Developing the CAST Highlight CO2 Emission Estimator (Beta) - February 2024
CAST Research Labs studied the impact of removing green deficiencies detected by CAST Highlight on CO2 emissions and energy consumption in custom software applications. The study led to a formula for estimating potential CO2 emission reductions, which was integrated into the new CAST Highlight CO2 E
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Bayesian Estimation and Hypothesis Testing in Statistics for Engineers
In this course on Bayesian Estimation and Hypothesis Testing for Engineers, various concepts such as point estimation, conditional expectation, Maximum a posteriori estimator, hypothesis testing, and error analysis are covered. Topics include turning conditional PDF/PMF estimates into one number, es
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Query Optimization in Database Management Systems
This content covers the fundamentals of query optimization in Database Management Systems (DBMS), including steps involved, required information for evaluating queries, cost-based query sub-system, and the role of various components like query parser, optimizer, plan generator, and cost estimator. I
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CNN-based Multi-task Learning for Crowd Counting: A Novel Approach
This paper presents a novel end-to-end cascaded network of Convolutional Neural Networks (CNNs) for crowd counting, incorporating high-level prior and density estimation. The proposed model addresses the challenge of non-uniform large variations in scale and appearance of objects in crowd analysis.
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State & Parameter Estimation for Gas-Liquid Cylone in Subsea Production
Discussing the challenges, research status, and scope of estimation for Gas-Liquid Cylindrical Cyclones in subsea production, focusing on the use of soft sensors and different estimation techniques like Unscented Kalman Filter and Linear Moving Horizon Estimator.
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Foundations of Parameter Estimation and Decision Theory in Machine Learning
Explore the foundations of parameter estimation and decision theory in machine learning through topics such as frequentist estimation, properties of estimators, Bayesian parameter estimation, and maximum likelihood estimator. Understand concepts like consistency, bias-variance trade-off, and the Bay
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Zipaworld's EximGPT: AI-Driven Tools for Freight Estimation, HSN Code Lookup
Zipaworld's EximGPT is a cutting-edge AI-powered platform designed to simplify the export-import process with a range of essential tools. The platform features an instant Freight Estimator that provides real-time shipping rate quotes, streamlining yo
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Gender Wage Gap Among Those Born in 1958: A Matching Estimator Approach
Examining the gender wage gap among individuals born in 1958 using a matching estimator approach reveals significant patterns over the life course. The study explores drawbacks in parametric estimation, the impact of conditioning on various variables, and contrasts with existing literature findings,
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Student Loan Repayment Tips and Resources
Explore essential information on student loan repayment, including the loan life cycle, basics of repayment, loan history at UW, available repayment plans, and key resources. Understand the importance of keeping loan servicers informed and utilizing tools such as the loan repayment estimator. Take c
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Multiple Regression Analysis of Energy Consumption in Luxury Hotels - Hainan Province, China
Conducting a multiple regression analysis on the energy consumption of luxury hotels in Hainan Province, China using matrix form in Excel. The dataset includes 19 luxury hotels with the dependent variable being energy consumption (1M kWh) and predictors such as area, age, and effective number of gue
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Robust Sensor Fusion for Robot Attitude Estimation
Attitude estimation is crucial for robots to understand their orientation relative to the global frame. This project presents an attitude estimator that combines gyro, accelerometer, and magnetometer data to calculate a quaternion orientation estimate. The robust sensor fusion method ensures accurat
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Understanding Resampling Methods: Bootstrap vs Jackknife
Resampling methods, such as Bootstrap and Jackknife, offer valuable ways to estimate statistical properties without relying on specific data distributions. The Bootstrap method generates samples by resampling data with replacement, while Jackknife involves systematically leaving out observations. Bo
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Introduction to Survival Analysis in Epidemiological Research
In epidemiology, survival analysis is used to analyze time-to-event outcomes like time until death or disease occurrence. It evaluates the effect of treatments on outcomes and considers both event occurrence and timing. This involves various methods such as the Kaplan-Meier estimator, hazard analysi
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Analyzing Variations in MIK Class Means by Jeremy Vincent
The presentation delves into the MIK estimator, exploring its impact on estimation with constant class means and non-Gaussian data. Review of initial results, examination of class mean bias in upper tail, and implications for metal containment are discussed. Cross-validation study findings, future w
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Understanding Correlated Errors in Data Analysis
Explore the impact of correlated errors in data analysis, learn how to identify and address them, and discover solutions such as using Newey-West estimator or adding lagged variables to the model. See examples like Coca-Cola stock prices and understand how correlated errors can affect model fitting.
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Understanding IV Regression in Development Economics
This research provides insights into the use of instrumental variable (IV) regressions in development economics, addressing issues of endogeneity bias and outlining the principles and conditions for IV estimation. It covers examples related to institutions, growth, and foreign aid, highlighting the
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Trust Metric Estimator: Computational Model for Trustworthiness Assessment
The Trust Metric Estimator project aims to create a computational model to estimate user trust levels towards system performance over time. It considers social and technical factors, integrating trust, trustworthiness, and economic aspects to aid decision-making. Research includes surveys to identif
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