Focal brachytherapy treatment planning using multi-parametric MRI and biological dose optimisation

We describe a novel approach to treatment planning for focal brachytherapy utilizing a biologically based inverse optimization algorithm and biological imaging to target an ablative dose at known regions of significant tumour burden and a lower, therapeutic dose to low risk regions.

Trust and strong ties in the selection and evaluation of business advisors by small firms

Principal Topic A small firm is unlikely to possess internally the full range of knowledge and skills that it requires or could benefit from for the development of its business. The ability to acquire suitable external expertise - defined as knowledge or competence that is rare in the firm and acquired from the outside - when needed thus becomes a competitive factor in itself. Access to external expertise enables the firm to focus on its core competencies and removes the necessity to internalize every skill and competence. However, research on how small firms access external expertise is still scarce. The present study contributes to this under-developed discussion by analysing the role of trust and strong ties in the small firm's selection and evaluation of sources of external expertise (henceforth referred to as the 'business advisor' or 'advisor'). Granovetter (1973, 1361) defines the strength of a network tie as 'a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding) and the reciprocal services which characterize the tie'. Strong ties in the context of the present investigation refer to sources of external expertise who are well known to the owner-manager, and who may be either informal (e.g., family, friends) or professional advisors (e.g., consultants, enterprise support officers, accountants or solicitors). Previous research has suggested that strong and weak ties have different fortes and the choice of business advisors could thus be critical to business performance) While previous research results suggest that small businesses favour previously well known business advisors, prior studies have also pointed out that an excessive reliance on a network of well known actors might hamper business development, as the range of expertise available through strong ties is limited. But are owner-managers of small businesses aware of this limitation and does it matter to them? Or does working with a well-known advisor compensate for it? Hence, our research model first examines the impact of the strength of tie on the business advisor's perceived performance. Next, we ask what encourages a small business owner-manager to seek advice from a strong tie. A recent exploratory study by Welter and Kautonen (2005) drew attention to the central role of trust in this context. However, while their study found support for the general proposition that trust plays an important role in the choice of advisors, how trust and its different dimensions actually affect this choice remained ambiguous. The present paper develops this discussion by considering the impact of the different dimensions of perceived trustworthiness, defined as benevolence, integrity and ability, on the strength of tie. Further, we suggest that the dimensions of perceived trustworthiness relevant in the choice of a strong tie vary between professional and informal advisors. Methodology/Key Propositions Our propositions are examined empirically based on survey data comprising 153 Finnish small businesses. The data are analysed utilizing the partial least squares (PLS) approach to structural equation modelling with SmartPLS 2.0. Being non-parametric, the PLS algorithm is particularly well-suited to analysing small datasets with non-normally distributed variables. Results and Implications The path model shows that the stronger the tie, the more positively the advisor's performance is perceived. Hypothesis 1, that strong ties will be associated with higher perceptions of performance is clearly supported. Benevolence is clearly the most significant predictor of the choice of a strong tie for external expertise. While ability also reaches a moderate level of statistical significance, integrity does not have a statistically significant impact on the choice of a strong tie. Hence, we found support for two out of three independent variables included in Hypothesis 2. Path coefficients differed between the professional and informal advisor subsamples. The results of the exploratory group comparison show that Hypothesis 3a regarding ability being associated with strong ties more pronouncedly when choosing a professional advisor was not supported. Hypothesis 3b arguing that benevolence is more strongly associated with strong ties in the context of choosing an informal advisor received some support because the path coefficient in the informal advisor subsample was much larger than in the professional advisor subsample. Hypothesis 3c postulating that integrity would be more strongly associated with strong ties in the choice of a professional advisor was supported. Integrity is the most important dimension of trustworthiness in this context. However, integrity is of no concern, or even negative, when using strong ties to choose an informal advisor. The findings of this study have practical relevance to the enterprise support community. First of all, given that the strength of tie has a significant positive impact on the advisor's perceived performance, this implies that small business owners appreciate working with advisors in long-term relationships. Therefore, advisors are well advised to invest into relationship building and maintenance in their work with small firms. Secondly, the results show that, especially in the context of professional advisors, the advisor's perceived integrity and benevolence weigh more than ability. This again emphasizes the need to invest time and effort into building a personal relationship with the owner-manager, rather than merely maintaining a professional image and credentials. Finally, this study demonstrates that the dimensions of perceived trustworthiness are orthogonal with different effects on the strength of tie and ultimately perceived performance. This means that entrepreneurs and advisors should consider the specific dimensions of ability, benevolence and integrity, rather than rely on general perceptions of trustworthiness in their advice relationships.

