Machine Learning-Based Detection of Anomalies, Intrusions, and Threats in Industrial Control Systems by Denis Benka, Dusan Horvath, Lukas Spendla, Gabriel Gaspar, Maximilian Stremy

“…This paper proposes a machine learning (ML)-based approach to anomaly detection in ICS communication networks, focusing on techniques such as 1D Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, Support Vector Machines (SVMs), and Isolation Forest (iForest) algorithms. …”
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Shannon Entropy Computations in Navier–Stokes Flow Problems Using the Stochastic Finite Volume Method by Marcin Kamiński, Rafał Leszek Ossowski

“…Further numerical extension of this technique is seen in an application of the artificial neural networks, where polynomial approximation may be replaced automatically by some optimal, and not necessarily polynomial, bases.…”
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Development of Chemo-Selective Gas Sensors Based on Molecularly Imprinted Polymer-Quartz Crystal Microbalance for Detection of Bioactive Compounds in <i>Curcuma longa</i> by Fajar Hardoyono

“…The turmeric sample classification using backpropagation neural networks reached high accuracies, with 97.04% in training and 98.73% in testing datasets. …”
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Blockchain-Powered Secure and Scalable Threat Intelligence System With Graph Convolutional Autoencoder and Reinforcement Learning Feedback Loop by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…Subsequently, graph convolutional neural networks with autoencoders are trained on large unlabeled sets of threat data to automatically label various types of threats, with the system employing fuzzy logic to rank and score possible threats. …”
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From Baseline to Best Practice: An Advanced Feature Selection, Feature Resampling and Grid Search Techniques to Improve Injury Severity Prediction by Soukaina EL Ferouali, Zouhair Elamrani Abou Elassad, Sara Qassimi, Abdelmounaîm Abdali

“…Fourth predictive systems are employed to investigate the intricate problem of predicting the severity of injuries sustained in traffic crashes using different regression algorithms, such as Random Forest, Decision Trees, XGBoost, and Artificial Neural Networks. Compared to comparable systems without feature selection, feature resampling, and optimization methods, the results demonstrate that employing optimized XGBoost along with grid search in conjunction with SelectKBest and SMOTE strategy has resulted in greater performance, with an 89% R2 score. …”
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Improving Network Security: An Intelligent IDS with RNN-LSTM and Grey Wolf Optimization by murtadha ali

“…Therefore, for such we recommend an IDS that merges the Grey Wolf Optimization (GWO) algorithm and Recurrent Neural Networks with Long Short-Term Memory (RNN-LSTM). …”
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Ensemble graph auto-encoders for clustering and link prediction by Chengxin Xie, Jingui Huang, Yongjiang Shi, Hui Pang, Liting Gao, Xiumei Wen

“…Graph auto-encoders are a crucial research area within graph neural networks, commonly employed for generating graph embeddings while minimizing errors in unsupervised learning. …”
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Automated recognition and segmentation of lung cancer cytological images based on deep learning. by Qingyang Wang, Yazhi Luo, Ying Zhao, Shuhao Wang, Yiru Niu, Jinxi Di, Jia Guo, Guorong Lan, Lei Yang, Yu Shan Mao, Yuan Tu, Dingrong Zhong, Pei Zhang

“…With the development of deep neural networks, the You Only Look Once (YOLO) object-detection model has been recognized for its impressive speed and accuracy. …”
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Blink Detection Using 3D Convolutional Neural Architectures and Analysis of Accumulated Frame Predictions by George Nousias, Konstantinos K. Delibasis, Georgios Labiris

“…Two different 3D convolutional neural networks are utilized (a simple 3D CNN and 3D ResNet), as well as a 3D autoencoder combined with a classifier coupled to the latent space. …”
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DeepLabCut custom-trained model and the refinement function for gait analysis by Giulia Panconi, Stefano Grasso, Sara Guarducci, Lorenzo Mucchi, Diego Minciacchi, Riccardo Bravi

