• Journal of Species Research
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• v.10 no.4
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• pp.356-363
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• 2021

Heterotrophic nanoflagellates (HNFs, 2-20 ㎛ in size) are substantially capable of controlling bacterial abundance in aquatic environments, and microbial taxonomists have studied ecologically important and abundant HNFs for a long time. However, the classifications of HNFs have rarely been reported in Korea on the basis of morphology and 18S rDNA sequencing. Here, previously reported five HNFs from non-Korean habitats were isolated from Korean coastal seawater or intertidal sediments for the first time. Light microscopic observations and 18S rDNA phylogenetic trees revealed that the five isolated species were Cafeteria burkhardae strain PH003, Cafeteria graefeae strain UL001, Aplanochytrium minuta (formerly Labyrinthuloides minuta) strain PH004, Neobodo curvifilus strain KM017 (formerly Procryptobia sorokini), and Ancyromonas micra (formerly Planomonas micra) strain IG005. Being morphologically and phylogenetically indistinct from its closest species, all isolates from Korea were therefore regarded as identical species detected in other countries. Thus, this result indicates an expansion of known habitats that range from those of the five isolates in natural ecosystems on Earth.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.378-385
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• 2023

Human biosignals provide essential information for diagnosing diseases such as dementia and Parkinson's disease. Owing to the shortcomings of current clinical assessments, noninvasive solutions are required. Machine learning (ML) on wearable sensor data is a promising method for the real-time monitoring and early detection of abnormalities. ML facilitates disease identification, severity measurement, and remote rehabilitation by providing continuous feedback. In the context of wearable sensor technology, ML involves training on observed data for tasks such as classification and regression with applications in clinical metrics. Although supervised ML presents challenges in clinical settings, unsupervised learning, which focuses on tasks such as cluster identification and anomaly detection, has emerged as a useful alternative. This review examines and discusses a variety of ML algorithms such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Neural Networks (NN), and Deep Learning for the analysis of complex clinical data.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.19-19
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• 2015

The term of Mushrooms means to spread like the April showers. After 18th century, the mycelium and spores of mushrooms were observed by microscope and then was denominated as fungi. About one hundred thousand species of mushrooms in appearance were worldly reported, and in Korea about four thousand species of mushrooms are estimated. In Korea, total of one thousand nine hundred one species of mushrooms have been recorded. Mushrooms belonging to the group of organisms called fungi, which must obtain their food from living plants or animals or from their remains after death. A large number of mushrooms grow in association with the roots of trees and other woody plants, called mycorrhizal fungi, both mushrooms and plants require this relationship for growth and development. And also many Mushrooms are saprobic, living on decayed various fallen leaves, twigs, trees and vegetable remains and etc. some of these million of spores settles on the proper habitat, these spores germinates and grows into a mass of threads, then a mycelium. This is the vegetable part of the mushrooms, what we call mushrooms are the carpophores, all the characteristics of the morphological features are appropriately used to identify species of mushrooms. Recently, identification and classification of mushrooms are newly confirmed by molecular analysis. In 2013, One thousand nine hundred one species of mushrooms in "List of Mushrooms in Korea" which published by the Korean Society of Mycology were recorded. Total of 238species, 107genera, 40families, 13orders, 6Classes belong to phylum Ascomycota. Total of 1,663species, 403genera 81families, 18orders, 7classes belong to phylum Basidiomycota.

• The Korean Journal of Ecology
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• v.24 no.5
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• pp.259-265
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• 2001

This paper describes the species composition of the remnant forest vegetation (Natural Monument No. 65) in the Mok-do island of Ulsan city and its relation to ecological long-term monitoring. Syntaxonomical classification and actual vegetation map were depicted in very fine scale 1:800 for better understanding spatial distribution and vitality of individual trees and communities. A total of 111 species and 13 plant communities occurred on the 19,166 ㎡ area. Evergreen broad-leaved forest of Machilus thunbergii is a representative vegetation type, which covers 37.4% of the island area. Evergreen coniferous forest of Pinus thunbergii covers 18.6% of the island. These two forests occurred at different parts of the island, i.e., the former at the rearward and the later at the frontward of island against marine. 95.7% of trees analysed was determined as critically and absolutely monitored individuals. From a conservation perspective the Mok-do vegetation is extremely vulnerable, which must be long-termly monitored using an assessment of tree vitality and a fine scale map of vegetation.

