Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification by Yasin Kaya, Ezgisu Akat, Serdar Yıldırım

“…ABSTRACT Problem Brain tumors are among the most prevalent and lethal diseases. …”
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Evaluating the performance of pixel-based and object-based multidimensional clustering algorithms for automated surface water mapping by Bohao Li, Kai Liu, Ming Wang, Yanfang Wang, Linmei Zhuang, Weihua Zhu, Chenxia Li, Linhao Zhang, Yanan Chen

“…Unsupervised classification holds promise for automating large-scale surface water detection, and it helps solve the difficult problem of sample collection in supervised classification. …”
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A Scene Knowledge Integrating Network for Transmission Line Multi-Fitting Detection by Xinhang Chen, Xinsheng Xu, Jing Xu, Wenjie Zheng, Qianming Wang

“…Aiming at the severe occlusion problem and the tiny-scale object problem in the multi-fitting detection task, the Scene Knowledge Integrating Network (SKIN), including the scene filter module (SFM) and scene structure information module (SSIM) is proposed. …”
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Eksplikacja znaku percepcyjnego zapachu w świadomości użytkowników języka polskiego oraz w definicjach słownikowych (na materiale eksperymentu psycholingwistycznego) by Alina Yodlovska

“… EXPLICATION OF THE PERCEPTUAL SIGN ”SMELL” IN THE MINDS OF POLISH LANGUAGE USERS AND IN DICTIONARY DEFINITIONS (BASED ON THE MATERIAL OF A PSYCHOLINGUISTIC EXPERIMENT) The problem of explicating perceptual features in vocabulary definitions is still underdeveloped in linguistics. …”
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A Wi-Fi sensing method for complex continuous human activities based on CNN-BiGRU by Yang LIU, Anming DONG, Jiguo YU, Kai ZHAO, You ZHOU

“…Human activity sensing based on Wi-Fi channel state information (CSI) has an important application prospect in future intelligent interaction scenarios such as virtual reality, intelligent games, and the metaverse.Accurate sensing of complex and continuous human activities is an important challenge for Wi-Fi sensing.Convolutional neural network (CNN) has the ability of spatial feature extraction but is poor at modeling the temporal features of the data.While long short-term memory (LSTM) network or gated recurrent unit (GRU) network, which are suitable for modeling time-series data, neglect learning spatial features of data.In order to solve this problem, an improved CNN that integrates bidirectional gated recurrent unit (BiGRU) network was proposed.The bi-directional feature extraction ability of BiGRU was used to capture the correlation and dependence of the front and back information in the time series data.The extraction of the spatiotemporal features of the time series CSI data was realized, and then the mapping relationship between the action and the CSI data was present.Thus the recognition accuracy of the complex continuous action was improved.The proposed network structure was tested with basketball actions.The results show that the recognition accuracy of this method is above 95% under various conditions.Compared with the traditional multi-layer perceptron (MLP), CNN, LSTM, GRU, and attention based bidirectional long short-term memory (ABLSTM) baseline methods, the recognition accuracy has been improved by 1%～20%.…”
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Using a Solution Construction Algorithm for Cyclic Shift Network Coding under Multicast Network to the Transformation of Musical Performance Styles by Xiuqin Wang, Jun Geng, Zhiyuan Li

“…A two-way recurrent neural network based on the gated recurrent unit is used to extract a sequence of note feature vectors of different styles, and a one-dimensional convolutional neural network is used to predict the intensity of the extracted note feature vector sequence for a specific style, which better learns the intensity variation of different styles of MIDI music.…”
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Diagnosis of abnormal sound in loudspeakers by integrated attention mechanism convolutional neural network by ZHOU Jinglei, WANG Xiaoming, LI Limin

“…Secondly, the feature data was input into the 1DCNN-BiLSTM network for initial feature extraction. …”
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Research on Wind Turbine Unbalance Fault Diagnosis Based on Wavelet Transform and Convolutional Neural Network by Zhenling Li, Yukun Gao

“…It consists of two feature extractors of different scales, which are combined in the fully connected layer. …”
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Surrounding Object Material Detection and Identification Method for Robots Based on Ultrasonic Echo Signals by Bo Zhu, Tao Geng, Gedong Jiang, Zheng Guan, Yang Li, Xialun Yun

“…This method primarily adopts the 16-dimensional feature vector extracted from intrinsic mode functions that we gain from empirical mode decomposition as inputs of machine learning algorithms to recognize different materials, and we use K-nearest neighbor, decision tree, and support vector machine algorithms on the feature vector set to decide the best classifier, and its acoustic theoretical model is established additionally. …”
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Analysis of Internet Marketing Forecast Model Based on Parallel K-Means Algorithm by Xiaolei Chen, Sikun Ge

