A comparison between High-Performance Thin-Layer Chromatography (HPTLC) analysis and Liquid Chromatography High Resolution Mass Spectrometry (LC–HRMS), coupled with Principal Component Analysis (PCA) was carried out by performing a combined met...
Crop leaf disease management and control pose significant impact on enhancement in yield and quality to fulfill consumer needs. For smart agriculture, an intelligent leaf disease identification system is inevitable for efficient crop health monitorin...
This paper presents a novel feature descriptor termed principal component analysis (PCA)-based Advanced Local Octa-Directional Pattern (ALODP-PCA) for content-based image retrieval. The conventional approaches compare each pixel of an image with cert...
To overcome the shortage of traditional temperature sensors, this paper adopts infrared thermal imaging technology for temperature measurement. To avoid the spatial information loss issue during the image data vectorization process, this paper adopte...
Industrial Internet of Things (IIoT) systems generate high-dimensional, non-stationary sensor streams under strict memory and computational constraints, limiting the applicability of classical batch dimensionality reduction methods. While incremental...
With the increasing demand for high quality audio, stereo audio coding has become more and more important. In this paper, a multi-frame coding method based on Principal Component Analysis (PCA) is proposed for the compression of audio signals, includ...
Malware is any malicious program that can attack the security of other computer systems for various purposes. The threat of malware has significantly increased in recent years. To protect our computer systems, we need to analyze an executable file to...
In the process of medical imaging, often because of some disturbance, the medical images frequently have some undesirable tilt, which has costly negative effect on the following image alignment and fusion. In order to solve the tilt problem, Sing...
In recent years, geographically weighted regression (GWR) models have been widely used to address the spatial heterogeneity and spatial autocorrelation of PM2.5, but these studies have not fully considered the effects of all potential variables on PM...
Fine particulate matter (PM2.5) is one of the main air pollution problems that occur in major cities around the world. A country’s PM2.5 can be affected not only by country factors but also by the neighboring country’s air quality factors. Therefore,...
Automated medical image analysis is an emerging field of research that identifies the disease with the help of imaging technology. Diabetic retinopathy (DR) is a retinal disease that is diagnosed in diabetic patients. Deep neural network (DNN) is wid...
Ground reaction force (GRF) components can be estimated using insole pressure sensors. Principal component analysis in conjunction with machine learning (PCA-ML) methods are widely used for this task. PCA reduces dimensionality and requires pre-norma...
To achieve sustainable development and improve market competitiveness, many manufacturers are transforming from traditional product manufacturing to service manufacturing. In this trend, the product service system (PSS) has become the mainstream of s...
Remifentanil is a potent opioid characterized by a unique pharmacokinetic profile that makes it well-suited for analgesia in obstetrics. When administered in a patient-controlled analgesia (PCA) modality, remifentanil has become a recognized and vers...
In radar target detection, constant false alarm rate (CFAR), which stands for the adaptive threshold adjustment with variation of clutter to maintain the constant probability of false alarm during the detection, plays an important role. Matrix CFAR d...
Spatial and spectral information are essential sources of information in remote sensing applications, and the fusion of panchromatic and multispectral images effectively combines the advantages of both. Due to the existence of two main classes of fus...
Automated data exploration is very useful for evaluating key aspects of populations such as young adults (which here refers to the youth population in the United States represented by students in grades 9 through 12). This article shows how Principal...
Compression of hyperspectral imagery increases the efficiency of image storage and transmission. It is especially useful to alleviate congestion in the downlinks of planes and satellites, where these images are usually taken from. A novel compression...
The aim of the study was a quantitative analysis of p-chloroaniline (PCA) formation during 2% CHX activation with US and MDI methods in a root canal-like environment with the HPLC-DAD method and, thus, a safety assessment of US and MDI agitation of C...
A Distributed Elevator Fault Diagnosis System (DEFDS) is developed to tackle frequent malfunctions stemming from the widespread distribution and aging of elevator systems. Due to the complexity of elevator fault data and the subtlety of fault charact...
Image data sharpening is a challenging field of remote sensing science, which has become more relevant as high spatial-resolution satellites and superspectral sensors have emerged. Although the spectral property is crucial for mineral mapping, spatia...
To explore the application of a traditional machine learning model in the intelligent management of pigs, in this paper, the influence of PCA pre-treatment on pig face identification with RF is studied. By this testing method, the parameters of two t...
Dictionary pruning step is often employed prior to the sparse unmixing process to improve the performance of library aided unmixing. This paper presents a novel recursive PCA approach for dictionary pruning of linearly mixed hyperspectral data motiva...
Raicilla is a distinctive Mexican beverage produced in two central regions of Jalisco. This study aimed to analyze the physicochemical parameters of 25 raicilla alcoholic drinks originating from the Coast and Sierra regions. Each of the 25 raicilla b...
The financial stability of the commercial banking sector remains one of the critical responsibilities of the Reserve Bank of India (RBI). Weak banks cause instability in the financial system, triggering depositor runs. While several studies covered t...
