Optimising a coal rail network under capacity constraints

This research deals with an innovative methodology for optimising the coal train scheduling problem. Based on our previously published work, generic solution techniques are developed by utilising a “toolbox” of standard well-solved standard scheduling problems. According to our analysis, the coal train scheduling problem can be basically modelled a Blocking Parallel-Machine Job-Shop Scheduling (BPMJSS) problem with some minor constraints. To construct the feasible train schedules, an innovative constructive algorithm called the SLEK algorithm is proposed. To optimise the train schedule, a three-stage hybrid algorithm called the SLEK-BIH-TS algorithm is developed based on the definition of a sophisticated neighbourhood structure under the mechanism of the Best-Insertion-Heuristic (BIH) algorithm and Tabu Search (TS) metaheuristic algorithm. A case study is performed for optimising a complex real-world coal rail system in Australia. A method to calculate the lower bound of the makespan is proposed to evaluate results. The results indicate that the proposed methodology is promising to find the optimal or near-optimal feasible train timetables of a coal rail system under network and terminal capacity constraints.

Scheduling a flow-shop with combined buffer conditions

In this paper, No-Wait, No-Buffer, Limited-Buffer, and Infinite-Buffer conditions for the flow-shop problem (FSP) have been investigated. These four different buffer conditions have been combined to generate a new class of scheduling problem, which is significant for modelling many real-world scheduling problems. A new heuristic algorithm is developed to solve this strongly NP-hard problem. Detailed numerical implementations have been analysed and promising results have been achieved.

Evaluation of the 2010 child restraint legislation in Queensland

Occupant injury comprises the largest proportion of child road crash trauma in most highly motorised countries. In Australia, road crashes are the primary cause of death for children aged 1-14 years and are among the top three causes of serious injury to this age group. For this reason considerable research attention has been focused on understanding the contributing factors and the most effective ways of improving children’s safety as car passengers. Australia has been particularly active in this area, with well regarded work being conducted on levels of use of dedicated child restraints, restraint crash performance in laboratory conditions, examination of real world restraint crash performance (case review), and studies of psychosocial factors influencing perceptions about restraints and their use (Brown & Bilston, 2006; Brown, McCaskill, Henderson & Bilston, 2006; Edwards, Anderson & Hutchinson, 2006; Lennon, 2005, 2007). New legislation for the restraint of children as vehicle passengers was enacted in Queensland in March 2010. This new legislation recognises the importance of dedicated restraint use for children up to at least age 7 years and the protective benefits of rear seating position in the event of a crash. As part of improving children’s safety and addressing key priority areas, the Queensland Injury Prevention Council (QIPC) and Department of Transport and Main Roads (TMR) commissioned the Centre for Accident Research and Road Safety, Queensland (CARRS-Q) to evaluate the impact of the new legislation. Although at the time of commencing the research the legislation had only been in force for 14 months, it was deemed critical to review its effectiveness in guiding parental choices and compliance in order to inform the design and focus of further supporting initiatives and interventions. Specifically, the research sought clear evidence of exactly what impact, if any, the legislation has had on compliance levels and what difficulties (if any) parents/carers experience in relation to interpreting as well as complying with the requirements of the new law. Knowledge about these barriers or difficulties will allow any future changes or improvements to the legislation to address such barriers and thus improve its effectiveness. Moreover, better information about how the legislation has affected parents will provide a basis to plan non-legislative comprehensive multi-strategy interventions such as community, educational or behavioural interventions with parents/carers and other stakeholder groups. In addition, it will allow identification of the most effective aspects of the legislation and those areas in need of extra attention to improve effectiveness/compliance and thus better protect children travelling in cars and improve their health and safety. This report presents the findings from the four components of the research: the literature review; observational study; intercept interviews and focus group with parents; and the interviews with key stakeholders.

Commentary on Spence et al. : "Problem solving programme implemented by teachers may prevent depression in the short term, but longer term benefits are unclear"

This is a methodologically exemplary trial of a population based (universal) approach to preventing depression in young people. The programme used teachers in a classroom setting to deliver cognitive behavioural problem solving skills to a cohort of students. We have little knowledge about “best practice” to prevent depression in adolescence. Classroom-based universal approaches appear to offer advantages in recruitment rates and lack of stigmatisation over approaches that target specific groups of at risk students. Earlier research on a universal school-based approach to preventing depression in adolescents showed promise, but employed mental health professionals to teach cognitive behavioural coping skills in small groups.1 Using such an approach routinely would be economically unsustainable. Spence’s trial, with teachers as facilitators, therefore represents a “real world” intervention that could be routinely disseminated.

