CHDPL-Net: a lightweight network for Chinese herbal decoction pieces detection by Chuhe Lin, Zhijun Xie, Xing Jin, Hangjuan Lin, Renguang Shan

“…Additionally, a newly designed downsampling module, RDown, replaces conventional downsampling methods to reduce computational overhead, while the adopted upsampling module, DySample, significantly enhances the recovery of detailed features. To further improve lightweight performance, we apply GhostConv to optimize the SPPF and C2F modules and incorporate a novel attention mechanism, EHA, which makes the model more sensitive to color and texture information, mitigating the performance degradation caused by lightweight design. …”
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Remote Sensing Change Detection by Pyramid Sequential Processing With Mamba by Jiancong Ma, Bo Li, Hanxi Li, Siying Meng, Ruitao Lu, Shaohui Mei

“…These enhancements not only accelerate training but also improve the model’s generalization capability. …”
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A Two-Phase and Bi-Level Spatial Configuration Methodology of Shelters Based on a Circular Assignment Model and Evacuation Traffic Flow Allocation by Yujia Zhang, Wei Chen, Guangchun Zhong, Guofang Zhai, Wei Zhai

“…A genetic algorithm and exhaustive approach are programmed to determine the solution of the model in the first and second phases, respectively. …”
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Bandit Algorithms for Efficient Toxicity Detection in Competitive Online Video Games by Jacob Morrier, Rafal Kocielnik, R. Michael Alvarez

“…Using data from the popular first-person action game Call of Duty®: Modern Warfare® III, we show that our algorithm consistently outperforms baseline algorithms that rely solely on individual players’ past behavior, achieving improvements in detection rate of up to 24.56 percentage points or 51.5%. …”
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Power inspection UAV task assignment matrix reversal genetic algorithm by Kai Liu, Meizhao Liu, Ming Tang, Chen Zhang

“…The model is then optimized using two-point crossover and single-point reversal mutation operations, which enhance the UAV unit utility and generate an optimal allocation matrix. …”
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Motion control and singular perturbation algorithms for lower limb rehabilitation robots by Yanchun Xie, Anna Wang, Xue Zhao, Yang Jiang, Yao Wu, Hailong Yu

“…To better assist patients with lower limb injuries in their rehabilitation training, this paper focuses on motion control and singular perturbation algorithms and their practical applications. First, the paper conducts an in-depth analysis of the mechanical structure of such robots and establishes detailed kinematics and dynamics models. …”
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Wafer Defect Classification Algorithm With Label Embedding Using Contrastive Learning by Jeongjoon Hwang, Somi Ha, Dohyun Kim

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Assortment and promotion optimization in a retail chain by Hamed Karimi

“…Overall, the proposed model provides a valuable tool for chain stores to optimize their promotion and assortment strategies, and improve their market competitiveness.…”
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A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network by Kui Liu, Sanyang Liu, Hailin Feng

“…A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. …”
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Optimal Waveform Selection for Robust Target Tracking by Fengming Xin, Jinkuan Wang, Qiang Zhao, Yuhuan Wang

“…This paper proposes a new optimal waveform selection algorithm for intelligent target tracking. …”
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Topology optimization of a cargo gripper design using the minimum effort principle by Gnezdilov S.G.

“…The study emphasizes accounting for varied load scenarios (e.g., sheet tilting) for future refinement. It confirms the algorithm’s effectiveness in simplifying models and highlights iterative refinement for rational topology. …”
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Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning by Shuai Zhou, Shuai Zhou, Shuai Zhou, Shuai Zhou, Zexiang Liu, Zexiang Liu, Zexiang Liu, Haoge Huang, Haoge Huang, Haoge Huang, Hanxu Xi, Xiao Fan, Xiao Fan, Xiao Fan, Yanbin Zhao, Yanbin Zhao, Yanbin Zhao, Xin Chen, Xin Chen, Xin Chen, Yinze Diao, Yinze Diao, Yinze Diao, Yu Sun, Yu Sun, Yu Sun, Hong Ji, Feifei Zhou, Feifei Zhou, Feifei Zhou

