Energy efficient design and implementation of approximate adder for image processing applications by Naik Jatothu Brahmaiah, Kumar Kanagala Sateesh, Krishnaiah Kondragunta Rama, Koteswararao Seelam

“…Approximate computing is a new technique that promises to speed up computations while preserving a level of precision suitable for error-tolerant systems such as neural networks and graphics. …”
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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Katia Benamara, Hocine Amimeur, Yanis Hamoudi, Maher G. M. Abdolrasol, Umit Cali, Umit Cali, Taha Selim Ustun

“…The findings reveal a notable reduction in steady-state error, signifying improved stability, and an overall enhancement in the wind power system’s performance. …”
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STOCK PRICE PREDICTION AND SIMULATION USING GEOMETRIC BROWNIAN MOTION-KALMAN FILTER: A COMPARISON BETWEEN KALMAN FILTER ALGORITHMS by Dimas Avian Maulana, A'yunin Sofro, Danang Ariyanto, Riska Wahyu Romadhonia, Affiati Oktaviarina, Mohammad Dian Purnama

“…This research will compare the mean absolute percentage error (MAPE) value between GBM-KF, which was manually computed and computed using the Python library. …”
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Single-Shot Wavefront Sensing in Focal Plane Imaging Using Transformer Networks by Hangning Kou, Jingliang Gu, Jiang You, Min Wan, Zixun Ye, Zhengjiao Xiang, Xian Yue

“…Experimental results in both simulated and real-world conditions indicate that our method achieves a 4.5% reduction in normalized wavefront error (NWE) compared to ResNet34, suggesting improved performance over conventional deep learning models. …”
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Deep learning for predicting porosity in ultra-deep fractured vuggy reservoirs from the Shunbei oilfield in Tarim Basin, China by Ziyan Deng, Dongsheng Zhou, Hezheng Dong, Xiaowei Huang, Shiping Wei, Zhijiang Kang

“…Validation using blind wells from the Shunbei oilfield shows that this approach achieves a 76% reduction in Mean Square Error (MSE) compared to traditional impedance inversion techniques, highlighting its high predictive accuracy. …”
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Determination of cervical vertebral maturation using machine learning in lateral cephalograms by Shahab Kavousinejad, Asghar Ebadifar, Azita Tehranchi, Farzan Zakermashhadi, Kazem Dalaie

“…A ratio-based approach was employed to compute the values of C3 and C4, accompanied by the implementation of an auto_error_reduction (AER) function to enhance the accuracy of landmark selection. …”
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Integrated top-down process and voxel-based microstructure modeling for Ti-6Al-4V in laser wire direct energy deposition process by Yousub Lee, Peeyush Nandwana, Brian Gibson, Paritosh Mhatre, Julio Ortega Rojas, Bhagyashree Prabhune, Aaron Thornton, Joshua Vaughan, Srdjan Simunovic

“…This approach anticipates a significant reduction in data points and computation time and resources. …”
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Turtle shell-inspired exosuit with large output, model-based torque estimation, and load compensation by Chen-Hao LIU, Yu GU, Shuo-Yu WANG, Jin-Gang YI, Tao LIU

“…The closed-loop torque control achieves constant load compensation with a root mean square error (RMSE) of 0.77 N. The EMG results indicate a 38.4% average reduction of muscle activation under a 2.5 kg weight lifting. …”
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Optimization and predictive performance of fly ash-based sustainable concrete using integrated multitask deep learning framework with interpretable machine learning techniques by Bhupesh P. Nandurkar, Jayant M. Raut, Pawan K. Hinge, Boskey V. Bahoria, Tejas R. Patil, Sachin Upadhye, Vikrant S. Vairagade, Sagar D. Shelare

“…This shows a 10–15% increase in the mean-squared error, surpassing existing models. Feature analysis shows that fly ash percentage contributes around 25% to the predictions. …”
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Tracking Poultry Drinking Behavior and Floor Eggs in Cage-Free Houses with Innovative Depth Anything Model by Xiao Yang, Guoyu Lu, Jinchang Zhang, Bidur Paneru, Anjan Dhungana, Samin Dahal, Ramesh Bahadur Bist, Lilong Chai

“…The accuracy of the model in estimating physical depth was assessed using root mean square error (RMSE) between predicted and actual perch frame depths, yielding an RMSE of 0.11 m, demonstrating high precision. …”
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Intradialytic optical assessment of C-mannosyl tryptophan removal using spent dialysate by Joosep Paats, Annika Adoberg, Liisi Leis, Jürgen Arund, Kai Lauri, Merike Luman, Risto Tanner, Jana Holmar, Kristjan Pilt, Ivo Fridolin

