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machine learning shell

Created Jan 12, 2021 (14:51)

A construction based on generic machine learning models that can be used to fit various applications. Generic machine learning models are coding mechanism that allow for a machine to improve its behavior based on experience.

MAE Center

Created Jan 12, 2021 (14:51)

Engineering MAE Center is the Center for Creating a Multi-Hazard Approach to Engineering, at the University of Illinois at Urbana-Champaign. “The MAE Center started as one of three national earthquake engineering research centers established by the National Science Foundation and its partner institutions. Its current mission is to develop through research, and to disseminate through education and outreach, new integrated approaches necessary to minimize the consequences of future natural and human-made hazards. Integrated interdisciplinary research synthesizing damage across regions, estimating vulnerability across regional and national networks, and identifying different hazards forms the core research activities needed to develop a Multi-hazard Approach to Engineering and to support stakeholder and societal interests in risk assessment and mitigation. Core research is separated into the following five thrust areas: 1) Multi-hazard Analysis; 2) Consequence-based Risk Management Framework; 3) Engineering Engines; 4) Social and Economic Sciences; 5) Information Technology. The outcomes of the MAE Center research is of value to many stakeholders allowing for better informed decision- and policy-making. Stakeholders include state transportation departments, state emergency management agencies, utilities operators, insurance and reinsurance companies, managing agents, investment banks, lenders, industry organizations, and governments. In addition, many projects integrate research and education for both undergraduate and graduate students, advance curricula and outreach to pre-college students, and enhance public awareness.” (MAE Center 2019) [MAE Center. (2019). About MAE Center. Retrieved from: http://mae.cee.illinois.edu/about/about.html]

Magnitude Distribution

Created Jan 12, 2021 (14:51)

A Magnitude Frequency Distribution is a function that describes the rate (per year) of earthquakes across all magnitudes. An MFD can have an analytical form or, as in the case of OpenSHA implementations, be described by rates of earthquakes over descrete intervals. (Field et al. 2005; 1.1-1.3) [Field, E.H., T.H. Jordan, and C.A. Cornell (2005) Magnitude Frequency Distribution (MFD). v. Retrieved from http://www.opensha.org/glossary-magFreqDist]

Mainshock

Created Jan 12, 2021 (14:51)

“The mainshock is the largest earthquake in a sequence, sometimes preceded by one or more foreshocks, and almost always followed by many aftershocks.” (USGS Earthquake; web)

Mainshock-Aftershock Fragility

Created Jan 12, 2021 (14:51)

Refers to the conditional probability of attaining or exceeding a specified performance level, given the intensity measures of a mainshock and its aftershocks

Mainshock-Aftershock Parameterized Fragility Models

Created Jan 12, 2021 (14:51)

Referes to a parametric function for the mainshock-aftershock fragility

Mainshock Magnitude

Created Jan 12, 2021 (14:51)

“The magnitude is a number that characterizes the relative size of an earthquake. Magnitude is based on measurement of the maximum motion recorded by a seismograph. Several scales have been defined, but the most commonly used are (1) local magnitude (ML), commonly referred to as "Richter magnitude", (2) surface-wave magnitude (Ms), (3) body-wave magnitude (Mb), and (4) moment magnitude (Mw). Scales 1-3 have limited range and applicability and do not satisfactorily measure the size of the largest earthquakes. The moment magnitude (Mw) scale, based on the concept of seismic moment, is uniformly applicable to all sizes of earthquakes but is more difficult to compute than the other types. All magnitude scales should yield approximately the same value for any given earthquake.” (USGS Earthquake Glossary https://earthquake.usgs.gov/learn/glossary/?term=magnitude)

Market Economies

Created Jan 12, 2021 (14:51)

A market economy is an economic system in which most goods and services are produced and distributed following the price signals created by the forces of supply and demand.

Mathematical Optimization Models

Created Jan 12, 2021 (14:51)

Physics The use of joint optimization of program motion and an ensemble of perturbed motions allows engineers to break down the modelling process more than dynamical processing.Joint optimization opens the system up to its details and shows the was that the engineer can manipulate the models and equations. These mathematical models include description of controlled dynamical process, choice of control functions or parameters of optimization as well as construction of quality functionals, which allow efficient evaluation of various characteristics of examined control motions. This optimization problem is considered as the problem of mathematical control theory. The suggested approach allows to develop various methods of directed search and to conduct parallel optimization of program and perturbed motions. (Bondarev et al. 2006; 390) [Bondarev, B. I., Durkin, A. P., & Ovsvnnanikov, A. D. (2006, August 06). New mathematical optimization models for RFQ structures. Retrieved from: https://ieeexplore.ieee.org/abstract/document/792945/citations#citations ]

Metaheuristics

Created Jan 12, 2021 (14:51)

Engineering A metaheuristic is a set of concepts that can be used to define heuristic methods that can be applied to a wide set of different problems. In other words, a metaheuristic can be seen as a general algorithmic framework that can be applied to different optimization problems with relatively few modifications. Examples of metaheuristics include simulated annealing, tabu search, iterated local search, evolutionary algorithms, and ant colony optimization. [Dorigo M., Birattari M., Stützle T. (2017) Metaheuristic. In: Sammut C., Webb G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi-org.ezproxy.lib.ou.edu/10.1007/978-1-4899-7687-1_537]

