Using a statistical approach, this research delves into the pore-scale modeling of intermittency and Ostwald ripening in two-phase flows. The study challenges the traditional linear relationship between pressure gradient and capillary number, highlighting the impact of fluid intermittency on flow be

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The U.S. Army Modeling and Simulation Office (AMSO) serves as the lead activity in developing strategy and policy for the Army Modeling and Simulation Enterprise. It focuses on effective governance, resource management, coordination across various community areas, and training the Army Analysis, Mod

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This presentation unveils the Capacity Zone modeling calculations for Forward Capacity Auction 17 associated with the 2026-2027 Capacity Commitment Period by ISO-NE PUBLIC. It delves into boundary definitions, import-constrained zone modeling, and market rules guiding the assessments and modeling pr

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This document delves into the modeling, optimization, and simulation of power distribution systems, specifically focusing on Distribution Feeder Modeling and Analysis. It covers the components of a typical distribution feeder, series components, Wye-Connected Voltage Regulator modeling, and equation

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Data modeling involves exploring data-oriented structures, identifying entity types, and assigning attributes similar to class modeling in object-oriented development. Object models should not be solely based on existing data schemas due to impedance mismatches between object and relational paradigm

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Workshop on joint efforts between IEEE 802 and ITU-T Study Group 15 focused on information modeling, data modeling, and system control in the realm of transport systems and equipment. The mandate covers technology architecture, function management, and modeling methodologies like UML to YANG generat

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Geometric modeling in computer-aided design (CAD) is crucially done in three key ways: wireframe modeling, surface modeling, and solid modeling. Wireframe modeling represents objects by their edges, whereas surface modeling uses surfaces, vertices, and edges to construct components like a box. Each

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Mathematical modeling plays a crucial role in solving engineering problems efficiently. Numerical methods are powerful tools essential for problem-solving and learning. This chapter explores the importance of studying numerical methods, the concept of mathematical modeling, and the evaluation proces

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Exploring the concept of degrees of freedom in statistical modeling, this presentation discusses the importance of having adequate degrees of freedom for model fitting and interpretation. It compares different models with varying degrees of freedom, illustrating how a null model with zero parameters

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Variability is key in statistical studies, shaping the essence of statistical analysis. Students often struggle to grasp the concept of variability, despite being taught statistical methods. The term "variation" takes on different meanings in various statistical contexts, presenting challenges in co

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This material introduces the fundamental concepts of data collection and statistics. Learning objectives include distinguishing statistical questions, identifying populations and samples, and understanding the difference between observational studies and experiments. It discusses the process of stat

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Dynamic Structural Equation Modeling (DSEM) is a powerful analytical tool used to analyze intensive longitudinal data, combining multilevel modeling, time series modeling, structural equation modeling, and time-varying effects modeling. By modeling correlations and changes over time at both individu

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Dive into the world of statistical learning with a focus on the impact of wise queries. Discover how statistical problems are approached, the significance of statistical queries, and the comparisons between wise and unary queries. Explore the implications for PAC learning and uncover key insights in

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IBM SPSS, formerly known as Statistical Package for the Social Sciences, is a powerful software package for statistical analysis used by researchers across various industries. Developed in the late 1960s, SPSS offers features for data management, statistical analysis, and data documentation. It simp

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Object modeling is a crucial concept in software development, capturing the static structure of a system by depicting objects, their relationships, attributes, and operations. This modeling method aids in demonstrating systems to stakeholders and promotes a deeper understanding of real-world entitie

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The Myanmar Statistical System operates as a decentralized system with the Central Statistical Organization playing a crucial role at the national level. Various surveys and data collection efforts are undertaken by different ministries and agencies, coordinated by the CSO. The CSO compiles and pres

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The Trust Fund for Statistical Capacity Building (TFSCB) is a multi-donor trust fund launched in 1999, supporting over 200 projects worldwide to strengthen statistical systems in developing countries. It focuses on national strategy development and improving statistical capacity in key priority area

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Coupled ocean-atmosphere modeling on horizontally icosahedral and vertically hybrid-isentropic/isopycnic grids is a cutting-edge approach to modeling climate variability. The design goals aim to achieve a global domain with no grid mismatch at the ocean-atmosphere interface, with key indicators such

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FASMEE is a collaborative project aimed at assessing and advancing fire and smoke modeling systems through critical measurement techniques and observational data. Led by key technical leads, FASMEE focuses on diverse modeling areas such as fire growth, effects, coupled fire-atmosphere behavior, smok