“…During the simulation experiment, the weight calculation formula is used to calculate the weight of the feature term. The basic idea is that if a feature word appears more often in this document but less frequently in other nodes, the word will be assigned higher. …”
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Characteristics and classification of intangible assets by Vyacheslav V. Kress

“…The article analyses legislative and doctrinal characteristics of intangible goods: inalienability and non-transferability, the problem of lack of economic substance, intangible nature, belonging to a citizen from birth or by virtue of law. …”
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Presenting a Novel Hybrid Approach of Text Mining Sentiment Analysis in Twitter Using CART Decision Tree by Nasir Tayarani, Mehrdad Jalali

“…CART is very effective in processing discrete and continuous data in text mining. The unique CART feature is a complex data structure analysis that can support regression as well as classification operations, according to the input of the problem. …”
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A Wi-Fi sensing method for complex continuous human activities based on CNN-BiGRU by Yang LIU, Anming DONG, Jiguo YU, Kai ZHAO, You ZHOU

“…Human activity sensing based on Wi-Fi channel state information (CSI) has an important application prospect in future intelligent interaction scenarios such as virtual reality, intelligent games, and the metaverse.Accurate sensing of complex and continuous human activities is an important challenge for Wi-Fi sensing.Convolutional neural network (CNN) has the ability of spatial feature extraction but is poor at modeling the temporal features of the data.While long short-term memory (LSTM) network or gated recurrent unit (GRU) network, which are suitable for modeling time-series data, neglect learning spatial features of data.In order to solve this problem, an improved CNN that integrates bidirectional gated recurrent unit (BiGRU) network was proposed.The bi-directional feature extraction ability of BiGRU was used to capture the correlation and dependence of the front and back information in the time series data.The extraction of the spatiotemporal features of the time series CSI data was realized, and then the mapping relationship between the action and the CSI data was present.Thus the recognition accuracy of the complex continuous action was improved.The proposed network structure was tested with basketball actions.The results show that the recognition accuracy of this method is above 95% under various conditions.Compared with the traditional multi-layer perceptron (MLP), CNN, LSTM, GRU, and attention based bidirectional long short-term memory (ABLSTM) baseline methods, the recognition accuracy has been improved by 1%～20%.…”
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CNN-GRU Battery SOC Estimation Method Fused with Attention Mechanism for Electric Multiple Units by WANG Shenghui, TIAN Qin, LIU Lihao, FENG Enlai, YU Tianjian

“…The model employs a convolutional neural network (CNN) to extract short-term feature dependencies from long sequences within the battery cycling data. …”
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HOW TO CREATE BUSINESS PERFORMANCE MANAGEMENT (BPM) SYSTEM by B. Ye. Odintsov, A. N. Romanov

“…The reasons of occurrence of these problems as well as their semantics and features are analyzed in terms of practical creation of BPM-systems. …”
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Quality Management at Russian Enterprises in Conditions of Import-Substitution by S. P. Burlankov, A. S. Baldina

“…The article deals with specific features of quality management at Russian enterprises in conditions of intensive import-substitution connected with introduction of economic sanctions against our country. …”
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Metabolic aspects of diabetes mellitus type 1 in representatives of different ethnic groups by M. A. Darenskaya, L. A. Grebyonkina, S. V. Gnusina

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UWMambaNet: Dual-Branch Underwater Image Reconstruction Based on W-Shaped Mamba by Yuhan Zhang, Xinyang Yu, Zhanchuan Cai

“…At the present stage, the methods based on the CNN have the problem of insufficient global attention, and the methods based on Transformer generally have the problem of quadratic complexity. …”
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Research on Clustering Based PWR pin-by-pin Homogenization Parameters Compression Method by LI Tianya1, 2, LUO Qi3, YAO Dong2, HE Caiyun1, CAI Yun2, WANG Dan1, DUAN Yongqiang1, LIAO Hongkuan1, XIAO Peng2

“…Firstly, this paper conducted a study on the number and characteristics of clustering, focusing on typical fuel assemblies of pressurized water reactors, multiple clustering features and numbers were studied, fast and thermal flux ratio, fission sigma and thermal flux were chosen as clustering features, and it was determined that using the fast and heat flux ratio as the clustering feature and 5 as the clustering number were appropriate. …”

Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, E... by Daniel Niguse Mamo, Tesfahun Melese Yilma, Makda Fekadie Tewelgne, Yakub Sebastian, Tilahun Bizuayehu, Mequannent Sharew Melaku, Agmasie Damtew Walle

“…Association rule mining was used to generate the best rule for the association between independent features and the target feature. Result Out of 5264 study participants, 1893 (35.06%) males and 3371 (64.04%) females were included. …”
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