A Novel Copula-Based Multi-Feature CFAR Framework for Radar Target Detection by Juan Li, Yunlong Dong, Ningbo Liu, Yong Huang, Xingyu Jiang, Jinping Sun

“…First, a Copula-CFAR theorem is established, which models the feature dependence structure and enables the derivation of closed-form expressions for probability of false alarm (PFA) and detection probability across various Copula models. …”
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Generative and predictive neural networks for the design of functional RNA molecules by Aidan T. Riley, James M. Robson, Aiganysh Ulanova, Alexander A. Green

“…We pair these predictive models with generative adversarial RNA design networks (GARDN), allowing the generative modelling of a diverse range of functional RNA molecules with targeted experimental attributes. …”
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Verification of the method for classifying the technical state of a turboshaft engine fuel regulator in the space of operational process parameters under factory test conditions by Ihor Ohanian, Sergiy Yepifanov

“…It was determined that the method demonstrates high efficiency in most operational modes; however, its accuracy depends on the degree of correlation between the diagnosed structural parameters and the precision of the mathematical model identification. Recommendations for further improvement of the method include using expert systems and developing effective model identification algorithms. …”
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Invertible networks-based method with dual-embedding and attack layer for robust audio watermarking by ZHANG Xulong, QU Xiaoyang, LI Pengcheng, XIAO Chunguang, WANG Jianzong

“…We also consider the impact of the attack layer on the invertible neural network in robustness training, improving the model to enhance both its reasonableness and stability. …”
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A Variational Bayesian Truncated Adaptive Filter for Uncertain Systems with Inequality Constraints by Tianli Ma, Rong Zhang, Song Gao, Hong Li, Yang Zhang

“…Results show that the proposed algorithms improve estimation accuracy compared with the existing adaptive filters when the states suffer inequality constraints.…”
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Invertible networks-based method with dual-embedding and attack layer for robust audio watermarking by ZHANG Xulong, QU Xiaoyang, LI Pengcheng, XIAO Chunguang, WANG Jianzong

“…We also consider the impact of the attack layer on the invertible neural network in robustness training, improving the model toenhance both its reasonableness and stability. …”
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Nondestructive estimation of leaf chlorophyll content in banana based on unmanned aerial vehicle hyperspectral images using image feature combination methods by Weiping Kong, Weiping Kong, Lingling Ma, Huichun Ye, Huichun Ye, Jingjing Wang, Chaojia Nie, Binbin Chen, Xianfeng Zhou, Wenjiang Huang, Zikun Fan

“…We proposed two methods of image feature combination for banana LCC inversion, which are a two-pair feature combination and a multivariable feature combination based on four machine learning algorithms (MLRAs).ResultsThe results indicated that compared to conventionally used VIs alone, the banana LCC estimations with both proposed VI and TF combination methods were all significantly improved. …”
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Combination of ultrasound-based radiomics and deep learning with clinical data to predict response in breast cancer patients treated with neoadjuvant chemotherapy by Wu Tenghui, Liu Xinyi, Si Ziyi, Zhang Yanting, Ma Ziqian, Zhu Yiwen, Gan Ling

“…Multiple machine learning algorithms were employed to model and validate the diagnostic performance of different types of features. …”
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MSASGCN :  Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting by Yang Cao, Detian Liu, Qizheng Yin, Fei Xue, Hengliang Tang

“…Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. …”
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Stock Price Prediction Using Machine Learning: Evidence from Pakistan Stock Exchange by Zafar Akhter, Dr. Hassan Raza

“…The report additionally proposes potential avenues for future research, such as exploring alternate data sources, employing sentiment analysis techniques, and developing more advanced algorithms. The findings of this study hold significant significance for investors and financial institutions, as they highlight the potential of machine learning in facilitating informed investment decisions and improving financial forecasts and analysis. …”
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Dynamic load balancing in cloud computing using predictive graph networks and adaptive neural scheduling by K. Rajammal, M. Chinnadurai

“…Additionally, comparative analyses with existing optimization algorithms exhibit the proposed model ability in managing the loads in cloud computing. …”
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Rapid Quality Assessment of Polygoni Multiflori Radix Based on Near-Infrared Spectroscopy by Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao

“…After optimizing the model using CARS, R2C increased by 0.15%, 0.41%, and 0.34%, RMSECV decreased by 0.53%, 0.32%, and 0.24%, R2P increased by 0.21%, 0.63%, and 0.35%, RMSEP decreased by 0.36%, 0.41%, and 0.31%, and RPD increased by 1.1, 0.9, and 0.6, significantly improving the predictive capacity of the model. …”
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Soot Mass Concentration Prediction at the GPF Inlet of GDI Engine Based on Machine Learning Methods by Zhiyuan Hu, Zeyu Liu, Jiayi Shen, Shimao Wang, Piqiang Tan

“…To improve the prediction accuracy of soot load in gasoline particulate filters (GPFs) and the control accuracy during GPF regeneration, this study developed a prediction model to predict the soot mass concentration at the GPF inlet of gasoline direct injection (GDI) engines using advanced machine learning methods. …”
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Evaluation of Modified Reflection Symmetry Decomposition Polarization Features for Sea Ice Classification by Tianlang Lan, Chengfei Jiang, Xiaofan Luo, Wentao An

“…The results show that MRSD polarization features significantly improve model performance, particularly distinguishing among sea ice categories. …”
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Prediction of induction motor faults using machine learning by Ademola Abdulkareem, Tochukwu Anyim, Olawale Popoola, John Abubakar, Agbetuyi Ayoade

“…To enhance model performance in future work, potential avenues include refining the ANN and RF models, exploring transfer learning or ensemble methods, and incorporating diverse datasets to improve generalization.…”
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SurfILE: An Open-Source Python Package for Surface Topography Analysis by Andrea Giura, Massimo Zucco, Luigi Ribotta

“…There are also freely available tools, including open-source options, that provide a variety of algorithms and methods. The rapid growth of investigations aimed at better understanding the effects of the microscale phenomena requires the improved traceable calibration of samples, the development of new methodologies and measuring techniques, and the specification of new mathematical models and processing techniques. …”
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Experimental Study on Glass Deformation Calculation Using the Holographic Interferometry Double-Exposure Method by Yucheng Li, Yang Zhang, Deyu Jia, Song Gao, Muqun Zhang

“…This approach (1) eliminates object wave amplitude interference via dual-exposure superposition, establishing submicron linear mapping between fringe displacement and deformation amplitude; (2) introduces a fringe gradient-based direction detection algorithm resolving deformation vector ambiguity; and (3) implements an error-compensated fusion framework integrating theoretical modeling, MATLAB 2015b simulations, and experimental validation. …”
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Efficiency Optimization of PMSM-Type Elevator Machine: An Industrial Comparison by Mucahit Soyaslan, Osman Eldogan, Ahmet Fenercioglu, Yusuf Avsar, Nurdogan Ceylan, Muhammed Salih Sarıkaya

“…This study presents the design, modeling, and prototyping of an external rotor permanent magnet synchronous motor (ER-PMSM) specifically for elevator traction systems. …”
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PPLA-Transformer: An Efficient Transformer for Defect Detection with Linear Attention Based on Pyramid Pooling by Xiaona Song, Yubo Tian, Haichao Liu, Lijun Wang, Jinxing Niu

“…When compared to the Swin-Transformer model on the public PKU-Market-PCB dataset, our model achieves an improvement of 1.7% mAP and 51 FPS. …”
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Early Detection of Alzheimer’s Disease: An Extensive Review of Advancements in Machine Learning Mechanisms Using an Ensemble and Deep Learning Technique by Renjith Prabhavathi Neelakandan, Ramesh Kandasamy, Balasubramani Subbiyan, Mariya Anto Bennet

“…The proposed system employs an Ensemble Classification algorithm, which integrates the outcomes of multiple predictive models to enhance diagnostic accuracy. …”
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