A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…An attention mechanism is added to focus on the most important features,improving the prediction accuracy of the model. …”
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TSD-Net: A Traffic Sign Detection Network Addressing Insufficient Perception Resolution and Complex Background by Chengcheng Ma, Chang Liu, Litao Deng, Pengfei Xu

“…By incorporating the C3k2 module and dynamic convolution into the network, the framework achieves enhanced feature extraction flexibility while maintaining high computational efficiency. …”
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Choice of machine learning models for predicting the development of psychological disorders in people with hypothireosis and hyperthireosis by Нурал Гулієв

“…Later, the diseases develop to the point where complications occur in the body, some of the most dangerous of which are psychological disorders: depression, mania, aggression, etc. …”
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Signal Processing for Transient Flow Rate Determination: An Analytical Soft Sensor Using Two Pressure Signals by Faras Brumand-Poor, Tim Kotte, Enrico Gaspare Pasquini, Katharina Schmitz

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Research on rock fracture evolution prediction model based on Adam-ConvLSTM and transfer learning by Runze Liu, Ziwei Wang, Yanbo Zhang, Xulong Yao, Shaohong Yan, Zhiyuan Chen, Shuai Wang, Hua Li, Qi Wang

“…In practical applications, the comprehensive model uses structure similarity index measure to align test samples with the most similar images from the model, selecting the predictive model with the most similar images for forecasting fracture evolution. …”
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Automated histopathological detection and classification of lung cancer with an image pre-processing pipeline and spatial attention with deep neural networks by Tushar Nayak, Nitila Gokulkrishnan, Krishnaraj Chadaga, Niranjana Sampathila, Hilda Mayrose, Swathi K. S.

“…Histopathological examination of tumorous tissue biopsy is the gold standard method used to clinically identify the type, sub-type, and stage of cancer. Two of the most prevalent forms of lung cancer: Adenocarcinoma & Squamous Cell Carcinoma account for nearly 80% of all lung cancer cases, which makes classifying the two subtypes of high importance. …”
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Image-based Artificial Intelligence-driven modelling for blank shape optimisation in sheet metal forming by Haosu Zhou, Haoran Li, Yingxue Zhao, Peter R.N. Childs, Nan Li

“…Nevertheless, existing methods are mostly constrained by fixed shape parameterisation schemes, limiting their flexibility and effectiveness. …”
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Empirical Evaluation and Analysis of YOLO Models in Smart Transportation by Lan Anh Nguyen, Manh Dat Tran, Yongseok Son

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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…The aim of this study was to carry out a detailed assessment of the water resources in the region, focussing on the most important aspects affecting water quality. The main objectives were to calculate various water quality indices for drinking and irrigation purposes, to develop an automated system using convolutional neural networks (CNN) to predict these indices and to increase the transparency of these models using explainable artificial intelligence (XAI) methods. …”
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Integrated deep learning framework for driver distraction detection and real-time road object recognition in advanced driver assistance systems by Rakesh Salakapuri, Naveen Kumar Navuri, Thrimurthulu Vobbilineni, G. Ravi, Karthik Karmakonda, K. Asish vardhan

“…Abstract Most accidents are a result of distractions while driving and road user’s safety is a global concern. …”
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Improving YOLOv11 for marine water quality monitoring and pollution source identification by Fang Wang

“…Additionally, Multi-scale Feature Fusion (MFF) combines Convolutional Neural Networks (CNN) and Transformer-based feature extraction to enhance robustness in complex environments. …”
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METHOD FOR EVALUATING EXCAVATION SHORING DESIGN CONCEPTS by Yu. G. Zheglova, B. P. Titarenko

“…Aim.When conducting engineering and geological surveys at the conceptual stage of the feasibility study, it is necessary to create an automated system that allows the designer to take all possible factors into account and choose the most optimal design solution for the shoring of excavations.Method. …”
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SFPFMformer: Short-Term Power Load Forecasting for Proxy Electricity Purchase Based on Feature Optimization and Multiscale Decomposition by Chengfei Qi, Yanli Feng, Junling Wan, Xinying Mao, Peisen Yuan

“…Finally, we utilize a depthwise separable convolution block to extract features from power load data, which efficiently captures the pattern of change in load. …”
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Enhancing pediatric distal radius fracture detection: optimizing YOLOv8 with advanced AI and machine learning techniques by Farid Amirouche, Aashik Mathew Prosper, Majd Mzeihem

“…Abstract Background In emergency departments, residents and physicians interpret X-rays to identify fractures, with distal radius fractures being the most common in children. Skilled radiologists typically ensure accurate readings in well-resourced hospitals, but rural areas often lack this expertise, leading to lower diagnostic accuracy and potential delays in treatment. …”
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Extension of the First-Order Recursive Filters Method to Non-Linear Second-Kind Volterra Integral Equations by Rodolphe Heyd

“…A new numerical method for solving Volterra non-linear convolution integral equations (NLCVIEs) of the second kind is presented in this work. …”
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PolSAR image classification using shallow to deep feature fusion network with complex valued attention by Mohammed Q. Alkhatib, M. Sami Zitouni, Mina Al-Saad, Nour Aburaed, Hussain Al-Ahmad

“…The results indicate that the proposed approach achieves notable improvements in Overall Accuracy (OA), with enhancements of 1.30% and 0.80% for the AIRSAR datasets, and 0.50% for the ESAR dataset. However, the most remarkable performance of the CV-ASDF2Net model is observed with the Flevoland dataset; the model achieves an impressive OA of 96.01% with only a 1% sampling ratio. …”
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Physical bases for determination of scattering kernels from incomplete data in grid-less X-ray imaging by A. Yu. Danyk, O. O. Sudakov

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Application of deep learning in cloud cover prediction using geostationary satellite images by Yeonjin Lee, Seyun Min, Jihyun Yoon, Jongsung Ha, Seungtaek Jeong, Seonghyun Ryu, Myoung-Hwan Ahn

“…We explore the effectiveness of advanced deep learning techniques – specifically 3D Convolutional Neural Networks, Long Short-Term Memory networks, and Convolutional Long Short-Term Memory (ConvLSTM) – using GK2A cloud detection data, which provides updates every 10 minutes at 2 km spatial resolution. …”
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Models, systems, networks in economics, engineering, nature and society by D.V. Mirosh

“…The technical diagnostic tools used today in the repair and maintenance of asynchronous motors are an important aspect of the functioning of the most important devices in enterprises. Asynchronous drive is used in many areas of human activity, in industry as well as in everyday life. …”

Leveraging hybrid 1D-CNN and RNN approach for classification of brain cancer gene expression by Heba M. Afify, Kamel K. Mohammed, Aboul Ella Hassanien

“…The continuous availability of gene expression datasets over the preceding years has made them one of the most accessible sources of genome-wide data, advancing cancer bioinformatics research and advanced prediction of cancer genomic data. …”
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