New multi-layer data correlation algorithm for multi-passive-sensor location system

Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.

Privacy Protection for Big Data Linking using the Identity Correlation Approach

Privacy protection for big data linking is discussed here in relation to the Central Statistics Office （CSO）, Ireland＇s, big data linking project titled the ＇Structure of Earnings Survey - Administrative Data Project＇ （SESADP）. The result of the project was the creation of datasets and statistical outputs for the years 2011 to 2014 to meet Eurostat＇s annual earnings statistics requirements and the Structure of Earnings Survey （SES） Regulation. Record linking across the Census and various public sector datasets enabled the necessary information to be acquired to meet the Eurostat earnings requirements. However, the risk of statistical disclosure （i.e. identifying an individual on the dataset） is high unless privacy and confidentiality safe-guards are built into the data matching process. This paper looks at the three methods of linking records on big datasets employed on the SESADP, and how to anonymise the data to protect the identity of the individuals, where potentially disclosive variables exist.

Determination of Causal Effect in Observational Studies： Analysis of Correlated Data with Binary End-Points

Identifying the causal impact of＇ some intervention challenging when one is faced with correlated binary end-points in observational studies is a challenging task, and it is even more The statistical literature on analyzing such data is well documented. Dependence between observations from the same study subject in correlated data renders invalid the usual chi-square tests of independence and inflates the variance ofparameter estimates. Disaggregated approaches such as hierarchical linear models which are able to adjust for individual level covariate：s are favoured in the analysis of such data, thereby gaining power over aggregated and individual-level analyses. In this article the authors, therefore, address the issue of analyzing correlated data with dichotomous end-points by using hierarchical logistic regression, a generalization of the standard logistic regression model for independent outcomes.

Study on the Monitoring Malfunction of Water Pollution during Drought or Flood Period and Low-carbon and High-value Methodology--A Case Study of the Correlation Test of Water,Soil and Gas Pollution in Xiangxiang County

Based on the low-carbon and high-value methodology of chemical ecology and chemical informatics,combining theory and methods,taking saving,environmental protection,low carbon,high production,high value and circulation as values and aims,the relationship between human and land as a basis,ecosystem as a center,overall control as a goal and agricultural ecological engineering as a mean,environmental pollution detection,as one of bottlenecks for agricultural products and food security,should be solved firstly;through the field survey in dry years from 2009 to 2010 when drought and flood were frequent and the frequency of drought was higher than that of flood,plus the determination of surface water flow and water quantity in a small typical river basin,the correlation of local water,soil and gas in the county could be found,and the transfer of monitoring focus from water environment to atmospheric environment was possible and necessary.The study would promote the quantitative research on the correlation among water,soil and gas,and the results were in accordance with the conclusions of related studies.

Distribution of Traditional Chinese Medicine syndromes in diabetic kidney disease chronic kidney disease 1-5: a correlation study

OBJECTIVE: To analyze the distribution of Traditional Chinese medicine(TCM) syndromes in patients with diabetic kidney disease(DKD) and its related factors.METHODS: We enrolled 435 patients with DKD, who were not undergoing dialysis, admitted to the Department of Nephrology, First Medical Center, Chinese PLA General Hospital from April 2020 to August 2021.Analysis of their TCM syndromes and related factors was carried out.RESULTS: The 435 patients included 109, 117, 86, and 123 chronic kidney disease(CKD) 1-2, CKD3, CKD4, and CKD5 cases, respectively. With the progression of CKD1-5, the proportion of Yin deficiency and dry heat syndrome,and that of Qi and Yin deficiency syndrome showed a downward trend, whereas the proportion of spleen-kidney Yang deficiency, blood deficiency, blood stasis, water stagnation, and phlegm turbidity syndromes showed an upward trend;the differences were statistically significant(P < 0.05). Multivariate logistic regression analysis showed that Yin deficiency and dry heat syndrome was positively correlated with hemoglobin [odds ratio(OR) =1.022, P = 0.005], albumin(OR = 1.058, P = 0.006), and estimated glomerular filtration rate(eGFR)(OR = 1.020,P < 0.001) but negatively correlated with male sex(OR =0.277, P = 0.004). Qi and Yin deficiency syndrome was positively correlated with albumin(OR = 1.056, P < 0.001)and eGFR(OR = 1.008, P = 0.022) but negatively correlated with age(OR = 0.977, P = 0.023). Liver-kidney Yin deficiency syndrome was positively correlated with age(OR = 1.028, P = 0.021) and glycosylated hemoglobin(OR = 1.223, P = 0.007) but negatively correlated with total cholesterol(OR = 0.792, P = 0.006).Spleen-kidney Yang deficiency syndrome was negatively correlated with hemoglobin(OR = 0.977, P < 0.001),albumin(OR = 0.891, P < 0.001), and eGFR(OR = 0.978,P < 0.001) but positively correlated with high density lipoprotein(OR = 3.376, P = 0.001). CONCLUSION: With CKD1-5 progression, TCM syndromes changed from Yin deficiency and dry heat syndrome to syndrome of deficiency of both Qi and Yin, liver-kidney Yin, and spleen-kidney Yang deficiency syndromes. TCM syndromes were correlated with laboratory test results.

