Labroots

Log-linear Model for Modeling for Biases in Microbiome Studies

Microbiome sequencing data are known to be biased; the measured taxa relative abundances can be systematically distorted from their true values at every step in the experimental/analysis workflow. If ...
University of Bristol

Introduction to Linear and Logistic Regression Models

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...
IEEE

Data-Driven Linear Parameter-Varying Model Predictive Control for Unknown Nonlinear Systems

Abstract: This article proposes a data-driven linear parameter variation model predictive control (DDLPVMPC) method for unknown nonlinear (NL) systems. The approach eliminates reliance on prior ...
IEEE

Adaptive Model-Free Deadbeat Predictive Current Control for Linear Permanent Magnet Synchronous Motor Based on Immune Algorithm

Abstract: The model free deadbeat predictive current control (MFDPCC) for linear permanent magnet synchronous motor (LPMSM) drive system is emerging as a promising method due to its straightforward ...
GitHub

Can Large Language Models Predict Parallel Code Performance?

We took this version of HeCBench and are modifying it to build the CUDA and OMP codes to gather their roofline performance data. So far we have a large portion of the CUDA and OMP codes building ...