Social media in selected Australian federal and state election campaigns, 2010-15

Campaigning in Australian election campaigns at local, state, and federal levels is fundamentally affected by the fact that voting is compulsory in Australia, with citizens who are found to have failed to cast their vote subject to fines. This means that - contrary to the situation in most other nations – elections are decided not by which candidate or party has managed to encourage the largest number of nominal supporters to make the effort to cast their vote, but by some 10-20% of genuine ‘swinging voters’ who change their party preferences from one election to the next. Political campaigning is thus aimed less at existing party supporters (so-called ‘rusted on’ voters whose continued support for the party is essentially taken for granted) than at this genuinely undecided middle of the electorate. Over the past decades, this has resulted in a comparatively timid, vague campaigning style from both major party blocs (the progressive Australian Labor Party [ALP] and the conservative Coalition of the Liberal and National Parties [L/NP]). Election commitments that run the risk of being seen as too partisan and ideological are avoided as they could scare away swinging voters, and recent elections have been fought as much (or more) on the basis of party leaders’ perceived personas as they have on stated policies, even though Australia uses a parliamentary system in which the Prime Minister and state Premiers are elected by their party room rather than directly by voters. At the same time, this perceived lack of distinctiveness in policies between the major parties has also enabled the emergence of new, smaller parties which (under Australia’s Westminster-derived political system) have no hope of gaining a parliamentary majority but could, in a close election, come to hold the balance of power and thus exert disproportionate influence on a government which relies on their support.

"Like a monkey with a miniature cymbal": Cultural practices of repetition in visual social media

Looping media are recurring components of online content, from gifs to Vine videos, in addition to the conceptual repetition of memes and related practices. This paper analyses practices around looping visual media as examples of vernacular creativity, social media literacies, and internet culture, especially for irreverent and playful purposes. Focusing on the LGBTQ digital cultural context as a pilot study, this research examines multi-platform uses of looping media, including personal narratives through Vine videos and animated gifs on Tumblr. In addition to textual analysis of LGBTQ looping visual social media content, the study will further explore the platform context as part of the experience of looped media. The research will address how these factors may also contribute to practices of irreverence and play, both within the specific case of LGBTQ culture and internet culture more generally.

Effect of position on precision within the recording field of a markerless motion capture system

Introduction Markerless motion capture systems are relatively new devices that can significantly speed up capturing full body motion. A precision of the assessment of the finger’s position with this type of equipment was evaluated at 17.30 ± 9.56 mm when compare to an active marker system [1]. The Microsoft Kinect was proposed to standardized and enhanced clinical evaluation of patients with hemiplegic cerebral palsy [2]. Markerless motion capture systems have the potential to be used in a clinical setting for movement analysis, as well as for large cohort research. However, the precision of such system needs to be characterized. Global objectives • To assess the precision within the recording field of the markerless motion capture system Openstage 2 (Organic Motion, NY). • To compare the markerless motion capture system with an optoelectric motion capture system with active markers. Specific objectives • To assess the noise of a static body at 13 different location within the recording field of the markerless motion capture system. • To assess the smallest oscillation detected by the markerless motion capture system. • To assess the difference between both systems regarding the body joint angle measurement. Methods Equipment • OpenStage® 2 (Organic Motion, NY) o Markerless motion capture system o 16 video cameras (acquisition rate : 60Hz) o Recording zone : 4m * 5m * 2.4m (depth * width * height) o Provide position and angle of 23 different body segments • VisualeyezTM VZ4000 (PhoeniX Technologies Incorporated, BC) o Optoelectric motion capture system with active markers o 4 trackers system (total of 12 cameras) o Accuracy : 0.5~0.7mm Protocol & Analysis • Static noise: o Motion recording of an humanoid mannequin was done in 13 different locations o RMSE was calculated for each segment in each location • Smallest oscillation detected: o Small oscillations were induced to the humanoid mannequin and motion was recorded until it stopped. o Correlation between the displacement of the head recorded by both systems was measured. A corresponding magnitude was also measured. • Body joints angle: o Body motion was recorded simultaneously with both systems (left side only). o 6 participants (3 females; 32.7 ± 9.4 years old) • Tasks: Walk, Squat, Shoulder flexion & abduction, Elbow flexion, Wrist extension, Pronation / supination (not in results), Head flexion & rotation (not in results), Leg rotation (not in results), Trunk rotation (not in results) o Several body joint angles were measured with both systems. o RMSE was calculated between signals of both systems. Results Conclusion Results show that the Organic Motion markerless system has the potential to be used for assessment of clinical motor symptoms or motor performances However, the following points should be considered: • Precision of the Openstage system varied within the recording field. • Precision is not constant between limb segments. • The error seems to be higher close to the range of motion extremities.

