Use of refractive aids among adults in a general population by Toke Bek, Bodil Hammer Bech, Ivan Nisted

“…Uncorrected refractive error resulted in a reduction in distance visual acuity of 2.99 ETDRS letters per diopter of hyperopia and of 10.3 ETDRS letters per diopter myopia (p < 0.0001 for both regressions). …”
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Hierarchical Multi-Scale Decomposition and Deep Learning Ensemble Framework for Enhanced Carbon Emission Prediction by Yinuo Sun, Zhaoen Qu, Zhuodong Liu, Xiangyu Li

“…Experiments on four real-world datasets (133,225 observations) demonstrate that our CEEMDAN–CNN–Transformer framework outperforms 12 state-of-the-art methods, achieving a 13.3% reduction in root mean square error (RMSE) to 0.117, 12.7% improvement in mean absolute error (MAE) to 0.088, and 13.0% improvement in continuous ranked probability score (CRPS) to 0.060. …”
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Efficient Hybrid Deep Learning Model for Battery State of Health Estimation Using Transfer Learning by Jinling Ren, Misheng Cai, Dapai Shi

“…The experimental results show that the root mean square error (RMSE) of the model on the NCM and NMC datasets is 0.522% and 0.283%, respectively, with a coefficient of determination (R²) not less than 0.98 and mean absolute percentage error (MAPE) of 0.431% and 0.22%, respectively. …”
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Comparing the effect of pre-anesthesia clonidine and tranexamic acid on intraoperative bleeding volume in rhinoplasty: a machine learning approach by Zahra Asghari Varzaneh, Akram Hemmatipour, Hadi Kazemi-Arpanahi

“…The results revealed that the Linear and Ridge regression algorithms outperformed all other models based on three evaluation metrics: mean absolute error (MAE), mean square error (MSE), and R-squared. …”
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UAV coal-rock recognition and 3D coal seam model dynamic correction technology in open-pit mine by Jie Yuan, Guangwei Liu, Senlin Chai, Weiqiang Guo, Yunlong Huang

“…Field measurements reveal that the average elevation error of the corrected model is 0.34 m, representing a 78.76% reduction in error compared to the initial model.…”
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METHODS FOR 3D INVERSION OF GRAVITY DATA IN INDENTIFYING TECTONIC FACTORS CONTROLLING HYDROCARBON ACCUMULATIONS IN THE EL ZEIT BASIN AREA, SOUTHWESTERN GULF OF SUEZ, EGYPT by A.G.M. Hassan, K.S.I. Farag, A.A.F. Aref, A. L. Piskarev

“…Our study included direct and inverse parameterization sequences that involved analyzing the inputs and outputs within trial-and-error initiations and inverse estimations to assess whether and how much the constraining parameters used in the calculations could achieve the intended aim. …”
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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

“…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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Camera Absolute Pose Estimation Using Hierarchical Attention in Multi-Scene by Xinhua Lu, Jingui Miao, Qingji Xue, Hui Wan, Hao Zhang

“…Compared to the baseline algorithm PoseNet, our algorithm has achieved a 41.1% reduction in translation error and a 61.1% decrease in rotation error, demonstrating superior performance in multi-scene absolute camera pose regression.…”
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Just-in-time updated DBN BOF steel-making soft sensor model based on dense connectivity of key features by Lu Zongxu, Liu Hui, Chen FuGang, Li Heng, Xue XiaoJun

“…According to the actual BOF steel production process data, the prediction accuracy of the terminal carbon content reached 82.0% within the error range of ±0.02%, and the prediction accuracy of the temperature reached 80.0% within the error range of ±10°C.…”
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Stereo Visual Odometry and Real-Time Appearance-Based SLAM for Mapping and Localization in Indoor and Outdoor Orchard Environments by Imran Hussain, Xiongzhe Han, Jong-Woo Ha

“…Substantial improvements in both mapping and localization performance over the traditional approach were demonstrated, with an average error of 0.018 m against the ground truth for outdoor mapping and a consistent average error of 0.03 m for indoor trails with a 20.7% reduction in visual odometry trajectory deviation compared to traditional methods. …”
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Efficient Channel Prediction Technique Using AMC and Deep Learning Algorithm for 5G (NR) mMTC Devices by Vipin Sharma, Rajeev Kumar Arya, Sandeep Kumar

