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.

Sensors and imaging for wound healing : a review

Wound healing involves a complex series of biochemical events and has traditionally been managed with 'low tech' dressings and bandages. The concept that diagnostic and theranostic sensors can complement wound management is rapidly growing in popularity as there is tremendous potential to apply this technology to both acute and chronic wounds. Benefits in sensing the wound environment include reduction of hospitalization time, prevention of amputations and better understanding of the processes which impair healing. This review discusses the state-of-the-art in detection of markers associated with wound healing and infection, utilizing devices imbedded within dressings or as point-of-care techniques to allow for continual or rapid wound assessment and monitoring. Approaches include using biological or chemical sensors of wound exudates and volatiles to directly or indirectly detect bacteria, monitor pH, temperature, oxygen and enzymes. Spectroscopic and imaging techniques are also reviewed as advanced wound monitoring techniques. The review concludes with a discussion of the limitations of and future directions for this field.

Modeling resource management in the building design process by information constraint Petri nets

The effect of resource management on the building design process directly influences the development cycle time and success of construction projects. This paper presents the information constraint net (ICN) to represent the complex information constraint relations among design activities involved in the building design process. An algorithm is developed to transform the information constraints throughout the ICN into a Petri net model. A resource management model is developed using the ICN to simulate and optimize resource allocation in the design process. An example is provided to justify the proposed model through a simulation analysis of the CPN Tools platform in the detailed structural design. The result demonstrates that the proposed approach can obtain the resource management and optimization needed for shortening the development cycle and optimal allocation of resources.

Preliminary insights from a multiple case study on process modelling impact

Process modelling – the design and use of graphical documentations of an organisation’s business processes – is a key method to document and use information about business processes in organisational projects. Still, despite current interest in process modelling, this area of study still faces essential challenges. One of the key unanswered questions concerns the impact of process modelling in organisational practice. Process modelling initiatives call for tangible results in the form of returns on the substantial investments that organisations undertake to achieve improved processes. This study explores the impact of process model use on end-users and its contribution to organisational success. We posit that the use of conceptual models creates impact in organisational process teams. We also report on a set of case studies in which we explore tentative evidence for the development of impact of process model use. The results of this work provide a better understanding of process modelling impact from information practices and also lead to insights into how organisations should conduct process modelling initiatives in order to achieve an optimum return on their investment.

Advanced numerical characterization of silicon with defect by nanoindentation

Nano silicon is widely used as the essential element of complementary metal–oxide–semiconductor (CMOS) and solar cells. It is recognized that today, large portion of world economy is built on electronics products and related services. Due to the accessible fossil fuel running out quickly, there are increasing numbers of researches on the nano silicon solar cells. The further improvement of higher performance nano silicon components requires characterizing the material properties of nano silicon. Specially, when the manufacturing process scales down to the nano level, the advanced components become more and more sensitive to the various defects induced by the manufacturing process. It is known that defects in mono-crystalline silicon have significant influence on its properties under nanoindentation. However, the cost involved in the practical nanoindentation as well as the complexity of preparing the specimen with controlled defects slow down the further research on mechanical characterization of defected silicon by experiment. Therefore, in current study, the molecular dynamics (MD) simulations are employed to investigate the mono-crystalline silicon properties with different pre-existing defects, especially cavities, under nanoindentation. Parametric studies including specimen size and loading rate, are firstly conducted to optimize computational efficiency. The optimized testing parameters are utilized for all simulation in defects study. Based on the validated model, different pre-existing defects are introduced to the silicon substrate, and then a group of nanoindentation simulations of these defected substrates are carried out. The simulation results are carefully investigated and compared with the perfect Silicon substrate which used as benchmark. It is found that pre-existing cavities in the silicon substrate obviously influence the mechanical properties. Furthermore, pre-existing cavities can absorb part of the strain energy during loading, and then release during unloading, which possibly causes less plastic deformation to the substrate. However, when the pre-existing cavities is close enough to the deformation zone or big enough to exceed the bearable stress of the crystal structure around the spherical cavity, the larger plastic deformation occurs which leads the collapse of the structure. Meanwhile, the influence exerted on the mechanical properties of silicon substrate depends on the location and size of the cavity. Substrate with larger cavity size or closer cavity position to the top surface, usually exhibits larger reduction on Young’s modulus and hardness.

