Time Complexity of Training DNNs With Parallel Computing for Wireless Communications by Pengyu Cong, Chenyang Yang, Shengqian Han, Shuangfeng Han, Xiaoyun Wang

“…Then, we compare the results with the se-FLOPs for inference of the DNNs and for executing a popular numerical algorithm, and provide the scaling laws of these complexities with respect to the numbers of antennas and users. …”
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PolSAR Forest Height Estimation Enhancement With Polarimetric Rotation Domain Features and Multivariate Sensitivity Analysis by Fu-Gen Jiang, Ming-Dian Li, Si-Wei Chen

“…Then, we propose a Bayesian-optimized ensemble learning algorithm to improve the accuracy of forest height estimation. …”
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Characterizing Wake Behavior of Adaptive Aerodynamic Structures Using Reduced-Order Models by Kyan Sadeghilari, Aditya Atre, John Hall

“…These TAD shapes are evaluated across Region 2 operating conditions. The previous study used a genetic algorithm to obtain nine TAD shapes that maximized aerodynamic efficiency in Region 2. …”
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Mitigating the Impact of Satellite Vibrations on the Acquisition of Satellite Laser Links Through Optimized Scan Path and Parameters by Muhammad Khalid, Wu Ji, Deng Li, Li Kun

“…This study presents a framework for evaluating the acquisition time of four different scanning methods: spiral, raster, square spiral, and hexagonal, using a probabilistic approach. …”
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Light positioning: A high-accuracy visible light indoor positioning system based on attitude identification and propagation model by Qu Wang, Haiyong Luo, Aidong Men, Fang Zhao, Xile Gao, Jie Wei, Yuexia Zhang, Yan Huang

“…The system can accurately identify the attitude of a smartphone using its integrated sensors, distinguish different light emitting diode beacons using the fast Fourier transform algorithm, construct a position cost-function based on a visible light radiative decay model, and apply a nonlinear optimizing method to acquire the optimal estimation of final location. …”
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Investigating the relationship between land use and water quality in urban water bodies by Omur Faruq, Md. Abdul Malak, Nahrin Jannat Hossain, Md. Shamsudduha Sami, Abdul Majed Sajib

“…This study employed the Root Mean Squared Water Quality Index (RMS-WQI) model to rank the WQ status of these water bodies. The random forest algorithm was utilized on the Google Earth Engine platform to map LULC. …”
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Multimodal Classification of Alzheimer’s Disease Using Longitudinal Data Analysis and Hypergraph Regularized Multi-Task Feature Selection by Shuaiqun Wang, Huan Zhang, Wei Kong

“…We used functional magnetic resonance imaging and structural functional magnetic resonance imaging data from Alzheimer’s Disease Neuroimaging Initiative at four different time points (baseline (T1), 6th month (T2), 12th month (T3), and 24th month (T4)) to evaluate our method. …”
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High-throughput phenotyping tools for blueberry count, weight, and size estimation based on modified YOLOv5s by Xingjian Li, Sushan Ru, Zixuan He, James D. Spiers, Lirong Xiang

“…The first pipeline used traditional algorithms such as Hough Transform, Watershed, and filtering. …”
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Extract optimization of Ulva lactuca L. and biological activities of optimized extracts by Nuh Korkmaz

“…In our study, the biological activities of extracts produced under the extract conditions that provided the highest biological activity of Ulva lactuca L. were determined. Methods Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA) integration were used for optimization. …”
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Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models by Muhammad Salman Khan, Tianbo Peng, Hanzlah Akhlaq, Muhammad Adeel Khan

“…One of the most significant challenges in AI lies in selecting and fine-tuning the optimal algorithm for a given task. Automated Machine Learning (AutoML) models have emerged as a promising solution to address this challenge by systematically exploring hyperparameter spaces to identify optimal configurations efficiently. …”
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Implementation Of Deep Learning Using Convolutional Neural Network Method In A Rupiah Banknote Detection System For Those With Low Vision by Dinul Akhiyar, Tukino Tukino, Sarjon Defit

“…For validation, 140 test images were utilized, which yielded an impressive mAP value of 97.5%. To further evaluate the system's reliability, tests were conducted under varying conditions, such as banknotes with creases, folds, or different lighting scenarios. …”
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Energy consumption forecasting and thermal insulator selection with random forest regression by Mohammed Fellah, Salma Ouhaibi, Naoual Belouaggadia, Khalifa Mansouri

