Long short-term-memory-based depth of anesthesia index computation for offline and real-time clinical application in pigs by Benjamin Caillet, Gilbert Maître, Steve Devènes, Darren Hight, Alessandro Mirra, Olivier L. Levionnois, Alena Simalatsar

“…They are analyzed using classical signal processing algorithms combined with pharmacokinetic and pharmacodynamic (PK/PD) predictions of anesthetic concentrations and their effects on DoA and the prediction of DoA using a novel deep learning-based algorithm. …”
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Sources and trends of black carbon aerosol in the megacity of Nanjing, eastern China, after the China Clean Action Plan and Three-Year Action Plan by A. Abulimiti, A. Abulimiti, Y. Zhang, Y. Zhang, M. Yu, M. Yu, Y. Hong, Y. Hong, Y.-C. Lin, Y.-C. Lin, C. Gul, F. Cao, F. Cao

“…Based on 3-year monitoring data, the random forest (RF) algorithm was employed to reconstruct BC concentrations in Nanjing from 2014 to 2021. …”
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Method of unknown protocol classification based on autoencoder by Chunxiang GU, Weisen WU, Ya’nan SHI, Guangsong LI

“…Aiming at the problem that a large number of unknown protocols exist in the Internet,which makes it very difficult to manage and maintain the network security,a classification and identification method of unknown protocols was proposed.Combined with the autoencoder technology and the improved K-means clustering technology,the unknown protocol was classified and identified for the network traffic.The autoencoder was used to reduce dimensionality and select features of network traffic,clustering technology was used to classify the dimensionality reduction data unsupervised,and finally unsupervised recognition and classification of network traffic were realized.Experimental results show that the classification effect is better than the traditional K-means,DBSCAN,GMM algorithm,and has higher efficiency.…”
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Robust Fault Classification in Permanent Magnet Synchronous Machines Under Dynamic and Noisy Conditions by Mikal Laursen, Van-Van Huynh, Duy-Hung Ha, Mahmoud S. Mahmoud, van Khang Huynh

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Inter layer up-sampling filtering scheme applied in SVC by WANG Zhang1, LIU Jian2, YAN Guo-ping2

“…An efficient inter layer up-sampling filtering algorithm in scalable video coding （SVC） was proposed. …”
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On Some Types of Multigranulation Covering Based on Binary Relations by Ashraf Nawar, E. A. Elsakhawy

“…Then, we put forward an algorithm to illustrate the method of reduction based on the presented model. …”
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Seismic Failure Probability of a Curved Bridge Based on Analytical and Neural Network Approaches by K. Karimi-Moridani, P. Zarfam, M. Ghafory-Ashtiany

“…Different types of neural network training algorithm were used and the best algorithm was adopted. …”
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Genetic analysis of a serologically weak D phenotype caused by the p. R191G variant of the RHAG gene by ZHANG Xu, LI Xiaofeng, LI Jianping

“…R191Q) mutation was predicted to be “probably damaging”, “deleterious” and “affected” by PolyPhen2, PROVEAN and Mutation Taster algorithms, respectively. …”
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Q-Learning-Based Medium Access Technology for Minimizing AoI in LoRa Wireless Relay Networks by Dowon Kim, Geonha Hwang, Ohyun Jo, Kyungseop Shin

“…Simulations demonstrate significant performance improvements over baseline algorithms, achieving average AoI reductions of 23% in high-density scenarios and 31% in high data transfer environments. …”
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Modeling and long-term forecasting of CO2 emissions in Asia: An optimized Artificial Neural Network approach with consideration of renewable energy scenarios by Erfan Abbasian Hamedani, S. Talebi

“…After preprocessing the data, a 5-6-1 MLP-ANN that is optimized with two metaheuristic algorithms (PSO and GWO) is utilized to train and validate the model for each country. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Recent advancements in artificial intelligence (AI) and machine learning (ML) have significantly improved the ability to analyze complex datasets, predict molecular properties, and design new compounds. …”
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Field Grading of Longan SSC via Vis-NIR and Improved BP Neural Network by Jun Li, Meiqi Zhang, Kaixuan Wu, Hengxu Chen, Zhe Ma, Juan Xia, Guangwen Huang

“…Initially, nine preprocessing methods were combined with six classification algorithms to develop the longan SSC grading prediction model. …”
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Features of Breast Cancer Progression after Comprehensive Treatment, Prognosis of Metastatic Spread by Yu. Chuprovska, V. Bodiaka, O. Ivashchuk, Ch. Tsagkaris

“…Still, there are no clear criteria and algorithms for predicting the occurrence of this complication. …”
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Non-Invasive Monitoring of Cerebral Edema Using Ultrasonic Echo Signal Features and Machine Learning by Shuang Yang, Yuanbo Yang, Yufeng Zhou

“…We utilized support vector machine (SVM), logistic regression (LogR), decision tree (DT), and random forest (RF) algorithms for classifying cerebral edema types, and SVM, RF, linear regression (LR), and feedforward neural network (FNNs) for predicting the cerebral infarction volume ratio. …”
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A localization strategy combined with transfer learning for image annotation. by Zhiqiang Chen, Leelavathi Rajamanickam, Jianfang Cao, Aidi Zhao, Xiaohui Hu

“…The optimal K value is obtained experimentally and used to determine the number of predicted labels, thereby solving the empty label set problem that occurs when the predicted label values of images are below a fixed threshold. …”
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Spike Stall Precursor Detection in a Single-Stage Axial Compressor: A Data-Driven Dynamic Modeling Approach by Anish Thapa, Jichao Li, Marco P. Schoen

“…Reducing this margin through active control requires stall precursor detection and mitigation mechanisms. While several algorithms have shown promising results in predicting modal stalls, predicting spike stalls remains a challenge due to their rapid onset, leaving little time for corrective actions. …”
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Deep-learning model for embryo selection using time-lapse imaging of matched high-quality embryos by Lisa Boucret, Floris Chabrun, Magalie Boguenet, Pascal Reynier, Pierre-Emmanuel Bouet, Pascale May-Panloup

“…Abstract Time-lapse imaging and deep-learning algorithms are promising tools to assess the most viable embryos and improve embryo selection in IVF laboratories. …”
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A novel machine learning-based approach to thermal integrity profiling of concrete pile foundations by Javier Sánchez Fernández, Agustín Ruiz López, David M.G. Taborda

“…This is followed by a regression algorithm that predicts the defect size and its location within the cross-section. …”
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Optimizing the learning rate for adaptive estimation of neural encoding models. by Han-Lin Hsieh, Maryam M Shanechi

“…Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

“…The effectiveness of sulfur removal was predicted by analyzing five important factors: temperature, concentration, surface area, fuel/adsorbent, and time. …”
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