• The Korean Journal of Archival Studies
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• no.30
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• pp.175-204
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• 2011

Electronic records are generated not only in public sector but also in private sector. Records will be used across the public-private boundary. The Certified e-Document Authorities(CeDAs) may keep electronic documents in private sector for preservation and evidence, like the official Record Management Systems for Public sector. A CeDA is the Trusted Third Party (TTP) as a business to be entrusted and proof interchanging documents between parties. This CeDA system could be sustainable only if the CeDA earn the enough sales through enough uses. And yet, all the eight CeDA companies have not had enough users. How to utilize CeDAs is one of the hot issues in this area. In this paper, We analyze the threat to trustworthiness of CeDA due to payment of only one party among others, and describe the difficulty in use of CeDA for an individual user. These things make CeDAs cannot have enough users. To do address these, We expand the boundary of relevant parties for a document, present a delegate-establishing option under a joint name, show the needs of identifying and notifying minimum relevant parties, and suggest the proxy parties to help the individual users.

• 한국사회정책
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• v.23 no.2
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• pp.113-139
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• 2016

This article tries to compare exchange relations between welfare and dictatorship in the East Germany and the North Korea. Unlike capitalist welfare aiming at correcting market results socialist welfare has been proposed to satisfy people's basic needs, but it had operated as instrument of dictatorship. Relation between welfare and dictatorship could be distinguished as hard exchange and soft one in line with social construction of welfare. Welfare-dictatorship relation in East Germany had developed from its formation(1949-1970s), crisis(1980s) and dissolution(1989-1990). There had established hard exchange relation in which the legitimacy of dominance had debted to welfare as social rights. While crisis of the exchange relation had been modest in a form of insufficient supply of consumption goods, it was one of the elements of collapse of dictatorship, leading to the unification with West Germany. The journey of the exchange relation in North Korea can be characterized by its formation(1948-1980), crisis(1990s-2000s), and transformation(2010s). Unlike East Germany, welfare was socially constructed as gift form the ruler to the ruled, which made the combination of welfare and dictatorship loosely coupled. Although economic crisis was severe compared to East German one the rulers have succeeded maintaining dictatorial dominance by creating dual exchange relation. They separated core group and subordinated one supporting the former at the expense of the latter. They blocked out most of the people from soft exchange relation making bad use of muddling-through life style dependent on market activities. This strategy led to a 'dictatorship neutral welfare extinction'. Taking the high degree of institutionalization of newly establishing welfare-dictatorship relation into account, lives of most people are hardly expected to be improved by gift by their rulers even if North Korean economy will recover in the future.

• Journal of Korean Society of Disaster and Security
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• v.15 no.2
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• pp.13-25
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• 2022

Public consent is essential to proceed with large-scale projects such as dam and hydroelectric power plant in the Carbon Neutral Era. In general, when designing facilities such as dams and river facilities, the impact due to constructing them is analyzed through numerical simulation in advance. Those facilities are built to cope with floods and usually HEC-RAS is used for numerical simulation in this process. The numerical simulation provides accurate data, but it is very difficult to persuade the public only with the data. Therefore, this study intends to consider the utilization of metaverse in the field of urban flooding and flood response. The applicability of metaverse was confirmed by emphasizing visual effects and providing easy-to-see data, using a kind of metaverse platform called Cities: Skylines. The functions and limitations of this platform were reviewed. A virtual flood scenario was applied after implementing real cities on a metaverse. The hazard map established in Korea and the results of applying the scenario of metaverse platform were compared. On the metaverse, not only the disaster situation caused by realizing the city and society as it is, but also the spread of social disasters after the disaster can be confirmed. Through this, countermeasures can be virtually implemented. If these social and humanistic data are also verified in the future, it is expected that the overall process for responding to urban flooding can be modeled.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.53-60
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• 2022

