Motion Control of a Flexible-Towed Underwater Vehicle Based on Dual-Winch Differential Tension Coordination Control by Hongming Wu, Xiong Li, Kan Xu, Dong Song, Yingkai Xia, Guohua Xu

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A review of deep learning in blink detection by Jianbin Xiong, Weikun Dai, Qi Wang, Xiangjun Dong, Baoyu Ye, Jianxiang Yang

“…In recent years, with the rapid development of deep learning, the application of deep learning techniques for precise blink detection has emerged as a significant area of interest among researchers. Compared with traditional methods, the blink detection method based on deep learning offers superior feature learning ability and higher detection accuracy. …”
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Global surface eddy mixing ellipses: spatio-temporal variability and machine learning prediction by Tian Jing, Ru Chen, Chuanyu Liu, Chunhua Qiu, Chunhua Qiu, Cuicui Zhang, Mei Hong

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Semi-Implicit Numerical Integration of Boundary Value Problems by Maksim Galchenko, Petr Fedoseev, Valery Andreev, Endre Kovács, Denis Butusov

“…Constructing semi-implicit numerical methods of higher-accuracy orders is also of interest for further research.…”
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Advancements in digital twin technology and machine learning for energy systems: A comprehensive review of applications in smart grids, renewable energy, and electric vehicle optim... by Opy Das, Muhammad Hamza Zafar, Filippo Sanfilippo, Souman Rudra, Mohan Lal Kolhe

“…There are ample opportunities into further research and development to design a more advanced and digital system as compared to conventional power systems. …”
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Protecting kidney function: from mechanisms to therapeutic targets and traditional Chinese medicine by Yilin Meng, Lu Sui, Ligeer Che, Zihang Jin, Yutong Ma, Li Sun

“…In this review, we provided an overview of current research advances in the mechanisms of renal fibrosis, summarized the promising therapeutic strategies for delaying CKD progression and proposed possible research priorities in the future. …”
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New Predictive Models for the Computation of Reinforced Concrete Columns Shear Strength by Anthos I. Ioannou, David Galbraith, Nikolaos Bakas, George Markou, John Bellos

“…This research work focuses on structural elements that exhibit pronounced strength degradation with plastic deformation and brittle failure characteristics. …”
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Inflow Prediction for Agricultural Reservoirs Using Disaster Prevention Measurement Data: A Comparison of TANK Model and Machine Learning by Bong-Kuk Lee, Joonyoung Choi, Kyoung Jae Lim, Jeongho Han

“…The results of this study demonstrate the potential of machine learning techniques for inflow prediction in agricultural reservoirs and suggest the need for further research on model improvement using various algorithms and input variables.…”
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An Improved Tree Crown Delineation Method Based on a Gradient Feature-Driven Expansion Process Using Airborne LiDAR Data by Jiaxuan Jia, Lei Zhang, Kai Yin, Uwe Sörgel

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Impact of a crop insurance mechanism on credit obtained by smallholders: evidence from “Proagro Mais” in Paraná by Carlos Oñate-Paredes, Vitor Augusto Ozaki

“… Abstract This research analyzes a public compulsory crop-credit public insurance program, Proagro Mais, which is one of the largest agricultural risk management programs in Brazil and is also focused on smallholder producers. …”
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Ensemble Techniques for Robust Fake News Detection: Integrating Transformers, Natural Language Processing, and Machine Learning by Mohammed Al-alshaqi, Danda B. Rawat, Chunmei Liu

“…For textual data, the Random Forest classifier achieved 99% accuracy, outperforming other algorithms. The multimodal approach showed superior performance compared to baseline models, with a 3.1% accuracy improvement over existing multimodal techniques. …”
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Predictive modeling of PMMA-based polymer composites reinforced with hydroxyapatite: a machine learning and FEM approach by Rohit Kumar Singh, Khyati Verma, G. C. Mohan Kumar

“…This research examines the mechanical characteristics of polymer composites (PMMA) that are reinforced with Hydroxyapatite (HAp), with a particular emphasis on the Elastic Modulus and Compressive Strength. …”
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Evolutionary learning in neural networks by heterosynaptic plasticity by Zedong Bi, Ruiqi Fu, Guozhang Chen, Dongping Yang, Yu Zhou, Liang Tian

“…Our method effectively trains spiking and analog neural networks in both feedforward and recurrent architectures, it also achieves performance in tasks like MNIST classification and Atari games comparable to gradient-based methods. Overall, this research extends training approaches for biophysical neuron models, offering a robust alternative to traditional algorithms.…”
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Design and optimization of distributed energy management system based on edge computing and machine learning by Nan Feng, Conglin Ran

“…Future research can further explore how to integrate multiple machine learning algorithms to optimize energy scheduling strategies and improve the system’s adaptability in complex environments.…”
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Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors by Habeeb Balogun, Hafiz Alaka, Christian Nnaemeka Egwim

“…Purpose – This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO2 prediction models. …”
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Use of deep learning-based NLP models for full-text data elements extraction for systematic literature review tasks by Jingcheng Du, Dong Wang, Bin Lin, Long He, Liang-Chin Huang, Jingqi Wang, Frank J. Manion, Yeran Li, Nicole Cossrow, Lixia Yao

“…The three resulting annotated corpora are shared publicly at [ https://github.com/Merck/NLP-SLR-corpora ], to provide training data and a benchmark baseline for the NLP community to further research this challenging task. We then compared three classic Named Entity Recognition (NER) algorithms, namely Conditional Random Fields (CRF), Long Short-Term Memory (LSTM), and the Bidirectional Encoder Representations from Transformers (BERT) models, to assess performance on the data element extraction task. …”
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Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

“…The study highlights the strengths and weaknesses of each model, providing valuable insights into their practical application for network anomaly detection. By comparing different algorithms, this research contributes to advancing the application of machine learning in network security, offering guidance on model selection and optimization for improved detection of cyber threats.…”
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Less complicated adaptive equalization for UWB channels by WANG Yi-ming1, 2 ZHU Hong-bo1

“…A new adaptive equalization technology aiming at the intersymbol and interuser interferences in the multiuser UWB channels was presented specially for DS-UWB/TH-UWB receivers.Its computational complexity and convergence rate were compared with the traditional algorithms.The research results show that the computational complexity of this technology is less than employing RLS method solely and the convergence rate of this technology is farther off employing LMS method solely.…”
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Radiomic Analysis of Contrast‐Enhanced CT Predicts Recompensation in Hepatitis B‐Related Decompensated Cirrhosis by Qiaofeng Chen, Yuanping Fan, Kaini Wu, Tianpan Cai, Chunyu Lan, Mingju Yu, Yunfeng Fu, Qi Zhu, Jianhao Qiu, Xiaodong Zhou

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The Role of Pitch Filter in Pulse-by-Pulse Reoptimization of the LP Synthesis Filter by Allam Mousa

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