Innovative approaches to beam forming antenna array systems with adaptive Partial Update NLMS algorithms by Zahraa A. Shubber, Thamer M. Jamel, Ali.K. Nahar

“…Using a Uniform Linear Array (ULA) Antennas in a simulation environment, we find that the, in terms of Mean Square Error (MSE), convergence rate, and steady-state error, it is evident that all PU NLMS algorithms (with the exception of Periodic-NLMS) had performed close, and approximately equivalent performance to the full band NLMS algorithms. …”
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NSMO-Based Adaptive Finite-Time Command-Filtered Backstepping Speed Controller for New Energy Hybrid Ship PMSM Propulsion System by Dan Zhang, Suijun Xiao, Hongfen Bai, Diju Gao, Baonan Wang

“…The results of this study demonstrate a significant reduction in speed-tracking overshoot to zero, a substantial decrease in integral squared error by 90.15%, and a notable improvement in response time by 18.6%.…”
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Thermal features prediction in asphalt pavements using ANFIS-based regression by Mohammad Ali Khasawneh, Hiren Mewada, Ahmad Ali Khasawneh, Ansam Adnan Sawalha

“…Model performance was evaluated using mean squared error (MSE), root mean squared error (RMSE), and coefficient of determination (R2). …”
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Self-Weighted Quantile Estimation for Drift Coefficients of Ornstein–Uhlenbeck Processes with Jumps and Its Application to Statistical Arbitrage by Yuping Song, Ruiqiu Chen, Chunchun Cai, Yuetong Zhang, Min Zhu

“…The estimation performance is evaluated using metrics such as mean, standard deviation, and mean squared error (MSE). The simulation results show that the self-weighted quantile estimator proposed in this paper performs well across different metrics, such as 8.21% and 8.15% reduction of MSE at the 0.9 quantile for drift parameter <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>γ</mi></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>κ</mi></semantics></math></inline-formula> compared with the traditional quantile estimator. …”
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Delivering Dual Polarization-Division-Multiplexing Millimeter-Wave Signals at W-Band by One Pair of Antennas by Yifan Chen, Jiangnan Xiao, Ze Dong

“…For simplification of network architecture, apart from being deployed as multiplexer&#x002F;de-multiplexer, two ortho-mode transducer devices are used to be a pair of panel antennas at both the transmitter and the receiver sides in the scheme of the short-haul wireless link employing PDM-16QAM signal. The bit error ratio (BER) is less than the new-generation forward-error-correction (eFEC) threshold of 2&#x00A0;&#x00D7;&#x00A0;10^&#x2212;2 with CMA algorithm for equalization.…”
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Construction of a Surface Roughness and Burr Size Prediction Model Through the Ensemble Learning Regression Method by Ali Khosrozadeh, Seyed Ali Niknam, Fatemeh Hajizadeh

“…The model was trained using cutting parameters as inputs and evaluated with performance metrics such as mean absolute error (<i>MAE</i>), mean squared error (<i>MSE</i>), and the coefficient of determination (<i>R</i>²). …”
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Rudraksh: A compact and lightweight post-quantum key-encapsulation mechanism by Suparna Kundu, Archisman Ghosh, Angshuman Karmakar, Shreyas Sen, Ingrid Verbauwhede

“…We have done a scrupulous and extensive analysis and evaluation of different design elements, such as polynomial size, field modulus structure, reduction algorithm, and secret and error distribution of an LWE-based KEM. …”
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Atropine (0.05%) for rapid progressive childhood myopia (ARM study) by Rohit Saxena, Vinay Gupta, Himani Thakur, Rebika Dhiman, Thirumurthy Velpandian, Swati Phuljhele, Namrata Sharma

