Deep Learning Based Early Intrusion Detection in IIoT using Honeypot by Abbasgholi Pashaei, Mohammad Esmaeil Akbari, Mina Zolfy Lighvan, Asghar Charmin

“…Due to the unpredictability of network technology and attack attempts, traditional Deep Learning (DL) approaches are made ineffective. The accuracy of DL algorithms has been shown across a range of scientific fields. …”
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Detection of cotton crops diseases using customized deep learning model by Hafiz Muhammad Faisal, Muhammad Aqib, Saif Ur Rehman, Khalid Mahmood, Silvia Aparicio Obregon, Rubén Calderón Iglesias, Imran Ashraf

“…Thanks to deep learning algorithms, researchers have developed innovative disease detection approaches that can help safeguard the cotton crop and promote economic growth. …”
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A New Approach for Brain Tumor Detection Using Machine Learning by Elsadek Hussien Ibrahim, Shaaban Ebrahim Abo-Youssef, Khaled El-Bahnasy, Khaled Ahmed Mohamed Fathy

“…Methods: Researchers have developed algorithms for detecting and classifying brain tumors and prioritizing accuracy and efficiency. …”
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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

“…Using a combination of advanced deep learning and machine learning techniques, we offer a comprehensive solution to enhance breast cancer detection accuracy. …”
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A machine learning model for early detection of sexually transmitted infections by Juma Shija, Judith Leo, Elizabeth Mkoba

“…This was done by using surveys and questionnaires to get the data. The dataset was split into a 70%:15%:15% ratio for training, testing, and validation, respectively, and five machine learning algorithms were evaluated: AdaBoost, Support Vector Machine, Random Forest, Decision Tree, and Stochastic Gradient Descent. …”
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A comprehensive image dataset for carambola leaf and fruit disease classification and quality assessmentMendeley Data by S.M. Abdullah Al Muhib, Rejowan Arifin Nayeem, Noman Mezi, Nafiz Ahmed Emon

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Automatic detection of fake reviews at marketplaces using expert-based features and consumers’ reactions by A. N. Borodulina, E. V. Mikhalkova

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Comparing Classification Algorithms to Recognize Selected Gestures Based on Microsoft Azure Kinect Joint Data by Marc Funken, Thomas Hanne

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Performance Evaluation of Neighbors-Based Learning Methods for Network Intrusion Detection System by Ngoc Thien Nguyen

“…In particular, Machine Learning (ML) and Artificial Intelligence (AI) have become important tools in enhancing cyber-attack detection capabilities. …”
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Using Artificial Intelligence Techniques For Intrusion Detection System by Manar Ahmed, Bayda Khaleel

“…And also classifies this dataset into 2 classes (Normal, and Attack), one for normal traffic and another for attack, also these algorithms are used to detect intrusion. Other techniques were used which are artificial neural network (ANN) represented by counter propagation neural network (CPN) which is hybrid learning (supervised and unsupervised) that is applied to classify intrusion into 23, 5 and 2 class(es) and used it to detect the network intrusions, and then we combined fuzzy c-mean with two layers Kohonen layer and Grossberg layer for counter propagation neural network to produce the proposed approach or system that called it fuzzy counter propagation neural network (FCPN) were applied it to classify network intrusion into 23, 5 and 2 class(es) and detect the intrusion. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…It further investigates the relationship between turbulent coherent structures and the intensity of particle movement, clarifying the mechanism through which turbulent coherent structures influence sediment transport.MethodsThe optimization algorithm developed in this study aims to maximize the detection of moving particles, providing more accurate data to support understanding sediment transport patterns at the particle scale and their association with turbulent coherent structures. …”
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An Early Detection of Asthma Using BOMLA Detector by Md. Abdul Awal, Md. Shahadat Hossain, Kumar Debjit, Nafiz Ahmed, Rajan Dev Nath, G. M. Monsur Habib, Md. Salauddin Khan, Md. Akhtarul Islam, M. A. Parvez Mahmud

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Mitigating Sinkhole Attacks in MANET Routing Protocols using Federated Learning HDBNCNN Algorithm by Sherril Sophie Maria Vincent

“…Further, the Hierarchical Deep Belief Network Convolutional Neural Network (HDBNCNN) algorithm has analysed the accumulated data in detecting the anomalies revealing the sinkhole activity centred on learning routing patterns. …”
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Heart Disease Prediction Using Ensemble Tree Algorithms: A Supervised Learning Perspective by Enoch Sakyi-Yeboah, Edmund Fosu Agyemang, Vincent Agbenyeavu, Akua Osei-Nkwantabisa, Priscilla Kissi-Appiah, Lateef Moshood, Lawrence Agbota, Ezekiel N. N. Nortey

“…Data related to heart disease clinical features was obtained from the open Kaggle Machine Learning Dataset repository. …”
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Tennis Assistance Technology Based on Dynamic Time Warping Algorithm by Penggang Wang, Pengpeng Zhang, Guanxi Fan

“…In view of this research, a tennis sports assistance technology based on dynamic time warping algorithm is developed. By collecting athletes’ motion data and using dynamic time warping algorithm for motion similarity analysis, personalized technical improvement suggestions are provided for athletes. …”
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Predicting cancer risk using machine learning on lifestyle and genetic data by Mohamed Abdelmoaty Ahmed, Ahmed AbdelMoety, Asmaa Mohamed Ahmed Soliman

“…Nine supervised learning algorithms were evaluated and compared, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machines (SVMs), and several ensemble methods. …”
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Comparison of Different Machine Learning Algorithms to Classify Epilepsy Seizure from EEG Signals by Pankaj Kunekar, Chanchal Kumawat, Vaishnavi Lande, Sushant Lokhande, Ram Mandhana, Malhar Kshirsagar

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Investigation of the Application of Machine Learning Algorithms in Credit Risk Assessment of Medium and Micro Enterprises by Yujie Zhao

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Comparative Analysis of Oversampling and SMOTEENN Techniques in Machine Learning Algorithms for Breast Cancer Prediction by Tri Yulian, Erliyan Redy Susanto

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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…Initially, principal component analysis (PCA) was used to visualise the clustering of the three target gas samples at room temperature, providing a preliminary data analysis. For the classification phase, we chose three classification algorithms—MLP (Multilayer Perceptron), ELM (Extreme Learning Machine), and SVM (Support Vector Machine)—and performed a comprehensive comparison of their classification and generalisation abilities using grid search for hyperparameter optimisation and five-fold cross-validation. …”
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