Observation of a rare beta decay of the charmed baryon with a Graph Neural Network by The BESIII Collaboration

“…This work highlights a new approach to further understand fundamental interactions in the charmed baryon sector, and showcases the power of modern machine learning techniques in experimental high-energy physics.…”
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A Novel First-Order Fuzzy Rules-Based Forecasting System Using Distance Measures Approach for Financial Market Forecasting by Shahbaz Gul Hassan, Tran Thi Kieuvan, Shuangyin Liu, Harish Garg, Munawar Hassan, Shafqat Iqbal

“…The precise estimates about finance, atmospheric science, power sector, industries, agriculture, and other science help governments and institutions economically in making the relevant policies regarding import-export, demand, consumption, storage, and local industries. …”
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The Time-Series Production Simulation in Cost Management of New Energy Grid Connection Under the Internet of Things by Shurui Wang

“…The research results indicate that with the penetration of new energy, the system’s idle capacity gradually increases, and the solar power generation also increases, but the utilization hours of solar energy slightly decrease. …”
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Forecasting Shifts in Europe's Renewable and Fossil Fuel Markets Using Deep Learning Methods by Yonghong Liu, Muhammad S. Saleem, Javed Rashid, Sajjad Ahmad, Muhammad Faheem

“…These challenges will be addressed by the bidirectional gated recurrent unit (Bi‐GRU) model, which forecasts power‐generating outcomes more efficiently. The investigation is done over a health data set from 2000 to 2023, including the energy states of the United Kingdom, Finland, Germany, and Switzerland. …”
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The governing system of the Vatican City State under the Fundamental Law of the Vatican City State of 2023 by Agnieszka Romanko

“…This issue required an in-depth analysis due to the fact that the Vatican City State, despite being an absolute monarchy in which the Sovereign enjoys full power, has specialised bodies equipped with legislative, executive and judicial functions, which they always exercise on behalf of the Pope. …”
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An Assessment of the Validity of an Audio-Video Method of Food Journaling for Dietary Quantity and Quality by Emily Jago, Alain P. Gauthier, Ann Pegoraro, Sandra C. Dorman

“…Interclass correlation coefficient (ICC) was calculated for absolute agreement between the two methods to assess interrater reliability. …”
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Asymptomatic Severe Vagal and Sympathetic Cardiac Denervation in Holmes-Adie’s Syndrome by B. Estañol, R. C. Callejas-Rojas, S. Cortés, R. Martínez-Memije, O. Infante-Vázquez, G. Delgado-García

“…HRV in the frequency domain was low with a decrease in the absolute power of HF and LF and a decrease in the sympathovagal balance in supine and standing positions. …”
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Visible Light Broadband Achromatic Metalens Based on Variable Height Nanopillar Structures by Yongyang Li, Haiyang Huang, Cong Zhang, Xiangshuo Shang, Yang Liu, Junyan Hu, Dengyu Shan, Naiyun Tang, Wei Li

“…The multi-level metalens designed by this method achieves a constant and approximate focal length in the visible wavelength range of λ = 450–650 nm, with a polarization-independent absolute focusing efficiency of about 17%, and a numerical aperture (NA) of 0.31 for a lens diameter of 100 μm. …”
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Modeling the Relationship between Rice Yield and Climate Variables Using Statistical and Machine Learning Techniques by Lasini Wickramasinghe, Rukmal Weliwatta, Piyal Ekanayake, Jeevani Jayasinghe

“…Rice harvest and yield data over the last three decades and monthly climatic data were used to develop the prediction model by applying artificial neural networks (ANNs), support vector machine regression (SVMR), multiple linear regression (MLR), Gaussian process regression (GPR), power regression (PR), and robust regression (RR). …”
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Simulation Study on Dynamics of Hydraulic Turbines Used in Drilling Engineering by Yijin Zeng, Jin Wang, Shidong Ding, Haobo Zhou, Yanbin Zang, Fangtao Li

