Nonlinear model structure design and construction using orthogonal least squares and D-optimality design

A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model robustness and adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the model subset selection cost function includes a D-optimality design criterion that maximizes the determinant of the design matrix of the subset to ensure the model robustness, adequacy, and parsimony of the final model. The proposed approach is based on the forward orthogonal least square (OLS) algorithm, such that new D-optimality-based cost function is constructed based on the orthogonalization process to gain computational advantages and hence to maintain the inherent advantage of computational efficiency associated with the conventional forward OLS approach. Illustrative examples are included to demonstrate the effectiveness of the new approach.

The automatic layout model in the sequencing of construction activities of multi-objective diaphragm wall unit by using self-learning neural network

Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.

The future of lean construction: a brave new world

Lean construction is considered from a human resource management (HRM) perspective. It is contended that the UK construction sector is characterised by an institutionalised regressive approach to HRM. In the face of rapidly declining recruitment rates for built environment courses, the dominant HRM philosophy of utilitarian instrumentalism does little to attract the intelligent and creative young people that the industry so badly needs. Given this broader context, there is a danger that an uncritical acceptance of lean construction will exacerbate the industry's reputation for unrewarding jobs. Construction academics have strangely ignored the extensive literature that equates lean production to a HRM regime of control, exploitation and surveillance. The emphasis of lean thinking on eliminating waste and improving efficiency makes it easy to absorb into the best practice agenda because it conforms to the existing dominant way of thinking. 'Best practice' is seemingly judged by the extent to which it serves the interests of the industry's technocratic elite. Hence it acts as a conservative force in favour of maintaining the status quo. In this respect, lean construction is the latest manifestation of a long established trend. In common with countless other improvement initiatives, the rhetoric is heavy in the machine metaphor whilst exhorting others to be more efficient. If current trends in lean construction are extrapolated into the future the ultimate destination may be uncomfortably close to Aldous Huxley's apocalyptic vision of a Brave New World. In the face of these trends, the lean construction research community pleads neutrality whilst confining its attention to the rational high ground. The future of lean construction is not yet predetermined. Many choices remain to be made. The challenge for the research community is to improve practice whilst avoiding the dehumanising tendencies of high utilitarianism.

Re-thinking stakeholder management in construction: theory & research

From its roots in strategic management theory, stakeholder management has been adopted by the construction management academic community and applied as a valid paradigm around which research work has been generated aiming to improve project effi ciencies and effectiveness. However, academics have argued that stakeholder management should move away from purely theoretical discussions and engage more with the realities of construction project work. This paper re-appraises the stakeholder management concept for the construction domain by re-thinking some of the fundamental principles and ideals present within the more general stakeholder theory literature. It engages with issues which researchers have arguably failed to acknowledge and calls for a re-evaluation of construction stakeholder management research by presenting a review around four distinctive themes: the moral obligations of engaging with stakeholders against the business and efficiency driven imperatives of construction organisations; the contrast between theoretical abstractions and empirically grounded research; the tensions between theoretical convergence versus calls for multiple and divergent perspectives on stakeholder management and the practicalities of conducting stakeholder management in the construction domain. Such a critical re-appraisal of stakeholder management thinking both generates new lines of enquiry and promises to help inform and shape current and future industry practice.

Motivational factors impacting the productivity of construction master craftsmen in Kuwait

In today's global economic conditions, improving the productivity of the construction industry is becoming more pressing than ever. Several factors impact the efficiency of construction operatives, but motivation is among the most important. Since low productivity is one of the significant challenges facing the construction industry in the State of Kuwait, the objective of this case study is to identify, explore, and rank the relative importance of the factors perceived to impact the motivational level of master craftsmen involved in primary construction trades. To achieve this objective, a structured questionnaire survey comprising 23 factors, which were shortlisted based on relevant previous research on motivation, the input of local industry experts, and numerous interviews with skilled operatives, was distributed to a large number of master craftsmen. Using the “Relative Importance Index” technique, the following prominent factors are identified: (1) payment delay; (2) rework; (3) lack of a financial incentive scheme; (4) the extent of change orders during execution; (5) incompetent supervisors; (6) delays in responding to Requests For Information (RFI); (7) overcrowding and operatives interface; (8) unrealistic scheduling and performance expectation; (9) shortage of materials on site; and (10) drawings quality level. The findings can be used to provide industry practitioners with guidance for focusing, acting upon, and controlling the critical factors influencing the performance of master craftsmen, hence, assist in achieving an efficient utilization of the workforce, and a reasonable level of competitiveness and cost effective operation.

Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

Auto ID-Bridging the physical and the digital on construction projects

This book looks at how auto-ID has evolved and how it can be used in the construction industry and across projects from the perspective of all the stakeholders, from owners to design consultants, contractors and the supply chain. It could help to improve efficiency, reduce costs, ensure quality, protect the environment, and enhance safety.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.

