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29 results on '"Song, Xiaoou"'

2. A Phased BOC Signal Detection Algotithm Based on Cyclic Stationary Characteristics

Author

Yang, Hang, Wang, Xiaorong, Song, Xiaoou, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Yan, Liang, editor, and Yu, Xiang, editor

Published
2022
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3. A Weak Signal Capture Algorithm Considering DBZP and Half-bit Difference

Author

Shan, Kun, Song, XiaoOu, Li, GuoBin, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Woungang, Isaac, editor, and Enokido, Tomoya, editor

Published
2021
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4. An Improved DOA Estimation Algorithm of Neural Network Based on Interval Division

Author

Li, GuoBin, Song, XiaoOu, Shan, Kun, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Woungang, Isaac, editor, and Enokido, Tomoya, editor

Published
2021
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5. Exploration of MPSO-Two-Stage Classification Optimization Model for Scene Images with Low Quality and Complex Semantics.

Author

Liu, Kexin, Wang, Rong, Song, Xiaoou, Deng, Xiaobing, and Zhu, Qingchao

Subjects
OPTIMIZATION algorithms, ADAPTIVE testing, CLASSIFICATION, IMAGE recognition (Computer vision), CLASSIFICATION algorithms
Abstract

Currently, complex scene classification strategies are limited to high-definition image scene sets, and low-quality scene sets are overlooked. Although a few studies have focused on artificially noisy images or specific image sets, none have involved actual low-resolution scene images. Therefore, designing classification models around practicality is of paramount importance. To solve the above problems, this paper proposes a two-stage classification optimization algorithm model based on MPSO, thus achieving high-precision classification of low-quality scene images. Firstly, to verify the rationality of the proposed model, three groups of internationally recognized scene datasets were used to conduct comparative experiments with the proposed model and 21 existing methods. It was found that the proposed model performs better, especially in the 15-scene dataset, with 1.54% higher accuracy than the best existing method ResNet-ELM. Secondly, to prove the necessity of the pre-reconstruction stage of the proposed model, the same classification architecture was used to conduct comparative experiments between the proposed reconstruction method and six existing preprocessing methods on the seven self-built low-quality news scene frames. The results show that the proposed model has a higher improvement rate for outdoor scenes. Finally, to test the application potential of the proposed model in outdoor environments, an adaptive test experiment was conducted on the two self-built scene sets affected by lighting and weather. The results indicate that the proposed model is suitable for weather-affected scene classification, with an average accuracy improvement of 1.42%. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Improved Cooperative Spectrum Sensing Algorithm with Artificial Neural Network

Author

Miao, Jingcheng, Song, Xiaoou, Wang, Zili, Wang, Xu-an, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Javaid, Nadeem, editor, Ikeda, Makoto, editor, and Takizawa, Makoto, editor

Published
2019
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8. Cooperative Spectrum Sensing Using Dual Nonparametric Cumulative Sum Algorithm

Author

Miao, Jingcheng, Yang, Hang, Song, Xiaoou, Wang, Zili, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Javaid, Nadeem, editor, Ikeda, Makoto, editor, and Takizawa, Makoto, editor

Published
2019
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20. Future Education Trend Learned From the Covid-19 Pandemic: Take ≪Artificial Intelligence≫ Online Course As an Example

Author

Song Xiaoou, Liu Kexin, Qu Yi, and Li Yan

Subjects
030222 orthopedics, Class (computer programming), Coronavirus disease 2019 (COVID-19), business.industry, Computer science, Plan (drawing), Blended learning, 03 medical and health sciences, 0302 clinical medicine, Online course, Scale (social sciences), Pandemic, ComputingMilieux_COMPUTERSANDEDUCATION, Artificial intelligence, Set (psychology), business
Abstract

COVID-19 Pandemic facilitates the development of online courses on a large scale. As a supplementary teaching in a special period, online courses play a gratifying role in enabling students to learn repeatedly and master effectively. However, it cannot be ignored that there are still some problems, and we need to find better solutions. This article takes the “Artificial Intelligence” course as an example, through a set of data analysis, puts forward the improvement plan of the network course, and discusses the “before and after class” teaching mode in blended learning. Through this way we could have a glimpse of the future education, which makes full use of online courses and uses online courses as an icing on the cake for traditional classrooms.

Published
2020

22. Deep Sequencing Uncovers Rice Long siRNAs and Its Involvement in Immunity Against Rhizoctonia solani

Author

Niu, Dongdong, primary, Zhang, Xin, additional, Song, Xiaoou, additional, Wang, Zhihui, additional, Li, Yanqiang, additional, Qiao, Lulu, additional, Wang, Zhaoyun, additional, Liu, Junzhong, additional, Deng, Yiwen, additional, He, Zuhua, additional, Yang, Donglei, additional, Liu, Renyi, additional, Wang, Yanli, additional, and Zhao, Hongwei, additional

Published
2018
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27. A study of the neurotoxicity of MPTP and analogs in human neuroblastoma SH-SY5Y cells

Author

Song, Xiaoou and Veterinary Medical Sciences

Subjects
human neuroblastoma, dopaminergic system, nervous system, in vitro, cholinergic system, LD5655.V856 1996.S697, tau protein, nervous system diseases, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine
Abstract

Neuronal alterations resulting from exposure to Parkinsonian-inducing 1-methyl-4- phenyl-1,2,3,6-tetrahydropyridine (MPTP) in an in vitro model SH-SYSY human neuroblastoma cells were explored using cytotoxic effects, neurochemical changes and pathological injury as endpoints. The results suggested that: MPTP entered the SH-SYS5Y human neuroblastoma cells through a non-dopamine transport mechanism, and was metabolized to 1-methyl-4-phenyl-2,3-dihydropyridium (MPDP⁺) and 1-methyl-4-phenylpyridium (MPP⁺) by monoamine oxidase (MAO). MPP⁺, the neurotoxic analog of MPTP, was taken up into cells through a dopamine (DA) uptake mechanism. MPTP, via its metabolite MPP⁺, inhibited NADH dehydrogenase activity. The MPTP-induced alterations of morphology included formation of blebs, attenuated neutrites, abnormal mitochondria with electron-density of matrix and disorganization of cristae, and abnormal aggregation of filamentous material of the cytoskeleton. MPTP was neurotoxic to the dopaminergic system, inhibiting monoamine oxidase (MAO) activity, and decreasing levels of dopamine (DA) and other catecholamines. In addition, MPTP enhanced ³H-DA release from cells, and its metabolite MPP⁺ inhibited ³H-DA uptake. MPTP was found to directly act on the cholinergic system in SH-SY5Y cells, causing dose-related decreases in the binding at muscarinic and nicotinic receptors. MPTP also inhibited acetylcholinesterase (AChE) activity and increased choline levels. The MPTP-induced increase in DA release and the decreases in catecholamines in SH-SYSY cells were blocked by pretreatment with acetylcholine receptor antagonists atropine and d-tubocurarine. MPTP caused increases in tau proteins, and also caused an increased expression of the reverse transcriptase polymerase chain reaction (RT-PCR) product after treatment for 2 to 5 days at 10⁻³ to 10⁻⁴ M. The results, for the first time, demonstrated that MPTP affected cytoskeletal associated tau protein and altered its mRNA. These results demonstrated that the human neuroblastoma cell line, SH-SYSY, can be used as an in vitro model for the study of the neurotoxicity of MPTP, including the mechanisms associated with exposure to this neurotoxicitant. Ph. D.

Published
1996

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