Implementation of Inpatient Medical Records at dr. Reksodiwiryo Hospital: A Qualitative Study by Mutia Rahmi, Ayulia Sari, Sri Siswati

“…The Miles and Huberman model was employed for data analysis, encompassing reduction, display, and conclusion operations. The data validity test employed both source triangulation and method triangulation. …”
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Prediction of Daily Entrance and Exit Passenger Flow of Rail Transit Stations by Deep Learning Method by Huaizhong Zhu, Xiaoguang Yang, Yizhe Wang

“…The results verify that this method accurately predicts the daily entrance passenger flow and daily exit passenger flow of rail transit stations with the prediction error of less than 4.1%. Finally, the proposed model is compared with the linear regression model.…”
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Effects of aging on word position encoding in Chinese reading by Zhiwei Liu, Yan Li, Jingxin Wang

“…Crucially, young adults showed a more pronounced transposed-word effect than older adults, suggesting an age-related reduction in the flexibility of word position coding. …”
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Signal Recognition for English Speech Translation Based on Improved Wavelet Denoising Method by Zhuo Chen

“…Based on this, this paper will improve the traditional wavelet denoising algorithm, abandon the single-threshold judgment of the original traditional algorithm, innovatively adopt the combination of soft threshold and hard threshold, further solve the distortion problem of the denoising algorithm in the process of English speech translation signal recognition, improve the signal-to-noise ratio of English speech recognition, and further reduce the root mean square error of the signal. Good noise reduction effect is realized, and the accuracy of speech recognition is improved. …”
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Testing the Level of Alternative Institutions as a Slowdown Factor of Economic Development: the Case of Montenegro by Mimo Draškovic, Sanja Bauk, Dalia Streimikiene, Veselin Draskovic

“…On the basis of the conducted statistical examines: standard error of the regression estimate, correlation coefficient, and coefficient of determination are calculated on the basis of previously determined regression coefficients and forecast values of the linear function of free variables (factors: a, b, and c). …”
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Modeling and Performance for Seabed Airlift Device Based on Pressure Drop by Zhineng WANG, Junwei ZOU, Weiming LIN, Xiaochuan WANG

“…Finally, an experiment is conducted to validate this new model; the results showed that: 1) The new model aligns well with the experimental data with a maximum error of 17.6%. 2) A high gas flow rate increases the pressure drop but reduces the solid fraction. …”
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Effect of Public Health Care Expenditure on Malaria Incidence in Uganda. by Mugabe, Andrew

“…On the contrary, malaria incidence is increased in the long term by female-headed households and GDP per capita, though both factors lead to a short-term decrease, albeit at a slower initial rate. The error correction term (ECT) coefficient, -0.130, was statistically significant at the 1% level. …”
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A data-driven control method for ground locomotion on sloped terrain of a hybrid aerial-ground robot by Xinhang Xu, Yizhuo Yang, Muqing Cao, Thien-Minh Nguyen, Kun Cao, Lihua Xie

“…Then, we design a sliding mode controller using these predictions and establish its input-to-state stability and error bounds. Experiments show improvements of the proposed neural network in training speed and robustness over a baseline ReLU network, and a 40% reduction in tracking error compared to a baseline PID controller.…”
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Enhanced load frequency regulation in microgrids with renewable energy sources and electric vehicles by Imran Khan, Suheel Abdullah Malik, Amil Daraz, Baitullah Bareer

“…Simulation results show that the (I-P) cascaded PDN controller significantly outperforms existing controllers, such as PID, and PI-based models, by reducing frequency deviations, improving settling time, and minimizing overshoot and error indices. There is notable 77% reduction in overshoot (OSH) and 52% decrease in undershoot (USH) in tie-line power variations. …”
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The artificial intelligence-based agricultural field irrigation warning system using GA-BP neural network under smart agriculture. by Xiying Wang

“…The results reveal that as the number of nodes in the hidden layer increases, the model's Mean Squared Error (MSE) and Relative Error (RE) show a decreasing trend, indicating an improvement in model prediction accuracy. …”
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User Trajectory Prediction in Cellular Networks Using Multi-Step LSTM Approaches: Case Study and Performance Evaluation by Iskandar, Hajiar Yuliana, Hendrawan, Adriel Timoteo, Fabian Rafinanda Benyamin, Naufal Bhanu Anargyarahman

