Decision models - an analytical framework for the Watertime Project

This paper suggests a possible framework for the encapsulation of the decision making process for the Waterime project. The final outcome maybe a computerised model, but the process advocated is not prescriptive, and involves the production of a "paper model" as mediating representation between the knowledge acquired and any computerised system. This paper model may suffice in terms of the project's goals.

The use of a mathematical multicriteria decision-making model for selecting the fire origin room

Over the last three decades, the fire safety codes have been changing from a prescriptive approach to a performance-based one. Some countries, such as the USA, Sweden, New Zealand, Australia and the UK, are in an advanced stage of development and implementation of the performance-based codes. However, there are some difficulties in this process. Most of them are due to the uncertainties associated with fire design. For instance, one of the questions that need to be answered is how to select the most probable fire origin room (FOR)? On the other hand, to know where the FOR is located is also an important aspect in terms of forensic issues. Given that, to address this question is an important step for the establishment of fire designs (i.e., pre-fire phases) and also for fire investigations (i.e., post-fire phases). This paper proposes a methodology for selecting the FOR through the use of a mathematical multicriteria decision-making model: the analytical hierarchy process (AHP). The proposed method is then applied to a hypothetical study case. The results are presented and discussed in this paper.

Computerised Diagnostic Decision Support System for the Classification of Pre-Invasive Cervical Squamous Lesions.

Previous studies have revealed considerable interobserver and intraobserver variation in the histological classification of preinvasive cervical squamous lesions. The aim of the present study was to develop a decision support system (DSS) for the histological interpretation of these lesions. Knowledge and uncertainty were represented in the form of a Bayesian belief network that permitted the storage of diagnostic knowledge and, for a given case, the collection of evidence in a cumulative manner that provided a final probability for the possible diagnostic outcomes. The network comprised 8 diagnostic histological features (evidence nodes) that were each independently linked to the diagnosis (decision node) by a conditional probability matrix. Diagnostic outcomes comprised normal; koilocytosis; and cervical intraepithelial neoplasia (CIN) 1, CIN II, and CIN M. For each evidence feature, a set of images was recorded that represented the full spectrum of change for that feature. The system was designed to be interactive in that the histopathologist was prompted to enter evidence into the network via a specifically designed graphical user interface (i-Path Diagnostics, Belfast, Northern Ireland). Membership functions were used to derive the relative likelihoods for the alternative feature outcomes, the likelihood vector was entered into the network, and the updated diagnostic belief was computed for the diagnostic outcomes and displayed. A cumulative probability graph was generated throughout the diagnostic process and presented on screen. The network was tested on 50 cervical colposcopic biopsy specimens, comprising 10 cases each of normal, koilocytosis, CIN 1, CIN H, and CIN III. These had been preselected by a consultant gynecological pathologist. Using conventional morphological assessment, the cases were classified on 2 separate occasions by 2 consultant and 2 junior pathologists. The cases were also then classified using the DSS on 2 occasions by the 4 pathologists and by 2 medical students with no experience in cervical histology. Interobserver and intraobserver agreement using morphology and using the DSS was calculated with K statistics. Intraobserver reproducibility using conventional unaided diagnosis was reasonably good (kappa range, 0.688 to 0.861), but interobserver agreement was poor (kappa range, 0.347 to 0.747). Using the DSS improved overall reproducibility between individuals. Using the DSS, however, did not enhance the diagnostic performance of junior pathologists when comparing their DSS-based diagnosis against an experienced consultant. However, the generation of a cumulative probability graph also allowed a comparison of individual performance, how individual features were assessed in the same case, and how this contributed to diagnostic disagreement between individuals. Diagnostic features such as nuclear pleomorphism were shown to be particularly problematic and poorly reproducible. DSSs such as this therefore not only have a role to play in enhancing decision making but also in the study of diagnostic protocol, education, self-assessment, and quality control. (C) 2003 Elsevier Inc. All rights reserved.

Adoption from Care in Northern Ireland: Problems in the process

This is a study of the processes for freeing children for adoption in Northern Ireland. The focus was the time taken from admission to care to adoption order. The findings confirmed that the process is dogged by delay at each stage. In total the average time from the child becoming looked after to the granting of an adoption order was 4.5 years. Most of the time taken was in the stages for which social services had lead responsibility, principally the decision to pursue adoption as the plan for a child. The children were very young when admitted to care - average age 1 year 7 months. Most were admitted to care because they were being neglected. Their parents were well known to social services and had multiple problems. Most parents unsuccessfully contested the social services' application and this contributed much to the delay. Their former foster parents adopted almost half of the children and these children tended to be placed more quickly with their adopters than those placed with adopters who were not their foster parents prior to the adoption process.

