Exploring context-awareness in the construction logistics services delivery

Managing a construction project supply chain effectively and efficiently is extremely difficult due to involvement of numerous sectors that are supported by ineffective communication system. An efficient construction supply chain system ensures the delivery of materials and other services to construction site while minimising costs and rewarding all sectors based on value added to the supply chain. The advancement of information, communication and wireless technologies is driving construction companies to deploy supply chain management strategies to seek better outputs. As part of the emerging wireless technologies, contextaware computing capability represents the next generation of ICT to the construction services. Conceptually, context-awareness could be integrated with Web Services in order to ensure the delivery of pertinent information to construction site and enhance construction supply chain collaboration. An initial study has indicated that this integrated system has the potential of serving and improving the construction services delivery through access to context-specific data, information and services on as-needed basis.

An entropy-based financial decision support system (e-FDSS) for project analysis in construction SMEs

Uncertainty contributes a major part in the accuracy of a decision-making process while its inconsistency is always difficult to be solved by existing decision-making tools. Entropy has been proved to be useful to evaluate the inconsistency of uncertainty among different respondents. The study demonstrates an entropy-based financial decision support system called e-FDSS. This integrated system provides decision support to evaluate attributes (funding options and multiple risks) available in projects. Fuzzy logic theory is included in the system to deal with the qualitative aspect of these options and risks. An adaptive genetic algorithm (AGA) is also employed to solve the decision algorithm in the system in order to provide optimal and consistent rates to these attributes. Seven simplified and parallel projects from a Hong Kong construction small and medium enterprise (SME) were assessed to evaluate the system. The result shows that the system calculates risk adjusted discount rates (RADR) of projects in an objective way. These rates discount project cash flow impartially. Inconsistency of uncertainty is also successfully evaluated by the use of the entropy method. Finally, the system identifies the favourable funding options that are managed by a scheme called SME Loan Guarantee Scheme (SGS). Based on these results, resource allocation could then be optimized and the best time to start a new project could also be identified throughout the overall project life cycle.

Learner strategies and self-efficacy: making the connection

This article reports on part of a larger study of the impact of strategy training in listening on learners of French, aged 16 to 17. One aim of the project was to investigate whether such training might have a positive effect on the self-efficacy of learners, by helping them see the relationship between the strategies they employed and what they achieved. One group of learners, as well as receiving strategy training, also received detailed feedback on their listening strategy use and on the reflective diaries they were asked to keep, in order to draw their attention to the relationship between strategies and learning outcomes. Another group received strategy training without feedback or reflective diaries, while a comparison group received neither strategy training nor feedback. As a result of the training, there was some evidence that students who had received feedback had made the biggest gains in certain aspects of self-efficacy for listening; although their gains as compared to the non-feedback group were not as great as had been anticipated. Reasons for this are discussed. The article concludes by suggesting changes in how teachers approach listening comprehension that may improve learners' view of themselves as listeners.

Carbohydrate-based micelle clusters which enhance hydrophobic drug bioavailability by up to 1 order of magnitude

Amphiphilic chitosan-based polymers (M-w < 20 kDa) self-assemble in aqueous media at low micromolar concentrations to give previously unknown micellar clusters of 100-300 nm in size. Micellar clusters comprise smaller 10-30 nm aggregates, and the nanopolarity/drug incorporation efficiency of their hydrophobic domains can be tailored by varying the degree of lipidic derivatization and molecular weight of the carbohydrate. The extent of drug incorporation by these novel micellar clusters is 1 order of magnitude higher than is seen with triblock copolymers, with molar polymer/drug ratios of 1:48 to 1:67. On intravenous injection, the pharmacodynamic activity of a carbohydrate propofol formulation is increased by 1 order of magnitude when compared to a commercial emulsion formulation, and on topical ocular application of a carbohydrate prednisolone formulation, initial drug aqueous humor levels are similar to those found with a 10-fold dose of prednisolone suspension.

Self-exclusion from health care in women at high risk for postpartum depression

Background A significant proportion of women who are vulnerable to postnatal depression refuse to engage in treatment programmes. Little is known about them, other than some general demographic characteristics. In particular, their access to health care and their own and their infants' health outcomes are uncharted. Methods We conducted a nested cohort case-control study, using data from computerized health systems, and general practitioner (GP) and maternity records, to identify the characteristics, health service contacts, and maternal and infant health outcomes for primiparous antenatal clinic attenders at high risk for postnatal depression who either refused (self-exclusion group) or else agreed (take-up group) to receive additional Health Visiting support in pregnancy and the first 2 months postpartum. Results Women excluding themselves from Health Visitor support were younger and less highly educated than women willing to take up the support. They were less likely to attend midwifery, GP and routine Health Visitor appointments, but were more likely to book in late and to attend accident and emergency department (A&E). Their infants had poorer outcome in terms of gestation, birthweight and breastfeeding. Differences between the groups still obtained when age and education were taken into account for midwifery contacts, A&E attendance and gestation;the difference in the initiation of breast feeding was attenuated, but not wholly explained, by age and education. Conclusion A subgroup of psychologically vulnerable childbearing women are at particular risk for poor access to health care and adverse infant outcome. Barriers to take-up of services need to be understood in order better to deliver care.

Fast kernel classifier construction using orthogonal forward selection to minimise leave-one-out misclassification rate

We propose a simple yet computationally efficient construction algorithm for two-class kernel classifiers. In order to optimise classifier's generalisation capability, an orthogonal forward selection procedure is used to select kernels one by one by minimising the leave-one-out (LOO) misclassification rate directly. It is shown that the computation of the LOO misclassification rate is very efficient owing to orthogonalisation. Examples are used to demonstrate that the proposed algorithm is a viable alternative to construct sparse two-class kernel classifiers in terms of performance and computational efficiency.

