Developing Software Agents for Data Mining : [AIMM] Agents for Improving Maintenance Management

This report demonstrates the development of: • Development of software agents for data mining • Link data mining to building model in virtual environments • Link knowledge development with building model in virtual environments • Demonstration of software agents for data mining • Populate with maintenance data

Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

Polyurethane (PU) scaffolds prepared by solvent casting/particulate leaching (SCPL) combined with centrifugation

This article reports an enhanced solvent casting/particulate (salt) leaching (SCPL) method developed for preparing three-dimensional porous polyurethane (PU) scaffolds for cardiac tissue engineering. The solvent for the preparation of the PU scaffolds was a mixture of dimethylformamide (DFM) and tetrahydrofuran (THF). The enhanced method involved the combination of a conventional SCPL method and a step of centrifugation, with the centrifugation being employed to improve the pore uniformity and the pore interconnectivity of scaffolds. Highly porous three-dimensional scaffolds with a well interconnected porous structure could be achieved at the polymer solution concentration of up to 20% by air or vacuum drying to remove the solvent. When the salt particle sizes of 212-295, 295-425, or 425-531 µm and a 15% w/v polymer solution concentration were used, the porosity of the scaffolds was between 83-92% and the compression moduli of the scaffolds were between 13 kPa and 28 kPa. Type I collagen acidic solution was introduced into the pores of a PU scaffold to coat the collagen onto the pore walls throughout the whole PU scaffold. The human aortic endothelial cells (HAECs) cultured in the collagen-coated PU scaffold for 2 weeks were observed by scanning electron microscopy (SEM). It was shown that the enhanced SCPL method and the collagen coating resulted in a spatially uniform distribution of cells throughout the collagen-coated PU scaffold.

Industry Partners

AIMM stands for 'Agents for Improved Maintenance Management.' The AIMM system is a prototype tool that has developed the state of the art life cycle modelling of buildings through the linking of a 3D model with maintenance data to allow both the facility manager and the designer to gain access to building maintenance information and knowledge that is currently inaccessible. AIMM integrates data mining agents into the maintenance process to produce timely data for the facility manager on the effects of different maintenance regimes.

Conceptualising value creation for social change management

Australian and international governments are increasingly adopting social marketing as a social change management tool to deal with complex social problems. Government decision makers typically need to balance the use of business models and management theories whilst maintaining the integrity of government policy. In taking this approach, decision makers experience management tensions between a social mission to equitably deliver social services and the accountability and affordability of providing quality social and health services to citizens. This is a significant challenge as the nature of the ‘social product’ in government is often more service-oriented than goods-based. In this paper the authors examine value creation in government social marketing services. The contribution of this paper is a value creation process model, which considers the nature of governments to create social good. This is particularly important for governments where consumers still expect value and quality in the service delivered, despite that offering being ‘free’.

Cyclic strain disrupts endothelial network formation on Matrigel

Most forms of tissue healing depend critically on revascularisation. In soft tissues and in vitro, mechanical stimuli have been shown to promote vessel-forming activity. However, in bone defects, increased interfragmentary motion impairs vascular regeneration. Because these effects seem contradictory, we aimed to determine whether a range of mechanical stimuli exists in which angiogenesis is favoured. A series of cyclic strain magnitudes were applied to a Matrigel-based “tube formation” assay and the total lengths of networks formed by human microvascular endothelial cells measured at 24 h. Network lengths were reduced at all strain levels, compared to unstretched controls. However, the levels of pro-angiogenic matrix metalloproteases-2 and -9 in the corresponding conditioned media were unchanged by strain, and vascular endothelial growth factor was uniformly elevated in stretched conditions. By repeating the assay with the addition of conditioned media from mesenchymal stem cells cultivated in similar conditions, paracrine stimuli were shown to increase network lengths, but not to alter the negative effect of cyclic stretching. Together, these results demonstrate that directly applied periodic strains can inhibit endothelial organisation in vitro, and suggest that this may be due to physical disruption rather than biochemical modulation. Most importantly, the results indicate that the straining of endothelial cells and their assembly into vascular-like structures must be studied simultaneously to adequately characterise the mechanical influence on vessel formation.