Linking early design decisions across multiple disciplines

The early stages of the building design process are when the most far reaching decisions are made regarding the configuration of the proposed project. This paper examines methods of providing decision support to building designers across multiple disciplines during the early stage of design. The level of detail supported is at the massing study stage where the basic envelope of the project is being defined. The block outlines on the building envelope are sliced into floors. Within a floor the only spatial divisions supported are the “user” space and the building core. The building core includes vertical transportation systems, emergency egress and vertical duct runs. The current focus of the project described in the paper is multi-storey mixed use office/residential buildings with car parking. This is a common type of building in redevelopment projects within and adjacent to the central business districts of major Australian cities. The key design parameters for system selection across the major systems in multi-storey building projects - architectural, structural, HVAC, vertical transportation, electrical distribution, fire protection, hydraulics and cost – are examined. These have been identified through literature research and discussions with building designers from various disciplines. This information is being encoded in decision support tools. The decision support tools communicate through a shared database to ensure that the relevant information is shared across all of the disciplines. An internal data model has been developed to support the very early design phase and the high level system descriptions required. A mapping to IFC 2x2 has also been defined to ensure that this early information is available at later stages of the design process.

A review on reliability models with covariates

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semi-parametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

The explicit hazard model – part 1: theoretical development

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

The Explicit Hazard Model – Part 2 : Applications

Hazard and reliability prediction of an engineering asset is one of the significant fields of research in Engineering Asset Health Management (EAHM). In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset can be influenced and/or indicated by different factors that are termed as covariates. The Explicit Hazard Model (EHM) as a covariate-based hazard model is a new approach for hazard prediction which explicitly incorporates both internal and external covariates into one model. EHM is an appropriate model to use in the analysis of lifetime data in presence of both internal and external covariates in the reliability field. This paper presents applications of the methodology which is introduced and illustrated in the theory part of this study. In this paper, the semi-parametric EHM is applied to a case study so as to predict the hazard and reliability of resistance elements on a Resistance Corrosion Sensor Board (RCSB).

Mining trading partners’ preferences for efficient multi-issue bargaining in E‑business

Classical negotiation models are weak in supporting real-world business negotiations because these models often assume that the preference information of each negotiator is made public. Although parametric learning methods have been proposed for acquiring the preference information of negotiation opponents, these methods suffer from the strong assumptions about the specific utility function and negotiation mechanism employed by the opponents. Consequently, it is difficult to apply these learning methods to the heterogeneous negotiation agents participating in e‑marketplaces. This paper illustrates the design, development, and evaluation of a nonparametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. According to our empirical testing, the novel knowledge discovery method can speed up the negotiation processes while maintaining negotiation effectiveness. To the best of our knowledge, this is the first nonparametric negotiation knowledge discovery method developed and evaluated in the context of multi-issue bargaining over e‑marketplaces.

Temperature enhanced effects of ozone on cardiovascular mortality in 95 large US communities, 1987-2000 - assessment using the NMMAPS data

A few studies examined interactive effects between air pollution and temperature on health outcomes. This study is to examine if temperature modified effects of ozone and cardiovascular mortality in 95 large US cities. A nonparametric and a parametric regression models were separately used to explore interactive effects of temperature and ozone on cardiovascular mortality during May and October, 1987-2000. A Bayesian meta-analysis was used to pool estimates. Both models illustrate that temperature enhanced the ozone effects on mortality in the northern region, but obviously in the southern region. A 10-ppb increment in ozone was associated with 0.41 % (95% posterior interval (PI): -0.19 %, 0.93 %), 0.27 % (95% PI: -0.44 %, 0.87 %) and 1.68 % (95% PI: 0.07 %, 3.26 %) increases in daily cardiovascular mortality corresponding to low, moderate and high levels of temperature, respectively. We concluded that temperature modified effects of ozone, particularly in the northern region.

Behaviour and design of cold-formed steel compression members at elevated temperatures

