Performance Evaluation of Four Deep Learning-Based CAD Systems and Manual Reading for Pulmonary Nodules Detection, Volume Measurement, and Lung-RADS Classification Under Varying Ra... by Sifan Chen, Lingqi Gao, Maolu Tan, Ke Zhang, Fajin Lv

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A machine learning based radiomics approach for predicting No. 14v station lymph node metastasis in gastric cancer by Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Xiangli Li, Xiangchao Song, Xiangchao Song, Xiangchao Song, Xiangchao Song, Lingwei Wang, Lingwei Wang, Lingwei Wang, Lingwei Wang, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye

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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin Ab Rahman, Sakib Iqram Hamim

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User scheduling and power allocation strategy for cell-free networks based on federated learning by WANG Huahua, HUANG Yexia, LI Ling

“…In order to address the issue of limited training performance in federated learning (FL) due to user link quality disparities and imbalanced communication, and computing resource utilization in cell-free network systems, a joint optimization problem for user scheduling and power allocation was designed. …”
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Spreading Social Influence with both Positive and Negative Opinions in Online Networks by Jing (Selena) He, Meng Han, Shouling Ji, Tianyu Du, Zhao Li

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On improvements of multi-objective branch and bound by Julius Bauß, Sophie N. Parragh, Michael Stiglmayr

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A New Approach for Quantification of Finger Angles with Applications in Rehabilitation and Medical Assessment by Marius Turnea, Andrei Gheorghita, Irina Duduca, Mariana Rotariu

“…The study opens new perspectives for the development of advanced data processing algorithms, including the integration of deep learning neural networks for modelling and optimizing joint movements…”
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Robust face mask detection in complex scenarios using YOLOv8 and context-aware convolutions by Yingjie Wei, Huili Li, Yuanfei He, Li Li, Qiongshuai Lyu, Yu Yang

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Macro-microscopic study on the damage threshold strain of particle-filled polymer composites by Wang Jiaxiang, Qiang Hongfu, Wang Xueren, Wang Zhejun, Li Shiqi

“…Based on the statistical results of filling particles, a mathematical model was constructed to predict the damage threshold strain of solid propellants during uniaxial loading using micromechanics methods and Weibull damage statistics theory. Subsequently, optimization algorithms were used to determine the parameter values in the model, and the effectiveness of the model was compared and verified. …”
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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

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The analysis of deep reinforcement learning for dynamic graphical games under artificial intelligence by Yuyang Yan, Jiahui Li, Cristina Zaggia

“…The findings show that the DRL-based online iterative algorithm significantly improves decision accuracy and convergence speed, reduces computational complexity, and demonstrates strong performance and scalability in addressing optimal control problems in dynamic graphical intelligent games.…”
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Machine learning based multi-parameter droplet optimisation model study by Ting Li, Likun Lu, Qingtao Zeng, Kexin Liao

“…In order to achieve the accurate generation of ideal droplets in continuous inkjet devices, this paper proposes a new parameter optimisation method, BO-GP, which combines the Bayesian optimisation algorithm with computer vision, and after 50 rounds of iterations, it can converge to the optimal values of the control parameters, and successfully constructs the Pareto frontier of the control parameters. …”
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SB‐YOLO‐V8: A Multilayered Deep Learning Approach for Real‐Time Human Detection by Prince Alvin Kwabena Ansah, Justice Kwame Appati, Ebenezer Owusu, Edward Kwadwo Boahen, Prince Boakye‐Sekyerehene, Abdullai Dwumfour

“…ABSTRACT Over the past decade, significant advancements in computer vision have been made, primarily driven by deep learning‐based algorithms for object detection. …”
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The Hessian by blocks for neural network by backward propagation by Radhia Bessi, Nabil Gmati

“…The back-propagation algorithm used with a stochastic gradient and the increase in computer performance are at the origin of the recent Deep learning trend. …”
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University proceedings. Volga region. Technical sciences by V.V. Konovalov, M.V. Dontsova, A.N. Rasstegaev, V.Yu. Zaitsev

“…The developed technique made it possible to create a calculation algorithm based on it. The implemented computer model in the MatchCAD mathematical package allows optimizing the values of the number of parts processed in each group, but with machines of different types, by alternately optimizing to minimize operating costs, to minimize energy consumption and to minimize labor costs. …”

Design and Characterization of a Low-Cost Capacitive Soil Moisture Sensor System for IoT based Agriculture Applications by Siddhanta Borah, R. Kumar, Subhradip Mukherjee

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Performance Analysis and Improvement of Machine Learning with Various Feature Selection Methods for EEG-Based Emotion Classification by Sherzod Abdumalikov, Jingeun Kim, Yourim Yoon

“…The following feature selection methods were explored: filter (SelectKBest with analysis of variance (ANOVA) <i>F</i>-test), embedded (least absolute shrinkage and selection operator (LASSO) tuned using Bayesian optimization (BO)), and wrapper (genetic algorithm (GA)) methods. …”
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Sparse Multichannel Decomposition of Electrodermal Activity With Physiological Priors by Samiul Alam, Md. Rafiul Amin, Rose T. Faghih

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Nodes deployment strategy for underwater wireless sensors networks based on grids by Kai ZHOU

“…To optimal the node deployment of underwater wireless sensor network,a node deployment strategy with multi-metrics based on the grids was proposed.Firstly,the underwater environment was divided into some certain size grids.Then,based on number of nodes,coverage quality of nodes,lifetime of network,network redundancy,a multi-objectives model was proposed.In order to solve the model,cost function with constraint conditions was given.Based on the genetic algorithm,the cost and the energy consumption of the deployment method were computed.The simulation result shows that the energy consumption and the number of deployment nodes are reduced.…”
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A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…Two novel architectures, Sparse Convolutional DenseNet201 with Self-Attention (SC-DSAN) and CNN-GRU, are fused at the network level using a depth concatenation layer, avoiding the computational costs of feature-level fusion. Bayesian Optimization (BO) is employed for dynamic hyperparameter tuning, and an Entropy-controlled Marine Predators Algorithm (EMPA) selects optimal features. …”
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