Forecasting time-varying value-at-risk

In this thesis we are interested in financial risk and the instrument we want to use is Value-at-Risk (VaR). VaR is the maximum loss over a given period of time at a given confidence level. Many definitions of VaR exist and some will be introduced throughout this thesis. There two main ways to measure risk and VaR: through volatility and through percentiles. Large volatility in financial returns implies greater probability of large losses, but also larger probability of large profits. Percentiles describe tail behaviour. The estimation of VaR is a complex task. It is important to know the main characteristics of financial data to choose the best model. The existing literature is very wide, maybe controversial, but helpful in drawing a picture of the problem. It is commonly recognised that financial data are characterised by heavy tails, time-varying volatility, asymmetric response to bad and good news, and skewness. Ignoring any of these features can lead to underestimating VaR with a possible ultimate consequence being the default of the protagonist (firm, bank or investor). In recent years, skewness has attracted special attention. An open problem is the detection and modelling of time-varying skewness. Is skewness constant or there is some significant variability which in turn can affect the estimation of VaR? This thesis aims to answer this question and to open the way to a new approach to model simultaneously time-varying volatility (conditional variance) and skewness. The new tools are modifications of the Generalised Lambda Distributions (GLDs). They are four-parameter distributions, which allow the first four moments to be modelled nearly independently: in particular we are interested in what we will call para-moments, i.e., mean, variance, skewness and kurtosis. The GLDs will be used in two different ways. Firstly, semi-parametrically, we consider a moving window to estimate the parameters and calculate the percentiles of the GLDs. Secondly, parametrically, we attempt to extend the GLDs to include time-varying dependence in the parameters. We used the local linear regression to estimate semi-parametrically conditional mean and conditional variance. The method is not efficient enough to capture all the dependence structure in the three indices —ASX 200, S&P 500 and FT 30—, however it provides an idea of the DGP underlying the process and helps choosing a good technique to model the data. We find that GLDs suggest that moments up to the fourth order do not always exist, there existence appears to vary over time. This is a very important finding, considering that past papers (see for example Bali et al., 2008; Hashmi and Tay, 2007; Lanne and Pentti, 2007) modelled time-varying skewness, implicitly assuming the existence of the third moment. However, the GLDs suggest that mean, variance, skewness and in general the conditional distribution vary over time, as already suggested by the existing literature. The GLDs give good results in estimating VaR on three real indices, ASX 200, S&P 500 and FT 30, with results very similar to the results provided by historical simulation.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Axisymmetric shell structures for multi-use

Shell structures find use in many fields of engineering, notably structural, mechanical, aerospace and nuclear-reactor disciplines. Axisymmetric shell structures are used as dome type of roofs, hyperbolic cooling towers, silos for storage of grain, oil and industrial chemicals and water tanks. Despite their thin walls, strength is derived due to the curvature. The generally high strength-to-weight ratio of the shell form, combined with its inherent stiffness, has formed the basis of this vast application. With the advent in computation technology, the finite element method and optimisation techniques, structural engineers have extremely versatile tools for the optimum design of such structures. Optimisation of shell structures can result not only in improved designs, but also in a large saving of material. The finite element method being a general numerical procedure that could be used to treat any shell problem to any desired degree of accuracy, requires several runs in order to obtain a complete picture of the effect of one parameter on the shell structure. This redesign I re-analysis cycle has been achieved via structural optimisation in the present research, and MSC/NASTRAN (a commercially available finite element code) has been used in this context for volume optimisation of axisymmetric shell structures under axisymmetric and non-axisymmetric loading conditions. The parametric study of different axisymmetric shell structures has revealed that the hyperbolic shape is the most economical solution of shells of revolution. To establish this, axisymmetric loading; self-weight and hydrostatic pressure, and non-axisymmetric loading; wind pressure and earthquake dynamic forces have been modelled on graphical pre and post processor (PATRAN) and analysis has been performed on two finite element codes (ABAQUS and NASTRAN), numerical model verification studies are performed, and optimum material volume required in the walls of cylindrical, conical, parabolic and hyperbolic forms of axisymmetric shell structures are evaluated and reviewed. Free vibration and transient earthquake analysis of hyperbolic shells have been performed once it was established that hyperbolic shape is the most economical under all possible loading conditions. Effect of important parameters of hyperbolic shell structures; shell wall thickness, height and curvature, have been evaluated and empirical relationships have been developed to estimate an approximate value of the lowest (first) natural frequency of vibration. The outcome of this thesis has been the generation of new research information on performance characteristics of axisymmetric shell structures that will facilitate improved designs of shells with better choice of shapes and enhanced levels of economy and performance. Key words; Axisymmetric shell structures, Finite element analysis, Volume Optimisation_ Free vibration_ Transient response.

