The high price of hesitation where time of the essence

The decision of Lai v Soineva [2011] QSC 247 in relation to the operation of standard conditions in the Queensland REIQ contract highlights a very practical issue often overlooked in the heat of a transaction .The point is relatively simple. In this instance ,the case concerned the interpretation of the printed "Building and Pest Inspection Clause" but is of relevance to the printed "Finance Clause" in the same contract as the wording and principles are identical. It highlights the issue of knowing well what is in the standard contract and not making assumptions. The case also highlights the cost to a party of dithering in making an election in a time of the essence environment

Microscopic cooperative traffic based on NGSIM data

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Vehicles are able to communicate on the local traffic state in real time, which could result in an automatic and therefore better reaction to the mechanism of traffic jam formation. An upstream single hop radio broadcast network can improve the perception of each cooperative driver within radio range and hence the traffic stability. The impact of a cooperative law on traffic congestion appearance is investigated, analytically and through simulation. Ngsim field data is used to calibrate the Optimal Velocity with Relative Velocity (OVRV) car following model and the MOBIL lane-changing model is implemented. Assuming that congestion can be triggered either by a perturbation in the instability domain or by a critical lane changing behavior, the calibrated car following behavior is used to assess the impact of a microscopic cooperative law on abnormal lane changing behavior. The cooperative law helps reduce and delay traffic congestion as it increases traffic flow stability.

Establishing initial trust in autonomous delay tolerant networks without centralised PKI

A Delay Tolerant Network (DTN) is one where nodes can be highly mobile, with long message delay times forming dynamic and fragmented networks. Traditional centralised network security is difficult to implement in such a network, therefore distributed security solutions are more desirable in DTN implementations. Establishing effective trust in distributed systems with no centralised Public Key Infrastructure (PKI) such as the Pretty Good Privacy (PGP) scheme usually requires human intervention. Our aim is to build and compare different de- centralised trust systems for implementation in autonomous DTN systems. In this paper, we utilise a key distribution model based on the Web of Trust principle, and employ a simple leverage of common friends trust system to establish initial trust in autonomous DTN’s. We compare this system with two other methods of autonomously establishing initial trust by introducing a malicious node and measuring the distribution of malicious and fake keys. Our results show that the new trust system not only mitigates the distribution of fake malicious keys by 40% at the end of the simulation, but it also improved key distribution between nodes. This paper contributes a comparison of three de-centralised trust systems that can be employed in autonomous DTN systems.

Learning hierarchical prototypes of motion time series for interactive systems

Abstract. For interactive systems, recognition, reproduction, and generalization of observed motion data are crucial for successful interaction. In this paper, we present a novel method for analysis of motion data that we refer to as K-OMM-trees. K-OMM-trees combine Ordered Means Models (OMMs) a model-based machine learning approach for time series with an hierarchical analysis technique for very large data sets, the K-tree algorithm. The proposed K-OMM-trees enable unsupervised prototype extraction of motion time series data with hierarchical data representation. After introducing the algorithmic details, we apply the proposed method to a gesture data set that includes substantial inter-class variations. Results from our studies show that K-OMM-trees are able to substantially increase the recognition performance and to learn an inherent data hierarchy with meaningful gesture abstractions.

Residence time investigation in a co-axial dielectric barrier discharge reactor

The residence time distribution (RTD) is a crucial parameter when treating engine exhaust emissions with a Dielectric Barrier Discharge (DBD) reactor. In this paper, the residence time of such a reactor is investigated using a finite element based software: COMSOL Multiphysics 4.3. Non-thermal plasma (NTP) discharge is being introduced as a promising method for pollutant emission reduction. DBD is one of the most advantageous of NTP technologies. In a two cylinder co-axial DBD reactor, tubes are placed between two electrodes and flow passes through the annuals between these barrier tubes. If the mean residence time increases in a DBD reactor, there will be a corresponding increase in reaction time and consequently, the pollutant removal efficiency can increase. However, pollutant formation can occur during increased mean residence time and so the proportion of fluid that may remain for periods significantly longer than the mean residence time is of great importance. In this study, first, the residence time distribution is calculated based on the standard reactor used by the authors for ultrafine particle (10-500 nm) removal. Then, different geometrics and various inlet velocities are considered. Finally, for selected cases, some roughness elements added inside the reactor and the residence time is calculated. These results will form the basis for a COMSOL plasma and CFD module investigation.

Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

Efficient route update and maintenance processes for multipath routing in large-scale industrial wireless sensor networks

Reliable communications is one of the major concerns in wireless sensor networks (WSNs). Multipath routing is an effective way to improve communication reliability in WSNs. However, most of existing multipath routing protocols for sensor networks are reactive and require dynamic route discovery. If there are many sensor nodes from a source to a destination, the route discovery process will create a long end-to-end transmission delay, which causes difficulties in some time-critical applications. To overcome this difficulty, the efficient route update and maintenance processes are proposed in this paper. It aims to limit the amount of routing overhead with two-tier routing architecture and introduce the combination of piggyback and trigger update to replace the periodic update process, which is the main source of unnecessary routing overhead. Simulations are carried out to demonstrate the effectiveness of the proposed processes in improvement of total amount of routing overhead over existing popular routing protocols.

Bicyclists overestimate their own night-time conspicuity and underestimate the benefits of retroreflective markers on the moveable joints

Conspicuity limitations make bicycling at night dangerous. This experiment quantified bicyclists’ estimates of the distance at which approaching drivers would first recognize them. Twenty five participants (including 13 bicyclists who rode at least once per week, and 12 who rode once per month or less) cycled in place on a closed-road circuit at night-time and indicated when they were confident that an approaching driver would first recognize that a bicyclist was present. Participants wore black clothing alone or together with a fluorescent bicycling vest, a fluorescent bicycling vest with additional retroreflective tape, or the fluorescent retroreflective vest plus ankle and knee reflectors in a modified ‘biomotion’ configuration. The bicycle had a light mounted on the handlebars which was either static, flashing or off. Participants judged that black clothing made them least visible, retroreflective strips on the legs in addition to a retroreflective vest made them most visible and that adding retroreflective materials to a fluorescent vest provides no conspicuity benefits. Flashing bicycle lights were associated with higher conspicuity than static lights. Additionally, occasional bicyclists judged themselves to be more visible than did frequent bicyclists. Overall, bicyclists overestimated their conspicuity compared to previously collected recognition distances and underestimated the conspicuity benefits of retroreflective markings on their ankles and knees. Participants mistakenly judged that a fluorescent vest that did not include retroreflective material would enhance their night-time conspicuity. These findings suggest that bicyclists have dangerous misconceptions concerning the magnitude of the night-time conspicuity problem and the potential value of conspicuity treatments.

Diurnal temperature range and childhood asthma : a time-series study

BACKGROUND: Hot and cold temperatures have been associated with childhood asthma. However, the relationship between daily temperature variation and childhood asthma is not well understood. This study aimed to examine the relationship between diurnal temperature range (DTR) and childhood asthma. METHODS: A Poisson generalized linear model combined with a distributed lag non-linear model was used to examine the relationship between DTR and emergency department admissions for childhood asthma in Brisbane, from January 1st 2003 to December 31st 2009. RESULTS: There was a statistically significant relationship between DTR and childhood asthma. The DTR effect on childhood asthma increased above a DTR of 10[degree sign]C. The effect of DTR on childhood asthma was the greatest for lag 0--9 days, with a 31% (95% confidence interval: 11% -- 58%) increase of emergency department admissions per 5[degree sign]C increment of DTR. Male children and children aged 5--9 years appeared to be more vulnerable to the DTR effect than others. CONCLUSIONS: Large DTR may trigger childhood asthma. Future measures to control and prevent childhood asthma should include taking temperature variability into account. More protective measures should be taken after a day of DTR above10[degree sign]C.

