For gait phase estimation, time-series data of lower-limb motion can be segmented according to time windows. Time-domain features can then be calculated from the signal enclosed in a time window. A set of time-domain features is used for gait phase e...
The frequent occurrence of single-phase grounding faults affects the reliable operation of power systems. When a single-phase grounding fault occurs, it is difficult to accurately identify the fault type because of the weak characterization and subtl...
Compared with the amplitude modulation of conventional interrupted sampling repeater jamming (ISRJ), the image feature control method based on phase modulation exhibits greater energy efficiency and, therefore, has received wide attention recently. I...
Autofocus is an essential technique for airborne synthetic aperture radar (SAR) imaging to correct phase errors mainly due to unexpected motion error. There are several well-known conventional autofocus methods such as phase gradient autofocus (PGA)...
Images captured by different sensors with different spectral bands cause non-linear intensity changes between image pairs. Classic feature descriptors cannot handle this problem and are prone to yielding unsatisfactory results. Inspired by the illumi...
Channel state information (CSI) provides a fine-grained description of the signal propagation process, which has attracted extensive attention in the field of indoor positioning. However, considering the influence of environment and hardware, the pha...
In view of the limitations of the existing eccentricity error separation method of the rotary table, an eccentricity error separation method based on the phase feature of the moiré signal of a single reading head is proposed herein. A grating...
Local region description of multi-sensor images remains a challenging task in remote sensing image analysis and applications due to the non-linear radiation variations between images. This paper presents a novel descriptor based on the combination of...
18F-florbetaben (FBB) positron emission tomography is a representative imaging test that observes amyloid deposition in the brain. Compared to delay-phase FBB (dFBB), early-phase FBB shows patterns related to glucose metabolism in 18F-fluorodeoxygluc...
Two-phase flow is very important in many areas of science, engineering, and industry. Two-phase flow comprising gas and liquid phases is a common occurrence in oil and gas related industries. This study considers three flow regimes, including homogen...
The increasing consumption of fossil fuel resources in the world has placed emphasis on flow measurements in the oil industry. This has generated a growing niche in the flowmeter industry. In this regard, in this study, an artificial neural network (...
Titanium (Ti) alloy sheets are important mechanical and structural components. However, thickness deviations may occur during the production of Ti-alloy sheets, significantly compromising product quality and structural safety. Eddy current testing (E...
With the growing penetration of wind power into electric grids, improving wind speed prediction accuracy has become particularly valuable for the exploitation of wind power. In this paper, a novel hybrid strategy based on a three-phase signal decompo...
To improve the recognition accuracy of ship-radiated noise, a feature extraction method based on regenerated phase-shifted sinusoid-assisted empirical mode decomposition (RPSEMD), mutual information (MI), and differential symbolic entropy (DSE) is pr...
A segmented primary mirror is very important for extra-large astronomical telescopes, in order to detect the phase error between segmented mirrors. Traditional iterative algorithms are hard to detect co−phasing aberrations in real time due to t...
Recently, supervised learning methods have shown promising performance, especially deep neural network-based (DNN) methods, in the application of single-channel speech enhancement. Generally, those approaches extract the acoustic features directly fr...
Breast cancer is a leading cause of mortality among women worldwide. Early detection is crucial for increasing patient survival rates. Artificial intelligence, particularly convolutional neural networks (CNNs), has enabled the development of effectiv...
This paper proposes a novel approach for selecting a subset of features in semi-supervised datasets where only some of the patterns are labeled. The whole process is completed in two phases. In the first phase, i.e., Phase-I, the whole dataset is div...
The phases of high-entropy alloys (HEAs) are closely related to their properties. However, phase prediction bears a significant challenge due to the extensive search space and complex formation mechanisms of HEAs. This study demonstrates a precise an...
Measuring fluid characteristics is of high importance in various industries such as the polymer, petroleum, and petrochemical industries, etc. Flow regime classification and void fraction measurement are essential for predicting the performance of ma...
One of the factors that significantly affects the efficiency of oil and gas industry equipment is the scales formed in the pipelines. In this innovative, non-invasive system, the inclusion of a dual-energy gamma source and two sodium iodide detectors...
Accurate interferometric phase filtering is an essential step in InSAR data processing. The existing deep learning-based phase-filtering methods were developed based on local neighboring pixels and only use local phase information. The idea of nonloc...
This paper proposes a novel feature extraction method for intrusion event recognition within a phase-sensitive optical time-domain reflectometer (Φ-OTDR) sensing system. Feature extraction of time domain signals in these systems is time-consuming and...
This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In ord...
Gait phase recognition systems based on surface electromyographic signals (EMGs) are crucial for developing advanced myoelectric control schemes that enhance the interaction between humans and lower limb assistive devices. However, machine learning m...
