Predictive model to identify multiple synergistic effects of geriatric syndromes on quality of life in older adults: a hospital-based pilot study by Chien-Chou Su, Yung-Chen Yu, Deng-Chi Yang

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Developing a brain inspired multilobar neural networks architecture for rapidly and accurately estimating concrete compressive strength by Bashar Alibrahim, Ahed Habib, Maan Habib

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Flood susceptibility mapping leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR by Sackdavong Mangkhaseum, Yogesh Bhattarai, Sunil Duwal, Akitoshi Hanazawa

“…The results highlight Random Forest’s superior performance, achieving the highest train and test Area Under the Curve of Receiver Operating Characteristic (AUROC) (1.00 and 0.993), accuracy (0.957), F1-score (0.962), and kappa value (0.914), with the lowest mean squared error (0.207) and Root Mean Squared Error (0.043). …”
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Advanced computational approaches for predicting sunflower yield: Insights from ANN, ANFIS, and GEP in normal and salinity stress environments. by Sanaz Khalifani, Reza Darvishzadeh, Majid Montaseri, Sarvin Zaman Zad Ghavidel, Hamid Hatami Maleki, Mojtaba Kordrostami

“…The GEP model demonstrated the highest precision in predicting sunflower grain yield, with coefficient of determination (R2) values of 0.803 and 0.743, root mean squared error (RMSE) of 4.115 and 4.022, and mean absolute error (MAE) of 3.177 and 2.803 under normal conditions and salinity stress, respectively, during the testing phase. …”
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Stuck Pipe Detection in Oil and Gas Drilling Operations Using Deep Learning Autoencoder for Anomaly Diagnosis by Hasan N. Al-Mamoori, Jialin Tian, Haifeng Ma

“…The proposed model leverages reconstruction error as an anomaly detection metric, effectively distinguishing between normal and stuck cases. …”
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Forecasting Lake Nokoué Water Levels Using Long Short-Term Memory Network by Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

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A novel method for mapping high‐precision animal locations using high‐resolution imagery by Ian J. Axsom, Geoffrey A. Fricker, William T. Bean

“…Together, these tools can expand the application of spatial ecology research to smaller organisms than ever before.…”
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Estimation of Solar Diffuse Radiation in Chongqing Based on Random Forest by Peihan Wan, Yongjian He, Chaoyu Zheng, Jiaxiong Wen, Zhuting Gu

“…Solar diffuse radiation (DIFRA) is an important component of solar radiation, but current research into the estimation of DIFRA is relatively limited. …”
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A parameterized model for tower crane energy consumption was developed based on theoretical formulation and field data by Fan Zhang, Chunli Zhang, Yan Fu, Jun Liu, Jiarui Bu, Peng Duan, Si Chen

“…The best suitable version achieves a Mean Absolute Percentage Error of 25.55%, a Root Mean Square Error (RMSE) of 1036.19 kJ, and a Coefficient of Determination (R2) of 0.83, with just one independent variable. …”
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A hybrid approach to time series forecasting: Integrating ARIMA and prophet for improved accuracy by Sherly A, Mary Subaja Christo, Jesi V Elizabeth

“…This research investigates the critical role of time series forecasting within the burgeoning field of edge computing. …”
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Hydrological performance of gridded meteorological products in Peruvian Altiplano basins by Efrain Lujano, Renny Daniel Diaz, Rene Lujano, Miguel Sanchez-Delgado, Apolinario Lujano

“…However, it is important to evaluate these datasets to quantify their accuracy, error, and bias in estimates. The objective of this research was to assess the hydrological performance of gridded meteorological products in Peruvian Altiplano basins. …”
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Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China by Baoxin Zhao, Jingzhong Zhu, Youbiao Hu, Qimeng Liu, Yu Liu

“…We evaluate the performance of the model separately by statistical training and test dataset metrics, including sensitivity, specificity, accuracy, kappa, mean absolute error (MSE), root mean square error (RMSE), and area under the receiver operating characteristic curve. …”
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A Novel FDIA Model for Virtual Power Plant Cyber–Physical Systems Based on Network Topology and DG Outputs by Shuo Wu, Junhao Gong, Shiqu Xiao, Jiajia Yang, Xiangjing Su

