Impact of Phenological and Lighting Conditions on Early Detection of Grapevine Inflorescences and Bunches Using Deep Learning by Rubén Íñiguez, Carlos Poblete-Echeverría, Ignacio Barrio, Inés Hernández, Salvador Gutiérrez, Eduardo Martínez-Cámara, Javier Tardáguila

“…Traditional yield prediction methods are labor-intensive, subjective, and often restricted to advanced phenological stages. …”
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Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction by Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li

“…The model parameters, including the anomaly detection rate (P) and earthquake response time threshold (M), significantly impact the model's predictive capabilities. …”
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Application of QVP Method to Winter Precipitation Observation Based on Polarimetric Radar by Guan Li, Dai Jianhua, Tao Lan, Yin Chunguang, Meng Fanwang

“…Using polarimetric radars in conjunction with thermodynamic information is a promising way for better winter precipitation detection. To explore the microphysical characteristic and the internal structure of winter precipitation over eastern coast of China, the data collected by the WSR-88D polarimetric radar at Nanhui, Shanghai are exploited by the quasi-vertical profile (QVP) method. …”
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Advanced Machine Learning Techniques for Predicting Nha Trang Shorelines by Cheng Yin, Le Thanh Binh, Duong Tran Anh, Son T. Mai, Anh Le, Van-Hau Nguyen, Van-Chien Nguyen, Nguyen Xuan Tinh, Hitoshi Tanaka, Nguyen Trung Viet, Long D. Nguyen, Trung Q. Duong

“…The forecasting performance of the SARIMA model, NNAR model and LSTM model is comparable in both long and short-term predictions. …”
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Implementing GitHub Actions continuous integration to reduce error rates in ecological data collection by Albert Y. Kim, Valentine Herrmann, Ross Barreto, Brianna Calkins, Erika Gonzalez‐Akre, Daniel J. Johnson, Jennifer A. Jordan, Lukas Magee, Ian R. McGregor, Nicolle Montero, Karl Novak, Teagan Rogers, Jessica Shue, Kristina J. Anderson‐Teixeira

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Unlocking Potato Phenology: Harnessing Sentinel-1 and Sentinel-2 Synergy for Precise Crop Stage Detection by Diego Gomez, Pablo Salvador, Jorge Gil, Juan Fernando Rodrigo

“…The study demonstrates the potential of combining SAR and optical data for post-season crop phenology analysis, providing insights that can inform the development of new methods and strategies to enhance on-season crop monitoring and yield forecasting.…”
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A deep learning model for detection and classification of coffee-leaf diseases using the transfer-learning technique by Nabila Mansouri, Hanene Guessmi, Adel Alkhalil

“…Our method involves 195 different pre-trained deep learning models, including real-time models like MobileNet and dense ones like EfficientNet and ResNet for the detection of four different diseases. …”
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Multicentral Agent-Based Model of Six Epidemic Waves of COVID-19 in the Nizhny Novgorod Region of Russian Federation by A. V. Hilov, N. V. Saperkin, O. V. Kovalishena, N. A. Sadykova, V. V. Perekatova, N. V. Perekhozheva, D. A. Kurakina, M. Ju. Kirillin

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State-space modelling for infectious disease surveillance data: Stochastic simulation techniques and structural change detection by Christopher D. Prashad

“…Utilizing COVID-19 surveillance data from the province of Ontario, Canada, we employ Markov Chain Monte Carlo (MCMC) and Sequential Monte Carlo (SMC) methods to detect structural changes and pre-dict future trends in case counts. …”
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Detecting Arctic Icebergs in Sea Ice in L-Band SAR Images Using a Multiscale CFAR Algorithm by Laust Faerch, Wolfgang Dierking, Nick Hughes, Anthony P. Doulgeris

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Photovoltaic fault detection algorithm using ensemble learning enhanced with deep neural network feature engineering by Maryam Parvin, Hossein Yousefi, Behnam Mohammadi-Ivatloo

“…The incorporation of the developed technique led to notable fault detection accuracy enhancement across EL methods, with increase of 4.9 %, 5.3 %, 4.9 %, and 3.4 % in accuracy for detecting line-to-line, open-circuit, short-circuit, and partial shading faults, respectively. …”
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Sea Clutter Suppression Method Based on Ocean Dynamics Using the WRF Model by Guigeng Li, Zhaoqiang Wei, Yujie Chen, Xiaoxia Meng, Hao Zhang

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Experiments on the application of the infrasound method of remote monitoring of snow avalanches in the Khibiny Mountains by A. V. Fedorov, I. S. Fedorov, V. E. Asming, A. Yu. Motorin

“…Visual slope observations are still the main method of avalanche detection. As a result, avalanche statistics, especially in remote mountain areas, remain incomplete. …”
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Analysis and predictive validity of Kelantan River flow using RQA and time series analysis by Abdul Majid Mohammed, M. Hafidz Omar, M. S. M. Noorani

“…The study presents the results of the application of nonlinear and linear time series analysis on the river stream-flow data for flood detection and prediction of future values. The prediction results on a hold-out sample of 2014 data by the methods based on RQA and ARIMA have been compared and it was revealed that the ARIMA model provided a better forecast. …”
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Advances and applications of empirical mode decomposition and its variants in hydrology: A review by CHEN Yunfei, LIU Zuyu, LIU Xiuhua, HE Junqi, ZHENG Ce, MA Yandong

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Climate-driven models reveal temporal trends in Aedes breeding: implications for outbreak preparedness and control interventions by Jewelna Akorli, Stephen K. D. Oware, Derrick Baah Sackitey, Reuben M. Pul, Nukunu E. Akyea-Bobi, Samuel S. Akporh, Godwin K. Amlalo, Joseph H. N. Osei, Helena A. Boakye, Mufeez Abudu, Esinam A. Akorli, Kwadwo K. Frempong, Sellase Pi-Bansa, Millicent Opoku, Samuel K. Dadzie

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Structural health monitoring and evaluation method for an immersed tunnel based on deep learning by Yuhang Wei, Jinfang Hou, Linhu Yang, Bin Li, Zonghao Ma, Zhao Liu, Wenhao Sun, Binlei Wang

“…Abstract The health monitoring of the subsea-immersed tunnels is essential for the early detection of anomalies and the assurance of their long-term operational safety. …”
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Quality Control Technique for Ground-Based Lightning Detection Data Based on Multi-Source Data over China by Yongfang Xu, Yan Shen, Xiaowei Jiang, Fengyun Tian, Lei Cao, Nan Wang

“…The processed lightning data are further merged with CREF and generated a 1 km and 6 min resolution lightning location dataset, which significantly improves the accuracy of ground-based lightning detection and supports operational forecasting of severe convective weather.…”
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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…Quantitative evaluations demonstrate that the proposed method performs well in metrics such as pixel accuracy, recall, F _1 score, and IoU. …”
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MONITORING OF CHILDREN’S CANCER INCIDENCE IN THE REPUBLIC OF DAGESTAN by M. G. Daudova, G. M. Abdurakhmanov, A. G. Gasangadzhieva, T. N. Ashurbekova

“…Aim. Monitoring and forecasting of malignant tumors of the child population of the Republic of Dagestan.Methods. …”
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