Capacity Maximization Using Nash Bargaining in Indoor Optical Multiuser Interference-Limited Poisson Channel by Sudhanshu Arya, Yeon Ho Chung

“…With power constraints imposed, the resource allocation problem can be interpreted as a downlink beamforming game. To improve the capacity in a power- and interference-limited channel, we model the problem as a cooperative game and propose an altruistic algorithm using the Nash bargaining, where each self-interested user attempts to maximize its capacity through cooperation. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…The model performs multiple registrations from local to global regions. …”
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注射机增力机构优化研究 by 李铁军, 朱成实, 鄢利群, 王学平, 宁建荣

“…The analysis of motion and mechanics property is carried out on the five hinged incline arranged and double elbowed force increasing mechanism of injection machine.A complete optimal design procedure is carried out by using improved ant colony algorithms,so as to increase the stroke ratio and the amplification of the force,and to decrease the total length of mechanism.Its optimization mathematics model is established.The procedure of optimal design belongs to multi-object optimization problem.The optimal solution of the force increasing mechanism is found by improved ant colony algorithms.Compared with the traditional methods,the result shows that the total length of mechanism is decreased,the stroke ratio is increased,and the amplification of the force is increased.…”
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Phase Error Correction in Sparse Linear MIMO Radar Based on the Equivalent Phase Center Principle by Wenyuan Shao, Jianmin Hu, Yicai Ji, Jun Pan, Guangyou Fang

“…Multiple-input multiple-output (MIMO) technology is widely used in the field of radar imaging. Array sparse optimization reduces the hardware cost of MIMO radar, while virtual aperture and the equivalent phase center (EPC) principle simplify the radar signal model and reduce the computation and complexity of imaging algorithms. …”
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Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China by Baoxin Zhao, Jingzhong Zhu, Youbiao Hu, Qimeng Liu, Yu Liu

“…The main purpose of this research is to apply the logistic regression (LR) model, the support vector machine (SVM) model based on radial basis function, the random forest (RF) model, and the coupled model of the whale optimization algorithm (WOA) and genetic algorithm (GA) with RF, to make landslide susceptibility mapping for the Ankang City of Shaanxi Province, China. …”
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Two-Dimensional ISAR Fusion Imaging of Block Structure Targets by Xiaoxiu Zhu, Limin Liu, Baofeng Guo, Wenhua Hu, Lin Shi, Juntao Ma

“…The algorithm further accelerates the iterative convergence speed and improves the imaging efficiency by combining the weighted back-adding residual and condition number optimization of the basis matrix. …”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…In response to the serious imbalance in the data collected by ESP, firstly, a fault diagnosis model is established using a weighted extreme learning machine; Then, to solve the problems of insufficient algorithm learning, high computational costs caused by weighted strategies, and poor performance in applying to high-dimensional feature spaces, the Laplacian eigenmaps method is introduced to further optimize the model; finally, the effectiveness of the proposed method was validated on the TE chemical process dataset, and the practicality of the algorithm was experimentally validated on the real-time fault dataset of electric submersible pump. …”
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala, Chinta Anuradha, Patnala S. R. Chandra Murty, S. Rajeswari, N. Rajeswaran, M. Murugappan, Muhammad E. H. Chowdhury

“…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”
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Evaluation of stroke sequelae and rehabilitation effect on brain tumor by neuroimaging technique: A comparative study. by Xueliang Guo, Lin Sun

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. …”
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METRICS FOR EVALUATING CONSISTENCY IN DISTRIBUTED DATASTORES by Galyna Zholtkevych

“…This decision-making algorithm should be suitable for any business model and its requirements. …”
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Reliable Event Detection via Multiple Edge Computing on Streaming Traffic Social Data by Yipeng Ji, Jingyi Wang, Yan Niu, Hongyuan Ma

