Zonal Estimation of the Earliest Winter Wheat Identification Time in Shandong Province Considering Phenological and Environmental Factors by Jiaqi Chen, Xin Du, Chen Wang, Cheng Cai, Guanru Fang, Ziming Wang, Mengyu Liu, Huanxue Zhang

“…Other zones reached optimal timing between late December and late January, all with OA above 95%. …”
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Subjective Air Traffic Complexity Analysis Based on Weak Supervised Learning by Weining ZHANG, Weijun PAN, Changqi YANG, Xinping ZHU, Jianan YIN, Jinghan DU

“…Compared with the K-means algorithm based on Euclidean distance, metric learning improves the optimal silhouette coefficient and Davidson-Boldin index by 31.80% and 12.97%, respectively. …”
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Underwater Target 3D Reconstruction via Integrated Laser Triangulation and Multispectral Photometric Stereo by Yang Yang, Yimei Liu, Eric Rigall, Yifan Yin, Shu Zhang, Junyu Dong

“…At the same time, we propose to optimize the laser place calibration and laser line separation processes, further improving the reconstruction performance of underwater laser triangulation and multispectral photometric stereo. …”
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Enhanced identification of Morganella spp. using MALDI-TOF mass spectrometry by Mathilde Duque, Cécile Emeraud, Rémy A. Bonnin, Quentin Giai-Gianetto, Laurent Dortet, Alexandre Godmer

“…Methods: We applied Machine Learning (ML) algorithms to a collection of 235 clinicial Morganella spp. strains to develop an optimized identification model. …”
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Machine Learning for the estimation of foliar nitrogen content in pineapple crops using multispectral images and Internet of Things (IoT) platforms by Jorge Enrique Chaparro, José Edinson Aedo, Felipe Lumbreras Ruiz

“…In addition, regularization techniques were applied, including cross-validation, feature selection, boost methods, L1 (Lasso) and L2 (Ridge) regularization, as well as hyperparameter optimization. These strategies generated more robust and accurate models, with the multilayer perceptron regressor (MLP regressor) and extreme gradient boosting (XGBoost) algorithms standing out. …”
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The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…These findings provide useful insights for improving the accuracy of soil property retrieval using multi-angle hyperspectral observations.…”
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Construction of a sugar and acid content estimation model for Miliang-1 kiwifruit during storage by LIU Li, YANG Tianyi, DONG Congying, SHI Caiyun, SI Peng, WEI Zhifeng, GAO Dengtao

“…These algorithms are powerful tools for feature selection, and capable of identifying the most informative wavelengths from the hyperspectral data. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…Logistic Regression and Multilayer Perceptron also showed robust results, but SGD was superior in most metrics. For the Rules classifiers, JRip outperformed others due to its iterative rule optimization, whereas OneR's simplicity resulted in the lowest performance. …”
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The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…It is suggested that future research should develop towards more advanced optimisation techniques, such as artificial intelligence algorithms that may additionally improve the precision and efficiency of planning orbital trajectories.…”
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Resource Scheduling for Cloud Data Center Based on Data Mining in Smart Grid by Songtao Peng

“…Since the wide use of virtual technology,the resource use rate in cloud data center has been improved effectively than ever before.However,there is still a large space for improvement due to the resources usually are pre-started and pre-allocated by the user demand rather than the actual needs.In order to allocate available resource more accurately,two algorithms were proposed to meet the needs of the daily use in most of time.The available virtual resources would be arranged according the forecast using the algorithms of hierarchical composition of loading and the peek resources needs would be dynamic allocated using the algorithms of stochastic equilibrium and queuing theory.The results of experiment via the system based upon above theories show that the solution provides a kind of very effective advanced means for the optimal use of resources and energy saves.…”
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Enhancing Model Accuracy of UAV-Based Biomass Estimation by Evaluating Effects of Image Resolution and Texture Feature Extraction Strategy by Yaxiao Niu, Xiaoying Song, Liyuan Zhang, Lizhang Xu, Aichen Wang, Qingzhen Zhu

