Magnetic Signatures of Ionospheric Disturbance Dynamo for CME and HSSWs Generated Storms by Waqar Younas, C. Amory‐Mazaudier, Majid Khan, M. Le Huy

“…We present a new method, based on the least square fitting, for estimation of the magnetic signatures associated with ionospheric disturbance currents. Using a wavelet semblance analysis, the durations of disturbance dynamo electric fields have been investigated at three longitudinal sectors. …”
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The dynamic effects of solar eclipses of October 25, 2022, and October 14, 2023, on GPS-derived total electron content by Vishal Chauhan, Vishakha, Rakesh Singh, Shishupal Singh, Vikram Singh, Om Prakash Singh

“…Atmospheric gravity waves (AGWs) are also observed by performing wavelet analysis on TEC data. The global TEC maps visualize and confirm observed TEC variations, providing spatial and temporal insights into the ionospheric response. …”
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Mechanical Properties Measurement of Polymer Films by Bulge Test and Fringe Projection by C. S. Lin, T. L. Horng, J. H. Chen, K. H. Chen, J. J. Wu, C. Y. Chen, S. H. Ma

“…A deformed image was then obtained via fringe projections with a series of optical apparatuses, and a 3D membrane deformation distribution was further achieved from this deformed image by some image processes that are chiefly through wavelet transformation and phase expansion. With the measurements of maximum membrane deformation versus applied pressure and given the Young’s modulus of test membrane, we could further calculate the Poisson ration (and then biaxial modulus) and residual stress of the film. …”
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An MR Brain Images Classifier System via Particle Swarm Optimization and Kernel Support Vector Machine by Yudong Zhang, Shuihua Wang, Genlin Ji, Zhengchao Dong

“…The proposed method first employed digital wavelet transform to extract features then used principal component analysis (PCA) to reduce the feature space. …”
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Future Changes in Drought Characteristics under Extreme Climate Change over South Korea by Joo-Heon Lee, Hyun-Han Kwon, Ho-Won Jang, Tae-Woong Kim

“…Second, this study explored the low-frequency patterns associated with drought by comparing global wavelet power, with significance test. Future spectra decreased in the fractional variance attributed to a reduction in the interannual band from 2 to 8 years. …”
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A New Double Truncated Generalized Gamma Model with Some Applications by Awad A. Bakery, Wael Zakaria, OM Kalthum S. K. Mohamed

“…Additionally, the suggested model for wavelet histogram fitting of images and sounds is very accurate.…”
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A New Bearing Fault Diagnosis Method Based on Deep Transfer Network and Supervised Joint Matching by Chengyao Liu, Fei Dong, Kunpeng Ge, Yuanyuan Tian

“…To overcome these problems, by integrating the superiority of deep learning method and feature-based transfer learning method, this work proposes an innovative cross-domain fault diagnosis framework based on deep transfer convolutional neural network and supervised joint matching. First, the continue wavelet transform is used to process original bearing vibration signals and extract time-frequency images. …”
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A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet by Muhammad Waqas Ahmed, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz Alhammadi, Asaad Algarni, Ahmad Jalal, Jeongho Cho

“…We employ Azimuthal Average Feature Extraction, Haar Wavelet Transform, and Maximally Stable Extremal Regions (MSER) to capture a rich set of features encompassing texture, frequency, and shape information. …”
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Temperature variability and its effect on seasonal yield of rice in Bangladesh: a long-term trend assessment by Md. Abdullah Al Mamun, Md. Abdur Rouf Sarkar, Mou Rani Sarker, Andrew M. McKenzie, Sheikh Arafat Islam Nihad, Md. Arafat Hossain, Akbar Hossain

“…Seasonal heat incidence highlighted that Aus rice experienced greater temperature stress compared to Aman and Boro. Wavelet coherence analysis confirmed that recent heat events significantly impacted Aus and Boro yields, with high-frequency temperature anomalies affecting Aus and Aman. …”
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Multimodal consumer choice prediction using EEG signals and eye tracking by Syed Muhammad Usman, Shehzad Khalid, Aimen Tanveer, Ali Shariq Imran, Muhammad Zubair

“…Handcrafted features, including statistical and wavelet features, and automated features from Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM), have been extracted and concatenated to generate a feature space representation. …”
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A Synchronized Hybrid Brain-Computer Interface System for Simultaneous Detection and Classification of Fusion EEG Signals by Dalin Yang, Trung-Hau Nguyen, Wan-Young Chung

