Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building by Kyung-Won Min, Junhee Kim, Sung-Ah Park, Chan-Soo Park

“…As for the ambient vibration testing, measured structural responses are analyzed by two output-only system identification methods (i.e., frequency domain decomposition and stochastic subspace identification) to estimate modal parameters. …”
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Application of the variation operator in a genetic algorithm for the synthesis of fuzzy controllers by I. V. Kulikova

“…This article studies the problem of increasing the efficiency of fuzzy controller synthesis in a control system using a genetic algorithm. …”
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Multi-layer perceptron-particle swarm optimization: A lightweight optimization algorithm for the model predictive control local planner by Xiaoqing Guan, Tao Hu, Ziang Zhang, Yixu Wang, Yifan Liu, You Wang, Jie Hao, Guang Li

“…This letter reports a lightweight and efficient two-stage solving algorithm for the model predictive control planner. …”
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Decentralized Nonstationary Fuzzy Neural Network with Meta-Learning-Net by Zhen Zhang, Meiling Yu, Hui Jia

“…By integrating a meta-learning network, we further enhance the output strategy of the NFNN, enabling it to adaptively determine the contribution of individual sub-networks. …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…These findings underscore the M-CNN’s effectiveness in sequential well placement optimization, striking an optimal balance between predictive accuracy and computational efficiency. The method’s ability to dramatically reduce processing time while maintaining high accuracy makes it a valuable tool for enhancing oil field productivity and streamlining reservoir management decisions.…”
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A comprehensive recent review and practical insights on the usage of advanced materials and enhancement strategies in thermoelectric applications by Mohamad Darwiche, Jalal Faraj, Khaled Chahine, Ali Shaito, Sary Awad, Mehdi Mortazavi, Mahmoud Khaled

“…The main findings indicate that the strategic use of these advanced materials may significantly increase the efficiency and output power of TEG devices, making them more practical for a wide variety of applications. …”
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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

“…Methods Firstly, a new water surface target dataset was constructed. …”
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Quality Measurement and Optimization Prediction of Urban Waterfront Fitness Space Based on Behavior Simulation by Chunxia YANG, Ruoyao MIN

“…After qualitative and quantitative adjustments, the simulation model is validated, and the final results are obtained through data analysis and indicator output. The above methods are then applied to the quality assessment and optimization prediction for Minsheng Wharf. …”
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SIC based RL for massive MIMO NOMA signal detection for different modulation schemes under diverse channel conditions by Arun Kumar, Aziz Nanthaamornphong, Mohammed H. Alsharif, Mehedi Masud

“…Abstract Massive-multiple input and Multiple Outputs Non orthogonal multiple access (M-MIMO–NOMA) systems require efficient signal detection techniques to mitigate interference and enhance spectral efficiency, especially under diverse channel conditions and varying modulation schemes. …”
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Innovations in bioethanol production: A comprehensive review of feedstock generations and technology advances by Abeer Kazmi, Tahira Sultana, Amir Ali, Aneela Nijabat, Gaojie Li, Hongwei Hou

“…Batch, fed-batch, and continuous fermentation techniques are used, with advances such as immobilized cell reactors and genetic engineering improving output and efficiency. Furthermore, combining enzymatic hydrolysis with fermentation (simultaneous saccharification and fermentation) enhances the conversion of complex carbohydrates to ethanol. …”
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Shortcuts to adiabaticity in anisotropic Bose-Einstein condensates by Chinmayee Mishra, Thomas Busch, Thomás Fogarty

“…Finally, we apply these STA techniques to a unitary engine cycle with a BEC as the working medium. The STA methods significantly enhance the engine’s power output without reducing efficiency and remain highly effective even after multiple consecutive cycles.…”
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Machine Learning for Non-Destructive Prediction of Sunflower Leaf Area by Joao Everthon da Silva Ribeiro, Antonio Gideilson Correia da Silva, Pablo Henrique de Almeida Oliveira, Josiana Micarla da Silva Oliveira, Alessandra Nunes da Silva, John Victor Lucas Lima, Ivan Euzebio da Silva, Ester Dos Santos Coelho, Isaque de Oliveira Leite, Elania Freire da Silva, Toshik Iarley da Silva, Lindomar Maria da Silveira, Aurelio Paes Barros Junior

