Jason Jingshi Li

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Representing and reasoning spatial and temporal information is a key research issue in Computer Science and Artificial Intelligence. In this paper, we introduce tools that produce three novel encodings which translate problems in qualitative spatial and temporal reasoning into logic programs for answer set programming solvers. Each encoding reflects a(More)
White matter hyperintensities (WMHs) are a frequent finding on T2-weighted MRI of the brain in elderly individuals, but their prevalence and severity in younger asymptomatic populations is less well studied. We report the topography of WMHs on T2-weighted fluid inversion recovery (FLAIR) MRI in 428 individuals aged 44-48 years recruited randomly from a(More)
Air pollution has a direct impact to human health, and data-driven air quality models are useful for evaluating population exposure to air pollutants. In this paper, we propose a novel region-based Gaussian process model for estimating urban air pollution dispersion, and applied it to a large dataset of ultrafine particle (UFP) measurements collected from a(More)
As the Internet of Things grows to large scale, its components will increasingly be controlled by self-interested agents. For example, sensor networks will evolve to community sensing where a community of agents combine their data into a single coherent structure. As there is no central quality control, agents need to be incentivized to provide accurate(More)
Constraint networks in qualitative spatial and temporal reasoning (QSTR) typically feature variables defined on infinite domains. Mainstream algorithms for deciding network consistency are based on searching for network refinements whose consistency is known to be tractable, either directly or by using a SAT solver. Consequently, these algorithms treat all(More)
Urban air pollution have a direct impact on public health. Ultrafine particles (UFPs) are ubiquitous in urban environments, but their distribution are highly variable. In this paper, we take data from mobile deployments in Zürich collected over one year with over 25 million measurements to build a high-resolution map estimating the UFP distribution. More(More)
Sensing and monitoring of our natural environment are important for sustainability. As sensor systems grow to large scale, it will become infeasible to place all sensors under centralized control. We investigate community sensing, where sensors are controlled by self-interested agents that report their measurements to a center. The center can control the(More)
Deciding consistency of constraint networks is a fundamental problem in qualitative spatial and temporal reasoning. In this paper we introduce a divide-and-conquer method that recursively partitions a given problem into smaller sub-problems in deciding consistency. We identify a key theoretical property of a qualitative calculus that ensures the soundness(More)