Conversion to Variable Flow Rate—Advanced Control of a District Heating (DH) System with a Focus on Operational Data by Stanislav Chicherin

“…A combination of flow rate adjustments, bypass line implementation, and selective control strategies for transitional seasons (fall and spring) was modeled and analyzed. …”
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Multiscale Physics of Atomic Nuclei from First Principles by Z. H. Sun, A. Ekström, C. Forssén, G. Hagen, G. R. Jansen, T. Papenbrock

“…Our calculations accurately reproduce—within theoretical error bars—available experimental data for low-lying collective states and the electromagnetic quadrupole transitions in ^{20−30}Ne. …”
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Deformation pressure calculation method for shallow four-track high-speed rail tunnels: A field investigation and theoretical approach by Jianfei Ma, Shaohui He, Xiabing Liu, Jiaxin He

“…The deformation pressure calculated by the derived formula more accurately represents rock pressure than Wang’s formula and loosening pressure theories, especially in Class IV rocks, with error margins ranging from 22.55 % to 38.73 %. The corresponding kd values were provided when calculating the deformation pressure for shallow four-track HSR tunnels using Wang’s formula and loosening pressure theories.…”
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Predicting CO₂ Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally, S. K. Towfek

“…The empirical results show that the GGBERO-optimized BIGRU model produced a Mean Squared Error (MSE) of 1.0 × 10⁻⁵, the best tested approach. …”
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Multi-Agent Deep Reinforcement Learning for Integrated Demand Forecasting and Inventory Optimization in Sensor-Enabled Retail Supply Chains by Yongbin Yang, Mengdie Wang, Jiyuan Wang, Pan Li, Mengjie Zhou

“…Through extensive experiments on large-scale retail datasets incorporating sensor network data, we demonstrate that our method achieves 18.2% lower forecast error and 23.5% reduced stockout rates compared with state-of-the-art baselines. …”
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Improving Weakly-Supervised Video Instance Segmentation by Leveraging Spatio-Temporal Consistency by Farnoosh Arefi, Amir M. Mansourian, Shohreh Kasaei

“…By minimizing the mean absolute error between the eigenvalues of adjacent frames, this loss function promotes smooth transitions and stable segmentation boundaries over time, reducing temporal discontinuities and improving overall segmentation quality. …”
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Precision Agriculture for Dragon Fruit: A Novel Approach Based on Nighttime Light Remote Sensing by Tianhao Zhan, Xiaosheng Liu, Liang Zhong

“…The results demonstrate that the proposed method effectively monitors the dynamics of dragon fruit agriculture, achieving a Kappa Coefficient of 0.72 for area extraction and a Mean Relative Error (MRE) of 8.90% for production estimation. The spatial pattern of dragon fruit production follows a northwest–southeast distribution, with its centroid located in Nanning. …”
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Optimized Predictive Coverage by Averaging Time‐Windowed Bayesian Distributions by Han‐Fang Hsueh, Anneli Guthke, Thomas Wöhling, Wolfgang Nowak

“…With the proposed routine, we explicitly capture the time‐varying impact of model error on prediction uncertainty. The length of the calibration window is optimized to maximize goal‐oriented statistical skill scores for predictive coverage. …”
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Drive-by damage detection based on the use of CWT and sparse autoencoder applied to steel truss railway bridge by Lorenzo Bernardini, Francesco Morgan Bono, Andrea Collina

“…Starting from the average curve of the computed wavelet coefficients, bridge health status is assessed through the use of a sparse autoencoder exploiting multiple train transits and two different damage indices. First of all the Hotelling’s statistic computed at the latent space level, and, secondly, the batch mean absolute reconstruction error. …”
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Robust control of a compliant manipulator with reduced dynamics and sliding perturbation observer by Muhammad Salman, Zhenwei Niu, Rajmeet Singh, Lochan Kshetrimayum, Irfan Hussain

“…Simulation and experimental results validate its superior performance in reducing tracking error and energy consumption, particularly in scenarios where traditional controllers struggle to manage varying stiffness effectively.…”
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Assessment of noise pollution in region 16 of Tehran by Fatema Rahimi, Abolghasem Sadeghi Niaraki, Mostafa Ghodousi

“…Results and discussion: The percentage error between predicted and measured values is very negligible and thus the proposed model can be used to evaluate the pollution of other highways. …”
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Autonomous Maneuvering Decision-Making Algorithm for Unmanned Aerial Vehicles Based on Node Clustering and Deep Deterministic Policy Gradient by Xianyong Jing, Fuzhong Cong, Jichuan Huang, Chunyan Tian, Zikang Su

