Coronary Heart Disease Risk Prediction Model Based on Machine Learning by YUE Haitao, HE Chanchan, CHENG Yuyou, ZHANG Sencheng, WU You, MA Jing

“…Among them, the XGBoost model exhibited superior performance and can be referenced for future optimization of CHD prediction models. …”
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Limits of Solar Flare Forecasting Models and New Deep Learning Approach by G. Francisco, M. Berretti, S. Chierichini, R. Mugatwala, J. Fernandes, T. Barata, D. Del Moro

“…This study introduces a novel deep learning forecasting approach while emphasizing the need for performance evaluation methods tailored to better highlight current models’ limitations. …”
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The Emergence of Bull and Bear Dynamics in a Nonlinear Model of Interacting Markets by Fabio Tramontana, Laura Gardini, Roberto Dieci, Frank Westerhoff

“…In our paper we focus mainly on the dynamics of the one- and two- dimensional cases, with numerical experiments and some analytical results, and also show that the main features persist in the three-dimensional model.…”
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Chinese medical named entity recognition model based on local enhancement by CHEN Jing, XING Kexuan, MENG Weilun, GUO Jingfeng, FENG Jianzhou

“…Firstly, the representation of characters was enriched by LENER utilizing multi-source information, including phonetic, graphic and semantic features. Secondly, relative position encoding was combined to perform local attention calculations on sequence segments divided by sliding windows, and local information was fused with global information obtained from BiLSTM through nonlinear computation. …”
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XAI-FruitNet: An explainable deep model for accurate fruit classification by Shirin Sultana, Md All Moon Tasir, S.M. Nuruzzaman Nobel, Md Mohsin Kabir, M.F. Mridha

“…Despite their impressive performance, traditional deep learning models suffer from a lack of interpretability, which hampers their transparency and trustworthiness in practical applications. …”
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GCSA-ResNet: a deep neural network architecture for Malware detection by Yukang Fan, Kun Zhang, Bing Zheng, Yu Zhou, Jinyang Zhou, Wenting Pan

“…This paper proposes GCSA-ResNet, a novel deep learning model that significantly enhances malware detection performance by integrating the Global Channel-Spatial Attention (GCSA) module with ResNet-50. …”
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Two-Stream Modality-Based Deep Learning Approach for Enhanced Two-Person Human Interaction Recognition in Videos by Hemel Sharker Akash, Md Abdur Rahim, Abu Saleh Musa Miah, Hyoun-Sup Lee, Si-Woong Jang, Jungpil Shin

“…The high-performance accuracy of the proposed model proved its superiority.…”
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High-Order Moment Models of Landmark Distribution for Local Homing Navigation by Changmin Lee, Daeeun Kim

“…The suggested moment models combining both landmark distance and visual feature have better performances than the visual information alone, and high-order moment potentials can be searched to obtain a better description of landmark distribution for a given environment.…”
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Experimental characterization and numerical modelling analyses of nano-adhesive-bonded joints by Fayssal Hadjez, Brahim Necib

“…The shear tests have been carried out on the specimens with the purpose of measuring the resistance of the bonded joint, to look forward the resulting differences of structural performances. The second deals with numerical models which have been developed based on the experimental tests for adhesive joints using the finite element techniques. …”
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Intelligent Stroke Disease Prediction Model Using Deep Learning Approaches by Chunhua Gao, Hui Wang

“…This paper uses a range of physiological characteristic parameters and collaborates with deep neural networks, such as the Wasserstein generative adversarial networks with gradient penalty and regression network, to construct a stroke prediction model. Firstly, to address the problem of imbalance between positive and negative samples in the stroke public data set, we performed positive sample data augmentation and utilized WGAN-GP to generate stroke data with high fidelity and used it for the training of the prediction network model. …”
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Method of Achieving the Goal on a Graph Model with Two Quality Criteria by S. V. Chebakov, L. V. Serebryanaya

“…The features of the construction and application of graph models for solving applied problems are considered. …”
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Testing of Technical Indicators of Accumulators by Means of Complex Computer Model of EV by Fedotovs Jurijs, Bunina Inna, Zhiravetska Anastasia, Andrianova Svetlava

“…The aim of the research is to create a mathematical model of an electric vehicle that can capture the vehicle speed curve as a data input to generate the consumed and recovered battery current, which can allow the battery parameters to be analysed and conclude whether the vehicle can perform the trip around the city route with the selected battery parameters. …”
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A lightweight and explainable CNN model for empowering plant disease diagnosis by Chiranjit Pal, Swastik Karmakar, Imon Mukherjee, Partha Pratim Chakrabarti

“…To overcome these challenges, a novel architecture called Mob-Res, combining residual learning with the MobileNetV2 feature extractor, is introduced in this work. Despite having only 3.51 million parameters, Mob-Res is lightweight and well-suited for mobile applications while delivering exceptional performance. …”
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Bayesian Model Prediction for Breast Cancer Survival: A Retrospective Analysis by Islam Bani Mohammad, Muayyad M. Ahmad

“…Results: The Bayesian model exhibited the best discriminatory performance among the nine models, with an AUC of 0.859 and the highest accuracy of 96.661%. …”
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Covariate adjustment of spirometric and smoking phenotypes: The potential of neural network models. by Kirsten Voorhies, Ruofan Bie, John E Hokanson, Scott T Weiss, Ann Chen Wu, Julian Hecker, Georg Hahn, Dawn L Demeo, Edwin Silverman, Michael H Cho, Christoph Lange, Sharon M Lutz

“…We used mean squared error to compare neural network and regression models, and found the models performed similarly unless the observed distribution of the phenotype was skewed, in which case the neural network had smaller mean squared error. …”
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Semantic segmentation of underwater images based on the improved SegFormer by Bowei Chen, Bowei Chen, Wei Zhao, Wei Zhao, Qiusheng Zhang, Mingliang Li, Mingyang Qi, You Tang, You Tang, You Tang

“…To address these issues, this study presents a high-performance semantic segmentation approach for underwater images based on the standard SegFormer model. …”
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Telecom Fraud Recognition Based on Large Language Model Neuron Selection by Lanlan Jiang, Cheng Zhang, Xingguo Qin, Ya Zhou, Guanglun Huang, Hui Li, Jun Li

“…Furthermore, a dual-loss function has been employed to bolster the model’s performance in multi-class classification scenarios. …”
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Channel equalization in ultraviolet communication based on LSTM-DNN hybrid model by Liwei Zhang

“…Specifically, the LSTM-DNN model outperforms traditional methods across key performance metrics such as BER and Mean Squared Error (MSE). …”
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Innovative Approaches for PCB Image Reconstruction: Tailored Datasets, Metrics, and Models by Qianyue Wang

“…The validity of DRQ is further demonstrated by benchmarking it against SSIM and PSNR on diverse datasets, including DIV2K and Kodak, where DRQ achieves superior fine-detail reconstruction performance. 3) Comprehensive benchmarking across seven models, providing a robust evaluation of both traditional and state-of-the-art approaches. …”
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Experimental characterization and numerical modelling analyses of nano-adhesive-bonded joints by Fayssal Hadjez, Brahim Necib

“…The shear tests have been carried out on the specimens with the purpose of measuring the resistance of the bonded joint, to look forward the resulting differences of structural performances. The second deals with numerical models which have been developed based on the experimental tests for adhesive joints using the finite element techniques. …”
Get full text