Multipopulation Whale Optimization-Based Feature Selection Algorithm and Its Application in Human Fall Detection Using Inertial Measurement Unit Sensors by Haolin Cao, Bingshuo Yan, Lin Dong, Xianfeng Yuan

“…In addition, the proposed method is utilized to perform feature selection in human fall-detection tasks, and extensive real experimental results further illustrate the superior ability of the proposed method in addressing practical problems.…”
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MF-ShipNet: a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images by Jianfeng Li, Yibing Yang, Liutong Yang, Yang Zhao, Qinghua Luo, Chenxu Wang

“…To solve this problem, this paper proposes a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images. …”
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STEREOTYPICAL REPRESENTATION OF YOUTH IN THE MODERN ENGLISH LITERARY DISCOURSE by Olga V. Beshlei

“…The article reveals the stereotypical representation of young people, which is formed on the basis of the selection of individual, somewhat biased, axiologically marked subjective features and represents the spectrum of differential features of the actualization of the age concept YOUTH according to linguistic and cultural variability in the British-American literary discourse of the XXI century. …”
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A Procedure for Extending Input Selection Algorithms to Low Quality Data in Modelling Problems with Application to the Automatic Grading of Uploaded Assignments by José Otero, Ana Palacios, Rosario Suárez, Luis Junco, Inés Couso, Luciano Sánchez

“…When selecting relevant inputs in modeling problems with low quality data, the ranking of the most informative inputs is also uncertain. …”
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Enhancing heart disease classification based on greylag goose optimization algorithm and long short-term memory by Ahmed M. Elshewey, Amira Hassan Abed, Doaa Sami Khafaga, Amel Ali Alhussan, Marwa M. Eid, El-Sayed M. El-kenawy

“…Heart rhythm disorders (arrhythmias), heart valve problems, congenital heart defects present at birth, and heart muscle disorders (cardiomyopathies) are other types of heart disease. …”
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OM-VST: A video action recognition model based on optimized downsampling module combined with multi-scale feature fusion. by Xiaozhong Geng, Cheng Chen, Ping Yu, Baijin Liu, Weixin Hu, Qipeng Liang, Xintong Zhang

“…This model adds a multi-scale feature fusion module with an optimized downsampling module based on a Video Swin Transformer (VST) to improve the model's ability to perceive and characterize feature information. …”
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“Image-Spectral” fusion monitoring of peanut leaf spot disease level based on deep learning by Yongda Lin, Jiangtao Tan, Hong Li, Xi Li, Jianguo Wang, Tingting Chen, Lei Zhang

“…However, existing algorithms for peanut leaf disease detection techniques based on pictures or hyperspectral information still have problems with detection accuracy and stability. To address these limitations, this study proposes a robust multi-source feature fusion model for peanut leaf spot detection, integrating ResNet101 for RGB image feature extraction and an improved 1D-CNN for hyperspectral feature extraction. …”
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A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

“…To address the above problems, a lightweight personnel detection method YOLOv5-CWG is proposed for underground coal mine based on YOLOv5.Firstly, the coordinate attention mechanism (Coordinate Attention) embedded in the backbone network adaptively adjusts the weights of each channel in the feature map to enhance the expression ability of the features. …”
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DA-ResNeXt50 method for radio frequency fingerprint identification based on time-frequency and bispectral feature fusion by CHEN Mengdi, ZHANG Wei, SHEN Lei, LEI Fuqiang, ZHANG Jiafei

“…To address the problems that a single feature in radio frequency fingerprint recognition could not fully represent the integrity of the signal and that the differences between features of different classes were small, which limited the recognition accuracy, a DA-ResNeXt50 (ResNeXt50 with dense connection and ACBlock) method for radio frequency fingerprint identification based on time-frequency and bi-spectral feature fusion was proposed. …”
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Feature scale and identifiability: how much information do point hydraulic measurements provide about heterogeneous head and conductivity fields? by S. K. Hansen, D. O'Malley, J. P. Hambleton

