FOLU-Net: A novel framework using long short-term memory networks to predict future forestry and other land use by Sanchali Banerjee, Paige T. Williams, Randolph H. Wynne

“…The combined land cover prediction framework, titled Forestry and Other Land Use Neural Network (FOLU-Net), enables predictions of land use change without the need for potentially error-prone land use classifications at each prior time step necessitated by approaches such as Markov chain analysis. …”
Get full text

Identifying the Dimensions of Degraded Impact Structures Using Digital Elevation Models: A Proof of Concept for Silicate Planets by Connor J. Anderson, James B. Garvin, Devin R. McClain, Scott S. Sinno, Katherine A. Melocik, Compton J. Tucker

“…The most reliable predictions were achieved using the 12 m TanDEM-X data set with an estimated error ≤16%. We then achieved an estimated error ≤8% when applying the algorithm to three Martian peak ring impact structures (Kepler, Lowell, and Lyot) using 200 m resolution DEMs, and 1%–13% when applied to a 600 m resolution DEM of the Mead multi-ringed impact structure on Venus. …”
Get full text

Degradation and Migration Characteristics and Water‐Inrush Mechanism of Overburden Roof Under High‐Intensity Mining by Min Cao, Shangxian Yin, Xu Wang, Shuqian Li, Qixing Li, Yulong Di

“…For 90% of the predicted data, the error rate of the BP neural network model was less than 0.5%, with an average error of approximately 3%. (2) Through two similar simulation tests, where only the mining height of the coal seam (3 and 6 m) was varied while controlling other variables, it was concluded that higher mining heights lead to more severe damage and obvious fracture development in overlying rock. …”
Get full text

MODELING HYPERTENSION DISEASE RISK IN INDONESIA USING MULTIVARIATE ADAPTIVE REGRESSION SPLINE AND BINARY LOGISTIC REGRESSION APPROACHES by Nur Chamidah, Ardana Tegar Hendrawan, Figo Surya Ardiyanto, Martha Sayyida Hammami, Nurul Izzah, Salsabila Niken Hariadi

“…The analysis shows the Apparent Error Rate (APPER) for MARS is 84.706%, while for binary logistic regression it is 80%, indicating MARS is better at classifying hypertension data in Indonesia. …”
Get full text

Transfer Learning for Photovoltaic Power Forecasting Across Regions Using Large-Scale Datasets by Seongho Bak, Sowon Choi, Donguk Yang, Doyoon Kim, Heeseon Rho, Kyoobin Lee

“…It reduces the mean absolute percentage error by up to 38.8% compared with models trained solely on the target data. …”
Get full text

Machine learning assisted CFD optimization of fuel-staging natural gas burners for enhanced combustion efficiency and reduced NOx emissions by Muhammad Mubashir, Dekui Shen, Habib Kraiem, Aymen Flah, Nahar F. Alshammari, Muhammad Mubashar Hanif

“…A Support Vector Regression-based model was trained on CFD-generated data to guide design modifications and reduce reliance on trial-and-error experimentation. …”
Get full text

A New Approach for Quantification of Finger Angles with Applications in Rehabilitation and Medical Assessment by Marius Turnea, Andrei Gheorghita, Irina Duduca, Mariana Rotariu

“…Experimental results analysis revealed a maximum approximation error of approximately 3% after implementing a rigorous calibration procedure, using a classical reference method. …”
Get full text

Accuracy of Vegetation Height and Terrain Elevation Derived from Terrestrial Ecosystem Carbon Inventory Satellite in Forested Areas by Zhao Chen, Sijie He, Anmin Fu

“…Finally, we systematically evaluated the influence of multiple factors on estimation accuracy. Our analysis revealed that TECIS-derived ground and canopy height estimates exhibited mean errors of 0.7 m and −0.35 m, respectively, with corresponding root mean square error (RMSE) values of 3.83 m and 2.70 m. …”
Get full text

Relationship of Compliance of Personal Protective Equipment Usage and Housekeeping with Near Miss in Nurses by Angela Tesalonika Oktavera, Innaha Ilma Wardaya

