This paper presents a method for assessing the influence of the interaction environment of an organization. The interaction environment of an organization is composed of three elements： （1） the physical structure o...This paper presents a method for assessing the influence of the interaction environment of an organization. The interaction environment of an organization is composed of three elements： （1） the physical structure of the organization, including numbers of buildings, floors, common gathering areas, size, industry, and physical layout; （2） the information structure, consisting of the numbers and types of communication channels in the organization; and （3） the social structure, consisting of both individual-level assessments of the social environment of the organization as well as the organizational attempts to create a more social environment. This assessment tool has been tested in a large-scale study of organ donation campaigns in 46 organizations. Findings from this earlier test of the assessment tool demonstrate that interaction environment influences the way people communicate about, seek information about, and make decisions about health-related topics in organizations. Additionally, the individual elements of the interaction environment work in complex ways and also influence communication patterns and knowledge about health information. This paper details the procedures for using this assessment tool, methods for analyzing the findings, limitations of the tool, and areas in need of refinements and further researches.展开更多
Snow-cover parameters are important indicator factors for hydrological models and climate change studies and have typical vertical stratification characteristics. Remote sensing can be used for large-scale monitoring ...Snow-cover parameters are important indicator factors for hydrological models and climate change studies and have typical vertical stratification characteristics. Remote sensing can be used for large-scale monitoring of snow parameters. In SAR(Interferometric Synthetic Aperture Radar) technology has advantages in detecting the vertical structure of snow cover. As a basis of snow vertical structure detection using In SAR, a scattering model can reveal the physical process of interaction between electromagnetic waves and snow. In recent years, the In SAR scattering model for single-layer snow has been fully studied;however, it cannot be applied to the case of multi-layer snow. To solve this problem, a multi-layer snow scattering mode is proposed in this paper, which applies the QCA(Quad-Crystal Approximation) theory to describe the coherent scattering characteristics of snow and introduces a stratification factor to describe the influence of snow stratification on the crosscorrelation of SAR echoes. Based on the proposed model, we simulate an In SAR volumetric correlation of different types of multi-layer snow at the X band(9.6 GHz). The results show that this model is suitable for multi-layer snow, and the sequence of sub-layers of snow has a significant influence on the volumetric correlation. Compared to the single layer model, the multi-layer model can predict a polarization difference in the volumetric correlation more accurately and thus has a wider scope of application. To make the model more available for snow parameter inversion, a simplified multi-layer model was also developed.The model did not have polarization information compared to that of the full model but showed good consistency with the full model. The phase of the co-polarization In SAR volumetric correlation difference is more sensitive to snow parameters than that of the phase difference of the co-polarization In SAR volumetric correlation and more conducive to the development of a parameter-inversion algorithm. The model can be applied to deepen our understanding of In SAR scattering mechanisms and to develop a snow parameter inversion algorithm.展开更多
文摘This paper presents a method for assessing the influence of the interaction environment of an organization. The interaction environment of an organization is composed of three elements： （1） the physical structure of the organization, including numbers of buildings, floors, common gathering areas, size, industry, and physical layout; （2） the information structure, consisting of the numbers and types of communication channels in the organization; and （3） the social structure, consisting of both individual-level assessments of the social environment of the organization as well as the organizational attempts to create a more social environment. This assessment tool has been tested in a large-scale study of organ donation campaigns in 46 organizations. Findings from this earlier test of the assessment tool demonstrate that interaction environment influences the way people communicate about, seek information about, and make decisions about health-related topics in organizations. Additionally, the individual elements of the interaction environment work in complex ways and also influence communication patterns and knowledge about health information. This paper details the procedures for using this assessment tool, methods for analyzing the findings, limitations of the tool, and areas in need of refinements and further researches.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41471065 & 41471066)the International Partnership Program of Chinese Academy of Sciences (Grant No. 131C11KYSB20160061)+1 种基金the Science & Technology Basic Resources Investigation Program of China (Grant No. 2017FY100502)the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA19070201)
文摘Snow-cover parameters are important indicator factors for hydrological models and climate change studies and have typical vertical stratification characteristics. Remote sensing can be used for large-scale monitoring of snow parameters. In SAR(Interferometric Synthetic Aperture Radar) technology has advantages in detecting the vertical structure of snow cover. As a basis of snow vertical structure detection using In SAR, a scattering model can reveal the physical process of interaction between electromagnetic waves and snow. In recent years, the In SAR scattering model for single-layer snow has been fully studied;however, it cannot be applied to the case of multi-layer snow. To solve this problem, a multi-layer snow scattering mode is proposed in this paper, which applies the QCA(Quad-Crystal Approximation) theory to describe the coherent scattering characteristics of snow and introduces a stratification factor to describe the influence of snow stratification on the crosscorrelation of SAR echoes. Based on the proposed model, we simulate an In SAR volumetric correlation of different types of multi-layer snow at the X band(9.6 GHz). The results show that this model is suitable for multi-layer snow, and the sequence of sub-layers of snow has a significant influence on the volumetric correlation. Compared to the single layer model, the multi-layer model can predict a polarization difference in the volumetric correlation more accurately and thus has a wider scope of application. To make the model more available for snow parameter inversion, a simplified multi-layer model was also developed.The model did not have polarization information compared to that of the full model but showed good consistency with the full model. The phase of the co-polarization In SAR volumetric correlation difference is more sensitive to snow parameters than that of the phase difference of the co-polarization In SAR volumetric correlation and more conducive to the development of a parameter-inversion algorithm. The model can be applied to deepen our understanding of In SAR scattering mechanisms and to develop a snow parameter inversion algorithm.
