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Public sector procurement is governed by laws and regulations enforcing a rigid structure with multiple criteria for assessing and selecting suppliers. This paper analyses legal and operational requirements of public sector e-procurement of the Maldives education sector. The research was based on a desktop review of traditional academic sources as well as gray literature to identify legal and fiscal constraints and regulations, followed by a field research to identify operational requirements. Subsequently, an evaluation study, which applied the findings of the desktop study and the field research, was conducted to select an appropriate Multi-Criteria Decision Analysis (MCDA) method for that specific context. After a thorough analysis of MCDA methods, two methods emerged as applicable for the Maldivian context and capable of meeting both operational and legal constraints. The paper provides an extensive discussion on the selection of suitable MCDA methods for Maldivian public sector procurement requirements. [ABSTRACT FROM AUTHOR]

By way of introduction, this chapter provides a general overview of the Ecosystem Management Decision Support (EMDS) system, including a brief account of its development history, key factors that have motivated its development, and more central topics such as concepts, principles, and functionality. We conclude the chapter with discussions on applications involving multiple spatial scales, ways in which the technology can support the modern planning process, critical design factors behind the relative success of the system, and experiences drawn from design and use of the system. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to case-based decision analysis supported by case-based reasoning (CBR). The strength of CBR is utilized for building a situation dependent decision model without complete domain knowledge. This is achieved by deriving states probabilities and general utility estimates from the case library and the subset of cases retrieved in a situation described in query. In particular, the derivation of state probabilities is realized through an information fusion process which comprises evidence (case) combination using the Dempster-Shafer theory and Bayesian probabilistic reasoning. Subsequently decision theory is applied to the decision model learnt from previous cases to identify the most promising, secured, and rational choices. In such a way we take advantage of both the strength of CBR to learn without domain knowledge and the ability of decision theory to analyze under uncertainty. We have also studied the issue of imprecise representations of utility in individual cases and explained how fuzzy decision analysis can be conducted when case specific utilities are assigned with fuzzy data. [ABSTRACT FROM AUTHOR]

This paper presents an approach that uses a decision model for resolving variations in a so-called learning space, which aim is to enhance the reuse of explicitly documented experiences by providing context-aware learning content. Decision models promise a better possibility to separate the variabilities in e-learning content, and address the problem of closed corpus of adaptive hypermedia systems. Adaptation is not coupled to a fixed set of learning resources, but to types of learning space concepts. The system adapts and personalizes the learning space to the learner΄s situation. A controlled experiment provides first statistically significant results, which show an experience package reuse improvement regarding knowledge acquisition and application efficiency. Further, it provides a baseline for future evaluations of different adaptation methods and techniques. [ABSTRACT FROM AUTHOR]

The paper describes the development of a clinical decision model to help Emergency Department physicians assess the severity of pediatric asthma exacerbations. The model should support an early identification (at 2 hours) of those patients who are having a mild attack and those who are having a moderate/severe attack. A comprehensive approach combining rough sets and expert-driven manual feature selection was applied to develop a rule-based decision model from retrospective data that described asthmatic patients visiting the Emergency Department. The experiment involved creating the following four potential decision models differentiated by the subsets of clinical attributes that were considered: Model A using all attributes collected in the retrospective chart study; Model B using only attributes describing the patient΄s history; Model C using only attributes describing the triage and repeated assessments; and Model D using attributes from Model C expanded with some of the attributes from Model B identified by expert clinical knowledge. Model D offered the highest assessment accuracy when tested on an independent retrospective data set and was selected as the decision model for asthma exacerbations. [ABSTRACT FROM AUTHOR]

Software product lines are used by companies to provide a set of reusable software assets sharing common features that satisfy a market. Though a product line is based on the expression and the capitalization of afamily of similar systems, the differences between products must be identified and expressed in order to be able to build the applications by taking the good decisions. Today, even if the flexibility aspects are well covered, there isn΄t as many studies on variability description and usage. This paper presents a process, methods and techniques investigated in THALES (Research Center and Business Units) to express the variability between products and its usage to derive new products from the Software product line. [ABSTRACT FROM AUTHOR]