Cold-formed steel members have been widely used in residential, industrial and commercial buildings as primary load bearing structural elements and non-load bearing structural elements (partitions) due to their advantages such as higher strength to weight ratio over the other structural materials such as hot-rolled steel, timber and concrete. Cold-formed steel members are often made from thin steel sheets and hence they are more susceptible to various buckling modes. Generally short columns are susceptible to local or distortional buckling while long columns to flexural or flexural-torsional buckling. Fire safety design of building structures is an essential requirement as fire events can cause loss of property and lives. Therefore it is essential to understand the fire performance of light gauge cold-formed steel structures under fire conditions. The buckling behaviour of cold-formed steel compression members under fire conditions is not well investigated yet and hence there is a lack of knowledge on the fire performance of cold-formed steel compression members. Current cold-formed steel design standards do not provide adequate design guidelines for the fire design of cold-formed steel compression members. Therefore a research project based on extensive experimental and numerical studies was undertaken at the Queensland University of Technology to investigate the buckling behaviour of light gauge cold-formed steel compression members under simulated fire conditions. As the first phase of this research, a detailed review was undertaken on the mechanical properties of light gauge cold-formed steels at elevated temperatures and the most reliable predictive models for mechanical properties and stress-strain models based on detailed experimental investigations were identified. Their accuracy was verified experimentally by carrying out a series of tensile coupon tests at ambient and elevated temperatures. As the second phase of this research, local buckling behaviour was investigated based on the experimental and numerical investigations at ambient and elevated temperatures. First a series of 91 local buckling tests was carried out at ambient and elevated temperatures on lipped and unlipped channels made of G250-0.95, G550-0.95, G250-1.95 and G450-1.90 cold-formed steels. Suitable finite element models were then developed to simulate the experimental conditions. These models were converted to ideal finite element models to undertake detailed parametric study. Finally all the ultimate load capacity results for local buckling were compared with the available design methods based on AS/NZS 4600, BS 5950 Part 5, Eurocode 3 Part 1.2 and the direct strength method (DSM), and suitable recommendations were made for the fire design of cold-formed steel compression members subject to local buckling. As the third phase of this research, flexural-torsional buckling behaviour was investigated experimentally and numerically. Two series of 39 flexural-torsional buckling tests were undertaken at ambient and elevated temperatures. The first series consisted 2800 mm long columns of G550-0.95, G250-1.95 and G450-1.90 cold-formed steel lipped channel columns while the second series contained 1800 mm long lipped channel columns of the same steel thickness and strength grades. All the experimental tests were simulated using a suitable finite element model, and the same model was used in a detailed parametric study following validation. Based on the comparison of results from the experimental and parametric studies with the available design methods, suitable design recommendations were made. This thesis presents a detailed description of the experimental and numerical studies undertaken on the mechanical properties and the local and flexural-torsional bucking behaviour of cold-formed steel compression member at ambient and elevated temperatures. It also describes the currently available ambient temperature design methods and their accuracy when used for fire design with appropriately reduced mechanical properties at elevated temperatures. Available fire design methods are also included and their accuracy in predicting the ultimate load capacity at elevated temperatures was investigated. This research has shown that the current ambient temperature design methods are capable of predicting the local and flexural-torsional buckling capacities of cold-formed steel compression members at elevated temperatures with the use of reduced mechanical properties. However, the elevated temperature design method in Eurocode 3 Part 1.2 is overly conservative and hence unsuitable, particularly in the case of flexural-torsional buckling at elevated temperatures.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Flexural behaviour and design of cold-formed steel beams with rectangular hollow flanges

Until recently, the hot-rolled steel members have been recognized as the most popular and widely used steel group, but in recent times, the use of cold-formed high strength steel members has rapidly increased. However, the structural behavior of light gauge high strength cold-formed steel members characterized by various buckling modes is not yet fully understood. The current cold-formed steel sections such as C- and Z-sections are commonly used because of their simple forming procedures and easy connections, but they suffer from certain buckling modes. It is therefore important that these buckling modes are either delayed or eliminated to increase the ultimate capacity of these members. This research is therefore aimed at developing a new cold-formed steel beam with two torsionally rigid rectangular hollow flanges and a slender web formed using intermittent screw fastening to enhance the flexural capacity while maintaining a minimum fabrication cost. This thesis describes a detailed investigation into the structural behavior of this new Rectangular Hollow Flange Beam (RHFB), subjected to flexural action The first phase of this research included experimental investigations using thirty full scale lateral buckling tests and twenty two section moment capacity tests using specially designed test rigs to simulate the required loading and support conditions. A detailed description of the experimental methods, RHFB failure modes including local, lateral distortional and lateral torsional buckling modes, and moment capacity results is presented. A comparison of experimental results with the predictions from the current design rules and other design methods is also given. The second phase of this research involved a methodical and comprehensive investigation aimed at widening the scope of finite element analysis to investigate the buckling and ultimate failure behaviours of RHFBs subjected to flexural actions. Accurate finite element models simulating the physical conditions of both lateral buckling and section moment capacity tests were developed. Comparison of experimental and finite element analysis results showed that the buckling and ultimate failure behaviour of RHFBs can be simulated well using appropriate finite element models. Finite element models simulating ideal simply supported boundary conditions and a uniform moment loading were also developed in order to use in a detailed parametric study. The parametric study results were used to review the current design rules and to develop new design formulae for RHFBs subjected to local, lateral distortional and lateral torsional buckling effects. Finite element analysis results indicate that the discontinuity due to screw fastening has a noticeable influence only for members in the intermediate slenderness region. Investigations into different combinations of thicknesses in the flange and web indicate that increasing the flange thickness is more effective than web thickness in enhancing the flexural capacity of RHFBs. The current steel design standards, AS 4100 (1998) and AS/NZS 4600 (1996) are found sufficient to predict the section moment capacity of RHFBs. However, the results indicate that the AS/NZS 4600 is more accurate for slender sections whereas AS 4100 is more accurate for compact sections. The finite element analysis results further indicate that the current design rules given in AS/NZS 4600 is adequate in predicting the member moment capacity of RHFBs subject to lateral torsional buckling effects. However, they were inadequate in predicting the capacities of RHFBs subject to lateral distortional buckling effects. This thesis has therefore developed a new design formula to predict the lateral distortional buckling strength of RHFBs. Overall, this thesis has demonstrated that the innovative RHFB sections can perform well as economically and structurally efficient flexural members. Structural engineers and designers should make use of the new design rules and the validated existing design rules to design the most optimum RHFB sections depending on the type of applications. Intermittent screw fastening method has also been shown to be structurally adequate that also minimises the fabrication cost. Product manufacturers and builders should be able to make use of this in their applications.

