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A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. Meta-analytic results are considered the most trustworthy source of evidence by the evidence-based medicine literature.
A startup or start-up is a company or project undertaken by an entrepreneur to seek, develop, and validate a scalable business model. While entrepreneurship includes all new businesses, including self-employment and businesses that do not intend to go public, startups are new businesses that intend to grow large beyond the solo founder. At the beginning, startups face high uncertainty and have high rates of failure, but a minority of them do go on to be successful and influential.
A dive computer, personal decompression computer or decompression meter is a device used by an underwater diver to measure the elapsed time and depth during a dive and use this data to calculate and display an ascent profile which, according to the programmed decompression algorithm, will give a low risk of decompression sickness.
Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-validation is a resampling method that uses different portions of the data to test and train a model on different iterations. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice. In a prediction problem, a model is usually given a dataset of known data on which training is run, and a dataset of unknown data against which the model is tested. The goal of cross-validation is to test the model's ability to predict new data that was not used in estimating it, in order to flag problems like overfitting or selection bias and to give an insight on how the model will generalize to an independent dataset.
Quantitative structure–activity relationship models are regression or classification models used in the chemical and biological sciences and engineering. Like other regression models, QSAR regression models relate a set of "predictor" variables (X) to the potency of the response variable (Y), while classification QSAR models relate the predictor variables to a categorical value of the response variable.
An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, ABMs are also called individual-based models (IBMs). A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.
Computational science, also known as scientific computing, technical computing or scientific computation (SC), is an area of science that uses advanced computing capabilities to understand and solve complex physical problems. This includes
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided into multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets.
Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place.
Safety culture is the collection of the beliefs, perceptions and values that employees share in relation to risks within an organization, such as a workplace or community. Safety culture is a part of organizational culture, and has been described in a variety of ways; notably the National Academies of Science and the Association of Land Grant and Public Universities have published summaries on this topic in 2014 and 2016.
Metaxalone, sold under the brand name Skelaxin, is a muscle relaxant medication used to relax muscles and relieve pain caused by strains, sprains, and other musculoskeletal conditions. Its exact mechanism of action is not known, but it may be due to general central nervous system depression. It is a moderately strong muscle relaxant, with relatively low incidence of side effects.
The Monthly Weather Review is a peer-reviewed scientific journal published by the American Meteorological Society. It covers research related to analysis and prediction of observed and modeled circulations of the atmosphere, including technique development, data assimilation, model validation, and relevant case studies. This includes papers on numerical techniques and data assimilation techniques that apply to the atmosphere and/or ocean environment. The editor-in-chief is David M. Schultz.
The Minerals, Metals & Materials Society (TMS) is a professional organization for materials scientists and engineers that encompasses the entire range of materials and engineering, from minerals processing and primary metals production to basic research and the advanced applications of materials.
Risk magazine provides news and analysis covering the financial industry, with a particular focus on risk management, derivatives and complex finance. It includes articles and papers on credit risk, market risk, risk systems, swap option pricing, derivatives risk and pricing, regulation and asset management. Articles include news, features, comment, analysis and mathematical papers. Risk has a tradition of covers featuring pieces of abstract modern art.
An ecosystem model is an abstract, usually mathematical, representation of an ecological system, which is studied to better understand the real system.
Drug Discovery Today is a monthly peer-reviewed scientific journal that is published by Elsevier. It was established in 1996 and publishes reviews on all aspects of preclinical drug discovery from target identification and validation through hit identification, lead identification and optimisation, to candidate selection.
Verification and validation are independent procedures that are used together for checking that a product, service, or system meets requirements and specifications and that it fulfills its intended purpose. These are critical components of a quality management system such as ISO 9000. The words "verification" and "validation" are sometimes preceded with "independent", indicating that the verification and validation is to be performed by a disinterested third party. "Integration verification and validation" can be abbreviated as "IV&V".
Quantification of Margins and Uncertainty (QMU) is a decision support methodology for complex technical decisions. QMU focuses on the identification, characterization, and analysis of performance thresholds and their associated margins for engineering systems that are evaluated under conditions of uncertainty, particularly when portions of those results are generated using computational modeling and simulation. QMU has traditionally been applied to complex systems where comprehensive experimental test data is not readily available and cannot be easily generated for either end-to-end system execution or for specific subsystems of interest. Examples of systems where QMU has been applied include nuclear weapons performance, qualification, and stockpile assessment. QMU focuses on characterizing in detail the various sources of uncertainty that exist in a model, thus allowing the uncertainty in the system response output variables to be well quantified. These sources are frequently described in terms of probability distributions to account for the stochastic nature of complex engineering systems. The characterization of uncertainty supports comparisons of design margins for key system performance metrics to the uncertainty associated with their calculation by the model. QMU supports risk-informed decision-making processes where computational simulation results provide one of several inputs to the decision-making authority. There is currently no standardized methodology across the simulation community for conducting QMU; the term is applied to a variety of different modeling and simulation techniques that focus on rigorously quantifying model uncertainty in order to support comparison to design margins.
The Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability is a quarterly peer-reviewed academic journal that covers risk analysis and reliability engineering, including engineering, mathematical modelling and statistical analysis. The journal was established in 2006 and is published by SAGE Publications on behalf of the Institution of Mechanical Engineers. According to the Journal Citation Reports, its 2013 impact factor is 0.775.
Technology readiness levels (TRLs) are a method for estimating the maturity of technologies during the acquisition phase of a program. TRLs enable consistent and uniform discussions of technical maturity across different types of technology. TRL is determined during a technology readiness assessment (TRA) that examines program concepts, technology requirements, and demonstrated technology capabilities. TRLs are based on a scale from 1 to 9 with 9 being the most mature technology.
References
- ↑ "The Journal of Risk Model Validation". 2015 Journal Citation Reports . Web of Science (Social Sciences ed.). Thomson Reuters. 2016.