Hysteresis modeling of Magneto-Rheological (MR) fluid damper by self tuning fuzzy control

Magneto-rheological (MR) fluid damper is a semi-active control device that has recently received more attention by the vibration control community. But inherent nonlinear hysteresis character of magneto-rheological fluid dampers is one of the challenging aspects for utilizing this device to achieve high system performance. So the development of accurate model is necessary to take the advantage their unique characteristics. Research by others [3] has shown that a system of nonlinear differential equations can successfully be used to describe the hysteresis behavior of the MR damper. The focus of this paper is to develop an alternative method for modeling a damper in the form of centre average fuzzy interference system, where back propagation learning rules are used to adjust the weight of network. The inputs for the model are used from the experimental data. The resulting fuzzy interference system is satisfactorily represents the behavior of the MR fluid damper with reduced computational requirements. Use of the neuro-fuzzy model increases the feasibility of real time simulation.

Test and evaluation system for multi-protocol sampled value protection schemes

Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

The relative impact of work-related stress, life stress and driving environment stress on driving outcomes

Previous research has shown the association between stress and crash involvement. The impact of stress on road safety may also be mediated by behaviours including cognitive lapses, errors, and intentional traffic violations. This study aimed to provide a further understanding of the impact that stress from different sources may have upon driving behaviour and road safety. It is asserted that both stress extraneous to the driving environment and stress directly elicited by driving must be considered part of a dynamic system that may have a negative impact on driving behaviours. Two hundred and forty-seven public sector employees from Queensland, Australia, completed self-report measures examining demographics, subjective work-related stress, daily hassles, and aspects of general mental health. Additionally, the Driver Behaviour Questionnaire (DBQ) and the Driver Stress Inventory (DSI) were administered. All participants drove for work purposes regularly, however the study did not specifically focus on full-time professional drivers. Confirmatory factor analysis of the predictor variables revealed three factors: DSI negative affect; DSI risk taking; and extraneous influences (daily hassles, work-related stress, and general mental health). Moderate intercorrelations were found between each of these factors confirming the ‘spillover’ effect. That is, driver stress is reciprocally related to stress in other domains including work and domestic life. Structural equation modelling (SEM) showed that the DSI negative affect factor influenced both lapses and errors, whereas the DSI risk-taking factor was the strongest influence on violations. The SEMs also confirmed that daily hassles extraneous to the driving environment may influence DBQ lapses and violations independently. Accordingly, interventions may be developed to increase driver awareness of the dangers of excessive emotional responses to both driving events and daily hassles (e.g. driving fast to ‘blow off steam’ after an argument). They may also train more effective strategies for self-regulation of emotion and coping when encountering stressful situations on the road.

Leveraging R&D investment for the Australian built environment

This paper discusses a current research project building new understandings and knowledge relevant to R&D funding strategies in Australia. Building on a retrospective analysis of R&D trends and industry outcomes, an industry roadmap will be developed to inform R&D policies more attuned to future industry needs to improve research investment effectiveness. The project will also include analysis of research team formation and management (involving end users from public and private sectors together with research and knowledge institutions), and dissemination of outcomes and uptake in the Australian building and construction industry. The project will build on previous research extending open innovation system theory and network analysis and procurement, focused on R&D. Through the application of dynamic capabilities and strategic foresighting theory, an industry roadmap for future research investment will be developed, providing a stronger foundation for more targeted policy recommendations. This research will contribute to more effective construction processes in the future through more targeted research funding and more effective research partnerships between industry and researchers.

Porphyromonas gingivalis lipopolysaccharide alters atherosclerotic-related gene expression in oxidized low-density-lipoprotein-induced macrophages and foam cells

The molecular mechanism between atherosclerosis formation and periodontal pathogens is not clear although positive correlation between periodontal infections and cardiovascular diseases has been reported. Objective: To determine if atherosclerosis related genes were affected in foam cells during and after its formation by P. gingivalis lipopolysaccharide (LPS) stimulation. Methods: Macrophages from human THP-1 monocytes were treated with oxidized low density lipoprotein (oxLDL) to induce the formation of foam cells. P. gingivalis LPS was added to cultures of either oxLDL-induced macrophages or foam cells. The expression of atherosclerosis related genes was assayed by quantitative real time PCR and the protein production of granulocyte-macrophage colony-stimulating factor（GM-CSF）, monocyte chemotactic protein-1 (MCP-1), IL-1β, IL-10 and IL-12 was determined by ELISA. Nuclear translocation of NF-κB P65 was detected by immunocytochemistry and western blot was used to evaluate IKB-α degradation to confirm the NF-κB pathway activation. Results: P. gingivalis LPS stimulated atherosclerosis related gene expression in foam cells and increased oxLDL induced expression of chemokines, adhesion molecules, growth factors, apoptotic genes, and nuclear receptors in macrophages. Transcription of the pro-inflammatory cytokines IL-1β and IL-12 was elevated in response to LPS in both macrophages and foam cells, whereas the anti-inflammatory cytokine IL-10 was not affected. Increased NF-κB pathway activation was also observed in LPS and oxLDL co-stimulated macrophages. Conclusion: P. gingivalis LPS appears to be an important factor in the development of atherosclerosis by stimulation of atherosclerosis related gene expression in both macrophages and foam cells via activation of the NF-κB pathway.

