Linear Gaussian Bounding Box Representation and Ring-Shaped Rotated Convolution for Oriented Object Detection

In oriented object detection, current representations of oriented bounding boxes (OBBs) often suffer from boundary discontinuity problem. Methods of designing continuous regression losses do not essentially solve this problem. Although Gaussian bounding box (GBB) representation avoids this problem, directly regressing GBB is susceptible to numerical instability. We propose linear GBB (LGBB), a novel OBB representation. By linearly transforming the elements of GBB, LGBB avoids the boundary discontinuity problem and has high numerical stability. In addition, existing convolution-based rotation-sensitive feature extraction methods only have local receptive fields, resulting in slow feature aggregation. We propose ring-shaped rotated convolution (RRC), which adaptively rotates feature maps to arbitrary orientations to extract rotation-sensitive features under a ring-shaped receptive field, rapidly aggregating features and contextual information. Experimental results demonstrate that LGBB and RRC achieve state-of-the-art performance. Furthermore, integrating LGBB and RRC into various models effectively improves detection accuracy

Design of Seismic Intensity Rapid Report Platform

Abstract. Seismic intensity rapid report is one of the essential parts of the earthquake disaster relief and plays a baton role. In terms of serving the needs for earthquake early warning, emergency response, and seismic mobile observation, seismic network observation, a new seismic intensity rapid report platform is developed for the seismic intensity sensor network. The platform has a complete seismic intensity monitor system, and can achieve accurate and efficient intensity data recovery and analysis, built rapid and efficient intensity report system. Some key functions were utilized to integrate the platform, such as data collection, real-time data analysis, graphic display and intensity rapid reporting. A serial of experiments were carried out and the results showed that the platform could fulfill the purpose of seismic emergency response and deserve to be widely popularized

The Spatial Distribution and Potential for Energy Recovery of Urban-Rural Wastes in Guangdong Province, Southern China

Abstract Wastes-to-energy (WTE) has been widely recognized as an effective way to save resources while minimizing environmental pollution, which has become the key issue for a sustainable society. Urban-rural wastes include all kinds of waste generated during human activities, which have a wide range from municipal solid waste (MSW) to agricultural residues and animal excrement, etc. In order to evaluate their potential for energy recovery and greenhouse gas (GHG) mitigation in Guangdong province, the generation, spatial distribution and energy potential of three typical waste streams (i.e. MSW, agricultural residues and animal excrement) were investigated using statistical and estimation methods. Results showed that: (1) MSW was mainly concentrated in the Pearl River Delta, but agricultural residues and animal excrement mainly distributed in the East Wing, West Wing and Mountainous Areas; (2) energy potential of studied wastes at least can reach 15.661 million tons of coal-equivalent and corresponding GHG mitigation is 41.720 million tons CO2 equivalent. The pattern of distributed utilization may be appropriate for rural wastes, such as agricultural residues and animal excrement, because recycling is difficult due to they are dispersed distribution. Results of this study may help decision-makers to evaluate the proper management of urban-rural wastes and can be a reference for other developing countries

Analysis of Key Technologies of Bridge Damage Detection Based on Visual Recognition

In the identification of bridge damage in the series of deflection-affecting lines, noise signals due to axle coupling often occur. Removing these noise signals has become a key technique for effectively identifying damage. Taking the main line bridge of a overpass project in Fuzhou City of Fujian Province as an example, we collected the deflection a data of the bridge by using HPON-X target-free bridge deflectometer and used YOLOv3 algorithm for deep learning of the vehicle load position. The data were measured and studied by using DB9 wavelet de-noising method. The research shows that this method can greatly reduce the influence of vehicle bridge interaction on deflection influence line, and can enhance the accuracy and speed of bridge damage detection

Effectiveness of optimized control strategy and different hub height turbines on a real wind farm optimization

Highlights • An optimized control strategy approach and different hub height turbines are studied. • Means of handling irregular boundaries and wind speed variations over non-flat terrain are developed. • Optimized control strategy yields 9 kW more power per turbine than self-optimum control strategy. • Optimized control strategy reduces cost of energy by 0.08 million dollars per megawatt. • Different hub height turbines are more able to alleviate wake interactions than constant hub height

