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Construction projects are well known for their complexity and ambiguity. These projects carry out higher risk than traditional ones because they entail high capital outlays and intricate site conditions. Poor financial management of these projects may lead to bankruptcy; therefore, effective cash flow management is essential. Although the peculiar characteristics of construction projects, the accuracy of cash flow forecasting has been a long lasting problem. The paper aims to discuss these issues.

Many unforeseen factors affect the cash flow forecasting of construction projects. Therefore, the objective of the presented research in this paper is to examine the impact of these factors on contractor's cash flow. A model has been established by integrating analytic hierarchy process and simulation to examine the impact of various factors on cash flow. Data on the selected factors have been collected through questionnaires from various agencies in North America and China.

Results show that the most significant factors are: change of progress payment, payment duration, financial position of the contractor, project delays, and poor planning. It also shows that the effect of cash inflow factors varied approximately from 9.7 to 16.3 percent with a mean value of 12.4 percent.

The implementation of the developed models are limited to few case study projects in testing the models. However, the developed models and framework are sound for future improvement. They are considered as a major step toward a broader cash flow planning.

The developed methodology and models play essential roles in decision-making process.

The developed model is expected to help contractors realistically forecast project cash flow under uncertainty. This may lead to more dependable and professional cash flow management, which might substantially reduce failures in construction business.

Rolling bearings based on rotating machinery are one of the most widely used in industrial applications because of their low cost, high performance and robustness. The purpose of this paper is to describe how to identify degradation condition of rolling bearing and predict its fault time in big data environment in order to achieve zero downtime performance and preventive maintenance for the rolling bearing.

The degradation characteristic parameters of rolling bearings including intrinsic mode energy and failure frequency were, respectively, extracted from the pre-processed original vibration signals using EMD and Hilbert transform. Then, Spearman’s rank correlation coefficient and PCA were used to obtain the health index of the rolling bearing so as to detect the appearance of degradations. Furthermore, the degradation condition of the rolling bearings might be identified through implementing the monotonicity analysis, robustness analysis and degradation analysis of the health index.

The effectiveness of the proposed method is verified by a case study. The result shows that the proposed method can be applied to monitor the degradation condition of the rolling bearings in industrial application.

Further experiment remains to be done so as to validate the effectiveness of the proposed method using Apache Hadoop when massive sensor data are available.

The paper proposes a methodology for rolling bearing condition monitoring representing the steps that need to be followed. Real-time sensor data are utilized to find the degradation characteristics.

The result of the work presented in this paper form the basis for the software development and implementation of condition monitoring system for rolling bearings based on Hadoop.

This study aims to examine whether, in the opinion of patients selected in 13 hospitals of Hubei province, China, hospitals are smoke free. Patients were also asked whether their physicians had inquired about their smoking status.

Patients were recruited through an intercept method (i.e. stopped by the interviewer while in the hospital); data were collected through interviews, with a response rate of 96.1 percent.

Among the intercepted patients, 48.3 percent reported having seen people smoking in hospitals; 22.3 percent had seen a doctor and/or nurse smoking; 23.8 percent had smelled tobacco in hospitals; 68.4 percent reported having seen “no‐smoking” signs in hospital settings; 42.6 percent reported having been asked about smoking status in their latest visit to a doctor and 23.8 percent reported receiving tobacco cessation counseling. Compared to hospitals in large cities, patients from medium/small city hospitals reported significantly higher levels of cigarette smoking among physicians, and poorer implementation of regulations for a smoking‐free hospital, and less smoking cessation counseling by physicians.

Findings of this study point to the need for greater efforts to be made in promoting a smoke free environment in hospitals, as well as encouraging physicians to provide more smoking cessation counseling to smoking patients, particularly physicians in small and medium hospitals.

We extend empirical evidence on the profitability of momentum trading to the realm of plain-equity ETFs.

We employ several ranking measures used in prior research, and for each we apply a traditional ranking based on total return, and a variation based only on the capital gain/loss portion of return.

While we find that past momentum is not a strong predictor of future performance in our overall sample period, 2007 to June 2018, we find that the percent off 52-week high price results in positive performance in the recovery years following the financial crisis of 2008–2009.

Our study is limited by the availability of ETF experience and data, and our test period covers just 2007 through June 2018. This period includes the financial crisis of 2008–2009, which previous research finding is associated with the momentum strategy's loss of profitability. When we exclude that period, we find evidence of a profitable momentum strategy based on the measure of percent off 52-week high price, enabling us to reject the null hypothesis that the momentum trading strategy is no longer profitable.

It is profitable based on both return measures used in the rankings. Our finding of a profitable momentum trading strategy suggests that the null hypothesis that the momentum strategy is no longer profitable can be rejected.

While perhaps not so strong as to reject the efficient markets hypothesis fully, our empirical findings are more consistent with a behavioral explanation and a market inefficiency. In view of the relative ease and low transactional costs of trading in ETFs, the markets have yet another opportunity to recognize an apparent mispricing and employ arbitrage based on it. To the extent that the relative ease of trading in ETFs makes momentum strategies easier to employ, the momentum anomaly might still be expected to disappear in an efficient market.