In the recent research of network sampling, some sampling concepts are misunderstood, and the variance of subnets is not taken into account. We propose the correct definition of the sample and sampling rate in network...In the recent research of network sampling, some sampling concepts are misunderstood, and the variance of subnets is not taken into account. We propose the correct definition of the sample and sampling rate in network sampling, as well as the formula for calculating the variance of subnets. Then, three commonly used sampling strategies are applied to databases of the connecting nearest-neighbor（CNN） model, random network and small-world network to explore the variance in network sampling. As proved by the results, snowball sampling obtains the most variance of subnets, but does well in capturing the network structure. The variance of networks sampled by the hub and random strategy are much smaller. The hub strategy performs well in reflecting the property of the whole network, while random sampling obtains more accurate results in evaluating clustering coefficient.展开更多
Mixing index is an important parameter to understand and assess the mixing state in various mixers including ribbon mixers,the typical food processing devices.Many mixing indices based on either sample variance method...Mixing index is an important parameter to understand and assess the mixing state in various mixers including ribbon mixers,the typical food processing devices.Many mixing indices based on either sample variance methods or non-sample variance methods have been proposed and used in the past,however,they were not well compared in the literature to evaluate their accuracy of assessing the final mixing state.In this study,discrete element method(DEM)modelling is used to investigate and compare the accuracy of these mixing indices for mixing of uniform particles in a horizontal cylindrical ribbon mixer.The sample variance methods for mixing indices are first compared both at particle-and macro-scale levels.In addition,non-sample variance methods,namely entropy and non-sampling indices are compared against the results from the sample variance methods.The simulation results indicate that,among the indices considered in this study,Lacey index shows the most accurate results.The Lacey index is regarded to be the most suitable mixing index to evaluate the steady-state mixing state of the ribbon mixer in the real-time(or without stopping the impeller)at both the particle-and macro-scale levels.The study is useful for the selection of a proper mixing index for a specific mixture in a given mixer.展开更多
基金supported by the Basic Research Fund of Beijing Institute of Technology(20120642008)
文摘In the recent research of network sampling, some sampling concepts are misunderstood, and the variance of subnets is not taken into account. We propose the correct definition of the sample and sampling rate in network sampling, as well as the formula for calculating the variance of subnets. Then, three commonly used sampling strategies are applied to databases of the connecting nearest-neighbor（CNN） model, random network and small-world network to explore the variance in network sampling. As proved by the results, snowball sampling obtains the most variance of subnets, but does well in capturing the network structure. The variance of networks sampled by the hub and random strategy are much smaller. The hub strategy performs well in reflecting the property of the whole network, while random sampling obtains more accurate results in evaluating clustering coefficient.
基金This work is financially supported by the Australian Research Council(DP180101232).
文摘Mixing index is an important parameter to understand and assess the mixing state in various mixers including ribbon mixers,the typical food processing devices.Many mixing indices based on either sample variance methods or non-sample variance methods have been proposed and used in the past,however,they were not well compared in the literature to evaluate their accuracy of assessing the final mixing state.In this study,discrete element method(DEM)modelling is used to investigate and compare the accuracy of these mixing indices for mixing of uniform particles in a horizontal cylindrical ribbon mixer.The sample variance methods for mixing indices are first compared both at particle-and macro-scale levels.In addition,non-sample variance methods,namely entropy and non-sampling indices are compared against the results from the sample variance methods.The simulation results indicate that,among the indices considered in this study,Lacey index shows the most accurate results.The Lacey index is regarded to be the most suitable mixing index to evaluate the steady-state mixing state of the ribbon mixer in the real-time(or without stopping the impeller)at both the particle-and macro-scale levels.The study is useful for the selection of a proper mixing index for a specific mixture in a given mixer.
