Computing the UV-finite electromagnetic corrections to the hadronic vacuum polarization in the muon (g − 2) from lattice QCD by Julian Parrino, Volodymyr Biloshytskyi, En-Hung Chao, Harvey B. Meyer, Vladimir Pascalutsa

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Application Value of an AI-based Imaging Feature Parameter Model 
for Predicting the Malignancy of Part-solid Pulmonary Nodule by Mingzhi LIN, Yiming HUI, Bin LI, Peilin ZHAO, Zhizhong ZHENG, Zhuowen YANG, Zhipeng SU, Yuqi MENG, Tieniu SONG

“…All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. …”
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Rationalised experiment design for parameter estimation with sensitivity clustering by Harsh Chhajer, Rahul Roy

“…Using two kinetic model systems with distinct dynamical features, we show that PARSEC-based experiments improve the parameter estimation of a complex system. …”
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Channel computation based on multi-scale attention residual network by Wengang Li, Deli Zhou, Qiong Ye

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Similarity and wavelet transform based data partitioning and parameter learning for fuzzy neural network by Pramoda Patro, Krishna Kumar, G. Suresh Kumar, Gandharba Swain

“…Neurons weight and bias values are computed by adapting wavelet functions. Finally, parameters of the fuzzy neural networks are fine-tuned using the hybrid ant colony particle swarm optimization (HASO). …”
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Copula Approximate Bayesian Computation Using Distribution Random Forests by George Karabatsos

“…This <i>Stats</i> invited feature article introduces and provides an extensive simulation study of a new approximate Bayesian computation (ABC) framework for estimating the posterior distribution and the maximum likelihood estimate (MLE) of the parameters of models defined by intractable likelihoods, that unifies and extends previous ABC methods proposed separately. …”
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Matrix computation over homomorphic plaintext-ciphertext and its application by Yang LIU, Linhan YANG, Jingwei CHEN, Wenyuan WU, Yong FENG

“…Those homomorphic encryption schemes supporting single instruction multiple data (SIMD) operations effectively enhance the amortized efficiency of ciphertext computations, yet the structure of ciphertexts leads to high complexity in matrix operations.In many applications, employing plaintext-ciphertext matrix operations can achieve privacy-preserving computing.Based on this, a plaintext-ciphertext matrix multiplication scheme for matrices of arbitrary dimension was proposed.The resulting ciphertext was computed through steps such as encoding the plaintext matrix, transforming the dimensions of the encrypted matrix, etc.Compared to the best-known encrypted matrix multiplication algorithm for square matrices proposed by Jiang et al., the proposed scheme supported matrix multiplication of arbitrary dimension, and consecutive matrix multiplications.Both theoretical analysis and experimental results show that the proposed scheme requires less rotations on ciphertexts and hence features higher efficiency.When applied to a privacy-preserving Bayesian classifier, the proposed scheme can complete classification tasks with higher security parameters and reduced running time.…”
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CONE-BEAM COMPUTED TOMOGRAPHY IN PALEOANTHROPOLOGY by A. Yu. Vasil’ev, A. P. Buzhilova, E. A. Egorova, D. V. Makarova, N. Ya. Berezina, I. S. Zorina, V. I. Khartanovich

“…Objective: to study the capabilities of cone-bean computed tomography (CBCT) in estimating the bone structure when analyzing anthropological findings.Material and methods. …”
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Evaluating the value of machine learning models for predicting hematoma expansion in acute spontaneous intracerebral hemorrhage based on CT imaging features of hematomas and surrou... by Tianyu Yang, Tianyu Yang, Zhen Zhao, Yan Gu, Shengkai Yang, Yonggang Zhang, Lei Li, Ting Wang, Zhongchang Miao

“…Model performance was evaluated using receiver operating characteristic (ROC) curves and the area under the curve (AUC).ResultsEight feature parameters were extracted from the CT images. …”
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A Flow Shop Scheduling Method Based on Dual BP Neural Networks with Multi-Layer Topology Feature Parameters by Hui Mu, Zinuo Wang, Jiaqi Chen, Guoqiang Zhang, Shaocun Wang, Fuqiang Zhang