Changing Attitudes of Community Through the Design Charrette Process

The traditional planning process in the UK and elsewhere takes too long to develop, are demanding on resources that are scarce and most times tend to be unrelated to the needs and demands of society. It segregates the plan making from the decision making process with the consultants planning, the politicians deciding and the community receiving without being integrated into the planning and decision making process. The Scottish Planning system is undergoing radical changes as evidenced by the publication of the Planning Advice Note, PAN by the Scottish Executive in July 2006 with the aim of enabling Community Engagement that allow for openness and accountability in the decision making process. The Public Engagement is a process that is driven by the physical, social and economic systems research aimed at improving the process at the level of community through problem solving and of the city region through strategic planning. There are several methods available to engage the community in large scale projects. The two well known ones are the Enquiry be Design and the Charrette approaches used in the UK and US respectively. This paper is an independent and rigorous analysis of the Charrette process as observed in the proposed Tornagrain Settlement in the Highlands area of Scotland. It attempts to gauge and analyse the attitudes, perceptions of the participants the Charrette as well as the mechanics and structure of the Charrette. The study analyzes the Charrette approach as a method future public engagement in and its effectiveness within the Scottish Planning System in view of PAN 2005. The analysis revealed that the Charrette as a method of engagement could be effective in changing attitudes of the community to the design process under certain conditions as discussed in the paper.

Extending BPM Environments of Your Choice with Performance Related Decision Support

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools process optimizations or a combination Of Such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.

The absence of creativity in Feist and the computational process

The decision of the U.S. Supreme Court in 1991 in Feist Publications, Inc. v. Rural Tel. Service Co. affirmed originality as a constitutional requirement for copyright. Originality has a specific sense and is constituted by a minimal degree of creativity and independent creation. The not original is the more developed concept within the decision. It includes the absence of a minimal degree of creativity as a major constituent. Different levels of absence of creativity also are distinguished, from the extreme absence of creativity to insufficient creativity. There is a gestalt effect of analogy between the delineation of the not original and the concept of computability. More specific correlations can be found within the extreme absence of creativity. "[S]o mechanical" in the decision can be correlated with an automatic mechanical procedure and clauses with a historical resonance with understandings of computability as what would naturally be regarded as computable. The routine within the extreme absence of creativity can be regarded as the product of a computational process. The concern of this article is with rigorously establishing an understanding of the extreme absence of creativity, primarily through the correlations with aspects of computability. The understanding established is consistent with the other elements of the not original. It also revealed as testable under real-world conditions. The possibilities for understanding insufficient creativity, a minimal degree of creativity, and originality, from the understanding developed of the extreme absence of creativity, are indicated. 

Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.

Integrating textual analysis and evidential reasoning for decision making in Engineering design

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. © 2013 Elsevier B.V. All rights reserved.

Supported decision making: a review of the international literature

Supported decision making (SDM) refers to the process of supporting people, whose decision making ability may be impaired, to make decisions and so promote autonomy and prevent the need for substitute decision making. There have been developments in SDM but mainly in the areas of intellectual disabilities and end-of-life care rather than in mental health. The main aim of this review was to provide an overview of the available evidence relevant to SDM and so facilitate discussion of how this aspect of law, policy and practice may be further developed in mental health services. The method used for this review was a Rapid Evidence Assessment which involved: developing appropriate search strategies; searching relevant databases and grey literature; then assessing, including and reviewing relevant studies. Included studies were grouped into four main themes: studies reporting stakeholders’ views on SDM; studies identifying barriers to the implementation of SDM; studies highlighting ways to improve implementation; and studies on the impact of SDM. The available evidence on implementation and impact, identified by this review, is limited but there are important rights-based, effectiveness and pragmatic arguments for further developing and researching SDM for people with mental health problems.

Analogies to semantic and syntactic mental labour in the Feist decision

The Supreme Court of the United States in Feist v. Rural (Feist, 1991) specified that compilations or databases, and other works, must have a minimal degree of creativity to be copyrightable. The significance and global diffusion of the decision is only matched by the difficulties it has posed for interpretation. The judgment does not specify what is to be understood by creativity, although it does give a full account of the negative of creativity, as ‘so mechanical or routine as to require no creativity whatsoever’ (Feist, 1991, p.362). The negative of creativity as highly mechanical has particularly diffused globally.

A recent interpretation has correlated ‘so mechanical’ (Feist, 1991) with an automatic mechanical procedure or computational process, using a rigorous exegesis fully to correlate the two uses of mechanical. The negative of creativity is then understood as an automatic computation and as a highly routine process. Creativity is itself is conversely understood as non-computational activity, above a certain level of routinicity (Warner, 2013).

The distinction between the negative of creativity and creativity is strongly analogous to an independently developed distinction between forms of mental labour, between semantic and syntactic labour. Semantic labour is understood as human labour motivated by considerations of meaning and syntactic labour as concerned solely with patterns. Semantic labour is distinctively human while syntactic labour can be directly humanly conducted or delegated to machine, as an automatic computational process (Warner, 2005; 2010, pp.33-41).

