Intrusion Detection System Framework for SDN-Based IoT Networks Using Deep Learning Approaches With XAI-Based Feature Selection Techniques and Domain-Constrained Features by Manlaibaatar Tserenkhuu, Md Delwar Hossain, Yuzo Taenaka, Youki Kadobayashi

“…This study proposes an IDS framework to detect various cyberattacks in SDN-based IoT networks utilizing three deep learning algorithms that incorporate hyperparameter tuning and the feature selection process based on explainable artificial intelligence (XAI), which uses domain-constrained features to improve performance and reduce computational complexity. …”
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OPTIMIZING LONG TEXT CLASSIFICATION PERFORMANCE THROUGH KEYWORD-BASED SENTENCE SELECTION: A CASE STUDY ON ONLINE NEWS CLASSIFICATION FOR INDONESIAN GDP GROWTH-RATE DETECTION by Dinda Pusparahmi Sholawatunnisa, Lya Hulliyyatus Suadaa

“…Additionally, in terms of computational efficiency, sentence selection also accelerates processing time during hyperparameter tuning and fine-tuning, as observed using the same computational resources.…”
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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…In this study, we propose an optimized hybrid DL framework that combines a transformer, generative adversarial network (GAN), and autoencoder (AE) components, referred to as Transformer–GAN–AE, for robust intrusion detection in Edge and IIoT environments. To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. …”
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Efficient Fault Diagnosis of Elevator Cabin Door Drives Using Machine Learning with Data Reduction for Reliable Transmission by Jakub Gęca, Dariusz Czerwiński, Bartosz Drzymała, Krzysztof Kolano

“…A comparative analysis of the fault detection performance of seven different machine learning algorithms was conducted. …”
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Secure Biometric Identification Using Orca Predators Algorithm With Deep Learning: Retinal Iris Image Analysis by Louai A. Maghrabi, Mohammed Altwijri, Sami Saeed Binyamin, Fouad Shoie Alallah, Diaa Hamed, Mahmoud Ragab

“…To validate the enhanced biometric detection results of the SBRIC-OPADL technique is tested using the biometric iris dataset. …”
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BibMon: An open source Python package for process monitoring, soft sensing, and fault diagnosis by Afrânio Melo, Tiago S.M. Lemos, Rafael M. Soares, Deris Spina, Nayher Clavijo, Luiz Felipe de O. Campos, Maurício Melo Câmara, Thiago Feital, Thiago K. Anzai, Pedro H. Thompson, Fábio C. Diehl, José Carlos Pinto

“…This paper introduces BibMon, a Python package that provides predictive models for data-driven fault detection and diagnosis, soft sensing, and process condition monitoring. …”
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Application of laser light backscattering for qualitative and quantitative assessment of dilution of clear and cloudy apple juices by Hoa Xuan Mac, Nga Thi Thanh Ha, László Friedrich, Lien Le Phuong Nguyen, László Baranyai

“…Support vector machine (SVM) was used and the hyperparameters were optimized to maximize model performance. …”
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An analytics-driven model for identifying autism spectrum disorder using eye tracking by Deblina Mazumder Setu

“…The efficient and early detection of Autism Spectrum Disorder (ASD) is a critical objective in improving diagnosis and intervention outcomes. …”
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Rice leaf disease classification using a fusion vision approach by B. Naresh kumar, S. Sakthivel

“…Hyperparameter tuning, such as learning rate and tree depth for LightGBM, was crucial for optimizing model performance. …”
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Random Forest-Based Prediction of the Optimal Solid Ink Density in Offset Lithography by Laihu Peng, Hao Fan, Yubao Qi, Jianqiang Li

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Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities by Munya A. Arasi, Hussah Nasser AlEisa, Amani A. Alneil, Radwa Marzouk

“…They are efficient in certifying functions of detection of actions, observing crucial functions, and tracking. …”
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Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…It combines these with the Gray Wolf Optimization (GWO) algorithm to optimize the LightGBM model, thereby building a new type of reflective Distributed Denial of Service (DDoS) attack detection model. The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
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Progressive multi-scale attention neural network for pneumonia classification in chest X-rays by Mohammad Reza Mahdiani

“…Unlike previous methods that overlook fine-grained edge information or fail to integrate multi-scale contextual features, our approach synergistically combines convolutional multi-scale feature extraction using depthwise separable convolutions with cross-layer feature fusion, Transformer blocks, advanced attention mechanisms, and a custom loss function that emphasizes diagnostically relevant edge details using Canny edge detection. Evaluated on the Kaggle chest X-ray pneumonia dataset—with optimal hyperparameters determined via extensive Optuna-based search—our model achieves a cross-validated accuracy of 97.3 % ± 0.4 % and an AUC of 0.995 ± 0.002 on the test set. …”
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A digital twin-enabled fog-edge-assisted IoAT framework for Oryza Sativa disease identification and classification by Goluguri N.V. Rajareddy, Kaushik Mishra, Satish Kumar Satti, Gurpreet Singh Chhabra, Kshira Sagar Sahoo, Amir H. Gandomi

“…To boost the model's predictive accuracy, the Chaotic Honey Badger Algorithm (CHBA) is employed to optimize the CNN hyperparameters, resulting in an impressive average accuracy of 93.5 %. …”
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Attack resilient IoT security framework using multi head attention based representation learning with improved white shark optimization algorithm by Jawhara Aljabri

“…The proposed MHAID-IWSOA model employs the bidirectional gated recurrent unit with multi-head attention (BiGRU-MHA) technique for attack detection and classification. Finally, the improved white shark optimization (IWSO) technique optimally alters the hyperparameter value of the BiGRU-MHA technique and results in superior classification performance. …”
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Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management by Mahmoud Badee Rokaya Mahmoud, Dalia Ismaeil Ibrahim Hemdan, Samah Hazzaa Alajmani, Raneem Yousif Alyami, Ghada Elmarhomy, Hassan Hashim, El-Sayed Atlam

“…However, water leak detection and irrigation scheduling traditional AI models are often computationally intensive and require complex hyperparameter tuning, making them less scalable. …”
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Combating electricity fraud: Employing hybrid learning and computer vision for sustainable energy management by Jui-Sheng Chou, Nader Anwar Charaf, Dani Nugraha Limantono, Hoang-Minh Nguyen

“…Traditional methods for detecting fraudulent activities often depend on extensive data preprocessing, such as outlier removal, which can introduce biases and reduce practical effectiveness. …”
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Adaptive Focal Loss for Keypoint-Based Deep Learning Detectors Addressing Class Imbalance by Zhihao Su, Afzan Adam, Mohammad Faidzul Nasrudin

“…Keypoint-based deep learning detectors have proven highly effective in object detection tasks by predicting specific keypoints to determine object classification and location. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…These methods struggle to detect complex or subtle patterns associated with early-stage faults. …”
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Evaluating YOLOv8-Based Distance Estimation: A Comparison of OpenCV and Coordinate Attention Weighting in Blind Navigation Systems by Erwin Syahrudin, Ema Utami, Anggit Dwi Hartanto, Suwanto Raharjo

“…Subsequently, targeted optimizations were applied to the OpenCV model, including adaptive image filtering, hyperparameter tuning, and integration of a Kalman filter. …”
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