Wheat biomass and yield increased when populations of the root-lesion nematode (Pratylenchus thornei) were reduced through sequential rotation of partially resistant winter and summer crops

The root-lesion nematode, Pratylenchus thornei, can reduce wheat yields by >50%. Although this nematode has a broad host range, crop rotation can be an effective tool for its management if the host status of crops and cultivars is known. The summer crops grown in the northern grain region of Australia are poorly characterised for their resistance to P. thornei and their role in crop sequencing to improve wheat yields. In a 4-year field experiment, we prepared plots with high or low populations of P. thornei by growing susceptible wheat or partially resistant canaryseed (Phalaris canariensis); after an 11-month, weed-free fallow, several cultivars of eight summer crops were grown. Following another 15-month, weed-free fallow, P. thornei-intolerant wheat cv. Strzelecki was grown. Populations of P. thornei were determined to 150 cm soil depth throughout the experiment. When two partially resistant crops were grown in succession, e.g. canaryseed followed by panicum (Setaria italica), P. thornei populations were <739/kg soil and subsequent wheat yields were 3245 kg/ha. In contrast, after two susceptible crops, e.g. wheat followed by soybean, P. thornei populations were 10 850/kg soil and subsequent wheat yields were just 1383 kg/ha. Regression analysis showed a linear, negative response of wheat biomass and grain yield with increasing P. thornei populations and a predicted loss of 77% for biomass and 62% for grain yield. The best predictor of wheat yield loss was P. thornei populations at 0-90 cm soil depth. Crop rotation can be used to reduce P. thornei populations and increase wheat yield, with greatest gains being made following two partially resistant crops grown sequentially.

The Science and Art of Light

Architecture today often is praised for its tectonics, floating volumes, and sensational, gravity-defying stunts of “starchitecture.” Yet, very so often there is a building that inspires descriptions of the sublime, the experiential, and the power of light and architecture to transcend our expectations. The new Meinel Optical Sciences Research Building, designed by Phoenix-based Richärd+Bauer for the University of Arizona, Tucson, is one of these architectural rarities. Already drawing comparisons to Louis Kahn's 1965 Salk Institute for Biological Studies in La Jolla, California, the indescribable quality of light that characterizes the best of Kahn's work also resonates in Richärd+Bauer's new building. Both an expansion and renovation of the existing College of Optical Sciences facilities, the Meinel building includes teaching and research laboratories, six floors of offices, discussion areas, conference rooms, and an auditorium. The new 47,000 square-foot cast-in-place concrete structure, wrapped on three-sides in copper-alloy panels, harmonizes with the largely brick vocabulary of the campus while reflecting the ethereal quality of the wide Arizona sky. The façade, however, is merely a prelude for what awaits inside—where light and architecture seamlessly combine to create moments of pure awe.

Optimal sleep-wake scheduling for quickest intrusion detection using sensor networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Deeper and wider fully convolutional network coupled with conditional random fields for scene labeling

Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning. One of the advantages of DCNNs is their representation robustness to object locations, which is useful for object recognition tasks. However, this also discards spatial information, which is useful when dealing with topological information of the image (e.g. scene labeling, face recognition). In this paper, we propose a deeper and wider network architecture to tackle the scene labeling task. The depth is achieved by incorporating predictions from multiple early layers of the DCNN. The width is achieved by combining multiple outputs of the network. We then further refine the parsing task by adopting graphical models (GMs) as a post-processing step to incorporate spatial and contextual information into the network. The new strategy for a deeper, wider convolutional network coupled with graphical models has shown promising results on the PASCAL-Context dataset.

Optimal Sleep-Wake Scheduling for Quickest Intrusion Detection using wireless sensor Networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices,we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: 1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, 2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which 3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time),based on the sensor observations obtained until time slot k.Our results show that an optimum closed loop control onMk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

A k-epsilon model for turbulent weld pool convection in gas metal arc welding process

In this paper, we present a modified k - epsilon model capable of addressing turbulent weld-pool convection in a GMAW process, taking into account the morphology of the phase change interface during a Gas Metal Arc Welding (GMAW) process. A three-dimensional turbulence mathematical model has been developed to study the heat transfer and fluid flow within the weld pool by considering the combined effect of three driving forces, viz., buoyancy, Lorentz force and surface tension (Marangoni convection). Mass and energy transports by the droplets are considered through the thermal analysis of the electrode. The falling droplet's heat addition to the molten pool is considered to be a volumetric heat source distributed in an imaginary cylindrical cavity ("cavity model") within the weld pool. This nature of heat source distribution takes into account the momentum and the thermal, energy of the falling droplets. The numerically predicted weld pool dimensions both from turbulence and laminar models are then compared with the experimental post-weld results sectioned across the weld axis. The above comparison enables us to analyze the overall effects of turbulent convection on the nature of heat and fluid flow and hence on the weld pool shape/size during the arc welding processes.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

THE FORMATION MECHANISM OF THE VITRIFIED SLAG IN A PLASMA ARC REACTOR FOR HAZARDOUS WASTE TREATMENT

Various hazardous wastes with additives have been vitrified to investigate the formation mechanism of the glassy slag by a 30 kW DC plasma-arc reactor developed by the Institute of Mechanics, Chinese Academy of Sciences. The average temperature in the reaction area is controlled at 1500°C. The chemical compositions of three sorts of fly ashes are analyzed by XRF (X-Ray Fluorescence). Fly ashes with vitrifying additives can be vitrified to form glassy slag, which show that the ratio of the whole oxygen ions to the whole network former ions in glass (R) is appropriate in the range of 2~3 to form durable vitrified slag. In this experiment, the arc power is controlled below 5 kW to inhibit waste evaporation. To enhance the effects of heat transfer to wastes, ferrous powder has been added into the graphite crucible, which aggregates as ingot below the molten silicate after vitrification. The slag fails to form glass if the quenching rate is less than 1 K/min. Therefore, the slag will break into small chips due to the sharp quenching rate, which is more than 100 K/sec.