“…Respondents were 53 nurses. The research data presented in the form of frequency distribution, cross tabulation, and correlation analysis. …”
Get full text

Logistics demand prediction using fuzzy support vector regression machine based on Adam optimization by Jing Quan, Yiwen Peng, Liyun Su

“…Our analysis reveals that all three models exhibit high predictive accuracy. …”
Get full text

Introduction of self-control of enterprise information system through accounting documentation process of by K.О. Volskа

“…The article proposes to implement the self-control at the input of the information system, when entering the data of the primary documents into the database, as there is a high probability of occurrence of errors right here.…”
Get full text

Wind vector retrieval from Gaofen-3 SAR imagery using the method of iterative line fitting in image power spectrum domain by Xuetong Xie, Jinlan Zhang, Yan Zheng, Kehai Chen

“…Experimental results indicate that the root mean square error (RMSE) of the retrieved wind direction is 17.10°. …”
Get full text

Quantifying motion blur by imaging shock front propagation with broadband and narrowband X-ray sources by Kathryn J. Harke, Michael R. Armstrong, David Martinez, Jonathan Lind, Mukul Kumar

“…Abstract Time-integrated radiography using MeV Bremsstrahlung X-ray sources is the norm for imaging during system-level testing of components and structures under dynamic condition. One source of error in the analysis of the time-integrated radiography data sets stems from motion blur which smears out sharp interfaces to a greater degree with longer exposure times, which become necessary to provide sufficient signal-to-noise with low X-ray penetration of objects of interest. …”
Get full text

Nexus Between Economic Growth, Renewable Energy, Industry Value Added and CO2 Emissions in ASEAN by M. Silahul Mu’min, Indah Susilowati, Hanny Qudsyina, Hesti Asri Wahyuni, Suci Rismawati, Hapsari Ayu Kusumawardhani, Md. Ruyel Miah

“…This study uses the vector error correction model (VECM) for analysis. The estimation results show that CO2 emissions are only influenced by the CO2 variable itself in the previous period in the short term. …”
Get full text

Semantic segmentation framework for atoll satellite imagery: An in-depth exploration using UNet variants and Segmentation Gym by Ray Wang, Tahiya Chowdhury, Alejandra C. Ortiz

“…However, identifying an appropriate segmentation approach for geoscience research remains challenging, often relying on trial-and-error experimentation for data preparation, model selection, and validation. …”
Get full text

Steering through the landscape: a study on entrepreneurs' perceptions of business environments by Gelmar García-Vidal, Laritza Guzmán-Vilar, Alexander Sánchez-Rodríguez, Reyner Pérez-Campdesuñer, Rodobaldo Martínez-Vivar

“…The study applied categorical principal component analysis (CATPCA) to identify the component structure of social capital by considering the ordinal and nominal nature of the data. …”
Get full text

The Successful Prediction of Waterflooding Using a Feed-Forward Algorithm by Qunazatul Shima Batubara*, Tomi Erfando

“…The statistical analysis value is 0.906139 for training and 0.899525 for testing data. …”
Get full text

Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control by Laila Nur Azizah, Adji Achmad Rinaldo Fernandes, Ni Wayan Surya Wardhani

“…This model is applied to secondary and simulated data with various scenarios to determine the best model. …”
Get full text

Prediction of permeability and effective porosity values using ANN in Maleh field by Mohammed Essa Nassani, Ali Alaji

“…The training phase achieved a minimum mean square error of 0.00001 within 58 seconds over 12,000 cycles, delivering a 100% recognition rate for the training data. …”
Get full text

Impact of mental fatigue on tennis players’ attention and groundstroke performance by Cenk Öztürker, Asuman Şahan, Kemal Alparslan Erman

“…Paired samples t-test and Wilcoxon test were used for pairwise comparisons of normally and non-normally distributed data, respectively.ResultsPost-test pairwise comparisons showed that the MF intervention significantly increased SAT completion times and SAT error scores (p < 0.001). …”
Get full text