Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…The proposed model demonstrated several advantages over conventional approaches: 1) Enhanced accuracy and relevance: The model ensured highly accurate and practically applicable results by carefully defining fitting parameters and incorporating engineering constraints. 2) Robust theoretical foundation: It was grounded in established mathematical theory and principles of fluid mechanics. 3) Practicality and efficiency: The model featured low implementation costs and high computational efficiency, presenting a viable and promising alternative for field evaluations. …”
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Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

“…Firstly, a mechanical model is established, and the parameters involved are analyzed to extract suitable parameters as inputs to the network to reduce the feature loss of the network inputs. …”
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A software pipeline for systematizing machine learning of speech data by Jimuel Celeste, Mashrura Tasnim, Amable J. Valdés Cuervo, Enrique A. de la Cal, Eleni Stroulia

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Optimal feedback control of dynamical systems via value-function approximation by Kunisch, Karl, Walter, Daniel

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Information Security and Artificial Intelligence–Assisted Diagnosis in an Internet of Medical Thing System (IoMTS) by Pi-Yun Chen, Yu-Cheng Cheng, Zi-Heng Zhong, Feng-Zhou Zhang, Neng-Sheng Pai, Chien-Ming Li, Chia-Hung Lin

“…Recently, artificial intelligence (AI)- based methods are being increasingly applied to preprocess digital data and extract features. The key physiological parameters and feature patterns can then be incorporated into AI- based tools to help monitor, detect, and diagnose applications. …”
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Deep CNN ResNet-18 based model with attention and transfer learning for Alzheimer's disease detection by Sofia Biju Francis, Sofia Biju Francis, Jai Prakash Verma

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逆向法选择渐开线齿轮的变位系数 by 赵振江

“…A new kind of method for the choice of gear modification coefficients is presented.Its main idea is regard gear modification coefficient as a known parameter.The method take full advantage of a computer’s features of quick operation and accurate calculation and judgement function.A computer can find modification coefficients from a lots of modification coefficients which meet the needs of given condition,in the same time user needs input all kinds of given parameters and limited conditions only.…”
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Research on Breast Cancer Detection Methods Based on ODMV-MulDyHead-YOLO by Yanhong Zhang, Pei Li, Yihua Lan, Xiao Jia, Yingjie Lv

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Skin cancer detection using dermoscopic images with convolutional neural network by Khadija Nawaz, Atika Zanib, Iqra Shabir, Jianqiang Li, Yu Wang, Tariq Mahmood, Amjad Rehman

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Transmuted exponential-compound Weibull distribution for modelling of positively skewed data by Nnaemeka Martin Eze, Waheed Babatunde Yahya

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RLita: A Region-Level Image–Text Alignment Method for Remote Sensing Foundation Model by Qiang Zhang, Decheng Wang, Xiao Yu

“…Specifically, a region-level image–text alignment optimization method is proposed to represent the features of images and texts as visual and sematic representation vectors in one embedding space for better model generalization, and a parameter-efficient tuning strategy is designed to reduce computational resources. …”
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Sea Surface Height Inversion Model Based on Multimodal Deep Learning for the Fusion of Heterogeneous FY-3E GNSS-R Data by Yun Zhang, Ganyao Qin, Shuhu Yang, Yanling Han, Zhonghua Hong

“…Traditional physical altimetry methods based on delay–Doppler mapping (DDM) are subject to errors that are difficult to correct computationally. The current deep-learning-based SSH inversion techniques primarily relying on single-modal data are unable to fully leverage the rich feature information from global navigation satellite system reflectometry (GNSS-R) remote sensing data, therefore limiting the potential accuracy improvement. …”
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Comprehensive Eye Diagram Analysis: A Transfer Learning Approach by Danshi Wang, Yilan Xu, Jianqiang Li, Min Zhang, Jin Li, Jun Qin, Cheng Ju, Zhiguo Zhang, Xue Chen

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Data-driven insights into groundwater quality: machine and deep learning approaches by Gift Mbuzi, Abdur Rashid Sangi, Baha Ihnaini, Anil Carie, Sruthi Sivarajan, Satish Anamalamudi

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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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Characteristics of CoVID-19 in children: the first experience in the hospital of st. Petersburg by E. A. Dondurey, L. N. Isankina, O. I. Afanasyeva, A. V. Titeva, T. V. Vishnevskaya, V. A. Kondrat`ev, I. A. Gryaznova, M. V. Berezina, M. A. Zolotova, V. M. Volzhanin

“…Objective: to identify the clinical, laboratory and epidemiological features of the new coronavirus (CV) infection in the provision of specialized medical care to children in the megalopolis of the Russian Federation. …”
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Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids by Amir Hossein Poursaeed, Farhad Namdari

“…The model uses a combination of deep learning and quantum computing techniques to extract features and improve accuracy. …”
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Overcoming Class Imbalance in Incremental Learning Using an Elastic Weight Consolidation-Assisted Common Encoder Approach by Engin Baysal, Cüneyt Bayılmış

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Particle motion and QPOs around Euler-Heisenberg black hole immersed in cold dark matter halo by G. Mustafa, S.K. Maurya, Tayyab Naseer, Arzu Cilli, Ertan Güdekli, Assmaa Abd-Elmonem, Neissrien Alhubieshi

“…We explore the motion of particles in the vicinity of an Euler-Heisenberg black hole immersed in a cold dark matter halo, focusing on how the black hole parameters influence particle dynamics. This black hole solution is characterized by five parameters, namely, the black hole mass M, the feature radius R, the parameter ρ describing the density of the cold dark matter halo, the quantum electrodynamics parameter α, and the black hole charge Q. …”
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MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism by Yuanqi Chen, Aiping Wang, Ziyang Liu, Jie Yue, Enxu Zhang, Fei Li, Ning Zhang

“…This study introduces MoSViT, an innovative classification model leveraging advanced machine learning and computer vision technologies. Built on the MobileViT V2 framework, MoSViT integrates the CLA focus mechanism, DRB module, MoSViT Block, and the LeakyRelu6 activation function to enhance feature extraction accuracy while reducing computational complexity. …”
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