Network access and spectrum allocation in next-generation multi-heterogeneous networks by Xiaoqing Dong, Lianglun Cheng, Gengzhong Zheng, Tao Wang

“…Based on this, two kinds of technical paths to solve the complex network selection and spectrum allocation problem are applied in this article. …”
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High-Performance Room-Temperature Terahertz Photodetection Using 2-Dimensional Electron Gas Channel Transport by Mengjuan Liu, Yongzhen Li, Ziyang Ren, Yao Wang, Haiming Zhu, Qinxi Qiu, Nasir Ali, He Zhu, Jiaqi Zhu, Weien Lai, Zhiming Huang, Huizhen Wu

“…However, the state-of-the-art detection strategies are still limited by issues such as low sensitivity, narrow response range, slow response speed, complex fabrication techniques, and difficulties in scaling up to large arrays. …”
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Novel Multi-Scale Attention Generative Adversarial Network for Photovoltaic Solar Cell Defect Inspection Using Electroluminescence Images by Yuanjun Guan, Yang Liu, Jiayi Wang, Tao Wang, Qianchuan Yi, Wenxin Jiang, Xiaopu Gu, Yichen Zhang, Li Zhang, Tianyan Han, Binbing Huang, Lilei Hu

“…This paper presents a novel Multi-Scale Attention Generative Adversarial Network (MAGAN), an innovative GAN-based framework specifically designed for data augmentation in the context of solar cell defect detection. When integrated with automated detection techniques, MAGAN markedly improves the accuracy and efficiency of current models. …”
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Review on development and utilization of offshore renewable energy: An analysis based on a five-dimensional framework by DU Wenjie, CAI Guotian, Qi Xiaoling, WANG Peng, ZHANG Jixiang

“…However, it also faces challenges such as complex environmental conditions, low reliability, and spatial competition. …”
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Extraction of thiacloprid from honey using aqueous biphasic systems based on potassium phosphate and ionic liquids by Marić Aleksandar Z., Jovanov Pavle T., Sakač Marijana B., Radić Bojana Đ., Đermanović Branislava B., Gadžurić Slobodan B.

“…Conventional extraction techniques are often complex and time-consuming, highlighting the need for more efficient methods. …”
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High‐dimensional Bayesian optimization for metamaterial design by Zhichao Tian, Yang Yang, Sui Zhou, Tian Zhou, Ke Deng, Chunlin Ji, Yejun He, Jun S. Liu

“…First, variational autoencoders (VAEs) are employed for efficient dimensionality reduction, mapping complex, high‐dimensional metamaterial microstructures into a compact latent space. …”
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EDHD-FG-XGBoost: Entropy-driven high-dimensional feature gain XGBoost model for short-term wind power prediction and application by Xing Liu, Xingyu Mou, Ying Zhang, Hui Chen, Xin Wang, Xihao Sun, Chengcheng Wang, Ruixiang Shong, Yunfeng Li

“…Wind power prediction is critical for the efficient utilization of wind energy and the stable operation of power grids. …”
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Multi-feature stock price prediction by LSTM networks based on VMD and TMFG by Zhixin Zhang, Qingyang Liu, Yanrong Hu, Hongjiu Liu

“…This paper proposes a novel stock price forecasting model—the Variational Mode Decomposition—Triangulated Maximally Filtered Graph—Long Short-Term Memory (VMD–TMFG–LSTM) combined model—aimed at improving prediction accuracy, stability, and computational efficiency. The proposed model first employs Variational Mode Decomposition (VMD) to decompose the stock price time series into multiple smooth intrinsic mode functions (IMFs), reducing data complexity and mitigating noise interference. …”
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Task Allocation and Path Planning for Collaborative Autonomous Underwater Vehicles Operating through an Underwater Acoustic Network by Yueyue Deng, Pierre-Philippe J. Beaujean, Edgar An, Edward Carlson

“…Dynamic and unstructured multiple cooperative autonomous underwater vehicle (AUV) missions are highly complex operations, and task allocation and path planning are made significantly more challenging under realistic underwater acoustic communication constraints. …”
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Maize Seed Variety Classification Based on Hyperspectral Imaging and a CNN-LSTM Learning Framework by Shuxiang Fan, Quancheng Liu, Didi Ma, Yanqiu Zhu, Liyuan Zhang, Aichen Wang, Qingzhen Zhu