Developing a Second Life virtual field trip for university students : an action research approach

Background: Integrating 3D virtual world technologies into educational subjects continues to draw the attention of educators and researchers alike. The focus of this study is the use of a virtual world, Second Life, in higher education teaching. In particular, it explores the potential of using a virtual world experience as a learning component situated within a curriculum delivered predominantly through face-to-face teaching methods. Purpose: This paper reports on a research study into the development of a virtual world learning experience designed for marketing students taking a Digital Promotions course. The experience was a field trip into Second Life to allow students to investigate how business branding practices were used for product promotion in this virtual world environment. The paper discusses the issues involved in developing and refining the virtual course component over four semesters. Methods: The study used a pedagogical action research approach, with iterative cycles of development, intervention and evaluation over four semesters. The data analysed were quantitative and qualitative student feedback collected after each field trip as well as lecturer reflections on each cycle. Sample: Small-scale convenience samples of second- and third-year students studying in a Bachelor of Business degree, majoring in marketing, taking the Digital Promotions subject at a metropolitan university in Queensland, Australia participated in the study. The samples included students who had and had not experienced the field trip. The numbers of students taking part in the field trip ranged from 22 to 48 across the four semesters. Findings and Implications: The findings from the four iterations of the action research plan helped identify key considerations for incorporating technologies into learning environments. Feedback and reflections from the students and lecturer suggested that an innovative learning opportunity had been developed. However, pedagogical potential was limited, in part, by technological difficulties and by student perceptions of relevance.

Complex events in business processes

Flow-oriented process modeling languages have a long tradition in the area of Business Process Management and are widely used for capturing activities with their behavioral and data dependencies. Individual events were introduced for triggering process instantiation and activities. However, real-world business cases drive the need for also covering complex event patterns as they are known in the field of Complex Event Processing. Therefore, this paper puts forward a catalog of requirements for handling complex events in process models, which can be used as reference framework for assessing process definition languages and systems. An assessment of BPEL and BPMN is provided.

Text mining and probabilistic language modeling for online review spam detecting

In the era of Web 2.0, huge volumes of consumer reviews are posted to the Internet every day. Manual approaches to detecting and analyzing fake reviews (i.e., spam) are not practical due to the problem of information overload. However, the design and development of automated methods of detecting fake reviews is a challenging research problem. The main reason is that fake reviews are specifically composed to mislead readers, so they may appear the same as legitimate reviews (i.e., ham). As a result, discriminatory features that would enable individual reviews to be classified as spam or ham may not be available. Guided by the design science research methodology, the main contribution of this study is the design and instantiation of novel computational models for detecting fake reviews. In particular, a novel text mining model is developed and integrated into a semantic language model for the detection of untruthful reviews. The models are then evaluated based on a real-world dataset collected from amazon.com. The results of our experiments confirm that the proposed models outperform other well-known baseline models in detecting fake reviews. To the best of our knowledge, the work discussed in this article represents the first successful attempt to apply text mining methods and semantic language models to the detection of fake consumer reviews. A managerial implication of our research is that firms can apply our design artifacts to monitor online consumer reviews to develop effective marketing or product design strategies based on genuine consumer feedback posted to the Internet.

Trust-based automated recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbours, generated from a database made up of the preferences of past users. With sufficient background information of item ratings, its performance is promising enough but research shows that it performs very poorly in a cold start situation where there is not enough previous rating data. As an alternative to ratings, trust between the users could be used to choose the neighbour for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world "friend of a friend" recommendations. To extend the boundaries of the neighbour, an effective trust inference technique is required. This thesis proposes a trust interference technique called Directed Series Parallel Graph (DSPG) which performs better than other popular trust inference algorithms such as TidalTrust and MoleTrust. Another problem is that reliable explicit trust data is not always available. In real life, people trust "word of mouth" recommendations made by people with similar interests. This is often assumed in the recommender system. By conducting a survey, we can confirm that interest similarity has a positive relationship with trust and this can be used to generate a trust network for recommendation. In this research, we also propose a new method called SimTrust for developing trust networks based on user's interest similarity in the absence of explicit trust data. To identify the interest similarity, we use user's personalised tagging information. However, we are interested in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbours used in the automated recommender system. Our experimental results show that our proposed tag-similarity based method outperforms the traditional collaborative filtering approach which usually uses rating data.

