Encoding arbitrary phase profiles to 2D diffraction orders with controllable polarization states by Zhao Ruizhe, Li Xin, Geng Guangzhou, Li Xiaowei, Li Junjie, Wang Yongtian, Huang Lingling

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Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination by Xu Ma, Dong Wang, Angela Cuadros, Tianyi Mao, Qile Zhao, Gonzalo R. Arce, Tingfa Xu

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Increasing the noise immunity of radio receiving paths with automatic sensitivity control by Р. V. Zayats, I. Y. Malevich

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Gaussian Process Regression-Based Fixed-Time Trajectory Tracking Control for Uncertain Euler–Lagrange Systems by Tong Li, Tianqi Chen, Liang Sun

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Context-Driven Active Contour (CDAC): A Novel Medical Image Segmentation Method Based on Active Contour and Contextual Understanding by Suane Pires Pinheiro da Silva, Roberto Fernandes Ivo, Calleo Belo Barroso, João Carlos Nepomuceno Fernandes, Thiago Ferreira Portela, Aldísio Gonçalves Medeiros, Pedro Henrique F. de Sousa, Houbing Song, Pedro Pedrosa Rebouças Filho

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Enhanced Multiphase Interleaved Boost Converter Interface for Grid-Connected PV Power System by Rasha Kassem, Nagwa F. Ibrahim, Mohamed Metwally Mahmoud, Abdulaziz Alkuhayli, Usama Khaled, Abderrahmane Beroual, Hedra Mahfouz Ibrahim Saleeb

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An Energy-Efficient Motion Strategy for Mobile Sensors in Mixed Wireless Sensor Networks by Zhen-Jiang Zhang, Jun-Song Fu, Han-Chieh Chao

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Neuro-fuzzy techniques for modeling process parameters in pulsed electrochemical machining of steel by Irvin Uriel Nopalera Angeles, Everardo Efrén Granda Gutiérrez, Roberto Alejo Eleuterio, René Arnulfo García Hernández, Ángel Hernández Castañeda, María Guadalupe Pineda Arizmendi

“…In this way, a root mean square error in the prediction of the material removal rate of 0.394 and a coefficient of determination  of 0.845 were obtained. …”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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Integration of DDPM and ILUES for Simultaneous Identification of Contaminant Source Parameters and Non‐Gaussian Channelized Hydraulic Conductivity Field by Xun Zhang, Simin Jiang, Na Zheng, Xuemin Xia, Zhi Li, Ruicheng Zhang, Jiangjiang Zhang, Xinshu Wang

“…To reduce the computational burden, an AR‐Net‐WL (ARNW) surrogate model was introduced, resulting in an efficient inversion framework (AEdiffusion‐ILUES‐ARNW) with similar prediction accuracy and predictive uncertainty estimation as the AEdiffusion‐ILUES but at a lower computational cost.…”
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Indirect Determination Approach of Blast-Induced Ground Vibration Based on a Hybrid SSA-Optimized GP-Based Technique by Zhaoxin Jiang, Hongyan Xu, Hui Chen, Bei Gao, Shijie Jia, Zhi Yu, Jian Zhou

“…For evaluating the peak particle velocity resulting from the quarry blast, a robust artificial intelligence system combined with the salp swarm algorithm (SSA) and Gaussian process (GP) was proposed, and the SSA was used to find the optimal hyperparameters of the GP here. …”
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Spectroscopy-Based Methods and Supervised Machine Learning Applications for Milk Chemical Analysis in Dairy Ruminants by Aikaterini-Artemis Agiomavriti, Maria P. Nikolopoulou, Thomas Bartzanas, Nikos Chorianopoulos, Konstantinos Demestichas, Athanasios I. Gelasakis

“…Currently, the advancements and utilization of spectroscopy-based techniques combined with machine learning algorithms have made the development of analytical tools and real-time monitoring and prediction systems in the dairy ruminant sector feasible. …”
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Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…However, the RF, with hyperparameters optimized by the genetic algorithm, was able to improve the R2 values of the prediction of storage temperature and period to 0.96 and 0.89. …”
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Revolutionizing Drug Design with Artificial Intelligence: A Comprehensive Review of Techniques, Applications, and Case Studies by Varun Pareek, Lakshya Tuteja, Lokendra Sharma, Susheel Kumar, Noopur Verma

“…Results: AI techniques such as machine learning, deep learning, and reinforcement learning have been successfully used in virtual screening, de novo drug design, and prediction of ADME properties. Virtual screening involves the use of AI algorithms to identify promising compounds for further testing, while de novo drug design involves the generation of novel compounds using AI techniques. …”
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A conceptual digital twin framework for supply chain recovery and resilience by Oluwagbenga Victor Ogunsoto, Jessica Olivares-Aguila, Waguih ElMaraghy

“…In the first phase, machine learning algorithms, including logistic regression and Long Short-Term Memory (LSTM), were trained on Kerala India's precipitation data to predict floods. …”
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Comparative effects of metformin and varying intensities of exercise on miR-133a expression in diabetic rats: Insights from machine learning analysis by Elahe Alivaisi, Sabrieh Amini, Karimeh Haghani, Hori Ghaneialvar, Fatemeh Keshavarzi

“…We used the CatBoost algorithm to develop a predictive model for miR-133a expression based on metabolic parameters. …”
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A Novel Mechanism for Fire Detection in Subway Transportation Systems Based on Wireless Sensor Networks by Zhen-Jiang Zhang, Jun-Song Fu, Hua-Pei Chiang, Yueh-Min Huang

“…In this paper, a novel mechanism based on wireless sensor networks is proposed and we can use the mechanism to detect fire in subway transportation systems. The core algorithm in this mechanism is an alternative of data fusion in wireless sensor networks. …”
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Mobile Phone Data in Urban Commuting: A Network Community Detection-Based Framework to Unveil the Spatial Structure of Commuting Demand by Qing Yu, Weifeng Li, Dongyuan Yang, Haoran Zhang

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Advanced machine learning artificial neural network classifier for lithology identification using Bayesian optimization by Saâd Soulaimani, Saâd Soulaimani, Ayoub Soulaimani, Kamal Abdelrahman, Abdelhalim Miftah, Mohammed S. Fnais, Biraj Kanti Mondal

“…A key feature of this strategy is leveraging population search algorithms to fine-tune hyperparameters, thus boosting prediction accuracy. …”
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Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification by Lili Yang, Yi Yang, Peng Liu, Lina Wang

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