The Four-dimensional Value of Mao Zedong Thought

Mao Zedong Thought was born in the revolutionary war period, and under specific background, it guided and led China to a semi-colonial and semi- feudal society to a novel democratic and socialist society. Maoism is the theoretical innovation and development of the Marxism–Leninism in China. It is the theoretical principle, objective reality and experience summary of the Chinese revolution and construction that has been practiced. Under the background of the new period, Mao Zedong Thought still has important practical significance and implication of the Times. To learn Mao Zedong Thought should also be interpreted from the four dimensions of historical values, theoretical value, practicable value and time value

An Empirical Study on the Intercultural Communicative Competence of Chinese EFL College Students

Through a questionnaire survey of 100 English majors and non-English majors in North China Electric Power University, this study explores the intercultural communicative competence (ICC) of Chinese EFL students at the tertiary level. The questions in the questionnaire are designed around three key points concerning the ICC: intercultural knowledge, intercultural awareness and ICC. The correlation between the ICC, the academic achievement, and other relevant factors has been examined. The results of the data analysis show that: (1) all students have a considerable amount of intercultural knowledge, have developed keen awareness of cultural differences, and are equipped with a relatively high level of ICC; (2) there is a positive correlation between their academic achievements and their ICC; (3) factors of international experience, gender and major have some effects on students’ ICC. Students with international experience tend to have a better intercultural performance, and so do the female students and English majors. Keywords: intercultural communicative competence, intercultural knowledge, intercultural awareness, Chinese EFL college student

A Neural Network Model for Driver’s Lane-Changing Trajectory Prediction in Urban Traffic Flow

The neural network may learn and incorporate the uncertainties to predict the driver’s lane-changing behavior more accurately. In this paper, we will discuss in detail the effectiveness of Back-Propagation (BP) neural network for prediction of lane-changing trajectory based on the past vehicle data and compare the results between BP neural network model and Elman Network model in terms of the training time and accuracy. Driving simulator data and NGSIM data were processed by a smooth method and then used to validate the availability of the model. The test results indicate that BP neural network might be an accurate prediction of driver’s lane-changing behavior in urban traffic flow. The objective of this paper is to show the usefulness of BP neural network in prediction of lane-changing process and confirm that the vehicle trajectory is influenced previously by the collected data

Investigation of Thin Cirrus Cloud Optical and Microphysical Properties on the Basis of Satellite Observations and Fast Radiative Transfer Models

This dissertation focuses on the global investigation of optically thin cirrus cloud optical thickness (tau) and microphysical properties, such as, effective particle size (D_(eff)) and ice crystal habits (shapes), based on the global satellite observations and fast radiative transfer models (RTMs). In the first part, we develop two computationally efficient RTMs simulating satellite observations under cloudy-sky conditions in the visible/shortwave infrared (VIS/SWIR) and thermal inferred (IR) spectral regions, respectively. To mitigate the computational burden associated with absorption, thermal emission and multiple scattering, we generate pre-computed lookup tables (LUTs) using two rigorous models, i.e., the line-by-line radiative transfer model (LBLRTM) and the discrete ordinates radiative transfer model (DISORT). The second part introduces two methods (i.e., VIS/SWIR- and IR-based methods) to retrieve tau and D_(eff) from satellite observations in corresponding spectral regions of the two RTMs. We discuss the advantages and weakness of the two methods by estimating the impacts from different error sources on the retrievals through sensitivity studies. Finally, we develop a new method to infer the scattering phase functions of optically thin cirrus clouds in a water vapor absorption channel (1.38-µm). We estimate the ice crystal habits and surface structures by comparing the inferred scattering phase functions and numerically simulated phase functions calculated using idealized habits. We find two critical features of the two retrieval methods: (1) the IR-based method is more sensitive to optically thin cirrus cloud, and (2) the VIS/SWIR-based method is more sensitive to the pre-assumed ice cloud microphysical parameterization schemes. We derive the optically thin cirrus cloud phase functions based on the two methods. We find that small column-like particles (e.g., solid columns and columnaggregates) and droxtals with rough surfaces are likely to reside in optically thin cirrus clouds