• Journal of the Society of Cosmetic Scientists of Korea
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• v.45 no.2
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• pp.185-198
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• 2019

Human tissue undergoes aging by the oxidant damage via structural change and its physical properties. The skin aging process is well known and many evaluations have been conducted. However, studies on hair aging were relatively few and thus care for aging hair is difficult. This study aims to fabricate an aging hair and identify anti-aging effect with known ingredient in anti-aging. First of all, physical properties of aging hair of age 60s by physiologically intrinsic factors were compared to those of the hair made by various extrinsic factors such as several chemical reactions and iteration numbers of the treatments. The extrinsic aging hair of this study relates to the less amount of lipid and to the hair of perm treated once accordingly, wherein several physical properties, preferably comprise roughness and tensile strength, present a novel concept of the intrinsic aging hair. The penetration of peptide into the aging hair was leading the extrinsic hair towards more structurally directed a younger hair. In addition to the structural change, the penetration of the peptide enhanced texture and tensile strength of the aging hair. These patterns have been also found in addition of propolis. For the first time, these qualitative studies exhibit that indeed our extrinsic aging hair well describes the anti-aging efficacy as a receptor for a cross-linker and the ingredients of human hair.

• Journal of Hospice and Palliative Care
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• v.22 no.3
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• pp.105-116
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• 2019

Purpose: Pediatric palliative care (PPC) is emphasized as standard care for children with life-limiting conditions to improve the quality of life. In Korea, a government-funded pilot program was launched only in July 2018. Given that, this study examined various PPC delivery models in other countries to refine the PPC model in Korea. Methods: Target countries were selected based on the level of PPC provided there: the United Kingdom, the United States, Japan, and Singapore. Relevant literature, websites, and consultations from specialists were analyzed by the integrative review method. Literature search was conducted in PubMed, Google, and Google Scholar, focusing publications since 1990, and on-site visits were conducted to ensure reliability. Analysis was performed on each country's process to develop its PPC scheme, policy, funding model, target population, delivery system, and quality assurance. Results: In the United Kingdom, community-based free-standing facilities work closely with primary care and exchange advice and referrals with specialized PPC consult teams of children's hospitals. In the United States, hospital-based specialized PPC consult teams set up networks with hospice agencies and home healthcare agencies and provide PPC by designating care coordinators. In Japan, palliative care is provided through several services such as palliative care for cancer patients, home care for technology-dependent patients, other support services for children with disabilities and/or chronic conditions. In Singapore, a home-based PPC association plays a pivotal role in providing PPC by taking advantage of geographic accessibility and cooperating with tertiary hospitals. Conclusion: It is warranted to identify unmet needs and establish an appropriate PPD model to provide need-based individualized care and optimize PPC in South Korea.

• Clean Technology
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• v.25 no.2
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• pp.129-139
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• 2019

Bamboo is an evergreen perennial plant, and it is known as one of the most productive and fastest-growing plants in the world. It grows quickly in moderate climates with only moderate water and fertilizer. Traditionally in Asia, bamboo is used for building materials, as a food source, and as versatile raw materials. Bamboo as a biomass feedstock can be transformed to prepare activated carbon using the thermal treatment of pyrolysis. The effect of process variables such as carbonization temperature, activation temperature, activation time, the amount of steam, and the mixing ratio of phosphoric acid and bamboo were systematically investigated to optimize the preparation conditions. Steam activation was proceeded after carbonization with a vapor flow rate of $0.8{\sim}1.8mL-H_2O\;g-char^{-1}\;h^{-1}$ and activation time of 1 ~ 3 h at $700{\sim}900^{\circ}C$. Carbon yield and surface area reached 2.04 ~ 20.59 wt% and $499.17{\sim}1074.04m^2\;g^{-1}$, respectively, with a steam flow rate of $1.4mL-H_2O\;g-char^{-1}\;h^{-1}$ for 2 h. Also, the carbon yield and surface area were 24.67 wt% and $1389.59m^2\;g^{-1}$, respectively, when the bamboo and phosphoric acid were mixed in a 1:1 weight ratio ($700^{\circ}C$, 2 h, $1.4mL-H_2O\;g-char^{-1}\;h^{-1}$). The adsorption of methylene blue into the bamboo activated carbon was studied based on pseudo first order and second order kinetics models. The adsorption kinetics were found to follow the pseudo second order model, which is governed by chemisorption.