“…Methods: This prospective interventional single-arm clinical trial included children aged between 6–12 years, spherical equivalent refractive (SER) error between − 2 and − 6D, and having documented myopia progression of >0.75D in the preceding year. …”
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Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…Assessment metrics, such as the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE), emphasize the MLP model’s exceptional performance. …”
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Machine learning techniques in monitoring and controlling friction stir welding process: a critical review by Bhardwaj Kulkarni, Saurabh Tayde, Yashwant Chapke, Swapnil Vyavahare, Avinash Badadhe

“…By employing machine learning techniques, the FSW process can become more cost-effective through optimizing process parameters, early detection of defects and tool failures, reduction of waste, and attainment of superior joint properties, all while minimizing the need for extensive trial and error. …”
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Research on channel estimation based on joint perception and deep enhancement learning in complex communication scenarios by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

“…Experimental results demonstrate that the framework achieves significant channel estimation accuracy and robustness across several public datasets and real test scenarios, with the channel estimation error markedly smaller than that of traditional least squares (LS) and linear minimum mean square error (LMMSE) methods. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…This metric considered overestimation and underestimation scenarios compared to ground truth, setting error upper and lower bounds to penalize data points exceeding error tolerance limits. …”
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Initialization improvement and clustering quality evaluation of K-means algorithm by HE Xuansen, HE Fan, YU Hailan

“…The simulation results show that the average λ test statistic of other algorithms is 2.72 times that of this scheme, and the improved clustering error is reduced by 6.04%.…”
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Reducing unnecessary blood tests in elderly care: a quality improvement project by Anavi Prakash, Theik Oo, Soe Aye, Jonathan Cullis

“…There was an observed improvement in the justification of tests, suggesting that clinicians were considering the necessity of the tests before requesting, although this observation was not statistically significant.A key limitation to this project is the small sample size, which may have resulted in type II errors. A larger data set collected over a long duration may provide more reliable results. …”
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Limb Body Wall Complex: First Trimester Ultrasonographic Diagnosis of a Case with Exencephaly and Megacystis by Mert Turğal, Aslıhan Yazıcıoğlu, Özgür Özyüncü, M. Sinan Beksaç

“…Despite the anomaly arises from an error occuring during the embryonic folding, the exact pathophysiological mechanisms are poorly understood. …”
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A thermodynamic inspired AI based search algorithm for solving ordinary differential equations by V. Murugesh, M. Priyadharshini, T. R. Mahesh, Esmael Adem Esleman

“…However, traditional numerical methods such as Euler’s method and the Runge–Kutta method generally suffer from problems like the grid dependency, propagation of errors and not all are applicable to nonlinear and systems that are complex. …”
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Aberration Effects of Planar Layers in Near-Field Multistatic Millimeter-Wave Imaging by Hakseok Ko, Mooseok Jang

“…Furthermore, based on the simulation results, we provide the relation between the thickness and refractive indices of aberrating layers and the positional error and brightness reduction in a reconstructed image. …”
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A Wavelet-based Filtering Algorithm for Enhancing Signal Processing in Coriolis Flow Meters by Khoo David Wee Yang, Ng Zhi Qun, Seah Leong Keey

“…It was also found that FFT with Zero Padding paired with Wavelet Denoising & Cross Correlation yielded a percentage error of < 1% when comparing with the original simulated signal.…”
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Active Noise Control Using a Fuzzy Inference System Without Secondary Path Modelling by Sebastian KURCZYK, Marek PAWELCZYK

“…Appropriate adjustment of the step size is then important to guarantee convergence of the algorithm, obtain small excess mean square error, and react with required rate to variation of plant properties or noise nonstationarity. …”
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Atmospheric Convection and Aerosol Absorption Boost Wildfire Smoke Injection by Rui Xu, Yan Yu, Xianglei Meng, Huiwen Xue, Chuanfeng Zhao, Jintai Lin

“…The new parameterization, optimized and validated by satellite measurements of smoke extinction profiles above active fires, achieves a 10% reduction in root mean square error and an over 95% reduction in mean bias compared to its predecessor. …”
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