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Dive into the research topics where Alisa Bandlow is active.

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Featured researches published by Alisa Bandlow.


Archive | 2017

The Impact of False and Nuisance Alarms on the Design Optimization of Physical Security Systems

Alisa Bandlow; Katherine A. Jones; Nathanael J. K. Brown; Linda K. Nozick

Despite the known degrading impact of high nuisance and false alarm rates (NAR/FAR) on operator performance, analyses of security systems often ignores operator performance. We developed a model to analyze the impact of nuisance alarm rates on operator performance and on overall system performance. The model demonstrates that current methods that do not account for operator performance produce optimistic estimates of system performance. As shown in our model, even low NAR/FAR levels and the associated alarm queueing effect can increase operator detect and response time, which in turn reduces the amount of time the response force has to interrupt the intruder. An illustrative analysis shows that alarm processing times can be higher than the assessment time due to queue wait times and that systems with only one or two operators can become overwhelmed as NAR increases, decreasing system performance.


international conference on human-computer interaction | 2011

Evaluating Information Visualizations with Working Memory Metrics

Alisa Bandlow; Laura E. Matzen; Kerstan Suzanne Cole; Courtney C. Dornburg; Charles J. Geiseler; John A. Greenfield; Laura A. McNamara; Susan Marie Stevens-Adams

Information visualization tools are being promoted to aid decision support. These tools assist in the analysis and comprehension of ambiguous and conflicting data sets. Formal evaluations are necessary to demonstrate the effectiveness of visualization tools, yet conducting these studies is difficult. Objective metrics that allow designers to compare the amount of work required for users to operate a particular interface are lacking. This in turn makes it difficult to compare workload across different interfaces, which is problematic for complicated information visualization and visual analytics packages. We believe that measures of working memory load can provide a more objective and consistent way of assessing visualizations and user interfaces across a range of applications. We present initial findings from a study using measures of working memory load to compare the usability of two graph representations.


hawaii international conference on system sciences | 2017

A Stochastic Programming Approach to the Design Optimization of Layered Physical Protection Systems

Nathanael J. K. Brown; Katherine A. Jones; Alisa Bandlow; Lucas Waddell; Linda K. Nozick

The performance of many of the technologies used in physical protection systems that guard highvalue assets are heavily influenced by weather and visibility conditions as well as intruder capabilities. This complicates the already difficult problem of optimizing the design of multi-layered physical protection systems. This paper develops an optimization model for the automatic design of these systems with explicit consideration of the impact of weather and visibility conditions as well as intruder capabilities on system performance. An illustrative case study is provided.


Archive | 2016

Contingency Contractor Optimization Phase 3 Sustainment Developer's Guide Contingency Contractor Optimization Tool - Prototype

Justin David Durfee; Christopher Rawls Frazier; Alisa Bandlow

This document provides background and instructions for developing and building the Contingency Contractor Optimization Tool - Prototype (CCOT-P) application.


Archive | 2016

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

Alisa Bandlow; Justin David Durfee; Christopher Rawls Frazier; Katherine A. Jones; Jared Lee Gearhart

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.


Archive | 2016

Contingency Contractor Optimization Phase 3 Sustainment Third-Party Software List - Contingency Contractor Optimization Tool - Prototype

Justin David Durfee; Christopher Rawls Frazier; Alisa Bandlow

The Contingency Contractor Optimization Tool - Prototype (CCOT-P) requires several third-party software packages. These are documented below for each of the CCOT-P elements: client, web server, database server, solver, web application and polling application.


Archive | 2013

Contingency contractor optimization.

Jared Lee Gearhart; Kristin Lynn Adair; Katherine A. Jones; Alisa Bandlow; Richard Joseph Detry; Justin David Durfee; Dean A. Jones; Nathaniel Martin; Alan Stewart Nanco; Linda K. Nozick

The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.


Archive | 2013

Varicella infection modeling.

Katherine A. Jones; Patrick D. Finley; Thomas W. Moore; Linda K. Nozick; Nathaniel Martin; Alisa Bandlow; Richard Joseph Detry; Leland B. Evans; Taylor Eugen Berger

Infectious diseases can spread rapidly through healthcare facilities, resulting in widespread illness among vulnerable patients. Computational models of disease spread are useful for evaluating mitigation strategies under different scenarios. This report describes two infectious disease models built for the US Department of Veteran Affairs (VA) motivated by a Varicella outbreak in a VA facility. The first model simulates disease spread within a notional contact network representing staff and patients. Several interventions, along with initial infection counts and intervention delay, were evaluated for effectiveness at preventing disease spread. The second model adds staff categories, location, scheduling, and variable contact rates to improve resolution. This model achieved more accurate infection counts and enabled a more rigorous evaluation of comparative effectiveness of interventions.


Archive | 2012

Contingency contractor optimization. Phase 2, model description and formulation.

Jared Lee Gearhart; Kristin Lynn Adair; Alisa Bandlow; Dean A. Jones; Katherine A. Jones; Nathaniel Martin; Nadine E. Miner; Alan Stewart Nanco; Linda K. Nozick

The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.


Archive | 2018

SNL Lesson Learned and Guidance for Data Repositories and Analytic Frameworks.

Alisa Bandlow; Katherine A. Jones; Vanessa N. Vargas

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Katherine A. Jones

Sandia National Laboratories

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Jared Lee Gearhart

Sandia National Laboratories

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Kristin Lynn Adair

Sandia National Laboratories

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Justin David Durfee

Sandia National Laboratories

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Dean A. Jones

Sandia National Laboratories

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Laura A. McNamara

Sandia National Laboratories

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Laura E. Matzen

Sandia National Laboratories

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