Metamodels of Spatial Surge Intensity

Created Jan 12, 2021 (14:51)

Meterology Metamodels provide numerical models that facilitate accurate but also computationally intensive simulations of hurricane responses. Having the ability to manipulate variables spatially has allowed for better prediction and adaption for storms. (Gidaris et al. 2015) [Gidaris, I., Taflanidis, A. A., & Mavroeidis, G. P. (2015). Kriging metamodeling in seismic risk assessment based on stochastic ground motion models. Retrieved from https://onlinelibrary.wiley.com/doi/pdf/10.1002/eqe.2586]

Metric

Created Jan 12, 2021 (14:51)

A quantitative standard of measurement that quantifies resilience. (Lin et al. 2016) [Lin, P., Wang, N., & Ellingwood, B. R. (2016). A risk de-aggregation framework that relates community resilience goals to building performance objectives. Sustainable and Resilient Infrastructure, 1(1-2), 1-13.]

Migration

Created Jan 12, 2021 (14:51)

The movement or relocation of humans, frequently involving the crossing of borders, driven by a certain need or desire; migration can be either voluntary or forced. Disasters, both the threat and outcomes thereof, are one form of motivation for migration. [Tataru, G.F. (2019). Migration – an Overview on Terminology, Causes and Effects. Logos Universality Mentality Education Novelty: Law, 7(2), 10-29. doi:10.18662/lumenlaw/24]

Mitigation Based Recovery

Created Jan 12, 2021 (14:51)

Capabilities necessary to reduce loss of life and property by lessening the impact of disasters. Mitigation capabilities include, but are not limited to, community-wide risk reduction projects; efforts to improve the resilience of critical infrastructure and key resource lifelines; risk reduction for specific vulnerabilities from natural hazards or acts of terrorism; and initiatives to reduce future risks after a disaster has occurred. [Federal Emergency Management Agency (FEMA) Glossary https://www.fema.gov/about/glossary] Public-Safety Recovery activities are those necessary to restore services and systems to a state of normalcy. Recovery actions include damage assessment and those necessary to return health and safety systems (e.g., water) and services (e.g., acute health care) to minimum operating standards. Various recovery activities are likely to be long-term and may continue for many years. Hazard mitigation is the effort to reduce loss of life and property by lessening the impact of disasters. It is most effective when implemented under a comprehensive, long-term mitigation plan. State, tribal, and local governments engage in hazard mitigation planning to identify risks and vulnerabilities associated with natural disasters, and develop long-term strategies for protecting people and property from future hazard events. Mitigation plans are key to breaking the cycle of disaster damage, reconstruction, and repeated damage. (DPS/DHS 2019; web) [Department of Public Safety, Division of Emergency Management – Homeland Security (DPS/DHS). (2019). Recovery and Mitigation. Retrieved from: http://dem.nv.gov/About/RandM/]

Model Calibration

Created Jan 12, 2021 (14:51)

The process of adjusting model parameters to obtain an accurate representation of the process being modeled

Modeling Deterioration

Created Jan 12, 2021 (14:51)

Engineering;Infrastructure-Science "Deterioration models are used to predict failure probabilities in infrastructure due to the action of environmental agents, and usually for long periods of time." (Twort et al. 2000) [Twort, A. C., Ratnayaka, D. D., & Brandt, M. J. (2000). Water supply. Elsevier.]

Momentum Flux

Created Jan 12, 2021 (14:51)

Momentum flux is the transport of momentum that acts in a direction perpendicular to the direction of fluid flow. It is considered as the rate of change of horizontal momentum which is moving across a unit area, equal to force per unit area. It is also equivalent to a stress in that it is a force per unit area where the force is acting in a direction within the plane of the area. (Flow Simulation Ltd. 2018; web) [Flow Simulation Ltd. (2018). Property>Momentum Flux: What is Momentum Flux. Retrieved from: https://www.calculator.org/properties/momentum_flux.html]

Momentum Flux-Based Curves

Created Jan 12, 2021 (14:51)

Fragility curves wherein the dependent variable is the momentum flux

Monte Carlo Simulations

Created Jan 12, 2021 (14:51)

Structural Reliability. Monte Carlo simulations are used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. It is a technique used to understand the impact of risk and uncertainty in prediction and forecasting models. [Kenton, W. (2019). Monte Carlo Simulation. Retrieved from https://www.investopedia.com/terms/m/montecarlosimulation.asp ]

MOU

Created Jan 12, 2021 (14:51)

