• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.247-252
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• 2006

오염 퇴적물내 중금속의 방출과 이에 따른 생이용성(bioavalability)은 기존의 가역 평형관계로써 설명하기에 불충분한 것으로 알려져 있다. 최근 연구결과에 의하면 이러한 탈착 저항성을 설명하기 위한 비가역적 모델에 의해 퇴적물내 중금속의 탈착저항성 부분이 존재함이 밝혀졌다. 탈착저항성에 대해서는 아직 충분한 규명이 이루어지지 않았으나, 오염물질의 노화(aging)에 의해 일단 탈착저항성을 띠게 되면 생이용성(bioavailability)이 감소되는 것으로 알려져 있다. 본 연구에서는 노화(aging)가 연안 퇴적물 내 납과 카드뮴의 흡/탈착 특성에 미치는 영향을 알아보기 위해 연속 탈착실험과 biphasic 탈착모델을 적용함으로써 납과 카드뮴의 탈착저항성을 규명하고자 하였다. 그리고 연속 추출 실험을 통해서 노화(aging)에 따른 퇴적물 내 납과 카드뮴의 흡착 기작을 규명하고자 하였다. 연속탈착 실험 결과 시간이 경과함에 따라 탈착저항성부분의 크기가 증가하였으며, 연속추출 실험 결과 납의 경우 carbonate fraction에서 추출된 납이 가장 많았으며, 노화(aging) 따라 exchangeable fraction에서 추출된 납이 감소하는 반면 reducible, organic material, residual fraction에서 추출된 납의 양이 증가하였다. 카드뮴의 경우 가장 많은 양이 추출된 단계는 exchangeable fraction이였으며, organic material fraction에서는 카드뮴이 추출되지 않았다. 노화(aging) 따라 reducible fraction과 residual fraction에서의 추출량이 증가하는 경향을 보였으나 그 양은 매우 적은 것으로 나타났으며, 노화(aging)에 따른 exchangeable fraction과 carbonate fraction에서의 추출량은 큰 변화가 없었다. 대해서는 북한지역의 분포상황을 밝혔다.것을 알 수 있었으며, 크롬과 비소의 경우는 초기에 많이 용출되고, 구리의 경우는 꾸준히 용출되는 것을 알 수 있었다. 3년 된 통나무집이 8년 된 통나무집보다. 용출양이 더 컸으며, 이는 CCA성분이 초기에 많이 용출된다는 것을 의미한다. 억제 효과를 나타내었고 Hep3B에서는 부탄을 분획물 (1 mg/mL)에서 82%의 비교적 높은 성장억제효과를 나타내었다.as a "front" and "back". Thus, Germany′s private space may face a genuine public space and street, which is rare in the Korean housing. Although the layout of indoor space in the korean housing tends to be open, such an openness may be outstanding in living and dining spaces, kitchen and various accesses to rooms. In the case of Germany, such indoor spaces are usually closed to each other. Thus corridors act to separate these spaces. Such differences are analysed to be due to the different perceptions of interpersonal and socio-cultural attributes as intra-family and inter-neighbor relationships or communications. 알 수 있었다.도 질소와 인산처럼 토양지지대가 있는 경우가 낮은 함량을 유지하였다.pe from the daily life, to fantasize and daydre

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.439-448
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• 1996

Extraction and selection of the informative features play a central role in pattern recognition. This paper describes a modified back-propagation algorithm that performs selection of the informative features and trains a neural network simultaneously. The algorithm is mainly composed of three repetitive steps : training, connection pruning, and input unit elimination. Afer initial training, the connections that have small magnitude are first pruned. Any unit that has a small number of connections to the hidden units is deleted,which is equivalent to excluding the feature corresponding to that unit.If the error increases,the network is retraned,again followed by connection pruning and input unit elimination.As a result,the algorithm selects the most im-portant features in the measurement space without a transformation to another space.Also,the selected features are the most-informative ones for the classification,because feature selection is tightly coupled with the classifi-cation performance.This algorithm helps avoid measurement of redundant or less informative features,which may be expensive.Furthermore,the final network does not include redundant parameters,i.e.,weights and biases,that may cause degradation of classification performance.In applications,the algorithm preserves the most informative features and significantly reduces the dimension of the feature vectors whiout performance degradation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.582-583
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Korean Journal of Food Science and Technology
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• v.41 no.3
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• pp.326-333
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• 2009

