Learning to Segment and Represent Motion Primitives from Driving Data for Motion Planning Applications

Developing an intelligent vehicle which can perform human-like actions requires the ability to learn basic driving skills from a large amount of naturalistic driving data. The algorithms will become efficient if we could decompose the complex driving tasks into motion primitives which represent the elementary compositions of driving skills. Therefore, the purpose of this paper is to segment unlabeled trajectory data into a library of motion primitives. By applying a probabilistic inference based on an iterative Expectation-Maximization algorithm, our method segments the collected trajectories while learning a set of motion primitives represented by the dynamic movement primitives. The proposed method utilizes the mutual dependencies between the segmentation and representation of motion primitives and the driving-specific based initial segmentation. By utilizing this mutual dependency and the initial condition, this paper presents how we can enhance the performance of both the segmentation and the motion primitive library establishment. We also evaluate the applicability of the primitive representation method to imitation learning and motion planning algorithms. The model is trained and validated by using the driving data collected from the Beijing Institute of Technology intelligent vehicle platform. The results show that the proposed approach can find the proper segmentation and establish the motion primitive library simultaneously

Dehazed Image Quality Evaluation: From Partial Discrepancy to Blind Perception

Image dehazing aims to restore spatial details from hazy images. There have emerged a number of image dehazing algorithms, designed to increase the visibility of those hazy images. However, much less work has been focused on evaluating the visual quality of dehazed images. In this paper, we propose a Reduced-Reference dehazed image quality evaluation approach based on Partial Discrepancy (RRPD) and then extend it to a No-Reference quality assessment metric with Blind Perception (NRBP). Specifically, inspired by the hierarchical characteristics of the human perceiving dehazed images, we introduce three groups of features: luminance discrimination, color appearance, and overall naturalness. In the proposed RRPD, the combined distance between a set of sender and receiver features is adopted to quantify the perceptually dehazed image quality. By integrating global and local channels from dehazed images, the RRPD is converted to NRBP which does not rely on any information from the references. Extensive experiment results on several dehazed image quality databases demonstrate that our proposed methods outperform state-of-the-art full-reference, reduced-reference, and no-reference quality assessment models. Furthermore, we show that the proposed dehazed image quality evaluation methods can be effectively applied to tune parameters for potential image dehazing algorithms

In vitro antioxidant activity and inhibitory hepatic steatosis effect on oleic acid-induced fatty liver model of consecutive extracts from Rosa davurica Pall

The nutrient and phytochemical composition of Rosa davurica Pall. fruit (RDF) from China were determined, including sugar, reducing sugar, ascorbic acid, caroteniods and phenolics. RDF was successively extracted with chloroform, ethyl acetate (EA), water-saturated n-butanol, ethanol and distilled water, respectively. Among the five fractions, EA fraction revealed the highest total phenolic content and the strongest antioxidant ability in cyclic voltammograms (CV) and oxygen radical absorbance capacity (ORAC) assays. Moreover, the strongest inhibitory activity against oleic acidinduced (OA-induced) fatty liver in vitro was also the EA fraction. Further, it was separated by a semipreparative high performance liquid chromatography (HPLC) on C18 column. The most active fraction (EA-FII) of EA in all assays above, which mainly included catechin, quercetin-sedoheptulose and quercetin-94, was identified by LC/MS, HPLC and ultraviolet (UV)/V spectrum analysis.Keywords: RDF extracts, composition properties, antioxidant ability, inhibitory activity, oleic acid-induced, HPLC, LC/MS.African Journal of Biotechnology Vol. 12(31), pp. 4944-495

A flame combustion model-based wildfire-induced tripping risk assessment approach of transmission lines

With the intensification of global climate change, the frequency of wildfires has markedly increased, presenting an urgent challenge in assessing tripping failures for power systems. This paper proposes an innovative method to evaluate the spatial wildfire-induced tripping risk of transmission lines based on a flame combustion model. Firstly, Bayes theory is employed to assess the spatial probability of wildfire occurrence. Subsequently, Wang Zhengfei’s flame combustion model is utilized to estimate the potential flame height of wildfires along the transmission corridor. Thirdly, the insulation breakdown risk of the transmission line is calculated based on the relative height difference between the flame and the transmission line. Finally, the spatial wildfire-induced tripping risk of the transmission line is then determined by combining the wildfire occurrence probability and the insulation breakdown risk. A case study conducted in Guizhou province, China validates the accuracy of the proposed model. Utilizing ArcGIS, the wildfire occurrence probability distribution in Guizhou is visualized to enhance the efficiency of operation and maintenance. The results indicate that over 80% of wildfire incidents occurred in areas with occurrence probabilities exceeding 50%

Reduced-reference quality assessment of point clouds via content-oriented saliency projection

