Supply chain management and optimization in transportation logistics by Saoussen Krichen

“…These problems are known as vehicle routing problems and have a fundamental economic importance in the field of distribution and customers’ satisfaction. …”
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A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…Furthermore, as the extrapolation time increases, the smoothing effect inherent to convolution operations leads to increasingly blurred predictions. To address the algorithmic limitations of deep learning-based echo extrapolation models, this study introduces three major improvements: (1) A Deep Convolutional Generative Adversarial Network (DCGAN) is integrated into the ConvLSTM-based extrapolation model to construct a DCGAN-enhanced architecture, significantly improving the quality of radar echo extrapolation; (2) Considering that the evolution of radar echoes is closely related to the surrounding meteorological environment, the study incorporates specific physical variable products from the initial zero-hour field of RMAPS-NOW (the Rapid-update Multiscale Analysis and Prediction System—NOWcasting subsystem), developed by the Institute of Urban Meteorology, China. …”
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Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review by Yinglin Guo, Ning Li, Chonghui Song, Juan Yang, Yinglan Quan, Hongjiang Zhang

“…Radiomics, an emerging field, focuses on extracting high-dimensional quantitative features from medical imaging data and utilizing them to construct predictive models for disease diagnosis, prognosis, and treatment evaluation. …”
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Precise prediction of choke oil rate in critical flow condition via surface data by Qing Wang, Muntadher Abed Hussein, Bhavesh Kanabar, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Mohammad Mahtab Alam, Hojjat Abbasi

“…The k-fold cross-validation technique is utilized in every algorithm to mitigate the overfitting problem during the training of models. …”
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Source reconstruction via deposition measurements of an undeclared radiological atmospheric release by S. Van Leuven, S. Van Leuven, S. Van Leuven, P. De Meutter, P. De Meutter, J. Camps, P. Termonia, P. Termonia, A. Delcloo, A. Delcloo

“…<p>Inverse modelling of atmospheric releases of radioactivity consists of reconstructing the release source by combining radiological field measurements with atmospheric transport calculations. …”
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Problems of optimizing the energy consumption of households in the tasks of improving the energy efficiency of the housing sector by G. G. Grebenuk, S. M. Nikishov, A. A. Krygin, L. A. Sereda

“…A number of  algorithms for determining some input indicators that are easy to use in households have also been proposed. …”
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Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows by Feng Liu, Haipeng Li, Guangyuan Zou, Junlun Li

“…Abstract Full waveform inversion (FWI) is able to construct high‐resolution subsurface models by iteratively minimizing discrepancies between observed and simulated seismic data. …”
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Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…The optical time domain reflectometer (OTDR) curve features of communication fibers exhibit subtle differences among their normal, subhealthy, and faulty operating states, making it challenging for existing machine learning-based fault diagnosis algorithms to extract these minute features. In addition, the OTDR curve field fault data are scarce, and data-driven deep neural network that needs a lot of data training cannot meet the requirements. …”
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Review and prospect of floating car data research in transportation by Chi Zhang, Yuming Zhou, Min Zhang, Bo Wang, Yuhan Nie

“…Future research could focus on leveraging transformer and graph neural networks to explore spatiotemporal features of data, developing lightweight real-time FCD processing algorithms, and constructing multimodal refined models tailored to specific traffic scenarios.…”
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Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder by Shubham Chaudhry, Azzedine Abdedou, Azzeddine Soulaïmani

“…The proposed models offer a robust framework for future research and applications in the field of additive manufacturing, providing high precision and efficiency.…”
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Classification of the Condition of Cancer Patients Receiving Home Health Care with Machine Learning Methods by Mürsel Kahveci

“…We thought that the use of machine learning in the field of cancer treatment and patient care could contribute to better patient outcomes and increased quality of life. …”
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Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis by Chao Tan, Hao Liu, Zhen Zhang, Xinyu Liu, Yinquan Ai, Xiumin Wu, Enlin Jian, Yongyan Song, Jin Yang

“…The field is characterized by strong interdisciplinary convergence, involving computer science, molecular biology, and clinical research. …”
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Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…Multi-feature-based maritime radar target detection algorithms often rely on statistical models to accurately characterize sea clutter variations. …”
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Novel Spatio-Temporal Joint Learning-Based Intelligent Hollowing Detection in Dams for Low-Data Infrared Images by Lili Zhang, Zihan Jin, Yibo Wang, Ziyi Wang, Zeyu Duan, Taoran Qi, Rui Shi

“…Hence, we proposed an innovative, non-destructive infrared inspection method via constructed dataset and proposed deep learning algorithms. …”
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Analysis of a Four-Legged Robot Kinematics during Rotational Movements of Its Body by M. J. Fernando, G. R. Saypulaev, M. R. Saypulaev

“…To provide high precision in controlling their movement, it is required to develop mathematical models and algorithms for planning the robot movement along various trajectories. …”
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The Need for High-Fidelity Robotics Sensor Models by Phillip J. Durst, Christopher Goodin, Burhman Q. Gates, Christopher L. Cummins, Burney McKinley, Jody D. Priddy, Peter Rander, Brett Browning

“…Simulations provide a safe, controlled setting for testing and are therefore ideal for rapidly developing and testing autonomous mobile robot behaviors. However, algorithms for mobile robots are notorious for transitioning poorly from simulations to fielded platforms. …”
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Combining Local Electromagnetic Scattering and Global Structure Features for SAR Open Set Recognition by Qinjie Lin, Hao Sun, Yanjie Xu, Junyu Wang, Kefeng Ji, Gangyao Kuang

“…However, existing SAR ATR primarily rely on algorithms from the field of computer vision, many methods have not adequately considered the imaging sensitivity of SAR images. …”
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Research on Concrete Crack and Depression Detection Method Based on Multi-Level Defect Fusion Segmentation Network by Zhaochen Yao, Yanjuan Li, Hao Fu, Jun Tian, Yang Zhou, Chee-Loong Chin, Chau-Khun Ma

“…Cracks and dents in concrete structures are core defects that threaten building safety, but the existing YOLO series algorithms face a huge bottleneck in complex engineering scenarios. …”
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Cross-dimensional adaptivity research on a 3D earth observation data cube model by Yu Jinsongdi, Cui Zhanying, Baumann Peter, Tong Ruiju, Wei Dandan, Luo Yuan

“…This finding has significant implications in the field of EO data analysis, enabling seamless interaction between data cubes with different dimensions. …”
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Conflict management training for future educators by N. A. Sokolova, N. V. Sivrikova, E. G. Chernikova, T. G. Ptashko, E. M. Harlanova, S. V. Roslyakova

“…Most students (97,6%) learned algorithms to solve typical interpersonal conflicts and began to choose more constructive strategies to solve them. …”
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