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.

Performance modelling and analysis of multiple coexisting IEEE 802.15.4 wireless sensor networks

With the features of low-power and flexible networking capabilities IEEE 802.15.4 has been widely regarded as one strong candidate of communication technologies for wireless sensor networks (WSNs). It is expected that with an increasing number of deployments of 802.15.4 based WSNs, multiple WSNs could coexist with full or partial overlap in residential or enterprise areas. As WSNs are usually deployed without coordination, the communication could meet significant degradation with the 802.15.4 channel access scheme, which has a large impact on system performance. In this thesis we are motivated to investigate the effectiveness of 802.15.4 networks supporting WSN applications with various environments, especially when hidden terminals are presented due to the uncoordinated coexistence problem. Both analytical models and system level simulators are developed to analyse the performance of the random access scheme specified by IEEE 802.15.4 medium access control (MAC) standard for several network scenarios. The first part of the thesis investigates the effectiveness of single 802.15.4 network supporting WSN applications. A Markov chain based analytic model is applied to model the MAC behaviour of IEEE 802.15.4 standard and a discrete event simulator is also developed to analyse the performance and verify the proposed analytical model. It is observed that 802.15.4 networks could sufficiently support most WSN applications with its various functionalities. After the investigation of single network, the uncoordinated coexistence problem of multiple 802.15.4 networks deployed with communication range fully or partially overlapped are investigated in the next part of the thesis. Both nonsleep and sleep modes are investigated with different channel conditions by analytic and simulation methods to obtain the comprehensive performance evaluation. It is found that the uncoordinated coexistence problem can significantly degrade the performance of 802.15.4 networks, which is unlikely to satisfy the QoS requirements for many WSN applications. The proposed analytic model is validated by simulations which could be used to obtain the optimal parameter setting before WSNs deployments to eliminate the interference risks.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

Analysis of single and multiple, non-permanent, tunable, birefringent spectral holes in a fibre-Bragg grating stop-band produced via uniaxial pressure

We present an experimental and numerical study of transversely loaded uniform fibre-Bragg gratings. A novel loading configuration is described, producing pressure-induced spectral holes in an initially strong uniform grating. The birefringence properties of these gratings are analysed. It is shown that the frequency splitting of the two spectral holes, corresponding to two orthogonal polarisation states, can be adjusted precisely using this loading configuration. We finally demonstrate a new and simple scheme to induce multiple spectral holes in the stop-band. © 2003 Elsevier Science B.V. All rights reserved.

Conclusion : on multiple levels of analysis, context, contingency and capital

In this concluding chapter, we bring together the threads and reflections on the chapters contained in this text and show how they relate to multi-level issues. The book has focused on the world of Human Resource Management (HRM) and the systems and practices it must put in place to foster innovation. Many of the contributions argue that in order to bring innovation about, organisations have to think carefully about the way in which they will integrate what is, in practice, organisationally relevant — but socially distributed — knowledge. They need to build a series of knowledge-intensive activities and networks, both within their own boundaries and across other important external inter-relationships. In so doing, they help to co-ordinate important information structures. They have, in effect, to find ways of enabling people to collaborate with each other at lower cost, by reducing both the costs of their co-ordination and the levels of unproductive search activity. They have to engineer these behaviours by reducing the risks for people that might be associated with incorrect ideas and help individuals, teams and business units to advance incomplete ideas that are so often difficult to codify. In short, a range of intangible assets must flow more rapidly throughout the organisation and an appropriate balance must be found between the rewards and incentives associated with creativity, novelty and innovation, versus the risks that innovation may also bring.

Time, Cost, and Environmental Impact Analysis for Sustainable Design at Multiple Building Levels

Construction projects are complex endeavors that require the involvement of different professional disciplines in order to meet various project objectives that are often conflicting. The level of complexity and the multi-objective nature of construction projects lend themselves to collaborative design and construction such as integrated project delivery (IPD), in which relevant disciplines work together during project conception, design and construction. Traditionally, the main objectives of construction projects have been to build in the least amount of time with the lowest cost possible, thus the inherent and well-established relationship between cost and time has been the focus of many studies. The importance of being able to effectively model relationships among multiple objectives in building construction has been emphasized in a wide range of research. In general, the trade-off relationship between time and cost is well understood and there is ample research on the subject. However, despite sustainable building designs, relationships between time and environmental impact, as well as cost and environmental impact, have not been fully investigated. The objectives of this research were mainly to analyze and identify relationships of time, cost, and environmental impact, in terms of CO2 emissions, at different levels of a building: material level, component level, and building level, at the pre-use phase, including manufacturing and construction, and the relationships of life cycle cost and life cycle CO2 emissions at the usage phase. Additionally, this research aimed to develop a robust simulation-based multi-objective decision-support tool, called SimulEICon, which took construction data uncertainty into account, and was capable of incorporating life cycle assessment information to the decision-making process. The findings of this research supported the trade-off relationship between time and cost at different building levels. Moreover, the time and CO2 emissions relationship presented trade-off behavior at the pre-use phase. The results of the relationship between cost and CO2 emissions were interestingly proportional at the pre-use phase. The same pattern continually presented after the construction to the usage phase. Understanding the relationships between those objectives is a key in successfully planning and designing environmentally sustainable construction projects.

