ABSTRACT
Objective To collect and summarize the opinions of experts on the improvement of China's disease prevention and control system published in the public media, so as to provide reference for the relevant construction planning of the government. Methods: Articles were collected from January to May, 2020, which were published on Chinese mainstream media. Based on the analysis of literature and the basic characteristics of experts, Analytic hierarchy process (AHP) was used to summarize the construction points of experts in different construction fields. Results: A total of 19 opinion articles were finally included in the study and 29 experts were involved. The suggestions of experts on the construction of China's disease prevention and control system were summarized into four aspects. Conclusion: The COVID-19 pandemic is a challenge to the existing public health epidemic prevention and control system in China, and also an important opportunity for the development and construction of the related system.
ABSTRACT
The effect of camera viewpoint and fruit orientation on the performance of a sweet pepper maturity level classification algorithm was evaluated. Image datasets of sweet peppers harvested from a commercial greenhouse were collected using two different methods, resulting in 789 RGB-Red Green Blue (images acquired in a photocell) and 417 RGB-D-Red Green Blue-Depth (images acquired by a robotic arm in the laboratory), which are published as part of this paper. Maturity level classification was performed using a random forest algorithm. Classifications of maturity level from different camera viewpoints, using a combination of viewpoints, and different fruit orientations on the plant were evaluated and compared to manual classification. Results revealed that: (1) the bottom viewpoint is the best single viewpoint for maturity level classification accuracy; (2) information from two viewpoints increases the classification by 25 and 15 percent compared to a single viewpoint for red and yellow peppers, respectively, and (3) classification performance is highly dependent on the fruit's orientation on the plant.