An efficient and robust system for multi-person event detection in real world indoor surveillance scenes

Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

From Catch Up to Innovation: A History of occupational Health and Safety Regulation in Queensland

From Queensland’s inception as a self-governing colony in December 1859 the issue of labour relations has preoccupied governments and shaped the experiences of its working men and women. However, despite the often turbulent nature of labour relations in Queensland there has, prior to this book, been no attempt to provide an overview of the system as a whole. This important addition to Queensland’s sesquicentenary celebrations redresses this failure, looking at the diverse range of experiences that, together, made up a unique system of labour relations – including those of employers, women workers, indigenous workers, unions, the Queensland Industrial Relations Commission, labour law, industrial disputation, the workings of health and safety system and life in regional areas. It is argued that, overall, Queensland’s system of industrial regulation was central to its economic and social development. Despite past emphasis on the large-scale strikes that periodically raked the state this book finds that consensus normally prevailed.

One year on and flood victims pick up the pieces

"For many Australians, January 10 last year is just a media memory — a vision of cars surfing down inner-city creeks in Toowoomba CBD and houses floating across farm paddocks in the Lockyer Valley. But for the people of the Lockyer Valley who were clinging to life, the terrifying visions of that day remain every time they close their eyes."

2nd ESMO consensus conference on lung cancer : early-stage non-small-cell lung cancer consensus on diagnosis, treatment and follow-up

To complement the existing treatment guidelines for all tumour types, ESMO organises consensus conferences to focus on specific issues in each type of tumour. The 2nd ESMO Consensus Conference on Lung Cancer was held on 11-12 May 2013 in Lugano. A total of 35 experts met to address several questions on non-small-cell lung cancer (NSCLC) in each of four areas: pathology and molecular biomarkers, first-line/second and further lines in advanced disease, earlystage disease and locally advanced disease. For each question, recommendations were made including reference to the grade of recommendation and level of evidence. This consensus paper focuses on early-stage disease. © The Author 2014. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved.

Learning-based Relevance Feedback for Web-based Relation Completion

In a pilot application based on web search engine calledWeb-based Relation Completion (WebRC), we propose to join two columns of entities linked by a predefined relation by mining knowledge from the web through a web search engine. To achieve this, a novel retrieval task Relation Query Expansion (RelQE) is modelled: given an entity (query), the task is to retrieve documents containing entities in predefined relation to the given one. Solving this problem entails expanding the query before submitting it to a web search engine to ensure that mostly documents containing the linked entity are returned in the top K search results. In this paper, we propose a novel Learning-based Relevance Feedback (LRF) approach to solve this retrieval task. Expansion terms are learned from training pairs of entities linked by the predefined relation and applied to new entity-queries to find entities linked by the same relation. After describing the approach, we present experimental results on real-world web data collections, which show that the LRF approach always improves the precision of top-ranked search results to up to 8.6 times the baseline. Using LRF, WebRC also shows performances way above the baseline.

A Memetic Algorithm for the location-based continuously operating reference stations placement problem in Network Real-Time Kinematic

Network Real-Time Kinematic (NRTK) is a technology that can provide centimeter-level accuracy positioning services in real time, and it is enabled by a network of Continuously Operating Reference Stations (CORS). The location-oriented CORS placement problem is an important problem in the design of a NRTK as it will directly affect not only the installation and operational cost of the NRTK, but also the quality of positioning services provided by the NRTK. This paper presents a Memetic Algorithm (MA) for the location-oriented CORS placement problem, which hybridizes the powerful explorative search capacity of a genetic algorithm and the efficient and effective exploitative search capacity of a local optimization. Experimental results have shown that the MA has better performance than existing approaches. In this paper we also conduct an empirical study about the scalability of the MA, effectiveness of the hybridization technique and selection of crossover operator in the MA.

Association hierarchy mining and its application for network traffic characterisation

This thesis presents an association rule mining approach, association hierarchy mining (AHM). Different to the traditional two-step bottom-up rule mining, AHM adopts one-step top-down rule mining strategy to improve the efficiency and effectiveness of mining association rules from datasets. The thesis also presents a novel approach to evaluate the quality of knowledge discovered by AHM, which focuses on evaluating information difference between the discovered knowledge and the original datasets. Experiments performed on the real application, characterizing network traffic behaviour, have shown that AHM achieves encouraging performance.

Real-time price based home energy management scheduler

With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.

Taking up the discourse : theory or praxis

This article responds to the invitation extended by Carney to engage in a dialogue on the topic of graduate legal research units. In his paper, Carney stated the approach of the Sydney course as being to teach theory rather than skills, to "pursue academic goals over skill competencies... ". The Faculty of Law at Queensland University of Technology introduced a postgraduate legal research unit in 1993 with different perspectives and purposes to the Sydney course, and given this experience, the opportunity for a discussion on aspects of such units including the theoretical versus practical approach to teaching cannot be ignored.

Predicting reduced driver alertness on monotonous highways : a driving simulator study

Impaired driver alertness increases the likelihood of drivers’ making mistakes and reacting too late to unexpected events while driving. This is particularly a concern on monotonous roads, where a driver’s attention can decrease rapidly. While effective countermeasures do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behavior in real-time. The aim of this study is to predict drivers’ level of alertness through surrogate measures collected from in-vehicle sensors. Electroencephalographic activity is used as a reference to evaluate alertness. Based on a sample of 25 drivers, data was collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device. Various classification models were tested from linear regressions to Bayesians and data mining techniques. Results indicated that Neural Networks were the most efficient model in detecting lapses in alertness. Findings also show that reduced alertness can be predicted up to 5 minutes in advance with 90% accuracy, using surrogate measures such as time to line crossing, blink frequency and skin conductance level. Such a method could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring, in real-time, drivers' behavior on highways.