Design of Mono-symmetric LiteSteel Beam Floor Joists with Web Openings

The new cold-formed LiteSteel beam (LSB) sections have found increasing popularity in residential, industrial and commercial buildings due to their lightweight and cost-effectiveness. They have the beneficial characteristics of including torsionally rigid rectangular flanges combined with economical fabrication processes. Currently there is significant interest in using LSB sections as flexural members in floor joist systems. When used as floor joists, the LSB sections require holes in the web to provide access for inspection and various services. But there are no design methods that provide accurate predictions of the moment capacities of LSBs with web holes. In this study, the buckling and ultimate strength behaviour of LSB flexural members with web holes was investigated in detail by using a detailed parametric study based on finite element analyses with an aim to develop appropriate design rules and recommendations for the safe design of LSB floor joists. Moment capacity curves were obtained using finite element analyses including all the significant behavioural effects affecting their ultimate member capacity. The parametric study produced the required moment capacity curves of LSB section with a range of web hole combinations and spans. A suitable design method for predicting the ultimate moment capacity of LSB with web holes was finally developed. This paper presents the details of this investigation and the results

Dynamics deflection analysis of nanoelectromechanical switches based on carbon nanotubes

This paper aims to develop an effective numerical simulation technique for the dynamic deflection analysis of nanotubes-based nanoswitches. The nanoswitch is simplified to a continuum structure, and some key material parameters are extracted from typical molecular dynamics (MD). An advanced local meshless formulation is applied to obtain the discretized dynamic equations for the numerical solution. The developed numerical technique is firstly validated by the static deflection analyses of nanoswitches, and then, the fundamental dynamic properties of nanoswitches are analyzed. A parametric comparison with the results in the literature and from experiments shows that the developed modelling approach is accurate, efficient and effective.

Adaptation to global warming by changing internal loads of buildings

Global warming can have a significant impact on the building thermal environment and energy performance. Because greenhouse gas concentrations are still continuing to increase, this warming process will continue and may accelerate. Adaptation to global warming is therefore emerging as one of the key requirements for buildings. This requires all the existing and new buildings not only to perform and operate satisfactorily in the new environment but also to satisfy the environmental performance criteria of sustainability. Through a parametric study using the building simulation technique, this paper investigates the adaptation potential of changing the building internal load densities to the future global warming. Case studies for office buildings in major Australian capital cities are presented. Based on the results of parametric study, possible adaptation strategies are also proposed and evaluated.

Modeling videokeratoscopic height data with spherical harmonics

Purpose: All currently considered parametric models used for decomposing videokeratoscopy height data are viewercentered and hence describe what the operator sees rather than what the surface is. The purpose of this study was to ascertain the applicability of an object-centered representation to modeling of corneal surfaces. Methods: A three-dimensional surface decomposition into a series of spherical harmonics is considered and compared with the traditional Zernike polynomial expansion for a range of videokeratoscopic height data. Results: Spherical harmonic decomposition led to significantly better fits to corneal surfaces (in terms of the root mean square error values) than the corresponding Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters, and model orders. Conclusions: Spherical harmonic decomposition is a viable alternative to Zernike polynomial decomposition. It achieves better fits to videokeratoscopic height data and has the advantage of an object-centered representation that could be particularly suited to the analysis of multiple corneal measurements.