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In the realm of statistical development, the National Institute of Statistics in Tunisia embarked on a transformative journey towards a fully SDMX compliant information system. Initiatives included capacity building, data migration, and the adoption of a new dissemination platform. Steps such as SDM

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In this lesson, we delve into subarea and corridor studies focusing on travel demand model refinements, highway network coding, corridor congestion relief, and trip assignment theory. Subarea modeling plays a crucial role in forecasting travel within smaller regions with detailed traffic patterns, t

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Explore the fundamentals of study design & research methodology, learn to select appropriate statistical tests, and practice statistical analysis using JMP Pro Software. Topics include research question formulation, statistical methods, regression, survival analysis, data visualization, and more. Un

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Ensure clarity on modeling goals and uncertainties. Select sample areas strategically based on interest and available data. Determine appropriate resolution for modeling. Define variables to model and validate the model effectively. Assess sample data adequacy and predictor variables availability. E

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This presentation by Justine Carroll, P.E., Project Manager, focuses on the hydraulic modeling and water quality considerations related to water storage tanks. It covers topics such as water age evaluation, steady state modeling, extended period simulations, pump controls, demand patterns, EPS verif

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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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A new flexible framework for forward and inverse modeling of stormwater lids is presented. It includes governing equations, hydraulic and contaminant transport, numerical methods, and demonstration cases for various green infrastructure components. The importance of different processes in modeling i

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This presentation discusses the importance of enhancing statistical capacities in OIC member countries to achieve Sustainable Development Goals (SDGs), with a focus on the role of SESRIC. It covers the evolution of statistical definitions, the use of Statistical Capacity Index (SCI) for analysis, an

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The post-2015 development agenda emphasizes the need for a comprehensive global policy agenda, impacting statistical systems worldwide. This agenda seeks to improve data collection, coordinate international statistical efforts, and enhance national statistical systems by 2020 to support the Sustaina

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Estimation methods play a crucial role in statistical modeling. Maximum Likelihood Estimation (MLE) is a powerful technique invented by Fisher in 1922 for estimating unknown model parameters. This session explores how MLE works, its applications in different scenarios like genetic analysis, and prac

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Statistical methods guide on using RooFit within the ROOT framework for data analysis and modeling. Learn about RooRealVar definitions, Gaussian PDF building, and plotting techniques in various dimensions.

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Explore the world of Automated Speech Recognition (ASR), including setup, basics, observations, preprocessing, language modeling, acoustic modeling, and Hidden Markov Models. Learn about the process of converting speech signals into transcriptions, the importance of language modeling in ASR accuracy

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The role of statistical standards in constructing national data backbones is crucial for efficient data dissemination and reporting, especially in the context of Sustainable Development Goals (SDGs). Statistical standards guide the orchestration of information flows within a national statistical net

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Several significant statistical events took place in the San Diego area between 2001 and 2003, featuring renowned speakers and experts in the field. These events covered topics such as meta-analysis, global atmospheric changes, statistical trends, and annual statistical career days. The gatherings p

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The U.S. Federal Statistical System comprises 13 principal statistical agencies responsible for collecting and analyzing data across various sectors. The system includes agencies like the Bureau of Economic Analysis, Bureau of Labor Statistics, and U.S. Census Bureau. Geographic identifiers (GEOIDs

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Statistical modeling is used to determine excess risks associated with different food items in cases of food poisoning. By calculating attack rates and risks, it is possible to identify which food items may be contributing to the illness. The approach is explained through examples and comparisons, h

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Knowledge-based approaches are crucial in genetic data analysis to enhance the accuracy and scope of genome-wide association studies (GWAS). Stochastic Relational AI (Star-AI) offers a solution by leveraging probability theory and First Order Logic to capture complex genetic interactions. By integra

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Weekly coordination calls with Ramboll and discussions with EPA OAQPS leads focused on Regional Haze and modeling adjustments. Final draft of procedures document with visibility projections and glide slope adjustments. Upcoming RTOWG meetings covering methodology, projections, and modeling evaluatio

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Introduction to data modeling and design in Industrial Information Systems at King Saud University College of Engineering. The chapter covers the significance of data modeling, capturing data characteristics, structural information, and the role of databases and DBMS. Data modeling fills crucial gap

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The Slovene National Statistical System comprises institutions like the Statistical Office of the Republic of Slovenia and various advisory committees responsible for producing official statistical data following European and UN standards. It emphasizes neutrality, objectivity, transparency, and con

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Mega-Modeling is a comprehensive approach that encompasses model construction, evaluation, composition, evolution, and search to address challenges in various areas such as social and economic resilience, health, transportation, and energy management. The pillars of Mega-Modeling include Model-Drive

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