Intelligent Malfunction Identification Method in Mechanical Manufacturing Process Based on Multisensor Data by Meng Wang

“…Current technology trends have been gradually integrated into the production of all walks of life, which play an indispensable part in promoting the intelligent development of enterprises, and have brought a greater impact on production and reformation. …”
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CALCULATION MODEL OF SOLID PARTICLES MOTION IN NATURAL TURBULENT FLOWS by M. R. Magomedova

“…Such a model is implemented by integrating averaged equations and vortex formations using a mathematical apparatus.Conclusion The calculated model of the movement of solid particles is implemented in the algorithmic language Fortran Power Station and tested on the basis of field and experimental studies in a wide range of hydraulic flow characteristics and physical and mechanical characteristics of channel soils.…”
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Vehicle Reidentification via Multifeature Hypergraph Fusion by Wang Li, Zhang Yong, Yuan Wei, Shi Hongxing

“…In this paper, we utilize hypergraph representation to integrate image features and tackle the issue of vehicles re-ID via hypergraph learning algorithms. …”
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Quantum DeepONet: Neural operators accelerated by quantum computing by Pengpeng Xiao, Muqing Zheng, Anran Jiao, Xiu Yang, Lu Lu

“…Our proposed quantum DeepONet integrates unary encoding and orthogonal quantum layers. …”
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Cooperative Graph-Based Predictive Collision Avoidance (CGPCA): A Decentralized Framework for Safe Drone Traffic Management by Fariborz Rasoulie

“…Unlike traditional methods that rely on fixed geometric rules or purely reactive algorithms, CGPCA leverages predictive learning. A GNN, trained on a wide range of simulated traffic scenarios, processes the traffic graph to forecast near-future positions and assign collision risk scores. …”
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Real time thermal environment monitoring and interior design of intelligent buildings based on the Internet of Things by Lang Jiaoyu

“…Designed an intelligent building indoor real-time thermal environment monitoring system based on the Internet of Things, constructed the system architecture, and proposed effective indoor monitoring algorithms to determine the monitoring effect of the system through data analysis. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…The experimental results show that the mAP@50 of the improved model reaches 94.2%, which is 2.4% higher than that of the baseline model YOLOv10n, and better than the mainstream algorithms such as YOLOv5 (93.1%) and YOLOv8n (93.2%).…”
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Multimodal fusion radiomic-immunologic scoring model: accurate identification of prostate cancer progression by Zhonglin Zhang, Huan Liu, Xiling Gu, Yang Qiu, Jiangqing Ma, Guangyong Ai, Xiaojing He

“…This included the Akaike Information Criterion (AIC), Maximum Relevance Minimum Redundancy (mRMR), and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms, validated through 10-fold cross-validation. …”
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Sound Sensing: Generative and Discriminant Model-Based Approaches to Bolt Loosening Detection by Liehai Cheng, Zhenli Zhang, Giuseppe Lacidogna, Xiao Wang, Mutian Jia, Zhitao Liu

“…The detection of bolt looseness is crucial to ensure the integrity and safety of bolted connection structures. …”
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Data-Driven and Mechanistic Soil Modeling for Precision Fertilization Management in Cotton by Miltiadis Iatrou, Panagiotis Tziachris, Fotis Bilias, Panagiotis Kekelis, Christos Pavlakis, Aphrodite Theofilidou, Ioannis Papadopoulos, Georgios Strouthopoulos, Georgios Giannopoulos, Dimitrios Arampatzis, Evangelos Vergos, Christos Karydas, Dimitris Beslemes, Vassilis Aschonitis

“…This study introduces a novel methodology for predicting cotton yield by integrating machine learning (ML) with mechanistic soil modeling. …”
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Proposal of a Thermal Network Model for Fast Solution of Temperature Rise Characteristics of Aircraft Wire Harnesses by Tao Cao, Wei Li, Tianxu Zhao, Shumei Cui

“…A structure consisting of series thermal resistance within layers and iterative parallel algorithms between layers is proposed to equivalently integrate and iteratively calculate the mutual thermal influence relationship between each layer of the harness, thereby constructing a hierarchical harness thermal network model. …”
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Optimizing additive manufacturing workflows using model-based systems engineering by Mohamed Amine Daoud, Khadija Bekkay Haouari, Meriem Hayani Mechkouri, Amine Ennawaoui, Hicham El hadraoui, Ilias Naser, Mustapha Ouardouz, Kamal Reklaoui

“…The ASAM framework utilizes the CESAM architecture and System Modelling Language (SysML) to create multi-architecture models of the AM process, integrating operational, functional, and constructional perspectives. …”
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Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model by Tingting Hu, Liheng Zhao, Xueling Zhao, Lin He, Xiaoli Zhong, Zhe Yin, Junjie Chen, Yanting Han, Ka Li

“…Abstract Objective The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery. …”
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An inductive learning-based method for predicting drug-gene interactions using a multi-relational drug-disease-gene graph by Jian He, Yanling Wu, Linxi Yuan, Jiangguo Qiu, Menglong Li, Xuemei Pu, Yanzhi Guo

“…In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. …”
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DGNMDA: Dual Heterogeneous Graph Neural Network Encoder for miRNA-Disease Association Prediction by Daying Lu, Qi Zhang, Chunhou Zheng, Jian Li, Zhe Yin

“…To tackle this challenge, we propose an innovative model named DGNMDA. Initially, we constructed various miRNA and disease similarity networks based on authoritative databases. …”
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Mapping County-Level Rice Planting Areas by Joint Use of High-Resolution Optical and Time Series SAR Imagery by Jia Xu, Haojie Wang, Lin Qiu, Hui Wang, Yang Mu

“…And the proposed method effectively integrated limited GF-6 imagery with time-series Sentinel-1 data and performed better than traditional machine learning algorithms like Random Forest and pixel-based methods, achieving an overall accuracy of over 88% and a Kappa coefficient of over 86% for the Dangtu and Rudong counties. …”
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AEM-D3QN: A Graph-Based Deep Reinforcement Learning Framework for Dynamic Earth Observation Satellite Mission Planning by Shuo Li, Gang Wang, Jinyong Chen

“…This framework constructs a Directed Acyclic Graph (DAG) atlas to represent task dependencies and constraints, leveraging GNNs to extract spatial–temporal task features. …”
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Study on a Traditional Chinese Medicine constitution recognition model using tongue image characteristics and deep learning: a prospective dual-center investigation by Yongyue Liu, Linmiao Fan, Mei Zhao, Dongshen Wei, Menglan Zhao, Yihang Dong, Xiaoqing Zhang

“…Eight machine learning algorithms were employed to construct and evaluate the efficacy of the models. …”
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The Future of Employment: Evaluating the Impact of STI Foresight Exercises by Ricardo Seidl da Fonseca

“…Linking policy-making, Foresight, and specific future-looking themes, the paper offers building blocks for constructing standards for the evaluation of foresight exercises. …”
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A Study Investigating Interpretable Deep Learning Models for Predicting Mortality and Survival in Patients with Primary Thyroid Lymphomas by Zihan Yu, Rong Hu, Jiaqing Chen

“…Primary thyroid lymphoma (PTL) is a rare malignancy, and this study aimed to develop a prognostic prediction model for PTL using deep learning algorithms while providing interpretable analyses. Machine learning models were employed for mortality risk prediction, with the SHAP framework introduced for feature interpretation, and a DeepSurv model was constructed for comparison with the Cox proportional hazards (Cox-PH) model. …”
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