How safe is safe enough? : a socio-technical view of low-cost level crossing safety

Low-cost level crossings are often criticized as being unsafe. Does a SIL (safety integrity level) rating make the railway crossing any safer? This paper discusses how a supporting argument might be made for low-cost level crossing warning devices with lower levels of safety integrity and issues such as risk tolerability and derivation of tolerable hazard rates for system-level hazards. As part of the design of such systems according to fail-safe principles, the paper considers the assumptions around the pre-defined safe states of existing warning devices and how human factors issues around such states can give rise to additional hazards.

Integration of opinion into customer analysis model

As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

Matching relevance features with ontological concepts

In order to comprehend user information needs by concepts, this paper introduces a novel method to match relevance features with ontological concepts. The method first discovers relevance features from user local instances. Then, a concept matching approach is developed for matching these features to accurate concepts in a global knowledge base. This approach is significant for the transition of informative descriptor and conceptional descriptor. The proposed method is elaborately evaluated by comparing against three information gathering baseline models. The experimental results shows the matching approach is successful and achieves a series of remarkable improvements on search effectiveness.

Sustainability in post disaster road infrastructure recovery projects in Queensland, Australia

between mid 2010 and early 2011, Queensland road related infrastructures were devastated by flood and cyclone related natural disasters. Responding to these recent events and in preparing for more regular and intense climate-change induced events in future, the Queensland Government is now reviewing how post-disaster road infrastructure recovery projects are planned and delivered. In particular, there is awareness that rebuilding such infrastructure need sustainable strategies across economic, environmental and social dimensions. A comprehensive sustainability assessment framework for pre and post disaster situations can minimize negative impact on our communities, economy and environment. This research is underway to develop a comprehensive sustainability element frame work for post disaster management in road infrastructures in Queensland, Australia. Analyzing the implications of disruption to transport network and associated services is an important part of preparing local and regional responses to the impacts of natural disasters. This research can contribute to strategic planning, management leading to safe, efficient and integrated transport system that supports sustainable economic, social and environmental outcomes in Queensland. Within this context, this paper provides an overview of the qualitative mixed-method research approach involving literature reviews and case studies to explore and evaluate a number of sustainability elements with a view to develop operational strategies for disaster recovery road projects.

Effects of schedule pressure on construction performance

Accelerating a project can be rewarding. The consequences, however, can be troublesome if productivity and quality are sacrificed for the sake of remaining ahead of schedule, such that the actual schedule benefits are often barely worth the effort. The tradeoffs and paths of schedule pressure and its causes and effects are often overlooked when schedule decisions are being made. This paper analyses the effects that schedule pressure has on construction performance, and focuses on tradeoffs in scheduling. A research framework has been developed using a causal diagram to illustrate the cause-and-effect analysis of schedule pressure. An empirical investigation has been performed by using survey data collected from 102 construction practitioners working in 38 construction sites in Singapore. The results of this survey data analysis indicate that advantages of increasing the pace of work—by working under schedule pressure—can be offset by losses in productivity and quality. The negative effects of schedule pressure arise mainly by working out of sequence, generating work defects, cutting corners, and losing the motivation to work. The adverse effects of schedule pressure can be minimized by scheduling construction activities realistically and planning them proactively, motivating workers, and by establishing an effective project coordination and communication mechanism.

Dynamic modeling for construction innovation

Previous research on construction innovation has commonly recognized the importance of the organizational climate and key individuals, often called “champions,” for the success of innovation. However, it rarely focuses on the role of participants at the project level and addresses the dynamics of construction innovation. This paper therefore presents a dynamic innovation model that has been developed using the concept of system dynamics. The model incorporates the influence of several individual and situational factors and highlights two critical elements that drive construction innovations: (1) normative pressure created by project managers through their championing behavior, and (2) instrumental motivation of team members facilitated by a supportive organizational climate. The model is qualified empirically, using the results of a survey of project managers and their project team members working for general contractors in Singapore, by assessing casual relationships for key model variables. Finally, the paper discusses the implications of the model structure for fostering construction innovations.

Ranked critical factors in PPP briefings

Public-private partnerships (PPPs) are increasingly used to procure Australian infrastructure projects. As with all construction projects, the early briefing stages are often the most crucial in determining a successful outcome. There is, however, a lack of systematic research on the type and nature of the critical factors affecting the effectiveness and efficiency of PPP during this period. A literature review is presented of PPP usage in Australia, in which four main categories of factors (procurement, stakeholder, risk, and finance) are identified, each with several subfactors. A questionnaire survey involving state government stakeholders is also described, and a mathematical model that ranks the factors involved is developed. This is followed by an examination of the potential of the factors to help improve the PPP briefing stage for both public and private sectors.

