Investigation of Load Sharing and Dynamic Load Characteristics of a Split Torque Transmission System with Double-Helical Gear Modification by Xuan Liu, Zongde Fang, Haitao Jia, Ning Zhao, Yunbo Shen, Hui Guo, Xijin Zhang

“…The modified tooth surface of a third-stage double-helical gear is obtained by optimizing the amplitude of static loaded transmission error and meshing-in impact via nondominated sorting genetic algorithm-II (NSGA-II). …”
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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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Selection of methods and tools of voltage unbalance reduction within the Eastern part of Siberian integrated power system by V. V. Dikovich, E. M. Katz, O. S. Stremilova

“…The conducted researches give an opportunity to choose technical tools and their installation sites to reduce voltage unbalance in the optimal way, that will help to increase operational reliability of consumers and the electric power system as a whole.…”
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Land Use Transition and Regional Development Patterns Under Shared Socioeconomic Pathways: Evidence from Prefecture-Level Cities in China by Xiaodong Zhang, Mingjie Yang, Rui Guo, Yaolong Li, Fanglei Zhong

“…These findings provide empirical evidence for optimizing land allocation policies during China’s economic transition.…”
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Impact of rainy season on approach trajectories in high-altitude airport terminal maneuvering area: a clustering analysis by Jianxiong Chen, Jingtao Wang, Fan Li, Lin Zou

“…After data preprocessing, a clustering algorithm was used to identify trajectory patterns and detect outlier trajectories. …”
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Performance Analysis of Three-Phase Interleaved Buck-Boost Converter in Wind Energy Maximum Power Point Tracking by Muhammad Qasim Nawaz Sciences, Wei Jiang Sciences, Aimal Khan Sciences

“…The system responds accurately to wind speed changes, ensuring optimal energy extraction across various operational conditions. …”
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Game-based resource allocation in heterogeneous downlink CR-NOMA network without subchannel sharing by Deepa Das, Rajendra Kumar Khadanga, Deepak Kumar Rout, Md. Minarul Islam, Taha Selim Ustun

“…We frame this joint optimization of SU cluster formation and power allocation as a cooperative multi-armed bandit game. …”
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Simplified Model Predictive for Controlling Circulating and Output Currents of a Modular Multilevel Converter by Abolfazl Sheybanifar, Seyed Masoud Barakati

“…In addition, a bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC for one step ahead. A sorting algorithm is used to retain the balancing capacitor voltage in each SM, while the cost function guarantees the regulation of the output current, and MMC circulating current. …”
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Hybrid feature selection for real-time road surface classification on low-end hardware: A machine learning approach by Cong Ngo Van, Duc-Nghia Tran, Ton That Long, Nguyen Gia Minh Thao, Duc-Tan Tran

“…One of the challenges in this field is using optimal datasets and classification models that meet real-time applications on low-end hardware devices. …”
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Energy Optimisation in Aquaponics—Integrating Renewable Source and Water as Energy Buffer for Sustainable Food Production by Abdul Aziz Channa, Kamran Munir, Mark Hansen, Muhammad Fahim Tariq

“…However, the high energy costs associated with maintaining optimal water conditions remain a critical factor in ensuring its long‐term viability. …”
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Estimation of Current RMS for DC Link Capacitor of S-PMSM Drive System by ZHANG Zhigang, CHANG Jiamian, ZHANG Pengcheng

“…The proposed technique simplifies the tedious calculation process of traditional algorithms and guarantees high calculation accuracy, providing guidance for optimizing the selection of DC link capacitors and the design of life monitoring controllers. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…Specifically, we frame the problem as an optimization process with the objective of minimizing a weighted loss function that balances cross-domain discrepancies and sample complexity. …”
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Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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Deep Reinforcement Learning Based Transferable EMS for Hybrid Electric Trains by Yogesh Wankhede, Sheetal Rana, Faruk Kazi

“…To this end, an energy management strategy [EMS] has been developed that optimizes the distribution of energy to reduce the amount of hydrogen required to power the train. …”
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Urban Land-use Features Mapping from LiDAR and Remote Sensing Images using Visual Transformer Network Model by Q. Yuan

“…LiDAR has relatively accurate three-dimensional spatial information, while remote sensing image has rich spectral information. …”
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Sentiment Analysis of Public Satisfaction with the 'INFO BMKG' Application using Naive Bayes, SVM, and KNN by Natasya Aditiya, Pratomo Setiaji, Supriyono Supriyono

“…Thus, Naive Bayes is shown to be the most optimal for sentiment analysis in this study, whereas KNN and SVM showed certain limitations, particularly in efficiency and classification accuracy.…”
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Renal failure in patients with hematological malignancies (literature review) by E. G. Gromova

“…The main reasons for the renal failure development in hematological cancer patients and syndromes that prevent adequate antitumor therapy are considered. Diagnostic algorithm optimization and supportive intensive care of acute renal failure is the key to the successful application of highly effective modern protocols of drug anticancer treatment.A special group is represented by patients suffering from monoclonal gammopathies with acute renal injury and hyperproduction of immunoglobulins free light chains. …”
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Memory consolidation from a reinforcement learning perspective by Jong Won Lee, Min Whan Jung, Min Whan Jung

“…We suggest that memory consolidation might be viewed as a process of deriving optimal strategies based on simulations derived from limited experiences, rather than merely strengthening incidental memories. …”
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An Improved Low-Bit-Rate Image Compression Framework Based on Semantic-Aware Model and Neighborhood Attention by Chengbin Zeng, Liang Zhang

“…In addition, our proposed algorithm effectively mitigates distortions in facial and textual regions while preserving the structural integrity and visual fidelity. …”
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A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
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