Time-aware topic recommendation based on micro-blogs

Topic recommendation can help users deal with the information overload issue in micro-blogging communities. This paper proposes to use the implicit information network formed by the multiple relationships among users, topics and micro-blogs, and the temporal information of micro-blogs to find semantically and temporally relevant topics of each topic, and to profile users' time-drifting topic interests. The Content based, Nearest Neighborhood based and Matrix Factorization models are used to make personalized recommendations. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on a real world dataset that collected from Twitter.com.

Effect of aging time and Al substitution on the morphology of aluminous goethite

Goethite and Al-substituted goethite were synthesized from the reaction between ferric nitrate and/or aluminum nitrate and potassium hydroxide. XRF, XRD, TEM with EDS were used to characterize the chemical composition, phase and lattice parameters, and morphology of the synthesized products. The results show that d(020) decreases from 4.953 to 4.949 Å and the b dimension decreases from 9.951 Å to 9.906 Å when the aging time increases from 6 days to 42 days for 9.09 mol% Al-substituted goethite. A sample with 9.09 mol% Al substitution in Al-substituted goethite was prepared by a rapid co-precipitation method. In the sample, 13.45 mol%, 12.31 mol% and 5.85 mol% Al substitution with a crystal size of 163, 131, and 45 nm are observed as shown in the TEM images and EDS. The crystal size of goethite is positively related to the degree of Al substitution according to the TEM images and EDS results. Thus, this methodology is proved to be effective to distinguish the morphology of goethite and Al substituted goethite.

Near Infrared Spectroscopy Evaluation of Articular Cartilage : Decision-Making in Arthroplasty : Real-Time Assessment of Articular Cartilage

Current diagnostic methods for assessing the severity of articular cartilage degenerative conditions, such as osteoarthritis, are inadequate. There is also a lack of techniques that can be used for real-time evaluation of the tissue during surgery to inform treatment decision and eliminate subjectivity. This book, derived from Dr Afara’s doctoral research, presents a scientific framework that is based on near infrared (NIR) spectroscopy for facilitating the non-destructive evaluation of articular cartilage health relative to its structural, functional, and mechanical properties. This development is a component of the ongoing research on advanced endoscopic diagnostic techniques in the Articular Cartilage Biomechanics Research Laboratory of Professor Adekunle Oloyede at Queensland University of Technology (QUT), Brisbane Australia.

GameFlow heuristics for designing and evaluating real-time strategy games

The GameFlow model strives to be a general model of player enjoyment, applicable to all game genres and platforms. Derived from a general set of heuristics for creating enjoyable player experiences, the GameFlow model has been widely used in evaluating many types of games, as well as non-game applications. However, we recognize that more specific, low-level, and implementable criteria are potentially more useful for designing and evaluating video games. Consequently, the research reported in this paper aims to provide detailed heuristics for designing and evaluating one specific game genre, real-time strategy games. In order to develop these heuristics, we conducted a grounded theoretical analysis on a set of professional game reviews and structured the resulting heuristics using the GameFlow model. The resulting 165 heuristics for designing and evaluating real-time strategy games are presented and discussed in this paper.

Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics

Internet services are important part of daily activities for most of us. These services come with sophisticated authentication requirements which may not be handled by average Internet users. The management of secure passwords for example creates an extra overhead which is often neglected due to usability reasons. Furthermore, password-based approaches are applicable only for initial logins and do not protect against unlocked workstation attacks. In this paper, we provide a non-intrusive identity verification scheme based on behavior biometrics where keystroke dynamics based-on free-text is used continuously for verifying the identity of a user in real-time. We improved existing keystroke dynamics based verification schemes in four aspects. First, we improve the scalability where we use a constant number of users instead of whole user space to verify the identity of target user. Second, we provide an adaptive user model which enables our solution to take the change of user behavior into consideration in verification decision. Next, we identify a new distance measure which enables us to verify identity of a user with shorter text. Fourth, we decrease the number of false results. Our solution is evaluated on a data set which we have collected from users while they were interacting with their mail-boxes during their daily activities.