“…After training and optimizing multiple ML algorithms, we generated a model with the highest area under the receiver operating characteristic curve (AUROC) to predict short-term outcomes following DCM surgery. …”
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ISAR High Resolution Imaging Algorithm Based on Weighted Adaptive Mixed Norm by Q. Zhang, Q. Q. Chen, G. Xu, J. R. Chi

“…The optimization model takes advantage of mixed norm to achieve fast convergence in the operation, and adopts conjugate gradient descent method and fast Fourier transform operation in the solution, which simplifies the solving process of the optimization problem and improves the operation efficiency of the algorithm. …”
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Optimization of costs in the enterprise. Effective strategies for business by N. Yu. Pracheva

“…The author offers an algorithm of actions for entrepreneurs who are ready to solve the optimization problem in a complex way.…”
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Python-Based Visual Classification Algorithm for Economic Text Big Data by Yihuo Jiang, Xiaomei Guo, Hongliang Ni, Wenbing Jiang

“…In order to improve the classification accuracy and reduce the classification time of the economic text big data visualization classification algorithm, one based on the Pitton algorithm is proposed. …”
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Depth first traversal algorithm for the back-off tree of distributed queuing by Wennai WANG, Yanhe ZHANG, Wei WU, Chen BAI, Bin WANG

“…An analytic model was provided for the conventional distributed queueing (DQ) and its back-off tree operations, followed by a design of improving algorithm based on depth first traversal.Combing the specific analysis of complete binary tree with generalized extension by random tree reconstruction, the performance of proposed algorithm was evaluated on the throughput in both theory and simulation experiment.A theoretic optimal solution of contention slots of DQ frame and a brief description of simulation extension based on the open source NS-3 were presented.The simulation results show that the maximum stationary throughput by the proposed algorithm reaches 70% of the physical capacity of channel.…”
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YOLOv8n-WSE-Pest: A Lightweight Deep Learning Model Based on YOLOv8n for Pest Identification in Tea Gardens by Hongxu Li, Wenxia Yuan, Yuxin Xia, Zejun Wang, Junjie He, Qiaomei Wang, Shihao Zhang, Limei Li, Fang Yang, Baijuan Wang

“…To enable the intelligent monitoring of pests within tea plantations, this study introduces a novel image recognition algorithm, designated as YOLOv8n-WSE-pest. Taking into account the pest image data collected from organic tea gardens in Yunnan, this study utilizes the YOLOv8n network as a foundation and optimizes the original loss function using WIoU-v3 to achieve dynamic gradient allocation and improve the prediction accuracy. …”
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Implementation and Evaluation of Machine Learning Algorithms in Ball Bearing Fault Detection by Stepanić Pavle, Dučić Nedeljko, Vidaković Jelena, Baralić Jelena, Popović Marko

“…Improved versions of the mentioned algorithms were obtained by optimizing their hyperparameters. …”
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A Workflow for Integrated Geological Modeling for Shale Gas Reservoirs: A Case Study of the Fuling Shale Gas Reservoir in the Sichuan Basin, China by Xiaofei Shang, Huawei Zhao, Shengxiang Long, Taizhong Duan

“…The selection and optimization of modeling methods, the innovation and development of modeling algorithms, and the evaluation techniques for model uncertainty are areas where breakthroughs may be possible in the geological modeling of shale gas reservoirs. …”
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Preventing postoperative pulmonary complications by establishing a machine-learning assisted approach (PEPPERMINT): Study protocol for the creation of a risk prediction model. by Britta Trautwein, Meinrad Beer, Manfred Blobner, Bettina Jungwirth, Simone Maria Kagerbauer, Michael Götz

“…Therefore, the planned research project aims to create a prediction model that enables the reliable identification of high-risk patients immediately after surgery based on a tailored machine learning algorithm.…”
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