Implementing value management as a decision-making tool in the design stages of design and build construction projects : a methodology for improved cost optimization

Value Management (VM) has been proven to provide a structured framework, together with other supporting tools and techniques, that facilitate effective decision-making in many types of projects, thus achieving ‘best value’ for clients. One of the major success factors of VM in achieving better project objectives for clients is through the provision of beneficial input by multi-disciplinary team members being involved in critical decision-making discussions during the early stage of construction projects. This paper describes a doctoral research proposal based on the application of VM in design and build construction projects, especially focusing on the design stage. The research aims to study the effects of implementing VM in design and build construction projects, in particular how well the methodology addresses issues related to cost overruns resulting from poor coordination and overlooking of critical constructability issues amongst team members in construction projects in Malaysia. It is proposed that through contractors’ early involvement during the design stage, combined with the use of the VM methodology, particularly as a decision-making tool, better optimization of construction cost can be achieved, thus promoting more efficient and effective constructability. The main methods used in this research involve a thorough literature study, semi-structured interviews, and a survey of major stakeholders, a detailed case study and a VM workshop and focus group discussions involving construction professionals in order to explore and possibly develop a framework and a specific methodology for the facilitating successful application of VM within design and build construction projects.

Land use effects on soil carbon fractions in the southeastern United States. II. changes in soil carbon fractions along a forest to pasture chronosequence

Since land use change can have significant impacts on regional biogeochemistry, we investigated how conversion of forest and cultivation to pasture impact soil C and N cycling. In addition to examining total soil C, we isolated soil physiochemical C fractions in order to understand the mechanisms by which soil C is sequestered or lost. Total soil C did not change significantly over time following conversion from forest, though coarse (250-2,000 mum) particulate organic matter C increased by a factor of 6 immediately after conversion. Aggregate mean weight diameter was reduced by about 50% after conversion, but values were like those under forest after 8 years under pasture. Samples collected from a long-term pasture that was converted from annual cultivation more than 50 years ago revealed that some soil physical properties negatively impacted by cultivation were very slow to recover. Finally, our results indicate that soil macroaggregates turn over more rapidly under pasture than under forest and are less efficient at stabilizing soil C, whereas microaggregates from pasture soils stabilize a larger concentration of C than forest microaggregates. Since conversion from forest to pasture has a minimal impact on total soil C content in the Piedmont region of Virginia, United States, a simple C stock accounting system could use the same base soil C stock value for either type of land use. However, since the effects of forest to pasture conversion are a function of grassland management following conversion, assessments of C sequestration rates require activity data on the extent of various grassland management practices.

Influence of iodine value on combustion and NOx emission characteristics of a DI diesel engine

