Fast On-Line/Off-Line Algorithms for Optimal Reinforcement of a Network and its Connections with Principal Partition

The problem of computing the strength and performing optimal reinforcement for an edge-weighted graph G(V, E, w) is well-studied. In this paper, we present fast (sequential linear time and parallel logarithmic time) on-line algorithms for optimally reinforcing the graph when the reinforcement material is available continuously on-line. These are the first on-line algorithms for this problem. We invest O(|V|³|E|log|V|) time (equivalent to (|V|) invocations of the fastest known algorithms for optimal reinforcement) in preprocessing the graph before the start of our algorithms. It is shown that the output of our on-line algorithms is as good as that of the off-line algorithms. Thus our algorithms are better than the fastest off-line algorithms in situations when a sequence of more than (|V|) reinforcement problems need to be solved. The key idea is to make use of ideas underlying the theory of Principal Partition of a Graph. Our ideas are easily generalized to the general setting of polymatroid functions. We also present a new efficient algorithm for computation of the Principal Sequence of a graph.     

Scheduling to minimize stringer utilization for continuous annealing operations

In this paper we present a mathematical program and heuristic algorithms to schedule coils for the production operations in a copper (or steel) coil manufacturing industry. The processing facility uses continuous operations for processing (e.g., galvanizing and annealing) while the handling unit is a discrete coil. The ends of coils are “stitched” or welded together to enable continuous processing, and the joint is later sheared off to obtain the processed coils. Processing constraints impose restrictions on the compatibility between a pair of coils that are overcome by introducing a dummy coil called stringer, which is very expensive to a mill. This paper deals with modeling the sequencing/scheduling problem of coils on parallel non-identical machines to minimize stringer utilization. Both computational and practical experiences show the efficiency and effectiveness of the solution approaches. Implementing these methods in an actual coil annealing facility resulted in 65% reduction in stringer utilization.     

Differential Susceptibility to Parenting in Adolescent Girls: Moderation by Neural Sensitivity to Social Cues

This research examined whether heightened neural activation to social cues confers adjustment advantages in supportive social contexts but adjustment disadvantages in stressful social contexts. Forty‐five adolescent girls were exposed to social exclusion during an fMRI scan and reported on parent–child relationship quality and depressive symptoms. Stressful parent–child relationships predicted subsequent depressive symptoms in girls with high and moderate but not low dorsal anterior cingulate cortex, subgenual anterior cingulate cortex, and anterior insula activation during exclusion. In the context of supportive parent–child relationships, however, neural activation to exclusion predicted particularly low levels of depressive symptoms. This support for a biological sensitivity to context model suggests the possibility of redirecting adolescent girls’ neural sensitivity to social cues toward more positive adaptation.     

Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies

Abstract

In this contribution, we aim to prioritise the indicators to enhance the organisational supply chain’s (SC) effectiveness from an industrial perspective. It will help industries to develop strategies for managing the SC effectively and ensuring improvement in performance continuously. To achieve this, this work proposes to use a two-phase research methodology. First, 36 SC performance improvement indicators are recognised from a literature survey and from field and industrial expert’s inputs. Secondly, a structural model is proposed using the fuzzy analytical hierarchy process (AHP) to prioritise the indicators strategically to improve the SC performance. The fuzzy AHP method helps determine the priority of concerns of the identified indicators under fuzzy surroundings. Inputs in this research are taken from four ancillary Indian plastic manufacturing firms. Research findings indicate that collaborations and information exchange dimension indicators obtained the highest priority in improving SC performance. The model proposed is considered very useful for the SC managers/practitioners/decision-makers to understand better and distinguish the essential SC performance improvement indicators and to take systematic decisions specifically to improve the performance of business in a SC context. Sensitivity analysis was conducted to examine the priority ranking of the indicators.     