Heterocyclic aromatic amines (HCAs) are mutagenic and carcinogenic substances that are formed during the heating of protein-rich foods. HCAs are generally found at low amounts in a complex matrix, which requires sophisticated analysis. In this study, HCAs were extracted from lyophilized fish and shellfish samples using solid-phase extraction (SPE) and determined by liquid chromatography-electrospray ionization/mass spectrometry (LC-ESI-MS). The HCA recoveries in the fish and shellfish ranged from 15.7 to 74.7% with standard deviations from 0.2 to 7.63%. And HCA concentrations ranged from 0.8 to 1,117.7 $ng/g^{-1}$ in cooked food samples. 1-methyl-9H-pyrido[3,4-b]indole (Harman), 9H-pyrido[3,4-b]indole (Norharman), and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) were the most abundant HCAs formed in the muscle of fried mackerel, at levels of 1,117.7, 926.6, and 133.7 ng/g, respectively. 3-amino-1-methyl-5H-pyrido[4,3-b]indole (Trp-P-2), 2-aminodipiryrido[1,2-a:3,2-d]imidazole(Glu-P-2), 2-amino-9H-pyrido[2,3-b]indole(A${\alpha}$C), 2-amino-3methyl-9H-pyrido [1,2-a:3,2-d]imidazole(MeA${\alpha}$C), 2-amino-3,4,7,8-tetramethylimidazo[4,5-f]quinoxaline (TriMeIQx), 2-amino-3,7,8-trimethylimidazo [4,5-f]quinoxaline(7,8-DiMeIQx), and 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) were only detected by small quantities ranged from 1.5 to 98.6 ng/g. Overall, this study provides useful information on HCA levels in fish and shellfish products consumed in Korea.

• Journal of Periodontal and Implant Science
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• v.28 no.4
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• pp.645-660
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• 1998

The purpose of this study was to make and ascertain a decision making process on the base of patient-oriented utilitarianism in the treatment of patients of chronic adult periodontitis. Fifty subjects were chosen in Yonsei Dental hospital and the other fifty were chosen in Severance dental hospital according to the selection criteria. Fifty four patients agreed in this study. NS group(N=32) was treated with scaling and root planing without any surgical intervention, the other S group(N=22) done with flap operation. During the active treatment and healing time, all patients of both groups were educated about the importance of oral hygiene and controlled every visit to the hospital. When periodontal treatment needed according to the diagnostic results, some patients were subjected to professional tooth cleaning and scaling once every 3 months according to an individually designed oral hygienic protocol. Probing depth was recorded on baseline and 18 months after treatments. A questionnaire composed of 6 kinds(hygienic easiness, hypersensitivity, post treatment comfort, complication, functional comfort, compliance) of questions was delivered to each patient to obtain the subjective evaluation regarding the results of therapy. The decision tree for the treatment of adult periodontal disease was made on the result of 2 kinds of periodontal treatment and patient's ubjective evaluation. The optimal path was calculated by using the success rate of the results as the probability and utility according to relative value and the economic value in the insurance system. The success rate to achieve the diagnostic goal of periodontal treatment as the remaining pocket depth less than 3mm and without BOP was $0.83{\pm}0.12$ by non surgical treatment and $0.82{\pm}0.14$ by surgical treatment without any statistically significant difference. The moderate success rate of more than 4mm probing pocket depth were 0.17 together. The utilities of non-surgical treatment results were 100 for a result with less than 3mm probing pocket depth, 80 for the other results with more than 4mm probing pocket depth, 0 for the extraction. Those of surgical treatment results were the same except 75 for the results with more than 4mm. The pooling results of subjective evaluation by using a questionnaire were 60% for satisfaction level and 40% for no satisfaction level in the patient group receiving nonsurgical treatment and 33% and 67% in the other group receiving surgical treatment. The utilities for 4 satisfaction levels were 100, 75, 60, 50 on the base of that the patient would express the satisfaction level with normal distribution. The optimal path of periodontal treatment was rolled back by timing the utility on terminal node and the success rate, the distributed ratio of patient's satisfaction level. Both results of the calculation was non surgical treatment. Therefore, it can be said that non-surgical treatment may be the optimal path for this decision tree of treatment protocol if the goal of the periodontal treatment is to achieve the remaining probing pocket depth of less than 3mm for adult chronic periodontitis and if the utilitarian philosophy to maximise the expected utility for the patients is advocated.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.25 no.2
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• pp.1-19
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• 2012

