1.Deep Neural Network-Based Concentration Model for Oak Pollen Allergy Warning in South Korea
Yun Am SEO ; Kyu Rang KIM ; Changbum CHO ; Jae Won OH ; Tae Hee KIM
Allergy, Asthma & Immunology Research 2020;12(1):149-163
PURPOSE: Oak is the dominant tree species in Korea. Oak pollen has the highest sensitivity rate among all allergenic tree species in Korea. A deep neural network (DNN)-based estimation model was developed to determine the concentration of oak pollen and overcome the shortcomings of conventional regression models. METHODS: The DNN model proposed in this study utilized weather factors as the input and provided pollen concentrations as the output. Weather and pollen concentration data were used from 2007 to 2016 obtained from the Korea Meteorological Administration pollen observation network. Because it is difficult to prevent over-fitting and underestimation by using a DNN model alone, we developed a bootstrap aggregating-type ensemble model. Each of the 30 ensemble members was trained with random sampling at a fixed rate according to the pollen risk grade. To verify the effectiveness of the proposed model, we compared its performance with those of models of regression and support vector regression (SVR) under the same conditions, with respect to the prediction of pollen concentrations, risk levels, and season length. RESULTS: The mean absolute percentage error in the estimated pollen concentrations was 11.18%, 10.37%, and 5.04% for the regression, SVR and DNN models, respectively. The start of the pollen season was estimated to be 20, 22, and 6 days earlier than that predicted by the regression, SVR and DNN models, respectively. Similarly, the end of the pollen season was estimated to be 33, 20, and 9 days later that predicted by the regression, SVR and DNN models, respectively. CONCLUSIONS: Overall, the DNN model performed better than the other models. However, the prediction of peak pollen concentrations needs improvement. Improved observation quality with optimization of the DNN model will resolve this issue.
Korea
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Pollen
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Quercus
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Rhinitis, Allergic
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Rhinitis, Allergic, Seasonal
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Seasons
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Trees
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Weather
2.The Atom of Evolution.
Jonghwa BHAK ; Dan BOLSER ; Daeui PARK ; Yoobok CHO ; Kiesuk YOON ; Semin LEE ; SungSam GONG ; Insoo JANG ; Changbum PARK ; Maryana HUSTON ; Hwanho CHOI
Genomics & Informatics 2004;2(4):167-173
The main mechanism of evolution is that biological entities change, are selected, and reproduce. We propose a different concept in terms of the main agent or atom of evolution: in the biological world, not an individual object,but its interactive network is the fundamental unit of evolution. The interaction network is composed of interaction pairs of information objects that have order information. This indicates a paradigm shift from 3D biological objects to an abstract network of information entities as the primary agent of evolution. It forces us to change our views about how organisms evolve and therefore the methods we use to analyze evolution.
3.Allergenic Pollen Calendar in Korea Based on Probability Distribution Models and Up-to-Date Observations
Ju Young SHIN ; Mae Ja HAN ; Changbum CHO ; Kyu Rang KIM ; Jong Chul HA ; Jae Won OH
Allergy, Asthma & Immunology Research 2020;12(2):259-273
PURPOSE: The pollen calendar is the simplest forecasting method for pollen concentrations. As pollen concentrations are liable to seasonal variations due to alterations in climate and land-use, it is necessary to update the pollen calendar using recent data. To attenuate the impact of considerable temporal and spatial variability in pollen concentrations on the pollen calendar, it is essential to employ a new methodology for its creation.METHODS: A pollen calendar was produced in Korea using data from recent observations, and a new method for creating the calendar was proposed, considering both risk levels and temporal resolution of pollen concentrations. A probability distribution was used for smoothing concentrations and determining risk levels. Airborne pollen grains were collected between 2007 and 2017 at 8 stations; 13 allergenic pollens, including those of alder, Japanese cedar, birch, hazelnut, oak, elm, pine, ginkgo, chestnut, grasses, ragweed, mugwort and Japanese hop, were identified from the collected grains.RESULTS: The concentrations of each pollen depend on locations and seasons due to large variability in species distribution and their environmental condition. In the descending order of concentration, pine, oak and Japanese hop pollens were found to be the most common in Korea. The pollen concentrations were high in spring and autumn, and those of oak and Japanese hop were probably the most common cause of allergy symptoms in spring and autumn, respectively. High Japanese cedar pollen counts were observed in Jeju, while moderate concentrations were in Jeonju, Gwangju and Busan.CONCLUSIONS: A new methodology for the creation of a pollen calendar was developed to attenuate the impact of large temporal and spatial variability in pollen concentrations. This revised calendar should be available to the public and allergic patients to prevent aggravation of pollen allergy.
Alnus
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Ambrosia
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Artemisia
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Asian Continental Ancestry Group
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Betula
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Busan
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Climate
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Corylus
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Cryptomeria
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Forecasting
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Ginkgo biloba
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Gwangju
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Humans
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Hypersensitivity
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Jeollabuk-do
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Korea
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Methods
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Poaceae
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Pollen
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Rhinitis, Allergic, Seasonal
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Seasons