Emergency In the United States, "the Disaster-Specific Memorandum of Understanding (Disaster-Specific MOU) is an agreement to be used by Federal, Tribal, state, and local Agencies to assist and define the relationship between and among Agencies during disaster recovery efforts. This tool is intended to be your guide in preparing for and writing Disaster-Specific MOUs for coordinating EHP reviews during disaster recovery. You should prepare a Disaster-Specific MOU to increase communication, collaboration, and transparency among Agencies participating in disaster recovery." (FEMA 2019; 1) [Federal Emergency Management Agency (FEMA). (2019). Disaster-Specific Memorandum of Understanding. Retrieved from https://www.fema.gov/media-library-data/1416583062704-86cb8bebe23906b594ce14860d86f8af/Disaster-Specific_MOU_updated_weblinks.pdf. ]

Multi-Hazard Cases

Created Jan 12, 2021 (14:51)

A scenario in which multiple hazards are considered. Examples include, but are not limited to, flooding and precipitation from hurricanes, or ground shaking and tsunami inundation from earthquakes

multi-hazard damage

Created Jan 12, 2021 (14:51)

The damage caused by a "multiple hazards (flooding, wave attack, erosion, etc.)" events is "considered simultaneously." (Vah Verseveld et al. 2015; 1)

Multi-Hazard Fragility

Created Jan 12, 2021 (14:51)

Multi-hazard fragility functions are vector-valued fragility functions, which provide the probability of exceeding a damage state as a function of the two or more hazard intensity measures. For example, a multi-hazard earthquake-tsunami fragility function provides the probability of exceeding a damage state based on a combination of {ground shaking, tsunami} intensity measures, such as {peak ground acceleration, inudation depth}.

Multi-Hazard Risk and Resilience Assessment

Created Jan 12, 2021 (14:51)

Civil Engineering "Multiple hazards and cascading hazards affect exposed infrastructure assets. Examples of these hazards include flood series over time, flood-earthquake, earthquake-induced tsunami, landslides and liquefaction, rainfall-induced landslides, or earthquake-aftershock events. Risk analysis in the multi-hazard context refers to assessing the consequences of such hazard scenarios combined with the occurrence probability of each consequence. Resilience describes the emergent property or attributes that infrastructure systems have, which allows them to withstand, respond and/or adapt to a vast range of disruptive events, by maintaining and/or enhancing their functionality." [Adapted from Argyroudis, Sotirios A., et al. "Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets." Science of The Total Environment 714 (2020): 136854.]

Multi-Hazard Risk Formulations

Created Jan 12, 2021 (14:51)

An approach to account for the different probability of occurrence and intensity from similar or various hazards.

Multi-Metric Decision Making Framework

Created Jan 12, 2021 (14:51)

Suggest changing to “Multi-Criteria Decision-Making Framework”; “Multi-Metric Decision Making Framework” does not appear in any search results. A framework detailing a structured decision-making methodology for determining the most ideal option in situations with multiple and conflicting criteria, each of which may be valued differently by different decision-makers; such frameworks may involve expert-informed value judgments to address the subjectivity of decision-making [Nappi et al. 2019]. General steps in this decision-making framework include: 1) identifying the problem, 2) structuring the problem, 3) estimating performance of alternatives with respect to each criterion, 4) eliciting stakeholders’ and/or decision-makers’ values, 5) synthesizing results using mathematical models, and 5) analyzing the sensitivity of the results to changes in model parameters to assess the robustness of the analysis [Saarikoski et al. 2016]. An example of multiple and conflicting criteria might include minimizing initial cost to enhance structural performance while simultaneously maximizing performance of a structure, given that the solution that maximizes performance is typically not the cheapest. [Nappi, M.M.L., Nappi, V. & Souza, J.C. (2019). Multi-criteria decision model for the selection and location of temporary shelters in disaster management. Int J Humanitarian Action 4, 16 doi: 10.1186/s41018-019-0061-z Saarikoski, H., Mustajoki, J., Barton, D. N., Geneletti, D., Langemeyer, J., Gomez-Baggethun, E., Marittunen, M., Antunes, P., Keune, H., and Santos, R. (2016). Multi-Criteria Decision Analysis and Cost-Benefit Analysis: Comparing alternative frameworks for integrated valuation of ecosystem services. Ecosystem Services, 22(B), 238-249.]

Multiple Commodities

Created Jan 12, 2021 (14:51)

Commodities are physical goods traded in a manner similar to stocks. They include metals such as gold and silver, and agricultural products such as coffee and sugar, oil and gas. Sometimes commodities are more generally used to mean anything produced for sale.

Multiple Network Performance Metrics

Created Jan 12, 2021 (14:51)

Network Science "Network performance refers to measures of service quality of a network as seen by the operator or customer. There are many different ways to measure the performance of a network, as each network is different in nature and design. Examples of the metrics are water quality, power interruption durations, network connectivity loss, call blocking probabilities, road travel time, etc. Performance can also be modeled and simulated instead of measured; one example of this is using state transition diagrams to model queuing performance, physics-based flow models, or using a Network Simulator." [Ghosn, M., Dueñas-Osorio, L., Frangopol, D. M., McAllister, T. P., Bocchini, P., Manuel, L., ... & Akiyama, M. (2016). Performance indicators for structural systems and infrastructure networks. Journal of Structural Engineering, 142(9), F4016003.]