On reliable computation by noisy random Boolean formulas

We study noisy computation in randomly generated k-ary Boolean formulas. We establish bounds on the noise level above which the results of computation by random formulas are not reliable. This bound is saturated by formulas constructed from a single majority-like gate. We show that these gates can be used to compute any Boolean function reliably below the noise bound.

Project risk management:a combined analytic hierarchy process and decision tree approach

Time, cost and quality achievements on large-scale construction projects are uncertain because of technological constraints, involvement of many stakeholders, long durations, large capital requirements and improper scope definitions. Projects that are exposed to such an uncertain environment can effectively be managed with the application of risk management throughout the project life cycle. Risk is by nature subjective. However, managing risk subjectively poses the danger of non-achievement of project goals. Moreover, risk analysis of the overall project also poses the danger of developing inappropriate responses. This article demonstrates a quantitative approach to construction risk management through an analytic hierarchy process (AHP) and decision tree analysis. The entire project is classified to form a few work packages. With the involvement of project stakeholders, risky work packages are identified. As all the risk factors are identified, their effects are quantified by determining probability (using AHP) and severity (guess estimate). Various alternative responses are generated, listing the cost implications of mitigating the quantified risks. The expected monetary values are derived for each alternative in a decision tree framework and subsequent probability analysis helps to make the right decision in managing risks. In this article, the entire methodology is explained by using a case application of a cross-country petroleum pipeline project in India. The case study demonstrates the project management effectiveness of using AHP and DTA.

Relocation:a more complete picture

The idea that relocation can cause detriment in the lives of individuals is now relatively accepted in the management community, however much less attention has been devoted to studying the benefits of relocation. We present a more balanced picture by examining both positive and negative consequences of geographical transience in a sample of frequent movers. In total, 29 employees without families, 33 employees with families, 33 spouses, and 15 children participated in interviews for this research (N = 110). The research outlines 160 relocation consequences, including 53 positive outcomes not previously considered. Our findings confirm that relocation can bring about short- and long-term benefits for individuals including task performance, skill development, learning, growth, job satisfaction, continued development, attractive job assignments, career advancement and increased responsibility. In conclusion, findings suggest that, at least in terms of relocation, a more complete picture is actually also a more positive picture. So, whilst organisations should continue to aim to reduce or eliminate the negative consequences of relocation, they should also seek to maintain or enhance the positive outcomes of transience.

Minimizing unsatisfaction in colourful neighbourhoods

Colouring sparse graphs under various restrictions is a theoretical problem of significant practical relevance. Here we consider the problem of maximizing the number of different colours available at the nodes and their neighbourhoods, given a predetermined number of colours. In the analytical framework of a tree approximation, carried out at both zero and finite temperatures, solutions obtained by population dynamics give rise to estimates of the threshold connectivity for the incomplete to complete transition, which are consistent with those of existing algorithms. The nature of the transition as well as the validity of the tree approximation are investigated.

Project risk management using multiple criteria decision-making technique and decision tree analysis:a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.

Fertigation potential of domestic wastewater for tree plantations

This study analyses feasibility of using domestic wastewater for fertigation of tree crops. Wastewater samples from different sources in domestic sector were analyzed and evaluated in terms of water quality and quantity. Water is rich in plant nutrients. However, due to possible presence of toxic ions and microbial load, it is recommended that direct use of wastewater for fertigation be limited to timber plantation and energy generation from biomass.