A dynamic approach to forecast rental growth

Numerous econometric models have been proposed for forecasting property market performance, but limited success has been achieved in finding a reliable and consistent model to predict property market movements over a five to ten year timeframe. This research focuses on office rental growth forecasts and overviews many of the office rent models that have evolved over the past 20 years. A model by DiPasquale and Wheaton is selected for testing in the Brisbane, Australia office market. The adaptation of this study did not provide explanatory variables that could assist in developing a reliable, predictive model of office rental growth. In light of this result, the paper suggests a system dynamics framework that includes an econometric model based on historical data as well as user input guidance for the primary variables. The rent forecast outputs would be assessed having regard to market expectations and probability profiling undertaken for use in simulation exercises. The paper concludes with ideas for ongoing research.

Green buildings for greying people : a case study of a retirement village in Australia

Purpose With an increasingly ageing population and widespread acceptance of the need for sustainable development in Australia, the demand for green retirement villages is increasing. This paper aims to identify the critical issues to be considered by developers and practitioners when embarking on their first green residential retirement project in Australia. Design/methodology/approach In view of the lack of adequate historical data for quantitative analysis, a case study approach is employed to examine the successful delivery of green retirement villages. Face-to-face interviews and document analysis were conducted for data collection. Findings The findings of the study indicate that one of the major obstacles to the provision of affordable green retirement villages is the higher initial costs involved. However, positive aspects were identified, the most significant of which relate to: the innovative design of site and floor plans; adoption of thermally efficient building materials; orientation of windows; installation of water harvesting and recycling systems, water conservation fittings and appliances; and waste management during the construction stage. With the adoption of these measures, it is believed that sustainable retirement development can be achieved without significant additional capital costs. Practical implications The research findings serve as a guide for developers in decision making throughout the project life-cycle when introducing green features into the provision of affordable retirement accommodation. Originality/value This paper provides insights into the means by which affordable green residential retirement projects for aged people can be successfully completed.

A framework for cost-aware process management : generation of accurate and timely management accounting cost reports

Organisations are constantly seeking efficiency improvements for their business processes in terms of time and cost. Management accounting enables reporting of detailed cost of operations for decision making purpose, although significant effort is required to gather accurate operational data. Business process management is concerned with systematically documenting, managing, automating, and optimising processes. Process mining gives valuable insight into processes through analysis of events recorded by an IT system in the form of an event log with the focus on efficient utilisation of time and resources, although its primary focus is not on cost implications. In this paper, we propose a framework to support management accounting decisions on cost control by automatically incorporating cost data with historical data from event logs for monitoring, predicting and reporting process-related costs. We also illustrate how accurate, relevant and timely management accounting style cost reports can be produced on demand by extending open-source process mining framework ProM.

The importance of mosquito behavioural adaptations to malaria control in Africa

Over the past decade the use of long-lasting insecticidal nets (LLINs), in combination with improved drug therapies, indoor residual spraying (IRS) and better health infrastructure, has helped reduce malaria in many African countries for the first time in a generation. However, insecticide resistance in the vector is an evolving threat to these gains. We review emerging and historical data on behavioural resistance in response to LLINs and IRS. Overall the current literature suggests behavioural and species changes may be emerging, but the data are sparse and, at times unconvincing. However, preliminary modelling has demonstrated that behavioural resistance could have significant impacts on the effectiveness of malaria control. We propose seven recommendations to improve understanding of resistance in malaria vectors. Determining the public health impact of physiological and behavioural insecticide resistance is an urgent priority if we are to maintain the significant gains made in reducing malaria morbidity and mortality.

Machine prognostics based on health state estimation using SVM

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 safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an 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. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

Bearing fault prognosis based on health state probability estimation

In condition-based maintenance (CBM), effective diagnostic and prognostic tools are essential for maintenance engineers to identify imminent fault and predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedule of production if necessary. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of bearings based on health state probability estimation and historical knowledge embedded in the closed loop diagnostics and prognostics system. The technique uses the Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation process to provide long term prediction. To validate the feasibility of the proposed model, real life fault historical data from bearings of High Pressure-Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life (RUL). The results obtained were very encouraging and showed that the proposed prognosis system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

A framework for cost-aware process management : cost reporting and cost prediction

Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.

