Suchergebnisse

Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

This paper investigates the impact of state ownership on the efficiency-equality tradeoff in a mixed economy with both state and nonstate sectors. Using overall capital productivity as an efficiency proxy and state output share as an inequality proxy, we identify the efficiency threshold of state capital share that splits the efficiency-equality relationship between a tradeoff and nontradeoff. When state capital share is greater than the threshold (as evidenced in the case of China), lowering state capital share improves efficiency and reduces inequality. Furthermore, our simulation results suggest that the threshold is sensitive to capital shares in output of the both sectors. A broad scope for mutual gains in efficiency and equality exists by raising the capital share in nonstate output and lowering the capital share in state output.

Part 1: GIS, GPS, RS and Precision Farming ; International audience ; In the background of the digital agriculture advanced step-by-step, Shanghai government is also accelerating the pace of agricultural informationization. "Precision Agriculture" has become a pointcut of "Digital Shanghai". Building the Operating System of Shanghai Agricultural Economy is a meaningful practice in Shanghai digital agriculture engineering. Its powerful function of spatial data analysis and inquiry provides the support system for the realization of "precision agriculture". It can provide the decision support and the information service for the government.

The number of surface water pollution accidents (abbreviated as SWPAs) has increased substantially in China in recent years. Estimation of economic losses due to SWPAs has been one of the focuses in China and is mentioned many times in the Environmental Protection Law of China promulgated in 2014. From the perspective of water bodies' functions, pollution accident damages can be divided into eight types: damage to human health, water supply suspension, fishery, recreational functions, biological diversity, environmental property loss, the accident's origin and other indirect losses. In the valuation of damage to people's life, the procedure for compensation of traffic accidents in China was used. The functional replacement cost method was used in economic estimation of the losses due to water supply suspension and loss of water's recreational functions. Damage to biological diversity was estimated by recovery cost analysis and damage to environmental property losses were calculated using pollutant removal costs. As a case study, using the proposed calculation procedure the economic losses caused by the major Songhuajiang River pollution accident that happened in China in 2005 have been estimated at 2263 billion CNY. The estimated economic losses for real accidents can sometimes be influenced by social and political factors, such as data authenticity and accuracy. Besides, one or more aspects in the method might be overestimated, underrated or even ignored. The proposed procedure may be used by decision makers for the economic estimation of losses in SWPAs. Estimates of the economic losses of pollution accidents could help quantify potential costs associated with increased risk sources along lakes/rivers but more importantly, highlight the value of clean water to society as a whole.

AbstractUnlike previous studies mainly focused on the economic impact of green innovation, this paper explores its social returns, denoted by the stakeholder engagement, given stakeholders can affect or are affected by the firm's low‐carbon transition. Drawing on the complementary view and the substitute view, our empirical results from China over the sample period of 2012 to 2018 found that more green innovation would crowd in stakeholder‐related activities, especially for the welfare improvement of customers and suppliers. However, better stakeholder relations do not bring positive economic returns given the weak social pressures and uncertain rewards for being socially responsible in emerging countries. By doing so, our study expands the theoretical knowledge about the social impact of green innovation, thus offering a practical guidance for firms to simultaneously manage their environmental performance, social performance and economic performance in China and, potentially, in other emerging countries which also pursue environmental transition and better stakeholder management.

BACKGROUND: As COVID-19 continues to spread globally, traditional emergency management measures are facing many practical limitations. The application of big data analysis technology provides an opportunity for local governments to conduct the COVID-19 epidemic emergency management more scientifically. The present study, based on emergency management lifecycle theory, includes a comprehensive analysis of the application framework of China's SARS epidemic emergency management lacked the support of big data technology in 2003. In contrast, this study first proposes a more agile and efficient application framework, supported by big data technology, for the COVID-19 epidemic emergency management and then analyses the differences between the two frameworks. METHODS: This study takes Hainan Province, China as its case study by using a file content analysis and semistructured interviews to systematically comprehend the strategy and mechanism of Hainan's application of big data technology in its COVID-19 epidemic emergency management. RESULTS: Hainan Province adopted big data technology during the four stages, i.e., migration, preparedness, response, and recovery, of its COVID-19 epidemic emergency management. Hainan Province developed advanced big data management mechanisms and technologies for practical epidemic emergency management, thereby verifying the feasibility and value of the big data technology application framework we propose. CONCLUSIONS: This study provides empirical evidence for certain aspects of the theory, mechanism, and technology for local governments in different countries and regions to apply, in a precise, agile, and evidence-based manner, big data technology in their formulations of comprehensive COVID-19 epidemic emergency management strategies.