“…In addition, a correlation analysis was conducted to identify the most influential characteristics on energy consumption, thereby enhancing the predictive performance of the model.The results show that the RF algorithm provides remarkable performance in predicting this performance index, with an R² accuracy of 84% and a mean absolute error of 0.02. …”
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Consistency and reliability of ultrasound-derived fat fraction in hepatic steatosis assessment: influence of posture and breathing variations by Tingjing You, Shengmin Zhang, Shuai Cheng, Zhenyu Shen

“…Methods A retrospective analysis was performed using the system with the UDFF algorithm. Two operators performed UDFF measurements in six different scenarios, each consisting of three measurements (18 in total). …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…These reservoir rock images are crucial for the digital characterization of the reservoir. We propose a novel algorithm consisting of the convolutional neural network, an attention mechanism, and a recurrent neural network for the reconstruction of reservoir rock or porous media images. …”
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Medium- Long-Term Runoff Forecasting Using Interpretable Hybrid Machine Learning Model for Data-Scarce Regions by YOU Yu-jun, BAI Yun-gang, LU Zhen-lin, ZHANG Jiang-hui, CAO Biao, LI Wen-zhong, YU Qi-ying

“…An Improved Particle Swarm Optimization (IPSO) algorithm was used to optimize this model, forming the IPSO-CNN-BiGRU-Attention hybrid model. …”
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Analysis of global stock market development-Integration of clustering, classification, and shapley values. by Marcin Stawarz

“…This is followed by using the random forest algorithm to classify these clusters and evaluate the importance of various features. …”
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ANISOTROPIC REGULATOR OF DAMPING OF RANDOM VIBRATIONS OF THE MOBILE PLATFORM OF A BILAMENT VEHICLE APPARATUS by A. S. Abufanas, A. A. Lobaty, Yu. F. Yacina

“…The coefficients of the optimal regulator are obtained by mathematical modeling. As an example for evaluating the operability of the proposed algorithm, one of the control channels of the mobile platform, defined by a discrete mathematical model of the second order, is considered. …”
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Development and validation of a 3-D deep learning system for diabetic macular oedema classification on optical coherence tomography images by Mingzhi Zhang, Tsz Kin Ng, Yi Zheng, Guihua Zhang, Jian-Wei Lin, Ji Wang, Jie Ji, Peiwen Xie, Yongqun Xiong, Hanfu Wu, Cui Liu, Huishan Zhu, Jinqu Huang, Leixian Lin

“…The deep learning (DL) performance was compared with the diabetic retinopathy experts.Setting Data were collected from Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Chaozhou People’s Hospital and The Second Affiliated Hospital of Shantou University Medical College from January 2010 to December 2023.Participants 7790 volumes of 7146 eyes from 4254 patients were annotated, of which 6281 images were used as the development set and 1509 images were used as the external validation set, split based on the centres.Main outcomes Accuracy, F1-score, sensitivity, specificity, area under receiver operating characteristic curve (AUROC) and Cohen’s kappa were calculated to evaluate the performance of the DL algorithm.Results In classifying DME with non-DME, our model achieved an AUROCs of 0.990 (95% CI 0.983 to 0.996) and 0.916 (95% CI 0.902 to 0.930) for hold-out testing dataset and external validation dataset, respectively. …”
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Assessment of OLCI absorption coefficients for non-water components across all optical water classes by Astrid Bracher, Astrid Bracher, Andrew Clive Banks, Hongyan Xi, David Dessailly, Juan Gossn, Carole Lebreton, Rüdiger Röttgers, Ewa Kwiatkowska, Spyros Chaikalis, Ehsan Mehdipour, Elli Pitta, Mariana Altenburg Soppa, Jan Wevers, Christina Zeri

“…Additionally, based on a different type of retrieval, the absorption of coloured dissolved organic matter (CDOM) from the OLCI 443 nm band, acdom(443), has been introduced as a new product. …”
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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Three metalearners with three machine learning algorithms each and a simple interpretable model-based regression tree were used to identify subgroups with differential treatment effects. …”
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