On trade-off solution pairs in a special type of transportation problem

Abstract is not available.

Things you don't want to know about yourself: Ambivalence about tracking and sharing personal information for behaviour change

Technologies that facilitate the collection and sharing of personal information can feed people's desire for enhanced self-knowledge and help them to change their behaviour, yet for various reasons people can also be reluctant to use such technologies. This paper explores this tension through an interview study in the context of smoking cessation. Our findings show that smokers and recent ex-smokers were ambivalent about their behaviour change as well as about collecting personal information through technology and sharing it with other users. We close with a summary of three challenges emerging from such ambivalence and directions to address them.

Assessing uncertainty in pollutant build-up and wash-off processes

Assessing build-up and wash-off process uncertainty is important for accurate interpretation of model outcomes to facilitate informed decision making for developing effective stormwater pollution mitigation strategies. Uncertainty inherent to pollutant build-up and wash-off processes influences the variations in pollutant loads entrained in stormwater runoff from urban catchments. However, build-up and wash-off predictions from stormwater quality models do not adequately represent such variations due to poor characterisation of the variability of these processes in mathematical models. The changes to the mathematical form of current models with the incorporation of process variability, facilitates accounting for process uncertainty without significantly affecting the model prediction performance. Moreover, the investigation of uncertainty propagation from build-up to wash-off confirmed that uncertainty in build-up process significantly influences wash-off process uncertainty. Specifically, the behaviour of particles <150µm during build-up primarily influences uncertainty propagation, resulting in appreciable variations in the pollutant load and composition during a wash-off event.

Influence of uncertainty inherent to heavy metal build-up and wash-off on stormwater quality

Uncertainty inherent to heavy metal build-up and wash-off stems from process variability. This results in inaccurate interpretation of stormwater quality model predictions. The research study has characterised the variability in heavy metal build-up and wash-off processes based on the temporal variations in particle-bound heavy metals commonly found on urban roads. The study outcomes found that the distribution of Al, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb were consistent over particle size fractions <150µm and >150µm, with most metals concentrated in the particle size fraction <150µm. When build-up and wash-off are considered as independent processes, the temporal variations in these processes in relation to the heavy metals load are consistent with variations in the particulate load. However, the temporal variations in the load in build-up and wash-off of heavy metals and particulates are not consistent for consecutive build-up and wash-off events that occur on a continuous timeline. These inconsistencies are attributed to interactions between heavy metals and particulates <150µm and >150µm, which are influenced by particle characteristics such as organic matter content. The behavioural variability of particles determines the variations in the heavy metals load entrained in stormwater runoff. Accordingly, the variability in build-up and wash-off of particle-bound pollutants needs to be characterised in the description of pollutant attachment to particulates in stormwater quality modelling. This will ensure the accounting of process uncertainty, and thereby enhancing the interpretation of the outcomes derived from modelling studies.

Besides tracking: Simulation of RFID marketing and beyond

This paper asks a new question: how we can use RFID technology in marketing products in supermarkets and how we can measure its performance or ROI (Return-on-Investment). We try to answer the question by proposing a simulation model whereby customers become aware of other customers' real-time shopping behavior and may hence be influenced by their purchases and the levels of purchases. The proposed model is orthogonal to sales model and can have the similar effects: increase in the overall shopping volume. Managers often struggle with the prediction of ROI on purchasing such a technology, this simulation sets to provide them the answers of questions like the percentage of increase in sales given real-time purchase information to other customers. The simulation is also flexible to incorporate any given model of customers' behavior tailored to particular supermarket, settings, events or promotions. The results, although preliminary, are promising to use RFID technology for marketing products in supermarkets and provide several dimensions to look for influencing customers via feedback, real-time marketing, target advertisement and on-demand promotions. Several other parameters have been discussed including the herd behavior, fake customers, privacy, and optimality of sales-price margin and the ROI of investing in RFID technology for marketing purposes. © 2010 Springer Science+Business Media B.V.

Tracking students through senior schooling: A successful case study

With society now recognizing that senior schooling is about flexibility in credentialing rather than a one-size-fits-all academic education, it has become necessary to track students through numerous pathways. This case study describes how Nambour State High School put into place a senior schooling tracking program which brought about cultural change throughout the school. Using the Tracking and Academic Management Index as a cohort tracking tool, the school has been able to monitor its senior schooling academic and non-academic performance over the past four years. By focusing on the four measures which make up the Index, Nambour State High School was able to demonstrate improved outcomes for all students in their senior school cohort.

Tracking brand positioning for an emerging destination: 2003 to 2015

Few published studies have monitored destination brand image over time. This temporal aspect is an important gap in the literature, given consensus around the role perceptions play in consumers’ decision making, and the ensuing emphasis on imagery in destination branding collateral. Whereas most destination image studies have been a snapshot of perceptions at one point in time, this paper presents findings from a survey implemented four times between 2003 and 2015. Brand image is the core construct in modelling destination branding performance, which has emerged as a relatively new field of research in the past decade. Using the consumer-based brand equity (CBBE) hierarchy, the project has benchmarked and monitored destination brand salience, image and resonance for an emerging regional destination, relative to key competitors, in the domestic Australian market; and the survey instrument has been demonstrated to be reliable in the context of short break holidays by car. What is particularly interesting to date is there has been relatively little change in the market positions of the five destinations, in spite of over a decade of marketing communications by the regional tourism organisations and their stakeholders, and more recently the mass of user-generated travel content on social media. The project didn’t analyse the actual marketing communications for each of the DMOs. Therefore an important implication is that irrespective of the level of marketing undertaken the DMOs seem to have had little control over the perceptions held in their largest market during this time period. Therefore it must be recognised any improvement in perceptions will likely take a long period of time, and so branding needs to be underpinned by a philosophy of a long term financial investment as well as commitment to a consistency of message over time; which given the politics of DMO decision making represents a considerable challenge.

