Explore the CGC Aarhus University International Summer Internship Program in Denmark focusing on business modelling and innovation. The program offers a comprehensive learning experience for graduate and postgraduate students, including online sessions and weeks in Denmark. Discover the significance

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This study examines the tradeoffs between water savings, economic impact, and greenhouse gas emissions resulting from technological changes in the irrigation industry. Key objectives include estimating water savings for different crops, quantifying GHG emissions from new irrigation technologies, and

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Explore a research study on modelling estuarine habitats in the Upper Sea Scheldt under various human-induced channel and floodplain adaptations. The study examines the impact of interventions on habitat size, water quality, ecosystem, and more, providing insights into the future of the estuarine en

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Explore the innovative methods and practical applications of Stochastic Storm Transposition (SST) in the context of HEC-HMS. Delve into the history, fundamentals, simulation procedures, and benefits of using SST for watershed-averaged precipitation frequency analysis. Learn about the non-parametric

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Threat modelling should commence at the early stage of the software development life cycle to identify potential security risks and vulnerabilities effectively. It should ideally begin during the requirement analysis and continue throughout development, testing, and maintenance phases to ensure robu

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This content discusses the CGRA-ME framework for modelling and exploration of Coarse-Grained Reconfigurable Arrays (CGRA). It covers the objectives, architecture description, inputs required, and tools included in the framework. CGRA-ME allows architects to model different CGRA architectures, map ap

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EUROfusion's WPSA Code Management and Modelling activities for 2021-2022 focus on developing operation-oriented tools and synthetic diagnostics for JT-60SA scientific exploitation. The tasks include discharge simulator development, breakdown simulator optimization, Energetic Particle stability analy

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Introducing xtsfkk, a new Stata command for fitting panel stochastic frontier models with endogeneity, offering better control for endogenous variables in the frontier and/or the inefficiency term in longitudinal settings compared to standard estimators. Learn about the significance of stochastic fr

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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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Enterprise and system models play a crucial role in the business world. This collection of images showcases various aspects of conceptual and requirement modelling using Unified Modelling Language (UML). From business process models to human interactions with software systems, these visual represent

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SCRUM2 project aims to enhance CMEMS through regional/coastal ocean-biogeochemical uncertainty modelling, ensemble consistency verification, probabilistic forecasting, and data assimilation. The research team plans to contribute significant advancements in ensemble techniques and reliability assessm

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Explore the simplest model of population growth and the assumptions it relies on. Delve into the challenges of real-world scenarios, such as stochastic effects caused by demographic and environmental variations in birth and death rates. Learn how these factors impact predictions and models.

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Discussion at the Climate Modelling User Group meeting highlighted the use of Ocean ECVs, with a focus on organic carbon production and model comparisons. Key topics included increasing resolution, biogeochemistry predictions, and validation using OC CCI data. Various WP projects were also discussed

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N-gram models play a crucial role in language modelling by predicting the next word in a sequence based on the probability of previous words. This technology is used in various applications such as word prediction, speech recognition, and spelling correction. By analyzing history and probabilities,

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In this workshop session by David Rogerson, an ITU expert, participants learn the key habits of successful cost modelling in the telecom industry. The session covers identifying, illustrating, remembering, and implementing these habits for effective regulatory cost-modelling practices, with a focus

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The content provides a detailed guide on accessing and utilizing CBA Results Files, including tips on reading the CBA Methodology and understanding various indicators and economic templates. It also highlights the importance of analyzing disrupted rates, quantities, flexibility, and other key compon

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The Climate Modelling User Group (CMUG) discussion session aims to foster collaboration among members, welcome new participants, identify common research questions and challenges, and establish long-term interaction mechanisms. The session includes presentations on ECV consistency and planetary visi

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Modelling and multi-objective optimization of quality attributes in variability-rich software is crucial for customizing software functionality to meet stakeholders' diverse needs. This involves addressing conflicting quality requirements such as cost, reliability, performance, and binary footprint

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Explore advanced techniques in dimensional modelling such as handling rapidly changing dimensions, snowflaking dimensions, and dealing with very large dimensions. Learn about different types of dimension structures, fact tables, and their combinations to optimize data storage and retrieval efficient

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Cross-classified models in multilevel modelling involve non-hierarchical data structures where entities are classified within multiple categories. These models extend traditional nested multilevel models by accounting for complex relationships among data levels. Professor William Browne from the Uni

