Model-Free Adaptive Iterative Learning Control of High-Order Pseudo Partial Derivatives for Nonlinear Systems by Wei Cao, Ting Wang, Jinjie Qiao, Buning Chai

“…The idea of compressive mapping was used to illustrate the provided algorithm’s convergence, and the conditions required for its convergence were given. …”
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An Enhanced Approach for Remaining Useful Life Prediction of Bearings Using Incomplete Lifecycle Data by Xunmeng An, Chao Zhang, Caiye Liu, Wentao Zhao

“…To further improve prediction accuracy, we employ a channel-independent transformer network, while RUL estimation is accomplished by integrating multi-source features through a multi-layer perceptron (MLP) layer. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…The proposed adaptive approach is model-free and eliminates the need for subsystem models, iterative algorithms, and extensive calibration procedures. Furthermore, the time-consuming and inaccurate estimation of soot emissions upstream of the DPF is avoided. …”
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Damage Recognition of Road Auxiliary Facilities Based on Deep Convolution Network for Segmentation and Image Region Correction by Yuanshuai Dong, Yanhong Zhang, Yun Hou, Xinlong Tong, Qingquan Wu, Zuofeng Zhou, Yuxuan Cao

“…In anti-glare panel area, on the largest outer polygon estimated by the convex hull algorithm, the optimal outer quadrilateral is determined according to the distance between the vertices, and then, the anti-glare panel area correction is completed by affine transformation and finally through the image one-dimensional projection mapping and adjacent shading. …”
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Strategic forecasting of renewable energy production for sustainable electricity supply: A machine learning approach considering environmental, economic, and oil factors in Türkiye... by Yasemin Ayaz Atalan, Hasan Şahin, Abdulkadir Keskin, Abdulkadir Atalan

“…For this purpose, well-known Machine Learning (ML) algorithms such as Random Forest (RF), Adaptive Boosting (AB), and Gradient Boosting (GB) were utilized. …”
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Automated Detection of High Frequency Oscillations in Intracranial EEG Using the Combination of Short-Time Energy and Convolutional Neural Networks by Dakun Lai, Xinyue Zhang, Kefei Ma, Zichu Chen, Wenjing Chen, Heng Zhang, Han Yuan, Lei Ding

“…A new methodology is presented in this paper for the automated detection of HFOs based on their 2D time–frequency map employing the short-time energy (STE) estimation and the convolutional neural network (CNN) classification algorithm. …”
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Substation Modelling and Network Security Monitoring Based on Scene Replication Technology by Xiaohu WANG, Guangxin Guo, Jiahan DONG, Lei WANG, Can CAO

“…The proposed algorithm can minimize the fitting error between the model and the original point cloud, so that the three-dimensional model of the power equipment objects can be obtained quickly, and the intelligent understanding and high quality reconstruction of the large scene of transmission and transformation can be realized finally. …”
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Indoor Dynamic Environment Mapping Based on Semantic Fusion and Hierarchical Filtering by Yiming Li, Luying Na, Xianpu Liang, Qi An

“…Subsequently, a multi-resolution semantic octree map is built using a recursive spatial partitioning algorithm. Finally, point cloud poses are corrected via Transform Frame (TF) transformation, and a 2D traversability grid map is generated using passthrough filtering and grid projection. …”
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Three-Dimensional Pulsed-Laser Imaging via Compressed Sensing Reconstruction Based on Proximal Momentum-Gradient Descent by Han Gao, Guifeng Zhang, Min Huang, Yanbing Xu, Yucheng Zheng, Shuai Yuan, Huan Li

“…Additionally, noise level estimation with the fast Johnson–Lindenstrauss transform is adopted, enabling the integration of a denoising neural network into PMGD to further enhance reconstruction accuracy. …”
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Digital Repeat Photography Application for Flowering Stage Classification of Selected Woody Plants by Monika A. Różańska, Kamila M. Harenda, Damian Józefczyk, Tomasz Wojciechowski, Bogdan H. Chojnicki