Sensitivity of proximal femoral stiffness and areal bone mineral density to changes in bone geometry and density

Areal bone mineral density (aBMD) is the most common surrogate measurement for assessing the bone strength of the proximal femur associated with osteoporosis. Additional factors, however, contribute to the overall strength of the proximal femur, primarily the anatomical geometry. Finite element analysis (FEA) is an effective and widely used computerbased simulation technique for modeling mechanical loading of various engineering structures, providing predictions of displacement and induced stress distribution due to the applied load. FEA is therefore inherently dependent upon both density and anatomical geometry. FEA may be performed on both three-dimensional and two-dimensional models of the proximal femur derived from radiographic images, from which the mechanical stiffness may be redicted. It is examined whether the outcome measures of two-dimensional FEA, two-dimensional, finite element analysis of X-ray images (FEXI), and three-dimensional FEA computed stiffness of the proximal femur were more sensitive than aBMD to changes in trabecular bone density and femur geometry. It is assumed that if an outcome measure follows known trends with changes in density and geometric parameters, then an increased sensitivity will be indicative of an improved prediction of bone strength. All three outcome measures increased non-linearly with trabecular bone density, increased linearly with cortical shell thickness and neck width, decreased linearly with neck length, and were relatively insensitive to neck-shaft angle. For femoral head radius, aBMD was relatively insensitive, with two-dimensional FEXI and threedimensional FEA demonstrating a non-linear increase and decrease in sensitivity, respectively. For neck anteversion, aBMD decreased non-linearly, whereas both two-dimensional FEXI and three dimensional FEA demonstrated a parabolic-type relationship, with maximum stiffness achieved at an angle of approximately 15o. Multi-parameter analysis showed that all three outcome measures demonstrated their highest sensitivity to a change in cortical thickness. When changes in all input parameters were considered simultaneously, three and twodimensional FEA had statistically equal sensitivities (0.41±0.20 and 0.42±0.16 respectively, p = ns) that were significantly higher than the sensitivity of aBMD (0.24±0.07; p = 0.014 and 0.002 for three-dimensional and two-dimensional FEA respectively). This simulation study suggests that since mechanical integrity and FEA are inherently dependent upon anatomical geometry, FEXI stiffness, being derived from conventional two-dimensional radiographic images, may provide an improvement in the prediction of bone strength of the proximal femur than currently provided by aBMD.

Australian Association for Exercise and Sport Science position stand : optimising cancer outcomes through exercise

Cancer represents a major public health concern in Australia. Causes of cancer are multifactorial with lack of physical activity being considered one of the known risk factors, particularly for breast and colorectal cancers. Participating in exercise has also been associated with benefits during and following treatment for cancer, including improvements in psychosocial and physical outcomes, as well as better compliance with treatment regimens, reduced impact of disease symptoms and treatment-related side effects, and survival benefits for particular cancers. The general exercise prescription for people undertaking or having completed cancer treatment is of low to moderate intensity, regular frequency (3-5 times/week) for at least 20 minutes per session, involving aerobic, resistance or mixed exercise types. Future work needs to push the boundaries of this exercise prescription, so that we can better understand what constitutes optimal, desirable and necessary frequency, duration, intensity and type, and how specific characteristics of the individual (e.g., age, cancer type, treatment, presence of specific symptoms) influence this prescription. What follows is a summary of the cancer and exercise literature, in particular the purpose of exercise following diagnosis of cancer, the potential benefits derived by cancer patients and survivors from participating in exercise programs, and exercise prescription guidelines and contraindications or considerations for exercise prescription with this special population. This report represents the position stand of the Australian Association of Exercise and Sport Science on exercise and cancer recovery and has the purpose of guiding Accredited Exercise Physiologists in their work with cancer patients.

How do other people influence your driving speed? Exploring the 'who' and the 'how' of social influences on speeding from a qualitative perspective

Using only legal sanctions to manage the speed at which people drive ignores the potential benefits of harnessing social factors such as the influence of others. Social influences on driver speeds were explored in this qualitative examination of 67 Australian drivers. Focus group interviews with 8 driver types (young, mid-age and older males and females, and self-identified Excessive and Rare speeders) were guided by Akers’ social learning theory (Akers, 1998). Findings revealed two types of influential others: people known to the driver (passengers and parents), and unknown other drivers. Passengers were generally described as having a slowing influence on drivers: responsibility for the safety of people in the car and consideration for passenger comfort were key themes. In contrast, all but the Rare speeders reported increasing their speed when driving alone. Parental role modelling was also described. In relation to other drivers, key themes included speeding to keep up with traffic flow and perceived pressure to drive faster. This ‘pressure’ from others to ‘speed up’ was expressed in all groups and reported strategies for managing this varied. Encouragingly, examples of actual or anticipated social rewards for speeding were less common than examples of social punishments. Three main themes relating to social punishments were embarrassment, breaching the trust of others, and presenting an image of a responsible driver. Impression management and self-presentation are discussed in light of these findings. Overall, our findings indicate scope to exploit the use of social sanctions for speeding and social praise for speed limit compliance to enhance speed management strategies.