Detecting approximate clones in process model repositories with Apromore

Approximate clone detection is the process of identifying similar process fragments in business process model collections. The tool presented in this paper can efficiently cluster approximate clones in large process model repositories. Once a repository is clustered, users can filter and browse the clusters using different filtering parameters. Our tool can also visualize clusters in the 2D space, allowing a better understanding of clusters and their member fragments. This demonstration will be useful for researchers and practitioners working on large process model repositories, where process standardization is a critical task for increasing the consistency and reducing the complexity of the repository.

Risk factors to predict the incidence of surgical adverse events following open or laparoscopic surgery for apparent early stage endometrial cancer: results from a randomised controlled trial

Aims: To identify risk factors for major Adverse Events (AEs) and to develop a nomogram to predict the probability of such AEs in individual patients who have surgery for apparent early stage endometrial cancer. Methods: We used data from 753 patients who were randomized to either total laparoscopic hysterectomy or total abdominal hysterectomy in the LACE trial. Serious adverse events that prolonged hospital stay or postoperative adverse events (using common terminology criteria 3+, CTCAE V3) were considered major AEs. We analyzed pre-surgical characteristics that were associated with the risk of developing major AEs by multivariate logistic regression. We identified a parsimonious model by backward stepwise logistic regression. The six most significant or clinically important variables were included in the nomogram to predict the risk of major AEs within 6 weeks of surgery and the nomogram was internally validated. Results: Overall, 132 (17.5%) patients had at least one major AE. An open surgical approach (laparotomy), higher Charlson’s medical co-morbidities score, moderately differentiated tumours on curettings, higher baseline ECOG score, higher body mass index and low haemoglobin levels were associated with AE and were used in the nomogram. The bootstrap corrected concordance index of the nomogram was 0.63 and it showed good calibration. Conclusions: Six pre-surgical factors independently predicted the risk of major AEs. This research might form the basis to develop risk reduction strategies to minimize the risk of AEs among patients undergoing surgery for apparent early stage endometrial cancer.

Performance analysis of IEC 61850 sampled value process bus networks

Process bus networks are the next stage in the evolution of substation design, bringing digital technology to the high voltage switchyard. Benefits of process buses include facilitating the use of Non-Conventional Instrument Transformers, improved disturbance recording and phasor measurement and the removal of costly, and potentially hazardous, copper cabling from substation switchyards and control rooms. This paper examines the role a process bus plays in an IEC 61850 based Substation Automation System. Measurements taken from a process bus substation are used to develop an understanding of the network characteristics of "whole of substation" process buses. The concept of "coherent transmission" is presented and the impact of this on Ethernet switches is examined. Experiments based on substation observations are used to investigate in detail the behavior of Ethernet switches with sampled value traffic. Test methods that can be used to assess the adequacy of a network are proposed, and examples of the application and interpretation of these tests are provided. Once sampled value frames are queued by an Ethernet switch the additional delay incurred by subsequent switches is minimal, and this allows their use in switchyards to further reduce communications cabling, without significantly impacting operation. The performance and reliability of a process bus network operating with close to the theoretical maximum number of digital sampling units (merging units or electronic instrument transformers) was investigated with networking equipment from several vendors, and has been demonstrated to be acceptable.

Reaching high-risk adolescents : a process evaluation of a school based injury prevention program

High-risk adolescents are a population most vulnerable to harm from injury due to increased engagement in risk taking behaviour. There is a gap in the literature regarding how universal school based injury prevention programs apply to high-risk adolescents. This study involves a component of the process evaluation of a school based injury prevention program, as it relates to high-risk adolescents (13-14 years)...

Characterisation of sugarcane juice particles that influence the clarification process

Problems associated with processing whole sugarcane crop can be minimised by removing impurities during the clarification stage. As a first step, it is important to understand the colloidal chemistry of juice particles on a molecular level to assist development of strategies for effective clarification performance. This paper presents the composition and surface characteristics of colloidal particles originating from various juice types by using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), X-ray photoelectron spectroscopy(XPS) and zeta potential measurements. The composition and surface characteristics of colloidal juice particles are reported. The results indicate that there are three types of colloidal particles present, viz. an aluminosilicatecompound, silica and iron oxide, with the latter two being abundant. Proteins, polysaccharides and organic acids were identified on the surface of particles in juice. The overall particle charge varies from -2 mV to -6 mV. In comparison to juice expressed from burnt cane, the zeta potential values were more negative with juice particles originating from whole crop. This in part explains why these juices are difficult to clarify.

