Review of Brain Computer Interface Technology in the Treatment of Motor Dysfunction after Stroke by Yulian ZHU, Sijie LIANG

“…The work flow of BCI in treating stroke patients could be roughly divided into five steps: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and control interface. …”
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Practices of Social Work with Migrants in Russia: Expert Assessments by E. A. Kovtun, V. P. Miletskiy

“…Regulation of social adaptation of migrants is one of the most important issues of state migration and social policy. One of the problems in the process of adaptation of migrants is the lack of a systematic approach to solving the problems faced by migrants in the host society. …”
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Technical solution for purifying emissions of climate-active gases by A. Yu. Briukhanov, E. V. Vasilev, S. A. Egorov

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Determination of Plant Developmental Stability in Plant Lighting with Hyperspectral Imaging by S. A. Rakutko, E. N. Rakutko, A. P. Mishanov

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Bioprinting of a multi-composition array to mimic intra-tumor heterogeneity of glioblastoma for drug evaluation by Gihyun Lee, Soo Jee Kim, Yejin Choi, Jongho Park, Je-Kyun Park

“…As printing time increases, the extruded bioink spreads and evaporates, leading to technical problems that decrease printing resolution and stability, as well as biological problems that affect 3D culture space and cell viability. …”
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Deciding Together as Faculty: Narratives of Unanticipated Consequences in Gendered and Racialized Departmental Service, Promotion, and Voting by Smith-Doerr Laurel, Mickey Ethel L., Kane-Lee Ember Skye W.

“…Workplace inequalities scholarship often assumes making people aware of problems will lead to change, although gendered and racialized organizations theories show systemic problems beyond individual awareness. …”
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Research on Vehicle Road Noise Prediction Based on AFW-LSTM by Yan Ma, Ruxue Dai, Tao Liu, Jian Liu, Shukai Yang, Jingjing Wang

“…Therefore, based on the road noise hierarchy constructed according to the road noise transmission path, the LSTM (Long Short-Term Memory) network is introduced to establish a data-driven prediction model, which effectively avoids the defects of the TPA method and CAE in analyzing road noise problems. Based on the LSTM prediction model, the AFW (adaptive feature weight) method is introduced to improve the model’s attention to the key features in the input data and finally improve the accuracy and robustness of the road noise prediction model. …”
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Encrypted traffic identification method based on deep residual capsule network with attention mechanism by Guozhen SHI, Kunyang LI, Yao LIU, Yongjian YANG

“…With the improvement of users’ security awareness and the development of encryption technology, encrypted traffic has become an important part of network traffic, and identifying encrypted traffic has become an important part of network traffic supervision.The encrypted traffic identification method based on the traditional deep learning model has problems such as poor effect and long model training time.To address these problems, the encrypted traffic identification method based on a deep residual capsule network (DRCN) was proposed.However, the original capsule network was stacked in the form of full connection, which lead to a small model coupling coefficient and it was impossible to build a deep network model.The DRCN model adopted the dynamic routing algorithm based on the three-dimensional convolutional algorithm (3DCNN) instead of the fully-connected dynamic routing algorithm, to reduce the parameters passed between each capsule layer, decrease the complexity of operations, and then build the deep capsule network to improve the accuracy and efficiency of recognition.The channel attention mechanism was introduced to assign different weights to different features, and then the influence of useless features on the recognition results was reduced.The introduction of the residual network into the capsule network layer and the construction of the residual capsule network module alleviated the gradient disappearance problem of the deep capsule network.In terms of data pre-processing, the first 784byte of the intercepted packets was converted into images as input of the DRCN model, to avoid manual feature extraction and reduce the labor cost of encrypted traffic recognition.The experimental results on the ISCXVPN2016 dataset show that the accuracy of the DRCN model is improved by 5.54% and the training time of the model is reduced by 232s compared with the BLSTM model with the best performance.In addition, the accuracy of the DRCN model reaches 94.3% on the small dataset.The above experimental results prove that the proposed recognition scheme has high recognition rate, good performance and applicability.…”
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An end-to-end mass spectrometry data classification model with a unified architecture by Yinchu Wang, Wei Zhang, Lin Guo, Fengyi Zhang, Zilong Liu, Xingchuang Xiong, Xiang Fang