Expression pattern of Oct-4, Sox2, and c-Myc in the primary culture of human dental pulp derived cells

Dental pulp cells (DPCs) have shown promising potential in dental tissue repair and regeneration. However, during in vitro culture, these cells undergo replicative senescence and result in significant alteration in cell proliferation and differentiation. Recently, the transcription factors of Oct-4, Sox2, c-Myc, and Klf4 have been reported to play a regulatory role in the stem cell self-renewal process, namely cell reprogramming. Therefore, it is interesting to know whether the replicative senescence during the culture of dental pulp cells is related to the diminishing of the expression of these transcription factors. In this study, we investigated the expression of the reprogramming markers Oct-4, Sox2, and c-Myc in the in vitro explant cultured dental pulp tissues and explant cultured dental pulp cells (DPCs) at various passages by immunofluorescence staining and real-time polymerase chain reaction analysis. Our results demonstrated that Oct-4, Sox2, and c-Myc translocated from nucleus in the first 2 passages to cytoplasm after the third passage in explant cultured DPCs. The mRNA expression of Oct-4, Sox2, and c-Myc elevated significantly over the first 2 passages, peaked at second passage (P < .05), and then decreased along the number of passages afterwards (P < .05). For the first time we demonstrated that the expression of reprogramming markers Oct-4, Sox2, and c-Myc was detectable in the early passaged DPCs, and the sequential loss of these markers in the nucleus during DPC cultures might be related to the cell fate of dental pulp derived cells during the long-term in vitro cultivation under current culture conditions.

Hylaluronan-based heparin-incorporated hydrogels for generation of axially vascularized bioartificial bone tissues : in vitro and in vivo evaluation in a PLDLLA-TCP-PCL-composite system

Smart matrices are required in bone tissueengineered grafts that provide an optimal environment for cells and retain osteo-inductive factors for sustained biological activity. We hypothesized that a slow-degrading heparin-incorporated hyaluronan (HA) hydrogel can preserve BMP-2; while an arterio–venous (A–V) loop can support axial vascularization to provide nutrition for a bioartificial bone graft. HA was evaluated for osteoblast growth and BMP-2 release. Porous PLDLLA–TCP–PCL scaffolds were produced by rapid prototyping technology and applied in vivo along with HA-hydrogel, loaded with either primary osteoblasts or BMP-2. A microsurgically created A–V loop was placed around the scaffold, encased in an isolation chamber in Lewis rats. HA-hydrogel supported growth of osteoblasts over 8 weeks and allowed sustained release of BMP-2 over 35 days. The A–V loop provided an angiogenic stimulus with the formation of vascularized tissue in the scaffolds. Bone-specific genes were detected by real time RT-PCR after 8 weeks. However, no significant amount of bone was observed histologically. The heterotopic isolation chamber in combination with absent biomechanical stimulation might explain the insufficient bone formation despite adequate expression of bone-related genes. Optimization of the interplay of osteogenic cells and osteo-inductive factors might eventually generate sufficient amounts of axially vascularized bone grafts for reconstructive surgery.

Participation index : improved measure of transport related social exclusion?

Although transport related social exclusion has been identified through zonal accessibility measures in the recent past, the debate has shifted from zonal to individual level measures. One way to identify disadvantaged individuals is to measure their size of participation in society (activity spaces). After reviewing existing literature, this paper has found two approaches to measure the activity spaces. One approach is based on the time-geographic potential path area (PPA) concept. The size of the PPA has largely been used as an indicator to the size of potential activity spaces and consequently individual accessibility. The limitations of the PPA concept have been identified in this paper and it is argued cannot be applied as a measure of social exclusion. The other approach is based on individuals’ actual travel activity participation called actual activity spaces. The size of actual activity spaces possesses a good potential measure of social exclusion. However, the indicators to measure the size of actual activity spaces are multidimensional representing the different aspects of social exclusion. The development of a unified approach has therefore been found to be important. This paper has developed a participation index (PI) using the different dimensions of actual activity spaces encountered. A framework has also been developed to operationalise the concept in GIS. The framework, on the one hand, will visualize individuals’ actual travel behaviour in real geographic space; on the other hand, it will calculate the size of their participation in society.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

Industry school partnerships : real world learning through the Gateway Schools Projects

In the last decade, a gradual but significant shift in education has taken place. Schools have transformed from hermetically sealed, impermeable bureaucracies to dynamic and flexible organisations characterised by openness to local communities and connectedness to global issues and cultures. They are also more responsive to the aspirations of students and parents. A central feature of what Christian Maroy (2009) has described as the post bureaucratic era of education has been the relationships formed between schools and other organisations through formalised partnerships. Partnerships have been a significant feature of schooling in Queensland since the 1980s when schools developed Vocational Education Programs (VET) providing alternative pathways from schooling to post school training or employment. However, partnerships that have emerged in recent times have been more structured in their organisation and more targeted in terms of the outcomes they aim to achieve. Examples here have included Queensland’s District Youth Achievement plans that linked schools, business, industry bodies, training organisations and community groups to improve transition outcomes, particularly for young people at risk in their transitions from school to post-school life.

