Construction, observation and knowledge abstraction for go endgames on small boards.

A Go endgame database consists of optimal game values and moves for every legal arrangement of no more than S pieces on an N by N board. This paper describes methods for constructing such databases when 1 < N ≤ 5 and S = N 2 . When cycles of plies with lengths greater than 4 are encountered, two rules, one allowing cycles and the other disallowing them, are implemented. Observations and knowledge are obtained for these endgames, which may elucidate the fundamental properties of the popular game Go. First, the optimal game values are different when N is even and odd, regardless of whether the repetition of positions is allowed. When N is odd, the first player can occupy the whole board, while this is not the case when N is even. Second, allowing cycles makes the first and second players equal in strength when N is even, whereas the first player always dominates when N is odd. Using the state-of-the-art open-source deep learning Go engine KataGo to correctly solve a given position as an indicator, factors affecting level of difficulty are found, including the distributions of the optimal game values among all legal plies and the cardinality and values of the true optimal plies. A simple formula is designed that works on more than 10% of the positions so that positions with a given level of difficulty can be found with a high probability.

Bidirectional association between obstructive sleep apnea and depression: A population-based longitudinal study.

An association may exist between obstructive sleep apnea (OSA) and depression. However, results regarding this association are inconsistent, and the direction of the association between OSA and depression remains unknown. Therefore, we used the Taiwan National Health Insurance Research Database to investigate the bidirectional association between OSA and depression.A total of 6427 OSA patients and 32,135 age and sex-matched control subjects were enrolled to analyze the risk of depression among patients with OSA, where 27,073 patients with depression and 135,365 control subjects were enrolled to address the risk of OSA among patients with depression. All subjects were followed to identify their outcomes of interest from January 1, 1997 to December 31, 2012.Cox proportional-hazards models, after adjusting for potential confounders, demonstrated that patients with OSA had an increased risk (adjusted hazard ratio 2.48, 95% confidence interval 2.20-2.79) of developing depression, whereas those with depression were associated with an increased risk of future OSA (adjusted hazard ratio 2.30, 95% confidence interval 2.11-2.50).Our results suggested that a strong bidirectional relationship exists between OSA and depression, with each disease influencing the development of the other. Health providers are recommended to ensure the early detection and management of depression among patients with OSA and vice versa.

Efficient simulation of the spatial transmission dynamics of influenza.

Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we present a significant improvement to the efficiency of an individual-based stochastic disease simulation framework commonly used in multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations. The ability to perform efficient simulation allows us to run a batch of simulations and take account of their average in real time. The averaged data are stable and can be used to differentiate spreading patterns that are not readily seen by only conducting a few runs.

Medical privacy protection based on granular computing.

Based on granular computing methodology, we propose two criteria to quantitatively measure privacy invasion. The total cost criterion measures the effort needed for a data recipient to find private information. The average benefit criterion measures the benefit a data recipient obtains when he received the released data. These two criteria remedy the inadequacy of the deterministic privacy formulation proposed in Proceedings of Asia Pacific Medical Informatics Conference, 2000; Int J Med Inform 2003;71:17-23. Granular computing methodology provides a unified framework for these quantitative measurements and previous bin size and logical approaches. These two new criteria are implemented in a prototype system Cellsecu 2.0. Preliminary system performance evaluation is conducted and reviewed.

Preserving confidentiality when sharing medical database with the Cellsecu system.

We propose a computer system called Cellsecu that maintains the anonymity and the confidentiality of each cell containing sensitive information in medical database. Cellsecu attains this by automatically removing, generalizing, and expanding information. It is designed to enhance data privacy protection so a data warehouse can automatically handle queries. In most cases, health organizations collect medical data with explicit identifiers, such as name, address and phone number. Simply removing all explicit identifiers prior to release of the data is not enough to preserve the data confidentiality. Remaining data can be used to re-identify individuals by linking or matching the data to other database, or by looking at unique characteristics found in the database. A formal model based on Modal logic is the theoretical foundation of Cellsecu. As well, a new confidentiality criteria called "non-uniqueness" is defined and implemented. We believe modeling this problem formally can clarify the issue as well as clearly identify the boundary of current technology. Base on our preliminary performance evaluation, the confidentiality check module and the confidentiality enhancing module only slightly degrade system performance.