Biodiesel is a renewable fuel that has been shown to reduce many exhaust emissions, except oxides of nitrogen (NOx), in diesel engine cars. This is of special concern in inner urban areas that are subject to strict environmental regulations, such as EURO norms. Also, the use of pure biodiesel (B100) is inhibited because of its higher NOx emissions compared to petroleum diesel fuel. The aim of this present work is to investigate the effect of the iodine value and cetane number of various biodiesel fuels obtained from different feed stocks on the combustion and NOx emission characteristics of a direct injection (DI) diesel engine. The biodiesel fuels were chosen from various feed stocks such as coconut, palm kernel, mahua (Madhuca indica), pongamia pinnata, jatropha curcas, rice bran, and sesame seed oils. The experimental results show an approximately linear relationship between iodine value and NOx emissions. The biodiesels obtained from coconut and palm kernel showed lower NOx levels than diesel, but other biodiesels showed an increase in NOx. It was observed that the nature of the fatty acids of the biodiesel fuels had a significant influence on the NOx emissions. Also, the cetane numbers of the biodiesel fuels are affected both premixed combustion and the combustion rate, which further affected the amount of NOx formation. It was concluded that NOx emissions are influenced by many parameters of biodiesel fuels, particularly the iodine value and cetane number.

Health risk from the use of roof-harvested rainwater in Southeast Queensland, Australia, as potable or nonpotable water, determined using quantitative microbial risk assessment

A total of 214 rainwater samples from 82 tanks were collected in urban Southeast Queensland (SEQ) in Australia and analysed for the zoonotic bacterial and protozoan pathogen using real-time binary PCR and quantitative PCR (qPCR). Quantitative Microbial Risk Assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to potential pathogens from potable and non-potable uses of roof-harvested rainwater. Of the 214 samples tested, 10.7%, 9.8%, and 5.6%, and 0.4% samples were positive for Salmonella invA, Giardia lamblia β-giardin , Legionella pneumophila mip, and Campylobacter jejuni mapA genes. Cryptosporidium parvum could not be detected. The estimated numbers of viable Salmonella spp., G. lamblia β-giradin, and L. pneumophila genes ranged from 1.6 × 101 to 9.5 × 101 cells, 1.4 × 10-1 to 9.0 × 10-1 cysts, and 1.5 × 101 to 4.3 × 101 per 1000 ml of water, respectively. Six risk scenarios were considered from exposure to Salmonella spp., G. lamblia and L. pneumophila. For Salmonella spp., and G. lamblia, these scenarios were: (1) liquid ingestion due to drinking of rainwater on a daily basis (2) accidental liquid ingestion due to garden hosing twice a week (3) aerosol ingestion due to showering on a daily basis, and (4) aerosol ingestion due to hosing twice a week. For L. pneumophila, these scenarios were: (5) aerosol inhalation due to showering on a daily basis, and (6) aerosol inhalation due to hosing twice a week. The risk of infection from Salmonella spp., G. lamblia, and L. pneumophila associated with the use of rainwater for showering and garden hosing was calculated to be well below the threshold value of one extra infection per 10,000 persons per year in urban SEQ. However, the risk of infection from ingesting Salmonella spp. and G. lamblia via drinking exceeds this threshold value, and indicates that if undisinfected rainwater were ingested by drinking, then the gastrointestinal diseases of Salmonellosis and Giardiasis is expected to range from 5.0 × 100 to 2.8 × 101 (Salmonellosis) and 1.0 × 101 to 6.4 × 101 (Giardiasis) cases per 10,000 persons per year, respectively. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically examined. Nonetheless, it would seem prudent to disinfect rainwater for potable use.

The relationship between strategic positioning and perceived value of social networking sites

The use of social networking sites (SNS) by online citizens to share photos, update friends, play games and to connect with the world has exploded, with SNS and blogs now eclipsing email traffic (eMarketer 2009). Just one popular application on one SNS, (Farmville on Facebook) acquired more than 63 million users since its launch in June 2009 (Marketing 2009. The major global social networks are Facebook, Twitter, YouTube and MySpace, with Facebook claiming that it passed 350 million users in November (Marketing 2009). As usage increases and competition intensifies, the major sites must strategically position themselves to develop a competitive advantage in order to maintain or grow their share of the pie. So how do the major SNS position their brands, and do users perceive significant differences among the big players? This presentation answers these questions by reporting the results of an empirical study of SNS usage by Australian adults. Like other brands, aligning brand positioning strategies with user knowledge and perceptions of SNS is an important ingredient to achieving success (Keller 1993). Furthermore we compare the types of value for three different SNS to identify the relationships between the value derived by users and the stated positioning of the site.