Cultural fitness for business process management : what is it and what is it worth?

While business process management (BPM) is often associated with large investments in IT systems and process analysis projects, the success of BPM initiatives largely depends on the cultural readiness of organizations for process management. In this article, we introduce a model that helps to understand the role of culture in managing business processes and to take the right investments into the development of organizational culture. For that purpose, we also describe an assessment tool that allows examining the supportiveness of an organizational culture for BPM initiatives. We show how the results of such an assessment help organizations to determine in which areas of a corporation investments in cultural change can be most beneficial.

Nitrous oxide emissions from subtropical horticultural soils : a time series analysis

Time series regression models were used to examine the influence of environmental factors (soil water content and soil temperature) on the emissions of nitrous oxide (N2O) from subtropical soils, by taking into account temporal lagged environmental factors, autoregressive processes, and seasonality for three horticultural crops in a subtropical region of Australia. Fluxes of N2O, soil water content, and soil temperature were determined simultaneously on a weekly basis over a 12-month period in South East Queensland. Annual N2O emissions for soils under mango, pineapple, and custard apple were 1590, 1156, and 2038 g N2O-N/ha, respectively, with most emissions attributed to nitrification. The N2O-N emitted from the pineapple and custard apple crops was equivalent to 0.26 and 2.22%, respectively, of the applied mineral N. The change in soil water content was the key variable for describing N2O emissions at the weekly time-scale, with soil temperature at a lag of 1 month having a significant influence on average N2O emissions (averaged) at the monthly time-scale across the three crops. After accounting for soil temperature and soil water content, both the weekly and monthly time series regression models exhibited significant autocorrelation at lags of 1–2 weeks and 1–2 months, and significant seasonality for weekly N2O emissions for mango crop and for monthly N2O emissions for mango and custard apple crops in this location over this time-frame. Time series regression models can explain a higher percentage of the temporal variation of N2O emission compared with simple regression models using soil temperature and soil water content as drivers. Taking into account seasonal variability and temporal persistence in N2O emissions associated with soil water content and soil temperature may lead to a reduction in the uncertainty surrounding estimates of N2O emissions based on limited sampling effort.

Modeling heat and mass transfer process during convection drying of fruit

Fruit drying is a process of removing moisture to preserve fruits by preventing microbial spoilage. It increases shelf life, reduce weight and volume thus minimize packing, storage, and transportation cost and enable storage of food under ambient environment. But, it is a complex process which involves combination of heat and mass transfer and physical property change and shrinkage of the material. In this background, the aim of this paper to develop a mathematical model to simulate coupled heat and mass transfer during convective drying of fruit. This model can be used predict the temperature and moisture distribution inside the fruits during drying. Two models were developed considering shrinkage dependent and temperature dependent moisture diffusivity and the results were compared. The governing equations of heat and mass transfer are solved and a parametric study has been done with Comsol Multiphysics 4.3. The predicted results were validated with experimental data.

Building sustainable and effective assurance of learning process in a changing higher education environment

In a study of assuring learning in Australian Business Schools, 25 Teaching and Learning Associate Deans were interviewed to identify current issues in developing and measuring the quality of teaching and learning outcomes. Results indicate that for most institutions developing a perspective on graduate attributes and mapping assessments to measure outcomes across an entire program required knowledge creation and the building of new inclusive processes. Common elements of effective practice, namely those which offered consistently superior outcomes, included: inclusive processes; embedded graduate attributes throughout a program; alongside consistent and appropriate assessment. Results indicate that assurance of learning processes are proliferating nationally while quality of teaching and learning outcomes and in the processes for assuring it is increasing as a result.

Understanding process behaviours in a large insurance company in Australia : a case study

Having a reliable understanding about the behaviours, problems, and performance of existing processes is important in enabling a targeted process improvement initiative. Recently, there has been an increase in the application of innovative process mining techniques to facilitate evidence-based understanding about organizations' business processes. Nevertheless, the application of these techniques in the domain of finance in Australia is, at best, scarce. This paper details a 6-month case study on the application of process mining in one of the largest insurance companies in Australia. In particular, the challenges encountered, the lessons learned, and the results obtained from this case study are detailed. Through this case study, we not only validated existing `lessons learned' from other similar case studies, but also added new insights that can be beneficial to other practitioners in applying process mining in their respective fields.