The value of the analogy is to greatly increase the intersubjective scope of the distinction between semantic and syntactic mental labour. The global diffusion of the standard for extreme absence of copyrightability embodied in the judgment also indicates the possibility that the distinction fully captures the current transformation in the distribution of mental labour, where syntactic tasks which were previously humanly performed are now increasingly conducted by machine.

The paper has substantive and methodological relevance to the conference themes. Substantively, it is concerned with human creativity, with rationality as not reducible to computation, and has relevance to the language myth, through its indirect endorsement of a non-computable or not mechanical semantics. These themes are supported by the underlying idea of technology as a human construction. Methodologically, it is rooted in the humanities and conducts critical thinking through exegesis and empirically tested theoretical development

References

Feist. (1991). Feist Publications, Inc. v. Rural Tel. Service Co., Inc. 499 U.S. 340.

Warner, J. (2005). Labor in information systems. Annual Review of Information Science and Technology. 39, 2005, pp.551-573.

Warner, J. (2010). Human Information Retrieval (History and Foundations of Information Science Series). Cambridge, MA: MIT Press.

Warner, J. (2013). Creativity for Feist. Journal of the American Society for Information Science and Technology. 64, 6, 2013, pp.1173-1192.

Shared decision making in patients at risk of cancer: The role of domain and numeracy

Background
Shared decision making has become an integral part of medical consultation. Research has, however, reported wide differences in individuals' desires to be involved in the decision-making process, and these differences in preferences are likely to be the result of a number of factors including age, education and numeracy.

Objective
To investigate whether patients at genetic risk for cancer had preferences for shared decision making that differed depending on medical domain (general health vs. cancer) and whether decision preferences are linked to numeracy abilities.

Methods
Four hundred and seventy-six women who consented to participate in response to an email sent by a local branch of the U.S.-based Cancer Genetics Network (CGN) to its members. Participants completed the Control Preference Scale, as well as an objective and subjective numeracy scales.

Results
Decision domain (cancer vs. general health) was not associated with women's preferences for involvement in decision making. Objective and subjective numeracy predicted a preference for decision involvement in general, and only objective numeracy was predictive with regard to cancer.

Conclusion
Participants were equally likely to state they wanted to play an active, collaborative or passive role in both medical domains (general and cancer). High-numeracy participants were more likely to express a desire for an active role in general and in case they were diagnosed with cancer.

Practice implications
Health authorities' recommendations to clinicians to include patients in their medical decisions are supported by patients' desires, and clinicians should be cognizant of their patients' preferences as well as their numeracy skills.

Consideration of coastal risk in the Irish spatial planning process

The vulnerability of coastal areas to associated hazards is increasing due to population growth, development pressure and climate change. It is incumbent on coastal governance regimes to address the vulnerability of coastal inhabitants to these hazards. This is especially so at the local level where development planning and control has a direct impact on the vulnerability of coastal communities. To reduce the vulnerability of coastal populations, risk mitigation and adaptation strategies need to be built into local spatial planning processes. Local government, however, operates within a complex hierarchal governance framework which may promote or limit particular actions. It is important, therefore, to understand how local coastal planning practices are shaped by national and supranational entities. Local governments also have to respond to the demands of local populations. Consequently, it is important to understand local populations’ perceptions of coastal risk and its management. Adopting an in-depth study of coastal planning in County Mayo, Ireland, this paper evaluates: (a) how European and national policies and legislation shape coastal risk management at local level; (b) the incorporation of risk management strategies into local plans; and (c) local perception of coastal risks and risk management. Despite a strong steer from supranational and national legislation and policy, statutory local plans are found to be lacking in appropriate risk mitigation or adaptation strategies. Local residents appear to be lulled into a sense of complacency towards these risks because of the low level of attention afforded to them by the local planning authorities. To avoid potentially disastrous consequences for local residents and businesses, it is imperative that this situation is redressed urgently. Based on our analysis, we recommend: the development and implementation of a national ICZM strategy, supported by detailed local ICZM plans; and obliging local government to address known risks in their plans rather than defer them to project level decision making.

An Adaptive Machine Learning Decision System for Flexible Predictive Maintenance

Process monitoring and Predictive Maintenance (PdM) are gaining increasing attention in most manufacturing environments as a means of reducing maintenance related costs and downtime. This is especially true in industries that are data intensive such as semiconductor manufacturing. In this paper an adaptive PdM based flexible maintenance scheduling decision support system, which pays particular attention to associated opportunity and risk costs, is presented. The proposed system, which employs Machine Learning and regularized regression methods, exploits new information as it becomes available from newly processed components to refine remaining useful life estimates and associated costs and risks. The system has been validated on a real industrial dataset related to an Ion Beam Etching process for semiconductor manufacturing.