“…The trained MS-DREDFeaMiC can integrate mixed features, reduce interbatch differences, and enhance feature distinctions among categories. …”
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Double periodicity of mechanical properties of a thin ice field formed under conditions of lateral constraint by V. P. Epifanov, S. A. Lychev

“…Experimental results confirming this fact were obtained during tests of a thin ice cover at the Krylov State Research Center (Saint-Petersburg, Russia). A characteristic feature of the test results is that their spatial distributions can be represented with sufficient accuracy as an overlap of two periodic functions with significantly different periods: long-wave and short-wave components. …”
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Improved immersed boundary/wall modeling method for RANS solver coupled with wall functions: application to Cartesian grid systems by Xueying Yu, David R. Fuhrman, Yanlin Shao

“…Another distinguishing feature of this turbulent-flow solver is that it employs the highly accurate immersed-boundary generalized harmonic polynomial cell (IB-GHPC) method to solve the Poisson equation for fluid pressure. …”
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Retracted: VR Panorama Mosaic Algorithm Based on Particle Swarm Optimization and Mutual Information by Zhonggao Yang, Dan Xiang, Yili Cheng

“…However, the development of image mosaic technology still faces some problems to be studied and these problems were solved. …”
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Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning by Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu

“…To solve these problems, deep learning has been proposed in recent years to exploit multiple layers of nonlinear information processing for unsupervised self-learning of features. …”
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Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review by Ilhem Gharbi, Fadoua Taia-Alaoui, Hassen Fourati, Nicolas Vuillerme, Zebo Zhou

“…Compared to these works, the proposed review provides some novelties such as an in-depth analysis of the current state-of-the-art techniques in TMD systems, relying on recent references and focusing particularly on the major existing problems, and an evaluation of existing methodologies for detecting travel modes using smartphone IMUs (including dataset structures, sensor data types, feature extraction, etc.). …”
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Technological Restructuring of Economies of the Former Soviet Union: from “Destruction” to “Creation” by I. V. Boiko

“…The article highlights the features of the trajectory of the economic development of the former Soviet republics. …”
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Automatic tag detection in multimedia survey condition by M. Russo, L. Martelli, R. Ravanelli, A. Pini

“…This paper focuses on such technical problems, presenting part of the qualitative and quantitative results obtained at this stage of our research and the approach used to resolve some detection limitations.…”
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Image and Mask in the Painting by Francisco Goya: The Ontological and Axiological Aspects by Loukitcheva Krassimira

“…Goya managed to decidedly push the established boundaries of the European art expanding its range with the themes and problems that had previously been rarely and poorly represented. …”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…Detecting the daily behavior of broiler chickens allows early detection of irregular activity patterns and, thus, problems in the flock. In an attempt to resolve the problems of the slow detection speed, low accuracy, and poor generalization ability of traditional detection models in the actual breeding environment, we propose a chicken behavior detection method called FCBD-DETR (Faster Chicken Behavior Detection Transformer). …”
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Is anybody ‘Learning’ from deaths? Sequential content and reflexive thematic analysis of national statutory reporting within the NHS in England 2017–2020 by Cecilia Vindrola-Padros, S Ramani Moonesinghe, Zoe Brummell, Dorit Braun, Zainab Hussein

“…Introduction The imperative to learn when a patient dies due to problems in care is absolute. In 2017, the Learning from Deaths (LfDs) framework, a countrywide patient safety programme, was launched in the National Health Service (NHS) in England. …”
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DSMF-Net: Dual Semantic Metric Learning Fusion Network for Few-Shot Aerial Image Semantic Segmentation by Xiyu Qi, Yidan Zhang, Lei Wang, Yifan Wu, Yi Xin, Zhan Chen, Yunping Ge

“…In this article, we propose to tackle these challenging problems via dual semantic metric learning and multisemantic features fusion and introduce a novel few-shot segmentation Network (DSMF-Net). …”
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