Data-Driven Carbon Emission Dynamics Under Ship In-Port Congestion by Weiyu Liu, Bowei Xu, Junjun Li

“…The 2DCNN-SEAM model significantly improves BiLSTM prediction accuracy—reducing Mean Absolute Percentage Error (MAPE) by 18.7% and increasing the R² value to 0.94—by effectively capturing spatiotemporal congestion features. …”
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Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon by Abhishu Oza, Dhaval K. Patel, Bryan J. Ranger

“…Our extensive experiments demonstrate that the Fusion ConvLSTM-Net not only extends the forecast window to 24 hours but also reduces the prediction error rate by approximately 47% compared to the next best model, improves the accuracy of aggregate load forecasts, and prevents model degradation.…”
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Prescribed Performance Bounded-H_∞ Control for Flexible-Joint Manipulators Without Initial Condition Restriction by Ye Zhang, Ruibo Sun, Jie Shang

“…An input control function (ICF) is employed to mitigate the impulse response of the control input, ensuring a smooth transition from zero. Furthermore, the improved tangent-type BLF enables the tracking error to rapidly converge to a small neighborhood of zero. …”
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Modeling of the"thin" structure probability discrepancy distribution in the indications of ADS-B and SSR. Uncompensated latency by I. V. Alipov, V. L. Kuznetsov

“…The estimates made revealed that about 30% of the aircraft, out of the total observed number, report their coordinates with an additional error of 75 m. at an average.…”
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SELFADJUSTING AUTOMATIC CONTROL OF SOWING UNIT by A. Yu. Izmaylov, V. K. Khoroshenkov, E. S. Luzhnova, I. I. Afonina, V. A. Kolesnikova

“…It was noted that for regulation of a fertilizing dose it is necessary to complete the unit with the electric drive, and for error reduction use navigation GLONASS, GPS, Galileo receivers. …”
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Supply chain performance evaluation model for integrated circuit industry based on fuzzy analytic hierarchy process and fuzzy neural network by Chen Qian, Wang Xiangping

“…The results indicate that the error value output after running the validation sample is relatively small. …”
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A note on prognostic accuracy evaluation of regression models applied to longitudinal autocorrelated binary data by Giulia Barbati, Alessio Farcomeni, Patrizio Pasqualetti, Gianfranco Sinagra, Massimo Bovenzi

“…No significant differences in calibration and MSE (Mean Square Error) emerged in the simulation study, that instead confirmed the MTM higher discrimination level. …”
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Quantum memory at nonzero temperature in a thermodynamically trivial system by Yifan Hong, Jinkang Guo, Andrew Lucas

“…Known models of passive quantum error correction similarly exhibit thermodynamic phase transitions to a low-temperature phase wherein logical qubits are protected by thermally stable topological order. …”
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Forecasting Price of Crude Oil Using the Weight Markov Chain (WMC) and ARIMA Model Techniques by محمد محمود فقى حسين

“…We compared two models using metrics such as mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and AIC. …”
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Rational strategies for improving the efficiency of design and discovery of nanomedicines by Xiaoting Shan, Ying Cai, Binyu Zhu, Lingli Zhou, Xujie Sun, Xiaoxuan Xu, Qi Yin, Dangge Wang, Yaping Li

“…Abstract The rise of rational strategies in nanomedicine development, such as high-throughput methods and computer-aided techniques, has led to a shift in the design and discovery patterns of nanomedicines from a trial-and-error mode to a rational mode. This transition facilitates the enhancement of efficiency in the preclinical discovery pipeline of nanomaterials, particularly in improving the hit rate of nanomaterials and the optimization efficiency of promising candidates. …”
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An Ultra-Short-Term Wind Power Prediction Method Based on the Fusion of Multiple Technical Indicators and the XGBoost Algorithm by Xuehui Wang, Yongsheng Wang, Yongsheng Qi, Jiajing Gao, Fan Yang, Jiaxuan Lu