“…Then, we utilize graph neural networks to perform semi-supervised learning on HIN to obtain the optimal meta-path weights. We also develop Binary Sample Graph Convolutional Neural Network (BS-GCN) and Binary Sample Graph Attention Network (BS-GAT) to improve the reliability of graph neural network models based on the characteristics of traffic event detection and design an incremental clustering algorithm based on event similarity to implement streaming social traffic event detection. …”
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From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…Utilizing a combination of statistical pre-processing, intelligent generative models, visual data transformations and deep learning, the methodology offers a comprehensive approach to enhancing production efficiency, ensuring superior process control and improving the quality of HPDC products. …”
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Detection of Tomato Leaf Pesticide Residues Based on Fluorescence Spectrum and Hyper-Spectrum by Jiayu Gao, Xuhui Yang, Simo Liu, Yufeng Liu, Xiaofeng Ning

“…In order to improve the operating rate of discrimination, a continuous projection algorithm (SPA) was used to extract the characteristic wavelengths of the fluorescence spectra and hyperspectral data of pesticide residues, and algorithms such as the least-squares support vector machine (LSSVM) algorithm and least partial squares regression (PLSR) were used to build a quantitative model, while algorithms such as the convolutional neural network (BPNN) algorithm and decision tree algorithm (CART) were used to build a qualitative model. …”
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Multi-Vehicle Object Recognition Method Based on YOLOv7-W by Xin Liu, Jingbin Zhao, Zhi Zhang, Rongxing Wu, Xun Li

“…Analysis of the XUPEI-CAR experimental dataset reveals significant variations in features across different traffic flow densities. To improve the matching accuracy of prior frames, the k-means++ clustering algorithm is employed to optimize the prior frame parameters. …”
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Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy by Wang Liangliang, Peng Jinshuan, Shao Yiming

“…The IRS- GA- CO,which not only lifted the coupling between all disciplines to improve the search most probable point,the burden of system- level optimizer also can be significantly reduced. …”
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YOLO-RDM: Innovative Detection Methods for Eggplants and Stems in Complex Natural Environment by Qin Liu, Zhibin Zhou, Lu Xiong, Meilian Lu, Jingwen Ouyang

“…Next, the DD-Head structure reparameterization detection head module is integrated, effectively merging deep and shallow information while retaining small-scale target feature information to improve detection accuracy. Finally, the loss function is substituted with the MPDIoU loss, optimizing the bounding box regression algorithm and enhancing convergence speed and regression accuracy. …”
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Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer by Le Zhang, Chunqiu Zheng, Tian Li, Lei Xing, Han Zeng, Tingting Li, Huan Yang, Jia Cao, Badong Chen, Ziyuan Zhou

“…Our results demonstrate that (1) the explored genetic and environmental biomarkers are validated to connect to the CRC by biological function- or population-based evidences, (2) the model can efficiently predict the risk of CRC after parameter optimization by the big CRC-related data, and (3) our innovated heterogeneous ensemble learning model (HELM) and generalized kernel recursive maximum correntropy (GKRMC) algorithm have high prediction power. …”
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Intelligent Dynamic Trajectory Planning of UAVs: Addressing Unknown Environments and Intermittent Target Loss by Zhengpeng Yang, Suyu Yan, Chao Ming, Xiaoming Wang

“…Specifically, the system employs a bidirectional Temporal Convolutional Network (TCN) and Gated Recurrent Unit (GRU) network algorithm with an adaptive attention mechanism (BITCN-BIGRU-AAM) to train a model that incorporates the historical motion trajectory features of the target and motion intention the inferred by a Dynamic Bayesian Network (DBN). …”
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Enhanced engine misfire diagnosis through integration of vibration and acoustic emission signals using artificial neural networks by Mohamed H. Abdelati, M. Mourad, Al-Hussein Matar, M. Rabie

“…After all the features were put into a complete matrix, the selection algorithms chose the most essential ones for classifying the data. …”
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Balancing resource utilization and slice dissatisfaction through dynamic soft slicing for 6G wireless networks by Zeinab Sasan, Siavash Khorsandi

“…This paper presents a comprehensive soft slicing framework that addresses these key challenges by (1) ensuring user-level QoS guarantees, (2) incorporating slice dissatisfaction into the optimization model, (3) implementing a holistic resource management strategy, and (4) supporting hybrid 6G use cases. …”
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