“…Efficient utilisation of adaptive modulation and coding ensures the quality transmission of information bits through the significant reduction in bit error rate (BER). Channel prediction using parametric estimation is not efficient for massive machine-type communication (mMTC) devices under the 5G New Radio (NR). …”
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Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables by Ricardo Caetano, José Manuel Oliveira, Patrícia Ramos

“…Models leveraging these variables achieve up to 12.4% reduction in Normalized Root Mean Squared Error (NRMSE) and 2.9% improvement in Mean Absolute Scaled Error (MASE) compared to models that rely solely on past sales. …”
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Pengolahan Citra Berbasis Video Proccesing dengan Metode Frame Difference untuk Deteksi Gerak by Yovi Apridiansyah, Ardi Wijaya, Pahrizal, Rozali Toyib, Arif Setiawan

“…The test results obtained 16 out of 20 test data that were successfully detected correctly (True Positive), there were 2 test data that resulted in a False Positive error, and 2 test data that resulted in a False Negative error. …”
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Multiple Fano Resonance Based Optical Refractive Index Sensor Composed Of Micro-Cavity and Micro-Structure by Yan Kong, Jianjun Cao, Wenchao Qian, Cheng Liu, Shouyu Wang

“…Adjusted by the micro-cavity thickness and the micro-structure configuration, multiple Fano resonances can be generated potential for refractive index sensing: the sensitivity of 831 nm/RIU and the figure of merit of <inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>600 can be reached according to a single Fano resonance; moreover, spectral interval between double Fano resonances can also be used for refractive index sensing with the sensitivity of 194 nm/RIU but significantly reducing the error due to the environmental changes. Considering the advantages as high sensitivity, narrow Fano resonant peak, high figure of merit and ease of integration, as well as its potential in environmental error reduction, the proposed multiple Fano resonance based optical refractive index sensor is expected to provide new tactics for optical refractive index sensing.…”
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A Hybrid Dropout Method for High-Precision Seafloor Topography Reconstruction and Uncertainty Quantification by Xinye Cui, Houpu Li, Yanting Yu, Shaofeng Bian, Guojun Zhai

“…The experimental results demonstrate significant improvements in the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Peak Signal-to-Noise Ratio (PSNR). …”
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SentiTSMixer: A Specific Model for Sales Forecasting Using Sentiment Analysis of Customer by Partha Ghosh, Subhashis Das, Subhankar Roy, Ankur Bhattacharjee, Agostino Cortesi, Soumya Sen

“…Experimental results on various types of Amazon data show that, depending on the dataset and the specific error detection techniques used, the proposed model delivers a reduction in error ranging from 65% to 99% compared to established models.…”
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The Application of Kalman Filter Algorithm in Rail Transit Signal Safety Detection by Zhinong Miao, Qilong Liao

“…The experiment outcomes demonstrate the noise reduction and object detection capability of the raised model. …”
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Online Core Temperature Estimation for Lithium-Ion Batteries via an Aging-Integrated ECM-1D Coupled Model-Based Algorithm by Yiqi Jia, Lorenzo Brancato, Marco Giglio, Francesco Cadini

“…Validation under extreme conditions (high-rate cycling, aging, and ISCs) demonstrates 60% lower core temperature RMSE during high-rate cycling, a maximum estimation error below 0.9 K, and 58.9% reduction in SOC estimation error under aging conditions versus existing methods. …”
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Forecasting Day-Ahead Electricity Demand in Australia Using a CNN-LSTM Model with an Attention Mechanism by Laial Alsmadi, Gang Lei, Li Li

“…The results show a significant reduction in both Mean Absolute Error and Mean Absolute Percentage Error, confirming the model’s effectiveness. …”
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Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments by Uzair Khan, Mohd Tariq, Arif I. Sarwat

“…The model effectively captures the battery’s dynamic behavior and inherent non-linearity. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) achieved during testing demonstrate promising accuracy and superior prediction. …”
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