Modeling of Bayesian machine learning with sparrow search algorithm for cyberattack detection in IIoT environment by Faten Khalid Karim, José Varela-Aldás, Mohamad Khairi Ishak, Ayman Aljarbouh, Samih M. Mostafa

“…Various research has been undertaken to address the concerns of cyberattacks on IIoT networks using machine learning (ML) and deep learning (DL) approaches. This study introduces a new Bayesian Machine Learning with the Sparrow Search Algorithm for Cyberattack Detection (BMLSSA-CAD) technique in the IIoT networks. …”
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Voice pathology detection using machine learning algorithms based on different voice databases by Nurul Mu'azzah Abdul Latiff, Fahad Taha Al-Dhief, Nurul Fariesya Suhaila Md Sazihan, Marina Mat Baki, Nik Noordini Nik Abd. Malik, Musatafa Abbas Abbood Albadr, Ali Hashim Abbas

“…Unlike traditional approaches that focus solely on single-database training and testing, this study presents a cross-database evaluation strategy to assess the robustness and generalizability of machine learning algorithms for voice pathology detection. …”
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Network intrusion detection based on improved KNN algorithm by Hongsheng Bao, Jie Gao

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A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders by Shahid Tufail, Hasan Iqbal, Mohd Tariq, Arif I. Sarwat

“…This study shows the importance of understanding algorithmic behavior and data features and how it can impact the performance of ML models. …”
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Research Progress of Machine Learning Algorithms Applied in FSO Communication Systems by LIU Hainan, SHAO Yufeng, WANG Anrong, ZHU Yaodong, YANG Linjie, CHEN Chao, LI Wenchen, HU Wenguang

“…In this article, the research progress of applying typical machine learning algorithms in FSO communication systems in signal detection, channel estimation, auxiliary optical compensation, and other aspects are reviewed. …”
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Adaptive convolutional neural network-based principal component analysis algorithm for the detection of manufacturing data by Tsun-Kuo Lin

“…This adaptive algorithm is capable of learning from limited image signals or features, enhancing data interpretability and increasing the amount of feature information for detecting manufacturing data.…”
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Multimodal Data Fusion for Precise Lettuce Phenotype Estimation Using Deep Learning Algorithms by Lixin Hou, Yuxia Zhu, Mengke Wang, Ning Wei, Jiachi Dong, Yaodong Tao, Jing Zhou, Jian Zhang

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A Comparison of Machine Learning Algorithms for Predicting Alzheimer’s Disease Using Neuropsychological Data by Zakaria Mokadem, Mohamed Djerioui, Bilal Attallah, Youcef Brik

“…These findings highlight the robustness and efficiency of ensemble learning algorithms, especially in handling complex, non-linear data structures. …”
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Exploration of geo-spatial data and machine learning algorithms for robust wildfire occurrence prediction by Svetlana Illarionova, Dmitrii Shadrin, Fedor Gubanov, Mikhail Shutov, Usman Tasuev, Ksenia Evteeva, Maksim Mironenko, Evgeny Burnaev

“…Consequently, there is no unified approach for predicting wildfire occurrences using remote sensing data and AI techniques. The goal of this study is to explore the potential of predicting wildfire occurrences using various available environmental parameters - meteorological, geo-spatial, and anthropogenic - and machine learning (ML) algorithms. …”
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A big data analysis algorithm for massive sensor medical images by Sarah A. Alzakari, Nuha Alruwais, Shaymaa Sorour, Shouki A. Ebad, Asma Abbas Hassan Elnour, Ahmed Sayed

“…The danger of security breaches and unauthorized access, which might lead to identity theft and privacy violations, increases when sending and storing sensitive medical data on the cloud. Our effort will improve patient care and well-being by creating an anomaly detection system based on machine learning specifically for medical images and providing timely treatments and notifications. …”
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Diagnosis of oral cancer using deep learning algorithms by Mayra Alejandra Dávila Olivos, Henry Miguel Herrera Del Águila, Félix Melchor Santos López

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Machine learning for Internet of things anomaly detection under low-quality data by Shangbin Han, Qianhong Wu, Yang Yang

“…Therefore, practitioners may not know which algorithm to choose due to the lack of review and evaluation of anomaly detection methods under low-quality data. …”
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Overcoming data scarcity in life-threatening arrhythmia detection through transfer learning by Giuliana Monachino, Beatrice Zanchi, Michael Wand, Giulio Conte, Athina Tzovara, Francesca Dalia Faraci

“…One of the main challenges in building robust LTA detection algorithms is the limited availability of labeled LTA data. …”
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Weed detection on embedded systems using computer vision algorithms by D. Shadrin, S. Illarionova, R. Kasatov, M. Akimenkova, G. Rudensky, E. Erhan

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Optimal Fuzzy Deep Neural Networks-Based Plant Disease Detection and Classification on UAV-Based Remote Sensed Data by M. Pajany, S. Venkatraman, U. Sakthi, M. Sujatha, Mohamad Khairi Ishak

“…The OFDNN-PDDC technique follows a three-stage process to enhance plant disease detection performance. At the primary level, the OFDNN-PDDC technique employs an improved ShuffleNetv2 model for learning complex and intrinsic feature patterns on the RS data. …”
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Deep Learning based Individual Cattle Face Recognition using Data Augmentation and Transfer Learning by Caner Koç, Kamil Ekinci, Ömer Ertuğrul, Dilara Gerdan Koc, Havva Eylem Polat

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ANALYZING EEG SIGNALS FOR STRESS DETECTION USING RANDOM FOREST ALGORITHM by Fi Imanur Sifaunnufus Ms, Fitra Abdurrachman Bachtiar, Barlian Henryranu Prasetio

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Detecting soil mixing, grain size distribution, and clogging potential of tunnel excavation face by classification-regression algorithms using EPBM operational data by Sharmin Sarna, Marte Gutierrez

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Discriminating Types of Volcanic Electrical Activity: Toward an Eruption Detection Algorithm by S. A. Behnke, H. E. Edens, J. Theiler, D. J. Swanson, S. Senay, A. R. Van Eaton, M. Iguchi, D. Miki

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On the Application of a Sparse Data Observers (SDOs) Outlier Detection Algorithm to Mitigate Poisoning Attacks in UltraWideBand (UWB) Line-of-Sight (LOS)/Non-Line-of-Sight (NLOS) C... by Gianmarco Baldini

“…In particular, the study described in this paper proposes a recent outlier detection algorithm, which has low computing complexity: the sparse data observers (SDOs) algorithm. …”
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