Purpose To describe a new stereotest in the form of a game on an autostereoscopic tablet computer designed to be suitable for use in the eye clinic and present data on its reliability and the distribution of stereo thresholds in adults. Methods Test stimuli were four dynamic random-dot stereograms, one of which contained a disparate target. Feedback was given after each trial presentation. A Bayesian adaptive staircase adjusted target disparity. Threshold was estimated from the mean of the posterior distribution after 20 responses. Viewing distance was monitored via a forehead sticker viewed by the tablet's front camera, and screen parallax was adjusted dynamically so as to achieve the desired retinal disparity. Results The tablet must be viewed at a distance of greater than ∼35 cm to produce a good depth percept. Log thresholds were roughly normally distributed with a mean of 1.75 log 10 arcsec = 56 arcsec and SD of 0.34 log 10 arcsec = a factor of 2.2. The standard deviation agrees with previous studies, but ASTEROID thresholds are approximately 1.5 times higher than a similar stereotest on stereoscopic 3D TV or on Randot Preschool stereotests. Pearson correlation between successive tests in same observer was 0.80. Bland-Altman 95% limits of reliability were ±0.64 log 10 arcsec = a factor of 4.3, corresponding to an SD of 0.32 log 10 arcsec on individual threshold estimates. This is similar to other stereotests and close to the statistical limit for 20 responses. Conclusions ASTEROID is reliable, easy, and portable and thus well-suited for clinical stereoacuity measurements. Translational Relevance New 3D digital technology means that research-quality psychophysical measurement of stereoacuity is now feasible in the clinic.

We utilise collaborative path-finding to improve efficiency of smart parking systems and therefore reduce traffic congestion in metropolitan environments, while increasing efficiency and profitability of parking garages. A significant portion of traffic in urban areas is accounted for by drivers searching for an available parking space. Many cities have adopted a parking guidance and information system to try to alleviate this traffic congestion. Typically these systems entail informing the driver of the whereabouts of an available space, reserving that space for the specific driver, and providing directions to reach the destination. Little or no account is taken of how much congestion will be caused by multiple drivers being directed to the same car-park concurrently. We introduce the concept of collaborative path-finding to the problem. We simulate a smart parking system for an urban environment, and show that a novel approach to collaboratively planning paths for multiple agents can lead to reduced traffic congestion on routes toward busy parking areas, while reducing the amount of time when parking spaces are vacant, thereby increasing the revenue earned.

No abstract

In this paper we describe an implementation of a software transactional memory library for the GPU written in CUDA. We describe the implementation of our transaction mechanism which features both tentative and regular locking along with a contention management policy based on a simple, yet effective, static priority rule called Priority Rule Software Transactional Memory (PR-STM ). We demonstrate competitive performance results in comparison with existing STMs for both the GPU and CPU. While GPU comparisons have been studied, to the best of our knowledge we are the first to provide results comparing GPU based STMs with a CPU based STM.

No abstract