Assessment reliability parameters of the DVB-T2 broadcasting station’s equipment with local content insertion by S. V. Sai, N. Yu. Sorokin, О. V. Tissen

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Morphological Estimation of Primary Branch Inclination Angles in Jujube Trees Based on Improved PointNet++ by Linyuan Shang, Fenfen Yan, Tianxin Teng, Junzhang Pan, Lei Zhou, Chao Xia, Chenlin Li, Mingdeng Shi, Chunjing Si, Rong Niu

“…The experimental results show that compared to PointNet++, the improved network achieved increases of 1.3, 1.47, and 3.33% in accuracy (Acc), class average accuracy (CAA), and mean intersection over union (mIoU), respectively. …”
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Analysis of the Efficiency of Hydrogen Production Technology at Mini-CHP Plants Using Local Fuelsby Thermochemical Method by V. A. Sednin, R. S. Ignatovich

“…The expansion of mini-CHP options operating on local fuels by introducing a hydrogen production unit by hybrid thermochemical method into its scheme makes it possible to increase the maneuverability of the station, which implies the possibility of organizing the operation of mini-CHP in accordance with the requirements of thermal consumers and electrical graph-reducing the loads of the power system during the hours of maxima and minima of its consumption by changing the electrical power supply to the network or increasing the power consumption of electricity from the external network to the power required for hydrogen production. …”
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Accurate and Robust Train Localization: Fusing Degeneracy-Aware LiDAR-Inertial Odometry and Visual Landmark Correction by Lin Yue, Peng Wang, Jinchao Mu, Chen Cai, Dingyi Wang, Hao Ren

“…Next, a kilometer post factor is constructed, and multi-source information is optimized within a factor graph framework. Finally, onboard experiments conducted on real railway vehicles demonstrate high-precision landmark detection at 35 FPS with 94.8% average precision. …”
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Research on a Crime Spatiotemporal Prediction Method Integrating Informer and ST-GCN: A Case Study of Four Crime Types in Chicago by Yuxiao Fan, Xiaofeng Hu, Jinming Hu

“…Therefore, this study proposes a hybrid model combining Informer and Spatiotemporal Graph Convolutional Network (ST-GCN) to achieve precise crime prediction at the community level. …”
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From Simulation to Implementation: A Systems Model for Electric Bus Fleet Deployment in Metropolitan Areas by Ludger Heide, Shuyao Guo, Dietmar Göhlich

“…The framework employs empirical energy models, graph-based scheduling algorithms, and integer linear programming for depot assignment and smart charging. …”
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A Study on Contestable Regions in Europe through the Use of a New Rail Cost Function: An Application to the Hinterland of the New Container Terminal of Leghorn Port by Marino Lupi, Antonio Pratelli, Mattia Canessa, Andrea Lorenzini, Alessandro Farina

“…Travel time and monetary costs of railway paths, connecting ports to their hinterland, have been determined. The rail network of a large part of Europe was modelled using a graph. …”
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Research of the Effective Diffusion Coefficient and Activation Energy for the Purpose of Energy Saving during Convection Dryin by J. E. Safarov, Sh. A. Sultanova, G. Gunes, A. S. Ponasenko, D. I. Samandarov, M. M. Pulatov, A. M. Mirkomilov, M. A. Nasirova

“…In order to find the most suitable mesh structure of the model, a network independence study was carried out using average moisture content values with an accuracy of 0.001. …”
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Antimicrobial Susceptibility Profiles of <i>Escherichia coli</i> Isolates from Clinical Cases of Ducks in Hungary Between 2022 and 2023 by Ádám Kerek, Ábel Szabó, Ákos Jerzsele

“…A decision tree classifier and a neural network were trained to predict MDR status. Cross-resistance relationships were visualized using graph-based models, and Monte Carlo simulations estimated MDR prevalence variations. …”
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Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection by Ali Nizam, Ertugrul Islamoglu, Omer Kerem Adali, Musa Aydin

