Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

Game Theory Based Sensor Management in Reducing Target Threat Level Assessment Risk

Sensor management schemes are calculated to reduce target threat level assessment risk in this paper.Hidden Markov model and risk theory are combined to build the target threat level model firstly.Then the target threat level estimation risk is defined.And the sensor management schemes are optimized with the smallest target threat level assessment risk.What’s more,the game theory is applied to calculate the optimal sensor management scheme.Some simulations are conducted to prove that the proposed sensor management method is effective.

Who Drives Environmental Governance of Enterprise:Official Tenure Evaluation or Five-Year Plan Target Assessment?

Based on the non-financial listed enterprises data from 2000 to 2014,this paper calculates the level of environmental governances of enterprises with environmental investment,and empirically analyzes the impact of provincial official tenure and Five-Year Plan target assessment on the environmental governance of enterprises.The results show that the enterprise environmental investment presents a significant periodic trend in the Five-Year Plan,while the trend is not significant in official’s tenure.The further test suggests that with the clear requirement of“environmental performance”incorporated into the performance evaluation system of local government officials,it has become significant in the periodic trend in the impact of officials’tenure on environmental investment.In contrast,the trend has become less prominent in the Five-Year Plan,which indicates that there is a substitute relation between the two evaluation systems.The mechanism test also finds that both environmental subsidies and pollution abatement expenditures present a significantly periodic trend in the Five-Year Plan.And official’s tenure plays a regulatory role in the Five-Year Plan periodic trend in the environmental governance of enterprise,showing that it is more significant when the time about officials’tenure evaluation is earlier than Five-Year Plan target assessment.The above results indicate that it is beneficial to improve local environment governance from the perspective of top institutional design by both strengthening the environmental evaluation.

Resource prediction and assessment based on 3D/4D big data modeling and deep integration in key ore districts of North China

The North China district has been subjected to significant research with regard to the ore-forming dynamics,processes,and quantitative forecasting of gold deposits;it accounts for the highest number of gold reserves and annual products in China.Based on the top-level design of geoscience theory and the method adopted by the National Key R&D Project(deep process and metallogenic mechanism of North China Craton(NCC)metallogenic system),this paper systematically collects and constructs the geoscience data(district,camp,and deposit scales)in four key gold districts of North China(Jiaojia-Sanshandao,Southern Zhaoping,Wulong,and Qingchengzi).The settings associated with the geological dynamics of gold deposits were quantitatively and synthetically analyzed,namely:NCC destruction,metallogenic events,genetic models,and exploration models.Three-dimensional(3D)and four-dimensional(4D)geological modeling was performed using the big data on the districts,while the district-scale 3D exploration criteria were integrated to construct a quantitative exploration model.Among them,FLAC3D modelling and the Geo Cube software(version 3.0)were used to implement the numerical simulation of the 3D geological models and the constraints of the fluid saturation parameters of the Jiaojia fault to reconstruct the 4D fault structure models of the Jiaojia fault(with a depth of 5000 m).Using Geo Cube3.0,multiple integration modules(general weights of evidence(Wof E),Boost Wof E,Fuzzy Wof E,Logistic Regression,Information Entropy,and Random Forest)and exploration criteria were integrated,while the C-V fractal classification of A,B and C targets in four districts was carried out.The research results are summarized in the following four areas:(1)Four gold districts in the study area have more than three targets(the depth is 3000 m),and the class A,B and C targets exhibit a good spatial correlation with gold bodies that are controlled by mining engineering at depths greater than 1000 m.(2)The Boost Wof E method was used to identify the target optimization in 3D spaces(at depths of 3000–5000 m)of the Jiaojia-Sanshandao,Southern Zhaoping,and Wulong districts.(3)The general Wof E method is based on the Bayesian theory in 3D space and provides robust integration and target optimization that are suitable for the Jiaojia-Sanshandao and Southern Zhaoping districts in the Jiaodong area;it can also be applied to the Wulong district in the Liaodong area using a quantitative genetic model and an exploration model.Random forest is a multi-objective integration and target optimization method for 3D spaces,and it is suitable for the complex exploration model in the Qingchengzi district of the Liaodong area.The genetic model and exploration criteria associated with the exploration model of the Qingchengzi district were constrained by the common characteristics of the gold fault structure,magmatic rock emplacement in North China,and the strata fold and interlayer detachment structure.(4)Based on the gold reserves and the 3D block unit model of the Sanshandao gold deposit in the Jiaojia-Sanshandao district,the gold contents of the 3D block units in class A and B targets of the ore concentration were estimated to be 65.5%and 25.1%,respectively.The total Au resources of the optimized targets below a depth of 3000 m were 3908 t(including 1700 t reserves),and the total Au resources of the targets at depths from 3000 to 5000 m were 936 t.The study shows that the deep gold deposits in the four gold districts of North China exhibit a strong"transport-deposition"spatial correlation with potential targets.These"transport-deposition"spatial models represent the tectonic-magmatic-hydrothermal activities of the metallogenic system associated with the NCC destruction events and indicate the Au enrichment zones.

Evaluation of bacterial pathogen diversity,abundance and health risks in urban recreational water by amplicon next-generation sequencing and quantitative PCR

The microbial quality of urban recreational water is of great concern to public health.The monitoring of indicator organisms and several pathogens alone is not sufficient to accurately and comprehensively identify microbial risks.To assess the levels of bacterial pathogens and health risks in urban recreational water,we analyzed pathogen diversity and quantified four pathogens in 46 water samples collected from waterbodies in Beijing Olympic Forest Park in one year.The pathogen diversity revealed by 16 S r RNA gene targeted next-generation sequencing（NGS） showed that 16 of 40 genera and 13 of 76 reference species were present.The most abundant species were Acinetobacter johnsonii,Mycobacterium avium and Aeromonas spp.Quantitative polymerase chain reaction（q PCR） of Escherichia coli（uid A）,Aeromonas（aer A）,M.avium（16S r RNA）,Pseudomonas aeruginosa（oaa） and Salmonella（inv A） showed that the aer A genes were the most abundant,occurring in all samples with concentrations of 10^（4–6） genome copies/100 m L,followed by oaa,inv A and M.avium.In total,34.8% of the samples harbored all genes,indicating the prevalence of these pathogens in this recreational waterbody.Based on the q PCR results,a quantitative microbial risk assessment（QMRA） showed that the annual infection risks of Salmonella,M.avium and P.aeruginosa in five activities were mostly greater than the U.S.EPA risk limit for recreational contacts,and children playing with water may be exposed to the greatest infection risk.Our findings provide a comprehensive understanding of bacterial pathogen diversity and pathogen abundance in urban recreational water by applying both NGS and q PCR.