature of an explosion, failing to account for this could lead to misidentifying an earthquake as an explosion. The regional P phases Pn and Pg vary similarly with path and also with distance, with Pg sometimes being a strong phase at near regional distances but not far regional. One way to try and handle these issues is to correct for all four regional phases but choose the phase with the maximum amplitude. A variation on this strategy is to always use Pn but choose the maximum S phase (e.g. Bottone et al. 2002). Here we compare the discrimination performance of several different (max P)/(max S) measures to vertical, three-component and multivariate measures. Our preliminary results show that multivariate measures perform much better than single ratios, though transportability of the LDA weights between regions is an issue. Also in our preliminary results, we do not find large discrimination performance improvements with three-component averages and maximum phase amplitude measures compared to using the vertical component alone