Service-learning within higher education : rhizomatic interconnections between university and the real world

This paper discusses Service-learning within an Australian higher education context as pedagogy to teach about inclusive education. Using Deleuze and Guattari’s (1987) model of the rhizome, this study conceptualises pre-service teachers’ learning experiences as multiple, hydra and continuous. Data from reflection logs of pre-service teachers highlight how the learning experience allowed them to gain insights in knowledge as socially just, ethical and inclusive. The paper concludes by arguing the need to consider Service-learning as integral to university education for pre-service teachers.

A grouping model for distributed pipeline assets maintenance decision

Distributed pipeline assets systems are crucial to society. The deterioration of these assets and the optimal allocation of limited budget for their maintenance correspond to crucial challenges for water utility managers. Decision makers should be assisted with optimal solutions to select the best maintenance plan concerning available resources and management strategies. Much research effort has been dedicated to the development of optimal strategies for maintenance of water pipes. Most of the maintenance strategies are intended for scheduling individual water pipe. Consideration of optimal group scheduling replacement jobs for groups of pipes or other linear assets has so far not received much attention in literature. It is a common practice that replacement planners select two or three pipes manually with ambiguous criteria to group into one replacement job. This is obviously not the best solution for job grouping and may not be cost effective, especially when total cost can be up to multiple million dollars. In this paper, an optimal group scheduling scheme with three decision criteria for distributed pipeline assets maintenance decision is proposed. A Maintenance Grouping Optimization (MGO) model with multiple criteria is developed. An immediate challenge of such modeling is to deal with scalability of vast combinatorial solution space. To address this issue, a modified genetic algorithm is developed together with a Judgment Matrix. This Judgment Matrix is corresponding to various combinations of pipe replacement schedules. An industrial case study based on a section of a real water distribution network was conducted to test the new model. The results of the case study show that new schedule generated a significant cost reduction compared with the schedule without grouping pipes.

Blackboard as an online learning environment : what do teacher education students and staff think?

Abstract: As online learning environments now have an established presence in higher education we need to ask the question: How effective are these environments for student learning? Online environments can provide a different type of learning experience than traditional face-to-face contexts (for on-campus students) or print-based materials (for distance learners). This article identifies teacher education student and staff perceptions of teaching and learning using the online learning management system, Blackboard. Perceptions of staff and students are compared and implications for teacher education staff interested in providing high quality learning environments within an online space are discussed.

Resident-funded retirement village valuations : complications with the application of the DCF

Retirement village assets are different from traditional residential assets due to their operation in accordance with statutory legislation. Designed for independent living, retirement villages provide either detached or semi-detached residential dwellings with car parking and small private yards with community facilities providing a shared congregational area for village activities and socialising. In essence, the village operator provides the land and buildings to the residents who pay an amount on entry for the right of occupation. On departure from the units an agreed proportion of either the original purchase price or the sale price is paid to the outgoing resident. As ongoing levies are typically offset by ongoing operational expenses the market value of the operator's interest in the retirement village is therefore predominantly based upon the estimated future income from deferred management fees and capital gain upon roll-over receivable by the operator in accordance with the respective residency agreements. Given the lumpiness of these payments, there is general acceptance that the most appropriate approach to valuation is through discounted cash flow (DCF) analysis. There is however inconsistency between valuers across Australia in how they undertake their DCF analysis, leading to differences in reported values and subsequent confusion among users of valuation services. To give guidance to valuers and enhance confidence from users of valuation services this paper investigates the five major elements of DCF methodology, namely cash flows, escalation factors, holding period, terminal value and discount rate.

Using virtual worlds for collaborative business process modeling

Purpose Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. In this paper we suggest a 3D environment for collaborative process modeling, using Virtual World technology. Design/methodology/approach We suggest a new collaborative process modeling approach based on Virtual World technology. We describe the design of an innovative prototype collaborative process modeling approach, implemented as a 3D BPMN modeling environment in Second Life. We use a case study to evaluate the suggested approach. Findings Based on our case study application, we show that our approach increases user empowerment and adds significantly to the collaboration and consensual development of process models even when the relevant stakeholders are geographically dispersed. Research limitations implications – We present design work and a case study. More research is needed to more thoroughly evaluate the presented approach in a variety of real-life process modeling settings. Practical implications Our research outcomes as design artifacts are directly available and applicable by business process management professionals and can be used by business, system and process analysts in real-world practice. Originality/value Our research is the first reported attempt to develop a process modeling approach on the basis of virtual world technology. We describe a novel and innovative 3D BPMN modeling environment in Second Life.