Flood change detection model based on an improved U-net network and multi-head attention mechanism by Fajing Wang, Xu Feng

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Intronomics-MIP: a snakemake pipeline for analyzing multilocus intron polymorphisms in species identification and population genomics by A. Scapolatiello, E. Boscari, L. Schiavon, N. Vitulo, L. Congiu

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A PSO-CNN-LSTM Model for Seismic Facies Analysis: Methodology and Applications by Luyao Liao, Huailai Zhou, Junping Liu, Jie Zhou, Donghang Zhang, Jian Wang

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Identification and the molecular mechanism of novel duck liver-derived anti-inflammatory peptides in lipopolysaccharide-induced RAW264.7 cell model by Xiankang Fan, Laidi Zhang, Yangying Sun, Changyu Zhou, Qiang Xia, Lihui Du, Zhen Wu, Daodong Pan

“…In the lipopolysaccharide-induced RAW264.7 cell model, the release of NO, TNF-α, and IL-6 and the mRNA expression of inflammatory factors (TNF-α, IL-6, COX-2, and NF-κB) were significantly inhibited by these peptides. …”
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Application Analysis of Block Technology Based on Block Chain Computer Model in the False Identification of the Catalog List of the Financial Department of Multinational Companies by Zhihua Hu

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Identification of a novel prognostic and therapeutic prediction model in clear cell renal carcinoma based on Renin-angiotensin system related genes by Qinzheng Chang, Shuo Zhao, Jiajia Sun, Wei Guo, Lin Yang, Laiyuan Qiu, Nianzhao Zhang, Yidong Fan, Jikai Liu

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A Predictive Disease Risk Model for Ankylosing Spondylitis: Based on Integrated Bioinformatic Analysis and Identification of Potential Biomarkers Most Related to Immunity by Wenxin Gao, Ruirui Hou, Yungang Chen, Xiaoying Wang, Guoyan Liu, Wanli Hu, Kang Yao, Yanke Hao

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Comprehensive analysis and identification of energy performance and unsteady two-phase flow patterns based on experiments and comparison between two distinct multiphase flow models by Asad Ali, Jianping Yuan, Qiaorui Si, Shahzad Iqbal, Yuan Shouqi, Yolandani Yolandani, Ibra Fall

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Prediction of Lightweight AIS-Based Ship Trajectories with Spline Interpolation by Jiantao HU, Tianjiao LI, Hui LIU, Shuxin LI, Xu CHENG

“…However, realizing accurate long-time trajectory prediction faces two major problems: One is the integrity of AIS data itself, and the other is the efficiency of prediction models. Therefore, how to effectively deal with the missing AIS data and how to construct a lightweight and efficient prediction model have become the key problems to be solved. …”
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Modeling the Electricity Generation Processes of a Combined Solar and Small Hydropower Plant by Mykola Dyvak, Volodymyr Manzhula, Andriy Melnyk, Nataliia Petryshyn, Tiande Pan, Arkadiusz Banasik, Piotr Pikiewicz, Wojciech M. Kempa

“…This method integrates a metaheuristic algorithm for model structure synthesis, inspired by the behavioral model of a bee colony, with gradient-based methods for parameter identification. …”
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LLM-ACNC: Aerospace Requirement Texts Knowledge Graph Construction Utilizing Large Language Model by Yuhao Liu, Junjie Hou, Yuxuan Chen, Jie Jin, Wenyue Wang

“…An efficient continual learning based on token index encoding is then implemented, guiding the model to focus on key information and enhancing domain adaptability through fine-tuning of the Qwen2.5 (7B) model. …”
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Temporal Evolution of the Hydrodynamics of a Swimming Eel Robot Using Sparse Identification: SINDy-DMD by Mostafa Sayahkarajy, Hartmut Witte

“…In this study, we employ machine learning strategies to investigate the temporal evolution of the system and discover a data-driven model. Three methods were studied, including dynamic mode decomposition (DMD), sparse system identification (SINDy using PySINDy package), and autoencoder neural network (AE NN), as a general function approximator. …”
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Managing Cyber-Security of in-Bank Ecosystem in Conditions of Digitalization by A. D. Bezdelov, E. V. Loginova

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Deriving Early Citrus Fruit Yield Estimation by Combining Multiple Growing Period Data and Improved YOLOv8 Modeling by Menglin Zhai, Juanli Jing, Shiqing Dou, Jiancheng Du, Rongbin Wang, Jichi Yan, Yaqin Song, Zhengmin Mei

“…A citrus yield estimation model was constructed and validated by combining network identification counts with manual field counts. …”
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Intelligent Identification of Tea Plant Seedlings Under High-Temperature Conditions via YOLOv11-MEIP Model Based on Chlorophyll Fluorescence Imaging by Chun Wang, Zejun Wang, Lijiao Chen, Weihao Liu, Xinghua Wang, Zhiyong Cao, Jinyan Zhao, Man Zou, Hongxu Li, Wenxia Yuan, Baijuan Wang

“…To achieve an efficient, non-destructive, and intelligent identification of tea plant seedlings under high-temperature stress, this study proposes an improved YOLOv11 model based on chlorophyll fluorescence imaging technology for intelligent identification. …”
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A Study of Corrosion-Grade Recognition on Metal Surfaces Based on Improved YOLOv8 Model by Hao Chen, Ying Cao, Shengxian Cao, Heng Piao

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Latent Thermal Energy Storage for Cooling Demands in Battery Electric Vehicles: Development of a Dimensionless Model for the Identification of Effective Heat-Transferring Structure... by Volker Dreißigacker, Andrea Gutierrez

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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

“…In summary, the intelligent tea garden pest identification model proposed in this study excels at precise the detection of key pests in tea plantations, enhancing the efficiency and accuracy of pest management through the application of advanced techniques in applied science.…”
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Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images by Zheng Han, Bangjie Fu, Zhenxiong Fang, Yange Li, Jiaying Li, Nan Jiang, Guangqi Chen

“…In this paper, we propose an efficient DCNN-based landslide semantic segmentation method, the so-called Dynahead-YOLO-Otsu, to perform a PSS based on the OOD results. …”
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Multi-Innovation Stochastic Gradient Identification Algorithm for Hammerstein Controlled Autoregressive Autoregressive Systems Based on the Key Term Separation Principle and on the... by Huiyi Hu, Xiao Yongsong, Rui Ding

“…The key term separation principle can simplify the identification model of the input nonlinear system, and the decomposition technique can enhance computational efficiencies of identification algorithms. …”
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