Perceptions of visibility and conspicuity of biomotion clothing configurations for road workers at road work sites

Aims: This study determined whether the visibility benefits of positioning retroreflective strips in biological motion configurations were evident at real world road worker sites. Methods: 20 visually normal drivers (M=40.3 years) participated in this study that was conducted at two road work sites (one suburban and one freeway) on two separate nights. At each site, four road workers walked in place wearing one of four different clothing options: a) standard road worker night vest, b) standard night vest plus retroreflective strips on thighs, c) standard night vest plus retroreflective strips on ankles and knees, d) standard night vest plus retroreflective strips on eight moveable joints (full biomotion). Participants seated in stationary vehicles at three different distances (80m, 160m, 240m) rated the relative conspicuity of the four road workers using a series of a standardized visibility and ranking scales. Results: Adding retroreflective strips in the full biomotion configuration to the standard night vest significantly (p<0.001) enhanced perceptions of road worker visibility compared to the standard vest alone, or in combination with thigh retroreflective markings. These visibility benefits were evident at all distances and at both sites. Retroreflective markings at the ankles and knees also provided visibility benefits compared to the standard vest, however, the full biomotion configuration was significantly better than all of the other configurations. Conclusions: These data provide the first evidence that the benefits of biomotion retroreflective markings that have been previously demonstrated under laboratory and closed- and open-road conditions are also evident at real work sites.

Semantics-based web service discovery using information retrieval techniques

This paper demonstrates an experimental study that examines the accuracy of various information retrieval techniques for Web service discovery. The main goal of this research is to evaluate algorithms for semantic web service discovery. The evaluation is comprehensively benchmarked using more than 1,700 real-world WSDL documents from INEX 2010 Web Service Discovery Track dataset. For automatic search, we successfully use Latent Semantic Analysis and BM25 to perform Web service discovery. Moreover, we provide linking analysis which automatically links possible atomic Web services to meet the complex requirements of users. Our fusion engine recommends a final result to users. Our experiments show that linking analysis can improve the overall performance of Web service discovery. We also find that keyword-based search can quickly return results but it has limitation of understanding users’ goals.

Evolution of traffic management measures on road traffic noise

Road traffic noise affects the quality of life in the areas adjoining the road. The effect of traffic noise on people is wide ranging and may include sleep disturbance and negative impact on work efficiency. To address the problem of traffic noise, it is necessary to estimate the noise level. For this, a number of noise estimation models have been developed which can estimate noise at the receptor points, based on simple configuration of buildings. However, for a real world situation we have multiple buildings forming built-up area. In such a situation, it is almost impossible to consider multiple diffractions and reflections in sound propagation from the source to the receptor point. An engineering solution to such a real world problem is needed to estimate noise levels in built-up area.

Using virtual reality modelling in cultural management, archiving and research

This paper outlines how the Ortelia project’s 3D virtual reality models have the capacity to assist our understanding of sites of cultural heritage. The VR investigation of such spaces can be a valuable tool in 'real world' empirical research in theatre and spatiality. Through a demonstration of two of Ortelia's VR models (an art gallery and a theatre), we suggest how we might consider interpreting cultural space and sites as contributing significantly to cultural capital. We also introduce the potential for human interaction in such venues through motion-capture to discuss the potential for assessing how humans interact in such contexts.

CAT-SLAM : probabilistic localisation and mapping using a continuous appearance-based trajectory

This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

SOA for business networks - service delivery framework

The next generation of SOA needs to scale for flexible service consumption, beyond organizational boundaries and current B2B applications, into communities, eco-systems, and business networks. In the wider and, ultimately, global settings, new capabilities are needed so that business partners can efficiently and reliably enable, adapt, and expose services where they can be discovered, ordered, consumed, metered, and paid for, through new applications and opportunities, driven by third parties in the global "village". This trend is already underway, in different ways, through various early adopter market segments. For the small medium enterprises segment, Google, Intuit-Microsoft, and others have launched appstores, through which an open-ended array of hosted applications are sourced from the development community and procured as maketplace commondities. In the corporate sector, the marketplace model and business network hubs are being put in place on top of connectivity and network orchestration investments for capitalizing services as tradable assets, seen in banking/finance (e.g. American Express Intelligent Marketplace), logistics (e.g., the E2open hub), and the public sector (e.g., UK DirectGov whole-of-government citizen services delivery).

A requirements framework for semantic business process modelling

The emergence of semantic technologies to deal with the underlying meaning of things, instead of a purely syntactical representation, has led to new developments in various fields, including business process modeling. Inspired by artificial intelligence research, technologies for semantic Web services have been proposed and extended to process modeling. However, the applicablility of semantic Web services for semantic business processes is limited because business processes encompass wider requirements of business than Web services. In particular, processes are concerned with the composition of tasks, that is, in which order activities are carried out, regardless of their implementation details; resources assigned to carry out tasks, such as machinery, people, and goods; data exchange; and security and compliance concerns.