Solubility of Paclitaxel in Mixtures of Dichloromethane and Supercritical Carbon Dioxide

Phase behavior of paclitaxel in solvent mixtures of dichloromethane and supercritical carbon dioxide was investigated using a supercritical phase monitor.Cloud point pressures were determined as a function of temperature,pressure and paclitaxel content from 313.1 to 343.1K and pressures up to 33.52 MPa.The ternary mixtures exhibit a typical lower critical solution temperature behavior.When paclitaxel content increases,the single-phase region shrinks in size.Three cubic equations of state(Redlich-Kworng,Soave-Redlich-Kwong and Peng-Robinson equation of state) coupled with the van der Waals one-fluid mixing rules were selected to correlate the experimental data.The results indicate that SRK EOS coupled with two binary interaction parameters kij and lij can predict paclitaxel solubility for the best fit of experimental data.

ADAPTIVE FUSION ALGORITHMS BASED ON WEIGHTED LEAST SQUARE METHOD

Weighted fusion algorithms, which can be applied in the area of multi-sensor data fusion, are advanced based on weighted least square method. A weighted fusion algorithm, in which the relationship between weight coefficients and measurement noise is established, is proposed by giving attention to the correlation of measurement noise. Then a simplified weighted fusion algorithm is deduced on the assumption that measurement noise is uncorrelated. In addition, an algorithm, which can adjust the weight coefficients in the simplified algorithm by making estimations of measurement noise from measurements, is presented. It is proved by emulation and experiment that the precision performance of the multi-sensor system based on these algorithms is better than that of the multi-sensor system based on other algorithms.

Observation and Modeling of Geostationary Orbit Electron Energization Induced by Enhanced Dayside Whistler-Mode Waves

We provide correlated observations of enhanced dayside whistler-mode waves and energetic electron acceleration collected by the CLUSTER and GOES satellites during the 23～24 September 2001 storm. Energetic （〉0.6 MeV） electron fluxes are found to increase significantly during the recovery phase and the main phase, by a factor of～50 higher than the prestorm level. These high electron fluxes occur when strong dayside whistler-mode waves are present. Two-dimensional （2D） numerical simulations are carried out and the results demonstrate that the dayside whistler-mode wave can contribute to such enhancements in electron flux within 24 h, consistent with the observation.

A New Approach for Dispersion Parameters

This paper presents a new approach to identify and estimate the dispersion parameters for bivariate, trivariate and multivariate correlated binary data, not only with scalar value but also with matrix values. For this direction, we present some recent studies indicating the impact of over-dispersion on the univariate data analysis and comparing a new approach with these studies. Following the property of McCullagh and Nelder [1] for identifying dispersion parameter in univariate case, we extended this property to analyze the correlated binary data in higher cases. Finally, we used these estimates to modify the correlated binary data, to decrease its over-dispersion, using the Hunua Ranges data as an ecology problem.

Correlation analysis of combined and separated effects of wing deformation and support system in the CAE-AVM study

The Chinese Aeronautical Establishment（CAE） Aerodynamic Validation Model（AVM）is a dual-purpose test geometry dedicated to verify the aerodynamic performance of a conceptual intercontinental jet aircraft and to provide a dataset for CFD software validation. To this end, a scaled model of the AVM was tested in the High-Speed Tunnel（HST） of the German-Dutch Wind-tunnels（DNW） with special test consideration and instrumentation. For complementary analysis of experimental results, specific CAE-AVM geometries are analyzed using a CAE inhouse CFD code. The specific geometries consist of a baseline aircraft, an aircraft with a deformed wing shape, and an aircraft with both a deformed wing shape and a representation of the model support system used in the wind tunnel. Detailed analysis of numerical and experimental results is presented; both the combined and individual attributions of wing deformation and support system interference on wing pressure distributions and longitudinal aerodynamic characteristics are summarized.

Correlation analysis between characteristics under gastroscope and image information of tongue in patients with chronic gastritis

OBJECTIVE:To explore the correlation between diagnostic information of tongue and gastroscopy results of patients with chronic gastritis.METHODS:Frequent pattern growth(FP-Growth),SPSS Modeler was used to analyze the correlation rules between the image information of tongue parameters and the characteristics of the stomach and duodenum seen under gastroscopy.RESULTS:Ranking in order of confidence:cyanotic tongue,slippery fur,yellow fur and spotted tongue were sequently associated with both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.L,one value of tongue coating color,which counted among(30,60),tooth-marked tongue and b,one value of tongue coating color,which counted in the range of(5,20)were sequently associated with gastric antrum mucosal erythema/macula.A,one value of tongue body color,which counted in the range of(0,20),was related to both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.a,one value of tongue coating color,which counted in the range of(15,35),was associated with gastric antrum mucosal erythema/macula.There are a total of 9 strong correlation rules.CONCLUSIONS:Cyanotic tongue,slippery fur,yellow fur,the CIE Lab value of tongue coating,a,the value of tongue body color,spotted tongue,and tooth-marked tongue are all related to the gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.The conditions of gastric mucosa could be predicted by the examination of the above related image information of tongue.

Shrinkage estimation analysis of correlated binary data with a diverging number of parameters

For analyzing correlated binary data with high-dimensional covariates,we,in this paper,propose a two-stage shrinkage approach.First,we construct a weighted least-squares(WLS) type function using a special weighting scheme on the non-conservative vector field of the generalized estimating equations(GEE) model.Second,we define a penalized WLS in the spirit of the adaptive LASSO for simultaneous variable selection and parameter estimation.The proposed procedure enjoys the oracle properties in high-dimensional framework where the number of parameters grows to infinity with the number of clusters.Moreover,we prove the consistency of the sandwich formula of the covariance matrix even when the working correlation matrix is misspecified.For the selection of tuning parameter,we develop a consistent penalized quadratic form(PQF) function criterion.The performance of the proposed method is assessed through a comparison with the existing methods and through an application to a crossover trial in a pain relief study.

A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments

A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle(PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.