Highly discriminatory single-nucleotide polymorphism interrogation of Escherichia coli by use of allele-specific real-time PCR and eBURST analysis

In total, 782 Escherichia coli strains originating from various host sources have been analyzed in this study by using a highly discriminatory single-nucleotide polymorphism (SNP) approach. A set of eight SNPs, with a discrimination value (Simpson's index of diversity [D]) of 0.96, was determined using the Minimum SNPs software, based on sequences of housekeeping genes from the E. coli multilocus sequence typing (MLST) database. Allele-specific real-time PCR was used to screen 114 E. coli isolates from various fecal sources in Southeast Queensland (SEQ). The combined analysis of both the MLST database and SEQ E. coli isolates using eight high-D SNPs resolved the isolates into 74 SNP profiles. The data obtained suggest that SNP typing is a promising approach for the discrimination of host-specific groups and allows for the identification of human-specific E. coli in environmental samples. However, a more diverse E. coli collection is required to determine animal- and environment-specific E. coli SNP profiles due to the abundance of human E. coli strains (56%) in the MLST database.

Test and evaluation of non conventional instrument transformers and sampled value process bus on Powerlink's transmission network

IEC 61850 Process Bus technology has the potential to improve cost, performance and reliability of substation design. Substantial costs associated with copper wiring (designing, documentation, construction, commissioning and troubleshooting) can be reduced with the application of digital Process Bus technology, especially those based upon international standards. An IEC 61850-9-2 based sampled value Process Bus is an enabling technology for the application of Non-Conventional Instrument Transformers (NCIT). Retaining the output of the NCIT in its native digital form, rather than conversion to an analogue output, allows for improved transient performance, dynamic range, safety, reliability and reduced cost. In this paper we report on a pilot installation using NCITs communicating across a switched Ethernet network using the UCAIug Implementation Guideline for IEC 61850-9-2 (9-2 Light Edition or 9-2LE). This system was commissioned in a 275 kV Line Reactor bay at Powerlink Queensland’s Braemar substation in 2009, with sampled value protection IEDs 'shadowing' the existing protection system. The results of commissioning tests and twelve months of service experience using a Fibre Optic Current Transformer (FOCT) from Smart Digital Optics (SDO) are presented, including the response of the system to fault conditions. A number of remaining issues to be resolved to enable wide-scale deployment of NCITs and IEC 61850-9-2 Process Bus technology are also discussed.

Sustainable fashion textiles design : value adding through technological enhancement

A key concern in the field of contemporary fashion/textiles design is the emergence of ‘fast fashion’: best explained as "buy it Friday, wear it Saturday and throw it away on Sunday" (O'Loughlin, 2007). In this contemporary retail atmosphere of “pile it high: sell it cheap” and “quick to market”, even designer goods have achieved a throwaway status. This modern culture of consumerism is the antithesis of sustainability and is proving a dilemma surrounding sustainable practice for designers and producers in the disciplines (de Blas, 2010). Design researchers including those in textiles/fashion have begun to explore what is a key question in the 21st century in order to create a vision and reason for their disciplines: Can products be designed to have added value to the consumer and hence contribute to a more sustainable industry? Fashion Textiles Design has much to answer for in contributing to the problems of unsustainable practices on a global scale in design, production and waste. However, designers within this field also have great potential to contribute to practical ‘real world’ solutions. ----- ----- This paper provides an overview of some of the design and technological developments from the fashion/textiles industry, endorsing a model where designers and technicians use their transferrable skills for wellbeing rather than desire. Smart materials in the form of responsive and adaptive fibres and fabrics combined with electro active devices, and ICT are increasingly shaping many aspects of society particularly in the leisure industry and interactive consumer products are ever more visible in healthcare. Combinations of biocompatible delivery devices with bio sensing elements can create analyse, sense and actuate early warning and monitoring systems which can be linked to data logging and patient records via intelligent networks. Patient sympathetic, ‘smart’ fashion/textiles applications based on interdisciplinary expertise utilising textiles design and technology is emerging. An analysis of a series of case studies demonstrates the potential of fashion textiles design practitioners to exploit the concept of value adding through technological garment and textiles applications and enhancement for health and wellbeing and in doing so contribute to a more sustainable future fashion/textiles design industry.

