Risk−Based Cost−Benefit Optimization Design for Steel Frame Structures to Resist Progressive Collapse by Feng Guo, Xuancen Li, Aiyan Xu, Yuchen Zhang, Wanping Pan

“…Additionally, the integration of the SAP2000 API with Python 3.8 automation streamlines the parameterization process, minimizes manual errors, and enhances the precision and efficiency of the structural design optimization. …”
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Design Optimization and Burst Speed Prediction of a Ti2AlNb Blisk by Yue Guo, Yi-xiong Liu, Yun-wu Wu, Hang Cao, Da Mo

“…The increasing demand for power, fuel efficiency, and safety of aeroengines has called for weight reduction and structural integrity examination of the critical components. …”
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Design and Analysis of an MPC-PID-Based Double-Loop Trajectory Tracking Algorithm for Intelligent Sweeping Vehicles by Zhijun Guo, Mingtian Pang, Shiwen Ye, Yangyang Geng

“…To enhance the precision and real-time performance of trajectory tracking control in differential-steering intelligent sweeping robots and to improve the adaptability of the control algorithm to errors caused by sensor noise, tire slip, and skid, an MPC-PID (Model Predictive Control–Proportional-Integral-Derivative) dual closed-loop control strategy was proposed. …”
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The Impact of Electronic Health Records on Healthcare: Global Benefits and Challenges by Iuliana ŞOLDĂNESCU, Andrei LOBIUC, Mihai DIMIAN

“…Examples of good practices in the use and uptake of electronic health records have shown significant progress in reducing medical errors, continuous monitoring of patients with chronic diseases, collaboration between professionals, and reduced costs. …”
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Leveraging Deep Learning for Robust Structural Damage Detection and Classification: A Transfer Learning Approach via CNN by Burak Duran, Saeed Eftekhar Azam, Masoud Sanayei

“…This study highlights the integration of simulation data into the Deep Learning-based SHM framework, demonstrating that a generalized model created via Joint Learning utilizing FEM can potentially reduce the consequences of modeling errors and operational uncertainties unavoidable in real-world applications.…”
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Torsional Vibration Suppression in Multi-Condition Electric Propulsion Systems Through Harmonic Current Modulation by Hanjie Jia, Guanghong Hu, Xiangyang Xu, Dong Liang, Changzhao Liu

“…A nonlinear dynamic model has been developed, accounting for time-varying meshing stiffness, meshing errors, and multi-harmonic motor excitation. The motor and transmission system models are coupled using torsional angular displacement. …”
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Depressive symptoms and overwork among physicians employed at a university hospital in Japan by Toru Maruyama

“…Introduction: The excessive workload of Japanese hospital physicians is a serious social problem due to effects on their mental health status, as well as the potential for medical errors and lawsuits. The extent of overwork among resident physicians employed at national university hospitals in Japan is unknown and needs to be investigated. …”
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Deep learning-based approach for extracting inflorescence morphology features in cut chrysanthemum by Shanpeng Xu, Jingshan Lu, Yin Wu, Huahao Liu, Fadi Chen, Fei Zhang, Sumei Chen, Weimin Fang, Zhiyong Guan

“…For diameter estimation, mean squared errors (MSE) of 6.605 mm (ligulate) and 2.034 mm (bisexual) were obtained, with coefficients of determination (R2) approaching 0.98. …”
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Estimating energy expenditure from heart rate in older adults: a case for calibration. by Jennifer A Schrack, Vadim Zipunnikov, Jeff Goldsmith, Karen Bandeen-Roche, Ciprian M Crainiceanu, Luigi Ferrucci

“…Although using five calibration measures provided the greatest reduction in the standard deviation of prediction errors (1.08 kcals/min), substantial improvement was also noted with two (0.75 kcals/min).…”
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Global Secular Trend of Gonadal Size in Men: Review and Analysis of Publications by A. Yu. Seroukhov, A. A. Afoko, I. E. Mamaev

“…Standardization of methods of assessment results obtained will help in reducing errors whilst assisting in the analysis of existing tendencies.…”
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Finite-Set Model Predictive Direct Power Control for DFIG with Reduced Number of Voltage Vectors by Felipe S. Guedes, Nady Rocha, Alvaro M. Maciel, Alfeu J. Sguarezi Filho

