Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2
Search results for: Dr.Siwei Cao
2 Reform of the Intellectual Property Administrative System and High-Quality Innovation of Enterprises
Authors: Prof. Hao Mao, Phd Qia Wei, Dr.Siwei Cao
Abstract:
The administrative system is the organisational carrier for managing the operation of the market and the basic guarantee for achieving innovation incentives. This paper takes the reform of provincial administrative institutions in the process of Chinese national intellectual property administrative system reform in 2018 as a quasi-natural experiment to assess the impact of IP administrative system reform on enterprise innovation. The study finds that reducing the independence of some provincial administrative institutions will lead to a reduction in the number of local enterprises' innovations and a decrease in the quality of innovations, which is mainly triggered by a decrease in R&D investment due to a decrease in the strength of subsidy policies. The new round of intellectual property administrative system reform in 2023 elevated the administrative status of China National Intellectual Property Administration (CNIPA), and re-strengthened the top-level design and centralization of IP administration. This paper clarifies the role of the 2018 IP administrative system reform on China's market innovation, provides empirical evidence for the properly handling government market relations and property rights incentives and other institutional designs, and also provides empirical references for further promoting the improvement of national and local IP institutional mechanisms and the implementation of the innovation-driven development strategy in the new round of reform.Keywords: intellectual property, administrative systems, reform, high-quality innovation
Procedia PDF Downloads 401 Performance Analysis of Vision-Based Transparent Obstacle Avoidance for Construction Robots
Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang
Abstract:
Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle
Procedia PDF Downloads 80