Test and evaluation system for multi-protocol sampled value protection schemes

Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

'Which is the best Doctor Who story?' : a case study in value judgements outside the academy'

One of Cultural Studies' most important contributions to academic thinking about culture is the acceptance as axiomatic that we must not simply accept traditional value hierarchies in relation to cultural objects (see, for example, McGuigan, 1992: 157; Brunsdon, 1997: 5; Wark, 2001). Since Richard Hoggart and Raymond Williams took popular culture as a worthy object of study, Cultural Studies practitioners have accepted that the terms in which cultural debate had previously been conducted involved a category error. Opera is not 'better' than pop music, we believe in Cultural Studies - 'better for what?', we would ask. Similarly, Shakespeare is not 'better' than Mills and Boon, unless you can specify the purpose for which you want to use the texts. Shakespeare is indeed better than Mills and Boon for understanding seventeenth century ideas about social organisation; but Mills and Boon is unquestionably better than Shakespeare if you want slightly scandalous, but ultimately reassuring representations of sexual intercourse. The reason that we do not accept traditional hierarchies of cultural value is that we know that the culture that is commonly understood to be 'best' also happens to be that which is preferred by the most educated and most materially well-off people in any given culture (Bourdieu, 1984: 1- 2; Ross, 1989: 211). We can interpret this information in at least two ways. On the one hand, it can be read as proving that the poorer and less well-educated members of a society do indeed have tastes which are innately less worthwhile than those of the material and educational elite. On the other hand, this information can be interpreted as demonstrating that the cultural and material elite publicly represent their own tastes as being the only correct ones. In Cultural Studies, we tend to favour the latter interpretation. We reject the idea that cultural objects have innate value, in terms of beauty, truth, excellence, simply 'there' in the object. That is, we reject 'aesthetic' approaches to culture (Bourdieu, 1984: 6; 485; Hartley, 1994: 6)1. In this, Cultural Studies is similar to other postmodern institutions, where high and popular culture can be mixed in ways unfamiliar to modernist culture (Sim, 1992: 1; Jameson, 1998: 100). So far, so familiar.

Value-adding to cellulosic ethanol: Lignin polymers

Lignocellulosic waste materials are the most promising feedstock for generation of a renewable, carbon-neutral substitute for existing liquid fuels. The development of value-added products from lignin will greatly improve the economics of producing liquid fuels from biomass. This review gives an outline of lignin chemistry, describes the current processes of lignocellulosic biomass fractionation and the lignin products obtained through these processes, then outlines current and potential value-added applications of these products, in particular as components of polymer composites. Research highlights The use of lignocellulosic biomass to produce platform chemicals and industrial products enhances the sustainability of natural resources and improves environmental quality by reducing greenhouse and toxic emissions. In addition, the development of lignin based products improves the economics producing liquid transportation fuel from lignocellulosic feedstock. Value adding can be achieved by converting lignin to functionally equivalent products that rely in its intrinsic properties. This review outlines lignin chemistry and some potential high value products that can be made from lignin. Keywords: Lignocellulose materials; Lignin chemistry; Application

Maximising the manufacturer performance value through lean initiatives using cost based model

Numerous tools and techniques have been developed to eliminate or reduce waste and carry out lean concepts in the manufacturing environment. However, appropriate lean tools need to be selected and implemented in order to fulfil the manufacturer needs within their budgetary constraints. As a result, it is important to identify manufacturer needs and implement only those tools, which contribute maximum benefit to their needs. In this research a mathematical model is proposed for maximising the perceived value of manufacturer needs and developed a step-by-step methodology to select best performance metrics along with appropriate lean strategies within the budgetary constraints. With the help of a case study, the proposed model and method have been demonstrated.