Mathematical modelling to improve Rolled Throughput Yield in a supply chain

The outspread of supply chains competition entails inevitable application of quality improvement methods, such as Six Sigma. It is less than a decade that Six Sigma methodology has entered the supply chain scope; however, researches undertaken in this field have massively increased. Most of these research works have been done towards the application of the Six Sigma method for supply chain improvement, yet nothing has been done about suitable entity selection in supply chain for improvement. The purpose of this article is to propose a method for individual entity selection in the supply chain. Accordingly, a mixed integer non-linear programming model is presented that shows which supply chain entity should be selected, and how much to improve, in order to maximise financial benefit. This article also presents new comprehensive criteria based on the previous approach, which can measure the performance of the supply chain. Moreover, the ability of the proposed criteria is shown through a numerical example. Finally, the optimisation model was applied for selecting individual entity in tweedy supply chain in order to illustrate the capability of the model. In addition, sensitivity analysis is carried out on the parameters of the model.     

Comparing different propensity score estimation methods for estimating the marginal causal effect through standardization to propensity scores

Hernan and Robins proposed a method for calculating marginal causal effect of treatment using standardization to propensity scores.

?Data adaptive methods have been suggested as alternatives to logistic regression for the estimation of propensity scores. We examined the performance of various data mining methods using simulated data. The estimators' performance was evaluated in terms of relative bias, 95% CI coverage rate, and mean squared error.

?All methods (except CART and GBM) displayed generally acceptable performance. However, under the conditions of moderate non-additivity and moderate nonlinearity, ANN and SL outperformed logistic regression with better bias reduction and more consistent 95% CI coverage.     

Urban Growth and Housing Quality in Iran

Rapid urban population growth and the lack of effective policies in order to desired population settlement, has encountered Iran’s major cities with multiple social, economic and environment problems. Physical expansion of cities in order to settlement the increasing population, causes the formation of new textures surrounding old urban textures. In the new textures, urban housing is formed with the modern approach and least logical connection with common practice in the old textures. Therefore, the main objective of this paper is to evaluate the housing quality and identify strengths and weaknesses in old and new urban textures to improve the quality of urban housing in Iran. Household survey were conducted to collect the needed data in the old and new textures in Khorramabad city. Results showed that the satisfaction level of housing quality in new texture is far more than old ones. The highest satisfaction level in both textures are related to housing basic facilities domain. However, satisfaction level of this domain in new texture is much greater compared to the old texture. The lowest level of satisfaction is related to the quality of neighborhood domain in old texture and to the access to public services domain in the new one. Results from the factor analysis to identify the dimensions of housing quality in old and new textures illustrated that housing quality is a multidimensional concept, studying of which requires considering all dimensions and aspects.     

A new method for generating distributions with an application to exponential distribution

A new method has been proposed to introduce an extra parameter to a family of distributions for more flexibility. A special case has been considered in detail, namely one-parameter exponential distribution. Various properties of the proposed distribution, including explicit expressions for the moments, quantiles, mode, moment-generating function, mean residual lifetime, stochastic orders, order statistics, and expression of the entropies, are derived. The maximum likelihood estimators of unknown parameters cannot be obtained in explicit forms, and they have to be obtained by solving non linear equations only. Further, we consider an extension of the two-parameter exponential distribution also, mainly for data analysis purposes. Two datasets have been analyzed to show how the proposed models work in practice.     

Why Do Neighbors Have Different Environmental Priorities? Analysis of Environmental Risk Perception in a Beirut Neighborhood

