Automatic Identification and Segmentation of Overlapping Fog Droplets Using XGBoost and Image Segmentation by Dongde Liao, Xiongfei Chen, Muhua Liu, Yihan Zhou, Peng Fang, Jinlong Lin, Zhaopeng Liu, Xiao Wang

“…In order to accurately measure the droplet size and grasp the droplet distribution pattern, this study proposes a method based on the optimized XGBoost classification model combined with improved concave-point matching to achieve multi-level overlapping-droplet segmentation. …”
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Automatic license-plate recognition by A. V. Poltavskii, T. G. Yurushkina, M. V. Yurushkin

“…Quality of the system is provided through the optimization of various models with different modifications. …”
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PolicySegNet: a policy-based reinforcement learning framework with pretrained embeddings and transformer decoder for joint brain tumors segmentation and classification in MRI by Vishv Patel, Vandana Patel, Aakash Shinde

“…PolicySegNet uniquely integrates a policy-based reinforcement learning algorithm—specifically proximal policy optimization (PPO)—to jointly optimize the decoder and classifier based on a reward signal that balances segmentation accuracy with classification performance. …”
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Stochastic economic placement and sizing of electric vehicles charging station with renewable units and battery bank in smart distribution network by Mehdi Veisi

“…Benders decomposition algorithm is used to extract the optimal solution. …”
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Detection of false data injection in electric energy metering platforms using gradient lifting decision trees and MLP neural networks by Yakui Zhu, Yangrui Zhang, Chao Zhang, Bingyu Zhang, Hongying Wang, Shaokang Feng

“…The discriminator used a multilayer perceptron (MLP) neural network, combined with difference analysis between the predicted and actual values, to determine false data injection. The improved Cauchy mutation grey Wolf optimization algorithm is used to optimize the model training to improve the detection accuracy. …”
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Software and hardware co-design of lightweight authenticated ciphers ASCON for the internet of things by Jing WANG, Lesheng HE, Zhonghong LI, Luchi LI, Hang YANG

“…ASCON was the most promising algorithm to become an international standard in the 2021 NIST lightweight authenticated encryption call for proposals.The algorithm was designed to achieve the best performance in IoT resource-constrained environments, and there was no hardware IP core implementation based on this algorithm in the open literature.A software-hardware collaborative implementation method of ASCON was proposed, which improved the speed and reduced the memory footprint of ASCON in IoT security authentication applications through hardware means such as S-box optimization, prior calculation and advanced pipeline design.As a comparison, ASCON has been transplanted on the common IoT embedded processor platform.The results showed that the described method was more than 7.9 times faster, while the memory footprint was reduced by at least 90%.The schemes can be used for the design and implementation of IoT security application-specific integrated circuits or SoCs.…”
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Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding by Laizhong Cui, Nan Lu, Fu Chen

“…The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. …”
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Underwater Target 3D Reconstruction via Integrated Laser Triangulation and Multispectral Photometric Stereo by Yang Yang, Yimei Liu, Eric Rigall, Yifan Yin, Shu Zhang, Junyu Dong

“…At the same time, we propose to optimize the laser place calibration and laser line separation processes, further improving the reconstruction performance of underwater laser triangulation and multispectral photometric stereo. …”
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Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions by Guangcan Xu, Qiguang Lyu

“…As a method to solve the model, genetic variation of multiobjective particle swarm optimization algorithm is considered. …”
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Predicting hospital outpatient volume using XGBoost: a machine learning approach by Lingling Zhou, Qin Zhu, Qian Chen, Ping Wang, Hao Huang

“…Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allocation of medical resources. This study aims to develop a predictive model for daily hospital outpatient volume using the XGBoost algorithm. …”
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Energy Storage Regulation Method of Base Stations in 5G Integrated Distribution Network Based on Energy Sharing and Trading Coordination by Yanru WANG, Xiyang YIN, Qinghai OU, Wenjie MA, Hui LIU, Zhigang DU

