A low complexity semidefinite relaxation for large-scale MIMO detection

Many wireless communication problems is based on a convex relaxation of the maximum likelihood problem which further can be cast as binary quadratic programs (BQPs). The two standard relaxation methods that are widely used for solving general BQPs such as spectral methods and semidefinite programming problem (SDP), each have their own advantages and disadvantages. It is widely accepted that small and medium sized SDP problems can be solved efficiently by interior point methods. Albeit, semidefinite relaxation has a tighter bound for large scale problems, but its computational complexity is high. However, Row-by-Row method (RBR) for solving SDPs could be opted for an alternative for large-scale MIMO detection because of low complexity. The present work is a spectral SDP-cut formulation to which the RBR is applied for large-scale MIMO detection. A modified RBR algorithm with tighter bound is presented to specify the efficiency in detecting massive MIMO.     

Post-randomization for controlling identification risk in releasing microdata from general surveys

Before releasing survey data, statistical agencies usually perturb the original data to keep each survey unit''s information confidential. One significant concern in releasing survey microdata is identity disclosure, which occurs when an intruder correctly identifies the records of a survey unit by matching the values of some key (or pseudo-identifying) variables. We examine a recently developed post-randomization method for a strict control of identification risks in releasing survey microdata. While that procedure well preserves the observed frequencies and hence statistical estimates in case of simple random sampling, we show that in general surveys, it may induce considerable bias in commonly used survey-weighted estimators. We propose a modified procedure that better preserves weighted estimates. The procedure is illustrated and empirically assessed with an application to a publicly available US Census Bureau data set.     

Changes in Diarrheal Disease and Treatment Among Brazilian Children from 1986 to 1996

We examined changes in diarrhea prevalence and treatment in Brazil between 1986 and 1996. Over this 10-year period there was a small decline in diarrhea prevalence but treatment with oral rehydration therapy (ORT) increased greatly. Deaths due to dehydration were thus averted, although the costly burden of morbidity remained high. The decline in diarrhea prevalence was largely due to changes in the effects of several key covariates, such as breastfeeding, with only a modest role played by socioeconomic change, infrastructure improvements, and other behavioral factors. ORT treatment of diarrhea was essentially unrelated to child and family characteristics, suggesting that the large increase was due to the success of public health efforts to promote its use widely. Our results suggest that the most effective policies for reducing diarrhea prevalence are likely to be further increases in education and the promotion of breastfeeding. Persistent disparities in diarrhea prevalence mean that policies to prevent the disease should be targeted at disadvantaged socioeconomic groups.     

The importance of international demographic research for the United States

International demographic research hasprovided many benefits for the U.S. This paperidentifies five main reasons for these benefits. First, cross-national research provides unique policyinsights that help the U.S. to develop more effectiveprograms and policies to address pressing andpersistent domestic challenges. Second, it helps theU.S. to understand and address problems and issues inmany countries or regions of the world that are ofparticular relevance to the U.S. because of theirstrategic or commercial importance to us. Third, ithelps the U.S. to address problems and issues that areglobal in nature and require international policyresponses. Fourth, it helps the U.S. to providehumanitarian aid to poor countries more effectivelyand efficiently. Finally, it contributes to theadvancement of science, which in turn stimulates andenriches research focusing on the U.S.     

An integrated lean and green approach for improving sustainability performance: a case study of a packaging manufacturing SME in the U.K.

Abstract

Competitive landscape, informed consumers and stringent regulations have forced many manufacturing small- and medium-sized enterprises (SMEs) to focus on operational efficiency along with sustainability issues in recent years. While many manufacturing organisations have been taking lean initiatives for the past few years for operational excellence, an impulsive rush to adopt lean without a strategic deployment vision has led to scattered implementation of lean tools and projects without desired success. Many researchers and practitioners prescribe value stream mapping as a foundation for lean transformation initiatives; however, little empirical work is available on the symbiosis of lean and green paradigms to reap maximum benefits. This research, through a systematic methodology and a novel tool called Green Integrated Value Stream Mapping (GIVSM), integrates both paradigms in a case study on a U.K. packaging-manufacturing SME. Applying the GIVSM demonstrates that simultaneous deployment of lean and green paradigms have synergistic effect for improving both operational efficiency and environmental performance. In addition, continuous improvement framework with sustainable procurement is proposed to overcome the lean-green misalignments. This study also provides a guiding reference for practitioners to undertake similar improvement projects and identifies opportunities to expand this academic research on integrated lean-green approach into other industry sectors.     

A Generalized Poisson Distribution

Cumulative probabilities of a Poisson distribution can be written in terms of incomplete gamma function where the parameter of the gamma function is an integer. From this definition a new generalization of the Poisson distribution is obtained with two parameters. Asymptotic behavior of this distribution is shown to be normal. Some order properties of this distribution are also studied.     

Large Sample Theory for the Bounds on the Gini and Related Indices of Inequality Estimated From Grouped Data

The joint asymptotic distribution of the upper and lower bounds for the Gini index derived by Gastwirth for grouped data are obtained. From them a conservative asymptotically distribution-free confidence interval for the population Gini index is presented. The methods also yield similar results for other indices of inequality (e.g., Theil's and Atkinson's).     

Least squares estimation of the coefficients of a partially explosive model,with polynomial regressions of same degree,generating a pair of related time series

This paper is concerned with a partially explosive linear model with polynomial regression components generating a pair of related time series. The least squares estimates of the coefficients are shown to be √N-consistent and asymptotically singular normal, when the degrees of polynomial regression components are same, thus generalising a result due to Venkataraman (1974).     

Diabetes mellitus in Native Americans: The problem and its implications

Since World War II, diabetes has become one of the most common serious diseases among Native Americans. Rates of diabetes and its complications, which include premature death, renal failure, and limb amputation, are substantially higher among Native Americans than among the US general population, and the frequency of diabetes among Native Americans is increasing. Several potentially modifiable factors, including obesity, dietary composition, and physical inactivity, are thought to be contributing to these high rates. The potential benefit from prevention of diabetes is considerable, and a population-based approach may be the most effective way of achieving sustainable lifestyle changes among Native Americans. Estimation of the social and economic costs of diabetes and assessment of the marginal costs and benefits of various diabetes control measures can support resource allocation decisions aimed at improving the health of Native American people.