Comparative study of discretization method and Monte Carlo method for wind farm layout optimization under Weibull distribution

The wind farm layout optimization is an effective tool to alleviate the wake power losses caused by wind turbine interactions in a wind farm. It is widely recognized that for a real wind farm site with abundant wind resources, wind speed variation of the wind condition can be approximated by the Weibull distribution, which therefore needs to be incorporated into the power evaluation of a real wind farm design. Current researchers have employed the discretization method by dividing the wind speed region into bins to calculate the power output of wind turbines under Weibull distribution, which has two main drawbacks including: 1) complicated discretization process with large computational cost and 2) dependency of calculation accuracy on the discretization resolution. This paper aims to propose a new Monte Carlo method to evaluate the wind farm power output under Weibull distribution, and verify the effectiveness and efficiency of the new method by comparison to the widely used discretization method. Through reducing the wind speed discretizing interval, it is found that when the discretized wind speed interval is smaller than 0.1 m/s, the improvement of optimization results is negligible while the computational cost significantly increases for the discretization method. By testing different sample numbers, it is found that selecting 100000 samples for the Monte Carlo method calculation is able to achieve accurate results with less computational cost than the discretization method especially when large number of turbines is installed in the wind farm. In conclusion, the Monte Carlo method greatly facilitates the power evaluation of wind farm layout optimization under Weibull distribution, with a balance between the calculation accuracy and the computational cost

Diverse molecular compositions of dissolved organic matter derived from different composts using ESI FT-ICR MS

Dissolved organic matter (DOM) derived from various composts can promote significant changes of soil properties. However, little is known about the DOM compositions and their similarities and differences at the molecular level. In this study, the molecular compositions of DOM derived from kitchen waste compost (KWC), green waste compost (GWC), manure waste compost (MWC), and sewage sludge compost (SSC) were characterized by electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS). The molecular formulas were classified into four subcategories: CHO, CHON, CHOS, and CHONS. The KWC, MWC, and SSC DOM represented the highest fraction (35.8%-47.4%) of CHON subcategory, while the GWC DOM represented the highest fraction (68.4%) of CHO subcategory. The GWC DOM was recognized as the nitrogen- and sulfur-deficient compounds that were less saturated, more aromatic, and more oxidized compared with other samples. Further analysis of the oxygen, nitrogen-containing (N-containing), and sulfur-containing (S-containing) functional groups in the four subcategories revealed higher organic molecular complexity. Comparison of the similarities and differences of the four samples revealed 22.8% ubiquitous formulas and 17.4%, 11.1%, 10.7%, and 6.3% unique formulas of GWC, KWC, SSC, and MWC DOM, respectively, suggesting a large proportion of ubiquitous DOM as well as unique, source-specific molecular signatures. The findings presented herein provide new insight into the molecular characterization of DOM derived from various composts and demonstrated the potential role of these different compounds for agricultural utilization. (C) 2020 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V

Combined optimization of continuous wind turbine placement and variable hub height

This paper aims to systematically study the wind farm optimization with the continuous selection of wind turbine placement (using Cartesian coordinates) and wind turbine hub height (restrained among a predefined range). Two case studies are performed. The first case involves an ideal two-dimensional (i.e., flat terrain) wind farm, and the other is a three-dimensional wind farm with real terrain altitudes. The schemes of simultaneously optimizing the wind farm layout and wind turbine hub heights applying the simplified and augmented PARK wake model are established for the ideal and real wind farm cases, respectively. The results show that applying different wind turbine hub heights for the wind farm layout optimization yields significant improvement: up to a 0.2 MW increase in total power and a 2% increase of the wind farm efficiency for the ideal wind farm. However, for the real wind farm the effectiveness of applying different wind turbine hub heights varies depending on the number of turbines installed. With less number of turbines installed, the impact of varying hub heights is small. However, significant improvements can be achieved as the number of turbines increases. With 39 wind turbines, the wind farm cost of energy can be reduced by $15000 per megawatt and the wind farm efficiency can increase by up to 0.2%. Given the nameplate capacity and the lifespan of wind farm project, the resulting effect on total energy production can be significant and thus improve the competitiveness of wind power exploitation.</p