A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate

We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class classifiers in terms of performance and computational efficiency.

Articulation of information requirements for personalised knowledge and construction

The quality of information provision influences considerably knowledge construction driven by individual users’ needs. In the design of information systems for e-learning, personal information requirements should be incorporated to determine a selection of suitable learning content, instructive sequencing for learning content, and effective presentation of learning content. This is considered as an important part of instructional design for a personalised information package. The current research reveals that there is a lack of means by which individual users’ information requirements can be effectively incorporated to support personal knowledge construction. This paper presents a method which enables an articulation of users’ requirements based on the rooted learning theories and requirements engineering paradigms. The user’s information requirements can be systematically encapsulated in a user profile (i.e. user requirements space), and further transformed onto instructional design specifications (i.e. information space). These two spaces allow the discovering of information requirements patterns for self-maintaining and self-adapting personalisation that enhance experience in the knowledge construction process.

Compression of polymer brushes: quantitative comparison of self-consistent field theory with experiment

The self-consistent field theory (SCFT) prediction for the compression force between two semi-dilute polymer brushes is compared to the benchmark experiments of Taunton et al. [Nature, 1988, 332, 712]. The comparison is done with previously established parameters, and without any fitting parameters whatsoever. The SCFT provides a significant quantitative improvement over the classical strong-stretching theory (SST), yielding excellent quantitative agreement with the experiment. Contrary to earlier suggestions, chain fluctuations cannot be ignored for normal experimental conditions. Although the analytical expressions of SST provide invaluable aids to understanding the qualitative behavior of polymeric brushes, the numerical SCFT is necessary in order to provide quantitatively accurate predictions.

Self-assembled healable materials through a combination of pi-pi stacking and hydrogen bonding

The discovery of polymers with stimuli responsive physical properties is a rapidly expanding area of research. At the forefront of the field are self-healing polymers, which, when fractured can regain the mechanical properties of the material either autonomically, or in response to a stimulus. It has long been known that it is possible to promote healing in conventional thermoplastics by heating the fracture zone above the Tg of the polymer under pressure. This process requires reptation and subsequent re-entanglement of macromolecules across the fracture void, which serves to bridge, and ‘heal’ the crack. The timescale for this mechanism is highly dependent on the molecular weight of the polymer being studied. This process is in contrast to that required to affect healing in supramolecular polymers such as the plasticised, hydrogen bonded elastomer reported by Leibler et al. The disparity in bond energies between the non-covalent and covalent bonds within supramolecular polymers results in fractures propagating through scission of the comparatively weak supramolecular interactions, rather than through breaking the stronger, covalent bonds. Thus, during the healing process the macromolecules surrounding the fracture site only need sufficient energy to re-engage their supramolecular interactions in order to regenerate the strength of the pristine material. Herein we describe the design, synthesis and optimization of a new class of supramolecular polymer blends that harness the reversible nature of pi-pi stacking and hydrogen bonding interactions to produce self-supporting films with facile healable characteristics.

Exporting construction professional services in a global service economy

Globalisation has prompted increasing numbers of construction profes-sional services (CPS) firms to internationalise and export their services. The driver has been twofold; firstly to increase turnover/profits and sec-ondly, to minimise the risk of a reliance on working in a single domestic market which has a fluctuating demand. Secondly, where firms have out-grown their domestic market, and in order to expand, they must export overseas. There has been little research into the way CPS firms operate overseas, yet construction represents approximately 10% of global GDP; this means that understanding CPS firms is important. This paper investigates how CPS firms internationalise and the drivers that impact their decisions and operations overseas. A survey was undertaken and interviews conducted that showed CPS firms are project driven, in-vesting heavily in the process of seeking work/bidding for projects, and are very focused on delivering projects with minimum risk. Increasing foreign ownership, changing procurement approaches and more consolidation of CPS firms in the global marketplace present a changing business land-scape. The research develops a framework of tangible and intangible factors, such as competencies, business organisation culture, leadership and reputation in order to better understand how CPS firms export their ser-vices. Whilst all CPS firms share the same framework of factors, the re-sulting synergies are different not only for each firm but also for each pro-ject. The knowledge-intensive and project-based nature of CPS firms presents a challenge in understanding the way they operate in the global service economy.

Reduced-order modelling of a high-voltage oscillatory impulse generator

The design of high-voltage equipment encompasses the study of oscillatory surges caused by transients such as those produced by switching. By obtaining a model, the response of which reconstructs that observed in the actual system, simulation studies and critical tests can be carried out on the model rather than on the equipment itself. In this paper, methods for the construction of simplified models are described and it is shown how the use of a complex model does not necessarily result in superior response pattern reconstruction.

Self-organising neural networks for adaptive control

Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

Using self-organising feature maps for the control of artificial organisms

Variations on the standard Kohonen feature map can enable an ordering of the map state space by using only a limited subset of the complete input vector. Also it is possible to employ merely a local adaptation procedure to order the map, rather than having to rely on global variables and objectives. Such variations have been included as part of a hybrid learning system (HLS) which has arisen out of a genetic-based classifier system. In the paper a description of the modified feature map is given, which constitutes the HLSs long term memory, and results in the control of a simple maze running task are presented, thereby demonstrating the value of goal related feedback within the overall network.