“…We find that significant feature identification becomes possible as feature scale exceeds 4 times the measurement spacing, and identification reliability subsequently improves in a power-law fashion with increasing feature scale.…”
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A Joint Network of 3D-2D CNN Feature Hierarchy and Pyramidal Residual Model for Hyperspectral Image Classification by Hongwei Wei, Yufan Wang, Yu Sun, Jianfeng Zheng, Xiaodong Yu

“…Since convolutional neural networks (CNN) can extract deeper features from hyperspectral images, they show good classification performance in the hyperspectral image (HSI) classification task. …”
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FW-S3KIFCM: Feature Weighted Safe-Semi-Supervised Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method by Shirin Khezri, Nasser Aghazadeh, Mahdi Hashemzadeh, Amin Golzari Oskouei

“…This issue is frequently related to numerous real-world problems. On the other hand, existing SSC techniques fail to differentiate between the varied attributes within the feature space. …”
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LGM-Net: Wheat Pest and Disease Detection Network Based on Local Global Information Interaction and Multi-Level Feature Fusion by Yimin Qu, Shaobo Yu, Jing Yang

“…Firstly, this paper designs a lightweight feature interactive network (LFI-Net) to fully extract the local and global features of wheat leaf diseases and improve the detection of wheat pest and disease targets under noise interference. …”
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MLGFENet: Multiscale Local–Global Feature Enhancement Network for High-Resolution Remote Sensing Image Change Detection by Huanhuan Lv, Xianqi Yan, Hui Zhang, Cuiping Shi, Ruiqin Wang

“…Next, a cascading feature decoder is employed to perform upsampling on the extracted features. …”
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GREEKS IN ODESSA (END OF THE 18TH - BEGINNING OF THE 20th CENTURY): HISTORIOGRAPHICAL DIMENSION by Anna Hedo, Olga Sarajeva

“…Historiographical work on the problem has been classified by chronological criteria. …”
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وعی أعضاء هیئة التدریس فی الإنسانیات بقضایا النشر العلمی الدولی by سفّانه زیدان

“…Generally, the results showed that faculty members of the study community do not have sufficient awareness about materials of scientific publishing, quality criteria of scientific indexed journals, predatory journals features, tools available on the internet that help researchers and authors identify the appropriate and trusted journals, digital object identifier, and the reasons of rejecting publishing scientific research in scientific journals. …”
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RESETTLEMENT OF THE KALMYKS IN THE VOLGO-URAL INTERFLUVE IN THE XVII-XVIII CENTURIES: PROBLEMS OF INTERACTION WITH THE NEIGHBORING PEOPLES IN THE CONTEXT OF RUSSIAN FOREIGN POLICY by K. Koltsova, P. Koltsov

“…The authors addresses the problem of the relations between the Kalmyks and the neighboring peoples in the context of Russian foreign policy. …”
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Problems of FSES 3+ implementation at different stages of professional training of future tourism industry workers in the context of competence approach in education by Elena Alexandrovna Yeremina, Tatyana Nicolaevna Poddubnaya, Vladimir Gavrilovich Minchenko

“…This circumstance has formulated the research problem: what are the problems of FSES 3+ implementation at different levels of professional training of future workers in tourism industry in the context of a competence-based approach in education? …”
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EEG channels selection for stroke patients rehabilitation using equilibrium optimizer by Al-Betar Mohammed Azmi, Alyasseri Zaid Abdi Alkareem, Makhadmeh Sharif Naser

“…The EO algorithm is utilized to represent the EEG channel selection problem, transforming the features of each individual EEG into binary values and subsequently applying a k-nearest neighbor classifier technique to determine the accuracy rate. …”
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Small Face Recognition Algorithm Based on Super-resolution Reconstruction by LI Jing-yu, CHENG Wei-yue, LI Zi-xiang, LIN Ke-zheng

“…The algorithm first performs super-resolution reconstruction on the collected low-resolution face images, and uses the method of detail enhancement to restore high-frequency information such as facial contour information and texture details of the image, and then uses an improved densely connected network to do feature extraction and image recognition. Experimental results show that this method is aimed at small-scale face images, and is superior to other face recognition algorithms in image recognition rate, and can effectively solve the problem of low recognition rate of small faces in real environments.…”
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