“…Maize AGB estimation models were established based on SIs only and combination of SIs and TFs using machine learning algorithms. We explored the impacts of spatial resolution and TF_CP on the performance of AGB models and analyzed the potentials of combination of SIs and TFs for improving maize AGB estimation accuracy. …”
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Revolutionizing Clear-Sky Humidity Profile Retrieval with Multi-Angle-Aware Networks for Ground-Based Microwave Radiometers by Yinshan Yang, Zhanqing Li, Jianping Guo, Yuying Wang, Hao Wu, Yi Shang, Ye Wang, Langfeng Zhu, Xing Yan

“…Based on the 7-year (2018–2024) in situ measurements from Beijing, Nanjing, and Shanghai, validation results reveal that AngleNet achieves substantial improvements, with an average R2 of 0.71 and a root mean square error (RMSE) of 10.39%, surpassing conventional models such as LGBM (light gradient boosting machine) and RF (random forest) by over 10% in both metrics, and demonstrating a remarkable 41% increase in R2 and a 10% reduction in RMSE compared to the previous BRNN method (batch normalization and robust neural network). …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…The framework leverages machine learning interpretability tools (Shapley Additive Explanations, SHAP) to optimize input feature selection and employs a grid search strategy for hyperparameter tuning.Results and discussionSystematic validation against independent in-situ measurements demonstrates that the baseline DNN model constructed for the entire region and time period outperforms conventional algorithms including K-Nearest Neighbors, Random Forest, and XGBoost and the standard SMAP SSS product, achieving a reduction of 36.0%, 33.4%, 40.1%, and 23.2%, respectively in root mean square error (RMSE). …”
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Thermal performance enhancement in a solar air heater fitted with flapped V-baffles: Numerical study by Chinnapat Turakarn, Pitak Promthaisong, Teerapat Chompookham

“…The energy costs can be effectively managed by VG as well as improving thermal performance if the VG was optimally designed.The effect of flapped V-baffles (FVB) on thermal performance enhancement in a solar air heater in the turbulent flow regime was numerically investigated. …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…Compared to existing superficial deposit maps, our peat predictions significantly improve the spatial detail of peatlands at the national level, offering new opportunities for land use planning and emission mitigation. …”
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Feasibility of Implementing Motion-Compensated Magnetic Resonance Imaging Reconstruction on Graphics Processing Units Using Compute Unified Device Architecture by Mohamed Aziz Zeroual, Natalia Dudysheva, Vincent Gras, Franck Mauconduit, Karyna Isaieva, Pierre-André Vuissoz, Freddy Odille

“…Motion correction in magnetic resonance imaging (MRI) has become increasingly complex due to the high computational demands of iterative reconstruction algorithms and the heterogeneity of emerging computing platforms. …”
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Belief in building a full-fledged distance learning course in athletic training by Andrii Yefremenko, Illia Shutieiev

“…In particular, the experts mostly agreed with the logic and completeness of the course structure, the expediency of centralised content placement in the cloud environment, the optimality of the selected communication channels (email and cloud services), the clarity of the motor learning algorithm for remote performance by students, the adequacy of the proposed evaluation system and the presence of significant advantages in the use of tablets/smartphones in the educational process. …”
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Distributed Beamforming for Relay Assisted Multiuser Machine-to-Machine Networks by Chen Chen, Lin Bai, Meiping Feng, Minhua Huang, Tian Tian

“…Numerical simulations for the proposed algorithms are presented showing the performance of the proposed schemes is close to that of the optimal scheme with global CSI in terms of bit error rate (BER) criterion.…”
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Acute Appendicitis Remains a Great Mimicker – The Pitfalls in the Differential Diagnosis and Tactics - A Case Report by Georgi Popivanov, Marina Konaktchieva, Vladimir Vasilev, Kirien Kjossev, Marin Penkov, Dimitar Penchev

“…Acute appendicitis (AA) is the most common non-traumatic abdominal emergency. Despite the improved knowledge, experience, and technological advance, its diagnosis remains a challenge. …”
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A Novel Temperature Reconstruction Method for Acoustic Pyrometry Under Strong Temperature Gradients and Limited Measurement Points by Jingkao Tan, Lehang Chen, Na Li, Qulan Zhou, Zhongquan Gao, Jie Zhou

“…Acoustic pyrometry (AP) is a promising methodology for high-quality temperature field reconstruction, which is widely used in the monitoring of atmosphere, room, and furnace. However, most of the existing acoustic reconstruction algorithms are developed and utilized in relatively uniform temperature distributions. …”
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