Validation of the use of input-output data for embodied energy analysis of the Australian construction industry

This paper evaluates a recently developed hybrid method for the embodied energy analysis of the Australian construction industry. It was found that the truncation associated with process analysis can be up to 80%, whilst the use of input-output analysis alone does not always provide a perfect model for replacing process data. There is also a considerable lack in the quantity and possibly quality of process data currently available. These findings suggest that current best-practice methods are sufficiently accurate for most typical applications, but this is heavily dependant upon data quality and availability. The hybrid method evaluated can be used for the optimisation of embodied energy and for identifying opportunities for improvements in energy efficiency.

The development of a typology for remote construction projects

Remotely located sites have become more accessible and therefore more valuable and profitable to investors and entrepreneurs. Typically these sites are environmentally sensitive. For the designer, these sites offer a unique challenge conceptually, in terms of the physical and cultural constraints. The built environment research community has yet to seriously take up the challenge of developing theoretical models for the management of the design and construction processes for remotely located projects. Such models would explore efficiency and efficacy management for projects in remote and often hostile areas, in an integrated and sustainable manner. There are varying degrees of remoteness experienced in nearly all construction projects and therefore a clearer definition of the characteristics of remote sites is required. Towards this definition, a typology is initiated for the concept of remotely located construction projects related to environmental sustainability and the management of the design process. The characteristics of the typology are drawn from a selected literature review of the fields of design management and environmental sustainability, and from an exploratory investigation of two case studies.

A comprehensive framework for assessing the life cycle energy of building construction assemblies

Environmental decision making during the building design process has typically focused on improvements to operational efficiencies. Improvements to thermal performance and efficiency of appliances and systems within buildings both aim to reduce resource consumption and environmental impacts associated with the operation of buildings. Significant reductions in building energy and water consumption are possible; however often the impacts occurring across the other stages of a building‘s life are not considered or are seen as insignificant in comparison.

Previous research shows that embodied impacts (raw material extraction, processing, manufacture, transportation and construction) can be as significant as those related to building operation. There is, however, limited consistent and comprehensive information available for building designers to make informed decisions in this area. Often the information that is available is from disparate sources, which makes comparison of alternative solutions unreliable and risky. lt is also important that decisions are made from a life cycle perspective, ensuring that strategies to reduce environmental impacts from one life cycle stage do not come at the expense of an increase in overall life cycle impacts

A consistent and comprehensive framework for assessing and specifying building assemblies for enhanced environmental outcomes does not currently exist. This paper presents the initial findings of a project that aims to establish a database of the life cycle energy requirements of a broad range of construction assemblies, based on a comprehensive assessment framework. Life cycle energy requirements have been calculated for eight standard residential construction assemblies integrating an innovative embodied energy assessment technique with thermal performance simulation modelling and ranked according to their performance.

Strategic knowledge for the identification and construction of goal states

There is widespread recognition that goal recognition strategies, in the context of structural analysis and cognitive (user) models, represent a major field of contemporary research into discourse understanding. This thesis reports a goal interpretation paradigm that embraces both a novel goal structure formalism and strategic knowledge. The goal interpretation processes involve the identification of goal primitives and the construction of goal states. The mechanisms developed for goal interpretation rely on explicit goal recognition (selection) and confirmation of feasibility. A goal state contains all the information required by the planner. By constructing a goal state, the chance of failure in planning is greatly reduced and the efficiency of the planning system is vastly improved. These mechanisms are not limited to inference. Other mechanisms are reported include goal structure processing, goal primitives identification and searching strategies, extended heuristic classification method and a new conceptual graph operation (i.e. SPLIT).

A critical analysis of techniques for risk mitigation in the construction industry

Risks exist in every form of construction project. The risks associated with construction projects are often diverse and varied and the management of these risks is nowadays considered compulsory in order to achieve project success. This paper analyses the diverse strategies of risk mitigation that have been employed in construction projects. These strategies are classified into analysed categories of procurement strategies. contingency and co-operative approach along with the utilisation of a designated risk manager. The analysis showed that in order to improve risk mitigation within the construction industry, there is a requirement tor an industry based standard. This standard will improve the efficiency and effectiveness of the risk mitigation response technique to risk management.

Malmquist indices of total factor productivity changes in the Australian construction industry

Construction is an important industry and forms a vital part of national economics in the world. Factors affecting the productivity of the construction industry should be measured appropriately to reflect its development situation and economic performance. The Malmquist index method with a novel decomposition technique is employed to estimate the total factor productivity of the Australian construction industry during the period 1990-2007 and to analyse the factors affecting the technological change in the industry. Research results exemplified by two input variables and one output variable elaborate how construction technology, pure technical efficiency and scale economy take effect in the change of construction productivity. In addition, based on temporal and spatial comparisons, the analysis for construction productivities reveals their changes over time and across the country. Proposals and recommendations are expected to be beneficial for policy making and strategic decisions to improve the performance of the Australian construction industry.

A construction method of Atanassov’s intuitionistic fuzzy sets for image processing

In this work we introduce a new construction method of Atanassov's intuitionistic fuzzy sets (A-IFSs) from fuzzy sets. We use A-IFSs in image processing. We propose a new image magnification algorithm using A-IFSs. This algorithm is characterized by its simplicity and its efficiency.