Enhancing phishing detection with dynamic optimization and character-level deep learning in cloud environments by Vishnukumar Ravula, Mangayarkarasi Ramaiah

“…As cloud computing becomes increasingly prevalent, the detection and prevention of phishing URL attacks are essential, particularly in the Internet of Vehicles (IoV) environment, to maintain service reliability. …”
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Ransomware detection and family classification using fine-tuned BERT and RoBERTa models by Amjad Hussain, Ayesha Saadia, Faeiz M. Alserhani

“…This research explores these challenges and proposes a novel approach using hyperparameter-optimized transfer learning-based models, Bidirectional Encoder Representations from Transformers (BERT), and a Robustly Optimized BERT Approach (RoBERTa), to not only detect but also classify ransomware targeting IoT devices by analyzing dynamically executed API call sequences in a sandbox environment. …”
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Computer Vision With Explainable Artificial Intelligence for Visual Pollution Detection in the Kingdom of Saudi Arabia by Alanoud Al Mazroa, Mohammed Maray, Abdullah M. Alashjaee, Faiz Abdullah Alotaibi, Ahmad A. Alzahrani, Abdulwhab Alkharashi, Shoayee Dlaim Alotaibi, Mrim M. Alnfiai

“…Therefore, this study focuses on designing and developing the Modeling of Computer Vision with Explainable Artificial Intelligence for Visual Pollution Detection (MCVXAI-VPD) model. The MCVXAI-VPD model involves DL-based object detection and classification with a hyperparameter tuning strategy. …”
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OncoFusion: Multi-Model Approach for Generalized and Ovarian Cancer Detection with Stacked Ensembles by Zaware Sarika, Neharkar Rutuja, Sayyad Ayesha, Patil Aarya, Mulla Salma

“…Cancer detection is a critical task in the medical field, where accurate and early diagnosis can save lives. …”
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Cyberattack Detection Systems in Industrial Internet of Things (IIoT) Networks in Big Data Environments by Abdullah Orman

“…Additionally, the study explores a broad range of hyperparameter configurations, optimizing model effectiveness for IIoT-specific intrusion detection. …”
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Machine Learning for Accurate Office Room Occupancy Detection Using Multi-Sensor Data by Yusuf Ibrahim, Umar Yusuf Bagaye, Abubakar Ibrahim Muhammad

“…In this paper, we present a comparative study of several machine learning (ML) approaches for accurate office room occupancy detection through the analysis of multi-sensor data. …”
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Multi-domain Urdu fake news detection using pre-trained ensemble model by Sheetal Harris, Hassan Jalil Hadi, Naveed Ahmad, Mohammed Ali Alshara

“…Natural Language Processing (NLP) techniques have been used for Fake News Detection (FND) for English news and various language-related tasks. …”
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Detecting cognitive impairment in cerebrovascular disease using gait, dual tasks, and machine learning by Vânia Guimarães, Inês Sousa, Miguel Velhote Correia

“…Nested cross-validation was used for model training, hyperparameter tuning, and evaluation. Grid search with cross-validation was used to optimize the hyperparameters of a set of feature selectors and classifiers. …”
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Feasibility of EfficientDet-D3 for Accurate and Efficient Void Detection in GPR Images by Sung-Pil Shin, Sang-Yum Lee, Tri Ho Minh Le

“…The detection of voids in pavement infrastructure is essential for road safety and efficient maintenance. …”
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An efficient bearing fault detection strategy based on a hybrid machine learning technique by Khalid Alqunun, Mohammed Bachir Bechiri, Mohamed Naoui, Abderrahmane Khechekhouche, Ismail Marouani, Tawfik Guesmi, Badr M. Alshammari, Amer AlGhadhban, Abderrahim Allal

“…The methodology also incorporates machine learning model tuning through Tree-Structured Parzen Estimators (TPE) for optimal hyperparameter adjustment, ensuring high-performance classification. …”
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Driven early detection of chronic kidney cancer disease based on machine learning technique. by Wafa Almukadi, Sayed Abdel-Khalek, Adel A Bahaddad, Ahmed Mohammed Alghamdi

“…Moreover, the SO model is used to tune the hyperparameter of the SE-DenseNet method. Finally, the bidirectional long shortterm memory (BiLSTM) model is implemented to detect and classify kidney cancer. …”
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CDK: A novel high-performance transfer feature technique for early detection of osteoarthritis by Mohammad Shariful Islam, Mohammad Abu Tareq Rony

“…This underscores the need for more advanced diagnostic methods, such as machine learning (ML) and deep learning (DL), to improve OA detection and classification. This research introduces a novel ensemble learning approach for image data feature extraction which ingeniously combines the strengths of 2 advanced (ML) models with a (DL) method to substantially improve the accuracy of OA detection from radiographic images. …”
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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

“…The BMLSSA-CAD technique uses the Bayesian Belief Network (BBN) model for cyberattack detection. The hyperparameter tuning process employs the sparrow search algorithm (SSA) model to enhance the BBN model performance. …”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…To address the current challenges in fire detection algorithms, including insufficient feature extraction, high computational complexity, limited deployment on resource-constrained devices, missed detections, false detections, and low accuracy, we developed a high-precision algorithm named GSF-YOLOv8. …”
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Distributed optimization for IoT attack detection using federated learning and Siberian Tiger optimizer by Brij B. Gupta, Akshat Gaurav, Wadee Alhalabi, Varsha Arya, Eman Alharbi, Kwok Tai Chui

“…The rapid growth of IoT devices has heightened the risk of botnet attacks, calling for scalable and distributed detection solutions. In this context, this study proposes a distributed optimization system for IoT attack detection using CNN model utilizing federated learning. …”
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LSTM-JSO framework for privacy preserving adaptive intrusion detection in federated IoT networks by Shaymaa E. Sorour, Mohammed Aljaafari, Amany M. Shaker, Ahmed E. Amin

“…This research introduces a novel framework that enhances intrusion detection in IoT systems through a decentralized approach. …”
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A Weak Signal Detection Method Based on HFER Features in Sea Clutter Background by Yan Yan, Yongxian Song, Hongyan Xing, Zhengdong Qi

“…This feature detection approach significantly enhances the detection performance of weak signals against the backdrop of sea clutter. …”
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A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
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Automated Early-Stage Glaucoma Detection Using a Robust Concatenated AI Model by Wheyming Song, Ing-Chou Lai

“…Glaucoma is a leading cause of irreversible blindness worldwide; therefore, detection of this disease in its early stage is crucial. …”
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CNN-ViT: A multi-feature learning based approach for driver drowsiness detection by Madduri Venkateswarlu, Venkata Rami Reddy Chirra

“…The strong results, supported by optimized hyperparameters, highlight the reliability and effectiveness of the hybrid model for real-time driver drowsiness detection.…”
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