“…However, its measurement using traditional methods can be limited. The search for non-destructive approaches based on leaf dimensions is essential, and machine learning offers promising alternatives for accurate estimation. …”
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Hyperspectral Imaging for Phenotyping Plant Drought Stress and Nitrogen Interactions Using Multivariate Modeling and Machine Learning Techniques in Wheat by Frank Gyan Okyere, Daniel Kingsley Cudjoe, Nicolas Virlet, March Castle, Andrew Bernard Riche, Latifa Greche, Fady Mohareb, Daniel Simms, Manal Mhada, Malcolm John Hawkesford

“…Accurate detection of drought stress in plants is essential for water use efficiency and agricultural output. Hyperspectral imaging (HSI) provides a non-invasive method in plant phenotyping, allowing the long-term monitoring of plant health due to sensitivity to subtle changes in leaf constituents. …”
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Advancing energy optimization in building systems through multi-scale sensitivity, adaptive modeling, and real-time management by Yaser Issam Hamodi Al-Janabi, Sameer Algburi, Omer Al-Dulaimi, Hassan Falah Fakhruldeen, Azamat Makhmudov, Doaa H. Khalaf, Talib Munshid Hanoon, Feryal Ibrahim Jabbar, Ali Khudhair Al-Jiboory, Qusay Hassan, Stella Kiconco

“…Additionally, the integration of principal component analysis helps manage the high correlation among multiple energy outputs at finer scales, leading to substantial computational cost savings. …”
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Toward Intelligent Fading Channel Prediction: A Comprehensive Survey by Ramoni Adeogun

“…We place a significant emphasis on the shift towards machine learning techniques, which offer a promising avenue for enhancing prediction accuracy and operational efficiency. The survey delves into various predictive models, including neural networks, parametric models, and their applications across multiple input multiple output (MIMO) systems, highlighting their relative strengths and limitations. …”
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Dynamics and key directions of sustainable development of regional agriculture in the context of ensuring national and food security of the Russian Federation by Sergey V. Ryazantsev, Marina L. Vartanova

“…The main arguments proving the relevance of target qualitative indicators in the methodology of regional management of the agricultural sector (improved efficiency of agricultural sector and increased output of agricultural and food products to the level that ensures regional food security) were chosen according to the initial and projected situation in food supply. …”
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Investigation on the interaction force measurement between bubble and particle in flotation based on resistance strain cantilever beam by Xibing REN, Lijuan SUN, Qinshan LIU, Yulong CHENG, Xiahui GUI, Yaowen XING

“…The interaction force between bubble and particle directly determine the efficiency of bubble-particle mineralization and serve as a crucial window into the microscopic mechanism of flotation. …”
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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…This statistical method is favored by regulatory authorities in various countries due to its simplicity in assumptions and clear interpretation. …”
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Deep Learning for Early Earthquake Detection: Application of Convolutional Neural Networks for P-Wave Detection by Dauren Zhexebay, Alisher Skabylov, Margulan Ibraimov, Serik Khokhlov, Aldiyar Agishev, Gulnur Kudaibergenova, Aibala Orazakova, Almansur Agishev

“…The research outputs presented for the local region are unique. …”
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Hybrid AI-Based Framework for Renewable Energy Forecasting: One-Stage Decomposition and Sample Entropy Reconstruction with Least-Squares Regression by Nahed Zemouri, Hatem Mezaache, Zakaria Zemali, Fabio La Foresta, Mario Versaci, Giovanni Angiulli

“…To optimize forecasting accuracy, outputs from all models are combined using a least-squares regression technique that assigns optimal weights to each prediction. …”
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