“…Feature extraction is performed by the wavelet transform, which is extracted by the features in the frequency and time domains. …”
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Identifying etiologies of heart failure using non-contrast cardiac magnetic resonance imaging: cine imaging, T1 and T2 mapping, and texture analysis for T1 mapping by Yasuo Amano, Yasuyuki Suzuki, Xiaoyan Tang, Chisato Ando

“…Vertical run length nonuniformity, vertical gray level nonuniformity (vGLNU), wavelet energy LL(3) and HH (4) on T1 mapping were estimated at the mid-septal segment using open-access software. …”
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Research on a 44 Day Quasi-periodic Oscillation of Optical Bands for BL Lac S5 0716+714 by Lin Lu, Bin Sun, Zhen-Xing Fang, Meng Wan, Yunlu Gong

“…The Lomb–Scargle periodogram method and the weighted wavelet Z-transform method were used to search for a quasi-periodic oscillation (QPO) signal in the data. …”
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Stratum P- and S-Wave <italic>Q</italic> Factors Estimation via Improved Spectral Envelope Matching Method by Chao Wang

“…This method first extracts a seismic wavelet, followed by the centroid frequency shift (CFS) method to estimate formation Q values and construct an initial attenuation model. …”
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Dynamics‐Oriented Underwater Mechanoreception Interface for Simultaneous Flow and Contact Perception by Hua Zhong, Yaxi Wang, Jiahao Xu, Yu Cheng, Sicong Liu, Jia Pan, Wenping Wang, Zheng Wang

“…Therefore, by evaluating the oscillation dynamics with tailored wavelet‐based indices, DOUMI can distinguish between contact‐ and flow‐induced oscillations at each receptor unit with 90.5% accuracy. …”
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Brain Tumor Detection and Classification Using IFF-FLICM Segmentation and Optimized ELM Model by Suvashisa Dash, Mohammed Siddique, Satyasis Mishra, Demissie J. Gelmecha, Sunita Satapathy, Davinder Singh Rathee, Ram Sewak Singh

“…The IFF-FLICM algorithm is utilized to accurately segment the brain’s magnetic resonance (MR) images to identify the tumor regions. The Mexican hat wavelet transform is employed for feature extraction from the segmented images. …”
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NIGWO-iCaps NN: A Method for the Fault Diagnosis of Fiber Optic Gyroscopes Based on Capsule Neural Networks by Nan Lu, Huaqiang Zhang, Chunmei Dong, Hongtao Li, Yu Chen

“…To address these challenges, this paper proposes a new fault diagnostic model that performs a fault diagnosis of gyroscopes using the enhanced capsule neural network (iCaps NN) optimized by the improved gray wolf algorithm (NIGWO). The wavelet packet transform (WPT) is used to construct a two-dimensional feature vector matrix, and the deep feature extraction module (DFE) is added to extract deep-level information to maximize the fault features. …”
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Descriptores espacio-frecuencia para identificación automática de patrones de textura en productos textiles utilizando aprendizaje supervisado by Arley Bejarano Martínez, Andres Felipe Calvo Salcedo, Carlos Alberto Henao Baena

“…En la etapa de caracterización se utilizan descriptores como la transformada Wavelet, la transformada de Fourier y la adaptación de la Transformada corta de Fourier en espacio para la generación de un vector de características, a este vector se le computa los momentos estadísticos como Kurtosis, sesgo, media y desviación estándar. …”
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Defect Detection in Concrete Structures Based on Characteristics of Hammer Reaction Force and Apparent Stiffness of Concrete by Koki Shoda, Jun Younes Louhi Kasahara, Qi An, Atsushi Yamashita

“…To address this challenge, we propose a novel method that enhances defect discrimination accuracy by integrating statistical processing and physical property analysis within a machine learning framework designed for force signal characteristics. Our method employs wavelet transformation to convert short-duration force signals into high-resolution time-frequency features, capturing their non-stationary behavior in detail. …”
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Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT‐Based Radiomic Features in Non‐Small Cell Lung Cancer by Shrey S. Sukhadia, Christoph Sadée, Olivier Gevaert, Shivashankar H. Nagaraj

“…Results Our ML‐based radiogenomic modeling identified specific imaging features—wavelet, three‐dimensional local binary patterns, and logarithmic sigma of gray‐level variance—as predictive indicators for high (1) vs. low (0) gene expression of pivotal NSCLC‐related genes: SLC35C1, BCL2L1, and MAPK1. …”
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