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	Social comparisons differentially affect fair and unfair processing in ultimatum bargaining 期刊论文 OAI收割 NEUROPSYCHOLOGIA, 2022, 卷号: 174, 页码: 10 作者: Li, Qi; Dai, Weine; Zheng, Ya; Wang, Chunsheng; Yang, Zhong \| 收藏 \| 浏览/下载：38/0 \| 提交时间：2022/12/16 Traditional models Comparative models Decision -making Ultimatum game MFN P300
	The application of variable-structure control in theodolite fast capture (EI CONFERENCE) 会议论文 OAI收割 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012, August 1, 2012 - August 2, 2012, Guangxi, China Bing G. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 The high capability of O-E theodolite to track and acquire fast moving targets is required these years because of the rapid advancement of tested targets and automation of equipments. The traditional method of increasing the frequency width is limit. By using multi control models and velocity leading the capability to track and acquire fast moving target is improved highly. The theories and technologies discussed in this dissertation were tested with experiments. It verifies that the theoretical analysis in this dissertation is correct. (2012) Trans Tech Publications Switzerland.
	Study of the neural network constitutive models for turfy soil with different decomposition degree (EI CONFERENCE) 会议论文 OAI收割 2011 2nd International Conference on Mechanic Automation and Control Engineering, MACE 2011, July 15, 2011 - July 17, 2011, Inner Mongolia, China 作者: Nie L. 收藏 \| 浏览/下载：19/0 \| 提交时间：2013/03/25 The turfy soil is of a special humus soil. The decomposition degree is the main factor on the physical and mechanical properties of turfy soil. To build the turfy soil constitutive model there are a few shortages such as the calculation cumbersome and low accuracy for parameter value with the method of traditional models. Furthermore those methods did not reflect the influence of strength that effected by decomposition degree of the turfy soil. In this paper the relationship of stress-strain with different decomposition degrees of turfy soil was carried out through indoor tests. Based on above experimental results an improved method which divided into different zones according to different decomposition degrees of turfy soil and calculated combining with neural network constitutive model is put forward. The result shows that the neural network of turfy soil has good fitting precision and good generalization ability. It can fully describe the influence of the turfy soil. 2011 IEEE.
	Heterogeneous architecture-based software reliability estimation: Case study (EI CONFERENCE) 会议论文 OAI收割 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008, November 11, 2008 - November 13, 2008, Busan, Korea, Republic of Wei Y.; Shen X.-H. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 With growing system complication multiple structures are constructed in software instead of single architecture style. As a result the traditional architecture-based models that have considered only homogeneous software behaviors are not suitable to the complex system. In this paper a heterogeneous architecture-based model is presented. In order to verify the practicability we apply the model to estimate the system reliability of the astronautics payload communication and monitoring system (APCMS). Multiple structures are constructed in the system i.e. sequence parallel and fault-tolerance. The study results demonstrate that the model is accurate when compared to the actual reliability. Theoretical research must be applied on actual systems to understand their applicability and accuracy. 2008 IEEE.
	Remote chlorophyll-a retrieval in eutrophic inland waters by concentration classification Taihu Lake case study 会议论文 OAI收割 International Conference on Earth Observation Data Processing and Analysis, ICEODPA,, Wuhan, China, December 28, 2008 - December 30,2008 Du, Cong; Wang, Shixin; Zhou, Yi; Yan, Fuli 收藏 \| 浏览/下载：33/0 \| 提交时间：2014/12/07 In order to improve the precision of phytoplankton chlorophyll-a (chla) concentration retrieval this study classified the data into two groups (the high and the low) by chla concentration with the threshold of 50gA&bullL-1. And then build the statistical models for each group. Particularly a modifying factor OSS/TSS was used to unmixing the spectra in the low model to improve the low relationship between spectral reflectance and chla concentrations. As a result the concentration classification model allowed estimation of chla with a root mean square error (RMSE) of 21.12gA&bullL-1 and the determination coefficient (R2) was 0.92 comparing with RMSE of chla estimation was 35.72gA&bullL-1 and R2=0.72 in the traditional model. It shows that concentration classification is a helpful method for accurate remote chla retrieval in eutrophic inland waters. 2008 SPIE.