Granger causality (GC) is a popular method in causal linkage recovery and has been applied to various fields, such as economics and neuroscience. While the conventional Granger causality model is capable of identifying symmetrical causal relationship...
The present paper is concerned with the study of the quality of life index. Such an index has become an important index for measuring the well-being of individuals. However, the quality of life index is always subjective, intangible, and often hard t...
The traditional battery state of charge (SOC) estimation method, which is based on neural networks, directly uses terminal voltage and terminal current as the input data. Although it is convenient to implement, it produces a large estimation error wh...
Because of noise interference, improper exposure, and the over thickness of human tissues, the detailed information of DR (digital radiography) images can be masked, including unclear edges and reduced contrast. An image-enhancement algorithm based o...
Hydrological regionalization is a useful step in hydrological modeling and prediction. The regionalization is not always straightforward, however, due to the lack of long-term hydrological data and the complex multi-scale variability features embedde...
To achieve high-precision geomagnetic matching navigation, a reliable geomagnetic anomaly basemap is essential. However, the accuracy of the geomagnetic anomaly basemap is often compromised by noise data that are inherent in the process of data acqui...
Scrap steel represents a sustainable and recyclable resource, instrumental in diminishing carbon footprints and facilitating the eco-friendly evolution of the steel sector. However, current scrap steel recycling faces a series of challenges, such as...
Congestive heart failure (CHF) is a chronic heart condition associated with debilitating symptoms that can lead to mortality. The electrocardiogram (ECG) is a noninvasive and simple diagnostic method that can show detectable changes in CHF. However,...
Owing to the problems that imperfect decomposition process of empirical mode decomposition (EMD) denoising algorithm and poor self-adaptability, it will be extremely difficult to reduce the noise of signal. In this paper, a noise reduction method of...
The proposed research takes place in the framework of the analysis of the mechanical consequences of accidental scenarios for pressurized water reactors (PWR). It is particularly dedicated to the effects of the propagation of a transverse rarefaction...
Discriminative feature extraction and rolling element bearing failure diagnostics are very important to ensure the reliability of rotating machines. Therefore, in this paper, we propose multi-scale wavelet Shannon entropy as a discriminative fault fe...
This paper presents a novel framework to determine the number of resolution levels in the application of a wavelet transformation to a rainfall time series. The rainfall time series are decomposed using the à trous wavelet transform. Then, multi-scal...
Super-resolution (SR) is significant for hyperspectral image (HSI) applications. In single-frame HSI SR, how to reconstruct detailed image structures in high resolution (HR) HSI is challenging since there is no auxiliary image (e.g., HR multispectral...
The relationship between urban landscape pattern and land surface temperature (LST) is one of the core issues in urban thermal environment research. Although previous studies have shown a significant correlation between LST and landscape pattern, mos...
As critical components of planetary gearboxes, gears directly affect mechanical system reliability when faults occur. Traditional feature extraction methods exhibit limitations in accurately identifying fault characteristics and achieving satisfactor...
Soil is a critical natural resource that requires continuous monitoring to support sustainable agriculture. Among soil properties, pH is an essential indicator because it strongly affects nutrient availability and biological activity. Visible–N...
Lost circulation is a major challenge in the drilling process, which seriously restricts the safety and efficiency of drilling. The traditional monitoring model is hindered by the presence of noise and the complexity of temporal fluctuations in lost...
Image super resolution (SR) is an important image processing technique in computer vision to improve the resolution of images and videos. In recent years, deep convolutional neural network (CNN) has made significant progress in the field of image SR;...
Accurate segmentation of the intercondylar notch of the femur is of great significance for the diagnosis of knee joint diseases, surgical planning, and anterior cruciate ligament (ACL) reconstruction. Among them, the obvious anatomical heterogeneity,...
Ultrasound imaging is widely used in medical diagnostics due to its non-invasive and real-time capabilities. However, existing methods often overlook the benefits of fractional-order filters for denoising and dehazing. Thus, this work introduces an e...
Arc faults are one of the important causes of electric fires. In order to solve the problem of randomness, diversity, the concealment of series arc faults and to improve the detection accuracy, a novel arc fault detection method integrated random for...
Infrared small target detection (ISTD) means distinguishing small and faint targets from IR images. Small targets typically span only a handful of pixels, lacking distinct texture and clear structural details. For the past few years, deep learning ha...
In remote sensing imagery, objects smaller than
This paper presents a rolling bearing fault diagnosis approach by integrating wavelet packet decomposition (WPD) with multi-scale permutation entropy (MPE). The approach uses MPE values of the sub-frequency band signals to identify faults appearing i...
Chatter is a complex dynamic instability in machining processes and presents nonlinear and nonstationary behavior. Detection of this phenomenon before a catastrophic failure occurs has great importance in the industry today. This behavior demands onl...