First flush behaviour in urban residential catchments

The current state of knowledge in relation to first flush does not provide a clear understanding of the role of rainfall and catchment characteristics in influencing this phenomenon. This is attributed to the inconsistent findings from research studies due to the unsatisfactory selection of first flush indicators and how first flush is defined. The research study discussed in this thesis provides the outcomes of a comprehensive analysis on the influence of rainfall and catchment characteristics on first flush behaviour in residential catchments. Two sets of first flush indicators are introduced in this study. These indicators were selected such that they are representative in explaining in a systematic manner the characteristics associated with first flush. Stormwater samples and rainfall-runoff data were collected and recorded from stormwater monitoring stations established at three urban catchments at Coomera Waters, Gold Coast, Australia. In addition, historical data were also used to support the data analysis. Three water quality parameters were analysed, namely, total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The data analyses were primarily undertaken using multi criteria decision making methods, PROMETHEE and GAIA. Based on the data obtained, the pollutant load distribution curve (LV) was determined for the individual rainfall events and pollutant types. Accordingly, two sets of first flush indicators were derived from the curve, namely, cumulative load wash-off for every 10% of runoff volume interval (interval first flush indicators or LV) from the beginning of the event and the actual pollutant load wash-off during a 10% increment in runoff volume (section first flush indicators or P). First flush behaviour showed significant variation with pollutant types. TSS and TP showed consistent first flush behaviour. However, the dissolved fraction of TN showed significant differences to TSS and TP first flush while particulate TN showed similarities. Wash-off of TSS, TP and particulate TN during the first 10% of the runoff volume showed no influence from corresponding rainfall intensity. This was attributed to the wash-off of weakly adhered solids on the catchment surface referred to as "short term pollutants" or "weakly adhered solids" load. However, wash-off after 10% of the runoff volume showed dependency on the rainfall intensity. This is attributed to the wash-off of strongly adhered solids being exposed when the weakly adhered solids diminish. The wash-off process was also found to depend on rainfall depth at the end part of the event as the strongly adhered solids are loosened due to impact of rainfall in the earlier part of the event. Events with high intensity rainfall bursts after 70% of the runoff volume did not demonstrate first flush behaviour. This suggests that rainfall pattern plays a critical role in the occurrence of first flush. Rainfall intensity (with respect to the rest of the event) that produces 10% to 20% runoff volume play an important role in defining the magnitude of the first flush. Events can demonstrate high magnitude first flush when the rainfall intensity occurring between 10% and 20% of the runoff volume is comparatively high while low rainfall intensities during this period produces low magnitude first flush. For events with first flush, the phenomenon is clearly visible up to 40% of the runoff volume. This contradicts the common definition that first flush only exists, if for example, 80% of the pollutant mass is transported in the first 30% of runoff volume. First flush behaviour for TN is different compared to TSS and TP. Apart from rainfall characteristics, the composition and the availability of TN on the catchment also play an important role in first flush. The analysis confirmed that events with low rainfall intensity can produce high magnitude first flush for the dissolved fraction of TN, while high rainfall intensity produce low dissolved TN first flush. This is attributed to the source limiting behaviour of dissolved TN wash-off where there is high wash-off during the initial part of a rainfall event irrespective of the intensity. However, for particulate TN, the influence of rainfall intensity on first flush characteristics is similar to TSS and TP. The data analysis also confirmed that first flush can occur as high magnitude first flush, low magnitude first flush or non existence of first flush. Investigation of the influence of catchment characteristics on first flush found that the key factors that influence the phenomenon are the location of the pollutant source, spatial distribution of the pervious and impervious surfaces in the catchment, drainage network layout and slope of the catchment. This confirms that first flush phenomenon cannot be evaluated based on a single or a limited set of parameters as a number of catchment characteristics should be taken into account. Catchments where the pollutant source is located close to the outlet, a high fraction of road surfaces, short travel time to the outlet, with steep slopes can produce high wash-off load during the first 50% of the runoff volume. Rainfall characteristics have a comparatively dominant impact on the wash-off process compared to the catchment characteristics. In addition, the pollutant characteristics also should be taken into account in designing stormwater treatment systems due to different wash-off behaviour. Analysis outcomes confirmed that there is a high TSS load during the first 20% of the runoff volume followed by TN which can extend up to 30% of the runoff volume. In contrast, high TP load can exist during the initial and at the end part of a rainfall event. This is related to the composition of TP available for the wash-off.

Comparison of historic exploration with contemporary space policy suggests a retheorisation of settings

The 2008 NASA Astrobiology Roadmap provides one way of theorising this developing field, a way which has become the normative model for the discipline: science-and scholarship-driven funding for space. By contrast, a novel re-evaluation of funding policies is undertaken in this article to reframe astrobiology, terraforming and associated space travel and research. Textual visualisation, discourse and numeric analytical methods, and value theory are applied to historical data and contemporary sources to re-investigate significant drivers and constraints on the mechanisms of enabling space exploration. Two data sets are identified and compared: the business objectives and outcomes of major 15th-17th century European joint-stock exploration and trading companies and a case study of a current space industry entrepreneur company. Comparison of these analyses suggests that viable funding policy drivers can exist outside the normative science and scholarship-driven roadmap. The two drivers identified in this study are (1) the intrinsic value of space as a territory to be experienced and enjoyed, not just studied, and (2) the instrumental, commercial value of exploiting these experiences by developing infrastructure and retail revenues. Filtering of these results also offers an investment rationale for companies operating in, or about to enter, the space business marketplace.

Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.

Evaluation of the performance of a dengue outbreak detection tool for China

An outbreak detection and response system, using time series moving percentile method based on historical data, in China has been used for identifying dengue fever outbreaks since 2008. For dengue fever outbreaks reported from 2009 to 2012, this system achieved a sensitivity of 100%, a specificity of 99.8% and a median time to detection of 3 days, which indicated that the system was a useful decision tool for dengue fever control and risk-management programs in China.

An efficient DSE using conditional multivariate complex Gaussian distribution

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.

Risedronate in adults with osteogenesis imperfecta type I: Increased bone mineral density and decreased bone turnover, but high fracture rate persists

Summary Bisphosphonates can increase bone mineral density (BMD) in children with osteogenesis imperfecta (OI). In this study of adults with OI type I, risedronate increased BMD at lumbar spine (but not total hip) and decreased bone turnover. However, the fracture rate in these patients remained high. Introduction Intravenous bisphosphonates given to children with OI can increase BMD and reduce fracture incidence. Oral and/or intravenous bisphosphonates may have similar effects in adults with OI. We completed an observational study of the effect of risedronate in adults with OI type I. Methods Thirty-two adults (mean age, 39 years) with OI type I were treated with risedronate (total dose, 35 mg weekly) for 24 months. Primary outcome measures were BMD changes at lumbar spine (LS) and total hip (TH). Secondary outcome measures were fracture incidence, bone pain, and change in bone turnover markers (serum procollagen type I aminopropeptide (P1NP) and bone ALP). A meta-analysis of published studies of oral bisphosphonates in adults and children with OI was performed. Results Twenty-seven participants (ten males and seventeen females) completed the study. BMD increased at LS by 3.9% (0.815 vs. 0.846 g/cm 2, p=0.007; mean Z-score, -1.93 vs. -1.58, p=0.002), with no significant change at TH. P1NP fell by 37% (p=0.00041), with no significant change in bone ALP (p=0.15). Bone pain did not change significantly (p=0.6). Fracture incidence remained high, with 25 clinical fractures and 10 major fractures in fourteen participants (0.18 major fractures per person per year), with historical data of 0.12 fractures per person per year. The meta-analysis did not demonstrate a significant difference in fracture incidence in patients with OI treated with oral bisphosphonates. Conclusions Risedronate in adults with OI type I results in modest but significant increases in BMD at LS, and decreased bone turnover. However, this may be insufficient to make a clinically significant difference to fracture incidence.

Teatterinjohtamisen dramaturgiaa : Keskeiset tehtävät, arjen ongelmat ja rakenteelliset muutostarpeet

DRAMATURGY OF THEATRE MANAGEMENT Essential tasks, everyday problems and the need for structural changes Theatre justifies its existence only through high quality performances. Maintaining the artistic level and organizing performances are the primary tasks of a manager, even though in everyday life this often seems to be overshadowed by all the other tasks of a manager s work. How does a theatre manager design strategies and make everyday decisions if aims are to have artistically meaningful performances, financial success and a socially healthy ensemble, when not only artistic work or leadership of an organization are to be taken into consideration, but also a manpower-based art institution with long traditions? What does theatre management consist of and what kind of dramaturgical movement happens in it? Based on interviews carried out in five different city theatres in Finland in the years 2004-2008, incident stories were written within a continuous comparison theory frame. Social constructionism within a dramaturgic framework enabled versatile dialog on a manager s work and problem areas. The result is an interpretative study, where instead of common regularities, many details are collected that can be taken into consideration when similar situations occur. Based on the interviews and historical data, four factors that influence a manager s work were chosen: ownership, media, work community and programme. Within theatre management, the central problems were 1) the inconsistent use of theatre resources and problems in corporate governance caused by the administrative models; 2) the theatre s image, based on the image of its manager, as presented by the media and its influence on the wellbeing of the staff; 3) unsolved problems between the staff left behind by the previous managers and problems related to casting; 4) knowledge of the audience. These points influence how the manager plans the artistic programme and divides the resources. The theatre manager s job description has remained quite the same since the early days of Kaarlo Bergbom. In the future, special attention should be placed on why managers face fairly similar problems decade after decade. Reducing these problems partly depends on whether structural improvements are made to a theatre s close network of owners, financers and labour unions. During this study clear evidence was seen that structural changes are necessary in the production of performances and in the creation of a more versatile programme. In this process, different kinds of co-operation, experiments, development projects, continuing education and international relations have special importance, especially if the aim is to make it possible for all citizens of Finland to enjoy a vibrant and revitalized theatre.

Modelling the impact of traffic incidents on travel time reliability

Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.