Informs Annual Meeting 2017

MD61

INFORMS Houston – 2017

3 - Assessing Engineering Students’ Intercultural Competence Sadan Kulturel-Konak, Penn State Berks, Tulpehocken Road, P.O Box 7009, Reading, PA, 19610, United States, sadan@psu.edu Students must now be globally aware in order to remain competitive in today’s globalized society. In order to effectively assess engineering students’ intercultural competence development and engagement throughout their education, an instrument was developed. In this study we focus on students’ responses to knowledge-based questions regarding different global content/issues. Our findings using the proposed assessment framework will be presented, and factors affecting engineering students’ intercultural competence will be analyzed. 370B Topics for PhD Students Sponsored: Minority Issues Sponsored Session Chair: Maria Esther Mayorga, North Carolina State University, Raleigh, NC, 27695, United States, memayorg@ncsu.edu 1 - Topics for PhD Students In this session, a group of panelists will discuss topics of interest to PhD students. The list of topics include: finding your research topic, mentoring, choosing a career path, preparing for the job market, and tips for success. Panelists range from new graduates to full professors, and are from business and engineering schools as well as industry. The amount of time spent on each topic will depend on questions from the audience. 2 - Panelist Gabriel Zayas-Caban, University of Michigan, 1731 Broadview Lane, Ann Arbor, MI, 48105, United States, gzayasca@umich.edu 3 - Panelist Shannon Harris, The Ohio State University, 1005 W. 5th Avenue, Unit 535, Columbus, OH, 43212-3085, United States, harris.2572@osu.edu 4 - Panelist Mark E. Lewis, Cornell University, School of Ops Research & Information Engin., 221 Rhodes Hall, Ithaca, NY, 14853, United States, mark.lewis@cornell.edu 5 - Panelist William Christian, US.Dept of Defense, Washington, DC, United States, wchristia@gmail.com Maria Esther Mayorga, North Carolina State University, 400 Daniels Hall, Dept. of Industrial & Systems Engineering, Raleigh, NC, 27695, United States, memayorg@ncsu.edu 370C IISE-Transaction Session Sponsored: Quality, Statistics and Reliability Sponsored Session Chair: Jianjun Shi, Georgia Institute of Technology, Atlanta, GA, 30332-0205, United States, jianjun.shi@isye.gatech.edu 1 - A Multi-response Multilevel Model with Application in Nurse Care Coordination Bing Si, Arizona State University, Tempe, AZ, 85287, United States, bingsi@asu.edu, Jing Li The recently developed Nurse Care Coordination Instrument (NCCI) enables data to be collected for measuring nurse care coordination, which plays a vital role in promoting patients’ safety and quality outcomes by a recent report by the Institute of Medicine. Driven by this, we propose a novel multi-response multilevel model with joint fixed/random effect selection across multiple responses and apply it to a dataset collected across four U.S. hospitals using the NCCI. Our study conducts the first quantitative analysis that links multiple care coordination metrics with multilevel predictors, and thus providing important insight into how care coordination might be impacted or improved. 2 - Identifying Multistage Nanocrystal Growth using in Situ TEM Video Data Yanjun Qian, Texas A&M.University, 1501 Harvey Rd, Apt 806, College Station, TX, 77840, United States, qianyanjun09@gmail.com, Jianhua Z Huang, Yu Ding The in situ transmission electron microscopy (TEM) technique is receiving considerable attention as it provides the capability of directly observing nanocrystal growth processes. As more and more TEM video data become MD61 MD62

available, one of the bottlenecks appears to be the lack of automated and dynamic processing tools. We introduce a method that analyzes the in situ TEM videos in an automated and effective way, which tracks the normalized particle size distribution and identifies the change points delineating the stages in nanocrystal growth. Using the outcome of the change-point detection, we propose a hybrid multi-stage growth model and test it on an in situ TEM video published in 2009 by Science. 3 - Scalable Prognostic Models for Large-scale Condition Monitoring Applications Xiaolei Fang, Georgia Institute of Technology, 1546 Woodlake Dr NE, Apt F, Atlanta, GA, 30329, United States, xfang33@gatech.edu, Nagi Gebraeel, Kamran Paynabar Capturing degradation of high-value engineering assets usually entails the use of various types of sensors, which generate massive amounts of data. Building a prognostic model for such large-scale datasets often presents two key challenges: how to effectively fuse the signals from a large number of sensors and how to make the model scalable to the large data size. To address the challenges, we present a scalable model designed for fusing multistream signals using two fusion algorithms developed from functional PCA. Using the algorithms, we identify fused features and predict the RUL via an adaptive (log)-location-scale regression framework. We validate our model using numerical and case studies. 370D Energy and Climate 11 Invited: Energy and Climate Invited Session Chair: Ross Baldick, University of Texas at Austin, Austin, TX, 78712, United States, baldick@ece.utexas.edu Co-Chair: Vaidyanathan Krishnamurthy, University of Texas-Austin, vaidyanathan@utexas.edu Co-Chair: Sambuddha Chakrabarti, University of Texas-Austin, sambuddha.chakrabarti@gmail.com 1 - Contingency Analysis During Extreme Events for Electric Power Systems Sambuddha Chakrabarti, University of Texas-Austin, Austin, TX, United States, sambuddha.chakrabarti@gmail.com, Vaidyanathan Krishnamurthy Extreme events such as natural disasters and weapon of mass destruction attacks have a major impact on electric power resiliency. This talks discusses contingency analysis for the electric transmission grid considering the physical impact of extreme events on electric power infrastructure. 2 - The University of Texas at Austin - A Microgrid in Practice Rossen Tzartzev, UT.Austin Utilities and Energy Management, Austin, TX, United States, tzartzev@gmail.com The University of Texas at Austin has selected the microgrid approach to serving all of the campus energy needs - power, cooling, and thermal. The talk will explore the benefits, opportunities, and challenges presented by these interconnected energy systems, as well as their effect on the overall system resiliency. 3 - Enhancing Grid Resiliency Robert Hebner, University of Texas-Austin, Austin, TX, United States, r.hebner@cem.utexas.edu : Achieving the level of resilience needed in the future electricity grid requires hardening against aging infrastructure, malicious attacks, and disasters. Developing a more robust system requires modeling of the physics of failure, robust controls, and a grid that can quickly disaggregate. These are necessary, but not sufficient. There is also a need to understand the interconnection of disparate systems such as transportation, telecommunications, and power. 4 - Contingency Constrained Day-ahead Scheduling of Large-scale Power Systems Ramtin Madani, Assistant Professor, The University of Texas at Arlington, Arlington, TX, United States, ramtin.madani@uta.edu, Edward Quarm A computational method will be introduced for solving power system scheduling problems under load and generation uncertainty as well as contingency constraints. A polynomial-time solvable model is created, whose scalability is beyond the reach of standard branch and bound methods. It either fully determines the globally optimal decision or, in the worst case, offers a vastly simplified input to standard solvers. MD63

258