Improving GOCI ocean color data under high solar-zenith angle over open oceans using neural networks by Xiaoming Liu, Menghua Wang

“…However, in early morning and late afternoon measurements, there are significant errors in GOCI-derived ocean color products as the solar-zenith angle (θ0) goes beyond 70°, especially in autumn and winter seasons. …”
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Optimizing hybrid models for forest leaf and canopy trait mapping from EnMAP hyperspectral data with limited field samples by Nizom Farmonov, Susanne Walden, Eric Martinée, Christian Lampei, Mona Schreiber, Lars Opgenoorth, Anjaharinony Andry Ny Aina Rakotomalala, Tobias Müller, Nina Farwig, Stefan Pinkert, Lucy Saueressig, Annabell Rosemarie Wagner, Robert R. Junker, Jochem Verrelst, Jörg Bendix

“…This study investigates the potential of spaceborne hyperspectral data from the Environmental Mapping and Analysis Program (EnMAP) for mapping key forest vegetation traits such as leaf area index (LAI), leaf chlorophyll content (Cab), leaf mass per area (LMA), specific leaf area (SLA), and leaf water content (Cw) as well as the rarely addressed leaf anthocyanin content (Canth) using a hybrid approach combining radiative transfer calculations and machine learning. …”
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Analysis of Typed Inclusion Dependencies with Null Values by Vladimir S. Zykin, Sergey V. Zykin

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Analysis and optimization of digital agency project activities by Olga Yu. Basharina, Tatiana V. Fer, Irina S. Shilnikova

“…The reorganisation of business processes inherent in the target model allows for a significant reduction in the development time of advertising projects for digital agency clients. Using a centralised data warehouse in the project accounting system eliminates information redundancy, reduces time for data entry and processing, and min imises the probability of errors. …”
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Hybrid Deep Learning Models for Sentiment Analysis by Cach N. Dang, María N. Moreno-García, Fernando De la Prieta

“…Hybrid techniques have shown to be potential models for reducing sentiment errors on increasingly complex training data. This paper aims to test the reliability of several hybrid techniques on various datasets of different domains. …”
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Contrastive Analysis of Concord in Arabic, English, and Indonesian by Supardi Supardi, Abdel Karim Muhammad Hassan Jabal

“…Recognizing the differences in concord among languages will be very important to avoid mistakes in using these languages because concord errors are the most common errors in language use. …”
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Didactic Transposition Analysis on Line and Angle Concepts by Elvina Damayanti, Winda Ramadianti, Rahmat Jumri

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Age-stratified analysis of adverse event signals for clarithromycin: a disproportionality analysis using the FDA Adverse Event Reporting System by Haiyan Mai, Zhenpo Zhang, Yankun Liang, Jingping Zheng, Ling Su

“…Design: A disproportionality analysis was performed using data from the FAERS database. …”
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Resource Time Series Analysis and Forecasting in Large-Scale Virtual Clusters by Yue Lin, Jiamin Wen, Xudong Zhang, Yan Liang, Jianjiang Li

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Multi-Index Assessment and Machine Learning Integration for Drought Monitoring Using Google Earth Engine by Xulong Duan, Rana Waqar Aslam, Syed Ali Asad Naqvi, Dmitry E. Kucher, Zohaib Afzal, Danish Raza, Rana Muhammad Zulqarnain, Yahia Said

“…The framework’s AI-driven error correction and multisensor synergy provide a scalable model for drought applications, such as ecosystem resilience monitoring (integrating thermal and optical analysis) and hydrological modelling (fusing soil moisture, precipitation, and vegetation datasets). …”
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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…However, there is no petrophysical method that can directly evaluate the median grain size of rock in the logging data. The predecessors used natural gamma logging data to calculate the median rock grain size (Md) based on linear and statistical analysis for medium-high porosity and permeability sandstone reservoirs work. …”
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Comparing the Forecast Performance of Advanced Statistical and Machine Learning Techniques Using Huge Big Data: Evidence from Monte Carlo Experiments by Faridoon Khan, Amena Urooj, Saud Ahmed Khan, Abdelaziz Alsubie, Zahra Almaspoor, Sara Muhammadullah

“…To compare the predictive ability of all methods, we split the data into two halves (i.e., data over 1973–2007 as training data and data over 2008–2020 as testing data). …”
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Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model by Hasib Khan, Jehad Alzabut, D.K. Almutairi

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Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study by Xiaolei Lu, Chenye Qiao, Hujun Wang, Yingqi Li, Jingxuan Wang, Congxiao Wang, Yingpeng Wang, Shuyan Qie

“…This study utilizes data captured from sensors embedded in the Biodex dynamometry system and the Vicon 3D motion capture system, highlighting the integration of sensor technology in clinical gait analysis. …”
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Determining the Wave Vector Direction of Equatorial Fast Magnetosonic Waves by Scott A. Boardsen, George B. Hospodarsky, Kyungguk Min, Terrance F. Averkamp, Scott R. Bounds, Craig A. Kletzing, Robert F. Pfaff

“…Abstract We perform polarization analysis of the equatorial fast magnetosonic waves electric field over a 20‐min interval of Van Allen Probes A waveform receiver burst mode data. …”
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Sustainable strengthening of concrete deep beams with openings using ECC and Bamboo: An equation and data-driven approach through abaqus modeling and GEP by Fayiz Amin, Ijaz Ali, Ali Husnain, Muhammad Faisal Javed, Hisham Alabduljabbar, Asher Junaid

“…Initially, the model was validated with experimental data, followed by an analysis of various ECC and bamboo configurations to select the most economical strengthening approach for each material. …”
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APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

“…For the purpose of minimizing the number of churning customers, the company should perform a customer churn analysis. Customer churn analysis is the process of identifying a pattern or trend in churning customers. …”
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Optimizing compressive strength of foamed concrete using stepwise regression by Iman Kattoof Harith, Ehsan Elewy Salman, Mohammed L. Hussien, Ahmed Y. Mohammed, Wissam Nadir

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Deep Learning Autoencoders for Fast Fourier Transform-Based Clustering and Temporal Damage Evolution in Acoustic Emission Data from Composite Materials by Serafeim Moustakidis, Konstantinos Stergiou, Matthew Gee, Sanaz Roshanmanesh, Farzad Hayati, Patrik Karlsson, Mayorkinos Papaelias

“…The autoencoder model reduces the dimensionality of the data while preserving essential features, enabling unsupervised clustering to identify distinct damage states. …”
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A data mining approach for proposing a relationship to predict self-compaction concrete crack width after the self-healing period by Saeid Hosseini, Ali Seyedkazemi, Abdullah Davoudi-Kia, Saman Soleimani Kutanaei

“…This model achieved the lowest errors, with MSE, RMSE, and MAE values of 48.5713, 6.969, and 4.878, respectively, indicating its high accuracy in prediction and error minimization. …”
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