Relative performance of academic departments using DEA with sensitivity analysis

The process of liberalization and globalization of Indian economy has brought new opportunities and challenges in all areas of human endeavor including education. Educational institutions have to adopt new strategies to make best use of the opportunities and counter the challenges. One of these challenges is how to assess the performance of academic programs based on multiple criteria. Keeping this in view, this paper attempts to evaluate the performance efficiencies of 19 academic departments of IIT Roorkee (India) through data envelopment analysis (DEA) technique. The technique has been used to assess the performance of academic institutions in a number of countries like USA, UK, Australia, etc. But we are using it first time in Indian context to the best of our knowledge. Applying DEA models, we calculate technical, pure technical and scale efficiencies and identify the reference sets for inefficient departments. Input and output projections are also suggested for inefficient departments to reach the frontier. Overall performance, research performance and teaching performance are assessed separately using sensitivity analysis.     

Confidence intervals and tests on the variance ratio in random models with two variance components

The LM test is modified to test any value of the ratio of two variance components in a mixed effects linear model with two variance components. The test is exact, so it can be used to construct exact confidence intervals on this ratio.Exact Neyman-Pearson (NP) tests on the variance ratio are described.Their powers provide attainable upper bounds on powers of tests on the variance ratio.Efficiencies of LM tests, which include ANOVA tests, and NP tests are compared for unbalanced, random, one-way ANOVA models.Confidence intervals corresponding to LM tests and NP tests are described.     

A family of shrinkage estimators for Weibull shape parameter in censored sampling

In this paper a new class of shrinkage estimators has been introduced for the shape parameter in an independently identically distributed two-parameterWeibull model under censored sampling. The main idea is to incorporate the prior guessed value by correcting the standard estimator, which is essentially an unbiased estimator, with optimally weighted ratios of the guessed value and the standard estimator, instead of considering a convex combination of the standard estimator and the difference of the guessed value and the standard estimator. The resulting estimator dominates the standard estimator in a surprisingly large neighborhood of the guessed value. The suggested estimator has also been compared with the minimum mean squared error estimator and a class of estimators suggested by Singh and Shukla in IAPQR Trans 25(2), 107–118, 2000. It is found that the suggested class of estimators has lesser bias as well as lesser mean squared error than its competitors subject to certain conditions.      

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.     

The Detection of Nuclear Materials Losses*

The identification and location of materials losses in nuclear facilities is an important issue. Many complexities arise in monitoring such losses. These complexities include the dependency among materials balance observations and the influence of errors (outliers) on parameter estimates of various monitoring methods. The proposed Joint Estimation procedure is superior to standard methods (control chart and CUSUM) and to methods that build in correlation (ARMA control chart, ARMA CUSUM, and the Generalized M procedure) in the detection of nuclear materials losses. The Joint Estimation procedure is robust to the influence of outliers, is flexible in accommodating a range of dependencies among observations, and provides information on the type of loss. Further, the procedure is reliable in that it yields a probability of false alarms and a probability of detecting losses closer to specifications.     

Sequential estimation of the sum of sinusoidal model parameters

Estimating the parameters of the sum of a sinusoidal model in presence of additive noise is a classical problem. It is well known to be a difficult problem when the two adjacent frequencies are not well separated or when the number of components is very large. In this paper we propose a simple sequential procedure to estimate the unknown frequencies and amplitudes of the sinusoidal signals. It is observed that if there are p components in the signal then at the k  th (k?p)$(k?p)$ stage our procedure produces strongly consistent estimators of the k   dominant sinusoids. For k>p$k>p$, the amplitude estimators converge to zero almost surely. Asymptotic distribution of the proposed estimators is also established and it is observed that it coincides with the asymptotic distribution of the least squares estimators. Numerical simulations are performed to observe the performance of the proposed estimators for different sample sizes and for different models. One ECG data and one synthesized data are analyzed for illustrative purpose.     

Provincializing europe: towards a post-colonial reconstruction: a critique of baconian science as the last stand of imperialism

This article treats Europe's claim to universality as its problematic, and contends that any serious attempt to reorganize the past and/or the future must subvert the European appropriation of the universal. Noting that the justification for Europe's ‘confiscation’ of the universal is often grounded in the argument that only Europe has succeeded in inventing an epistemological tool (namely, Baconian science) that successfully opens the doors to Truth, the article seeks to further its project of provincializing Europe by demonstrating the inadequacy of Euro-science as humanity's chosen vehicle to Truth. This the article does by developing the thesis that violence is encoded in the very fabric of modern science. Following a broadly Gandhian perspective, therefore, the article rejects science's epistemological pretensions. Such rejection of Euro-science, the article points out, leads also to a denial of Europe's presumed universality. Finally, the paper offers some preliminary thoughts on a post-science reorganization of knowledge-creative practices.     

A comparison of model selection criteria

There has been significant new work published recently on the subject of model selection. Notably Rissanen (1986, 1987, 1988) has introduced new criteria based on the notion of stochastic complexity and Hurvich and Tsai(1989) have introduced a bias corrected version of Akaike's information criterion. In this paper, a Monte Carlo study is conducted to evaluate the relative performance of these new model selection criteria against the commonly used alternatives. In addition, we compare the performance of all the criteria in a number of situations not considered in earlier studies: robustness to distributional assumptions, collinearity among regressors, and non-stationarity in a time series. The evaluation is based on the number of times the correct model is chosen and the out of sample prediction error. The results of this study suggest that Rissanen's criteria are sensitive to the assumptions and choices that need to made in their application, and so are sometimes unreliable. While many of the criteria often perform satisfactorily, across experiments the Schwartz Bayesian Information Criterion (and the related Bayesian Estimation Criterion of Geweke-Meese) seem to consistently outperfom the other alternatives considered.     

Construction and validation of Rejection Sensitive Expectation,Perception, and Reaction Questionnaire—Partner (RSEPR-P)

The Rejection Sensitive Expectation, Perception, and Reaction Questionnaire—Partner (RSEPR-P) was developed to assess rejection expectation, perception of rejection, and reactions to perceived rejection among intimate partners. This article details the construction and validation procedures, including item pool generation, factor analysis, and the estimation of reliability and validity. The researchers examined the psychometric properties of RSEPR-P in a community sample of 151 participants. Confirmatory factor analysis (CFA) with the final 24 items suggested four-factor loading with each subscale loading on a separate factor. The subscales had good to excellent internal consistency. In support of the convergent validity, RSEPR-P exhibited robust correlations with rejection sensitivity-personal, mindfulness, marital adjustment, and self-esteem measures. A 6-month test–retest reliability was established. RSEPR-P is proposed to have potential therapeutic and research utility.