The effect of the addition of hip strengthening exercises to a lumbopelvic exercise programme for the treatment of non-specific low back pain : a randomized controlled trial

Objectives To compare the efficacy of two exercise programs in reducing pain and disability for individuals with non-specific low back pain and to examine the underlying mechanical factors related to pain and disability for individuals with NSLBP. Design A single-blind, randomized controlled trial. Methods: Eighty participants were recruited from eleven community-based general medical practices and randomized into two groups completing either a lumbopelvic motor control or a combined lumbopelvic motor control and progressive hip strengthening exercise therapy program. All participants received an education session, 6 rehabilitation sessions including real time ultrasound training, and a home based exercise program manual and log book. The primary outcomes were pain (0-100mm visual analogue scale), and disability (Oswestry Disability Index V2). The secondary outcomes were hip strength (N/kg) and two-dimensional frontal plane biomechanics (°) measure during the static Trendelenburg test and while walking. All outcomes were measured at baseline and at 6-week follow up. Results There was no statistical difference in the change in pain (xˉ = -4.0mm, t= -1.07, p =0.29, 95%CI -11.5, 3.5) or disability (xˉ = -0.3%, t= -0.19, p =0.85, 95%CI -3.5, 2.8) between groups. Within group comparisons revealed clinically meaningful reductions in pain for both Group One (xˉ =-20.9mm, 95%CI -25.7, -16.1) and Group Two (xˉ =-24.9, 95%CI -30.8, -19.0). Conclusion Both exercise programs had similar efficacy in reducing pain. The addition of hip strengthening exercises to a motor control exercise program does not appear to result in improved clinical outcome for pain for individuals with non-specific low back pain.

Differential effects of refractive blur on day and night-time driving performance

Purpose To investigate the effect of different levels of refractive blur on real-world driving performance measured under day and nighttime conditions. Methods Participants included 12 visually normal, young adults (mean age = 25.8 ± 5.2 years) who drove an instrumented research vehicle around a 4 km closed road circuit with three different levels of binocular spherical refractive blur (+0.50 diopter sphere [DS], +1.00 DS, +2.00 DS) compared with a baseline condition. The subjects wore optimal spherocylinder correction and the additional blur lenses were mounted in modified full-field goggles; the order of testing of the blur conditions was randomized. Driving performance was assessed in two different sessions under day and nighttime conditions and included measures of road signs recognized, hazard detection and avoidance, gap detection, lane-keeping, sign recognition distance, speed, and time to complete the course. Results Refractive blur and time of day had significant effects on driving performance (P < 0.05), where increasing blur and nighttime driving reduced performance on all driving tasks except gap judgment and lane keeping. There was also a significant interaction between blur and time of day (P < 0.05), such that the effects of blur were exacerbated under nighttime driving conditions; performance differences were evident even for +0.50 DS blur relative to baseline for some measures. Conclusions The effects of blur were greatest under nighttime conditions, even for levels of binocular refractive blur as low as +0.50 DS. These results emphasize the importance of accurate and up-to-date refractive correction of even low levels of refractive error when driving at night.

Impact of real-time traffic characteristics on freeway crash occurrence : systematic review and meta-analysis

A systematic literature review and a comprehensive meta-analysis that combines the findings from existing studies, was conducted in this thesis to analyse the impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to investigate the quality, publication bias and outlier bias of the various studies, and the time intervals used to measure traffic characteristics were considered. Based on this comprehensive and systematic review, and the results of the subsequent meta-analysis, major issues in study design, traffic and crash data, and model development and evaluation are discussed.

Integrated marketing communications

Organisations continually use integrated marketing communications to achieve a competitive advantage and meet their marketing objectives. This 4th edition of Integrated Marketing Communications emphasises digital and interactive marketing, the most dynamic and crucial components to a successful IMC campaign today. Incorporating the most up to date theories and practice, the text clearly explains and demonstrates how to best select and co-ordinate all of a brand’s marketing communications elements to effectively engage the target market. Chapters adopt an integrative approach to examine marketing communications from both a consumer’s and marketer’s perspective. A wide range of local and global examples include: Spotify, Pandora, Coca-Cola, Pepsi, Woolworths, Nike, KFC, Victoria Bitter, Tigerair and Air New Zealand. Each new copy of the text also offers 12 month access to wealth of student on-line revision and learning tools: CourseMate Express + Search me! marketing. Unique to the text is a series of end of chapter local videos showing students how key objectives in IMC theory are applied by real businesses.

Adsorption and mobility of metals in build-up on road surfaces

The study investigated the adsorption and bioavailability characteristics of traffic generated metals common to urban land uses, in road deposited solids particles. To validate the outcomes derived from the analysis of field samples, adsorption and desorption experiments were undertaken. The analysis of field samples revealed that metals are selectively adsorbed to different charge sites on solids. Zinc, copper, lead and nickel are adsorbed preferentially to oxides of manganese, iron and aluminium. Lead is adsorbed to organic matter through chemisorption. Cadmium and chromium form weak bonding through cation exchange with most of the particle sizes. Adsorption and desorption experiments revealed that at high metal concentrations, chromium, copper and lead form relatively strong bonds with solids particles while zinc is adsorbed through cation exchange with high likelihood of being released back into solution. Outcomes from this study provide specific guidance for the removal of metals from stormwater based on solids removal.