“…Performance evaluation is conducted using metrics like Mean Squared Error (MSE), Mean Absolute Error (MAE), and Average Distance Error to compare the models. …”
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Advanced Numerical Validation of Integrated Electrochemical-Thermal Models for PCM-Based Li-Ion Battery Thermal Management System by Mahdieh Nasiri, Hamid Hadim

“…Incorporating Capric acid (with a phase transition range of 302–305 K) as the PCM, the thermal management model demonstrates significantly improved accuracy over existing models in the literature. Notable error reductions include a 78.3% decrease in the Mean Squared Error (0.477 vs. 2.202), a 53.4% reduction in the Root Mean Squared Error (0.619 vs. 1.483), and a 55.5% drop in the Mean Absolute Percentage Error. …”
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UWB Indoor Localization Based on Artificial Rabbit Optimization Algorithm and BP Neural Network by Chaochuan Jia, Can Tao, Ting Yang, Maosheng Fu, Xiancun Zhou, Zhendong Huang

“…In LOS conditions, the ARO-BP model achieves a localization error of 6.29 cm, representing a 49.48% reduction compared to the 12.45 cm error of the standard BPNN. …”
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Quantum Computing-Accelerated Kalman Filtering for Satellite Clusters: Algorithms and Comparative Analysis by Shreyan Prakash, Raj Bhattacherjee, Sainath Bitragunta, Ashutosh Bhatia, Kamlesh Tiwari

“…Our quantum computing-based approach achieves a significant improvement in prediction accuracy and a reduction in mean absolute error compared to classical Kalman filtering techniques. …”
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Energy harvesting enhancement: A roadmap for systematically tuning controllers applied on synchronous generators of wind turbines by John Breno Santos Freitas, Felipe Augusto Silva Martins, Vinicius Foletto Montagner, Paulo Jefferson Dias de Oliveira Evald

“…Compared to the tenth algorithm in the rank, the ALO-based controller ensured a reduction of 96.78% and 90.27% of mean absolute error and root mean squared error, respectively. …”
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Optimization of the Backstepping Control Parameters of an Active Electrohydraulic Suspension to Improve Passenger Comfort and Road Handling by Rachid Fattah, Jean-Pierre Kenne, Khalid Benjelloun, Ahmed Chebak

“…The optimization process considers worst-case road disturbances, leading to a 79.5% reduction in tracking error, a 44.7% decrease in VDV, and a 51.2% improvement in Crest Factor, complying with ISO 2631 standards. …”
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Optimizing load demand forecasting in educational buildings using quantum-inspired particle swarm optimization (QPSO) with recurrent neural networks (RNNs):a seasonal approach by Sunawar Khan, Tehseen Mazhar, Tariq Shahzad, Tariq Ali, Muhammad Ayaz, Yazeed Yasin Ghadi, EL-Hadi M. Aggoune, Habib Hamam

“…Performance indicators, including Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE), were used to assess the models. …”
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Network Coding-Enhanced Polar Codes for Relay-Assisted Visible Light Communication Systems by Congduan Li, Mingyang Zhong, Yiqian Zhang, Dan Song, Nanfeng Zhang, Jingfeng Yang

“…Simulation results demonstrate a significant reduction in bit error rate (BER) compared to uncoded transmission, with a coding gain of at least 5 dB. …”
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Predicting Ship Waiting Times Using Machine Learning for Enhanced Port Operations by Min-Hwa Choi, Woongchang Yoon

“…Shapley additive explanation (SHAP)-based feature selection is typically applied to enhance interpretability, and its effect is compared with principal component analysis-based dimensionality reduction and nonselection methods. The XGBoost Regressor (XGBR) is optimized using genetic-algorithm-based hyperparameter tuning, reducing mean squared error (RMSE) from 20.9531 to 19.6387, mean absolute error (MAE) from 13.6821 to 12.6753, and improving coefficient of determination (R2) from 0.2791 to 0.2949. …”
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Optimizing Methanol Injection Quantity for Gas Hydrate Inhibition Using Machine Learning Models by Mohammed Hilal Mukhsaf, Weiqin Li, Ghassan Husham Jani

“…R²), mean absolute error (MAE), and root mean square error (RMSE), were KNN < DT < RF < XGBoost. …”
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