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Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Research Collection School Of Computing and Information Systems
Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …
What Is The Role Of Emotions In Educational Leaders’ Decision Making? Proposing An Organizing Framework, Yinying Wang
What Is The Role Of Emotions In Educational Leaders’ Decision Making? Proposing An Organizing Framework, Yinying Wang
Educational Policy Studies Faculty Publications
Purpose: Emotions have a pervasive, predictable, sometimes deleterious but other times instrumental effect on decision making. Yet the influence of emotions on educational leaders’ decision making has been largely underexplored. To optimize educational leaders’ decision making, this article builds on the prevailing data-driven decision-making approach, and proposes an organizing framework of educational leaders’ emotions in decision making by drawing on converging empirical evidence from multiple disciplines (e.g., administrative science, psychology, behavioral economics, cognitive neuroscience, and neuroeconomics) intersecting emotions, decision making, and organizational behavior. Proposed Framework: The proposed organizing framework of educational leaders’ emotions in decision making includes four core propositions: …
Using Research On Neuroeconomics Games In School Leaders’ Decision-Making Training, Yinying Wang
Using Research On Neuroeconomics Games In School Leaders’ Decision-Making Training, Yinying Wang
Educational Policy Studies Faculty Publications
This article demonstrates how to use three neuroeconomics games adapted from game theory— the Ultimatum Game, the Trust Game, and the Public Goods Game—in school leaders’ decisionmaking training. These three games have been commonly used in the emerging field of neuroeconomics—an interdisciplinary field intersecting behavioral economics, psychology, and cognitive neuroscience. For each game, I first outline how to play it in the training of school leaders’ decision making, followed by the constructs relevant to leaders’ decision making, including fairness, justice, inequity aversion, reciprocity, emotions, social identity, trust, distrust, and altruistic punishment. These games, with a lighthearted touch, serve as part …
Shipbuilding Supply Chain Framework And Digital Transformation: A Project Portfolios Risk Evaluation, Rafael Diaz, Katherine Smith, Rafael Landaeta, Antonio Padovano
Shipbuilding Supply Chain Framework And Digital Transformation: A Project Portfolios Risk Evaluation, Rafael Diaz, Katherine Smith, Rafael Landaeta, Antonio Padovano
VMASC Publications
Program portfolio managers in digital transformation programs have a need for knowledge that can guide decisions related to the alignment of program investments with the sustainability and strategic objectives of the organization. The purpose of this research is to illustrate the utility of a framework capable of clarifying the cost-benefit tradeoffs stemming from assessing digitalization program investment risks in the military shipbuilding sector. Our approach uses Artificial Neural Network to quantify benefits and risks per project while employing scenario analysis to quantify the effects of operational constraints. A Monte Carlo model is used to generate data samples that support the …
Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe
Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe
Engineering Management & Systems Engineering Faculty Publications
Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …