Using GPS and accelerometry to assess older adults' driving behaviours and performance : challenges and future directions

With the projected increase in older adults, the older driver population is estimated to be the fastest growing cohort of drivers among many developed countries. The increased physical fragility associated with the aging process make older adults who drive private automobiles a vulnerable road user group. Much of the current research on older drivers’ behaviours and practices rely on self-report data. This paper explores the utility of in-vehicle devices (Global Positioning Systems and recording accelerometers) in assessing older drivers’ habitual driving behaviours. Seventy-eight older drivers (above 65 years of age), from the Australian Capital Territory, Australia, participated in the current study. The driving behaviours and practices of these participants were prospectively assessed over a two-week period. The use of combined GPS and recording accelerometers to improve understanding of older drivers’ driving behaviours show promise within the current study. The challenges of using multiple in-vehicle devices in assessing driving beahaviours and performances within this cohort will be discussed. Based on the current findings, recommendations for future research regarding the use of in-vehicle devices among the older driver cohort are proposed.

Child sexual abuse in China : a meta-analysis of 27 studies

Objective: To examine whether Chinese studies of child sexual abuse (CSA) in the general population show lower prevalence rates than other international studies, and whether certain features of these studies may help to account for variation in estimates. Methods: A meta-analysis and meta-regression were conducted on 27 studies found in the English and Chinese language peer reviewed journals that involved general populations of students or residents, estimated CSA prior to age 18, and specified rates for males or females individually. Results: Estimates for Chinese females were lower than the international composites. For total CSA for females, the Chinese pooled estimate was 15.3% (95% CI = 12.6–18.0) based on the meta-analysis of 24 studies, lower than the international estimate (Stoltenborgh, van IJzendoorn, Euser, & Bakermans-Kranenburg, 2011) but not significantly. For contact CSA for females, the pooled estimate was 9.5% (95% CI = 7.5–11.5), based on 16 studies, significantly lower than the international prevalence. For penetrative CSA for females, the pooled estimate was 1% (95% CI = 0.7–1.3), based on 15 studies, significantly lower than the international estimate of 15.1%. Chinese men reported significantly less penetrative CSA but significantly more total CSA than international estimates; while contact CSA reported by Chinese and international males appeared to be roughly equivalent. Chinese CSA prevalence estimates were lower in studies from urban areas and non-mainland areas (Hong Kong and Taiwan), and in surveys with larger and probability samples, multiple sites, face-to-face interview method and when using less widely used instruments. Conclusions: The findings to date justify further research into possible cultural and sociological reasons for lower risk of contact and penetrative sexual abuse of girls and less penetrative abuse of boys in China. Future research should examine sociological explanations, including patterns of supervision, sexual socialization and attitudes related to male sexual prowess. Practice implications: The findings suggest that future general population studies in China should use well validated instruments, avoid face-to-face interview formats and be careful to maintain methodological standards when sampling large populations over multiple sites.

Modal flexibility method for structural damage detection in suspension bridges

Suspension bridges meet the steadily growing demand for lighter and longer bridges in today’s infrastructure systems. These bridges are designed to have long life spans, but with age, their main cables and hangers could suffer from corrosion and fatigue. There is a need for a simple and reliable procedure to detect and locate such damage, so that appropriate retrofitting can be carried out to prevent bridge failure. Damage in a structure causes changes in its properties (mass, damping and stiffness) which in turn will cause changes in its vibration characteristics (natural frequencies, modal damping and mode shapes). Methods based on modal flexibility, which depends on both the natural frequencies and mode shapes, have the potential for damage detection. They have been applied successfully to beam and plate elements, trusses and simple structures in reinforced concrete and steel. However very limited applications for damage detection in suspension bridges have been identified to date. This paper examines the potential of modal flexibility methods for damage detection and localization of a suspension bridge under different damage scenarios in the main cables and hangers using numerical simulation techniques. Validated finite element model (FEM) of a suspension bridge is used to acquire mass normalized mode shape vectors and natural frequencies at intact and damaged states. Damage scenarios will be simulated in the validated FE models by varying stiffness of the damaged structural members. The capability of damage index based on modal flexibility to detect and locate damage is evaluated. Results confirm that modal flexibility based methods have the ability to successfully identify damage in suspension bridge main cables and hangers.

Traffic state estimation from partial Bluetooth and volume observations : case study in the Brisbane metropolitan area

The application of the Bluetooth (BT) technology to transportation has been enabling researchers to make accurate travel time observations, in freeway and arterial roads. The Bluetooth traffic data are generally incomplete, for they only relate to those vehicles that are equipped with Bluetooth devices, and that are detected by the Bluetooth sensors of the road network. The fraction of detected vehicles versus the total number of transiting vehicles is often referred to as Bluetooth Penetration Rate (BTPR). The aim of this study is to precisely define the spatio-temporal relationship between the quantities that become available through the partial, noisy BT observations; and the hidden variables that describe the actual dynamics of vehicular traffic. To do so, we propose to incorporate a multi- class traffic model into a Sequential Montecarlo Estimation algorithm. Our framework has been applied for the empirical travel time investigations into the Brisbane Metropolitan region.

Governance challenges in the global games industry

Current governance challenges facing the global games industry are heavily dominated by online games. Whilst much academic and industry attention has been afforded to Virtual Worlds, the more pressing contemporary challenges may arise in casual games, especially when found on social networks. As authorities are faced with an increasing volume of disputes between participants and platform operators, the likelihood of external regulation increases, and the role that such regulation would have on the industry – both internationally and within specific regions – is unclear. Kelly (2010) argues that “when you strip away the graphics of these [social] games, what you are left with is simply a button [...] You push it and then the game returns a value of either Win or Lose”. He notes that while “every game developer wants their game to be played, preferably addictively, because it’s so awesome”, these mechanics lead not to “addiction of engagement through awesomeness” but “the addiction of compulsiveness”, surmising that “the reality is that they’ve actually sort-of kind-of half-intentionally built a virtual slot machine industry”. If such core elements of social game design are questioned, this gives cause to question the real-money options to circumvent them. With players able to purchase virtual currency and speed the completion of tasks, the money invested by the 20% purchasing in-game benefits (Zainwinger, 2012) may well be the result of compulsion. The decision by the Japanese Consumer Affairs agency to investigate the ‘Kompu Gacha’ mechanic (in which players are rewarded for completing a set of items obtained through purchasing virtual goods such as mystery boxes), and the resultant verdict that such mechanics should be regulated through gambling legislation, demonstrates that politicians are beginning to look at the mechanics deployed in these environments. Purewal (2012) states that “there’s a reasonable argument that complete gacha would be regulated under gambling law under at least some (if not most) Western jurisdictions”. This paper explores the governance challenged within these games and platforms, their role in the global industry, and current practice amongst developers in the Australian and United States to address such challenges.

Looking yonder : a model of arts engagement with teacher artists and professional artists in Queensland Schools

Since 2007 Kite Arts Education Program (KITE), based at Queensland Performing Arts Centre (QPAC), has been engaged in delivering a series of theatre-based experiences for children in low socio-economic primary schools in Queensland. KITE @ QPAC is an early childhood arts initiative of The Queensland Department of Education that is supported by and located at the Queensland Performing Arts Centre. KITE delivers relevant contemporary arts education experiences for Prep to Year 3 students and their teachers across Queensland. The theatre-based experiences form part of a three year artist-in-residency project titled Yonder that includes performances developed by the children with the support and leadership of Teacher Artists from KITE for their community and parents/carers in a peak community cultural institution. This paper provides an overview of the Yonder model and unpacks some challenges in activating the model for schools and cultural organisations.

Higher-order non-linear analysis of steel structures. Part I : elastic second-order formulation

This paper presents a higher-order beam-column formulation that can capture the geometrically non-linear behaviour of steel framed structures which contain a multiplicity of slender members. Despite advances in computational frame software, analyses of large frames can still be problematic from a numerical standpoint and so the intent of the paper is to fulfil a need for versatile, reliable and efficient non-linear analysis of general steel framed structures with very many members. Following a comprehensive review of numerical frame analysis techniques, a fourth-order element is derived and implemented in an updated Lagrangian formulation, and it is able to predict flexural buckling, snap-through buckling and large displacement post-buckling behaviour of typical structures whose responses have been reported by independent researchers. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. The higher-order element forms a basis for augmenting the geometrically non-linear approach with material non-linearity through the refined plastic hinge methodology described in the companion paper.

Higher-order non-linear analysis of steel structures. Part II : refined plastic hinge formulation

In the companion paper, a fourth-order element formulation in an updated Lagrangian formulation was presented to handle geometric non-linearities. The formulation of the present paper extends this to include material non-linearity by proposing a refined plastic hinge approach to analyse large steel framed structures with many members, for which contemporary algorithms based on the plastic zone approach can be problematic computationally. This concept is an advancement of conventional plastic hinge approaches, as the refined plastic hinge technique allows for gradual yielding, being recognized as distributed plasticity across the element section, a condition of full plasticity, as well as including strain hardening. It is founded on interaction yield surfaces specified analytically in terms of force resultants, and achieves accurate and rapid convergence for large frames for which geometric and material non-linearity are significant. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. In addition to the numerical efficiency, the present versatile approach is able to capture different kinds of material and geometric non-linearities on general applications of steel structures, and thereby it offers an efficacious and accurate means of assessing non-linear behaviour of the structures for engineering practice.

On the advanced analysis of steel frames allowing for flexural, local and lateral-torsional buckling

Detailed procedure for second-order analysis has been coded in the newest Eurocode 3 and the Hong Kong steel code (2005). The effective length method has been noted to be inapplicable to analysis of shallow domes of imperfect members exhibiting snap-through buckling, to portals with leaning columns and others. On the other hand, the advanced analysis is not limited to buckling design of these structures. This paper demonstrates its application to the design of a simple plane sway portal and a three diminsional non-sway steel building. The results by the advanced analysis and the first-order linear analysis are compared and the technique for practical second-order analysis steel structures is described. It is observed that the use of a straight element by itself cannot model the buckling resistance of columns governed by different buckling curves for hot-rolled and cold-formed sections of various shapes like I, H, hollow etc. Also the curvature of the conventional cubic Hermite element is not varied by the external axial force and thus it cannot simulate the response of a buckling column. Thus its use for second-order analysis is basically unacceptable. A technique for additional checking of beams undergoing lateral-torsional buckling is also suggested making the advanced analysis a complete design tool for conventional steel frames.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

Transforming morning to afternoon using linear regression techniques

Visual localization in outdoor environments is often hampered by the natural variation in appearance caused by such things as weather phenomena, diurnal fluctuations in lighting, and seasonal changes. Such changes are global across an environment and, in the case of global light changes and seasonal variation, the change in appearance occurs in a regular, cyclic manner. Visual localization could be greatly improved if it were possible to predict the appearance of a particular location at a particular time, based on the appearance of the location in the past and knowledge of the nature of appearance change over time. In this paper, we investigate whether global appearance changes in an environment can be learned sufficiently to improve visual localization performance. We use time of day as a test case, and generate transformations between morning and afternoon using sample images from a training set. We demonstrate the learned transformation can be generalized from training data and show the resulting visual localization on a test set is improved relative to raw image comparison. The improvement in localization remains when the area is revisited several weeks later.

Challenges of knowledge integration in small and medium enterprises

This study attempts to develop a better understanding of the challenges of knowledge integration (KI) within the innovation process in Small and Medium Enterprises (SMEs). Using several case studies, this study investigates how knowledge integration may be managed within the context of innovation in SMEs. The research places particular focus on identifying the challenges of knowledge integration in SMEs in relation to three aspects of knowledge integration activities, namely knowledge identification, knowledge acquisition, and knowledge sharing. Four distinct tasks emerged in the knowledge integration process, namely team building capability, capturing tacit knowledge, role of knowledge management (KM) systems, and technological systemic integration. The paper suggests that managing knowledge integration in SMEs can be best managed by focusing on these four tasks, which in turn will lead to innovation.

Novelty-based visual obstacle detection in agriculture

This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.

Online self-supervised multi-instance segmentation of dynamic objects

This paper presents a method for the continuous segmentation of dynamic objects using only a vehicle mounted monocular camera without any prior knowledge of the object’s appearance. Prior work in online static/dynamic segmentation is extended to identify multiple instances of dynamic objects by introducing an unsupervised motion clustering step. These clusters are then used to update a multi-class classifier within a self-supervised framework. In contrast to many tracking-by-detection based methods, our system is able to detect dynamic objects without any prior knowledge of their visual appearance shape or location. Furthermore, the classifier is used to propagate labels of the same object in previous frames, which facilitates the continuous tracking of individual objects based on motion. The proposed system is evaluated using recall and false alarm metrics in addition to a new multi-instance labelled dataset to evaluate the performance of segmenting multiple instances of objects.