Rapid in-air ultrasound holography measurement and camera-in-the-loop generation using thermography by Zak Morgan, Youngjun Cho, Sriram Subramanian

“…Finally, we integrate this with holography algorithms to propose a camera-in-the-loop algorithm that employs real-time measurement, enabling targeted data acquisition and on-line training of acoustic holography algorithms. …”
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SOFTWARE IMPLEMENTATION OF THE ARTIFICIAL NEURAL NETWORK FOR VIRTUAL OBJECTS СONTROL by Yu. B. Popova, S. V. Yatsynovich

“…The use of an artificial neural network has reduced the use of CPU time, which is extremely important in problems where rapid decision making is required, because complex calculations and prediction algorithms can not always be invested in 20 ms, which is fraught with skipping moves and losses. …”
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Artificial intelligence in colorectal cancer: a review by G. Singh

“…Challenges in AI development are addressed, such as data standardization and the interpretability of machine learning algorithms. The potential of AI in treatment decision support, precision medicine, and prognosis prediction is discussed, emphasizing the role of AI in selecting optimal treatments and improving surgical precision. …”
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Heisenberg-Limited Adaptive Gradient Estimation for Multiple Observables by Kaito Wada, Naoki Yamamoto, Nobuyuki Yoshioka

“…The proposed method is an adaptive version of the quantum gradient-estimation algorithm and has a resource-efficient implementation due to its adaptiveness. …”
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Quality assessment of chicken using machine learning and electronic nose by Hassan Anwar, Talha Anwar

“…This study investigates the use of an electronic nose system—a sensor array that detects odors and generates data, which is then analyzed by machine learning algorithms to predict chicken freshness. An electronic nose system was developed using six MQ gas sensors and one humidity temperature sensor. …”
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Incorporating Wave-ViT for Breast Cancer Diagnosis Using MRI Imaging by Sahil Mahey, Hamid Usefi

“…Machine learning (ML) algorithms offer a transformative solution by automating this process, improving efficiency, and enhancing diagnostic accuracy. …”
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Application of Machine Learning for Target Selection and Acid Treatment Design by I. I. Mannanov, M. A. Varfolomeev, G. R. Ganieva, A. R. Gimaeva, R. R. Giniyatullin

“…These algorithms significantly simplify the tasks of acid treatment design.…”
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Computerized Adaptive Testing Framework Based on Excitation Block and Gumbel-Softmax by Chengsong Liu, Yan Wei

“…In addition, most algorithms primarily focus on accurately predicting students’ abilities, neglecting critical factors such as concept diversity and question exposure rate, which are essential for model effectiveness. …”
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Short-Term Electrical Load Forecasting in Power Systems Using Deep Learning Techniques by Nihat Pamuk

“…Using a real dataset for one-step forecasting, this article compares three deep learning algorithms for short-term power load forecasting: LSTM, GRUs, and CNN. …”
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Seismic Vibration Control and Multi-Objective Optimization of Transmission Tower with Tuned Mass Damper Under Near-Fault Pulse-like Ground Motions by Ying Lin, Tao Liu

“…Based on the obtained analysis results, artificial neural network (ANN) is trained to predict the vibration reduction ratios of peak responses and the corresponding vibration reduction cost. …”
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Grey wolf‐based heuristic methods for accurate parameter extraction to optimize the performance of PV modules by Seyit Alperen Celtek, Seda Kul, Manish Kumar Singla, Jyoti Gupta, Murodbek Safaraliev, Hamed Zeinoddini‐Meymand

“…In this study, the parameter prediction of a four‐diode PV model was carried out using the Improved Grey Wolf Optimization (IGWO) algorithm, which builds upon the Grey Wolf Optimization (GWO) algorithm. …”
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Hybrid Machine Learning in Hydrological Runoff Forecasting: An Exploration of Extreme Gradient-Boosting and Categorical Gradient Boosting Optimization in the Russian River Basin by Reza Seifi Majdar, Ali Rahnamaei, Vahid Babazadeh

“…Recent advances in machine learning (ML) have opened new opportunities to improve prediction accuracy. This study focuses on evaluating commonly used ML methods for runoff prediction, with an emphasis on simplicity and comparability to more advanced models. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In recent years, machine learning techniques, such as artificial neural networks (ANNs), have been successfully applied to more efficiently extract valuable information from spectral data and to accurately predict quality traits. In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. …”
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Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches by Suleiman Ibrahim Mohammad, Hamza Abu Owida, Asokan Vasudevan, Suhas Ballal, Shaker Al-Hasnaawei, Subhashree Ray, Naveen Chandra Talniya, Aashna Sinha, Vatsal Jain, Ahmad Abumalek

“…A range of sophisticated artificial intelligence methods, including One-Dimensional Convolutional Neural Network (1D-CNN), Artificial Neural Networks (ANN), Decision Tree (DT), Ensemble Learning (EL), Adaptive Boosting (AdaBoost), Random Forest (RF), and Least Squares Support Vector Machine (LSSVM), were utilized to model and predict pH variations with high accuracy. The Coupled Simulated Annealing (CSA) algorithm was employed to optimize the hyperparameters of these models, enhancing their predictive performance. …”
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A three-dimensional reconstruction method of coal mine tunnel fused with LiDAR and IMU by Qinghua MAO, Jianquan CHAI, Yanzhang CHEN, Xusheng XUE, Chuanwei WANG

“…Compared with the A-LOAM and LEGO-LOAM algorithms, the proposed algorithm has significantly improved the accuracy and global consistency of pose estimation. …”
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Patterns and risk factors of falls among older adults: a systematic review by Tetiana Yermakova

“…The first algorithm is based on extracting documents with the highest citation metrics. …”
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Detection and Pattern Recognition of Chemical Warfare Agents by MOS-Based MEMS Gas Sensor Array by Mengxue Xu, Xiaochun Hu, Hongpeng Zhang, Ting Miao, Lan Ma, Jing Liang, Yuefeng Zhu, Haiyan Zhu, Zhenxing Cheng, Xuhui Sun

“…Finally, principal component analysis (PCA) and machine learning algorithms were applied for CWA classification. The obtained PCA plots showed significant differences between groups, and the narrow neural network among the machine learning algorithms achieves a prediction accuracy of nearly 100.0%. …”
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Multilevel determinants of racial/ethnic disparities in severe maternal morbidity and mortality in the context of the COVID-19 pandemic in the USA: protocol for a concurrent triang... by Bankole Olatosi, Jiajia Zhang, Xiaoming Li, Chen Liang, Jihong Liu, Peiyin Hung, Shan Qiao, Berry A Campbell, Myriam E Torres, Neset Hikmet

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A lightweight knowledge graph-driven question answering system for field-based mineral resource survey by Mingguo Wang, Chengbin Wang, Jianguo Chen, Bo Wang, Wei Wang, Xiaogang Ma, Jiangtao Ren, Zichen Li, Yicai Ye, Jiakai Zhang, Yue Wang

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Targeted urinary metabolomics combined with machine learning to identify biomarkers related to central carbon metabolism for IBD by Miao-Lin Lei, Guan-Wei Bi, Xiao-Lin Yin, Xiao-Lin Yin, Yue Wang, Yue Wang, Yue Wang, Zi-Ru Sun, Zi-Ru Sun, Zi-Ru Sun, Xin-rui Guo, Hui-peng Zhang, Xiao-han Zhao, Feng Li, Feng Li, Yan-Bo Yu

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