the Solving Partial Differential Equations by using Efficient Hybrid Transform Iterative Method by Ruaa Shawqi Ismael, Ali Al -Fayadh, Saad M. Salman

“…When used to solve KdV , Wave like and  Pseudo – Parabolic equations , the proposed method helps to avoid Problems that frequently arise when determining the Lagrange Multiplier and the difficult integration usedin the variation iteration method , as well as the need to use the transform convolution theorem. …”
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Research on Spaceborne Neural Network Accelerator and Its Fault Tolerance Design by Yingzhao Shao, Junyi Wang, Xiaodong Han, Yunsong Li, Yaolin Li, Zhanpeng Tao

“…To meet the high-reliability requirements of real-time on-orbit tasks, this paper proposes a fault-tolerant reinforcement design method for spaceborne intelligent processing algorithms based on convolutional neural networks (CNNs). This method is built on a CNN accelerator using Field-Programmable Gate Array (FPGA) technology, analyzing the impact of Single-Event Upsets (SEUs) on neural network computation. …”
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Enhanced People Re-identification in CCTV Surveillance Using Deep Learning: A Framework for Real-World Applications by Mossaab Idrissi Alami, Abderrahmane Ez-zahout, Fouzia Omary

“…In this paper, we propose a robust deep learning framework that leverages convolutional neural networks (CNNs) with a customized triplet loss function to overcome these obstacles and improve re-identification accuracy. …”
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Heat syndrome types prediction of traditional Chinese medicine in acute ischemic stroke through deep learning: a pilot study by Xiongwu Yu, Xiongwu Yu, Lingqian He, Qi Wang, Zhongyun Zhang, Zhongyun Zhang, Huaiqiu Zhu, Huaiqiu Zhu, Juexian Song

“…We developed a deep learning method with Convolutional Neural Networks (CNNs) to predict heat syndrome types in AIS patients by integrating TCM pattern characteristics and laboratory indicators. …”
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Automatic Detection and Classification of Natural Weld Defects Using Alternating Magneto-Optical Imaging and ResNet50 by Yanfeng Li, Pengyu Gao, Yongbiao Luo, Xianghan Luo, Chunmei Xu, Jiecheng Chen, Yanxi Zhang, Genxiang Lin, Wei Xu

“…These two models can be used for the classification of partial defect MO images, but the recognition accuracy for cracks and gas pores is comparatively low. …”
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A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

“…The performance of the partial least squares regression, random forest, and convolutional neural network–long short-term memory (CNN-LSTM) models was evaluated using a 10-fold cross-validation approach. …”
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Advancing irrigation uniformity monitoring through remote sensing: A deep-learning framework for identifying the source of non-uniformity by Ígor Boninsenha, Daran R. Rudnick, Everardo C. Mantovani, Higor de Q. Ribeiro

“…These images were classified into nine categories: vegetated, not vegetated, emitters, mechanical problems, low pressure, management zones, operational, partial crop, and clouds. Artificial images mimicking these patterns pre-trained a DenseNet121 convolutional neural network (CNN), addressing the challenge of limited labeled training data. …”
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Multi-Class Classification Methods for EEG Signals of Lower-Limb Rehabilitation Movements by Shuangling Ma, Zijie Situ, Xiaobo Peng, Zhangyang Li, Ying Huang

“…It systematically explored preprocessing techniques, feature extraction strategies, and multi-classification algorithms for multi-task MI-EEG signals. A novel 3D EEG convolutional neural network (3D EEG-CNN) that integrates time/frequency features is proposed. …”
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Integrated data-driven topology reconstruction and risk-aware reconfiguration for resilient power distribution systems under incomplete observability by Sipei Sun, Ning Li, Liang Zhang, Dongpo Zhao, Di Lun, Liang Feng

“…Motivated by real-world challenges where asset metadata, SCADA records, GIS layouts, and dispatcher logs are misaligned or incomplete, the proposed approach reconstructs network topology using a graph convolutional network (GCN) that fuses heterogeneous data attributes and learns structural representations from partial connectivity information. …”
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Deep learning driven methodology for the prediction of mushroom moisture content using a novel LED-based portable hyperspectral imaging system by Kai Yang, Ming Zhao, Dimitrios Argyropoulos

