Improvement of RT-DETR model for ground glass pulmonary nodule detection. by Siyuan Tang, Qiangqiang Bao, Qingyu Ji, Tong Wang, Naiyu Wang, Min Yang, Yu Gu, Jinliang Zhao, Yuhan Qu, Siriguleng Wang

“…This article proposed an algorithm based on RT-DETR model with the following enhancement: 1) optimize the backbone network with FCGE blocks to increase the detection accuracy of small-sized and blurred edge nodules; 2) replace the AIFI module with HiLo-AIFI module to reduce redundant computation and improve the detection accuracy of pure ground glass pulmonary nodules and mixed ground glass pulmonary nodules; 3) replace the DGAK module with CCFF module to address the issue of capturing complex features and recognition of irregularly shaped ground glass nodules. …”
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The impact of dietary metabolizable energy levels on the performance of medium-sized geese: A systematic review by Shuo Wang, Chunbo Wei, Jiaxin Yan, Ying Zhang

“…Following the literature review, a network meta-analysis was conducted by Stata software (StataCorp version 14.0). …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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Path Planning Method of Mobile Robot Using Improved Deep Reinforcement Learning by Wei Wang, Zhenkui Wu, Huafu Luo, Bin Zhang

“…In addition, an improved deep Q-network (DQN) method is proposed, which takes the directly collected information as the training samples and combines the environmental state characteristics of the robot and the target point to be reached as the input of the network. …”
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Study on Finite Element Model Modification of Long-Span Suspension Bridge Based on BPANN-GA by Zi-Xiu Qin, Xi-Rui Wang, Wen-Jie Liu, Zi-Jian Fan

“…First, finite element computational data is used to train the neural network. The trained neural network is then used to predict the natural frequencies corresponding to different modal shapes under various parameters. …”
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Research on Railway Passenger Volume Forecast Based on the Spline Interpolation and IPSO-Gradient Difference Acceleration Rule by Dingyuan Fan, Fei Yang, Jinghao Ji, Zexi Zhang

“…In comparison with the BP neural network, Holt exponential smoothing, simple averaging, and conventional redifference approaches, the IPSO-redifference acceleration method achieves a superior prediction performance, and the absolute values of the forecast error are reduced by 3.320%, 1.518%, 2.419%, and 0.602%.…”
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Analysis and Research on Intelligent Logistics Data under Internet of Things and Blockchain by Yige Li

“…In the comparative analysis of system transmission performance, the model exhibits outstanding results in transmission latency, consistently maintaining an average delay of approximately 350 ms. This stability is primarily attributed to the seamless integration of BC technology, which optimizes data packet transmission paths and mitigates waiting time. …”
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Synergistic effect of artificial intelligence and new real-time disassembly sensors: Overcoming limitations and expanding application scope by Bozhou Li, Dajiang Ju, Xingwang Li, Yan Liu, Hongru He, Hao Wang

“…Then, based on the gated recurrent unit (GRU) model, the article applied the particle swarm optimization (PSO) algorithm to optimize the parameters of the GRU network and used the support vector machine (SVM) model to optimize the classification function of the network output. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…In this research, several machine learning predictive models based on extra trees, decision tree, support vector machine, random forest, multilayer perceptron artificial neural network, K-nearest neighbors, convolutional neural network, ensemble learning, and adaptive boosting using a dataset gathered from a coke plant are developed to predict CRI. …”
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Spatial and temporal characteristics of water conservation services and rapid response framework for water yield in key ecological zones of the Yiluo River basin by Junqiang Xu, Fan Wang, Chao Ren, Jianmin Bian, Tao Li, Zikai Ping

“…Study focus: In this study, we analyzed the spatial and temporal patterns of water yield and the main influencing factors of the Yiluo River Basin based on the water yield response framework constructed by the SWAT model and the intelligent optimization algorithm. New hydrological insights for the region: The results indicated that the average annual total of water-source containment per unit area in the district was 330.03 mm from 2019 to 2023, with a Nash-Sutcliffe Efficiency (NSE) of 0.77, based on the average of two hydrological sites in the SWAT model. …”
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Application research of 3D virtual interactive technology in interactive teaching of arts and crafts by Mingqi Yao

