Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images by Ling-Chun Sun, Chia-Chiang Lee, Hung-Yen Ke, Chih-Yuan Wei, Ke-Feng Lin, Shih-Sung Lin, Hsin Hsiu, Ping-Nan Chen

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Genetic Variation Analysis of Hsp101 Gene in Common Wild Rice and Asian Cultivated Rice Germplasm Resources by Yue LIU, Liqun JIANG, Shuwei LYU, Bingrui SUN, Chen LI, Qing LIU, Hang YU

“…Further analyses including haplotype network analysis and phylogenetic analysis indicated that the wide rice haplotype Hap8 may be the oldest allele of the Hsp101 gene. …”
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Personality characteristics of students in the regulation of network activity by S. E. Panshina, N. L. Sungurova, N. B. Karabushchenko

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Manet: motion-aware network for video action recognition by Xiaoyang Li, Wenzhu Yang, Kanglin Wang, Tiebiao Wang, Chen Zhang

“…We conducted extensive experiments on five mainstream datasets, Something-Something V1 & V2, Jester, Diving48, and UCF-101, to validate the effectiveness of MANet. The MANet achieves competitive performance on Something-Something V1 (52.5%), Something-Something V2 (63.6%), Jester (95.9%), Diving48 (81.8%) and UCF-101 (86.2%). …”
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Analysis on Mobility Management of Multiple PLMNs EUTRAN Networking by Shangkun Xiong, Wenyi Li, ZhaoYe , Jie Chen, Qingyang Wang

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Virtual network mapping strategy and competitive analysis based on cost constraint by Jianjun YU, Chunming WU

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SVM directed machine learning classifier for human action recognition network by Dharmanna Lamani, Pramod Kumar, A Bhagyalakshmi, J. Maria Shanthi, Lakshmana Phaneendra Maguluri, Mohammad Arif, C Dhanamjayulu, Sathish Kumar. K, Baseem Khan

“…However, existing approaches such as three-dimensional convolutional neural networks (3D CNN) and two-stream neural networks (2SNN) have computational hurdles due to the significant parameterization they require. …”
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Spatiotemporal squeeze-and-excitation residual multiplier network for video action recognition by Huilan LUO, Kang TONG

“…Aiming at the shortcomings of shallow networks and general deep models in two-stream network structure,which could not effectively learn spatial and temporal information,a squeeze-and-excitation residual network was proposed for action recognition with a spatial stream and a temporal stream.Meanwhile,the long-term temporal dependence was captured by injecting the identity mapping kernel into the network as a temporal filter.Spatiotemporal feature multiplication fusion was used to further enhance the interaction between spatial information and temporal information of squeeze-and-excitation residual networks.Simultaneously,the influence of spatial-temporal stream multiplication fusion methods,times and locations on the performance of action recognition was studied.Given the limitations of performance achieved by a single model,three different strategies were proposed to generate multiple models,and the final recognition result was obtained by integrating these models through averaging and weighted averaging.The experimental results on the HMDB51 and UCF101 datasets show that the proposed spatiotemporal squeeze-and-excitation residual multiplier networks can effectively improve the performance of action recognition.…”
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Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…This research presents a novel HAR system combining graph structures with deep neural networks to capture both spatial and temporal patterns in activities. …”
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Deteksi Pneumonia Menggunakan Citra Sinar-X Paru berbasis Residual Network by Muhammad Adzkia, Firzal Arland, Agung Wahyu Setiawan

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Mechanism of Stochastic Resonance in a Quorum Sensing Network Regulated by Small RNAs by Ya-nan Zhu, Jianwei Shen, Yong Xu

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The Characteristics of Metaheuristic Method in Selection of Path Pairs on Multicriteria Ad Hoc Networks by Nyoman Gunantara, I Dewa Nyoman Nurweda Putra

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Space-ground integrated satellite communication network architecture for global energy internet by Yongliang LI, Xu’an LI, Jie TONG, Yuqing LEI, Huixia DING, Junfeng LAN

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Spatiotemporal Pattern Evolution in Global Green Trade Networks: Implications for Health Economics by Haiyan Zhou, Shaobin Wei, Xun Xi, Haitao Zhou, Hao Hu

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Administration of anticoagulation strategies for portal vein thrombosis in cirrhosis: network meta-analysis by Hui-Jun Li, Fu-Qiang Yin, Yu-Tong Ma, Teng-Yu Gao, Yu-Ting Tao, Xin Liu, Xian-Feng Shen, Chao Zhang

“…Comparison with control in network meta-analysis, direct oral anticoagulants (DOACs) (RR = 2.15, 95%CI: 1.33, 3.48), LMWH (RR = 1.41, 95%CI: 1.01, 1.99), TIPS (RR = 5.68, 95%CI: 2.63, 12.24), warfarin (RR = 2.16, 95%CI: 1.46, 3.21), EBL plus propranolol (RR = 2.80, 95%CI: 1.18, 6.60), LMWH-DOACs sequential (RR = 7.92, 95%CI: 2.85, 21.99) and LMWH-warfarin sequential (RR = 2.26, 95%CI: 1.16, 4.42) significantly improved the incidence of complete recanalization. …”
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Identification of Potential miRNA-mRNA Regulatory Network Contributing to Parkinson’s Disease by Xi Yin, Miao Wang, Wei Wang, Tong Chen, Ge Song, Yixuan Niu, Ziying Jiang, Zhongbao Gao, Zhenfu Wang

“…A miRNA-mRNA regulatory network was then constructed with 10 hub genes, and their interacting miRNAs overlapped with DEmis, including miR-30e-5p, miR-142-3p, miR-101-3p, miR-32-3p, miR-508-5p, miR-642a-5p, miR-19a-3p, and miR-21-5p. …”
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Bottom-Up Abstract Modelling of Optical Networks-on-Chip: From Physical to Architectural Layer by Alberto Parini, Luca Ramini, Fabio Lanzoni, Gaetano Bellanca, Davide Bertozzi

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A customized convolutional neural network-based approach for weeds identification in cotton crops by Hafiz Muhammad Faisal, Muhammad Aqib, Muhammad Aqib, Khalid Mahmood, Mejdl Safran, Sultan Alfarhood, Imran Ashraf

“…Automated approaches, based on convolutional neural networks (CNN), for crop disease identification, weed classification, and monitoring have substantially helped increase crop yields. …”
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DI-GEP: A New Lifetime Extending Algorithm for Target Tracking in Wireless Sensor Networks by Shucheng Dai, Chuan Li, Chun Chen

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Associations between social networks, messaging apps, addictive behaviors, and sleep problems in adolescents: the EHDLA study by María Navalón-González, José Adrián Montenegro-Espinosa, Héctor Gutiérrez-Espinoza, Jorge Olivares-Arancibia, Rodrigo Yañéz-Sepúlveda, Daniel Duclos-Bastías, Daniel Duclos-Bastías, Miriam Garrido-Miguel, Miriam Garrido-Miguel, Miriam Garrido-Miguel, Arthur Eumann Mesas, José Francisco López-Gil, Estela Jiménez-López, Estela Jiménez-López

“…ObjectiveThe current study aims to provide a comprehensive analysis of the relationships between social network (SN) use, messaging apps use, and addictive behaviors related to SNs, and sleep-related problems in a sample of Spanish adolescents.MethodsThis was a cross-sectional study using data from the Eating Healthy and Daily Life Activities (EHDLA) project, which involved adolescents aged 12–17 years from three secondary schools in Valle de Ricote (Region of Murcia, Spain). …”
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