An AI recognition method for children's clinical operative pain by skin potential (SP) signal by Mingxuan Huang, Cangcang Fu, Linbo Chui, Jiadong He, Xiaozhi Wang, Jikui Luo, Bin Wu, Yonggang Chen, Shaohua Hu, Jihua Zhu, Yubo Li

Get full text

Ultrawideband Non-Line-of-Sight Classification Using Transformer-Convolutional Neural Networks by Hae-Ji Hwang, Seon-Geun Jeong, Won-Joo Hwang

Get full text

Educational Data Mining by Optimally Fusing Shallow and Deep Features by Bo-An Xiao

“…In order to meet the requirement of designing the educational curriculum and extract the relevant data toward students, we in this paper utilize the deep learning architecture to study the personalized understanding and educational feature extraction algorithm of the high school and college students. …”
Get full text

Development of Self-Powered Energy-Harvesting Electronic Module and Signal-Processing Framework for Wearable Healthcare Applications by Jegan Rajendran, Nimi Wilson Sukumari, P. Subha Hency Jose, Manikandan Rajendran, Manob Jyoti Saikia

Get full text

Designing natural gesture interaction for archaeological data in immersive environments by Niccolò Albertini, Andrea Brogni, Riccardo Olivito, Emanuele Taccola, Baptiste Caramiaux, Marco Gillies

“…Interactive machine learning techniques have been used for the real time detection of the gestures. …”
Get full text

Leveraging Digital Twin for operational resilience in the oil and gas industry by Giovanni Mazzuto, Ilaria Pietrangeli, Marco Ortenzi, Filippo Emanuele Ciarapica, Maurizio Bevilacqua

Get full text

Wind Turbine SCADA Data Imbalance: A Review of Its Impact on Health Condition Analyses and Mitigation Strategies by Adaiton Oliveira-Filho, Monelle Comeau, James Cave, Charbel Nasr, Pavel Côté, Antoine Tahan

“…Five categories of such strategies were identified: Normal Behavior Models (NBMs), data-level strategies, algorithm-level strategies, cost-sensitive learning, and data augmentation techniques. …”
Get full text

Comparative Analysis of Anomaly Detection Techniques Using Generative Adversarial Network by Imran Ullah Khan, Shah Noor, Ahthasham Sajid, Junaid Javaid, Iqra Tabasusum

“…This paper places a special emphasis on Generative Adversarial Network-based algorithms for anomaly detection, since it is the most widely used machine-learning based algorithm for anomaly detection.  …”
Get full text

Towards Effective Parkinson’s Monitoring: Movement Disorder Detection and Symptom Identification Using Wearable Inertial Sensors by Umar Khan, Qaiser Riaz, Mehdi Hussain, Muhammad Zeeshan, Björn Krüger

“…The proposed pipeline employs and evaluates manual feature crafting for classical machine learning algorithms, as well as an RNN-CNN-inspired deep learning model that does not require manual feature crafting. …”
Get full text

Target recognition in diverse synthetic aperture radar image datasets with low size weight and power processing hardware by Richard O. Lane, Wendy J. Holmes, Timothy Lamont‐Smith

“…Abstract This paper studies the performance of target detection and classification algorithms applied to synthetic aperture radar (SAR) data. …”
Get full text

Prediction of Anemia from Multi-Data Attribute Co-Existence by Talal Qadah, Asmaa Munshi

Get full text

GaussianMix: Rethinking Receptive Field for Efficient Data Augmentation by A. F. M. Shahab Uddin, Maryam Qamar, Jueun Mun, Yuje Lee, Sung-Ho Bae

“…Mixed Sample Data Augmentation (MSDA) enhances deep learning model generalization by blending a source patch into a target image. …”
Get full text

Enhancing Student Management Through Hybrid Machine Learning and Rough Set Models: A Framework for Positive Learning Environments by Ateeq Ur Rehman Butt, Hamid Ali, Muhammad Asif, Hessa Alfraihi, Mohamad Khairi Ishak, Khalid Ammar

“…The model combines classification algorithms with rough set-based decision rules to analyze complex student data, including academic performance, behavior patterns, and levels of engagement. …”
Get full text

GSB: GNGS and SAG-BiGRU network for malware dynamic detection. by Zhanhui Hu, Guangzhong Liu, Xinyu Xiang, Yanping Li, Siqing Zhuang

“…For solving the problem, this study proposed the GNGS algorithm to construct a new balance dataset for the model algorithm to pay more attention to the feature learning of the minority attacks' malware to improve the detection rate of attacks' malware. …”
Get full text

Leveraging Bias in Pre-trained Word Embeddings for Unsupervised Microaggression Detection by Tolúlọpẹ́ Ògúnrẹ̀mí, Valerio Basile, Tommaso Caselli

“…We test the method on a dataset of racial and gender-based microaggressions, reporting promising results. We further run the algorithm on out-of-domain unseen data with the purpose of bootstrapping corpora of microaggressions “in the wild”, perform a pilot experiment with prompt-based learning, and discuss the benefits and drawbacks of our proposed method.1…”
Get full text

A Public Dataset of Annotated Orcinus orca Acoustic Signals for Detection and Ecotype Classification by K. J. Palmer, Emma Cummings, Michael G. Dowd, Kait Frasier, Fabio Frazao, Alex Harris, April Houweling, Jasper Kanes, Oliver S. Kirsebom, Holger Klinck, Holly LeBlond, Lauren Laturnus, Craig Matkin, Olivia Murphy, Hannah Myers, Dan Olsen, Caitlin O’Neill, Bruno Padovese, James Pilkington, Lucy Quayle, Amalis Riera Vuibert, Krista Trounce, Svein Vagle, Scott Veirs, Val Veirs, Jen Wladichuk, Jason Wood, Tina Yack, Harald Yurk, Ruth Joy

Get full text

A refined lion optimizer for deep learning by Jian Rong, Chenhao Ma, Qinghui Zhang, Yong Cao, Weili Kou

“…The YOLOV8, YOLOV11 on VOC2012 data and Object detection with Vision Transformers on Caltech 101 dataset are trained for Object detection. …”
Get full text

Multiple Sclerosis Lesion Detection Using Constrained GMM and Curve Evolution by Oren Freifeld, Hayit Greenspan, Jacob Goldberger

“…The CGMM-CE algorithm is automated and does not require an atlas for initialization or parameter learning. …”
Get full text

Anomaly detection in virtual machine logs against irrelevant attribute interference. by Hao Zhang, Yun Zhou, Huahu Xu, Jiangang Shi, Xinhua Lin, Yiqin Gao

“…However, its performance may vary when applied to disordered log data. This highlights the necessity of carefully selecting detection methods that align with the specific characteristics of different log data types.…”
Get full text

Swarm learning network for privacy-preserving and collaborative deep learning assisted diagnosis of fracture: a multi-center diagnostic study by Yi Xie, Yi Xie, Xinmeng Wang, Huiwen Yang, Huiwen Yang, Jiayao Zhang, Honglin Wang, Zineng Yan, Jiaming Yang, Zhiyuan Yan, Zhiwei Hao, Pengran Liu, Yijie Kuang, Zhewei Ye, Zhewei Ye

“…BackgroundWhile artificial intelligence (AI) has revolutionized medical diagnostics, conventional centralized AI models for medical image analysis raise critical concerns regarding data privacy and security. Swarm learning (SL), a decentralized machine learning framework, addresses these limitations by enabling collaborative model training through secure parameter aggregation while preserving data locality. …”
Get full text