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3D convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery EEG signal by Xiaoguang Li, Xiaoguang Li, Yaqi Chu, Xuejian Wu

“…Next, the paper designs a 3DCNN network with 1D and 2D convolutional layers in series to optimize the convolutional kernel parameters and effectively learn the spatial-frequency features of the EEG. …”
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Multi-scale feature fusion and feature calibration with edge information enhancement for remote sensing object detection by Lihua Yang, Yi Gu, Hao Feng

“…Abstract Vision Transformer-based detectors have achieved remarkable success in the field of object detection, but the application of these models to high-resolution remote sensing imagery faces challenges in computational costs and performance bottlenecks due to the increased computational complexity required to process high-resolution imagery, especially when capturing fine-grained edge features. …”
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Adolescents’ Digital activity and its Correlation with Cognitive-Emotional Features, School Performance, and Social and Age Factors: Cross-Sectional Study by George A. Karkashadze, Natalia E. Sergeeva, Leyla S. Namazova-Baranova, Elena A. Vishneva, Elena V. Kaytukova, Kamilla E. Efendieva, Tinatin Yu. Gogberashvili, Dmitriy S. Kratko, Safarbegim Kh. Sadilloeva, Marina A. Kurakina, Anastasiya I. Rykunova, Tatiana A. Konstantinidi, Nadezhda A. Ulkina, Daria A. Bushueva, Inessa A. Povalyeva, Leonid M. Yatsyk, Tatiana A. Salimgareeva, Yuliya V. Nesterova, Pavel A. Prudnikov, Natalia S. Sergienko, Margarita A. Soloshenko, Nikita S. Shilko, Yuliya E. Kazantzeva

“…The study of digital activity correlation with cognitive-emotional features, as well as with other parameters of adolescents’ life-activity in non-capital regions of Russian Federation remains relevant.Objective. …”
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MapSAM: adapting segment anything model for automated feature detection in historical maps by Xue Xia, Daiwei Zhang, Wenxuan Song, Wei Huang, Lorenz Hurni

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Early stroke behavior detection based on improved video masked autoencoders for potential patients by Meng Wang, Guanci Yang, Kexin Luo, Yang Li, Ling He

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DOA Estimation by Feature Extraction Based on Parallel Deep Neural Networks and MRMR Feature Selection Algorithm by Ashwaq Neaman Hassan Al-Tameemi, Mahmood Mohassel Feghhi, Behzad Mozaffari Tazehkand

“…The results by computer simulations on a uniform linear array show that the proposed structure significantly increases the accuracy of DOA estimation and is more robust to changes in input parameters than traditional algorithms, such as estimation of signal parameters via invariant rotation (ESPRIT), classification of multiple signals (MUSIC), and DNN method. …”
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Features of distillation separation of multicomponent mixtures by A. K. Frolkova, A. V. Frolkova, V. M. Raeva, V. I. Zhuchkov

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Apple Pest and Disease Detection Network with Partial Multi-Scale Feature Extraction and Efficient Hierarchical Feature Fusion by Weihao Bao, Fuquan Zhang

“…Furthermore, the model exhibits favorable lightweight characteristics in terms of computational complexity and parameter count, underscoring its effectiveness and robustness in practical applications. …”
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Multi-Domain Feature Incorporation of Lightweight Convolutional Neural Networks and Handcrafted Features for Lung and Colon Cancer Diagnosis by Omneya Attallah

“…This study presents a computer-aided diagnostic (CAD) framework that integrates multi-domain features through a hybrid methodology. …”
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Investigating the Effects of Spectroscopic Method in Estimating Soluble Solid Content Values and Firmness of Cherries from an Environmental Point of View: Prediction of Environment... by Shirzad Naim, Shahgholi Gholamhossein, Ardabili Sina, Szymanek Mariusz

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