Progress of Materials Science in Space Technology in China(2020-2022)

In this paper,the main research work and related reports of materials science research in China’s space technology field during 2020-2022 are summarized.This paper covers Materials Sciences in Space Environment,Materials Sciences for Space Environment,Materials Behavior in Space Environment and Space experimental hardware for material investigation.With the rapid development of China’s space industry,more scientists will be involved in materials science,space technology and earth science researches.In the future,a series of disciplines such as space science,machinery,artificial intelligence,digital twin and big data will be further integrated with materials science,and space materials will also usher in new development opportunities.

Understanding the Interaction Between Space and Behavior: A Review of Behavior Geography

Behavior Geography Authors: Chai Yanwei, Ta Na Year: 2022 Publisher: Southeast University Press ISBN: 9787564193508(320,000 characters, in Chinese) In the context of a fluid society and cities in transition, the dynamic relationship between humans and their environment has received considerable attention in the field of geography.

Assessing the visualization of space and traffic volume using GIS-based processing and visibility parameters of space syntax

Streets and physical layouts can be inherent in a sustainable city by emphasizing the use of space with planned strategies by promoting the movement of people and social behaviors for enhancing an economic structure.An analysis of the space layout is beneficial for defining the urban areas that can affect street behavior.A GIS incorporated with a space syntax can help to propagate the effectiveness of a spatial analysis in a study on urban spaces.The integration of the computational pieces of both a GIS analytical tool and space syntax parameters will stimulate research oriented urban systems and spatial morphologies combined with a spatial database.However,the development of livability can be affected by a set of parameters that define the used space.Thus,this paper was aimed at examining the space syntax parameters for space visualization to evaluate street behavior using the GIS processing and space syntax methods.In this study,a spatial analysis was used to generate spatial information on traffic volume,while a space syntax was used to test the street behavior.Also,a predictive analysis was conducted to identify the correlation between traffic behavior and a set of parameters.The results showed that integration and direct visibility were significant to the traffic volume.Most of the streets that were linked to the commercial area showed high integration and direct visibility,which increased by more than half,compared with the unlinked areas.Based on the statistical analysis,both parameters recorded aprobability of less than 5%.The results showed that any space designed with a continuous,direct and clear traffic volume will lead to increased integration and direct visibility,thus influencing a natural vehicle movement.

Trust Evaluation Model Based on Behavior Space Classification for Ad Hoc Networks

Trust management frameworks are used to evaluate and manage trust relationships between network nodes and enhance network security. However, trust management frameworks themselves are vulnerable to attacks. Attacks against trust management frameworks are described in this paper with a trust management framework to resist them. The trustworthiness between nodes is evaluated to classify node behavior using a three-dimensional classifier based on a fuzzy integral. Different behaviors are mapped to different behavioral spaces to detect malicious nodes and identify their behavior types. The security of ad hoc networks is then improved by various measures to handle different types of malicious behavior. Simula- tions of the model on the System In The Loop （SITL） platform show that this trust management framework can separate normal nodes and malicious nodes and can distinguish different types of malicious nodes.