“…The training data were subjected to various transformations to achieve the best classifications using the weighted <i>k</i>-nearest neighbors algorithm. …”
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Light positioning: A high-accuracy visible light indoor positioning system based on attitude identification and propagation model by Qu Wang, Haiyong Luo, Aidong Men, Fang Zhao, Xile Gao, Jie Wei, Yuexia Zhang, Yan Huang

“…The system can accurately identify the attitude of a smartphone using its integrated sensors, distinguish different light emitting diode beacons using the fast Fourier transform algorithm, construct a position cost-function based on a visible light radiative decay model, and apply a nonlinear optimizing method to acquire the optimal estimation of final location. …”
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Small Defects Detection of Galvanized Strip Steel via Schatten-<i>p</i> Norm-Based Low-Rank Tensor Decomposition by Shiyang Zhou, Xuguo Yan, Huaiguang Liu, Caiyun Gong

“…Firstly, the original defect images are transformed into a new patch-based tensor mode through data reconstruction for mining valuable information of the defect image. …”
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Crop yield prediction in agriculture: A comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability by Md. Abu Jabed, Masrah Azrifah Azmi Murad

“…The findings of this study shed light on the transformative potential of advanced AI techniques in improving crop yield estimation accuracy, ultimately enhancing agricultural planning and resource management. …”
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Density Profiles of TNG 300 Voids across Cosmic Time by Olivia Curtis, Bryanne McDonough, Tereasa G. Brainerd

“…Using the comoving galaxy fields, voids were identified via a well-tested, watershed transformation-based algorithm. Voids were defined to be underdense regions that are unlikely to have arisen from Poisson noise, resulting in the selection of ∼100–200 of the largest underdense regions in each snapshot. …”
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Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining by Muhammad Shariq Shaikh, Sibtain Ahmed, Saba Farrukh, Shahnawaz Bayunus

“…RIs were computed using an indirect KOSMIC algorithm, which assumes non-pathologic samples follow a Gaussian distribution after Box-Cox transformation. …”
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Automated Scan-vs-BIM Registration Using Columns Segmented by Deep Learning for Construction Progress Monitoring by G. Z. Tsige, B. S. A. Alsadik, S. Oude Elberink, M. Bassier

“…</p> <p>In this work, we propose an automatic coarse registration method that is motivated by the Random Sample Consensus (RANSAC) algorithm to estimate the transformation parameters that best align the as-built point cloud in the coordinate frame of the BIM model by matching the corresponding columns. …”
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Water depth inversion based on ICESat-2 and Sentinel-2—A case study of Qiagui Co and Ayakekumu Lake on the Tibetan Plateau by Baojin Qiao, Tianjiao Du, Jianting Ju, Liping Zhu

“…An improved OPTICS denoising algorithm was applied to extract lake water depths from the ICESat-2 data. …”
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Superwideband Bandwidth Extension Using Normalized MDCT Coefficients for Scalable Speech and Audio Coding by Young Han Lee, Seung Ho Choi

“…A bandwidth extension (BWE) algorithm from wideband to superwideband (SWB) is proposed for a scalable speech/audio codec that uses modified discrete cosine transform (MDCT) coefficients as spectral parameters. …”
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Advanced Necklace for Real-Time PPG Monitoring in Drivers by Anna Lo Grasso, Pamela Zontone, Roberto Rinaldo, Antonio Affanni

“…To evaluate the sensor’s performance, two algorithms for estimating the HR from PPG signals are implemented in a microcontroller: a modified version of the mountaineer’s algorithm and a sliding discrete Fourier transform. …”
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Robust Real-Time Cancer Tracking via Dual-Panel X-Ray Images for Precision Radiotherapy by Jing Wang, Jingjing Dai, Na Li, Chulong Zhang, Jiankai Zhang, Zuledesi Silayi, Haodi Wu, Yaoqing Xie, Xiaokun Liang, Huailing Zhang

“…It incorporates three key components: (1) a sophisticated data augmentation technique combining a hybrid deformable model with 3D thin-plate spline transformation, (2) a state-of-the-art Transformer-based segmentation network for precise tumor boundary delineation, and (3) a CNN regression network for accurate 3D tumor position estimation. …”
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