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Reference Model-Based Backstepping Control of Semi-Active Suspension for Vehicles Equipped with Non-Pneumatic Wheels by Jie Chen, Wei Liu, Renkai Ding, Dong Sun, Ruochen Wang

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Experimental and numerical simulation of carbonation-induced corrosion in reinforced concretes by Rasoul Banar, Faramarz Moodi, Ali Akbar Ramezanianpour, Amir Mohammad Ramezanianpour, Pooria Dashti

“…Despite the extensive research on carbonation-induced corrosion (CIC), there is still no consensus on the carbonation front location and the reinforcement corrosion onset. …”
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SYNTHESIS METHODS OF ALGEBRAIC NORMAL FORM OF MANY-VALUED LOGIC FUNCTIONS by A. V. Sokolov, O. N. Zhdanov, O. A. Ayvazian

“…The results could be the basis for further theoretical research and practical applications such as: the development of new cryptographic primitives, error-correcting codes, algorithms of data compression, signal structures, and algorithms of block and stream encryption, all based on the perspective principles of many-valued logic. …”
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MULTI-AXIAL FATIGUE LIFE PREDICTION METHOD OF WORKING ROLL NECK BEARING SECTION BASED ON STRAIN ENERGY by JIN Kai, QIN Xiaofeng, WANG Yong, QU Haixia, LI Shuojie, QIN Zhuoyang, XIE Weihang, MA Feiyang

“…The bearing section of the work roll neck often suffers burnout failure due to bearing seizure, and additive manufacturing is usually used in the field to repair it.Life prediction of the repaired roll neck is the key to predict the safe service of the work roll in the field production and carry out overhaul，but there is a lack of research on the related issues.In view of the above problems, the stress analysis and multi-axis life prediction of the working roll neck bearing section of the four-high mill were carried out.Based on the SIMS model and the influence function method, the rolling force and the stress between the rolls were calculated.The moment balance equation of the roll neck end was established in the bearing section, and the bending stress model of the roll neck bearing section was established.The deformation resistance was regarded as the plastic deformation energy per unit volume to calculate the rolling torque in the deformation zone, and the torsional shear stress model of the roll neck bearing section was established.Using the first strength theory, the equivalent stress was obtained by combining the bending stress and the torsional shear stress.On the basis of proving the calculation accuracy of the model, the multi-axis fatigue model was used to predict the fatigue life of the roll neck bearing section, and compared with the service life of the actual roll in the production line.The results show that the stress calculation model of the working roll neck bearing section of the four-high mill is in line with the actual stress state of the roll neck.The error between the expected service life predicted by the theoretical model and the actual service life is less than 20%, which meets the actual engineering error requirements.…”
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Multi-Scale Spatiotemporal Feature Enhancement and Recursive Motion Compensation for Satellite Video Geographic Registration by Yu Geng, Jingguo Lv, Shuwei Huang, Boyu Wang

“…The experimental results show that the method achieves the inter-frame matching accuracy of 0.8 pixel level, and the georeferencing accuracy error is 3 m, which is a significant improvement compared with the traditional single-frame method, and the method in this paper can provide a certain reference for the subsequent related research.…”
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Simulation of incremental update of electronic document information based on big data technology by Zhiyuan Jin, Qi Zhang, Tiejun Pan

“…Abstract Experimental results show that the algorithm converges faster and has a smaller average error compared to the BP algorithm and the attribute reduction algorithm. …”
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Comparative investigation of bagging enhanced machine learning for early detection of HCV infections using class imbalance technique with feature selection. by Ekramul Haque Tusher, Mohd Arfian Ismail, Abdullah Akib, Lubna A Gabralla, Ashraf Osman Ibrahim, Hafizan Mat Som, Muhammad Akmal Remli

“…The study utilizes a dataset comprising demographic information of 615 individuals suspected of having HCV infection. Additionally, the research employs oversampling and undersampling techniques to address class imbalances in the dataset and conducts feature reduction using the F-test in one-way analysis of variance. …”
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