Many dense 3D point clouds have been exploited to represent visual objects instead of traditional images or videos. To evaluate the perceptual quality of various point clouds, in this letter, we propose a novel and efficient Reduced-Reference quality metric for point clouds, which is based on Content-oriented sAliency Projection (RR-CAP). Specifically, we make the first attempt to simplify reference and distorted point clouds into projected saliency maps with a downsampling operation. Through this process, we tackle the issue of transmitting large-volume original point clouds to end-users for quality assessment. Then, motivated by the characteristics of the human visual system (HVS), the objective quality scores of distorted point clouds are produced by combining content-oriented similarity and statistical correlation measurements. Finally, extensive experiments are conducted on SJTU-PCQA and WPC databases. The experiment results demonstrate that our proposed algorithm outperforms existing reduced-reference and no-reference quality metrics, and significantly reduces the performance gap between state-of-the-art full-reference quality assessment methods. In addition, we show the performance variation of each proposed technical component by ablation tests

Study on stability and homology analysis of arginine kinase from oyster

Objective To identify the natural protein arginine kinase (AK) extracted from oysters, and to understand its basic properties and homology. Methods AK was isolated and purified from oysters by ammonium sulfate salting out and anion exchange, and the relative molecular mass and secondary structure were determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and circular dichroism (CD) spectroscopy. Its stability was also studied. The amino acid sequences of oyster AK and 11 other crustacean and mollusk allergens were compared by bioinformatics software, and their homology was analyzed. Results The natural protein with a relative molecular weight of 40 kDa was oyster AK. AK was neither heat-resistant nor acid-resistant. Oyster AK has high homology of mollusk allergen AK amino acid sequence, and homology of crustacean amino acid sequence is 55%-60%. Conclusion Natural AK is extracted from oysters, and the stability and homology are basically understood. It will lay the foundation for comprehensive research on sensitization and sensitization mechanism of oysters

Dehazed image quality evaluation: from partial discrepancy to blind perception

Nowadays, vision oriented intelligent vehicle systems such as autonomous driving or transportation assistance can be optimized by enhancing the visual visibility of images acquired in bad weather conditions. The presence of haze in such visual scenes is a critical threat. Image dehazing aims to restore spatial details from hazy images. There have emerged a number of image dehazing algorithms, designed to increase the visibility of those hazy images. However, much less work has been focused on evaluating the visual quality of dehazed images. In this paper, we propose a Reduced-Reference dehazed image quality evaluation approach based on Partial Discrepancy (RRPD) and then extend it to a No-Reference quality assessment metric with Blind Perception (NRBP). Specifically, inspired by the hierarchical characteristics of the human perceiving dehazed images, we introduce three groups of features: luminance discrimination, color appearance, and overall naturalness. In the proposed RRPD, the combined distance between a set of sender and receiver features is adopted to quantify the perceptually dehazed image quality. By integrating global and local channels from dehazed images, the RRPD is converted to NRBP which does not rely on any information from the references. Extensive experiment results on both synthetic and real dehazed image quality databases demonstrate that our proposed methods outperform state-of-the-art full-reference, reduced-reference, and no-reference quality assessment models. Furthermore, we show that the proposed dehazed image quality evaluation methods can be effectively applied to tune parameters for image dehazing algorithms and have the potential to be deployed in real transportation systems

Environmental Performance of China’s Industrial System Considering Technological Heterogeneity and Interaction

The industrial sector, the backbone of China’s economic development, is a key field that requires environmental management. The purpose of this study is to propose an improved data envelopment analysis (DEA) model to analyze the performance of provincial industrial systems (ISs) from 2011 to 2020 in China. To comprehensively characterize the operational framework of ISs, this study proposes an improved meta-frontier network DEA model. Unlike the existing models, the one proposed in this study not only considers the technical heterogeneity of ISs, but also reflects the interaction between IS subsystems. The empirical analysis yields valuable research findings. First, the overall environmental performance of Chinese ISs is generally low, with an average performance of 0.50, showing a U-shaped trend during the study period. Furthermore, significant regional differences are observed in the environmental performance of Chinese ISs. Second, the average performance of the production subsystem is 0.75, while the average performance of the pollution control subsystem (PTS) is 0.44. The low performance of the PTS pulls down the overall performance of Chinese ISs. Third, the technological level of Chinese ISs is low, with about 50% improvement potential. Finally, targeted suggestions to promote the green development of ISs are proposed on the basis of the empirical results

Dissolution kinetics of malachite in ethylene diamine phosphate solutions

Ethylene diamine phosphate (EDP), as a synthetic organic reagent, was used for the first time to leach malachite, and a new method of using organic amine to leach copper oxide ore was developed. The effects of stirring speed, particle size, reagent concentration, and reaction temperature on EDP-dissolution malachite were investigated. Results showed that malachite rapidly dissolved in EDP solution. The malachite-dissolving rate also increased with increased reagent concentration, increased reaction temperature, and decreased particle size. Stirring speed exhibited nearly no effect on EDP-induced malachite dissolution. The leaching kinetics was found to follow the shrinking-core model, and dissolution was controlled by surface chemical reaction with an activation energy of 52.63kJ×mol−1. A semiempirical rate equation was obtained to describe the dissolution process expressed as 1-(1-XCu)1/3=0.0149(CEDP)0.7814 × (Pmalachite)−0.7982×exp(−6.3308/T) ×t