Uncertainty quantification - PowerPoint PPT Presentation

FragPipe offers a comprehensive solution for DDA and DIA bottom-up proteomics analysis, supporting various advanced functionalities such as closed and open searches, FDR estimation, PTM discovery, and label-free quantification. It simplifies deep-learning-based rescoring and provides an easy-to-use

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Predicate logic is a powerful tool used in mathematics to express complex relationships and assertions that cannot be adequately represented by propositional logic. It allows for the quantification of statements over a range of elements using predicates and quantifiers like universal and existential

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Measurement uncertainty in testing is a crucial aspect that characterizes the dispersion of values attributed to a measurand. This uncertainty plays a key role in reporting accurate test results, requiring careful evaluation of all significant contributions. The ISO/IEC Guide 98 GUM provides essenti

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Explore the Grid Project Impact Quantification Tool (GridPIQ) for assessing impacts of grid projects, visualizing time series, comparing assumptions, and more. Quickly input data and analyze scenarios for energy storage, PV, emissions, and peak power impacts using this intuitive online tool.

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Explore the tension between creativity and efficiency in innovation through Pearsons' Uncertainty Map (1991), which categorizes uncertainty about ends and means. The map helps analyze uncertainty in various innovation processes, from exploratory research to improving existing products, offering insi

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This study by A.A. Sonzogni and E.A. McCutchan focuses on developing cumulative fission yield covariances for uncertainty quantification in nuclear reactors. The research involves calculating cumulative fission yields, using decay data and nuclear databases, to improve accuracy in predicting fission

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Irina Tezaur leads the Quantitative Modeling & Analysis Department, focusing on computational modeling and simulation of complex multi-scale, multi-physics problems. Her work benefits DOE nuclear weapons, national security, and climate missions. By employing innovative techniques like model order re

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Reviewing the O2 CO2 calibration uncertainty, recent updates include identifying beam clipping on the reflection photodiode, switching to the transmitted photodiode, correcting time-dependent errors, and reducing overall uncertainty budget to primarily statistical uncertainty. Data and scripts used

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This study explores the influences of supplier market competition, volume uncertainty, technological uncertainty, and production costs on make-or-buy decisions. Transaction cost economics theory highlights the impact of uncertainty and asset specificity on such decisions, with a focus on buyer-suppl

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Explore the sources of economic, social, and political uncertainty at regional and global levels. Discuss the rising tide of uncontrollable uncertainty and its implications for public policy and communities. Delve into economic globalization, social fragmentation, and the challenges posed by a world

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UV-Vis spectroscopy involves the absorption of electromagnetic radiation by molecules, causing electronic transitions. Different chromophores and conjugated systems determine the wavelength absorbed, with the Beer-Lambert Law essential for quantification. Specific compounds like caffeine showcase un

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General Practitioners (GPs) encounter uncertainty in their practice and utilize various strategies to address it. These strategies include safety netting, seeking advice from colleagues, sharing uncertainty with patients, review/follow-up processes, investigations, building rapport, and more. Collea

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Sampling uncertainty arises due to variations in sample values, impacting statistical estimates. Larger samples reduce uncertainty, providing more precise estimates. Adequate sample sizes are crucial, especially for comparing different groups or magnitudes of effects. By quantifying uncertainty, res

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Uncertainty Quantification (UQ) is crucial in determining likely outcomes in scenarios with unknown factors. Explore the concept through the Algae Example, where parameters like growth rates pose challenges due to uncertainty. Statistical techniques like MCMC and the DRAM algorithm play key roles in

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Analysis by Elena Zaitseva on the quantification of uncertainty in the behavior of multi-state systems, including binary-state and multiple-state systems. Discusses the principal problem in reliability engineering, the quantification of system models, and the structure function defining system perfo

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This presentation explores the intricate relationship between confidence, uncertainty, and risk in decision-making processes within engineering design studies. It highlights the importance of considering various perspectives and evaluating potential risks and benefits to make informed decisions. The

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This project focuses on assessing and quantifying uncertainty in High Frequency (HF) radar measurements, with key areas including sensitivity analysis and data record discussions. The team, comprised of experts from IBM, Rutgers, and ODU, aims to provide real-time ocean circulation forecasts for mar

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The presentation discusses the longstanding issue of uncertainty estimation in hydrology and the importance of incorporating physical knowledge in stochastic modeling of uncertain systems. It highlights the role of expert judgment and how uncertainty will always be present in hydrological assessment

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Efforts to enhance the nuclear data pipeline focus on providing high-quality nuclear physics parameters for simulation community, incorporating uncertainty studies, theory evaluations, and software improvements. Recent endeavors include evaluation of 239Pu, uncertainty quantification, processing and