“…Then, with the optimization objectives of promoting energy sharing of 5G base stations, improving operation efficiency of base stations, and participating in peak shaving and valley filling, the optimization problem of energy storage regulation of base stations in a 5G integrated distribution network is constructed, and an energy storage regulation algorithm of 5G base stations based on energy sharing and trading coordination is proposed. …”
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High-Dimensional Projected Clustering for Learner Competency Analysis in Medical Training Programs by Sandhya Harikumar, C. S. Jayamohan Pillai, V. Vani Chithra, Raghu Raman, Mr Kaimal, Kai-Yu Tang, Prema Nedungadi

“…Additionally, weak learners deficient in crucial healthcare areas are identified, and the model recommends the most qualified professionals for specific critical care cases.…”
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Energy-Efficient Resource Allocation for Near-Field MIMO Communication Networks by Tong Lin, Jianyue Zhu, Junfan Zhu, Yaqin Xie, Yao Xu, Xiao Chen

“…A low-complexity optimization algorithm is proposed to realize the joint optimization of power and antenna number. …”
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Simulation and test study of transmission characteristics of V-shaped rubber belt CVT by TIAN Zhewen, TIAN Hao, CHEN Shuoyan

“…ObjectiveThe dynamic matching problem of continuously variable transmission （CVT） with the engine and Baja racing car was subjected to research analysis.MethodsThe parameters of key components of CVT were first optimized by genetic algorithm in Matlab software, then the dynamic modeling and simulation of CVT and the whole vehicle were carried out in Matlab/Simulink and RecurDyn, and finally the vehicle test was carried out on the chassis dynamometer.ResultsThe results of modeling simulation and vehicle test show that the dynamic index of Baja racing car is significantly improved after the optimization of the parameters of key components of CVT. …”
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Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning by Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu

“…However, the hyperparameters of the deep learning, which significantly impact the feature extraction and prediction performance, are determined based on expert experience in most cases. The grid search method is introduced in this paper to optimize the hyperparameters of the proposed aircraft engine RUL prediction model. …”
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Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…Finally, the global model parameters are fed back to the vehicles to further optimize the local resource allocation strategy, thus improving the system spectrum efficiency. …”
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Research on caching strategy based on transmission delay in Cell-Free massive MIMO systems by Rui WANG, Min SHEN, Yun HE, Xiangyan LIU

“…To meet the ultra-low latency and ultra-high reliability requirements of users in the future mobile Internet， the wireless caching technology was combined with Cell-Free massive MIMO systems.The caching model was designed based on AP cooperative caching and regional popularity evaluation.The transmission delay expression involving AP clustering， cooperative caching， and regional popularity was derived， and the content placement problem was expressed as total content transmission delay minimization.Through the demonstration of the NP-hard and submodular monotony of the optimization problem， the greedy algorithm-based optimization strategy was proposed.Simulation results show that the proposed strategy can effectively reduce the content transmission delay and improve the cache hit rate.…”
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Deep learning-based prediction of individualized Real-time FSH doses in GnRH agonist long protocols by Na Kong, Yu Xia, Zhilong Wang, Hui Zhang, Liyan Duan, Yingchun Zhu, Chenyang Huang, Guijun Yan, Jie Mei, Wujun Li, Haixiang Sun

“…Most existing models are limited to static predictions of initial doses and do not support real-time adjustments throughout stimulation. …”
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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…Three sequential deep learning models—Recurrent Neural Network and Gated Recurrent Unit—were developed and optimized using the Adam algorithm. …”
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Analysis of IoT-Collected Radish Growth Data Using Deep Neural Networks by Ivan P. Malashin, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…The aim of this study was to apply genetic algorithm-based hyperparameter optimization (GA-HPO) to deep neural networks (DNNs) to classify an IoT-collected dataset on radish growth conditions, with the goal of identifying optimal growth parameters. …”
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