SVR-Optimized ANN Model for Predicting Earthquake Risk in Electrical Substations Based on Disaster Datasets in the Aceh Region, Indonesia by Elvy Sahnur Nasution, Yuwaldi Away, Syahrial, Ira Devi Sara, Andri Novandri

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A Comprehensive Approach to Intrusion Detection in IoT Environments Using Hybrid Feature Selection and Multi-Stage Classification Techniques by G. Logeswari, J. Deepika Roselind, K. Tamilarasi, V. Nivethitha

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Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study by Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

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BACAD: AI-based framework for detecting vertical broken access control attacks by Ahmed Anas, Ayman A. Alhelbawy, Salwa El Gamal, Basheer Youssef

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Detecting Cyber Threats in UWF-ZeekDataFall22 Using K-Means Clustering in the Big Data Environment by Sikha S. Bagui, Germano Correa Silva De Carvalho, Asmi Mishra, Dustin Mink, Subhash C. Bagui, Stephanie Eager

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UNION: A Trust Model Distinguishing Intentional and Unintentional Misbehavior in Inter-UAV Communication by Ezedin Barka, Chaker Abdelaziz Kerrache, Nasreddine Lagraa, Abderrahmane Lakas, Carlos T. Calafate, Juan-Carlos Cano

“…Our proposal simultaneously establishes the inter-UAV trust and estimates the current context in terms of UAV energy, mobility pattern, and enqueued packets, in order to ensure full context awareness in the overall honesty evaluation. In addition, based on computed trust and context metrics, we also propose a new inter-UAV packet delivery strategy. …”
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Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation by Gozewijn D Laverman, Stennie Zoet, Thomas Urgert, Anouk Veldhuis, Bert-Jan van Beijnum

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Temporal record linkage for heterogeneous big data records by Reham I. Abdel Monem, Ehab E. Hassanein, Ali Z. El Qutaany

“…Existing frameworks which are limited to, No model, Decay, Disprob, Mixed, and Agreement First Dynamic Second (AFDS) which deal with temporal record linkage achieve high accuracy but with high computation cost. They condition the presence of the time dimension to detect similar entities that refer to the same real-world object. …”
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Improvement of YOLO v8 Segmentation Algorithm and Its Study in the Identification of Hazards in Plateau Pika by Yaosheng Han, Yunpeng Jin, Chunmei Li, Xiangjie Huang

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An Interactive Framework for Personalized Navigation Based on Metacosmic Cultural Tourism and Large Model Fine-Tuning by Hang Guo, Zhiqiang Liu, Chuanqian Tang, Xiaodan Zhang

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SCH-Hunter: A Taint-Based Hybrid Fuzzing Framework for Smart Contract Honeypots by Haoyu Zhang, Baotong Wang, Wenhao Fu, Leyi Shi

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An Efficient Network-Based QoE Assessment Framework for Multimedia Networks Using a Machine Learning Approach by Parsa Hassani Shariat Panahi, Amir Hossein Jalilvand, Abolfazl Diyanat

“…The framework leverages Machine Learning (ML) to model the relationship between network parameters and QoE, providing a scalable and efficient solution for real-time QoE evaluation in multimedia networks.By focusing exclusively on network metrics (e.g., delay, jitter, and packet loss), it eliminates the need for video-specific parameters to calculate MOS. …”
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Time-frequency feature calculation of multi-stage audiovisual neural processing via electroencephalogram microstates by Yang Xi, Lu Zhang, Cunzhen Li, Xiaopeng Lv, Zhu Lan

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Expediency Analysis of Clustering Algorithms for Electric Two-Wheeler Driving Cycle Development Under Indian Smart City Driving Conditions by Azhaganathan Gurusamy, Akshat Bokdia, Harsh Kumar, A. Radhika, Bragadeshwaran Ashok, Chellamuthu Gunavathi

“…The standard driving cycles (DCs) used to evaluate spark-ignition engine-based two-wheelers are inadequate for electric two-wheelers (E2Ws). …”
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ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

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Power system corrective control considering topology adjustment: An evolution-enhanced reinforcement learning method by Haoran Zhang, Peidong Xu, Ji Qiao, Yuxin Dai, Yuyang Bai, Tianlu Gao, Fan Yang, Jun Zhang, Jun Hao, Wenzhong Gao

“…Conventional corrective control methods often struggle to balance computational speed with control optimality. In contrast, deep reinforcement learning facilitates faster control. …”
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Spatial prediction and visualization of PM2.5 susceptibility using machine learning optimization in a virtual reality environment by Seyed Vahid Razavi-Termeh, Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, X. Angela Yao, Soo-Mi Choi

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Enhancing energy consumption forecasting for electric vehicle charging stations with Time Series Dense Encoder (TiDE) by Amril Nazir, Abdul Khalique Shaikh, Aftab Ahmed Khan, Abdul Salam Shah, Nadia Khalique

“…The model’s novelty is the low computation cost, consideration of the data lagging, and day series past covariates. …”
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EEG-Based Emotion Detection Using Roberts Similarity and PSO Feature Selection by Mustafa Hussein Mohammed, Mustafa Noaman Kadhim, Dhiah Al-Shammary, Ayman Ibaida

“…Integration of Particle Swarm Optimization (PSO) for feature selection, with Robert’s similarity as the fitness function, effectively refines the feature set, boosting classification accuracy and computational efficiency. Evaluation on an EEG brainwave dataset demonstrated that the method achieved an accuracy of 98.75% with feature selection, compared to 94.04% without it in emotional state detection. …”
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Uncertainty quantification of CT regularized reconstruction within the Bayesian framework by Negin Khoeiniha, Patricio Guerrero, Wim Dewulf

“…Additionally, we aim to utilize computationally feasible sampling techniques to analyze the distribution of the solution, enabling an in-depth evaluation of the results. …”
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