• Journal of Life Science
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• v.16 no.2 s.75
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• pp.253-258
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• 2006

Garlic is a perennial herb primarily distributed throughout the world. These plants are regarded as a medically and agricultural important crop in the world. The genetic relationships between cultivated and wild species were investigated at the population levels by constructing tree based on ISSR (inter-simple sequence repeats) markers. In addition, ISSR analysis was also conducted to estimate genetic diversity and population structure of these species. Three wild garlic populations in Korea were found to have more alleles per locus (mean 1.672 vs. 1.510) higher percent polymorphic locus (67.2 vs. 51.0), and higher diversity (0.250 vs. 0.198) than three cultivated populations. The cultivated and wild species in Korea are well separated from each other at phylogenetic trees. Although there is not direct evidence that A. victorialis is an ancestor of Korean A. sativum, there is a possibility that cultivated A. sativum in Korea has evolved from wild A. victorialis in Korea. Populations of A. victorialis may be useful in germ-plasm classification and evolutionary process.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.9-16
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• 2019

The goal of this study is to propose an efficient model for recognizing and classifying tree images to measure the accuracy that can be applied to smart devices during class. From the 2009 revised textbook to the 2015 revised textbook, the learning objective to the fourth-grade science textbook of elementary schools was added to the plant recognition utilizing smart devices. In this study, we compared the recognition rates of trees before and after retraining using a pre-trained inception V3 model, which is the support of the Google Inception V3. In terms of tree recognition, it can distinguish several features, including shapes, bark, leaves, flowers, and fruits that may lead to the recognition rate. Furthermore, if all the leaves of trees may fall during winter, it may challenge to identify the type of tree, as only the bark of the tree will remain some leaves. Therefore, the effective tree classification model is presented through the combination of the images by tree type and the method of combining the model for the accuracy of each tree type. I hope that this model will apply to smart devices used in educational settings.

• Korean Journal of Environment and Ecology
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• v.21 no.2
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• pp.141-148
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• 2007

To investigate the forest community structure ranging from 200 meters to 1,350 meters above sea level at Donnaeko valley of Mt. Hallasan in 2006, 15 plots were surveyed. According to the classification analysis by TWINSPAN, the plant communities were divided into five groups of Castanopsis sieboidii community, Castanopsis sieboldii - Quercus acuta community, mixed forest, Carpinus laxiflora - Quercus serrata community and deciduous broad-leaved forest. 22 species of evergreen broad-leaved trees such as Castanopsis sieboldii, Quercus acuta, Distylium racemosum, Camellia japonica, Eurya japonica, Ligustrum lucidum, Ilex crenata, Daphnipyllum macropodum, etc. were growing at Donnaeko valley. According to the attitudinal distribution of evergreen broad-leaved trees, Castanopsis sieboidii was a dominant species distributed from 200 meters to 350 meters above sea level, Castanopsis sieboldii and Quercus acuta were dominant species distributed from 400 meters to 600 meters above sea level and Quercus acuta was a dominant species distributed from 660 meters to 700 meters above sea level. Ilex crenata, Daphniphyllum macropodum, Elaeagnus glabra were distributed up to 1,350 meters above sea level in Donnaeko.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.2
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• pp.131-140
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• 2004

It really needs fuzzy decision making of integrity assessment considering about both durability and load carrying capacity for maintenance and administration, such as repairing and reinforcing. This thesis shows efficient models about reinforced concrete structure using CART-ANFIS. It compares and analyzes decision trees parts of expert system, using the theory of fuzzy, and applying damage & diagnosis at reinforced concrete structure and decision trees of integrity assessment using established artificial neural. Decided the theory of reinforcement design for recovery of durability at damaged concrete ＆ the theory of reinforcement design for increasing load carrying capacity keep stability of damage and detection. It is more efficient maintenance and administration at reinforced concrete for using integrity assessment model of this study and can carry out predicting cost of life cycle.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.533-540
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• 2004

This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

• Journal of Korean Academy of Nursing
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• v.43 no.1
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• pp.1-10
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• 2013

Purpose: The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. Methods: A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. Results: The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. Conclusion: The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.