“…For this reason, the research proposes an image denoising model based on convolutional neural network and wavelet transform, which adopts residual neural network structure and batch normalization algorithm, aiming at gradient explosion and gradient disappearance that may be caused by convolutional neural network, And the problem of low training efficiency has been optimized. …”
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BA-ATEMNet: Bayesian Learning and Multi-Head Self-Attention for Theoretical Denoising of Airborne Transient Electromagnetic Signals by Weijie Wang, Xuben Wang, Xiaodong Yu, Debiao Luo, Xinyue Liu, Kai Yang, Wen Yang, Xiaolan Yang, Ke Hu, Wenyi Hu

“…Traditional denoising methods often fall short in addressing these complex noise backgrounds, leading to less-than-optimal signal extraction. To tackle this issue, a deep learning-based denoising network, called BA-ATEMNet, is introduced, using Bayesian learning alongside a multi-head self-attention mechanism to effectively denoise ATEM signals. …”
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A cooperative jamming resource allocation method based on PSO-SSNOA by Wei Liu, You Chen, Xiaohong Zhao, Dejiang Lu, Tianjian Yang

“…Subsequently, we propose a Particle Swarm Optimization Guided Seasonal Strategy Nutcracker Optimization Algorithm (PSO-SSNOA) based jamming resource allocation method. …”
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Multi-defect detection and classification for aluminum alloys with enhanced YOLOv8. by Ying Han, Xingkun Li, Gongxiang Cui, Jie Song, Fengyu Zhou, Yugang Wang

“…Finally, the backbone network structure is reconstructed. Fine-grained adjustments and improvements are made to enhance neck network layers and the feature extraction capability. …”
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Application of the SARIMA-LSTM model to evaluate the effectiveness of interventions for Visceral Leishmaniasis by Mengchen Han, Chongqi Hao, Zhiyang Zhao, Peijun Zhang, Bin Wu, Lixia Qiu

“…The hybrid model integrates a SARIMA component with a residual-based LSTM neural network. Results: In the SARIMA-LSTM model, the LSTM component included seven hidden layer nodes, a learning rate of 0.001, 500 training epochs, a batch size of 256, and utilized the Adam optimization algorithm. …”
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Mathematical Modeling and Statistical Evaluation of the Security–Performance Trade-Off in IoT Cloud Architectures: A Case Study of UBT Smart City by Besnik Qehaja, Edmond Hajrizi, Behar Haxhismajli, Lavdim Menxhiqi, Galia Marinova, Elissa Mollakuqe

“…Finally, we introduce a multi-objective cost-delay function that can guide the selection of optimal security configurations by balancing latency and cost, providing a valuable tool for the future optimization of secure IoT infrastructures…”
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An Adaptive Underwater Image Enhancement Framework Combining Structural Detail Enhancement and Unsupervised Deep Fusion by Semih Kahveci, Erdinç Avaroğlu

“…The principal structural features are then optimally combined with a gamma-corrected luminance channel using an unsupervised MU-Fusion network, achieving a balanced optimization of both global contrast and local details. …”
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A study on secure coding of intelligent inspection video in plant areas based on improved deep reinforcement learning by Yongmin Yang, Zhenhao Wang

“…First, the transmission and network model of the factory inspection video are analyzed, and a conditional depth network based on Transformer is designed. …”
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Tuning properties of CTAB-HSA-AuNR nanocomposite antibacterial thin films by Krishna Halder, Kabira Sabnam, Atri Sen, Swagata Dasgupta

“…AFM images reveal a pattern on the surface with different average heights with an increase in surface roughness with the addition of sorbitol. …”
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Edge-AI Enabled Wearable Device for Non-Invasive Type 1 Diabetes Detection Using ECG Signals by Maria Gragnaniello, Vincenzo Romano Marrazzo, Alessandro Borghese, Luca Maresca, Giovanni Breglio, Michele Riccio

“…By applying quantization as an optimization technique, the model effectively balances memory usage and accuracy, achieving an accuracy of 89.52% with an average precision and recall of 0.91 and 0.90, respectively. …”
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