“…The concentration of CMW in spent dialysate can be monitored based on spectrophotometric analysis of spent dialysate (r > 0.939, standard error: 0.07 μmol/L) and it is possible to evaluate CMW-based HD adequacy parameters, such as reduction ratio, mass of total removed solute, and TAC without blood sampling. …”
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Solar Radiation Pressure Modeling and Validation for BDS-3 MEO Satellites by Qiuli Chen, Xu Zhang, Chen Wang, Haihong Wang, Chen Ren, Fujian Ma, Xinglong Zhao

“…The orbit results, validated using satellite laser ranging (SLR) observations, show that the radial precision of approximately 3–4 cm can be achieved, with a reduction of the bias by up to 38% and a removal of the systematic error related to the Sun elongation angle in SLR residuals. …”
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A Machine Learning-Based Intelligent Framework for Predicting Energy Efficiency in Next-Generation Residential Buildings by Hafiz Muhammad Shakeel, Shamaila Iram, Richard Hill, Hafiz Muhammad Athar Farid, Akbar Sheikh-Akbari, Farrukh Saleem

“…Further, machine learning models revealed that Random Forest, Gradient Boosting, XGBoost, and LightGBM deliver the lowest mean square error scores of 6.305, 6.023, 7.733, 5.477, and 5.575, respectively, and demonstrated the effectiveness of advanced algorithms in forecasting energy performance. …”
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Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting by Minan Tang, Zhanglong Tao, Jiandong Qiu, Jinping Li, Mingyu Wang, Hongjie Wang, Chuntao Rao

“…Firstly, the initial dimensionality reduction of SCADA data is performed by sparse random projection matrix, which reduces the redundant data. …”
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Design and Implementation of a Comparative Study of Fractional-Order Fuzzy Logic and Conventional PI Controller for Optimizing Stand-Alone DFIG Performance in Wind Energy Systems by Fella Boucetta, Mohamed Toufik Benchouia, Amel Benmouna, Mohamed Chebani, Amar Golea, Mohamed Becherif, Mohammed Saci Chabani

“…This versatility allows for independent tuning of fractional parameters, optimizing the system’s response to transients, steady-state errors, and disturbances. The controller’s flexibility makes it particularly well-suited for nonlinear and dynamically complex stand-alone renewable energy systems. …”
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Digital twin manifesto for the pathology laboratory by Albino Eccher, Fabio Pagni, Massimo Dominici, Luca Reggiani Bonetti, Stefano Marletta, Enrico Munari, Giorgio Cazzaniga, Anil V Parwani, Vincenzo L’Imperio, Angelo Paolo Dei Tos

“…The framework highlights measurable gains such as up to 90% reduction in labeling errors, 20–30% improvements in slide quality, and 30–50% reductions in diagnostic turnaround time. …”
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A quantum-resilient lattice-based security framework for internet of medical things in healthcare systems by Zeyad Ghaleb Al-Mekhlaf, Murtaja Ali Saare, Jalal Mohammed Hachim Altmemi, Mahmood A. Al-Shareeda, Badiea Abdulkarem Mohammed, Gharbi Alshammari, Reem alrashdi, Yasser A. Alkhabra, Ibrahim Alreshidi

“…This paper proposes a quantum-resistant healthcare security framework based on lattice-based cryptographic primitives such as Learning With Errors (LWE), Ring-LWE (RLWE), and Short Integer Solution (SIS). …”
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About the trustworthiness of physics-based machine learning – considerations for geomechanical applications by D. Degen, D. Degen, D. Degen, M. Ziegler, M. Ziegler, O. Heidbach, O. Heidbach, A. Henk, K. Reiter, F. Wellmann, F. Wellmann

“…The usage of these surrogate geomechanical models yields a speed-up of 6 orders of magnitude while maintaining global errors in the range of less than 0.01 <span class="inline-formula">%</span>. …”
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Bidirectional reduced-order electrothermal modeling of power MOSFETs for electric vehicle thermal management applications by Chih-Chun Hsu, Yi-Hsuan Hsieh, Hsiao Chi Tang, Yu-Min Meng, Ming-Shi Huang, Po-Hsuan Tseng, Hai-Han Lu, Hua-Yi Hsu

“…Comprehensive validation using TO-263 packaged MOSFETs under constant power, dynamic cycling, and standardized driving cycles (UDDS, US06, NYCC) demonstrates exceptional accuracy with maximum temperature errors below 5.1 % while achieving over 99 % computational reduction compared to CFD approaches. …”
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Upper Elevational Limit of Vegetation in the Himalayas Identified from Landsat Images by Bo Wei, Yili Zhang, Linshan Liu, Binghua Zhang, Dianqing Gong, Changjun Gu, Lanhui Li, Basanta Paudel

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