“…This method successfully minimized data dimensionality, reduced variable collinearity, and boosted the model’s stability and computational efficiency. A CNN-LSTM model, built on the selected wavelengths, achieved an accuracy of 95.27% in maize variety classification, outperforming traditional chemometric models like partial least squares discriminant analysis, support vector machines, and extreme learning machines. …”
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A machine learning framework for predicting healthcare utilization and risk factors by Yead Rahman, Prerna Dua

“…A rigorous preprocessing pipeline ensured data integrity, while exploratory data analysis (EDA) guided feature selection, ultimately retaining 20 key variables to capture complex interactions. …”
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Quantitative evaluation of tight gas reservoir classification based on analytic hierarchy process: A case study of Penglaizhen Formation gas reservoir in Xinchang Gas Field by ZHOU Feng,HUANG Shilin,LI Xiaoming,LIAO Kaigui,LI Yong

“…This approach simplifies complex issues and quantifies qualitative aspects, facilitating a more structured evaluation. …”
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Evaluation of empirical relationships in carbonates by developing a 1D mechanical earth model in an oil field in Southwestern Iran by Hadi Ammarloo, Pedram Zoughy, Leili Fatahi Mehraban, Mohammadkazem Amiri

“…Accurate determination of rock mechanical parameters is crucial for safe and efficient drilling, production, and reservoir development in these complex formations. …”
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Advancements in Virtual Bioequivalence: A Systematic Review of Computational Methods and Regulatory Perspectives in the Pharmaceutical Industry by Nasser Alotaiq, Doni Dermawan

“…Background/Objectives: The rise of virtual bioequivalence studies has transformed the pharmaceutical landscape, enabling more efficient drug development processes. This systematic review aims to explore advancements in physiologically based pharmacokinetic (PBPK) modeling, its regulatory implications, and its role in achieving virtual bioequivalence, particularly for complex drug formulations. …”
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Improving battery safety and sustainability through testing material advances and industry developments by Zoltan Weltsch, Tibor Cseke, Robert Kun

“…By examining the interrelationships between material selection (cathode, anode), cell design, testing protocols and regulatory environment, the study highlights the complex challenges and development directions for battery energy storage. …”
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Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks by Guangzhi Han, Haifeng Jiang, Liansheng Lu, Shanshan Ma, Shuo Xiao

“…Hybrid wireless mesh networks are suitable for complex environment communication in coal mine. Mesh clients with application service and routing function in hybrid wireless mesh networks can form a highly robust hybrid network with mesh routers. …”
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Vigorous technique for augmented lifetime in WSNs by Sardar Jaffar Ali, Javed Iqbal, Faheem Khan, Yeon-Kug Moon

“…Existing solutions often address energy efficiency in isolation, failing to consider the complex interplay of factors affecting WSN performance. …”
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Investigate on the Fluid Dynamics and Heat Transfer Behavior in an Automobile Gearbox Based on the LBM-LES Model by Gaoan Zheng, Pu Xu, Lin Li

“…Under high-temperature conditions (such as 100 °C), the diffusion range of the lubricant increases, forming a wider oil film, but its viscosity significantly decreases, leading to greater stirring losses. By optimizing the selection of lubricants and stirring parameters, the efficiency and reliability of the gear transmission system can be further improved, extending its service life. …”
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THE RESULTS OF USE OF THE INITIAL MATERIAL DURING DURUM WINTER WHEAT BREEDING IN THE KUBAN CONDITIONS by A. A. Mudrova, A. S. Yanovsky

“…We revealed the donors of short stem trait among the varieties of own breeding, which have been recommended as initial material during the selection on stability to lodging. The types of cross-breeding used in hybridization have been shown. …”
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Source Term Estimation for Puff Releases Using Machine Learning: A Case Study by John Bartzis, Spyros Andronopoulos, Ioannis Sakellaris

“…Puff movement is highly stochastic due to atmospheric turbulence, intensified by complex urban canopies. This complexity, combined with time limitations, makes advanced computational modeling impractical. …”
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