Statistical Inference for the Inverted Scale Family under General Progressive Type-II Censoring

Two estimation problems are studied based on the general progressively censored samples, and the distributions from the inverted scale family (ISF) are considered as prospective life distributions. One is the exact interval estimation for the unknown parameter θ , which is achieved by constructing the pivotal quantity. Through Monte Carlo simulations, the average 90 % and 95 % confidence intervals are obtained, and the validity of the above interval estimation is illustrated with a numerical example. The other is the estimation of R = P ( Y < X ) in the case of ISF. The maximum likelihood estimator (MLE) as well as approximate maximum likelihood estimator (AMLE) is obtained, together with the corresponding R-symmetric asymptotic confidence intervals. With Bootstrap methods, we also propose two R-asymmetric confidence intervals, which have a good performance for small samples. Furthermore, assuming the scale parameters follow independent gamma priors, the Bayesian estimator as well as the HPD credible interval of R is thus acquired. Finally, we make an evaluation on the effectiveness of the proposed estimations through Monte Carlo simulations and provide an illustrative example of two real datasets

A hybrid model for stock price prediction based on multi-view heterogeneous data

Abstract Literature shows that both market data and financial media impact stock prices; however, using only one kind of data may lead to information bias. Therefore, this study uses market data and news to investigate their joint impact on stock price trends. However, combining these two types of information is difficult because of their completely different characteristics. This study develops a hybrid model called MVL-SVM for stock price trend prediction by integrating multi-view learning with a support vector machine (SVM). It works by simply inputting heterogeneous multi-view data simultaneously, which may reduce information loss. Compared with the ARIMA and classic SVM models based on single- and multi-view data, our hybrid model shows statistically significant advantages. In the robustness test, our model outperforms the others by at least 10% accuracy when the sliding windows of news and market data are set to 1–5 days, which confirms our model’s effectiveness. Finally, trading strategies based on single stock and investment portfolios are constructed separately, and the simulations show that MVL-SVM has better profitability and risk control performance than the benchmarks

Research on Seepage Control of Jurong Pumped Storage Hydroelectric Power Station

Based on the geological and hydrogeological conditions of the Jurong Pumped Storage Hydroelectric Power Station (JPSHP), a 3D groundwater flow model was developed in the power station area, which took into account the heterogeneity and anisotropy of fractured rocks. A control inversion method for fractured rock structural planes was proposed, where larger-scale fractures were used as water-conducting media and the relatively intact rock matrix was used as water-storage media. A statistical method was used to obtain the geometric parameter values of the structural planes, so as to obtain the hydraulic conductivity tensor of the fractured rocks. Combining the impermeable drainage systems of the upper storage reservoir, underground powerhouse and lower storage reservoir, the 3D groundwater seepage field in the study area was predicted using the calibrated model. The leakage amounts of the upper storage reservoir, powerhouse and lower storage reservoir were 710.48 m3/d, 969.95 m3/d and 1657.55 m3/d, respectively. The leakage changes of the upper storage reservoir, powerhouse and lower storage reservoir were discussed under the partial and full failure of the anti-seepage system. The research results provide a scientific basis for the seepage control of the power station, and it is recommended to strengthen the seepage control of the upper and lower storage reservoirs and the underground powerhouse to avoid excessive leakage and affect the efficiency of the reservoir operation

Synthesis and Antifungal Activity of Novel Triazole Compounds Containing Piperazine Moiety

Design and synthesis of triazole library antifungal agents having piperazine side chains, analogues to fluconazole were documented. The synthesis highlighted utilization of the click chemistry on the basis of the active site of the cytochrome P450 14α-demethylase (CYP51). Their structures were characterized by 1H-NMR, 13C-NMR, MS and IR. The influences of piperazine moiety on in vitro antifungal activities of all the target compounds were evaluated against eight human pathogenic fungi

Synthesis and Antifungal Activity of Novel Triazole Compounds Containing Piperazine Moiety

Design and synthesis of triazole library antifungal agents having piperazine side chains, analogues to fluconazole were documented. The synthesis highlighted utilization of the click chemistry on the basis of the active site of the cytochrome P450 14α-demethylase (CYP51). Their structures were characterized by 1H-NMR, 13C-NMR, MS and IR. The influences of piperazine moiety on in vitro antifungal activities of all the target compounds were evaluated against eight human pathogenic fungi