Time-modulated metasurfaces have attracted much attention due to their flexible manipulation of electromagnetic waves. Time-varying response leads to spread-spectrum and reallocation of energy. Thus, an amplitude-phase joint modulation (TAJM) method...
High density phase change memory array requires both minimized critical dimension (CD) and maximized process window for the phase change material layer. High in-wafer uniformity of the nanoscale patterning of chalcogenides material is challenging giv...
The advent of smart grids has facilitated data-driven methods for detecting electricity theft, with a preponderance of research efforts focused on user electricity consumption data. The multi-dimensional power state data captured by Advanced Metering...
Network epidemiology plays a fundamental role in understanding the relationship between network structure and epidemic dynamics, among which identifying influential spreaders is especially important. Most previous studies aim to propose a centrality...
Artificial metasurfaces can rapidly modulate their electromagnetic scattering properties and the characteristics of echo signals, which can lead to different imaging features in synthetic aperture radar (SAR) imaging results. Based on this, for the f...
Interferometric Synthetic Aperture Radar (InSAR) is a widely used remote sensing technology for Earth observation, enabling the detection and measurement of ground deformation through the generation of interferograms. However, phase noise remains a c...
Neural oscillations are present in the brain at different spatial and temporal scales, and they are linked to several cognitive functions. Furthermore, the information carried by their phases is fundamental for the coordination of anatomically distri...
Wavelet transform is an important tool in the computational signal processing of terahertz time-domain spectroscopy (THz-TDS) measurements. Despite its prevalence, the effects of using different forms of wavelet transforms in THz-TDS studies have not...
In recent years, convolutional neural networks have made many advances in the field of computer vision. In smart greenhouses, using robots based on computer vision technology to pollinate flowers is one of the main methods of pollination. However, du...
To address the difficulty of extracting the features of composite-fault signals under a low signal-to-noise ratio and complex noise conditions, a feature-extraction method based on phase-space reconstruction and maximum correlation Re’nyi entro...
Planetary gearboxes are the key components of large equipment, such as wind turbines, shield machines, etc. The operating state of the planetary gearbox is related to the safety of the equipment as a whole, and its feature extraction technology is es...
Determining the volume percentages of flows passing through the oil transmission lines is one of the most essential problems in the oil, gas, and petrochemical industries. This article proposes a detecting system made of a Pyrex-glass pipe between an...
Lipase B from Candida antarctica (CALB) and lipase from Thermomyces lanuginosus (TLL) were immobilized on octyl agarose. Then, the biocatalysts were chemically modified using glutaraldehyde, trinitrobenzenesulfonic acid or ethylenediamine and carbodi...
Planar targets with known features have been widely used for camera calibration in various vision systems. This paper utilizes phase-shifting wedge grating (PWG) arrays as an active calibration target. Features points are encoded into the carrier pha...
The formation of malignant neoplasm can be seen as deterioration of a pre-malignant skin neoplasm in its functionality and structure. Distinguishing melanocytic skin neoplasms is a challenging task due to their high visual similarity with different t...
Infrared and visible image matching methods have been rising in popularity with the emergence of more kinds of sensors, which provide more applications in visual navigation, precision guidance, image fusion, and medical image analysis. In such applic...
Phase wrapping is a common phenomenon in optical full-field imaging or measurement systems. It arises from large phase retardations and results in wrapped-phase maps that contain essential information about surface roughness and topology. However, th...
Audio classification algorithms for hearing aids require excellent classification accuracy. To achieve effective performance, we first present a novel supervised method, involving a spectral entropy-based magnitude feature with a random forest classi...
In numerous applications, such as the correction of grid voltage during voltage sag or swell events caused by system faults, it is necessary to ensure the stabilization of the output voltage with in-phase and out-phase features. This feature can also...
Advanced persistent threat (APT) attacks present significant challenges to cybersecurity due to their covert nature, high complexity, and ability to operate across multiple temporal and spatial scales. Existing detection techniques often struggle wit...
Camera parameters can’t be estimated accurately using traditional calibration methods if the camera is substantially defocused. To tackle this problem, an improved approach based on three phase-shifting circular grating (PCG) arrays is proposed in th...
Traditional eddy current technology identifies metal information with information of single frequency of limited frequency spectrum. To solve existing problems, this paper proposes a discrete wavelet transform-based metal material analysis model by u...
To address the problem of mechanical defect identification in a high-voltage circuit breaker (HVCB), this paper studies the circuit breaker vibration signal and proposes a method of feature extraction based on phase-space reconstruction of the vibrat...
Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how th...
In this paper, we address aerial tracking tasks by designing multi-phase aware networks to obtain rich long-range dependencies. For aerial tracking tasks, the existing methods are prone to tracking drift in scenarios with high demand for multi-layer...
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