ENHANCING INTERNAL COMBUSTION ENGINE FAULT DETECTION THROUGH CO-SIMULATION WITH PIEZOELECTRIC PRESSURE MEASURING CHAINS

Enhancing internal combustion engine fault detection through co-simulation with piezoelectric pressure measuring chains

This study undertakes a proof-of-concept investigation,employing a combination of physics-based and empirical 27" Warming Drawer models toanalyze an in-cylinder pressure piezo-electric measurement chain.Theprimary objective is to systematically characterize and comprehenddeviations arising from the components within the measuring chain.Themethod im

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A Rare Case of Triple-Negative Essential Thrombocythemia in a Young Postsplenectomy Patient: A Diagnostic Challenge

The distinction between primary and reactive thrombocytosis by bone marrow histology is very important.Reactive thrombocytosis, the most common cause of thrombocytosis, can be expected in postsplenectomy states; however, close hematological evaluation of prolonged thrombocytosis is essential to identify patients who may have an underlying myeloprol

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Chunk Incremental Canonical Correlation Analysis

For the large-scale dynamic data stream, incremental learning is an effective and efficient technique and is widely used in machine learning.Incremental dimensionality reduction algorithms have been proposed by many scholars.As an improved canonical correlation analysis (CCA) method based on incremental learning, incremental canonical correlation a

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Wheat Lodging Ratio Detection Based on UAS Imagery Coupled with Different Machine Learning and Deep Learning Algorithms

Wheat lodging is a negative factor affecting yield production.Obtaining timely and accurate wheat lodging information is critical.Using unmanned aerial systems (UASs) images for wheat lodging detection is a relatively WHEY ISOLATE VANILLA BEAN new approach, in which researchers usually apply a manual method for dataset generation consisting of plot

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