“…Our results showed that DLCCT outperformed DLCPT and OPPT, highlighting the importance of leveraging DeepLabCut transfer learning to enhance the pose estimation performance with a custom-trained neural networks. Moreover, DLCCT, with the implementation of the DLC refinement function, offers the most promising markerless pose estimation solution for evaluating locomotion. …”
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Vehicle-to-Vehicle Communication Channel Estimator Based on Gate Recurrent Unit by Jun-Han Wang, He He, Kosuke Tamura, Shun Kojima, Jaesang Cha, Chang-Jun Ahn

“…This study provides a useful reference for optimizing neural networks and thus improving the performance of channel estimators.…”
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Modeling the Relationship between Rice Yield and Climate Variables Using Statistical and Machine Learning Techniques by Lasini Wickramasinghe, Rukmal Weliwatta, Piyal Ekanayake, Jeevani Jayasinghe

“…Rice harvest and yield data over the last three decades and monthly climatic data were used to develop the prediction model by applying artificial neural networks (ANNs), support vector machine regression (SVMR), multiple linear regression (MLR), Gaussian process regression (GPR), power regression (PR), and robust regression (RR). …”
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Performance Evaluation of Various Z-Source Inverter Topologies for PV Applications Using AI-Based MPPT Techniques by N. Kalaiarasi, A. Sivapriya, Pradeep Vishnuram, Mukesh Pushkarna, Mohit Bajaj, Hossam Kotb, Sadam Alphonse

“…Also, artificial neural networks (ANNs), fuzzy logic controller (FLC), and adaptive neuro-fuzzy inference system (ANFIS)-based MPPT techniques are discussed for obtaining maximum power from PV panels. …”
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Evaluating waist-to-hip ratio in youth using frequency-modulated continuous wave radar and machine learning by Jun Byung Park, Jinjoo Choi, Jae Yoon Na, Seung Hyun Kim, Hyun-Kyung Park, Seung Yang, Sung Ho Cho

“…We included 100 participants aged 7–18 and radar data were analyzed using point cloud generation processed through convolutional neural networks for estimating WHR. The radar-based WHR measurements were compared to conventional clinician measurements. …”
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RGB-D salient object detection based on BC2 FNet network by WANG Feng, CHENG Yongmei

“…However, up-sampling and down-sampling operations in neural networks maybe blur the boundaries of objects in the saliency map, thereby reducing the performance of salient object detection. …”
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Chitosan suitability to adhesion, neuronal differentiation and maturation of hiPSCs compared to Matrigel coated substrates by Sara Grasselli, Donatella Di Lisa, Pier Francesco Ferrari, Sergio Martinoia, Laura Pastorino

“…Finding an adhesion factor that supports the differentiation and maturation of the neural networks of hiPSCs derived neurons is therefore crucial. …”
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PegasosQSVM: A Quantum Machine Learning Approach for Accurate Fake News Detection by Mehdi Khalil, Chi Zhang, Zhiwei Ye, Peng Zhang

“…The achieved results outperform other machine learning methods on the BUZZFEED dataset, including Quantum Neural Networks and Quantum K-Nearest Neighbors. Its successful implementation paves the way for further refinement of quantum machine learning techniques in fake news classification. …”
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Extending OpenStack Monasca for Predictive Elasticity Control by Giacomo Lanciano, Filippo Galli, Tommaso Cucinotta, Davide Bacciu, Andrea Passarella

“…We use our architecture to implement predictive scaling policies leveraging on linear regression, autoregressive integrated moving average, feed-forward, and recurrent neural networks (RNN). Then, we evaluate their performance on a synthetic workload, comparing them to those of a traditional policy. …”
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Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region by Gabriel Hermosilla, Gabriel Villavicencio, Giovanni Cocca-Guardia, Vicente Aprigliano, Manuel Silva, Juan Carlos Quezada, Pierre Breul, Vinicius Minatogawa, Jaime Morales

“…By integrating Geographic Information Systems (GIS) and Artificial Intelligence (AI)&#x2014;utilizing models like YOLOv11 and convolutional neural networks&#x2014;we automate the detection and characterization of WRD and LWD from satellite imagery, extracting critical parameters for PS assessment. …”
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Short-Term Origin-Destination Based Metro Flow Prediction with Probabilistic Model Selection Approach by Xiaoqing Dai, Lijun Sun, Yanyan Xu

“…., autoregressive-moving-average, neural networks, support vector regression, and averaging ensemble model, as well as the basic models. …”
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