Appendix 2: Color Coordinate Conversion

Digital Image Processing ◽

10.1002/9780470097434.app2 ◽

2007 ◽

pp. 753-757

Keyword(s):

Color Coordinate ◽

Coordinate Conversion

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Accelerating protein coordinate conversion using GPUs

2014 IEEE High Performance Extreme Computing Conference (HPEC) ◽

10.1109/hpec.2014.7040965 ◽

2014 ◽

Cited By ~ 1

Author(s):

Mahsa Bayati ◽

Jaydeep P. Bardhan ◽

David M. King ◽

Miriam Leeser

Keyword(s):

Coordinate Conversion

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Deep machine learning of the spectral power distribution of the LED system with multiple degradation mechanisms

Journal of Mechanics ◽

10.1093/jom/ufaa025 ◽

2020 ◽

Vol 37 ◽

pp. 172-183

Author(s):

Cadmus C A Yuan ◽

JiaJie Fan ◽

XueJun Fan

Keyword(s):

Machine Learning ◽

Thermal Aging ◽

Empirical Relationship ◽

Machine Learning Techniques ◽

Color Temperature ◽

Design Parameters ◽

Degradation Mechanisms ◽

Theoretical Understanding ◽

Color Coordinate ◽

Led Luminaire

Abstract The performance and reliability of the light-emitting diode (LED) system significantly depend on the thermal–mechanical loading-enhanced multiple degradation mechanisms and their interactions. The complexity of the LED system restricts the theoretical understanding of the root causes of the luminous fluctuation or the establishment of the direct correlation between the thermal aging loading and the luminous outputs. This paper applies the deep machine learning techniques and develops a gated network with the two-step learning algorithm to build the empirical relationship between the design parameters and the thermal aging loading and the luminous output of LED products. The flexibility of the proposed method will be demonstrated by integrating it with different neural network architectures. The proposed gated network concept has been validated in both multiple LED chip packaging and LED luminaire under thermal aging loading. The validation of the luminous data of multiple LED chip packaging shows that the maximum differences of the correlated color temperature (CCT) and color coordinate are 2.6% and 1.0%, respectively. Moreover, the machine learning results of the LED luminaire exhibit that the differences of lumen depreciation, CCT and color coordinate are 1.6%, 1.9% and 1.1%, after 2160 h of thermal aging.

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Historical map viewer technology that guarantees nonlinear bijective conversion without distortion

Abstracts of the ICA ◽

10.5194/ica-abs-1-284-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-2

Author(s):

Kohei Otsuka

Keyword(s):

Open Source ◽

History Education ◽

Historical Maps ◽

Ordinary People ◽

Historical Information ◽

Old Maps ◽

Aesthetic Appearance ◽

Historical Education ◽

The Aesthetic ◽

Coordinate Conversion

Abstract. Historical maps rich in historical information play an important role in fields such as tourism and history education. However, for ordinary people without knowledge of historical studies, it is difficult to understand inaccurate old maps that have not undergone surveying and to comprehend them in comparison with the current city townscape. Therefore, conventionally in GIS, a large number of corresponding points are prepared between an inaccurate historical map and an accurate map, the coordinates of the historical map are converted by forming a triangular mesh and conducting coordinate complement calculation, and the entire historical map image is re-represented by coordinate conversion. However, as shown in Figure 1, with this method there is a serious problem that causes distortion in the aesthetic appearance of the historical map, and remarkable impairment. It can be said that this problem has greatly damaged opportunities to use historical maps for tourism and historical education.In this paper, we introduce our technology to solve this problem. Our technology has been implemented in the historical map viewer named Maplat, which is available at https://github.com/code4nara/Maplat as MIT-licensed open source.

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The Bovine Genome Variation Database (BGVD): Integrated Web-database for Bovine Sequencing Variations and Selective Signatures

10.1101/802223 ◽

2019 ◽

Cited By ~ 1

Author(s):

Ningbo Chen ◽

Weiwei Fu ◽

Jianbang Zhao ◽

Jiafei Shen ◽

Qiuming Chen ◽

...

Keyword(s):

Bovine Genome ◽

Distribution Patterns ◽

Global Scale ◽

Genomic Region ◽

Genome Browser ◽

Web Database ◽

Genome Variation ◽

Gene Search ◽

Variation Database ◽

Coordinate Conversion

AbstractNext-generation sequencing has yielded a vast amount of cattle genomic data for the global characterization of population genetic diversity and the identification of regions of the genome under natural and artificial selection. However, efficient storage, querying and visualization of such large datasets remain challenging. Here, we developed a comprehensive Bovine Genome Variation Database (BGVD, http://animal.nwsuaf.edu.cn/BosVar) that provides six main functionalities: Gene Search, Variation Search, Genomic Signature Search, Genome Browser, Alignment Search Tools and the Genome Coordinate Conversion Tool. The BGVD contains information on genomic variations comprising ∼60.44 M SNPs, ∼6.86 M indels, 76,634 CNV regions and signatures of selective sweeps in 432 samples from modern cattle worldwide. Users can quickly retrieve distribution patterns of these variations for 54 cattle breeds through an interactive source of breed origin map using a given gene symbol or genomic region for any of the three versions of the bovine reference genomes (ARS-UCD1.2, UMD3.1.1, and Btau 5.0.1). Signals of selection are displayed as Manhattan plots and Genome Browser tracks. To further investigate and visualize the relationships between variants and signatures of selection, the Genome Browser integrates all variations, selection data and resources from NCBI, the UCSC Genome Browser and AnimalQTLdb. Collectively, all these features make the BGVD a useful archive for in-depth data mining and analyses of cattle biology and cattle breeding on a global scale.

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