Restimate:Recovery Estimation Tool for Resilience Planning

The U.S.National Institute of Standards and Technology(NIST)published the Community Resilience Planning Guide in 2016.The NIST Guide advocates for a participatory process for developing a performance measurement framework for the jurisdiction’s resilience against a scenario hazard.The framework centers around tables of expected and desired recovery times for selected community assets,such as electricity,water,and natural gas infrastructures.The NIST Guide does not provide a method for estimating the expected recovery times.However,building high-fidelity computer models for such estimations requires substantial resources that even larger ju-risdictions cannot cost-justify.The most promising approach to recovery time estimation is to systematically use data elicited from people to tap into the wisdom of the(knowledgeable)crowd.This paper describes a novel research-through-design project to enable the computer-supported elicitation of recovery time series data.This work is the first in the literature to examine people’s ability to estimate recovery curves and how design in-fluences such estimations.Its main contribution to resilience planning is three-fold:development of a new elicitation tool called Restimate,understanding its potential user base,and providing insights into how it can facilitate resilience planning.Restimate is the first tool to enable evidence-based expert elicitation in any community with limited resources for resilience planning.Beyond resilience planning,those who facilitate high-stakes planning activities under large uncertainties(e.g.,mission-critical system design and planning)will benefit from a similar research-through-design process.

Understanding and Exploiting Information Spreading and Integrating Technologies

Our daily life leaves an increasing amount of digital traces,footprints that are improving our lives.Data-mining tools,like recommender systems,convert these traces to information for aiding decisions in an ever-increasing number of areas in our lives.The feedback loop from what we do,to the information this produces,to decisions what to do next,will likely be an increasingly important factor in human behavior on all levels from individuals to societies.In this essay,we review some effects of this feedback and discuss how to understand and exploit them beyond mapping them on more well-understood phenomena.We take examples from models of spreading phenomena in social media to argue that analogies can be deceptive,instead we need to fresh approaches to the new types of data,something we exemplify with promising applications in medicine.

Research and application of the virtual simulation system teaching method in NC machining course

Virtual simulation technology has become one of the most popular technologies in the field of engineering education after the multimedia information technology in recent years.This paper,based on the comprehensive integrated simulation and verification module of UG NX software,describes and discusses a novel virtual simulation system teaching(VSST)for numerically controlled machining to support the student engineering training to achieve the theoretical knowledge and practical techniques in numerically controlled machining.The findings of a study designed to evaluate the impact of VSST for the development of numerically controlled machining course are presented here.In addition,analysis of the follow-up surveys indicates that the VSST method enables to provide the concrete experience of interaction between the students and the simulation environment and to further stimulate students’interest in learning,so that the students who used VSST achieve significantly higher results than their co-workers.