Student Engagement Recognition: Comprehensive Analysis Through EEG and Verification by Image Traits Using Deep Learning Techniques by Ajitha Sukumaran, Arun Manoharan

“…In this paper, we propose an engagement recognition system that detects student engagement using EEG signals by integrating levels of valence and arousal with the Russel 2D circumplex model using deep learning algorithm. The public DEAP dataset was used for training the model to predict valence and arousal values. …”
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Insulator Defect Recognition Based on Vision Big-Model Transfer Learning and Stochastic Configuration Network by Siyuan Liu, Yihua Ma, Zedong Zheng, Xinfu Pang, Bingyou Li

“…Second, StyleGanv3 adversarial generative networks are used to augment the dataset of defective insulators, which enhances dataset diversity. …”
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The Fundus Autofluorescence Spectrum of Punctate Inner Choroidopathy by Miaoling Li, Xiongze Zhang, Feng Wen

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On the Measurement of Laser Lines in 3D Space with Uncertainty Estimation by Ivan De Boi, Nasser Ghaderi, Steve Vanlanduit, Rudi Penne

“…Our approach to composing an accurate dataset of lines utilises a standard webcam and a checkerboard, avoiding the need for specialised hardware. …”
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End-to-End Semantic Leaf Segmentation Framework for Plants Disease Classification by Khalil Khan, Rehan Ullah Khan, Waleed Albattah, Ali Mustafa Qamar

“…Along with PlantVillage, we also collected a dataset of twenty thousand images and tested our framework on it. …”
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Propithecus verreauxi demography spanning 40 years at Bezà Mahafaly Special Reserve, southwest Madagascar by Joelisoa Ratsirarson, Jeannin Ranaivonasy, Richard Lawler, Isabella Fiorentino, Nelson Rios, Alison Richard

“…Data provide information on male and female life history parameters, individual development and aging, and social group dynamics. The dataset is an important resource for both research and management.…”
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Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…Fine-tuning the hyperparameters with the help of Bayesian optimization to obtain the best model performance is another important thing that we do in our model. Two datasets, InSDN and CICDDoS-2019, are utilized to assess the effectiveness of the proposed method, 99.95% for the true positive (TP) of the CICDDoS-2019 dataset and 99.98% for the InSDN dataset, the results show that the model is highly accurate.…”
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The Fruit Recognition and Evaluation Method Based on Multi-Model Collaboration by Mingzheng Huang, Dejin Chen, Dewang Feng

“…The improved YOLOv8 model improves the P, R, mAP50, and MAP50-95 indicators by 2.4%, 2.1%, 1%, and 1.3%, respectively, compared with the baseline model on only one generalized “fruit” label dataset. The classification model Swin Transformer used in this study has a classification accuracy of 92.6% on a dataset of 27 fruit categories, and the feature matching network based on cosine similarity can calibrate the classification results with low confidence. …”
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A feature-based approach for atlas selection in automatic pelvic segmentation. by Guoping Shan, Xue Bai, Yun Ge, Binbing Wang

“…However, atlas-based segmentation still faces challenges due to the lack of representative atlas dataset and the computational limitations of deformation algorithms. …”
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Quantitative Analysis of the Main Controlling Factors of Oil Saturation Variation by Ruijie Huang, Chenji Wei, Jian Yang, Xin Xu, Baozhu Li, Suwei Wu, Lihui Xiong

“…A total of 10 machine learning algorithms are tested and compared in the dataset. Random forest (RF) and gradient boosting (GBT) are optimal and selected to conduct quantitative analysis of the main controlling factors. …”
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Disease Identification of Lentinus Edodes Sticks Based on Deep Learning Model by Dawei Zu, Feng Zhang, Qiulan Wu, Wenyan Wang, Zimeng Yang, Zhengpeng Hu

“…Second, based on the ResNeXt-50(32 × 4d) model and the pretraining weight of the ImageNet dataset, the influence of pretraining weight parameters on recognition accuracy was studied. …”
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Unstructured Big Data Threat Intelligence Parallel Mining Algorithm by Zhihua Li, Xinye Yu, Tao Wei, Junhao Qian

“…Furthermore, our proposed PDFMLC algorithm incorporates label mutual information from the established dataset as input features. This captures latent label associations, significantly improving classification accuracy. …”
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A study of serum brain-derived neurotrophic factor level in individuals with obsessive compulsive disorder and their first-degree relatives as compared to the healthy population by Shaily Mina, Rupam Dhiman, Prakamya Singal, Sukanya Gangopadhyay, Pankaj Verma, Shivani Kathuria

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A novel deep learning-based 1D-CNN-optimized GRU approach for heart disease prediction by Jini Mol G., Ajith Bosco Raj T.

“…The suggested method attained a training accuracy of over 97% and a test accuracy of over 96% on the dataset. The proposed model’s overall accuracy is 99%. …”
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The Association of the Pulmonary Artery Pulsatility Index and Right Ventricular Function after Cardiac Surgery by Johnny Wei, Abigail Kee, Rachel Dukes, Jack Franke, Vincent Leonardo, Brigid C. Flynn

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Fault Diagnosis Approach for Rotating Machinery Based on Feature Importance Ranking and Selection by Zong Yuan, Taotao Zhou, Jie Liu, Changhe Zhang, Yong Liu

“…Thirdly, the categorical boosting (CatBoost) algorithm is introduced to rank the fault features by a certain strategy, and the optimal feature set is further utilized to identify and diagnose the fault types. A hybrid dataset of bearing and rotor faults and an actual dataset of the one-stage reduction gearbox are utilized for experimental verification. …”
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A Lightweight Person Detector for Surveillance Footage Based on YOLOv8n by Qicheng Wang, Guoqiang Feng, Zongzhe Li

“…Additionally, on a custom surveillance dataset, the model shows a 1.4% improvement in mAP@0.5:0.95, and on a more complex subset of the PASVOC public dataset, the model achieved a 2.8% improvement in mAP@0.5 and a 1.2% improvement in mAP@0.5:0.95, proving the high accuracy and generalization ability of the improved lightweight model.…”
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High-throughput methylation sequencing reveals novel biomarkers for the early detection of renal cell carcinoma by Wenhao Guo, Weiwu Chen, Jie Zhang, Mingzhe Li, Hongyuan Huang, Qian Wang, Xiaoyi Fei, Jian Huang, Tongning Zheng, Haobo Fan, Yunfei Wang, Hongcang Gu, Guoqing Ding, Yicheng Chen

“…Using a training set from The Cancer Genome Atlas (TCGA) dataset of 443 early-stage RCC tumors and matched normal tissues, we applied LASSO regression and identified 23 methylation signatures. …”
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Analisis Perilaku Entitas untuk Pendeteksian Serangan Internal Menggunakan Kombinasi Model Prediksi Memori dan Metode PCA by Rahmat - Budiarto, Yanif Dwi Kuntjoro

“…Algoritma PCA diterapkan untuk mengurangi jumlah fitur trafik sehingga mempercepat proses deteksi, Data untuk percobaan diambil dari jaringan nyata dengan 150 pengguna dan data serangan flooding dari dataset MACCDC. Hasil eksperimen dalam suatu jaringan testbed menunjukkan hasil akurasi pendeteksian mencapai 94.01%, presisi 95.64%, Sensitivitas 99.28% dan F1-Score 96.08%. …”
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Risk of hepatocellular carcinoma in Asian patients with primary biliary cholangitis: A nationwide and hospital cohort study by Jihye Lim, Ye-Jee Kim, Sehee Kim, Jonggi Choi

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