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Differences on Information Commitments in Consumption Domain
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作者 hung-ming lin 《Journal of Psychological Research》 2019年第3期43-47,共5页
Information commitments are a profile of evaluative standards and information searching strategies on the Internet.The purpose of this study is to examine the reliability and validity of the information commitments in... Information commitments are a profile of evaluative standards and information searching strategies on the Internet.The purpose of this study is to examine the reliability and validity of the information commitments instrument in consumption domain,and differences among scales underlying the instrument.A total of 258 university students participated in the survey who have experiences in online shopping.Using confirmatory factor analysis technical,this study has identified valid measures for each construct underlying information commitments in consumptions domain.The results indicate that participants preferred to utilize“content”to judge the usefulness of the information,and use“multiple sources”to evaluate the correctness of information,that they oriented to use search strategy“elaboration”in verifying online consumption information.Gender differences are also revealed on standard of the“multiple sources”and the“content”. 展开更多
关键词 INFORMATION commitments Confirmatory FACTOR analysis Online SHOPPING INFORMATION
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Assessment of highway slope failure using neural networks 被引量:2
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作者 Tsung-lin LEE hung-ming lin Yuh-pin LU 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2009年第1期101-108,共8页
An artificial intelligence technique of back-propagation neural networks is used to assess the slope failure.On-site slope failure data from the South Cross-Island Highway in southern Taiwan are used to test the perfo... An artificial intelligence technique of back-propagation neural networks is used to assess the slope failure.On-site slope failure data from the South Cross-Island Highway in southern Taiwan are used to test the performance of the neural network model.The numerical results demonstrate the effectiveness of artificial neural networks in the evaluation of slope failure potential based on five major factors,such as the slope gradient angle,the slope height,the cumulative precipitation,daily rainfall and strength of materials. 展开更多
关键词 Neural network PREDICTION HIGHWAY Slope failure
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