“…A triplet loss-based deep learning network is designed to optimize in-class similarity and increase the distance between classes. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…This paper introduced federated learning and discussed a few federated learning algorithms applied to the problem—these methods include Federated Graph Attention Network with Dilated Convolution Neural Network (FedGAT-DCNN), FedAvg with Convolutional Neural Network (CNN), and Federated Averaging with Distance-based Weighted Aggregation (FedAvg-DWA) with Random Forest (RF). …”
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Exploring Structural Characteristics of Lattices in Real World by Yu Chen, Jinguo You, Benyuan Zou, Guoyu Gan, Ting Zhang, Lianyin Jia

“…In this paper, we first tackle the structural statistics of lattice data from three aspects: the degree distribution, clustering coefficient, and average path length. We demonstrated by various datasets that data cube lattices and concept lattices share similarities underlying their topology, which are, in general, different from random networks and complex networks. …”
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CDPMF-DDA: contrastive deep probabilistic matrix factorization for drug-disease association prediction by Xianfang Tang, Yawen Hou, Yajie Meng, Zhaojing Wang, Changcheng Lu, Juan Lv, Xinrong Hu, Junlin Xu, Jialiang Yang

“…This process effectively reduces noise in the data, establishing a reliable foundation for the networks produced. Next, we generate multiple contrastive views from both the original and generated networks. …”
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Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Furthermore, a novel Attention-augmented Spatial-Temporal Graph Convolutional Network (AST-GCN) is developed for reliably identifying the action in each frame, enabling accurate computation of key kinematic features for fall risk prediction. …”
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Meta-YOLOv8: multi-scale few-shot object detection for Chinese medicinal decoction pieces by Kai Hu, Chu-he Lin, Xing Jin, Hangjuan Lin

“…We propose Meta-YOLOv8, a novel few-shot object detection network based on YOLOv8. To effectively integrate YOLOv8 with meta-learning, we introduce three key modules: (i) Multi-Scale Class Feature Extraction Module (CFEM), (ii) Heterogeneous Graph Convolutional Networks (HGCN), and (iii) Multi-Scale Classification Auxiliary Module (CAM). …”
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Winter Wheat Yield Prediction and Influencing Factors Analysis Based on FourierGNN–Random Forest Combined Modeling by Jianqin Ma, Yijian Chen, Bifeng Cui, Yu Ding, Xiuping Hao, Yan Zhao, Junsheng Li, Xianrui Su

“…A combined model of GNN (Graph Neural Network), based on the Fourier transform and the Random Forest algorithm was developed to predict winter wheat yield. …”
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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…We propose an Edge Location Prediction Model (ELPM) suitable for the MEC scenario, which integrates Spatial-Temporal Graph Neural Networks and attention mechanisms. By leveraging attention parameters, ELPM acquires spatio-temporal adaptive weights, enabling accurate location predictions. …”
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CrysMTM: a multiphase, temperature-resolved, multimodal dataset for crystalline materials by Can Polat, Erchin Serpedin, Mustafa Kurban, Hasan Kurban

“…Baseline benchmarking across 18 models–including graph neural networks (GNNs), convolutional neural networks, and foundation models–reveals significant property-specific challenges. …”
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Characterizing the effects of age, puberty, and sex on variability in resting-state functional connectivity in late childhood and early adolescence by Kelly A. Duffy, Andrea Wiglesworth, Donovan J. Roediger, Ellery Island, Bryon A. Mueller, Monica Luciana, Bonnie Klimes-Dougan, Kathryn R. Cullen, Mark B. Fiecas

“…Time-varying correlations in the frontolimbic, default mode, and dorsal and ventral corticostriatal networks, estimated using the Dynamic Conditional Correlations (DCC) method, were used to calculate variability of within- and between-network connectivity and of graph theoretical measures of segregation and integration. …”
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A Cross-Dimensional Attention Mechanism for Pedestrian Trajectory Forecasting by Feng Bian, Wensheng Zhang

“…Specifically, we utilize graph attention networks to capture spatial features and transformers to capture temporal features. …”
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