This study presents a method to quantify interlaminar damage in refractory composites through in-situ micro-X-ray computed tomography. The procedure aims to capture the progressive failure in ASTM-sized specimens, providing empirical data for improving simulations of composite materials. Various spe

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This resource delves into social science research fundamentals, encompassing types of inquiry, empirical research categories, primary and secondary research distinctions, and the importance of selecting a suitable research topic. It offers guidance on initiating research based on empirical observati

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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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In this chapter, Dr. Maram Bani Younes delves into the analysis of algorithm efficiency, focusing on aspects such as order of growth, best case scenarios, and empirical analysis of time efficiency. The dimensions of generality, simplicity, time efficiency, and space efficiency are explored, with a d

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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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Semi-empirical methods derived from Hartree-Fock theory aim to reduce computational effort by approximating or eliminating electron repulsion integrals. Strategies include introducing adjustable parameters to replace ERI calculations and utilizing zero differential overlap methods like CNDO, INDO, N

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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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Empirical Mode Decomposition (EMD) is a signal processing technique used for separating different oscillation modes in a time series signal. This paper explores the parallel implementation of Multivariate Empirical Mode Decomposition (MEMD) on GPU, discussing numerical steps, implementation details,

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The Law of Definite Proportions governs the composition of compounds based on molar masses, allowing us to calculate percentage compositions of elements within a compound. Through examples involving various compounds like Fe3C, sulfur dioxide, ammonium nitrate, glucose, and acetic acid, we explore t

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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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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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Associate Professor Debra Wilson from the University of Canterbury in New Zealand conducted empirical research on public opinions regarding surrogacy. The findings revealed three surprising results, including perspectives on surrogates being compensated, the importance of genetics in surrogacy arran

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This study delves into the generalization of Empirical Risk Minimization (ERM) in stochastic convex optimization, focusing on minimizing true objective functions while considering generalization errors. It explores the application of ERM in machine learning and statistics, particularly in supervised

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This research focuses on studying the behavior of the real equilibrium exchange rate (REER) of Kuwaiti Dinars, estimating the equilibrium exchange rate using the BEER model, and calculating real exchange misalignments (RERM). It delves into the impact of exchange rate fluctuations on macroeconomic v

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This content provides insights into CPSC 531: System Modeling and Simulation course, covering topics such as performance evaluation, simulation modeling, and terminology in system modeling. It emphasizes the importance of developing simulation programs, advantages of simulation, and key concepts lik

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The history of chemotherapy is divided into three phases, starting from the empirical use of compounds in ancient times to the modern era marked by targeted drug development. Ehrlich's pioneering work in the late 19th to early 20th centuries laid the foundation for understanding the selective toxici

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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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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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Exploring the utilization of CSS preprocessors in web development through an empirical study conducted by Davood Mazinanian and Nikolaos Tsantalis from Concordia University. The study delves into the motivations behind using CSS preprocessors, developers' preferences, features offered by preprocesso

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This research paper focuses on the modification and extension of the De Goede Learning Potential Structural Model, aiming to identify non-cognitive variables influencing learning potential. Through model development, hypothesis testing, and empirical evaluation, the study explores factors such as In

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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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Restricted quantifiers and literal analysis in natural language processing reveal the distinctions between empirical and analytical expressions. While empirical expressions refer to non-trivial intensions that require empirical investigation, analytical expressions denote constant intensions that ca

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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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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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Lake Trout Strategic Project Meeting held on April 24th, 2014, focused on developing new predictive tools to forecast the impact of climate change on hypolimnetic dissolved oxygen concentrations in Lake Trout lakes of Ontario. The meeting agenda covered project objectives, timeline, communication st

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Empirical Credit-Risk Management (ECM) presentation to FMB Group Credit Union by Financial Analytics Ltd discusses the background, traditional forecasting methods, income and risk recognition, provisioning approaches, and benefits for credit unions. ECM offers expert retail credit risk management th

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The research presented at the 18th Organic World Congress in Istanbul delves into the Sustainability and Organic Livestock (SOL-m) modeling approach developed by FAO and FiBL. The study aims to explore the potential impacts of global conversion to organic livestock production by 2050 on food securit

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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 Economist, Aziz Jaid, from the CEA Bureau for North Africa conducted an empirical evaluation on the impact of the ZLECAf in North Africa, focusing on goods. The context includes coverage of seven countries, the rationale behind the ZLECAf agreement, and details on the liberalization scenarios an

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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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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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Exploring the potential for collaboration between philosophy, theoretical psychology, and empirical research, this article delves into the historical divide, recent renaissance, and avenues for mutual enrichment. It raises questions about how each discipline can contribute to and benefit from the ot

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NetLogo is a powerful and versatile programmable modeling environment created by Uri Wilensky in 1999. It allows users to simulate natural and social phenomena by giving instructions to multiple agents operating independently, making it ideal for modeling complex systems evolving over time. NetLogo

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