The precise segmentation of thyroid nodules in ultrasound images is essential for computer-aided diagnosis and treatment. Although various deep learning methods have been proposed, similar intensity distributions and variable nodule morphology often...
This paper analyzes the underlying complexity and non-linearity of electroencephalogram (EEG) signals by computing a novel multi-scale entropy measure for the classification of seizure, seizure-free and normal EEG signals. The quality factor (Q) base...
In the Mallat algorithm, calculations are performed in the time domain. To speed up the signal conversion at each level, the wavelet coefficients are sequentially halved. This paper presents an algorithm for increasing the speed of multiscale signal...
In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image fro...
Accounting for realistic observation errors is a known bottleneck in data assimilation, because dealing with error correlations is complex. Following a previous study on this subject, we propose to use multiscale modelling, more precisely wavelet tra...
Rolling bearing vibration signals contain rich fault feature information. However, their periodic pulse feature is often interfered with by strong background noise, which reduces the feature recognition ability of fault diagnosis strategies. Therefor...
Blade icing is one of the main problems of wind turbines installed in cold climate regions, resulting in increasing power generation loss and maintenance costs. Traditional blade icing detection methods greatly rely on dedicated sensors, such as vibr...
A crucial assurance for coal mine safety production, prevention and control, and rescue, which is the fundamental tenet of implementing intelligent coal mining, is the safety, stability, and quick transmission of coal mine roadways. However, because...
Rotating machines predominantly operate under healthy conditions, leading to a limited availability of fault data and a significant class imbalance in diagnostic datasets. These challenges hinder the development and deployment of fault diagnosis meth...
Using the wavelet transform defined in the infinite domain to process the signal defined in finite interval, the wavelet transform coefficients at the boundary are usually very large. It will bring severe boundary effect, which reduces the calculatio...
The accurate and efficient classification of steel surface defects is critical for ensuring product quality and minimizing production costs. This paper proposes a novel method based on wavelet transform and texture descriptors for the robust and prec...
Infrared images are often degraded by complex noise due to hardware and environmental factors, posing challenges for subsequent processing and target detection. To overcome the shortcomings of existing denoising methods in balancing noise removal and...
The 2017 Jiuzhaigou Ms 7.0 earthquake occurred on the northeastern margin of the Tibetan Plateau, with no noticeable rupture surface recognized. We characterized the pre-seismic deformation of the earthquake from GPS (Global Positioning System) data...
Multiscale PCA (MSPCA) is a well-established fault-detection and isolation (FDI) technique. It utilizes wavelet analysis and PCA to extract important features from process data. This study demonstrates limitations in the conventional MSPCA fault dete...
Online partial discharge (PD) detection for power cables is one reliable means of monitoring their health. However, strong interference by white noise poses a major challenge in the process of collecting information on partial discharge signals. To s...
The article discusses experimental studies assessing the possibility of mapping surfaces with a characteristic distribution of irregularities. Tests involved surfaces produced using the L-PBF additive technology, using titanium-powder-based material...
Existing gearbox fault diagnosis methods are prone to noise interference and cannot extract comprehensive fault signals, leading to misdiagnosis or missed diagnosis. This paper proposes a method for gearbox fault diagnosis based on adaptive variation...
Bearing fault diagnosis methods play an important role in rotating machine health monitoring. In recent years, various intelligent fault diagnosis methods have been proposed, which are mainly based on the features extraction method combined with eith...
Despite the successful applications of the remote sensing image in agriculture, meteorology, and geography, its relatively low spatial resolution is hindering the further applications. Super-resolution technology is introduced to conquer such a dilem...
The article assesses the impact of data treatment on the possibility of assessing the morphological features of additively manufactured spherical surfaces. Tests were carried out on specimens manufactured by PBF-LB/M additive technology, using titani...
Aiming at the problems of leakage and misdetection caused by insufficient multi-scale feature extraction and an excessive amount of model parameters in bridge defect detection, this paper proposes the AMSF-Pyramid-YOLOv11n model. First, a Cooperative...
Deep learning models with convolutional operators have received widespread attention for their good image denoising performance. However, since the convolutional operation prefers to extract local features, the extracted features may lose some global...
Magnetotelluric (MT) sounding data can easily be damaged by various types of noise, especially in industrial areas, where the quality of measured data is poor. Most traditional de-noising methods are ineffective to the low signal-to-noise ratio of da...
The accurate detection of occluded tomatoes in complex greenhouse environments remains challenging due to the limited feature representation ability and high computational costs of existing models. This study proposes SWMD-YOLO, a lightweight multi-s...
The low-altitude atmospheric environment has been receiving increasing attention in recent years due to rising human activities and the emerging growth of the low-altitude economy. Urban wakes generate highly inhomogeneous, multiscale turbulent flows...
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