Past, present and future mathematical models for buildings (i)

This is the first of two articles presenting a detailed review of the historical evolution of mathematical models applied in the development of building technology, including conventional buildings and intelligent buildings. After presenting the technical differences between conventional and intelligent buildings, this article reviews the existing mathematical models, the abstract levels of these models, and their links to the literature for intelligent buildings. The advantages and limitations of the applied mathematical models are identified and the models are classified in terms of their application range and goal. We then describe how the early mathematical models, mainly physical models applied to conventional buildings, have faced new challenges for the design and management of intelligent buildings and led to the use of models which offer more flexibility to better cope with various uncertainties. In contrast with the early modelling techniques, model approaches adopted in neural networks, expert systems, fuzzy logic and genetic models provide a promising method to accommodate these complications as intelligent buildings now need integrated technologies which involve solving complex, multi-objective and integrated decision problems

Performance measurement system for a manufacturing environment: KB/GAP/AHP approach

YesDesigning and implementing Performance Measurement System (PMS) is an integral part of management control systems. This paper presents an original and novel approach to designing and benchmarking of PMSs for a manufacturing environment through a hybrid framework which overcomes the shortcomings of earlier models. A detailed review was taken of previous models and their limitations were identified. The present hybrid PMS model seeks to improve the earlier research models by the following novel approach: implementation of a Knowledge Based (KB) expert system, Gauging Absences of Pre-requisite (GAP) analysis and Analytic Hierarchy Process (AHP) methodology in an integrated KBPMS. The paper has shown that the present hybrid (KB-AHP-GAP) approach to developing a KBPMS model is a realistic methodology. The combination of the KB-AHP-GAP approach allows detailed benchmarking of the PMS existing within a manufacturing organisation. Furthermore, this approach can assist in identifying and prioritising the key decisions that need to be actioned to overcome the existing PMS shortcomings

A fuzzy front end model for concurrent specification in new product development

This research reports on the development of a new model for an early design stage in new product development (NPD) programmes called the Fuzzy Front End (FFE). The new FFE model aims at overcoming two kinds of limitations identified in previous FFE models. The first limitation concerns current trends in FFE model improvement including the need for a data-driven model, and to address agile development, incremental and radical NPDs, balanced explicitness and responsiveness characteristics, and balanced procedural and performative structures. The second limitation concerns deficiencies in the performance structure and operating mechanism regarding contextual performance and concurrent collaboration. This means that performances in the FFE do not systematically link with each other, either in a single functional domain or multidimensionally across diverse functional domains, but instead exist independently. A pragmatic-prescriptive model has been functionally embodied by analysing real-world FFE scenarios using inductive reasoning. The model is data-driven with a performative structure wherein parameters can interlock for contextual performance and concurrent collaboration throughout the entire FFE process. With this interlocking structure, once an initial parameter is produced, all remaining parameters considered from both perspectives can be obtained successively. This model allows performers to explicitly understand the purpose and roles of parameters and their relationships from both perspectives when processing parameters. The model thus leads to more agile FFE execution by reducing the iterative work needed to correct defective parameters which have not been handled with contextual performance and concurrent collaboration in mind but instead exist independently. A theoretical-descriptive model, produced by validating the developed pragmatic-prescriptive model, using deductive reasoning, consists of mathematical formulas, providing the underlying concept of an overall FFE as well as that of its parts. Consequently, the pragmatic-prescriptive model can serve as functional performance guidance, while the theoretical-descriptive model can serve as conceptual performance guidance when employing the pragmatic-prescriptive model.Open Acces

A case-based reasoning approach to improve risk identification in construction projects

Risk management is an important process to enhance the understanding of the project so as to support decision making. Despite well established existing methods, the application of risk management in practice is frequently poor. The reasons for this are investigated as accuracy, complexity, time and cost involved and lack of knowledge sharing. Appropriate risk identification is fundamental for successful risk management. Well known risk identification methods require expert knowledge, hence risk identification depends on the involvement and the sophistication of experts. Subjective judgment and intuition usually from par1t of experts’ decision, and sharing and transferring this knowledge is restricted by the availability of experts. Further, psychological research has showed that people have limitations in coping with complex reasoning. In order to reduce subjectivity and enhance knowledge sharing, artificial intelligence techniques can be utilised. An intelligent system accumulates retrievable knowledge and reasoning in an impartial way so that a commonly acceptable solution can be achieved. Case-based reasoning enables learning from experience, which matches the manner that human experts catch and process information and knowledge in relation to project risks. A case-based risk identification model is developed to facilitate human experts making final decisions. This approach exploits the advantage of knowledge sharing, increasing confidence and efficiency in investment decisions, and enhancing communication among the project participants

