Selective Maintenance in System Reliability with Random Costs of Repairing and Replacing the Components

In this paper we consider the problem of determining the optimum number of repairable and replaceable components to maximize a system's reliability when both, the cost of repairing the components and the cost of replacement of components by new ones, are random. We formulate it as a problem of non-linear stochastic programming. The solution is obtained through Chance Constrained programming. We also consider the problem of finding the optimal maintenance cost for a given reliability requirement of the system. The solution is then obtained by using Modified E-model. A numerical example is solved for both the formulations.     

Trends in Alcohol Consumption Among Undergraduate Students at a Northeastern Public University, 2002–2008

Abstract

Objective: This study examined alcohol consumption patterns and trends at a public university in the Northeast from 2002 to 2008. Participants: Stratified random sampling was used to select undergraduate students enrolled in courses during spring semesters in 2002, 2004, 2006, and 2008. Methods: Data were collected during regularly scheduled classes for 4 measures of alcohol consumption and 5 demographic categories using the Core Alcohol and Drug Survey. Results: Four groups showed significant increases in both frequency and volume of alcohol consumption—students who were female, over 21 years of age or over, living off-campus, or performing well academically. There were no decreasing trends for any demographic group. These results differ from national college health surveys, which have shown alcohol use remaining steady during this period. Conclusions: Campus-specific trend data can provide unique perspectives and guide programming efforts. These trends suggest a need for new intervention strategies on this campus.     

Optimized estimation for population mean using conventional and non-conventional measures under the joint influence of measurement error and non-response

Most of the research work in the theory of survey sampling only deals with the sampling errors under the assumptions: (i) there is a complete response and (ii) recorded information from individuals is correct but in practice it is not always true. Non-sampling errors like non-response and measurement errors (MEs) mostly creep into the survey and become more influential for estimators than sampling errors. Considering this practical situation of non-response and MEs jointly, we proposed an optimum class of estimators for population mean under simple random sampling using conventional and non-conventional measures. Bias and mean square error of the proposed estimators are derived up to first degree of approximation. Moreover, a simulation study is conducted to assess the performance of new estimators which proves that proposed estimators are more efficient than the traditional Hansen and Hurwitz estimator and other competing estimators.     

Compromise allocation in multivariate stratified surveys with stochastic quadratic cost function

In many real life situations the linear cost function does not approximate the actual cost incurred adequately. The cost of traveling between the units selected in the sample within a stratum is significant, instead of linear cost function. In this paper, we have considered the problem of finding a compromise allocation for a multivariate stratified sample survey with a significant travel cost within strata is formulated as a problem of non-linear stochastic programming with multiple objective functions. The compromise solutions are obtained through Chebyshev approximation technique, D ₁- distance and goal programming. A numerical example is presented to illustrate the computational details of the proposed methods.     

An integrated environmental risk assessment framework for coal-fired power plants: A fuzzy logic approach

This study quantifies the environmental risk of a coal-fired thermal power plant during operation by using environmental monitoring data, site surveys, and documented evidence. The following criteria are assessed: emissions (CO, SO₂, NO_x, PM₁₀), impact on aquatic ecosystem (fish protection at cooling water intake and cooling water discharge temperature), and waste management (fly ash and bottom ash). Fuzzy sets were defined for each criterion, taking environmental regulatory context as an expert judgment. A survey was conducted with multiple stakeholders to determine the relative importance of risk factors. The survey results showed that the most concerned risks are SO₂ and NO_x emissions. The proposed method estimates the risk of each environmental criterion separately and then accumulates them into an environmental risk index (ERI). Accordingly, we assessed the Catalagzi coal-fired power plant, which has been in operation on the Black Sea coast in northwestern Turkey. For this case study, the ERI resulted in a value of 0.78 (on a scale of 0–1), showing high environmental risk to the facility. Moreover, the applicability of the proposed framework was tested in several existing coal-fired power plants using simultaneous measurements. All studied coal-fired power plants in Turkey have unacceptable pollutants (PM₁₀, SO₂, and NO_x) concentration levels indicating high health risk potential. The application of the integrated environmental risk assessment framework showed that new environmental regulations are needed in Turkey to specify more strict emission limits and to monitor CO₂, fine particulate matter emissions, cooling water discharge, and fish protection at cooling water intake.     