Differences in environmental priorities within an urban neighborhood of Beirut are analyzed. The explanatory capabilities of five categories of contextual variables are compared: socioeconomic status, locality, health, behavior, and environmental beliefs. Semi-structured interviews with key individuals in the community and residents were first conducted. Four environmental issues of concern were identified. A survey was carried out to identify the relative priority accorded by respondents to these four issues, and to measure variables likely to explain differences of opinion. Bivariate and multivariate logistic regression analyses were conducted for each of the four problems. The 99% confidence interval (CI) of the odds ratio (OR) was used as a test of significance. Respondents suffering from a respiratory disease (OR = 6.94, 99%CI = 1.54-31.25), those living in less crowded houses (OR = 4.88, 99%CI = 1.38-17.24), and those not living close to the neighborhood's industrial street (OR=5.26, 99%CI = 1.01-27.78) are significantly more likely to rank poor air quality first. Significant associations are found between poor water quality as first priority and nonpresence of a smoker in the household (OR = 6.12, 99%CI = 1.84-20.32) and perception of water salinity as a problem (OR = 7.46, 99%CI = 1.50-37.03). Males (OR = 6.94, 99%CI = 1.02-47.62) and tenants versus owners (OR = 10.49, 99%CI = 1.36-80.61) are significantly more likely to rank the residential-industrial mix first. Socioeconomic variables retain their explanatory capability in the studied neighborhood, despite relatively small income disparities. Behavioral variables, such as smoking, may be causative factors of priorities. Analyzing relative priorities, rather than "concern" or lack of it, reveals more complex patterns of association. Identifying environmental-perception divide lines can help develop a more inclusive and effective participatory environmental management.     

The “Trojan Horse” Plot and the Fear of Muslim Power in British State Schools

In 2014, an alleged “Trojan Horse” plot to Islamise education in a number of schools attended predominantly by diverse Muslim pupils in the inner city wards of Birmingham raised considerable questions. Ofsted investigations of 21 schools explored these concerns at the behest of the then Secretary of State for Education, Michael Gove MP. At the head of this so-called plot, a certain Tahir Alam, once a darling of New Labour’s policies on British Muslim schools, faced the brunt of the media and political furore. Based on a series of face-to-face interviews with Alam in 2015 and 2016, this paper provides a detailed insight into the allegations, the context in which they emerged and the implications raised for young Muslims in the education system. Ultimately, as part of the government’s counter-terrorism policy the accusations of the “Islamisation” of education in these “Trojan Horse” schools foreshadowed the additional securitisation of all sectors of education. However, there was neither the evidence nor the legal justification to ratchet up anti-extremism education measures that eventually followed; namely the Counter-Terrorism and Security Act 2015. The consequences of the negative attention heightened existing Islamophobia but, paradoxically, they also limited the opportunities for de-radicalisation through education.     

Linking Food Security with Household’s Adaptive Capacity and Drought Risk: Implications for Sustainable Rural Development

In spite of green revolution and rapid economic growth, India’s vast population still suffers from hunger and poverty, especially in the rural areas. Moreover, drought adversely affects India’s economy by declining agricultural production and purchasing power. It also escalates rural unemployment which ultimately affects household food security. Our study investigated the food security of drought prone rural households in a broader context by linking the dimensions of food security with dimensions of climate change vulnerability. We used the primary data of 157 drought prone rural households of Odisha state in India for analysis. This study employed polychoric principal component analysis to construct an aggregate food security index. An ordered probit model was used to estimate the determinants of food security. The FSI showed that three-fourth of the respondents were facing food security issues with varying degrees. The estimates of ordered probit model indicated that joint family, education, migration and health insurance are key variables that determine food security, whereas drought adversely affected food security of rural households. Overarching strategies are required to effectively address food security issues in the wake of increased drought risk. This study provides an insight for policy makers in India and in similar south Asian countries who must consider food security in the light of drought.

     

Qualitative inquiry into women's menopause experiences in southeastern Iran

Menopause is defined as amenorrhea for one year. Signs and symptoms are categorized as physical and psychological changes, including depression, hot flushes and ageing. Woman's responses to menopause are governed by lifestyle factors. The purpose of this study was to determine how Iranian women experience menopause and hormone therapy. A qualitative inquiry was conducted through semistructured, in-depth interviews to explore study questions in 11 menopausal women. Participants had positive and negative menopause experiences. Negative menopause experiences are due to severity of symptoms. Menopause can be facilitated by increasing women's knowledge about this phase and ways to cope with it.