CROSSING TEHRAN AVENUE

The online city magazine TehranAvenue.com (TA) occupies the transnational crossroad of digital and urban space. It thus provides an important case study of how urban studies, postcolonial theory and critical cyber studies can be combined fruitfully to explain the potentialities and limits of digital and social networks in transnational Middle Eastern contexts. The article explores metaphors of the Internet as city, theories of transnational urban space and recent studies of the Internet and its politico-cultural uses in Iran to establish a theoretical method that can explain the simultaneity of local and transnational in digital and urban spaces. Qualitative data (email and telephone interviews with TA's founder, editor and contributors), combined with content analysis of the site, supports the claim that the city as metaphor and metonym can account for the intersection between contemporary North African and Middle Eastern digital spaces and national and diasporic urban spaces. The digital city – or blogabad – expands physical urban space into transnational networks. But there are important limits to the transnational reach of mediated social networking practices. In fact, the located identifications of web users are often much more important than the global reach of the technologies they use.     

A solution to an open problem on lower against number in graphs

In Wang (Appl Anal Discret Math 4:207–218, 2010) the problem of finding a sharp lower bound on lower against number of a general graph is mentioned as an open question. We solve the problem by establishing a tight lower bound on lower against number of a general graph in terms of order and maximum degree.     

Monitoring Multi-Attribute Processes Based on NORTA Inverse Transformed Vectors

Although multivariate statistical process control has been receiving a well-deserved attention in the literature, little work has been done to deal with multi-attribute processes. While by the NORTA algorithm one can generate an arbitrary multi-dimensional random vector by transforming a multi-dimensional standard normal vector, in this article, using inverse transformation method, we initially transform a multi-attribute random vector so that the marginal probability distributions associated with the transformed random variables are approximately normal. Then, we estimate the covariance matrix of the transformed vector via simulation. Finally, we apply the well-known T ² control chart to the transformed vector. We use some simulation experiments to illustrate the proposed method and to compare its performance with that of the deleted-Y method. The results show that the proposed method works better than the deleted-Y method in terms of the out-of-control average run length criterion.     

Three New Multivariate Process Capability Indices

Different multivariate process capability indices are developed by researchers to evaluate process capability when vectors of quality characteristics are considered in a study. This article presents three indices referred to as NCpM, MCpM, and NMC _PM in order to evaluate process capability in multivariate environment. The performance of the proposed indices is investigated numerically. Simulation results indicate that the proposed indices have descended estimation error and improved performance compared to the existing ones. These results can be important to researchers and practitioners who are interested in evaluating process capability in multivariate domain.     

Process Capability Analysis in Non Normal Linear Regression Profiles

When the distribution of a process characterized by a profile is non normal, process capability analysis using normal assumption often leads to erroneous interpretations of the process performance. Profile monitoring is a relatively new set of techniques in quality control that is used in situations where the state of product or process is represented by a function of two or more quality characteristics. Such profiles can be modeled using linear or nonlinear regression models. In some applications, it is assumed that the quality characteristics follow a normal distribution; however, in certain applications this assumption may fail to hold and may yield misleading results. In this article, we consider process capability analysis of non normal linear profiles. We investigate and compare five methods to estimate non normal process capability index (PCI) in profiles. In three of the methods, an estimation of the cumulative distribution function (cdf) of the process is required to analyze process capability in profiles. In order to estimate cdf of the process, we use a Burr XII distribution as well as empirical distributions. However, the resulted PCI with estimating cdf of the process is sometimes far from its true value. So, here we apply artificial neural network with supervised learning which allows the estimation of PCIs in profiles without the need to estimate cdf of the process. Box-Cox transformation technique is also developed to deal with non normal situations. Finally, a comparison study is performed through the simulation of Gamma, Weibull, Lognormal, Beta and student-t data.     

Family Change and Continuity in Iran: Birth Control Use Before First Pregnancy

Using data from the 2002 Iran Fertility Transition Survey, we examined birth control use between marriage and first pregnancy. We focused on the post‐1990 increase in birth control use and develop two explanations. The first posits that birth control use reflects a new marriage form, the conjugal marriage, which places a heightened value on the spousal relationship while deemphasizing the centrality of parenthood. A second explanation stresses the use of a new resource, effective birth control, within an Iranian‐Islamist view of marriage. Key to this explanation is the role of the state—Iranian political/religious actors encourage early marriage and the use of birth control. Although the explanations could be complementary, evidence provides more support for the latter.     

IRANIAN WOMEN AND FOOTBALL

The paper examines football as a site of social contestation for Iranian women. The recent political controversy regarding women's attendance at football matches is indicative of this social conflict. I start by contextualizing this episode within a feminist framework of analysis. I then look at the development of Iranian women's participation in football as rioters, fans, players, referees, coaches, sports-writers and administrators of the game. Examples of women footballers from other cultures are provided in order to foreground commonalities and differences. Finally, I demonstrate how this movement is catalysng both Iranian feminism and the wider working-class social movement confronting the mullah-bourgeoisie.     

Geodesic Lagrangian Monte Carlo over the space of positive definite matrices: with application to Bayesian spectral density estimation

We present geodesic Lagrangian Monte Carlo, an extension of Hamiltonian Monte Carlo for sampling from posterior distributions defined on general Riemannian manifolds. We apply this new algorithm to Bayesian inference on symmetric or Hermitian positive definite (PD) matrices. To do so, we exploit the Riemannian structure induced by Cartan's canonical metric. The geodesics that correspond to this metric are available in closed-form and – within the context of Lagrangian Monte Carlo – provide a principled way to travel around the space of PD matrices. Our method improves Bayesian inference on such matrices by allowing for a broad range of priors, so we are not limited to conjugate priors only. In the context of spectral density estimation, we use the (non-conjugate) complex reference prior as an example modelling option made available by the algorithm. Results based on simulated and real-world multivariate time series are presented in this context, and future directions are outlined.