What is Asset-Based Community Development and how might it improve the health of people with long-term conditions? A realist synthesis

Abstract Background Asset Based Community Development (ABCD) appears to be a promising way to supporting people with long-term health problems but there is currently a lack of evidence to support this approach. Methods Taking a realist approach, a review and concept-mapping exercise of ABCD approaches to improve health were conducted with a view to providing a better understanding about these approaches, how they work, and who they work for. Results 29 papers were deemed relevant and included in the review. The realist synthesis and concept mapping helped identify concepts most commonly associated with ABCD but found no papers focussed on LTCs and thus no evidence that this approach improves health outcomes for people with LTCs. Conclusions Whilst there is a lack of clarity about how to implement ABCD or how to evaluate it, this paper offers a clearer theoretical framework about the essential ingredients needed to activate ABCD

Monitoring the Performance of Educational Programmes in Developing Countries

Teaching/Communication/Extension/Profession,

Software process quality models: a comparative evaluation

Numerous software processes are implemented by software organisations in the production and maintenance of software products. Varying levels of success are observed in their execution, as processes vary in content and quality. A number of quality models for software processes have been published, each of which is intended to encompass the totality of quality factors and issues relevant to a specific notion of process quality. These quality models may be used to develop a new process, measure the quality of existing processes, or guide improvement of existing processes. It is therefore desirable that mechanisms exist to select the model of highest intrinsic quality and greatest relevance. In this thesis, mechanisms are proposed for the comparative evaluation of software process quality models. Case studies are performed in which existing software process quality models are applied to existing software processes. Case study results are used in empirical evaluation of models to augment theoretical evaluation results. Specific recommendations are made for selection of models against typical selection criteria. Assessment is performed of the assessment procedures against defined success criteria. Theoretical evaluation procedures are developed to measure process quality models against defined quality criteria. Measurements are performed of conformance of models to the requirements set for an ideal process quality model, and the relevance of model content to defined stakeholders in software processes. Comparison is also made of the scope and size of models. Empirical evaluation procedures are developed to assess model performance in the context of application to real software processes. These procedures assess the extent to which the results of process measurement using process quality models are observed to differ, and hence the importance of selecting one model in preference to others. Measurement is also performed of the extent of difference in the software processes evaluated in the case studies

Probabilistic and Fuzzy Approaches for Estimating the Life Cycle Costs of Buildings

The Life cycle cost (LCC) method makes it possible for the whole life performance of buildings and other structures to be optimized. The introduction of the idea of thinking in terms of a building life cycle resulted in the need to use appropriate tools and techniques for assessing and analyzing costs throughout the life cycle of the building. Traditionally, estimates of LCC have been calculated based on historical analysis of data and have used deterministic models. The concepts of probability theory can also be applied to life cycle costing, treating the costs and timings as a stochastic process. If any subjectivity is introduced into the estimates, then the uncertainty cannot be handled using the probability theory alone. The theory of fuzzy sets is a valuable tool for handling such uncertainties. In this Special Issue, a collection of 11 contributions provide an updated overview of the approaches for estimating the life cycle cost of buildings

State-of-the-Art Report on Systems Analysis Methods for Resolution of Conflicts in Water Resources Management

Water is an important factor in conflicts among stakeholders at the local, regional, and even international level. Water conflicts have taken many forms, but they almost always arise from the fact that the freshwater resources of the world are not partitioned to match the political borders, nor are they evenly distributed in space and time. Two or more countries share the watersheds of 261 major rivers and nearly half of the land area of the wo rld is in international river basins. Water has been used as a military and political goal. Water has been a weapon of war. Water systems have been targets during the war. A role of systems approach has been investigated in this report as an approach for resolution of conflicts over water. A review of systems approach provides some basic knowledge of tools and techniques as they apply to water management and conflict resolution. Report provides a classification and description of water conflicts by addressing issues of scale, integrated water management and the role of stakeholders. Four large-scale examples are selected to illustrate the application of systems approach to water conflicts: (a) hydropower development in Canada; (b) multipurpose use of Danube river in Europe; (c) international water conflict between USA and Canada; and (d) Aral See in Asia. Water conflict resolution process involves various sources of uncertainty. One section of the report provides some examples of systems tools that can be used to address objective and subjective uncertainties with special emphasis on the utility of the fuzzy set theory. Systems analysis is known to be driven by the development of computer technology. Last section of the report provides one view of the future and systems tools that will be used for water resources management. Role of the virtual databases, computer and communication networks is investigated in the context of water conflicts and their resolution.https://ir.lib.uwo.ca/wrrr/1005/thumbnail.jp