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NEW ENVIRONMENT FOR DEVELOPMENT OF NGOS IN CHINA
Deng Guosheng 연세대학교 동서문제연구원 2000 Global economic review Vol.29 No.4
Since 1978, great changes have taken place in the environment for the development of NGOs in China. From a macroscopic perspective, China's transformation process in the economic, political and social systems, has been progressing successively. The transformation process has broken the traditional structure of the Government's monopolization of resources and the strictly controlled private action space. The reforms have restructured the relationship between the Government and the market society, and thus provided an opportunity for the existence and development of all kinds of NGOs in China. In addition, China's entry into the WTO and current trends towards globalization also has promoted the development of NGOs in China.
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Copy-move Forgery Detection Robust to Various Transformation and Degradation Attacks
( Jiehang Deng ),( Jixiang Yang ),( Shaowei Weng ),( Guosheng Gu ),( Zheng Li ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.9
Trying to deal with the problem of low robustness of Copy-Move Forgery Detection (CMFD) under various transformation and degradation attacks, a novel CMFD method is proposed in this paper. The main advantages of proposed work include: (1) Discrete Analytical Fourier-Mellin Transform (DAFMT) and Locality Sensitive Hashing (LSH) are combined to extract the block features and detect the potential copy-move pairs; (2) The Euclidian distance is incorporated in the pixel variance to filter out the false potential copy-move pairs in the post-verification step. In addition to extracting the effective features of an image block, the DAMFT has the properties of rotation and scale invariance. Unlike the traditional lexicographic sorting method, LSH is robust to the degradations of Gaussian noise and JEPG compression. Because most of the false copy-move pairs locate closely to each other in the spatial domain or are in the homogeneous regions, the Euclidian distance and pixel variance are employed in the post-verification step. After evaluating the proposed method by the precision-recall-F1 model quantitatively based on the Image Manipulation Dataset (IMD) and Copy-Move Hard Dataset (CMHD), our method outperforms Emam et al.’s and Li et al.’s works in the recall and F1 aspects.
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Research on Spider Fine-Grained Recognition Technology Based on Transfer Learning
Jianming Wang,Longfeng Deng,Chenyang Shi,Guosheng Ye,Zizhong Yang 한국정보과학회 2023 Journal of Computing Science and Engineering Vol.17 No.4
Few-shot image recognition represents a critical challenge in computer vision research. The scarcity of samples often results in inaccurate classification, limited generalization capabilities, and overfitted model recognition. To address these issues, the present study focuses on spider image recognition utilizing transfer learning and data augmentation techniques in limited sample settings. First, the BasNet image segmentation model and background replacement algorithm are used to extract species image data from the foreground; data augmentation is then applied to address the scarcity of samples. Second, a layer-by-layer fine-tuned transfer learning strategy based on the ResNet-50 model is devised. Specifically, to mitigate overfitting in the few-shot image classification task, the first two residual blocks are frozen so that only the last two are trained. To enhance the model’s representation and generalization abilities, the SSC-ResNet-50 optimization model is constructed by introducing symmetry techniques. This study aims to enhance the accuracy and performance of spider image recognition. The experimental results demonstrate that the improved SSC-ResNet-50 model achieves an average accuracy of 99.1% in recognizing five types of spiders, thereby surpassing the performance of traditional models. These findings offer valuable insights for the field of small-sample high-precision image recognition.
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Volunteering and psychological wellbeing in college students in China
Geng Yun,Huang Chien‐Chung,Deng Guosheng,Cheung Shannon P.,Liao Jinyu 한국사회복지학회 2022 Asian Social Work and Policy Review Vol.16 No.2
This study used data from 1871 college students across China to examine the relations among volunteering and PWB in 2020. Results of regression analysis indicate that volunteering had positive effects on the PWB of the students. Students whose motivation to volunteer was public interest had greater PWB, regardless of the degree to which they also reported private gain as a motivation. The significant interaction results indicate that students whose volunteer motivation included both public interest and private gains and who had high frequency of volunteering were more likely to have higher PWB. Policy and practice implications were discussed.
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