Spatial Featuring of Animal Rabies Outbreaks in Maranhão State, Brazil (from 1992 to 2022) by de Arruda Roberto Carlos Negreiros, Soares Jose Wendel Araujo, Negreiros Isabella Rodrigues, de Moraes Pereira Helder, Costa Francisco Borges, Coimbra Viviane Correa Silva, Santos Hamilton Pereira

“…The aim of the current study is featuring animal rabies outbreaks in Maranhão State, Brazil, from 1992 to 2022. …”
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CLINICAL AND FUNCTIONAL FEATURES AND CHARACTERISTICS OF THE CONTROL OF ASTHMA AND CHRONIC OBSTRUCTIVE PULMONARY DISEASE IN OVERWEIGHT by V. A. Boykov, O. S. Kobyakova, I. A. Deyev, Ye. S. Kulikov

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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…This study focuses on the problem of dense object counting. In dense scenes, variations in object scales and uneven distributions greatly hinder counting accuracy. …”
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Genre Features of the Novel Epic in Ossetian Literature: Correlation between Ideological and National-Ethnic by I. V. Mamieva

“…The specific features of epic narration in the Ossetian novel prose (1940-1960) in the context of the all-Russian literary process are considered. …”
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Multipath Suppression and High-precision Angle Measurement Method Based on Feature Game Preprocessing by Houhong XIANG, Yongliang WANG, Yuxi LI, Yufeng CHEN, Fengyu WANG, Xiaolu ZENG

“…This method, based on a signal-level feature game approach, incorporates two interconnected components working together. …”
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A Unified Deep-Domain Adaptation Framework: Advancing Feature Separability and Local Alignment by Pranav Kumar, Jimson Mathew, Rakesh Kumar Sanodiya, Avinash Kumar Chouhan, Rahul Reddy Bukkasamudram, Chandra Sai Teja Adhikarla

“…To address this issue of domain shift, we introduce a novel method, called “A Unified Deep-Domain Adaptation Framework: Advancing Feature Separability and Local Alignment” (DDASLA) that incorporates an attention mechanism into the ResNet18 model to improve its feature extraction capability. …”
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A Block Object Detection Method Based on Feature Fusion Networks for Autonomous Vehicles by Qiao Meng, Huansheng Song, Gang Li, Yu’an Zhang, Xiangqing Zhang

“…Nowadays, automatic multi-objective detection remains a challenging problem for autonomous vehicle technologies. In the past decades, deep learning has been demonstrated successful for multi-objective detection, such as the Single Shot Multibox Detector (SSD) model. …”
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Remote Sensing Image Change Detection Based on Multi-Level Diversity Feature Fusion by Honggang Xie, Wanjie Ma

“…Furthermore, to effectively address the problem of boundary misjudgment in change areas caused by fixed thresholds, an Adaptive Threshold Module is devised to adaptively learn the texture features of change and unchanged regions, enabling the generation of more accurate thresholds for boundary determination, thereby improving the robustness of the algorithm model and alleviating false alarms. …”
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Double Filter and Double Wrapper Feature Selection Algorithm for High-Dimensional Data Analysis by Hong Chen, Yuefeng Zheng

“…Subsequently, the algorithm enters the double wrapper stage, where it uses the Random Walk Whale Optimization Algorithm (RWWOA) and the improved Adaptive Differential Evolution (ADE) to jointly optimize and obtain the optimal feature subset. Among them, in order to overcome the problem of single algorithm falling into the local optimum, the Algorithm Iteration Mechanism is proposed, which selectively runs two wrapper algorithms to make the algorithm jump out of local optimum and explore a broader optimization space. …”
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General and special types of exemption from criminal liability: appointment, purpose, design features by V. N. Borkov, S. E. Suverov

