AIMC Topic: Principal Component Analysis

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A new method for detecting mixed bacteria based on multi-wavelength transmission spectroscopy technology.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Previously, we successfully realized the identification of a single species of bacteria based on the multi-wavelength transmission spectrum of bacteria. The current research is focused on realizing the spectral analysis of mixed bacteria. Principal c...

Study on Structural Characteristics of Composite Smart Grille Based on Principal Component Analysis.

Computational intelligence and neuroscience
In recent years, many scholars have conducted in-depth and extensive research on the mechanical properties, preparation methods, and structural optimization of grid structural materials. In this paper, the structural characteristics of composite inte...

Intelligent Fault Diagnosis Framework for Modular Multilevel Converters in HVDC Transmission.

Sensors (Basel, Switzerland)
Open circuit failure mode in insulated-gate bipolar transistors (IGBT) is one of the most common faults in modular multilevel converters (MMCs). Several techniques for MMC fault diagnosis based on threshold parameters have been proposed, but very few...

Towards a Resilience to Stress Index Based on Physiological Response: A Machine Learning Approach.

Sensors (Basel, Switzerland)
This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These variables include electromyography, which is the muscle response, blood volume pulse, breathing rate...

An Intelligence Method for Recognizing Multiple Defects in Rail.

Sensors (Basel, Switzerland)
Ultrasonic guided waves are sensitive to many different types of defects and have been studied for defect recognition in rail. However, most fault recognition algorithms need to extract features from the time domain, frequency domain, or time-frequen...

Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain.

Scientific reports
Automatic pattern recognition using deep learning techniques has become increasingly important. Unfortunately, due to limited system memory, general preprocessing methods for high-resolution images in the spatial domain can lose important data inform...

Non-invasive diagnosis of Crohn's disease based on SERS combined with PCA-SVM.

Analytical methods : advancing methods and applications
Crohn's disease (CD) is an idiopathic chronic inflammatory bowel disease without a cure. Most of the CD patients are firstly diagnosed by invasive endoscopy, and clinical and pathological examinations are further required to confirm the diagnosis. He...

Predictive Analysis and Evaluation Model of Chronic Liver Disease Based on BP Neural Network with Improved Ant Colony Algorithm.

Journal of healthcare engineering
Timely prediction of the mechanism and characteristics of chronic liver disease using next-generation information technology is an effective way to improve the diagnosis rate of chronic liver disease. In this paper, we have proposed a modified backpr...

Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data.

Computational and mathematical methods in medicine
The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic ...