Hybrid Laminar Flow Control Optimizations for Infinite Swept Wings by Yayun Shi, Xiayu Lan, Tihao Yang

“…The Reynolds-averaged Navier-Stokes (RANS) solver coupled with the linear stability theory is applied for the laminar-turbulent transition prediction, and the traditional optimization method based on evolutionary algorithms is applied for laminar flow wing optimization. …”
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A multimodal MRI-based machine learning framework for classifying cognitive impairment in cerebral small vessel disease by Guihan Lin, Weiyue Chen, Yongkang Geng, Bo Peng, Surui Liu, Minjiang Chen, Chunying Pang, Pengjun Chen, Chenying Lu, Zhihan Yan, Shuiwei Xia, Yakang Dai, Jiansong Ji

“…Our study provides a multimodal MRI-based machine learning framework, utilizing the AutoGluon platform, that outperforms traditional algorithms in classifying MCI and NCI, offering a promising tool for the early prediction of MCI in CSVD.…”
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Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

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GRRIS: A Real-time Intrasite Observation Scheduling Scheme for Distributed Survey Telescope Arrays by Yajie Zhang, Ce Yu, Chao Sun, Yi Hu, Zhaohui Shang, Jizeng Wei, Xu Yang

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Forecasting Surface Velocity Fields Associated With Laboratory Seismic Cycles Using Deep Learning by G. Mastella, F. Corbi, J. Bedford, F. Funiciello, M. Rosenau

“…Using data from two types of experiments, we explore the prediction performances of multiple Deep Learning (DL) and ML algorithms. …”
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A Hybrid Approach to Call Admission Control in 5G Networks by Mohammed Al-Maitah, Olena O. Semenova, Andriy O. Semenov, Pavel I. Kulakov, Volodymyr Yu. Kucheruk

“…Such artificial intelligence techniques as neural networks, fuzzy systems, and genetic and evolutionary algorithms are widely used for communication systems management, optimization, and prediction. …”
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Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease by Salvatore Falciglia, Laura Caffi, Claudio Baiata, Chiara Palmisano, Ioannis Ugo Isaias, Alberto Mazzoni

“…Our study paves the way for remote monitoring strategies and the implementation of new algorithms for personalized auto-tuning aDBS devices.…”
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Comprehensive assessment on estimating the thermodynamic and mechanical properties of multicomponent Fe–Cr-based alloys using machine learning techniques by Ahed Habib, Bashar Alibrahim, Mahdi Z. Alnunu, Hussein Moussa, Maan Habib

“…This study investigates the performance of 11 different machine learning algorithms to predict the mixing enthalpy, Young’s modulus, and the shear-to-bulk modulus ratio of Fe–Cr alloys with additions of Ni, Mo, Al, W, V, and Nb. …”
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Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

“…These models are commonly used to predict outputs based on a combination of fixed parameters and adjustable variables. …”
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Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…Using deep learning algorithms to establish prediction models for sensor data is an effective approach; however, the performance of these models is significantly influenced by the quantity and quality of the training data. …”
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Are treatment plans optimized on the basis of acuros XB dose calculation robust against anatomic changes during online adaptive radiotherapy for lung cancer regarding dose homogene... by Khouya Aymane, Santiago Alina, Ringbaek Toke, Guberina Nika, Guberina Maja, Gauler Thomas, Lübcke Wolfgang, Zylka Waldemar, Pöttgen Christoph, Stuschke Martin

“…Abstract Introduction The Acuros XB dose calculation algorithm implements advanced modelling of lateral electron transport, making dose distributions sensitive to density changes between source and subsequent CT. …”
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Research on Monitoring Nitrogen Content of Soybean Based on Hyperspectral Imagery by Yakun Zhang, Mengxin Guan, Libo Wang, Xiahua Cui, Yafei Wang, Peng Li, Shaukat Ali, Fu Zhang

“…Three spectral characteristic variables selection methods, including correlation coefficient analysis, stepwise regression, and spectral index analysis, were used to determine the spectral characteristic variables that are closely related to the soybean canopy nitrogen content. The predictive models for soybean canopy nitrogen content based on spectral characteristic variables were established using a multiple linear regression algorithm. …”
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Identification of biomarkers for Laryngeal squamous cell carcinoma through Mendelian randomization and integrated bioinformatics analysis by Pengjian Zhang, Weizhang Chen, Kai Chen, Yuanhang Ye, Weijun Wu

“…The differences in immune landscapes between high-risk and low-risk groups were assessed using the CIBERSORT algorithm, and drug sensitivity was analyzed using the “oncoPredict” package. …”
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Building occupancy type classification and uncertainty estimation using machine learning and open data by Tom Narock, J. Michael Johnson, Justin Singh-Mohudpur, Arash Modaresi Rad

“…Multiple ML algorithms are compared. We address strategies to handle significant class imbalance and introduce Bayesian neural networks to handle prediction uncertainty. …”
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Scientists yet to consider spatial correlation in assessing uncertainty of spatial averages and totals by Alexandre M.J.-C. Wadoux, Gerard B.M. Heuvelink

“…The remote sensing data typically serve as covariates to deliver spatially explicit information using machine learning algorithms. Often the uncertainty associated with the maps is also quantified, for instance by prediction error variance maps or by maps of the lower and upper limits of a prediction interval. …”
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A Nighttime Driving-Scene Segmentation Method Based on Light-Enhanced Network by Lihua Bi, Wenjiao Zhang, Xiangfei Zhang, Canlin Li

“…Subsequently, the output of the light enhancement network is input into the segmentation network to obtain the final segmentation prediction. Experimental results show that the proposed method achieves mean Intersection over Union (mIoU) values of 59.4% on the Dark Zurich-test dataset, outperforming other segmentation algorithms for nighttime driving-scenes.…”
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Comprehensive Analysis of Phenotypic Traits in Chinese Cabbage Using 3D Point Cloud Technology by Chongchong Yang, Lei Sun, Jun Zhang, Xiaofei Fan, Dongfang Zhang, Tianyi Ren, Minggeng Liu, Zhiming Zhang, Wei Ma

“…By using multi-view image sequences and structure-from-motion algorithms, 3D point clouds of 50 plants from each of the 17 Chinese cabbage varieties were reconstructed. …”
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LSTM-MM: Efficient LSTM-Based Mobility Management for Power Inspection Vehicles in Smart Grids by Xiaoyan Wang, Xianfeng Xie, Shengnan Zhao

“…This scheme leverages Software-Defined Networking (SDN) technology to centrally manage vehicle communication and network traffic, integrating trajectory prediction algorithms to forecast the future movements of power inspection vehicles, optimizing route planning, and improving operational efficiency and network performance. …”
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Bounds on the initial macroporosity of sea ice pressure ridges by Sönke Maus

“…The proposed macroporosity prediction can be useful for modeling the consolidation and property evolution of sea ice ridges and rubble fields and for improving thickness redistribution algorithms in sea ice models.…”
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Inertial Subrange Optimization in Eddy Dissipation Rate Estimation and Aircraft-Dependent Bumpiness Estimation by Zhenxing Gao, Qilin Zhang, Kai Qi

“…In current vertical wind-based eddy dissipation rate (EDR) estimation algorithms based on flight data, the inertial subrange is determined empirically. …”
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