Objective : The purpose of this study is to investigate about comparison of Eastern-Western medicine on the acne. Methods : We searched Eastern and Western medicine books for acne. We analyzed these books and examined category, definition, etiology, classification, internal and external methods of treatment of acne. Results : The results were as follows. 1. In Eastern medicine, Acne belongs to the category of the Bunja(粉刺), Jwachang(痤瘡), Pyepungbunja(肺風粉刺). In Western medicine, the other name of Acne is acne vulgaris. 2. In Eastern medicine, the definition of Acne includes manual extraction of comedones and skin appearance. In Western medicine, Acne is a common skin disease during adolescence and a chronic inflammatory disease of pilosebaceous unit of self localization. It is characterized by noninflammatory, open or closed comedones and by inflammatory papules, pustules, and nodules and it affects the areas of skin with the densest population of sebaceous follicles, these areas include the face, neck, back, and the upper part of the chest. 3. In Eastern medicine, the cause and mechanism of Acne arose from the state of internal dampness-heat and spleen-stomach internal qi deficiency due to dietary irregularities and then invaded external pathogen such as wind-dampness-heat-cold-fire in lung meridian lead to qi and blood heat depression stagnation. So it appears in skin. In Western medicine, the etiology and pathogenesis of Acne is clearly not identified, but there are most significant pathogenic factors of blood heat depression stagnation. So it appears in skin. In Western medicine, the etiology and pathogenesis of Acne is clearly not identified, but there are most significant pathogenic factors of Acne; Androgen-stimulated production of sebum, hyperkeratinization and obstruction of sebaceous follicles, proliferation of Propionibacterium acnes and inflammation, abnormaility of skin barrier function, genetic aspects, environmental factors etc. 4. In Eastern medicine, differentiation of syndromes classifies clinical aspects, and cause and mechanism of disease; the former is papular, pustular, cystic, nodular, atrophic, comprehensive type; the latter is lung blood heat, intestine-stomach dampness-heat, phlegm-stasis depression, thoroughfare-conception disharmony, heat toxin type. In Western medicine, it divides into an etiology and invasion period, and clinical aspects; Acne neonatorum, Acne infantum, Acne in puberty and adulthood, Acne venenata; Acne vulgaris, Acne conglobata, Acne fulminans, Acne keloidalis. 5. In Eastern medicine, Internal methods of treatment of Acne are divided into five treatments; general treatments, the treatments of single-medicine and experiential description, the treatments depending on the cause and mechanism of disease, and clinical differentiation of syndromes, dietary treatments. In Western medicine, it is a basic principles that regulation on production of sebum, correction on hyperkeratinization of sebaceous follicles, decrease of Propionibacterium acnes colony and control of inflammation reaction. Internal methods of treatment of Acne are antibiotics, retinoids, hormone preparations etc. 6. In Eastern medicine, external methods of treatment of Acne are wet compress method, paste preparation method, powder preparation method, pill preparation method, acupuncture and moxibustion therapy, ear acupuncture therapy, prevention and notice, and so on. In Western medicine, external method of treatments of Acne are divided into topical therapy and other surgical therapies. Topical therapy is used such as antibiotics, sebum regulators, topical vitamin A medicines etc and other surgical therapies are used such as surgical treatments, intralesional injection of corticosteroids, skin dermabrasion, phototherapy, photodynamic therapy, and so on. Conclusions : Until now, there is no perfect, effective single treatment. We think that Eastern medicine approach and treatment can be helpful to overcome the limitations of acne cure.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.