“…However, despite the indicated feature, special types of exemption from criminal liability should be built taking into account the tasks facing the criminal law of Russia and the goals of criminal liability.Conclusion. …”
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An Effective Feature Extraction Method for Tomato Leafminer - Tuta Absoluta (Meyrick) (Lepidoptera: Gelechiidae) Classification by Tahsin Uygun, Serhat Kiliçarslan, Cemil Közkurt, Mehmet Metin Ozguven

“…Abstract Global warming caused by climate change causes some problems in agricultural production. One of these problems is the increase in various pest populations. …”
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Enhancing Adversarial Transferability With Intermediate Layer Feature Attack on Synthetic Aperture Radar Images by Xuanshen Wan, Wei Liu, Chaoyang Niu, Wanjie Lu, Yuanli Li

“…Existing SAR adversarial attack algorithms require access to the network structure, parameters, and training data, which are often inaccessible in real-world scenarios. To address this problem, this study proposes an intermediate layer feature attack algorithm that does not rely on training data for the adversary model. …”
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Multi-modal feature fusion with multi-head self-attention for epileptic EEG signals by Ning Huang, Zhengtao Xi, Yingying Jiao, Yudong Zhang, Zhuqing Jiao, Xiaona Li

“…Currently, the dominant single-modal feature extraction methods cannot cover the information of different modalities, resulting in poor classification performance of existing methods, especially the multi-classification problem. …”
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Bearing Fault Diagnosis Method Based on Self-attentional Time-frequency Feature Fusion by LIU Jing, ZHANG Minghui, WU Jian, CHEN Erlong, JI Haipeng

“…Aiming at the problem that the single time and frequency domain signal contains incomplete features in bearing fault diagnosis , which leads to the poor generalization ability of traditional fault diagnosis models, a bearing fault diagnosis method based on self-attention time-frequency feature fusion was proposed. …”
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A new verification approach for nowcasting based on intensity and spatial-temporal feature correction by Jun Liu, Tong Zhang, Yuanzhao Chen, Rui Wang, Mingjie Wang, Shuxin Wang, Ting Xu, Chunyang Zhao, Xunlai Chen

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Bearing Fault Diagnosis Based on Spatial Features of 2.5 Dimensional Sound Field by Junjian Hou, Jun Ma, Zhanpeng Fang, Wuyi Ming, Wenbin He

“…Different from the 2D technique with only one source image, the 2.5D acoustic field model consists of source image, holographic sound image, and the differences between them, and its effective feature model is constructed by Gabor wavelet feature extraction and random forest feature reduction algorithm. …”
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Learning Distinctive Feature Representation for Descriptors on Multimodal Images by Incorporating Multiple Negative Samples by Bohan Li, Yixuan Li, Yong Li, Guohan Zhang

“…This article proposes a method composed of a loss function and a feature extractor structure, to learn the distinctive feature representation (DIFR) for descriptors on multimodal images. …”
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Imbalanced feature generation based on bootstrap power spectral curve for estimating respiratory rate by Soojeong Lee, Gyanendra Prasad Joshi, Gangseong Lee

“…Hence, we use the parametric bootstrap model generated by artificial feature curves to estimate RR and solve this problem. …”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Abstract To address the challenge of accurately capturing tool wear states in small sample scenarios, this paper proposes a tool wear prediction method that combines XGBoost feature selection with a PSO-BP network. In order to solve the problem of input feature selection and parameter selection in BP neural network, a double-layer programming model of input feature and parameter selection is established, which is solved by XGBoost and PSO. …”
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Non-destructive Identification of Moldy Walnuts by Fusing X-Ray and Visual Image Features by NING Xinyue, ZHANG Hui, JI Shuai, LAI Lisi

“…To address the difficulty of detecting moldy walnuts and the problem of low detection efficiency, a non-destructive method based on fused features of X-ray and visual images was proposed to accurately distinguish four grades of moldy walnuts: moldy both internally and externally, moldy internally and normal externally, normal internally and moldy externally, and normal both internally and externally. …”
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