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Concept of uncertainty in health measurements is crucial for ensuring accuracy in diagnostic processes. This involves factors such as within-run precision, between-run precision, calibrator coverage, mean calculations, standard deviation, and expanded uncertainty. Proper calibration, repeated testin

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The paper explores the concept of uncertainty in the financial sector, proposing a novel measure using expectation errors of managers. It discusses the impact of uncertainty on economic activity, drawing from relevant literature and financial services survey data. The study aims to address the lack

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In Chapters 13 and 14 of Artificial Intelligence, explore how agents handle uncertainty with degrees of belief and probabilistic reasoning. Discover the use of probability theory in building network models to reason under uncertainty. Delve into topics like conditional probabilities, Bayesian networ

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This content delves into the interlinkages between uncertainty and investments at a micro-economic level, focusing on the impact of global economic policy uncertainty on investment flows. It highlights the relationship between uncertainty and investments in both advanced and emerging economies, disc

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This content provides insights into experimental considerations for library construction, focusing on input material quantification, quality control methods, and considerations for DNA, RNA, and ChIP-Seq library preparation. It covers topics such as methods for DNA and RNA quantification, optimal in

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Delve into the complexities of quantification in logic with David Gries, a Professor Emeritus in Computer Science at Cornell University. Explore the nuances of quantification, discussing notation, evaluation, and permissible operators. Gain insights into foundational axioms and theorems as you devel

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In this tutorial webinar, hosted by Brendan MacLean, delve into DDA to Targeted statistics using Skyline. Explore chromatography-based quantification, hypothesis testing, and group comparisons in mass spectrometry data analysis. Uncover insights from a case study, learn about sample preparation, and

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This work explores the application of Artificial Neural Networks (ANNs) in surrogate modeling for fission cross sections and criticality studies within the nuclear domain. Leveraging past simulations and data-driven ML techniques, the goal is to reduce the costs of uncertainty quantification, identi

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Grid Project Impacts Quantification Web Calculator, presented by Pacific Northwest National Laboratory, offers a user-friendly tool to ask 'what if?' questions, compare scenarios, and assess the impacts of grid projects. With intuitive functionalities, users can explore assumptions, visualize time s

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Explore the concept of Nonlinear Static Analysis (NSA) and the computational workflow. Understand uncertainty in structures' nonlinear behavior, including ductility, energy dissipation, and system overstrength. Visualize pushover curves and the setup of nonlinear models for building analysis.

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This study focuses on evaluating the impact of complex measurement uncertainty on the volume of methane discharged through a ventilation shaft in the hard coal mining industry. The research covers the methodology for measuring air flow rate and methane concentration, determination of complex measure

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Explore the fundamentals of probability and uncertainty in the context of artificial intelligence, covering topics such as acting under uncertainty, probability models, belief states, uncertain beliefs, dental diagnosis, reasoning under uncertainty, and probability basics.

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Explore cutting-edge techniques in Uncertainty Quantification (UQ) and Analytical Modeling (AM) for quantitative assessment of uncertainties, generation of response surfaces, leveraging PSUADE and Dakota toolkits, MARS algorithm, and resource allocation choices in a global computing environment.

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Discover the challenges and strategies for effectively communicating uncertainty in scientific products within teams. Join the Uncertainty Working Group as they share their achievements, plans, and the burning question every CMS science team member wants to address. Explore the sources of uncertaint

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Explore the transaction cost approach in make-or-buy decisions, analyzing factors like supplier market competition, volume uncertainty, technological uncertainty, and comparative production costs. Understand the impact of uncertainty and asset specificity on decision-making processes, emphasizing th

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This slideshow by Will Hopkins from Victoria University delves into the complexities of sampling uncertainty, covering topics such as sampling variation, standard error, confidence intervals, and magnitude-based inference. Understand the nuances of statistical significance and non-significance in a

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Utilizing data from precision and bias experiments in wine analysis to understand and quantify measurement uncertainty, focusing on factors influencing test results, sources of uncertainty, and calculation of combined uncertainty. The process involves a general approach to specify the measurand, ide

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This content discusses the measurement uncertainty in wine analysis, focusing on the general approach, single within-laboratory validation, precision data, and levels of uncertainty. It covers sources of uncertainty, quantification methods, and the importance of reproducibility in obtaining accurate

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Explore the genetic characteristics of newly sequenced desert Ensifer strains through gel electrophoresis, copy number quantification, and pairwise genome comparisons. Discover core and accessory genome proportions, sizes, and GC percentages in different Ensifer species.

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Dive into the fundamentals of risk quantification in software engineering project management, covering uncertainty, probabilities, statistics, and distributions to enhance decision-making and project outcomes.

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Explore the theory of uncertainty assessment in hydrological modelling from the XXXII Italian Conference of Hydraulics and Hydraulic Construction. This presentation by Alberto Montanari discusses the historical awareness of uncertainty in hydraulic engineering, the use of expert judgment for uncerta

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