The problem of air pollution has attracted more and more attention. PM2.5 is a key factor affecting air quality. In order to improve the prediction accuracy of PM2.5 concentration and make people effectively control the generation and propagation of...
Plant diseases have a large impact on agricultural production, leading to crop yield reduction and causing economic losses. For the development of intelligent agriculture, it is very important to identify crop diseases accurately. With the help of im...
Croatia’s tourism market is highly exposed to digital platforms and peer-to-peer information flows, yet evidence on how Croatian users differentiate between promotional formats (digital channels, agency websites, traditional media and word-of-m...
Hyperspectral anomaly detection application is essential in numerous different remote sensing applications, where the detection of rare and unknown targets in complex scenes is needed. The proposed anomaly detection method in this study is called L-P...
Supply Chain Finance (SCF) is a new type of financing business carried out by commercial banks on the basis of supply chain management, which effectively promotes the healthy development of the supply chain. As the most typical mode of SCF, accounts...
The aim of the study was the evaluation of the suitability of 5-oxo-2-pyrrolidinecarboxylic acid (PCA), also in combination with hyaluronic acid (HA), as artificial tears for treatment of dry eye syndrome (DES). Different aqueous formulations contain...
A novel fault diagnosis method is proposed, depending on a cloud service, for the typical faults in the hydraulic directional valve. The method, based on the Machine Learning Service (MLS) HUAWEI CLOUD, achieves accurate diagnosis of hydraulic valve...
Speech emotion recognition is key to many fields, including human–computer interaction, healthcare, and intelligent assistance. While acoustic features extracted from human speech are essential for this task, not all of them contribute to emoti...
In this study, chitosan nanoparticles were used as a carrier for Protocatechuic acid (PCA) to resist Pyricularia oryzae against rice blast. The final compound was characterized using zeta potentials for its surface electricity, Fourier transform infr...
Principal Component Analysis (PCA) is a technique for dimensionality reduction that is useful in removing redundant information in data for various applications such as Microwave Imaging (MI) and Hyperspectral Imaging (HI). The computational complexi...
Phosphorite is a nonrenewable strategic resource, a convenient and rapid method of phosphorite grade identification and classification is important to improve phosphate utilization. In this study, Raman spectroscopy has been combined with principal c...
Principal Component Analysis (PCA) is one of the main methods used for electronic nose pattern recognition. However, poor classification performance is common in classification and recognition when using regular PCA. This paper aims to improve the cl...
Ground penetrating radar (GPR) is one of the most generally used underground sensing equipment, but it is frequently contaminated by clutter and noise during data acquisition, which has a significant impact on the detection performance of buried targ...
Floods and droughts are driven, in part, by spatial patterns of extreme rainfall. Heat waves are driven by spatial patterns of extreme temperature. It is therefore of interest to design statistical methodologies that allow the rapid identification of...
Dimensionality reduction is fundamental for analyzing high-dimensional data, supporting visualization, denoising, and structure discovery. We present a systematic, large-scale benchmark of three widely used methods—Principal Component Analysis...
With the continuous development of human society, earthquakes are becoming more and more dangerous to the production and life of human society. Researchers continue to try to predict earthquakes, but the results are still not significant. With the de...
This tutorial provides a comprehensive and intuitive journey through the evolution of deep generative models, tracing a clear path from the foundations of Principal Component Analysis (PCA) to modern Variational Autoencoders (VAEs), showing how each...
To improve the signal-to-noise ratio (SNR) of vibration signals in a phase-sensitive optical time-domain reflectometer (Φ-OTDR) system, a principal component analysis variable step-size normalized least mean square (PCA-VSS-NLMS) denoising method...
The process of single-point incremental forming (SPIF) is a relatively new technology that is primarily used in the production of prototypes and small quantities of products. However, the process has several limitations with respect to the quality ch...
In this paper, we propose a boosted 3-D PCA algorithm based on an efficient analysis method. The proposed method involves three steps that improve image detection. In the first step, the proposed method designs a new analysis method to solve the perf...
Improving the quality of service (QoS) and meeting service level agreements (SLAs) are critical objectives in next-generation networks. This article presents a study on applying supervised learning (SL) algorithms in a 5G/B5G service dataset after be...
Location-based services have important economic and social values. The positioning accuracy and cost have a crucial impact on the quality, promotion, and market competitiveness of location services. Dead reckoning can provide accurate location inform...
Numerous studies have reported the effective use of artificial intelligence approaches, particularly artificial neural networks (ANNs)-based models, to tackle tunnelling issues. However, having a high number of model inputs increases the running time...
Surface electromyogram (sEMG) signals are easy to record and offer valuable motion information, such as symmetric and periodic motion in human gait. Due to these characteristics, sEMG is widely used in human-computer interaction, clinical diagnosis a...
The use of electroencephalography (EEG) has recently grown as a means to diagnose neurodegenerative pathologies such as Alzheimer’s disease (AD). AD recognition can benefit from machine learning methods that, compared with traditional manual di...
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