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

“…The AI model at the core of BACAD analyzes web requests and responses utilizing a robust feature extraction, and dynamic hyperparameter tuning to ensure optimal performance across diverse scenarios. …”
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Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection by Vikas Gaur, Gaurav Maggu, Khushboo Bairwa, Suprakash Chaudhury, Sana Dhamija, Tahoora Ali

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Toward Automatic Detection of Pi2 Magnetic Pulsation Using Machine Learning by Mohamed S. Abdalzaher, Essam Ghamry, Khairul Adib Yusof, Mostafa Shaaban

“…This paper introduces a novel ML-based classification framework that utilizes geomagnetic field data for Pi2 pulsation detection. A comprehensive analysis of various linear, ensemble, and non-linear ML models was conducted, employing hyperparameter optimization to identify the optimal model with high classification performance and minimal computational overhead during testing. …”
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PREDICTIVE MODELS FOR EARLY DETECTION OF PARKINSON’S DISEASE: A MACHINE LEARNING APPROACH by S. Jeyantha Jafna Juliet, D. Jasmine David, J. S. Raj Kumar, Angelin Jeba P., R. Golden Nancy, M. Selvarathi, T. Jemima Jebaseeli

“…Additionally, integrating wearable sensors and mobile health technologies further enhances the feasibility of continuous monitoring and early detection, providing patients and healthcare practitioners with the tools they need to manage PD proactively. …”
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Particle swarm optimization with YOLOv8 for improved detection performance of tomato plants by Sarah M. Ayyad, Nada M. Sallam, Samah A. Gamel, Zainab H. Ali

“…In a faster-growing world, there is a growing demand for fully automated tomato detection and grading systems. Within the past few years, applying deep learning in detecting and classifying tomatoes into different classes has gained popularity. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…Medical diagnosis plays a critical role in the early detection and treatment of diseases by examining symptoms and supporting findings through advanced laboratory testing. …”
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Optimization of Convolutional Neural Networks With Multi-Objective Function Metaheuristics for Melanoma Detection by Pamela Hermosilla, Ricardo Soto, Eric Monfroy, Emanuel Vega, Lucas Erazo, Valentina Guzman

“…Early and accurate detection of melanoma remains a critical challenge in medical imaging. …”
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Detection of Coffee Leaf Miner Using RGB Aerial Imagery and Machine Learning by Emerson Ferreira Vilela, Cileimar Aparecida da Silva, Jéssica Mayara Coffler Botti, Elem Fialho Martins, Charles Cardoso Santana, Diego Bedin Marin, Agnaldo Roberto de Jesus Freitas, Carolina Jaramillo-Giraldo, Iza Paula de Carvalho Lopes, Lucas de Paula Corrêdo, Daniel Marçal de Queiroz, Giuseppe Rossi, Gianluca Bambi, Leonardo Conti, Madelaine Venzon

“…The combined use of vegetation indices and crop data increased the accuracy of coffee leaf miner detection. The RF model performed poorly, while the SVM and SGD models performed better. …”
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Research on emulsion concentration detection technology based on interpretable machine learning methods by Jiaxu Kang, Jianwei Li, Meng Wang, Xinwei Guo, Dinghao Liu, Chao Qu, Chengbin Guo

“…However, existing underground emulsion concentration detection modules suffer from high failure rates and insufficient accuracy. …”
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Malware Detection in Forensic Memory Dumps: The Use of Deep Meta-Learning Models by Yalçın Özkan

“…Accordingly, considering the acquired performance value, it can be determined that high performance is achieved in malware detection, and thus what hyperparameters ensure success can be revealed. …”
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A hybrid ensemble framework with particle swarm optimization for network anomaly detection by Narinder Verma, Neerendra Kumar, Gourav Kumar, Kuljeet Singh

“…Traditional IDS approaches often struggle to detect sophisticated attacks due to their reliance on predefined patterns. …”
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Software engineering meets legal texts: LLMs for auto detection of contract smells by Moriya Dechtiar, Daniel Martin Katz, Hongming Wang

“…We leverage semi-auto labeling with GPT-4, prompting and expert spot checks, to create datasets for suitability testing of auto detection of these contract smells. Using transformer-based models, we explore the impact of legal domain knowledge, hyperparameters fine tuning and specific task information on detection success. …”
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An optimized multi-task contrastive learning framework for HIFU lesion detection and segmentation by Matineh Zavar, Hamid Reza Ghaffari, Hamid Tabatabaee

“…Abstract Accurate detection and segmentation of lesions induced by High-Intensity Focused Ultrasound (HIFU) in medical imaging remain significant challenges in automated disease diagnosis. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The unique characteristics of 5G networks, while enabling advanced communication, present challenges in distinguishing between legitimate and malicious traffic, making it more difficult to detect anonymous traffic. Current methodologies for intrusion detection within 5G communication exhibit limitations in accuracy, efficiency, and adaptability to evolving network conditions. …”
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Maximizing YOLOv2 efficiency: A study on multiclass detection of indoor objects by G Divya Deepak, Subraya Krishna Bhat

“…The objective of the present study is to present a systematic approach for optimizing the key hyperparameters of YOLOv2 model for multiclass object detection, specifically targeting seven classes of indoor objects: chair, fire extinguisher, printer, screen, trash bin, exit, and clock. …”
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Novel transfer learning based bone fracture detection using radiographic images by Aneeza Alam, Ahmad Sami Al-Shamayleh, Nisrean Thalji, Ali Raza, Edgar Anibal Morales Barajas, Ernesto Bautista Thompson, Isabel de la Torre Diez, Imran Ashraf

“…The proposed study can improve the detection of bone fractures using X-ray images.…”
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Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data by H. T. Rüdisser, A. Windisch, U. V. Amerstorfer, C. Möstl, T. Amerstorfer, R. L. Bailey, M. A. Reiss

“…The relatively fast training allows straightforward tuning of hyperparameters and could therefore easily be used to detect other structures and phenomena in solar wind data, such as corotating interaction regions.…”
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An optimized LSTM-based deep learning model for anomaly network intrusion detection by Nitu Dash, Sujata Chakravarty, Amiya Kumar Rath, Nimay Chandra Giri, Kareem M. AboRas, N. Gowtham

“…Over time, intrusion detection systems have been instrumental in identifying network breaches and deviations. …”
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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…The importance of early detection and diagnosis cannot be overstated in enhancing the survival prospects of those afflicted with breast cancer. …”
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Adaptive anomaly detection disruption prediction starting from first discharge on tokamak by X.K. Ai, W. Zheng, M. Zhang, Y.H. Ding, D.L. Chen, Z.Y. Chen, B.H. Guo, C.S. Shen, N.C. Wang, Z.J. Yang, Z.P. Chen, Y. Pan, B. Shen, B.J. Xiao, J-TEXT team

“…To address these challenges, this study further develops the enhanced convolutional autoencoder anomaly detection (E-CAAD) predictor and proposes a cross-tokamak adaptive transfer method based on E-CAAD. …”
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