Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment

A wide range of uncertainties will be introduced inevitably during the process of performing a safety assessment of engineering systems. The impact of all these uncertainties must be addressed if the analysis is to serve as a tool in the decision-making process. Uncertainties present in the components (input parameters of model or basic events) of model output are propagated to quantify its impact in the final results. There are several methods available in the literature, namely, method of moments, discrete probability analysis, Monte Carlo simulation, fuzzy arithmetic, and Dempster-Shafer theory. All the methods are different in terms of characterizing at the component level and also in propagating to the system level. All these methods have different desirable and undesirable features, making them more or less useful in different situations. In the probabilistic framework, which is most widely used, probability distribution is used to characterize uncertainty. However, in situations in which one cannot specify (1) parameter values for input distributions, (2) precise probability distributions (shape), and (3) dependencies between input parameters, these methods have limitations and are found to be not effective. In order to address some of these limitations, the article presents uncertainty analysis in the context of level-1 probabilistic safety assessment (PSA) based on a probability bounds (PB) approach. PB analysis combines probability theory and interval arithmetic to produce probability boxes (p-boxes), structures that allow the comprehensive propagation through calculation in a rigorous way. A practical case study is also carried out with the developed code based on the PB approach and compared with the two-phase Monte Carlo simulation results.     

Risks in offshore IT outsourcing: A service provider perspective

Offshore outsourcing of Information Technology (IT) services is the prevalent practice in global businesses today. Despite the strategic advantages and cost benefits that offshore outsourcing offers, outsourcing relationships also involve risks, for both the client, as well as the service provider – a fact that is evidenced by the reported failures of such engagements. Some of the prior researches in this area have focused on identifying various types of client risks and their sources. However, the study of risks from a service provider’s perspective has not received due treatment in literature. This study analyses offshore IT outsourcing risks from the perspective of service providers. A case based approach using the principles of grounded theory was used for studying the risks. Theoretical sampling was used to collect data from 5 mid-tier offshore third party service providers based in Bangalore, India. From our coding and analysis three broad categories of service provider risks emerged, namely, macroeconomic, relationship specific and project specific. Relationship maturity, nature of contract, nature of service or project and nature of client were identified as contextual factors which influence the degree of risk.     

Production knowledge and its impact on the mechanisms of governance

A framework is developed outlining how production knowledge and capabilities influence firm boundaries by impacting the transaction costs of markets and hierarchies. A central implication of the framework is that at lower levels of these capabilities the transaction costs of markets decline at a faster rate than the costs of hierarchy, while at higher levels of these capabilities the transaction costs of hierarchy decline at a faster rate than the costs of markets. The discriminating role of production capabilities arises because markets and hierarchies utilize different types of control (prices and output control versus authority and behavior control), and hence require different levels of knowledge to be efficient. The analysis suggests firms often maintain some production knowledge when contracting for various inputs since it not only reduces transactional hazards in markets, but also because in comparative institutional terms, initial gains in knowledge make markets more efficient than internal organization. In addition, the analysis suggests that there would be a U shaped relationship between the propensity to integrate vertically and the extent of production capabilities as opposed to a monotonically increasing relationship. I find support for the U shaped relationship in a cross sectional sample of 1553 manufacturing firms.     

Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

Class-based storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. The procedures reported in the literature for formation of storage classes primarily consider order-picking cost ignoring storage-space cost. Moreover, in these procedures items are ordered on the basis of their cube per order index (COI), and items are then partitioned into classes maintaining this ordering. This excludes many possible product combinations in forming classes which may result in inferior solutions. In this paper, a simulated annealing algorithm (SAA) is developed to solve an integer programming model for class formation and storage assignment that considers all possible product combinations, storage-space cost and order-picking cost. Computational experience on randomly generated data sets and an industrial case shows that SAA gives superior results than the benchmark dynamic programming algorithm for class formation with COI ordering restriction.     

Clustering of gamma-ray bursts through kernel principal component analysis

We consider the problem related to clustering of gamma-ray bursts (from “BATSE” catalogue) through kernel principal component analysis in which our proposed kernel outperforms results of other competent kernels in terms of clustering accuracy and we obtain three physically interpretable groups of gamma-ray bursts. The effectivity of the suggested kernel in combination with kernel principal component analysis in revealing natural clusters in noisy and nonlinear data while reducing the dimension of the data is also explored in two simulated data sets.     

A general class of non parametric tests for comparing scale parameters

In this paper, a general class of non parametric tests is proposed for the two-sample scale problem. Testing of the scale parameter is very useful in real-life situations commonly faced in engineering, trade, cultivation, industries, medicine, etc. In all these fields, one will prefer the method that gives more consistent results. Thus, it is worthwhile to test the equality of scale parameters. The distribution of the proposed test is established. To assess the performance of the proposed test, the asymptotic efficacies are studied for some underlying distributions and the results are interpreted with useful information. To see the working of the proposed test, an illustrative example for the real-life data set is provided. The simulation study is also carried out to find the asymptotic power of the proposed test. An extension of the general class of tests to the multiple-sample problem is also discussed.     

Addition of runs to an s-level supersaturated design

The purpose of the present work is to extend the work of Gupta et al. (2010) to s  -level column balanced supersaturated designs. Addition of runs to an existing E(χ²)-optimal$E({\chi }^2)\mathrm{-}\mathrm{optimal}$ supersaturated design and to study the optimality of the resulting design is an important issue. This paper considers the study of the optimality of the resulting design. A lower bound to E(χ²)$E({\chi }^2)$ has been obtained for the extended supersaturated designs. Some examples and a small catalogue of E(χ²)-optimal$E({\chi }^2)\mathrm{-}\mathrm{optimal}$ supersaturated designs are also presented.     

Charting the Course: An Overview of Domestic Violence in the South Asian Community in the United States

In the South Asian community in the United States, domestic violence is a prevalent problem of significant magnitude. Although the community stridently denies the existence of this horror, women have been systematically organizing antiviolenceagainst- women work for the last 15 yearsAt this time, it is a vibrant movement struggling with several complex issues that are perhaps less common in thedominant white community. As in the lives of immigrant women of color, much of the intricacies of domestic violencein the South Asian context emerge from the intersections of race, class, andsresidencystatus problems. Consequently, a slew of personal, institutional, and cultural barriers commingle to form roadblocks for battered South Asian women, who attempt to escape family violence. As the needs of battered South Asian first and second generation women enlarge and become more perceptible, the community-based organizations have to ready themselves for more complicated activities in the future.     

Analyzing Social Media Engagement and its Effect on Online Product Purchase Decision Behavior

The continuous progress of society in using online resources has given opportunity to many business executives to utilize social media for their brand promotion or recognition. Organizations utilize social media sites like Twitter, Facebook, LinkedIn, Flicker, Google Plus, and YouTube to promote their product, service, or brand worldwide. Increase of consumer engagement in online social activities has forced companies to integrate social media factors into their marketing strategy. The objective of this study is to find the important factors on which the online purchasing decision depends, based on the personality types of consumers and their attitude toward social media with brand perception.