Analysis of multiple cracking in metal/ceramic composites with lamellar microstructure

Financial support of this research by The Royal Society, UK (IE121116), The Carnegie Trust for the Universities of Scotland, UK (Trust Reference 31747) and DFG (PI 785/3-2, PI 785/1-2), Germany, is gratefully acknowledged. We thank Dr. S. Roy (KIT) for providing the microstructure images and Professor I. Tsukrov (University of New Hampshire, USA) for helpful discussions.

Ambient vibration tests and analysis of a multiple-span elevated bridge

Peer reviewed

DC fault performance and cost analysis of DC grids for connecting multiple offshore wind farms

ACKNOWLEDGMENT We are thankful to RTE for financial support of this project.

Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design

Marine protected areas (MPAs) are commonly employed to protect ecosystems from threats like overfishing. Ideally, MPA design should incorporate movement data from multiple target species to ensure sufficient habitat is protected. We used long-term acoustic telemetry and network analysis to determine the fine-scale space use of five shark and one turtle species at a remote atoll in the Seychelles, Indian Ocean, and evaluate the efficacy of a proposed MPA. Results revealed strong, species-specific habitat use in both sharks and turtles, with corresponding variation in MPA use. Defining the MPA's boundary from the edge of the reef flat at low tide instead of the beach at high tide (the current best in Seychelles) significantly increased the MPA's coverage of predator movements by an average of 34%. Informed by these results, the larger MPA was adopted by the Seychelles government, demonstrating how telemetry data can improve shark spatial conservation by affecting policy directly.

Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design

Marine protected areas (MPAs) are commonly employed to protect ecosystems from threats like overfishing. Ideally, MPA design should incorporate movement data from multiple target species to ensure sufficient habitat is protected. We used long-term acoustic telemetry and network analysis to determine the fine-scale space use of five shark and one turtle species at a remote atoll in the Seychelles, Indian Ocean, and evaluate the efficacy of a proposed MPA. Results revealed strong, species-specific habitat use in both sharks and turtles, with corresponding variation in MPA use. Defining the MPA's boundary from the edge of the reef flat at low tide instead of the beach at high tide (the current best in Seychelles) significantly increased the MPA's coverage of predator movements by an average of 34%. Informed by these results, the larger MPA was adopted by the Seychelles government, demonstrating how telemetry data can improve shark spatial conservation by affecting policy directly.

Gene mapping and expression analysis of 16q loss of heterozygosity identifies WWOX and CYLD as being important in determining clinical outcome in multiple myeloma.

We performed fluorescent in situ hybridization (FISH) for 16q23 abnormalities in 861 patients with newly diagnosed multiple myeloma and identified deletion of 16q [del(16q)] in 19.5%. In 467 cases in which demographic and survival data were available, del(16q) was associated with a worse overall survival (OS). It was an independent prognostic marker and conferred additional adverse survival impact in cases with the known poor-risk cytogenetic factors t(4;14) and del(17p). Gene expression profiling and gene mapping using 500K single-nucleotide polymorphism (SNP) mapping arrays revealed loss of heterozygosity (LOH) involving 3 regions: the whole of 16q, a region centered on 16q12 (the location of CYLD), and a region centered on 16q23 (the location of the WW domain-containing oxidoreductase gene WWOX). CYLD is a negative regulator of the NF-kappaB pathway, and cases with low expression of CYLD were used to define a "low-CYLD signature." Cases with 16q LOH or t(14;16) had significantly reduced WWOX expression. WWOX, the site of the translocation breakpoint in t(14;16) cases, is a known tumor suppressor gene involved in apoptosis, and we were able to generate a "low-WWOX signature" defined by WWOX expression. These 2 genes and their corresponding pathways provide an important insight into the potential mechanisms by which 16q LOH confers poor prognosis.

Heteroduplex PCR analysis of rearranged immunoglobulin genes for clonality assessment in multiple myeloma.

BACKGROUND AND OBJECTIVE: Molecular analysis by PCR of monoclonally rearranged immunoglobulin (Ig) genes can be used for diagnosis in B-cell lymphoproliferative disorders (LPD), as well as for monitoring minimal residual disease (MRD) after treatment. This technique has the risk of false-positive results due to the "background" amplification of similar rearrangements derived from polyclonal B-cells. This problem can be resolved in advance by additional analyses that discern between polyclonal and monoclonal PCR products, such as the heteroduplex analysis. A second problem is that PCR frequently fails to amplify the junction regions, mainly due to somatic mutations frequently present in mature (post-follicular) B-cell lymphoproliferations. The use of additional targets (e.g. Ig light chain genes) can avoid this problem. DESIGN AND METHODS: We studied the specificity of heteroduplex PCR analysis of several Ig junction regions to detect monoclonal products in samples from 84 MM patients and 24 patients with B cell polyclonal disorders. RESULTS: Using two distinct VH consensus primers (FR3 and FR2) in combination with one JH primer, 79% of the MM displayed monoclonal products. The percentage of positive cases was increased by amplification of the Vlamda-Jlamda junction regions or kappa(de) rearrangements, using two or five pairs of consensus primers, respectively. After including these targets in the heteroduplex PCR analysis, 93% of MM cases displayed monoclonal products. None of the polyclonal samples analyzed resulted in monoclonal products. Dilution experiments showed that monoclonal rearrangements could be detected with a sensitivity of at least 10(-2) in a background with >30% polyclonal B-cells, the sensitivity increasing up to 10(-3) when the polyclonal background was

Joint Analysis of Multiple Algorithms and Performance Measures

There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.