“…Hydroturbines have a very wide range of applications, which are commonly found in wind turbines, water turbines, aero engines, etc. This paper provided a detailed turbine design and a design method of turbine blade shape. …”
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Enhancing the mechanical properties’ performances coconut fiber and CDW composite in paver block: multiple AI techniques with a Performance analysis by G. Uday Kiran, G. Nakkeeran, Dipankar Roy, Sumant Nivarutti Shinde, George Uwadiegwu Alaneme

“…The outcomes from both the training and testing phases demonstrated the strong predictive power of RSM, SVM, GB, ANN, and RF with a criterion used Root Mean square error (RMSE), Mean square error (MSE), Mean Absolute Error (MAE) and correlation coefficient (R). …”
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Comparison of Two Toric IOL Calculation Methods by C. Kern, K. Kortüm, M. Müller, A. Kampik, S. Priglinger, W. J. Mayer

“…The predicted postoperative refraction and toric lens power values were evaluated and compared after postoperative recalculation using the Barrett calculator. …”
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Nonintrusive Load Disaggregation Based on Attention Neural Networks by Shunfu Lin, Jiayu Yang, Yi Li, Yunwei Shen, Fangxing Li, Xiaoyan Bian, Dongdong Li

“…Specifically, the proposed model shows a 13.85% improvement in mean absolute error (MAE), a 21.27% improvement in signal aggregate error (SAE), and a 26.15% improvement in F1 score over existing algorithms. …”
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Theoretical Sufism and Sharia regulations by Halilović Seid

“…Therefore, he will not have credible intuitive power and the most refined ontological and metaphysical secrets of the universe, which are discussed in theoretical Sufism, will not be revealed to him. …”
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Investigating Rotor Conditions on Wind Turbines Using Integrating Tree Classifiers by Bikash Chandra Saha, Joshuva Arockia Dhanraj, M. Sujatha, R. Vallikannu, Mohana Alanazi, Ahmad Almadhor, Ravishankar Sathyamurthy, Kuma Gowwomsa Erko, V. Sugumaran

“…Renewable wind power is productive and feasible to manage the energy crisis and global warming. …”
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Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting by Hyun-Jung Bae, Jong-Seong Park, Ji-hyeok Choi, Hyuk-Yoon Kwon

“…Abstract Electric load forecasting is crucial in the planning and operating electric power companies. It has evolved from statistical methods to artificial intelligence-based techniques that use machine learning models. …”
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Probabilistic forecasting of renewable energy and electricity demand using Graph-based Denoising Diffusion Probabilistic Model by Amir Miraki, Pekka Parviainen, Reza Arghandeh

“…Extensive experiments validate that our proposed method reduces the Continuous Ranked Probability Score (CRPS) by 2.1%–70.9%, Mean Absolute Error (MAE) by 4.4%–52.2%, and Root Mean Squared Error (RMSE) by 7.9%–53.4% over existing methods on two real-world datasets.…”
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An adaptive estimation method to predict thermal comfort indices man using car classification neural deep belief by Alireza Entezari, Fatemeh Mayvaneh, Khosro Rezaie, Fatemeh Rahimi

“…The results showed that the most severe cold temperature stress on PMV index is in the winter and late autumn and UTCI index in January and February are the coldest stress. The power of neural networks, prediction of future performance network (generalized orientation) it simply is not possible and the new model presented in this paper have been restricted Boltzmann machine-based neural networks or neural networks is used deep belief. …”
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ON THE THIN PRACTICAL RATIONALITY AND ITS THICKENINGS by Zenonas Norkus

“…Frankfurt gives handy means to demarcate the bounds of practical rationality too: human agents cannot pretend to achieve the absolute practical rationality in their choices because they in their choices of the preferences (or ethical preferences) cannot rely on arguments having the validating power not coming up to that possessed by the arguments substantiating the choices between the empirical hypotheses. …”
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ON THE THIN PRACTICAL RATIONALITY AND ITS THICKENINGS by Zenonas Norkus

“…Frankfurt gives handy means to demarcate the bounds of practical rationality too: human agents cannot pretend to achieve the absolute practical rationality in their choices because they in their choices of the preferences (or ethical preferences) cannot rely on arguments having the validating power not coming up to that possessed by the arguments substantiating the choices between the empirical hypotheses. …”
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