VOKATIVE AS AN ELEMENT OF UKRAINIAN SPEECH ETIQUETTE (SPECIAL FEATURES AND TRENDS IN THE FRAMEWORK OF THE NEWEST COMMUNICATIVE DISCOURSE) by Olena M. Turchak

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Synovial cesys in children: clinical features, diagnostics, treatment (analytical review of the literature and own observation) by V.S. Konoplitskyi, Yu. Ye. Korobko, B.L. Pavlenko, H.M. Rudenko, O.A. Korobko, S.V. Klymenko

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Pathogenetic Mechanisms of the Occurrence of Rheumatoid Arthritis and Ankylosing Spondylitis with the Activation-Enzymatic and Phenotypic Features of Lymphocytes by Lychkovska N., Chopyak V., Vorobets Z.

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Research on multi dimensional feature extraction and recognition of industrial and mining solid waste images based on mask R-CNN and graph convolutional networks by Shuqin Wang, Na Cheng, Yan Hu

“…Abstract Aiming at the problems of traditional methods for multi-dimensional feature extraction of industrial and mining solid waste images, such as single feature extraction, difficult fusion, missing high-order features, weak generalization ability and low computational efficiency, an innovative solution combining Mask R-CNN with Graph Convolutional Networks (GCN) was proposed to achieve automatic, multi-dimensional and efficient feature extraction. …”
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Development of critical thinking of students – future biotechnologists in the process of teaching mathematics by S. I. Toropova

“…Diagnostic tools were developed and tested. Its key feature is that the student does not work in a simulated environment, but on real problems. …”
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Research on Complex Classification Algorithm of Breast Cancer Chip Based on SVM-RFE Gene Feature Screening by Guobin Chen, Xianzhong Xie, Shijin Li

“…How to select an effective gene screening algorithm is the main problem to be solved by analyzing gene chips. The combination of KNN, SVM, and SVM-RFE is selected to screen complex classification problems, and a new method to solve complex classification problems is provided. …”
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Topological search and gradient descent boosted Runge–Kutta optimiser with application to engineering design and feature selection by Jinge Shi, Yi Chen, Ali Asghar Heidari, Zhennao Cai, Huiling Chen, Guoxi Liang

“…Additionally, the evaluation includes real‐world engineering design and feature selection problems serving as an additional test for assessing the optimisation capabilities of the algorithm. …”
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Binary Particle Swarm Optimization with Manta Ray Foraging Learning Strategies for High-Dimensional Feature Selection by Jianhua Liu, Yuxiang Chen, Shanglong Li

“…High-dimensional feature selection is one of the key problems of big data analysis. …”
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ResNet18 facial feature extraction algorithm improved based on hybrid domain attention mechanism. by Yingying Mei

“…In the research of face recognition technology, the traditional methods usually show poor recognition accuracy and insufficient generalization ability when faced with complex scenes such as lighting changes, posture changes and skin color diversity. To solve these problems, based on the improvement of adaptive boosting to improve the accuracy of face detection, the study proposes a residual network 18-layer face feature extraction algorithm based on hybrid domain attention mechanism algorithm. …”
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DFDA-AD: An Approach with Dual Feature Extraction Architecture and Dual Attention Mechanism for Image Anomaly Detection by Babak Masoudi

“…DFDA-AD consists of dual feature extraction from images by pre-trained DenseNet121 and ResNet50 networks. …”
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Deep learning and support vector machine-recursive feature elimination-based network intrusion detection model by YE Qing, ZHANG Yannian, WU Hao

“…However, there are a lot of redundant information and unbalanced distribution problems in network intrusion data, therefore, deep learning and support vector machine-recursive feature elimination-based network intrusion detection model (DLRF) was proposed. …”
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Cost-sensitive regression learning on small dataset through intra-cluster product favoured feature selection by Fangfang Xu, Huan Zhao, Weihua Zhou, Yun Zhou