Inferential statistics on the dynamic system model with time-dependent failure-rate

This study focuses on the classical and Bayesian analysis of a k-components load-sharing parallel system in which components have time-dependent failure rates. In the classical set up, the maximum likelihood estimates of the load-share parameters with their standard errors (SEs) are obtained. (1?γ) 100% simultaneous and two bootstrap confidence intervals for the parameters and system reliability and hazard functions have been constructed. Further, on recognizing the fact that life-testing experiments are very time consuming, the parameters involved in the failure time distribution of the system are expected to follow some random variations. Therefore, Bayes estimates along with their posterior SEs of the parameters and system reliability and hazard functions are obtained by assuming gamma and Jeffrey's priors of the unknown parameters. Markov chain Monte Carlo technique such as Gibbs sampler has been used to obtain Bayes estimates and highest posterior density credible intervals.     

Modelling critical success factors for sustainability initiatives in supply chains in Indian context using Grey-DEMATEL

Sustainability assists organisations to enhance ecological, financial and societal performances of their entire supply chains. The present paper uncovers the Critical Success Factors (CSFs) for effective adoption of sustainability initiatives in the supply chain in Indian context. Fifteen CSFs for the successful adoption of sustainability initiatives were identified and finalised firstly from the literature and followed by expert inputs. A methodology based on Grey-Decision Making Trial and Evaluation Laboratory (DEMATEL) was used to envisage the organisation of complex causal relationships between the recognised CSFs. ‘Government Legalisation’ has been found to be the most influential factor and ‘Community Welfare and Development’ is most easily influenced factor. A multiple case example of three automotive companies operating in India is conducted. To the end, some important policy measures and recommendations are proposed to help practicing managers and government bodies to adopt and effectively manage the concepts of sustainability oriented supply chains in India.     

The Indian Diaspora in Africa: The Commodification of Hindu Rashtra

A new approach to India’s diaspora has taken place within the wider context of the adoption, in 1991, of a neoliberal economic policy framework. In recent years, Indian private business enterprises have led the way in Africa and this has had an important impact on the state’s conceptualization of the diaspora. New Delhi’s elites actively seek to embrace an objectified ‘globalization’ as a means to benefit powerful externally oriented fractions and the diaspora’s value is measured in its contribution to this project. There has been a determined attempt to commodify the diaspora to serve particular Indian economic interests. However, the current government’s Hindu chauvinism makes the very question of what constitutes a genuine Indian rather narrow. Two factors thus dominate current policy: commodification and categorization. The diaspora in South Africa is discussed as an example where these dynamics can be acutely observed.     

Maternal Antecedents to Adolescent Girls’ Neural Regulation of Emotion

The purpose of this study was to investigate contributions of maternal emotional resources to individual differences in adolescents’ functional connectivity during emotion regulation. Participants included 35 adolescent girls who completed an implicit emotion regulation task during fMRI. Mothers reported on the quality of their adult attachment and emotional awareness when youth were in elementary school. Higher anxious attachment and lower emotional awareness were significantly correlated with more positive amygdala–right ventrolateral prefrontal cortex connectivity, a pattern linked in prior research with ineffective emotion regulation and emotional difficulties. Further, there was an indirect effect of anxious attachment on adolescent connectivity through emotional awareness. These results suggest that compromised maternal emotional resources in childhood may be linked to atypical neural processing of emotions.     

Minimum Risk Estimation of Scalar Means under Convex Combination of Loss Functions

We derive the minimum risk estimates of the scalar means for Normal, Exponential, and Gamma distributions, under the convex combination of SEL and LINEX loss functions. The functional forms of the proposed estimates for the three examples are general in nature, and for the boundary conditions provide us with the corresponding estimates under SEL and LINEX loss, respectively. We authenticate our proposed models using different iterative as well as meta-heuristic techniques, and through extensive simulation as well as application of live data sets, validate the efficacy of our proposed results.     

Estimation for the Multiple Regression Setup Using Balanced Loss Function

Consider the estimation problem for the multiple linear regression (MLR) setup, under the balanced loss function (BLF), where goodness of fit and precision of estimation are modeled using either squared error loss (SEL) or linear exponential (LINEX) loss functions. The authors derive the minimum risk estimates for two different variants of BLF and prove for both the cases the existence of the ubiquitous SEL and LINEX estimates at the boundary conditions. Conclusions draw from the exhaustive simulation runs prove the general nature of proposed theorems.