In sentencing, the judge's task is to determine the type and quantum of sentence appropriate to the facts of the case, and this judgment must be made in accordance with the relevant statutory provisions and appellate principles. But in Australia, as in England and elsewhere, sentencing law speaks in only general terms so that it is left to the sentencing judge to develop and apply the working rules required to give detailed effect to these provisions and principles in actual cases. What is not known is how individual judges have responded to this challenge. The present monograph is the second report from a continuing study of this matter. The first, Lovegrove (1989), examines how judges in Victoria scale and combine the seriousness of the offence characteristics, such as organization and violence, of a single count and use this to determine what is appropriate by way of sentence (quantum of imprisonment) for that count. The product of this work is a model offering both a decision strategy and a numerical guideline; since it takes no account of legally immaterial considerations or distortions in thinking arising from the limitations of human information processing, it represents an account of ideal (cf. actual) decision making in sentencing. The present study extends that enquiry, being concerned with multiple-count cases: how in Victoria the judge, having fixed an appropriate sentence of imprisonment for each of the comprising counts, determines an effective sentence appropriate to the overall seriousness of the case. [ABSTRACT FROM AUTHOR]

The fictitious cases were formulated and administered, as described in the previous chapter, with two ends in mind: (1) the delineation and quantification of the functions relating the variables in the alternative decision model; (2) the testing of this model's validity. Now, the strategy adopted to do this depends on the nature of the model under test – specifically, what is being claimed for it (the knowledge it represents) and what is required of it (the role it has to play). The purpose of the present chapter is to develop and justify an appropriate notion of model and apply it, within the limitations of the study, so as to move towards the above two goals. The idea of requisite modelling It will be recalled that only two of the judges in the present sample were able to articulate a relevant, general and coherent policy in considerable detail and with some consistency across the sentencing problems; moreover, from the manner in which these two judges gave their responses even they appeared to a significant extent not to be applying a ready solution but to be formulating on the spot what seemed appropriate by way of approach. And, in this respect, the best that can be said of the other judges is that, to the extent and on the occasions that it was possible to discern elements of a general approach to this type of sentencing problem in their responses, they were consistent with those of the former two (see Chapter 7). [ABSTRACT FROM AUTHOR]

This study has now reached a point where there is an alternative model describing the principles and working rules relied on with varying awareness and comprehension by judges in order to determine, according to current sentencing policy, effective sentences for multiple offenders where the counts are separate transactions and offence categories and once an appropriate sentence of imprisonment has been fixed for each of the multiple counts. This model was formulated in the previous chapter on the basis of the judges' responses to the sentencing problems. In the sentencing of the multiple offender, principle dictates that more serious principal offences require a higher effective sentence and more serious and additional multiple secondary counts require a greater quantum of sentence to be added to the sentence for the principal offence. Nevertheless, this cumulation must not result in what would be a crushing sentence on the offender. The model, then, is also concerned with the principle governing the constraint on the cumulation of sentence, and this was discerned to be: the higher the sentence appropriate to the principal offence and the higher the sum of the sentences appropriate to each of the other (i.e., the multiple secondary) counts, then the greater the degree of concurrence for each of the appropriate sentences associated with the multiple secondary counts. In view of the alternative model's provenance, a rigorous test of its validity requires the formulation of new sentencing problems specifically designed to test predictions from it, especially for those aspects inconsistent with its forerunner. [ABSTRACT FROM AUTHOR]

In the previous chapter the model describing how judges reach sentencing decisions in cases comprising multiple disparate and separate counts was used to derive hypotheses so that it was possible to test this model by means of a series of sentencing problems. This chapter describes how the data were collected for this purpose. Three sets of data were used, each set generated by a different technique, although the sentencing problems provided a common framework within which these three techniques were applied. The three techniques were: (1) sentences imposed by a sample of judges for the cases in the sentencing problems, to investigate which aspects of the model were consistent with the judges' sentencing behavior and which were not; (2) verbal protocols based on immediate retrospective reports and providing direct, detailed and accurate information on the content and sequence of the judges' thoughts as they worked through the sentencing problems; and (3) reflective retrospective reports in which the judges were asked to comment on whether the various elements of the model were accepted by them as valid descriptions of the method to be adopted when sentencing the multiple offender. For these three techniques of data collection, the judges in the sample were tested individually. Each of the three techniques is now described, justified, and its place in the testing of the model explained, in turn. Following this, the procedural details relating to the administration of these techniques are described. [ABSTRACT FROM AUTHOR]