• Journal of Mushroom
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• v.17 no.3
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• pp.119-125
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• 2019

This study aims to report the results for the analysis of the growth environment by applying smart farm technology to "Chunchu No 2" farmers in order to develop an optimal growth model for precision cultivation of bottle-grown oyster mushrooms. The temperature, humidity, carbon dioxide concentration, and illumination data were collected and analyzed using an environmental sensor installed to obtain growth environment data from the oyster mushroom cultivator. Analysis of the collected temperature data revealed that the temperature at the time of granulation was $19.5^{\circ}C$ after scraping, and the mushroom was generated and maintained at about $21^{\circ}C$ until the bottle was flipped. When the fruiting body grew and approached harvest time, mushrooms were harvested while maintaining the temperature between $14^{\circ}C$ and $18^{\circ}C$. The humidity was maintained at almost 100% during the complete growth stage. Carbon dioxide concentration gradually increased until 3 days after the beginning of cultivation, and then increased rapidly to almost 5,500 ppm. From the 6th day, carbon dioxide concentration was gradually decreased through ventilation and was maintained at 1,600 ppm during harvest. Light intensity of 8 lux was irradiated up to day 6 after seeding, and growth was then continued while periodically irradiating 4 lux light. The fruiting body characteristics of "Chunchu No 2" cultivated in the farmhouse were as follows: pileus diameter of 26.5 mm and thickness of 4.9 mm, stipe thickness of 8.9 mm, and length of 68.7 mm. The fruiting body yield was 166.8 g/850 ml, and the individual weight was 12.8 g/10 units.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.3
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• pp.39-48
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• 2019

This research is based on the analysis of in-depth interviews of designers who participated in the design of the Yeonnam-dong section, which was completed in 2016. The case study site has received many domestic and foreign awards and is receiving very positive reviews from actual users. 53 concepts were derived from the open coding of the ground theory methodology. Thirty-four higher categories incorporated the concepts and 18 higher categories that reintegrated them. Later, the six categories of the ground theory were interpreted as the paradigm, and it was determined that the aspects of 'will of client' and 'work efficiency', 'site resources' and 'field manager's specialty' were the categories that had the greatest positive impact on the park construction. The key category of this park's construction was interpreted as "a park-construction model with active empathy and communication." The results of the study and are linked to the following research proposals. First, the need to improve the trust between the client and the landscape designer and the need to improve the customary administrative procedures; second, the importance of the input of landscape experts into the park construction process; third, the importance of all efforts to develop the design; fourth, the importance of on-site circular resources and landscape preservation; and fifth active social participation to increase the opportunity. This study, which seeks to grasp the facts that existed behind the park's construction, which received excellent internal and external evaluations, and has a qualitative, objective and structural interpretation of the social network related to the park's construction, in contrast to the conventional quantitative post-evaluation. It is expected that the administration and system improvements related to landscaping will be further improved through the continuation of in-depth post-evaluation studies.

• The Korean Journal of Archival Studies
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• no.33
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• pp.85-112
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• 2012

Group for the People without History(GPH) was launched at September 2002 and had worked for around five years with the following purposes; Firstly, GPH collects first-hand data on people's everyday lives based on fieldworks. Secondly, GPH constructs digital archives of the collected data. Thirdly, GPH guarantees the accessibility to the archives for people. And lastly, GPH promotes users to utilize the archived data for the various levels. GPH has influenced on the construction of archives on everyday life history as well as the research areas such as anthropology and social history. What is important is that GPH tried to construct digital archives even before the awareness on archives was not widely spreaded in Korea other than formal sectors. Furthermore, the GPH archives proposed a model of open archives which encouraged the people's participation in and utilization of the archives. GPH also showed the ways in which archived data were used. It had published forty seven books of people's life histories and five photographic books, and held six photographic exhibitions on the basis of the archived data. Though GPH archives had contributed to the ignition of the discussions on archives in various areas as leading civilian archives, it has a few limitations. The most important problem is that the data are vanishing too fast for researchers to collect. It is impossible for researchers to collect the whole data. Secondly, the physical space and hardware for the data storage should be ensured. One of the alternatives to solve the problems revealed in the works of GPH is to construct community archives. Community archives are decentralized archives run by people themselves to preserve their own voices and history. It will guarantee the democratization of archives.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• 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.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.4
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• pp.67-83
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• 2022

Biochar is a carbon material produced through the pyrolysis of agricultural biomass with limited oxygen condition. It has been suggested to enhance the carbon sequestration and mineralization of soil carbon. Objective of this study was to investigate soil potential carbon mineralization and carbon dioxide(CO₂) emissions in different soils cooperated with barely straw and livestock manure biochars in the closed chamber. The incubation was conducted during 49 days using a closed chamber. The treatments consisted of 2 different biochars that were originated from barley straw and livestock manure, and application amounts were 0, 5, 10 and 20 ton ha^-1 with different soils as upland, protected cultivation, converted and reclaimed. The results indicated that the TC increased significantly in all soils after biochar application. Mineralization of soil carbon was well fitted for Kinetic first-order exponential rate model equation (P<0.001). Potential mineralization rate ranged from 8.7 to 15.5% and 8.2 to 16.5% in the barely straw biochar and livestock manure biochar treatments, respectively. The highest CO₂ emission was 81.94 mg kg^-1 in the upland soil, and it was more emitted CO₂ for barely straw biochar application than its livestock biochar regardless of their application rates. Soil amendment of biochar is suitable for barely straw biochar regardless of application rates for mitigation of CO₂ emission in the cropland.