Risk analysis of fast spreading species in a Kashmir Himalayan National Park (Dachigam) for better monitoring and management

Huge economic costs and ecological impacts of invasive alien species (IAS) in the protected areas (PAs) worldwide make their timely prediction and potential risk assessment of central importance for effective management. While the preborder weed risk assessment framework has been extensively evaluated and implemented, the postborder species risk assessment framework has not been subjected to the same degree of scrutiny. Here we used a rather more realistic modified version of the Australian Weed Risk framework (AWRM) for Dachigam National Park (DNP) in Kashmir Himalaya against 84 plant species, including 55 alien species and 29 fast spreading native species, for risk analysis. We found two very high-risk species, three high-risk species, 10 medium-risk species, 29 low-risk species, and 40 negligible-risk species in the DNP. The containment scores accordingly ranged from 14.4 to 293.5 comprising of 27 species that can be contained with very high feasibility, 23 species with high feasibility, 14 species with medium feasibility, and 12 species which cannot be contained easily thereby having low feasibility of containment (FOC) score. However, eight species which have a negligible FOC score are difficult to contain within their infestation sites. Our results demonstrate the merit of the AWRM with a caution that the necessary region-specific modifications may help in its better implementation. Overall, these results provide quite a promising tool in the hands of protected area managers to timely and effectively deal with the problem of plant invasions.     

Demand shocks and employment adjustments: Does employment protection legislation create rigidity?

With state‐level panel data from the Indian manufacturing sector for 2000–12, and labour turnover as a proxy for employment adjustments, the authors estimate differential effects of demand shocks on employment adjustment across states with high and low levels of EPL. They find that EPL does not hinder employment adjustment; the response of labour separation rates to negative demand shocks is relatively higher in states with high levels of EPL, and labour turnover is inversely associated with EPL, which may be viewed as indicative of the beneficial effects of EPL for both enterprises and workers.     

Inflation targeting and the exchange rate: Does it matter in Turkey?

This paper investigates the monetary policy reaction functions of the Central Bank of Republic of Turkey (CBRT) over the periods 1987:01–2001:12 and 2002:01–2009:05. We specifically attempt to shed light on question to what extent exchange rate developments still continue to influence monetary policy, even under inflation targeting. This study seeks to investigate how the monetary policy responded to the exchange rate shocks before and after adoption of inflation targeting regime. How large the effect of exchange rate shocks is accounted for in forecast error variances decompositions for monetary policy as compared to other shocks? Using the VAR model, this study shows that there has been strong pass-through during whole period. Moreover, in the postcrisis period, exchange rate has been the main reaction variable for the CBRT.     

Fertility trends in Pakistan--the decline that wasn't

The own-child method of fertility estimation was applied to data from 4 successive household surveys in Pakistan--the 1973 Housing, Economic, and Demographic Survey; the 1975 Pakistan Fertility Survey; the 1979 Population, Labor Force, and Migration Survey; and the 1981 Census. Results suggest large fertility oscillations 8-15 years before each survey, a sharp decline during the next 6 years, and a slight upturn in the year preceding the survey. However, when the 4 data sources are analyzed together, it becomes clear that the reported fertility declines are spurious. In fact, the results indicate that Pakistan's total fertility rate actually increased in the 2 decades preceding the 1981 Census, from slightly under to slightly above 7 children/women. This pattern is apparent when fertility data are aggregated over calendar years, allowing the tendency for errors from age misreporting to cancel one another out. Whatever fertility decline may have occurred has been confined to the very small group of Pakistan women with more than a primary education. It appears that births were misplaced away from the survey date, because of a pattern of exaggerations of children's ages that increases with age, thereby underestimating fertility in the 5-year period just before the survey. This analysis points to the value of juxtaposition of trends from multiple data sources. It further suggests a need for serious attention to family planning program performance in Pakistan if the Government's goal of achieving a birth rate of 36/1000 by 1988 is to be achieved.     

Exploring the co-movements between COVID-19 pandemic and international air traffic: A global perspective based on wavelet analysis

The travel and tourism industry was one of the fastest-growing industries before the onset of the COVID-19 pandemic. However, to avoid COVID-19 spread, the government authorities imposed strict lockdown and international border restrictions except for some emergency international flights that badly hit the travel and tourism industry. The study explores the nexus between international air departures and the COVID-19 pandemic in this strain. We use a novel wavelet coherence approach to dissect the lead and lag relationships between international flight departures and COVID-19 deaths from January 2020 to September 2020 (COVID-19 first wave period). The results reveal that international flights cause the spread of COVID-19 spread during May 2020 to June 2020 worldwide. The overall findings suggest asymmetries between daily international flight departures and COVID-19 deaths globally at different time-frequency periods due to uncertainty surrounding the COVID-19 pandemic. The study will be conducive for the policymakers to control the upsurge of COVID-19 spread worldwide.