Star Identification Based on Multilayer Voting Algorithm for Star Sensors

This paper describes the multilayer voting algorithm, a novel autonomous star identification method for spacecraft attitude determination. The proposed algorithm includes two processes: an initial match process and a verification process. In the initial match process, a triangle voting scheme is used to acquire candidates of the detected stars, in which the triangle unit is adopted as the basic voting unit. During the identification process, feature extraction is implemented, and each triangle unit is described by its singular values. Then the singular values are used to search for candidates of the imaged triangle units, which further improve the efficiency and robustness of the algorithm. After the initial match step, a verification method is applied to eliminate incorrect candidates from the initial results and then outputting the final match results of the imaged stars. Experiments show that our algorithm has more robustness to position noise, magnitude noise, and false stars than the other three algorithms, the identification speed of our algorithm is largely faster than the geometric voting algorithm and optimized grid algorithm. However, it takes more memory, and SVD also seems faster.

Cultural evolution of football tactics: Strategic social learning in managers' choice of formation

In order to solve complex problems or make difficult decisions, people must strategically combine personal information acquired directly from experience (individual learning) and social information copied from others (social learning). The game of football (soccer) provides a wealth of real world data with which to quantify managers' use of personal and social information in selecting team formations. I analyse a 5-year dataset of all games (n=9127, 2012-2017) in the five top European leagues (English Premier League, German Bundesliga, Spanish La Liga, French Ligue 1 and Italian Serie A) to quantify the extent to which a manager's initial match formation is guided by their personal past use or success with that formation, or other managers' use or success with that formation. I focus in particular on the use of the 4231 formation, which was the dominant formation at the start of this period but showed a gradual decline in use over time. I find that, as predicted, a manager's choice of whether to use 4231 or not is influenced by both their recent use of 4231 (personal information) and the use of 4231 in the entire population of managers in that division (social information). Contrary to expectations, managers appeared to rely more on personal than social information, although this estimate was highly variable across managers and divisions. Serie A managers, in particular, showed a much stronger use of personal information, likely due to the rarity of 4231 in that division. Finally, there did not appear to be an adaptive tradeoff between social and personal information use, with the relative reliance on each failing to predict managerial success.

Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation

ObjectiveWe describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology.MethodsProprietary CT exam terms and corresponding exam frequency data were obtained from 40 participant HIE sites that transmitted radiology data to the HIE from January 2013 through October 2015. These terms were mapped to the Logical Observations Identifiers Names and Codes (LOINC®) terminology using the Regenstrief LOINC mapping assistant (RELMA) beginning in January 2016. Terms without initial LOINC match were submitted to LOINC as new term requests on an ongoing basis. After new LOINC terms were created, proprietary terms without an initial match were reviewed and mapped to these new LOINC terms where appropriate. Content type and token coverage were calculated for the LOINC version at the time of initial mapping (v2.54) and for the most recently released version at the time of our analysis (v2.63). Descriptive analysis was performed to assess for significant differences in content-dependent coverage between the 2 versions.ResultsLOINC’s content type and token coverages of HIE CT exam terms for version 2.54 were 83% and 95%, respectively. Two-hundred-fifteen new LOINC CT terms were created in the interval between the releases of version 2.54 and 2.63, and content type and token coverages, respectively, increased to 93% and 99% (P < .001).ConclusionLOINC’s content type coverage of proprietary CT terms across 40 HIE sites was 83% but improved significantly to 93% following new term creation.

Image Dense Matching Method Based on Wavelet Edge Detection and Region Growing

Aiming at the computer vision image, firstly, image edge feature is obtained using the edge detection algorithm based on wavelet analysis, selecting some seed points, comparing the gray similarity of seeds, the result of the initial match is based on the SIFT matching algorithm. The weighted SSD (Sum of Squared Difference) series, as the objective function, spread the seeds to the rest of the image matching area with the original growing strategy. Experimental results show that the algorithm was effective to large parallax pictures, images without calibration, and images which textures are sparse.

From universal to language-specific in early grammatical development

Attempts to explain children’s grammatical development often assume a close initial match between units of meaning and units of form; for example, agents are said to map to sentence-subjects and actions to verbs. The meanings themselves, according to this view, are not influenced by language, but reflect children’s universal non-linguistic way of understanding the world. This paper argues that, contrary to this position, meaning as it is expressed in children’s early sentences is, from the beginning, organized on the basis of experience with the grammar and lexicon of a particular language. As a case in point, children learning English and Korean are shown to express meanings having to do with directed motion according to language-specific principles of semantic and grammatical structuring from the earliest stages of word combination.