“…The MPPC is implemented to regulate the stator active and reactive powers of DFIG, minimizing the error between them and their references, with an optimized null vector selection and a reduced number of active vectors, to decrease the computational burden. …”
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Genetic Programming and Standardization in Water Temperature Modelling by Maritza Arganis, Rafael Val, Jordi Prats, Katya Rodríguez, Ramón Domínguez, Josep Dolz

“…This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.…”
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Generalized Sampling Theory in the Quaternion Domain: A Fractional Fourier Approach by Muhammad Adnan Samad, Yuanqing Xia, Nader Al-Rashidi, Saima Siddiqui, Muhammad Younus Bhat, Huda M. Alshanbari

“…We illustrate the practical utility of the QFRFT-based GSE framework with a case study on signal denoising, demonstrating its effectiveness in noise reduction with the Mean Squared Error (MSE), highlighting the improvement in signal restoration.…”
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Low-Complexity Architecture of Orthogonal <italic>N</italic>-Continuous Precoding for Sidelobe Suppression of OFDM Signals and Its Analysis by Hikaru Kawasaki, Fumihide Kojima, Takeshi Matsumura

“…In conclusion, the proposed scheme drastically reduces the conventional precoding&#x2019;s complexity to a level matching that of a fast Fourier transform for OFDM and provides 99 % storage overhead reduction. All its inherent advantages are maintained such as fast, smooth, and symmetrical spectral decay of band-edges, and ideal characteristics of error rate and peak power.…”
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Design and Analysis of Modular Neural Network-Based PI-Controller Ensemble With Karush-Kuhn-Tucker Conditions for Grid-Connected Photovoltaic Systems Under Ground Fault Conditions by Burla Sridhar, Soorya Prakash Shukla, Ritesh Dash, Arpan Dwivedi, G. C. Biswal, Nivedita Singh, Mukesh Kumar Chandrakar, Kalvakurthi Jyotheeswara Reddy, Bhabasis Mohapatra, Binod Kumar Sahu

“…Experimental validation through hardware implementation demonstrates a 45% reduction in steady-state error, a 30% reduction in THD, and improved reactive power compensation and grid synchronization. …”
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Monitoring 5G Backhaul: An In-Band Telemetry Approach for Quality of Service by Eurico Dias, Duarte Raposo, Miguel Luis, Pedro Rito, Susana Sargento

“…The results demonstrate that this approach exhibits minimal measurement errors when assessing the throughput, latency, and Packet Error Rate (PER) of mmWave links. …”
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Denoising of Images using Wavelet Transform by M. Koteswara Rao, G. Chandra Reddy, K. V. Rama Rao

“…Performance is benchmarked against SCAD, Soft thresholding, and Wiener filter methods using Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR) metrics. …”
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Using de novo assembly to identify structural variation of eight complex immune system gene regions. by Jia-Yuan Zhang, Hannah Roberts, David S C Flores, Antony J Cutler, Andrew C Brown, Justin P Whalley, Olga Mielczarek, David Buck, Helen Lockstone, Barbara Xella, Karen Oliver, Craig Corton, Emma Betteridge, Rachael Bashford-Rogers, Julian C Knight, John A Todd, Gavin Band

“…Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. …”
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Study on Photovoltaic Plant Site Selection Models Based on Geographic and Environmental Features by RAO Zhi, YANG Zaimin, YANG Xiongping, LI Jiaming, YANG Ping, WEI Zhichu

“…Compared with the second-best performing informer model， the proposed model achieved reductions of 24.0%， 23.1%， and 28.5% in the mean absolute error， mean absolute percentage error， and root mean square error， respectively. …”
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Prediction of antipsychotic drug efficacy for schizophrenia treatment based on neural features of the resting-state functional connectome by Song Liu, Meng Wang, Weiyi Han, Anran Chen, Xuzhen Liu, Kang Liu, Xue Li, Yi Chen, Luwen Zhang, Qing Liu, Xiaoge Guo, Xiujuan Wang, Ning Kang, Yong Han, Yuanbo Li, Xi Su, Luxian Lv, Bing Liu, Wenqiang Li, Yongfeng Yang

“…The model incorporating resting-state connectome characteristics predicted individual treatment outcomes in both the discovery cohort (prediction vs. truth r = 0.59, mean squared error (MSE) = 0.021) and validation cohort (r = 0.41, MSE = 0.036). …”
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