Suppression of the zero-order term in off-axis digital holography through nonlinear filtering

We present experimental validation of a new reconstruction method for off-axis digital holographic microscopy (DHM). This method effectively suppresses the object autocorrelation,namely, the zero-order term,from holographic data,thereby improving the reconstruction bandwidth of complex wavefronts. The algorithm is based on nonlinear filtering and can be applied to standard DHM setups with realistic recording conditions.We study the robustness of the technique under different experimental configurations,and quantitatively demonstrate its enhancement capabilities on phase signals.

A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining

With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

A feedback-based algorithm forMotion analysis with application to object tracking

We present a motion detection algorithm which detects direction of motion at sufficient number of points and thus segregates the edge image into clusters of coherently moving points. Unlike most algorithms for motion analysis, we do not estimate magnitude of velocity vectors or obtain dense motion maps. The motivation is that motion direction information at a number of points seems to be sufficient to evoke perception of motion and hence should be useful in many image processing tasks requiring motion analysis. The algorithm essentially updates the motion at previous time using the current image frame as input in a dynamic fashion. One of the novel features of the algorithm is the use of some feedback mechanism for evidence segregation. This kind of motion analysis can identify regions in the image that are moving together coherently, and such information could be sufficient for many applications that utilize motion such as segmentation, compression, and tracking. We present an algorithm for tracking objects using our motion information to demonstrate the potential of this motion detection algorithm.

Measurement of shock stand-off distance on a 120 degrees blunt cone model at hypersonic Mach number in Argon

The flow around a 120 degrees blunt cone model with a base radius of 60mm has been visualised at Mach 14.8 and 9.1 using argon as the test gas, at the newly established high speed schlieren facility in the IISc hypersonic shock tunnel HST2. The experimental shock stand off distance around the blunt cone is compared with that obtained using a commercial CFD package. The computed values of shock stand off distance of the blunt cone is found to agree reasonably well with the experimental data.

Off-axis field approximations for ion traps with apertures

In recent work (Int. J. Mass Spec., vol. 282, pp. 112–122) we have considered the effect of apertures on the fields inside rf traps at points on the trap axis. We now complement and complete that work by considering off-axis fields in axially symmetric (referred to as “3D”) and in two dimensional (“2D”) ion traps whose electrodes have apertures, i.e., holes in 3D and slits in 2D. Our approximation has two parts. The first, EnoAperture, is the field obtained numerically for the trap under study with apertures artificially closed. We have used the boundary element method (BEM) for obtaining this field. The second part, EdueToAperture, is an analytical expression for the field contribution of the aperture. In EdueToAperture, aperture size is a free parameter. A key element in our approximation is the electrostatic field near an infinite thin plate with an aperture, and with different constant-valued far field intensities on either side. Compact expressions for this field can be found using separation of variables, wherein the choice of coordinate system is crucial. This field is, in turn, used four times within our trap-specific approximation. The off-axis field expressions for the 3D geometries were tested on the quadrupole ion trap (QIT) and the cylindrical ion trap (CIT), and the corresponding expressions for the 2D geometries were tested on the linear ion trap (LIT) and the rectilinear ion trap (RIT). For each geometry, we have considered apertures which are 10%, 30%, and 50% of the trap dimension. We have found that our analytical correction term EdueToAperture, though based on a classical small-aperture approximation, gives good results even for relatively large apertures.

Kernel-based spatial-color modeling for fast moving object tracking

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

A reverse Stroop task with mouse tracking

In a reverse Stroop task, observers respond to the meaning of a color word irrespective of the color in which the word is printed—for example, the word red may be printed in the congruent color (red), an incongruent color (e.g., blue), or a neutral color (e.g., white). Although reading of color words in this task is often thought to be neither facilitated by congruent print colors nor interfered with incongruent print colors, this interference has been detected by using a response method that does not give any bias in favor of processing of word meanings or processing of print colors. On the other hand, evidence for the presence of facilitation in this task has been scarce, even though this facilitation is theoretically possible. By modifying the task such that participants respond to a stimulus color word by pointing to a corresponding response word on a computer screen with a mouse, the present study investigated the possibility that not only interference but also facilitation would take place in a reverse Stroop task. Importantly, in this study, participants’ responses were dynamically tracked by recording the entire trajectories of the mouse. Arguably, this method provided richer information about participants’ performance than traditional measures such as reaction time and accuracy, allowing for more detailed (and thus potentially more sensitive) investigation of facilitation and interference in the reverse Stroop task. These trajectories showed that the mouse’s approach toward correct response words was significantly delayed by incongruent print colors but not affected by congruent print colors, demonstrating that only interference, not facilitation, was present in the current task. Implications of these findings are discussed within a theoretical framework in which the strength of association between a task and its response method plays a critical role in determining how word meanings and print colors interact in reverse Stroop tasks.