“…Massive regression and forecasting tasks are generally cost-sensitive regression learning problems with asymmetric costs between over-prediction and under-prediction. …”
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BA-ELM Gear Fault Diagnosis Method based on Energy Feature of Wavelet Packet Optimal Node by Qin Bo, Liu Yongliang, Wang Jianguo, Qin Yan, Yang Yunzhong

“…In order to solve the problems that gear fault classification model has weak generalization ability,poor accuracy causing by the fault features of gear is difficult to extract and extreme learning machine input weights and threshold of hidden layer nodes randomly selected,a BA- ELM gear fault diagnosis method is puts forward based on energy feature of wavelet packet optimal nodes.First,the gear vibration signals are decomposed by using wavelet packet in this method,the optimal nodes is selected by using the correlation coefficient between each node decomposition signals and original signal,and the energy feature is calculated.Second,the bat algorithm is used to optimize the extreme learning machine input weights and threshold of hidden layer node and the gear fault classification model of BA-ELM is established.Finally,the energy entropy feature vectors of the optimal wavelet packet nodes as the model input is used to identify the different fault states of gear.The experimental results show that,comparing with SVM and ELM fault classification method,the BA-ELM gear fault diagnosis method based on energy feature of wavelet packet optimal nodes has higher classification accuracy and better generalization ability.…”
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Triple Channel Feature Fusion Few-Shot Intent Recognition With Orthogonality Constrained Multi-Head Attention by Di Wu, Yuying Zheng, Peng Cheng

“…Intent recognition in few-shot scenarios is a hot research topic in natural language understanding tasks. Aiming at the problems of insufficient consideration of fine-grained features of the text and insufficient training of features in the process of model fine-tuning, the Triple Channel IntentBERT and Orthogonality Constrained Multi-Head Attention Model (TMH-IntentBERT) is proposed. …”
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Lithium-Ion Battery State of Health Estimation Based on Feature Reconstruction and Transformer-GRU Parallel Architecture by Bing Chen, Yongjun Zhang, Jinsong Wu, Hongyuan Yuan, Fang Guo

“…This study proposes a method for estimating the state of health of lithium-ion batteries based on feature reconstruction and Transformer-GRU parallel architecture to solve the problems of noisy feature data and the poor applicability of a single model to different types and operating conditions of batteries. …”
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Image small target detection in complex traffic scenes based on Yolov8 multiscale feature fusion by Xuguang Chai, Meizhi Zhao, Jing Li, Junwu Li

“…Addressing the challenging issues in small target detection within complex traffic scenes, such as scale variation, complex background noise, and the problems of missed and false detections, this paper introduces a Multi-Scale Feature Fusion YOLOv8 (MSFF-YOLOv8) approach. …”
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Precision Measurement and Feature Selection in Medical Diagnostics using Hybrid Genetic Algorithm and Support Vector Machine by Gowri Subadra K, Sathish Babu P

“…This study introduces a hybrid feature selection method based on genetic algorithm (GA) and Bucket of Models (BoM) approach to improve breast cancer detection and classification. …”
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Advanced Heart Disease Prediction Through Spatial and Temporal Feature Learning with SCN-Deep BiLSTM by Vivek Pandey, Umesh Kumar Lilhore, Ranjan Walia

“…Abstract Heart disease prediction using machine learning methods faces various challenges, such as low data quality, missing irrelevant values, and underfit and overfit problems, which increase the time complexity and degrade the model's prediction performance. …”
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An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

“…The results illustrate that TRSMA is powerful and can handle complex high-dimensional optimization problems.…”
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BBDetector: Intelligent border binary detection in IoT device firmware based on a multidimensional feature model. by Shudan Yue, Guimin Zhang, Qingbao Li, Wenbo Zhang, Xiaonan Li, Weihua Jiao

“…However, the existing methods for border binary detection have problems such as insufficient feature characterization, high false-negative rates, and low intelligence levels. …”
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