Optimizing construction planning schedules by virtual prototyping enabled resource analysis

The inherent uncertainty and complexity of construction work make construction planning a particularly difficult task for project managers due to the need to anticipate and visualize likely future events. Conventional computer-assisted technology can help but is often limited to the constructability issues involved. Virtual prototyping, however, offers an improved method through the visualization of construction activities by computer simulation — enabling a range of ‘what-if’ questions to be asked and their implications on the total project to be investigated. This paper describes the use of virtual prototyping to optimize construction planning schedules by analyzing resource allocation and planning with integrated construction models, resource models, construction planning schedules and site-layout plans. A real-life case study is presented that demonstrates the use of a virtual prototyping enabled resource analysis to reallocate space, logistic on access road and arrange tower cranes to achieve a 6-day floor construction cycle.

(-)-CGP12177 increases contractile force through beta1l-adrenoceptors but not through beta3-adrenoceptors in human right atrial myocardium

(-)-CGP12177 is a non-conventional partial agonist that causes modest and transient increases of contractile force in human atrial trabeculae (Kaumann and Molenaar, 2008). These effects are markedly increased and maintained by inhibition of phosphodiesterase PDE3. As verified with recombinant receptors, the cardiostimulant effect of (-)-CGP12177 is mediated through a site at the beta1-adrenoceptor with lower affinity (beta1LAR) compared to the site through which (-)-CGP12177 antagonizes the effects of catecholamines (beta1HAR). However, in a recent report it was proposed that the positive inotropic effects of CGP12177 are mediated through beta3-adrenoceptors (Skeberdis et al 2008). We therefore investigated whether the effects of (-)-CGP12177 on human atrial trabeculae are antagonized by the beta3-adrenoceptor-selective antagonist L-748,337 (1 microM). (-)-CGP12177 (200 nM) caused a stable increase in force which was significantly reduced by the addition of (-)-bupranolol (1 microM), P = 0.002, (basal 4.45 ± 0.78 mN, IBMX (PDE inhibitor) 5.47 ± 1.01 mN, (-)-CGP12177 9.34 ± 1.33 mN, (-)-bupranolol 5.79 ± 1.08 mN, n = 6) but not affected by the addition of L-748,337 (1 microM), P = 0.12, (basal 4.48 ± 1.32 mN, IBMX 7.15 ± 2.28 mN, (-)-CGP12177 12.51 ± 3.71 mN, L-748,337 10.90 ± 3.49 mN, n = 6). Cumulative concentration-effect curves for (-)-CGP12177 were not shifted to the right by L-748,337 (1 microM). The –logEC50M values of (-)-CGP12177 in the absence and presence of L-748,337 were 7.21±0.09 and 7.41±0.13, respectively (data from 25 trabeculae from 8 patients, P=0.2) The positive inotropic effects of (-)-CGP12177 (IBMX present) were not antagonized by L-748,337 but were blunted by (-)-bupranolol (1 microM). The results rule out an involvement of beta3-adrenoceptors in the positive inotropic effects (-)-CGP12177 in human right atrial myocardium and are consistent with mediation through beta1LAR. Kaumann A and Molenaar P (2008) Pharmacol Ther 118, 303-336 Skeberdis VA et al (2008) J Clin Invest, 118, 3219-3227

Acute compensatory eating following exercise is associated with implicit hedonic wanting for food

The efficacy of exercise to promote weight loss could potentially be undermined by its influence on explicit or implicit processes of liking and wanting for food which in turn alter food preference. The present study was designed to examine hedonic and homeostatic mechanisms involved in the acute effects of exercise on food intake. 24 healthy female subjects were recruited to take part in two counterbalanced activity sessions; 50 min of high intensity (70% max heart rate) exercise (Ex) or no exercise (NEx). Subjective appetite sensations, explicit and implicit hedonic processes, food preference and energy intake (EI) were measured immediately before and after each activity session and an ad libitum test meal. Two groups of subjects were identified in which exercise exerted different effects on compensatory EI and food preference. After exercise, compensators (C) increased their EI, rated the food to be more palatable, and demonstrated increased implicit wanting. Compensators also showed a preference for high-fat sweet food compared with non-compensators (NC), independent of the exercise intervention. Exercise-induced changes in the hedonic response to food could be an important consideration in the efficacy of using exercise as a means to lose weight. An enhanced implicit wanting for food after exercise may help to explain why some people overcompensate during acute eating episodes. Some individuals could be resistant to the beneficial effects of exercise due to a predisposition to compensate for exercise-induced energy expenditure as a result of implicit changes in food preferences.

Motivation, development and validation of a new spectral greenness index : a spectral dimension related to foliage projective cover

A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+ spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three principal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three principal components, of diminishing significance with respect to the reference image, complete the set. The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscapes containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demonstrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greenness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greenness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional-scale predictions of FPC could be gained over those based on spectral indices alone.