Prediction of Spot Price of Iron Ore Based on PSR-WA-LSSVM Combined Model

Aiming at the problems that the existing single time series models are not accurate and robust enough when it comes to forecasting the iron ore prices and the parameters of the traditional LSSVM model are difficult to determine, we propose a combined model based on Phase Space Reconstruction (PSR), wavelet transform and LSSVM (PSR-WA-LSSVM) to tackle these issues. ARIMA model, LSTM model, PSR-LSSVM model, and PSR-WA-LSSVM models were used for contrast simulation to forecast the spot price data of 61.5%PB powder from January 30, 2019, to February 1, 2021, in Ningbo Zhoushan port. The experimental results show that the PSR-WA-LSSVM combination model achieves better prediction results. At the same time, the model has a good performance in the multistep prediction of the iron ore price

Bayesian Estimation of Small Proportions Using Binomial Group Test

Group testing has long been considered as a safe and sensible relative to one-at-a-time testing in applications where the prevalence rate p is small. In this thesis, we applied Bayes approach to estimate p using Beta-type prior distribution. First, we showed two Bayes estimators of p from prior on p derived from two different loss functions. Second, we presented two more Bayes estimators of p from prior on π according to two loss functions. We also displayed credible and HPD interval for p. In addition, we did intensive numerical studies. All results showed that the Bayes estimator was preferred over the usual maximum likelihood estimator (MLE) for small p. We also presented the optimal β for different p, m, and k

Effect of Zhen-wu decoction on chronic heart failure in rats

Purpose: To investigate the effect of Zhen-wu decoction (ZWD) on oxidative stress and hemodynamics in chronic congestive heart failure (CHF) rats.Methods: After Sprague Dawley (SD) rats were successfully prepared into CHF, they were randomly divided into normal control group, model (untreated CHF) group,  captopril group, high-dose, middledose and low-dose of ZWD groups, and were  treated with drugs for 4 weeks respectively. At the end of the experiment,  hemodynamic function, whole heart weight index, blood creatinine kinase (CK), superoxide dismutase (SOD), malondialdehyde (MDA), nitric oxide (NO) and nitric oxide synthase (NOS) were determined.Results: Compared with normal control group, ZWD group showed decreased arterial systolic pressure (SBP, 89.16 ± 17.27 mmHg), diastolic pressure (DBP, 72.54 ± 22.36 mmHg), mean arterial pressure (MAP, 72.64 ± 11.87 mmHg), heart rate (HR, 368.25 ± 39.12 beats/min), left ventricular systolic peak (LVSP, 105.27 ± 15.23 mmHg), and left ventricular pressure change rate (dp/dt max) (p < 0.05), while left ventricular end diastolic pressure (LVEDP) (19.52 ± 1.89 mmHg), whole heart weight index (2.74 ± 0.16 mg/g), blood CK (0.98 ± 0.16 U/mL), MDA (17.28 ± 2.94 nmol/mL), NO (36.35 ± 3.27 umol/L), NOS (39.89 ± 3.56 U/mL) significantly  increased (p < 0.05). High dose of ZWD significantly improved hemodynamic  function, lowered MDA (8.85 ± 2.14 nmol/mL) and NO (24.25 ± 3.21 umol/L) levels (p < 0.05), and also decreased CK (0.58 ± 0.37 U/mL) and NOS (26.12 ± 3.87 U/mL) in CHF rats (p < 0.05).Conclusion: ZWD improves adriamycin-induced chronic congestive heart failure in rats significantly, and therefore has potential to be developed for the management of chronic congestive heart failure.Keywords: Zhen-wu decoction, Chronic heart failure, Hemodynamic function,  Oxidative stres

Identification of Extreme Temperature Fluctuation in Blast Furnace Based on Fractal Time Series Analysis

In this study, we aim to estimate the density distribution for the return intervals of extreme temperature fluctuation in blast furnace during iron making process. We first identified the fractal feature of the data based on R/S analysis and also calculated the Hurst coefficient. Secondly, based on the fractal feature of the data, we estimated a stretched exponential distribution of the return intervals of extreme temperature fluctuation. Finally, in order to test the result, we applied this method to the data of two blast furnaces, and compared with the traditional kernel density estimation method. The comparison was based on 100,000 times K-S test. The comparison results showed that the fractal time series estimation provides a greater fitness than traditional estimation method since it has no rejection in K-S test. With this method, the density of return intervals of unexpected temperature fluctuation can be estimated. This can be applied as a tool of temperature control and also can be applied as a tool to evaluate the efficiency of the control system

The impacts of service quality and customer satisfaction in the e-commerce context

This paper aims to investigate the impacts of service quality on customer satisfaction and loyalty in the e-commerce context, in particular from a triad view of customer-e-retailer-3PL (third party logistics) provider. A literature review is primarily used to determine the conceptual model and to develop the measurement scales. Data were collected through online questionnaire survey conducted in China. Structural equation modeling was used to analyze the collected data and test the proposed research hypotheses. The results indicate that both e-service quality and logistics service quality are strongly linked with customer satisfaction. The research results shown that practitioners (e-retailers) should not only focus on e-service quality, but also the logistics service quality. This research validates the proposed service quality framework with two dimensions (e-service quality and logistics service quality) in e-commerce context. Second, it highlights the impact path of service quality on customer satisfaction and loyalty