“…In the NC method, the node membership degree is defined according to the specific characteristics of the maneuvering decision-making problem, and error handling strategies are designed to reduce the number of transitions in the replay database effectively, ensuring that the most typical transitions are retained. …”
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Accounting for alternation in temporal quality analysis in MapBiomas Brazil by Ana Paula Matos, Maria Hunter, Robert Gilmore Pontius, Luis Rodrigo Baumann, Leandro Leal Parente, Laerte Guimarães Ferreira

“…Alternation, a newly defined error component, captures the number of land use transitions a location experiences throughout time. …”
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A Simulation of the Densification Process of NdFeB Bulks by a Modified Drucker–Prager Cap Model by Tao Song, Wenbin Jin, Fang Cheng, Bo Sun, Wenbin Qiu, Nan Liu, Hongliang Ge, Rui Wang, Huayun Mao

“…As the sintering temperature increased, longitudinal compressive stress at the edge of the cross-section transitioned into tensile stress. These results indicate that the developed simulation framework effectively identifies crack-prone areas, enabling data-driven optimization to reduce experimental trial-and-error costs in engineering applications.…”
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Robust JND-Guided Video Watermarking via Adaptive Block Selection and Temporal Redundancy by Antonio Cedillo-Hernandez, Lydia Velazquez-Garcia, Manuel Cedillo-Hernandez, Ismael Dominguez-Jimenez, David Conchouso-Gonzalez

“…To enhance resilience, each bit is redundantly inserted across multiple keyframes selected based on scene transitions. Extensive simulations over 21 benchmark videos (CIF, 4CIF, HD) validate that the method achieves superior performance in robustness and perceptual quality, with an average Bit Error Rate (BER) of 1.03%, PSNR of 50.1 dB, SSIM of 0.996, and VMAF of 97.3 under compression, noise, cropping, and temporal desynchronization. …”
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Accurate ZVS Analysis of a Full-Bridge T-Type Resonant Converter for a 20-kW Unfolding-Based AC-DC Topology by SHUBHANGI GURUDIWAN, Aditya Zade, Hongjie Wang, Regan Zane

“…An energy-based methodology is proposed to determine the minimum zero-voltage switching (ZVS) current and ZVS time during various switching transitions of the T-type bridge. It is shown that the existing literature on the ZVS analysis of the T-type bridge-based resonant dc-dc converter, relying solely on capacitive energy considerations, substantially underestimates the required ZVS current values, with errors reaching up to 50%. …”
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Optimal Dual Control Strategy for Multi-Interconnected Microgrids Under Unintentional Islanding and Fault Scenarios by H. K. Shaker, Ines Mahmoud, Magdi A. Mosa, K. M. Abdel-Latif, A. A. Ali, H. E. Keshta

“…The simulation results demonstrate that the ST-PI outperforms the PI controller under different disturbances in terms of overshoot, undershoot, settling time, and integral time absolute error (ITAE). Additionally, the paper utilizes an advanced bioinspired metaheuristic algorithm, the Newton-Raphson-based optimizer (NRBO), to optimize the design of the proposed controllers via the ITAE as a performance measure.…”
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Understanding the Relationship Between Critical Care Nurses’ Perception of Patient Safety Culture and Adverse Events by Sameer A. Alkubati PhD, Talal Al-Qalah PhD, Basma Salameh PhD, Mohammed Alsabri PhD, Gamil Ghaleb Alrubaiee PhD, Ahmed Loutfy PhD, Sadeq A. Alwesabi PhD, Ahmed H. El-Monshed PhD, Shimmaa M. Elsayed PhD

“…Results The study revealed areas for improvement in patient safety culture, with low positive response rates in staffing (26.6%), non-punitive response to errors (38%), handoffs and transitions (39.4%), teamwork across and within units (42.3%), and overall perception of patient safety (49.3%). …”
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SNUH methylation classifier for CNS tumors by Kwanghoon Lee, Jaemin Jeon, Jin Woo Park, Suwan Yu, Jae-Kyung Won, Kwangsoo Kim, Chul-Kee Park, Sung-Hye Park

“…Results Seoul National University Hospital Methylation Classifier (SNUH-MC) addressed data imbalance using the Synthetic Minority Over-sampling Technique (SMOTE) algorithm and incorporated OpenMax within a Multi-Layer Perceptron to prevent labeling errors in low-confidence diagnoses. Compared to two published CNS tumor methylation classification models (DKFZ-MC: Deutsches Krebsforschungszentrum Methylation Classifier v11b4: RandomForest, 767-MC: Multi-Layer Perceptron), our SNUH-MC showed improved performance in F1-score. …”
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HyQ2: A Hybrid Quantum Neural Network for NextG Vulnerability Detection by Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

“…The small and compact variational circuit of HyQ2 minimizes the noise and errors in the measurement. Our results demonstrate that HyQ2 achieves a high area under the curve (AUC) value of 0.9708 and an accuracy of 95.91%. …”
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