Generative Adversarial and Transformer Network Synergy for Robust Intrusion Detection in IoT Environments by Pardis Sadatian Moghaddam, Ali Vaziri, Sarvenaz Sadat Khatami, Francisco Hernando-Gallego, Diego Martín

“…Additionally, an improved non-dominated sorting biogeography-based optimization (INSBBO) algorithm is employed to fine-tune the hyper-parameters of the hybrid model, further enhancing learning stability and detection performance. …”
Get full text

Active Reinforcement Learning for the Semantic Segmentation of Urban Images by Mahya Jodeiri Rad, Costas Armenakis

“…Image segmentation using supervised learning algorithms usually requires large amounts of annotated training data, while urban datasets frequently contain unbalanced classes leading to poor detection of under-represented classes. …”
Get full text

Detection of Aflatoxin B1 in Maize Silage Based on Hyperspectral Imaging Technology by Lina Guo, Haiqing Tian, Daqian Wan, Yang Yu, Kai Zhao, Xinglu Zheng, Haijun Li, Jianying Sun

“…The results demonstrated that SD preprocessing was the most suitable for AFB1 detection in maize silage, and the Mixup data augmentation method effectively improved model performance. …”
Get full text

Recent Tools of Software-Defined Networking Traffic Generation and Data Collection by Tabarak Khudhair, Omar Athab

“…Results show success in generating several types of network metrics to be used in the future for training machine or deep learning algorithms. Therefore, when generating data for the purpose of congestion control, iperf3 is the best tool, whilst Ping is useful when generating data for the purpose of detecting distributed denial-of-service attacks. …”
Get full text

Performance of predictive algorithms in estimating the risk of being a zero-dose child in India, Mali and Nigeria by Sebastian Bauhoff, John Tucker, Arpita Biswas

“…We applied supervised learning algorithms with three increasingly rich sets of predictors and multiple years of data from India, Mali and Nigeria. …”
Get full text

Deep Learning in Finance: A Survey of Applications and Techniques by Ebikella Mienye, Nobert Jere, George Obaido, Ibomoiye Domor Mienye, Kehinde Aruleba

“…Machine learning (ML) has transformed the financial industry by enabling advanced applications such as credit scoring, fraud detection, and market forecasting. …”
Get full text

Reinforcement Learning Applications in Cyber Security: A Review by Murat Gök, Emine Cengiz

“…A significant portion of our personal data is stored online and organizations run their business online. …”
Get full text

Web application firewall based on machine learning models by Muhammed Ersin Durmuşkaya, Selim Bayraklı

“…The study evaluated five classification algorithms—K-nearest neighbors, logistic regression, naïve Bayes, support vector machine, and decision tree—for detecting cross site scripting (XSS), Structured Query Language (SQL) Injection, Operating System Command Injection, and Local File Inclusion attacks. …”
Get full text

Role of artificial intelligence in enhancing mechanical ventilation – A peek into the future by Neeraj Pal Singh, Masood Ali Mujawar, Akash Golani

“…Key practical issues surrounding the implementation of AI into existing clinical workflows, including data quality, data sharing and privacy, data standardisation, seamless integration with existing healthcare systems, transparency of algorithms, interoperability across multiple platforms, patient safety and addressing ethical concerns, remain. …”
Get full text

Effective Dose Estimation in Computed Tomography by Machine Learning by Matteo Ferrante, Paolo De Marco, Osvaldo Rampado, Laura Gianusso, Daniela Origgi

“…E calculated by DTS was chosen as the target value for prediction. Different machine learning algorithms were selected, optimizing parameters to achieve the best performance for each algorithm. …”
Get full text

Anomaly Detection in Blockchain Systems Leveraging Immutable Audit Trails for Enhanced Security by Hafiz Gulfam Ahmad Umar, Kashif Iqbal, Sajida Raz Bhutto, Asad Raza, Ammar Oad

“…Some of the key objectives include investigating how and to what extent immutable audit trails are effective toward security, enhancing security and transparency in such systems, and applying machine learning techniques to improve anomaly detection. The resultant research would lead to the development of more secure and efficient blockchain-based systems that can benefit a wide range of industries, especially those where data security and integrity are of utmost importance. …”
Get full text

Hybrid CNN-LSTM With Attention Mechanism for Robust Credit Card Fraud Detection by Iman Akour, Nour Mohamed, Said Salloum

“…Our hybrid CNN-LSTM-Attention model improves fraud detection by addressing both spatial and temporal data features while dynamically focusing on critical elements. …”
Get full text

Advanced Classifiers and Feature Reduction for Accurate Insomnia Detection Using Multimodal Dataset by Ameya Chatur, Mostafa Haghi, Nagarajan Ganapathy, Nima TaheriNejad, Ralf Seepold, Natividad Martinez Madrid

Get full text

Graph-Based COVID-19 Detection Using Conditional Generative Adversarial Network by Imran Ihsan, Azhar Imran, Tahir Sher, Mahmood Basil A. Al-Rawi, Mohammed A. Elmeligy, Muhammad Salman Pathan

“…These reconstructed features serve as input to a classification module, comprising a multi-layer neural network, GCN, adept at processing graph-structured data, alongside conventional machine learning classifiers such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Random Forest (RF), facilitating categorization of chest X-ray images into COVID-19, pneumonia, and normal cases. …”
Get full text

UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION by Vimal Gaur, Naman Veerwal, Ujjwal Chaudhary, Sparsh Kadian

“…Through meticulous preprocessing, including stemming and TF-IDF vectorization, the system optimizes textual data for analysis. Powered by Multinomial Naive Bayes and Passive Aggressive Classifier algorithms, Fake News Detection System ensures accurate classification. …”
Get full text

Explainability of Network Intrusion Detection Using Transformers: A Packet-Level Approach by Pahavalan Rajkumardheivanayahi, Ryan Berry, Nicholas U. Costagliola, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul

“…Machine learning based NIDS models leverage algorithms that learn from historical network traffic data to identify patterns and anomalies to capture complex relationships. …”
Get full text

Tensor RT optimized driver drowsiness detection system using edge device by Chandramohan Dhasarathan, Sambasivam Gnanasekaran, Arnab Pattanayak, Gourav Kumar, Kartik Vig, Vaibhav Narain, K.M. Deva Narayan, Sunidhi Garg

“…The system uses transfer learning techniques for implementing CNN model algorithms to analyze live video from the camera module, allowing for real-time detection of driver behavior such as fatigue or distraction. …”
Get full text

Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review by Seng Hansun, Ahmadreza Argha, Ivan Bakhshayeshi, Arya Wicaksana, Hamid Alinejad-Rokny, Greg J Fox, Siaw-Teng Liaw, Branko G Celler, Guy B Marks

“…ObjectiveWe aimed to provide a comprehensive evaluation of AI-based algorithms for TB detection across various data modalities. …”
Get full text

FedAware: a distributed IoT intrusion detection method based on fractal shrinking autoencoder by Keyuan Qiu, Meifang Yan, Tao Luo, Feng Chen

“…If the data from all devices is uploaded to a central server for centralised learning, it will not only face the pressure of computation and storage, but may also trigger the risk of privacy leakage. …”
Get full text

Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“… Human intervention cannot halt natural disasters like earthquakes, but machine learning application expertise can be utilized to detect patterns in data and increase understanding and predictive power. …”
Get full text