Publications by authors named "Kuan-Hui Lin"
Article Synopsis
- This study presents a methodology for reconstructing China's temperature index from 1368 to 1911 using the REACHES database, which digitizes historical meteorological records.
- The reconstruction utilizes an ordinal scale ranging from -2 (very cold) to 1 (warm) and retrieved 12,871 records through a standardized coding system.
- The reconstructed temperature index was validated against early instrumental data, demonstrating strong correlations, and annual and seasonal temperature series were produced for both the entire country and specific geographical regions.
Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions.
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- The paper details the ongoing project to create the East Asian climate database REACHES by utilizing Chinese historical documents, specifically the Compendium of Meteorological Records of China.
- It highlights the digitization process of records from 1644 to 1795, including translating original documents and converting time and location into modern formats.
- A hierarchical database system is established to categorize historical meteorological events, while code systems are devised to transform descriptive entries into digital records for computer analysis.
Article Synopsis
- - Weather and climate hazards can cause significant economic losses and societal disruptions, making risk quantification crucial, especially with climate change on the horizon.
- - Climate risk assessments increasingly rely on model chains that utilize both recent data and historical weather information to better simulate impacts.
- - The effective use of historical data involves integrating various sources and methods to enhance climate risk assessment, such as validating models, estimating hazards, and identifying worst-case scenarios.
A meta-learning approach for B-cell conformational epitope prediction.
BMC Bioinformatics
November 2014
Background: One of the major challenges in the field of vaccine design is identifying B-cell epitopes in continuously evolving viruses. Various tools have been developed to predict linear or conformational epitopes, each relying on different physicochemical properties and adopting distinct search strategies. We propose a meta-learning approach for epitope prediction based on stacked and cascade generalizations.
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