Abstract: Multivariate Time Series (MTS) analysis is crucial to understanding and managing complex systems, such as traffic and energy systems, and a variety of approaches to MTS forecasting have been ...
The AERCA algorithm performs robust root cause analysis in multivariate time series data by leveraging Granger causal discovery methods. This implementation in PyTorch facilitates experimentation on ...
LangGraph is a powerful framework by LangChain designed for creating stateful, multi-actor applications with LLMs. It provides the structure and tools needed to build sophisticated AI agents through a ...
ABSTRACT: Petiveria alliacea is a uterotonic plant that effectively helps resolve uterine contractility abnormalities in traditional medicine. However, scientific knowledge of its diversity remains ...
In today’s data-driven world, showcasing the right data analytics tools and skills on your data analyst resume can set you apart from the competition. Whether you’re an aspiring data analyst or a ...
Objective This study aimed to investigate how knee extensor and flexor strength change over time after anterior cruciate ligament reconstruction (ACLR). Design Systematic review with longitudinal meta ...
Recent advances in green chemistry have made multivariate experimental design popular in sample preparation development. This approach helps reduce the number of measurements and data for evaluation ...
The research methodology started with plowing and tilling the land to create a muddy environment. After that, the field was organized with a plot system measuring 3.5 m x 3.5 m and 1 m between plots.
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