“…For instance, on the Inner Mongolia dataset, the proposed model reduces the mean squared error (MSE) by approximately 11.4% compared to the long short-term memory (LSTM) model, significantly improving prediction accuracy.…”
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The Relationship between Poverty and Environmental Damage in Indonesia: A VECM Analysis by Setyo Tri Wahyudi, Nurul Badriyah, Rihana Sofie Nabella, Kartika Sari, Amalia Rahmawati

“…This study consists time series data covering the period from 2000 to 2023, and utilized the vector error correction model. The short-run findings reveal that economic inequality exacerbates CO2 emissions, as affluent groups exploit resources and disadvantaged community resort to unsustainable practices. …”
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Non-Myopic Beam Scheduling for Multiple Smart-Target Tracking in Phased Array Radar Networks by Yuhang Hao, Zengfu Wang, José Niño-Mora, Jing Fu, Quan Pan, Min Yang

“…This paper addresses beam scheduling for tracking multiple smart targets in phased array radar networks, aiming to mitigate the performance degradation in previous myopic scheduling methods and enhance the tracking performance, which is measured by a discounted cost objective related to the tracking error covariance (TEC) of the targets. The scheduling problem is formulated as a restless multi-armed bandit problem, where each bandit process is associated with a target and its TEC states evolve with different transition rules for different actions, i.e., either the target is tracked or not. …”
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A Survey of Holistic Approaches for Distributed Database Systems: From Conceptual Model to Deployment by Goncalo Carvalho, Jorge Bernardino, Bruno Cabral, Vasco Pereira

“…., Entity-Relationship (ER) diagrams, Unified Modeling Language (UML)) facilitate the transition to physical models, they still fall short when it comes to supporting distributed and multi-layered architectures. …”
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Current Status and Predictors of Patient Safety Culture in Hospitals of Qassim Region, Saudi Arabia by Ayed AlReshidi, Majeda Farajat, Tarek Ibrahim, Abdulaziz Alresheedi, Aliaa Elnefiely, Faisal Alforaih

“…The study has identified four PSC dimensions requiring improvement: teamwork across units, staffing, handoffs and transitions, and nonpunitive response to errors. In general, the categories of new hires and pharmacists were more likely to negatively perceive PSC dimensions. …”
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An improved Harris corner detection method for honeycomb structures by Pengfei Zheng, Wilson Byiringiro, Weiwei Xie, Zhengkai Jiang, Can Cui, Yongjun Wu

“…Test results confirm that the proposed method accurately determines the side lengths and angles with an error margin of less than ±2% compared with manual measurements, effectively evaluating the regularity of the honeycomb. …”
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Numerical simulation and experimental validation of the oleogel formation from grape seed oil and beeswax by Zohreh Baratian Ghorghi, Ali Faezian, Samira Yeganehzad, Mohammad Ali Hesarinejad, Alireza Sheikhi Darani, Marcello Fidaleo, Hashem Ahmadi Tighchi

“…The numerical model demonstrated a maximum relative error of 5.4%, indicating a strong agreement between the numerical results and experimental data. …”
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Optimizing the Architecture of a Quantum–Classical Hybrid Machine Learning Model for Forecasting Ozone Concentrations: Air Quality Management Tool for Houston, Texas by Victor Oliveira Santos, Paulo Alexandre Costa Rocha, Jesse Van Griensven Thé, Bahram Gharabaghi

“…This was evident from evaluating the assessment metrics root mean square error (RMSE), coefficient of determination (R²) and forecast skill (FS). …”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…The study identifies a critical transition at 100–300 samples where error rates drop sharply, with optimal performance requiring more than 600 samples. …”
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Evaluation of subgrid scale models in turbulent large eddy simulations of pumpjet propulsor by Lin Ke, Jinming Ye, Wei He

“…According to the results, as regards the prediction of the open water performance of the pumpjet propulsor containing both front and rear stators, the overall trend obtained by the three subgrid models is similar, and the error between the values predicted by the SL model and the experimental ones is the smallest. …”
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