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This presentation delves into the analysis and optimality of multiserver stochastic scheduling, focusing on the theory of large-scale computing systems, queueing theory, and prior work on single-server and multiserver scheduling. It explores optimizing response time and resource efficiency in modern

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This piece discusses approximation algorithms for stochastic optimization problems, focusing on modeling uncertainty in inputs, adapting to stochastic predictions, and exploring different optimization themes. It covers topics such as weakening the adversary in online stochastic optimization, two-sta

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Today's presentation will delve into the comparison between RNNs and CNNs for various tasks, discuss a state-of-the-art approach for Sequence Modelling, and explore augmented RNN models. The discussion will include empirical evaluations, baseline model choices for tasks like text classification and

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In this lecture, the focus is on modelling workflows and data domain in the context of system requirements and user experience. The topics covered include recap of use cases, use case diagrams, descriptions, events initiated by stakeholders, defining elements for each use case, use case diagrams, an

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Stochastic dynamic programming with Markov chains is used for optimal control of the forest sector, focusing on continuous cover forestry. This approach optimizes forest industry production, harvest levels, and logistic solutions based on market conditions. The method involves solving quadratic prog

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Exploring the use of a stochastic weather generator combined with downscaled General Circulation Models for climate change analysis in the California Department of Water Resources. The presentation outlines the motivation, weather-regime based generator description, scenario generation, and a case s

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Explore the significance of modelling knowledge through knowledge representation, making it explicit, independent, and reusable. Learn why knowledge representation is essential and how it facilitates exchange, query, inference, and visualization. Delve into examples of knowledge application in vario

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Explore the use of scientific modelling in atomic theory through a learning journey covering topics like the atom, hazards, risks, and atomic structure. Engage in a True or False task to test your knowledge and delve into a video timeline on the discovery of silver and gold elements.

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Explore the capabilities of COMPLEX-IT, a web-based software tool designed to enhance researchers' access to computational social science tools. It offers a compact platform integrating case-based modelling, artificial intelligence, scenario analysis, and more. With an intuitive interface and quick

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In June 2017, a Summer School on Modelling Tools for Sustainable Development was organized at ICTP, Trieste. The sessions covered topics like representation of water supply and demand, incorporation of land use in modelling, energy system diagrams, and structures of energy and water systems models.

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Energy systems modelling with OSeMOSYS involves linear programming to determine the optimal energy system configuration. The tool considers factors like demand, available technologies, emissions, and constraints to minimize costs over decades. Linear programming, developed during World War II, plays

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Explore the concept of intermediate stops in transportation modelling, including the development of a new tour-based model in Charlotte. Learn about the challenges faced in modelling stops and the estimation process using the Logit model. Discover how tour frequency, main destination choice, number

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Explore the concepts of Brownian motion, integration of stochastic differential equations, and derivations by Einstein and Langevin. Learn about the assumptions, forces, and numerical integration methods in the context of stochastic processes. Discover the key results and equations that characterize

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Explore the world of Modelling Weeks where small teams of students work on real-life problems under experienced instructors. Benefits include networking, teamwork, presenting results, and preparing scientific documents. Organize your own Modelling Week with support from MI-NET, focusing on PhD stude

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Explore Generalized Stochastic Petri Nets (GSPN) to model manufacturing systems and evaluate steady-state performances. Learn about stochastic Petri nets, inhibitors, priorities, and their applications through examples. Delve into models of unreliable machines, productions systems with priorities, a

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Stochastic algorithms, including Monte Carlo and Las Vegas variations, leverage randomness to tackle complex tasks efficiently. While Monte Carlo algorithms prioritize speed with some margin of error, Las Vegas algorithms guarantee accuracy but with variable runtime. They play a vital role in primal

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Explore an optimal stopping approach for early drought detection, focusing on setting trigger levels based on precipitation measures. The goal is to determine the best time to send humanitarian aid by maximizing expected rewards and minimizing expected costs through suitable gain/risk functions. Tas

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Explore the world of viral marketing and user behavior optimization through stochastic optimal control in the realm of human-centered machine learning. Discover strategies to maximize user activity in social networks by steering behaviors and understanding endogenous and exogenous events. Dive into

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Explore the relationship between sample and space complexity in stochastic streams to estimate distribution properties and solve various problems. The research delves into the tradeoff between the number of samples required to solve a problem and the space needed for the algorithm, covering topics s

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Training dense linear models on FPGA with low-precision data offers increased hardware efficiency while maintaining statistical efficiency. This approach leverages stochastic rounding and multivariate trade-offs to optimize performance in machine learning tasks, particularly using Stochastic Gradien

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