“…This study proposes a deep-learning driven methodology for the analysis of mushroom moisture content (MC) datasets acquired using a novel portable hyperspectral imaging (HSI) system. One-dimensional convolutional neural network (1D-CNN) was developed and validated to process the raw HSI data of white button mushrooms (Agaricus bisporus) for MC prediction. …”
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Reconfigurable and Scalable Artificial Intelligence Acceleration Hardware Architecture With RISC-V CNN Coprocessor for Real-Time Seizure Detection by Shuenn-Yuh Lee, Ming-Yueh Ku, Sing-Yu Pan, Chou-Ching Lin

“…Seizures are often accompanied by involuntary partial or whole-body convulsions, frothing at the mouth, and possible loss of consciousness, putting a patient at high risk. …”
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SOH Estimation Method for Lithium-Ion Batteries Using Partial Discharge Curves Based on CGKAN by Shengfeng He, Wenhu Qin, Zhonghua Yun, Chao Wu, Chongbin Sun

“…To address the limitations in the accuracy and robustness of existing methods under complex operating conditions, a CNN-BiGRU-KAN (CGKAN) method for SOH estimation based on partial discharge curves is proposed. Firstly, random forest analysis is applied to extract features highly correlated with battery health from the partial discharge curve data. …”
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Deep Learning Berbasis CNN Untuk Pengenalan Pola Partial Discharge Isolasi Silicone Rubber by Ferlian Seftianto, Sukemi Sukemi, Zainuddin Nawawi

“… Partial discharge (PD) activity measurements have been carried out by selecting noise signals (de-noising) using Support Vector Machine (SVM)and then recognized using Convolutional Neural Network (CNN). …”
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Data augmentation-assisted deep learning of hand-drawn partially colored sketches for visual search. by Jamil Ahmad, Khan Muhammad, Sung Wook Baik

“…To cope with these issues, we propose to fine-tune a deep convolutional neural network (CNN) using augmented dataset to extract features from partially colored hand-drawn sketches for query specification in a sketch-based image retrieval framework. …”
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AI-Driven Innovation Using Multimodal and Personalized Adaptive Education for Students With Special Needs by Nesren Farhah, Muhammad Adnan, Ahmed Abdullah Alqarni, M. Irfan Uddin, Theyazn H. H. Aldhyani

“…This study provides an in-depth exploration of the use of multimodal techniques in developing adaptive learning systems designed for students with special needs using various neural network models: a Baseline Neural Network, Convolutional Neural Network, Attention Model, LSTM, GRU, and Transformer models. …”
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A small‐target traffic sign detection algorithm based on partial conv and atrous spatial pyramid by Yuqi Li, Zijian Wang, Han Zhang, Xinpeng Yao, Zhou Zhou, Xin Cheng

“…First, to improve the feature extraction module of the backbone network and to increase the model's ability to capture contextual information, partial convolution (PConv) is introduced. Second, to prevent information loss during the downsampling process, a cross‐stage atrous spatial pyramid (ASPPFCSPC) is constructed using atrous convolution. …”
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Machine learning to predict killer whale (Orcinus orca) behaviors using partially labeled vocalization data by Sophia Sandholm

“…Despite that, with a careful combination of recent machine learning techniques, including a ResNet-34 convolutional neural network and a custom loss function designed for partially labeled learning, a 96.1% general behavior label classification accuracy on previously unheard segments is achieved. …”
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation. by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

“…This study proposes a novel method for the automated diagnosis of partial sleep deprivation utilizing electroencephalogram (EEG) signals.…”
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Design of a Portable Biofeedback System for Monitoring Femoral Load During Partial Weight-Bearing Walking by Tao Ma, Tianyang Fan, Xun Xu, Tao Sun

“…Patients with femoral fractures are typically advised to undergo partial weight-bearing (PWB) gait training during the postoperative rehabilitation period to facilitate bone healing and restore lower limb function. …”
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High‐Fidelity Information Transmission Through the Turbulent Atmosphere Utilizing Partially Coherent Cylindrical Vector Beams by Linxuan Yao, Hui Zhang, Yangsheng Yuan, Yaru Gao, Chunhao Liang, Sergey A. Ponomarenko, Yangjian Cai

“…This protocol combines the advantages of reducing the spatial coherence of light at the source with the capabilities of convolutional neural networks at the receiver to encode and transmit optical images through a noisy link. …”
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