Classification of railway bridges based on criticality and vulnerability factors

Bridges are currently rated individually for maintenance and repair action according to the structural conditions of their elements. Dealing with thousands of bridges and the many factors that cause deterioration, makes this rating process extremely complicated. The current simplified but practical methods are not accurate enough. On the other hand, the sophisticated, more accurate methods are only used for a single or particular bridge type. It is therefore necessary to develop a practical and accurate rating system for a network of bridges. The first most important step in achieving this aim is to classify bridges based on the differences in nature and the unique characteristics of the critical factors and the relationship between them, for a network of bridges. Critical factors and vulnerable elements will be identified and placed in different categories. This classification method will be used to develop a new practical rating method for a network of railway bridges based on criticality and vulnerability analysis. This rating system will be more accurate and economical as well as improve the safety and serviceability of railway bridges.

Embedding human expert cognition into autonomous UAS trajectory planning

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

Adaptive metering algorithm for electronic commercial vehicle preclearance systems

This paper presents an adaptive metering algorithm for enhancing the electronic screening (e-screening) operation at truck weight stations. This algorithm uses a feedback control mechanism to control the level of truck vehicles entering the weight station. The basic operation of the algorithm allows more trucks to be inspected when the weight station is underutilized by adjusting the weight threshold lower. Alternatively, the algorithm restricts the number of trucks to inspect when the station is overutilized to prevent queue spillover. The proposed control concept is demonstrated and evaluated in a simulation environment. The simulation results demonstrate the considerable benefits of the proposed algorithm in improving overweight enforcement with minimal negative impacts on nonoverweighed trucks. The test results also reveal that the effectiveness of the algorithm improves with higher truck participation rates in the e-screening program.

Application of profluorescent nitroxides for measurements of oxidative capacity of combustion generated particles

Oxidative stress caused by generation of free radicals and related reactive oxygen species (ROS) at the sites of deposition has been proposed as a mechanism for many of the adverse health outcomes associated with exposure to particulate matter (PM). Recently, a new profluorescent nitroxide molecular probe (BPEAnit) developed at QUT was applied in an entirely novel, rapid and non-cell based assay for assessing the oxidative potential of particles (i.e. potential of particles to induce oxidative stress). The technique was applied on particles produced by several combustion sources, namely cigarette smoke, diesel exhaust and wood smoke. One of the main findings from the initial studies undertaken at QUT was that the oxidative potential per PM mass significantly varies for different combustion sources as well as the type of fuel used and combustion conditions. However, possibly the most important finding from our studies was that there was a strong correlation between the organic fraction of particles and the oxidative potential measured by the PFN assay, which clearly highlights the importance of organic species in particle-induced toxicity.

A proposed Australian industrial control system security curriculum

The security of industrial control systems in critical infrastructure is a concern for the Australian government and other nations. There is a need to provide local Australian training and education for both control system engineers and information technology professionals. This paper proposes a postgraduate curriculum of four courses to provide knowledge and skills to protect critical infrastructure industrial control systems. Our curriculum is unique in that it provides security awareness but also the advanced skills required for security specialists in this area. We are aware that in the Australian context there is a cultural gap between the thinking of control system engineers who are responsible for maintaining and designing critical infrastructure and information technology professionals who are responsible for protecting these systems from cyber attacks. Our curriculum aims to bridge this gap by providing theoretical and practical exercises that will raise the awareness and preparedness of both groups of professionals.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.

Protection of structural systems and mechanisms from catastrophic and life-threatening failure caused by unforeseeable events

Structural framing systems and mechanisms designed for normal use rarely possess adequate robustness to withstand the effects of large impacts, blasts and extreme earthquakes that have been experienced in recent times. Robustness is the property of systems that enables them to survive unforeseen or unusual circumstances (Knoll & Vogel, 2009). Queensland University of Technology with industry collaboration is engaged in a program of research that commenced 15 years ago to study the impact of such unforeseeable phenomena and investigate methods of improving robustness and safety with protective mechanisms embedded or designed in structural systems. This paper highlights some of the research pertaining to seismic protection of building structures, rollover protective structures and effects of vehicular impact and blast on key elements in structures that could propagate catastrophic and disproportionate collapse.