YouTube realistically shows fake news and biased content based on facts that have not been verified due to low entry barriers and ambiguity in video regulation standards. Therefore, this study aims to analyze the influence of the media and YouTube on individual behavior and their relationship. Data from YouTube and Twitter are randomly imported with selenium, beautiful soup, and Twitter APIs to classify the 31 most frequently mentioned keywords. Based on 31 keywords classified, data were collected from YouTube, Twitter, and Naver News, and positive, negative, and neutral emotions were classified and quantified with NLTK's Natural Language Toolkit (NLTK) Vader model and used as analysis data. As a result of analyzing the correlation of data, it was confirmed that the higher the negative value of news, the more positive content on YouTube, and the positive index of YouTube content is proportional to the positive and negative values on Twitter. As a result of this study, YouTube is not consistent with the emotion index shown in the news due to its secondary processing and affected characteristics. In other words, processed YouTube content intuitively affects Twitter's positive and negative figures, which are channels of communication. The results of this study analyzed that YouTube plays a role in assisting individual discrimination in the current situation where accurate judgment of information has become difficult due to the emergence of yellow media that stimulates people's interests and instincts.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.1
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• pp.1-8
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• 2022

With the spread of COVID-19 worldwide, non-face-to-face services have grown rapidly, but at the same time, the problem of plastic waste is getting worse. Accordingly, eco-friendly policies such as carbon neutrality and sustainable circular economy are being promoted worldwide. Due to the high demand for eco-friendly products, the packaging industry is trying to develop eco-friendly packaging materials using PLA and PBAT and create new business models. On the other hand, Ulva australis occurs in large quantities in the southern seas of Korea and off the coast of Jeju Island, causing marine environmental problems. In this study, lactic acid was produced through dilute acid pretreatment, enzymatic saccharification, and fermentation processes to utilize Ulva australis as a new alternative energy raw material. In general, seaweeds vary in carbohydrate content and sugar composition depending on the species, harvest location, and time. Seaweed is mainly composed of polysaccharides such as cellulose, alginate, mannan, and xylan, but does not contain lignin. It is difficult to expect high extraction yield of the complex polysaccharide constituting Ulva australis with only one process. However, the fusion process of dilute acid and enzymatic saccharification presented in this study can extract most of the sugars contained in Ulva australis. Therefore, the fusion process is considered to be able to expect high lactic acid production yield when a commercial-scale production process is established.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of the Korean earth science society
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• v.42 no.5
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• pp.536-555
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• 2021

Sea-surface wind is an important variable in ocean-atmosphere interactions, leading to the changes in ocean surface currents and circulation, mixed layers, and heat flux. With the development of satellite technology, sea-surface winds data retrieved from scatterometer observation data have been used for various purposes. In a complex marine environment such as the Korean Peninsula coast, scatterometer-observed sea-surface wind is an important factor for analyzing ocean and atmospheric phenomena. Therefore, the validation results of wind accuracy can be used for diverse applications. In this study, the sea-surface winds derived from ASCAT (Advanced SCATterometer) mounted on MetOp-A/B (METeorological Operational Satellite-A/B) were validated compared to in-situ wind measurements at 16 marine buoy stations around the Korean Peninsula from January to December 2020. The buoy winds measured at a height of 4-5 m from the sea surface were converted to 10-m neutral winds using the LKB (Liu-Katsaros-Businger) model. The matchup procedure produced 5,544 and 10,051 collocation points for MetOp-A and MetOp-B, respectively. The root mean square errors (RMSE) were 1.36 and 1.28 m s^-1, and bias errors amounted to 0.44 and 0.65 m s^-1 for MetOp-A and MetOp-B, respectively. The wind directions of both scatterometers exhibited negative biases of -8.03° and -6.97° and RMSE values of 32.46° and 36.06° for MetOp-A and MetOp-B, respectively. These errors were likely associated with the stratification and dynamics of the marine-atmospheric boundary layer. In the seas around the Korean Peninsula, the sea-surface winds of the ASCAT tended to be more overestimated than the in-situ wind speeds, particularly at weak wind speeds. In addition, the closer the distance from the coast, the more the amplification of error. The present results could contribute to the development of a prediction model as improved input data and the understanding of air-sea interaction and impact of typhoons in the coastal regions around the Korean Peninsula.

• Korean Journal of Hospice Care
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• v.8 no.1
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• pp.13-28
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• 2008

Purpose: This paper aims to examine the subjective structures and types of school age children's perception of death through an investigative study on their perception of death in order to provide a basic material for them to understand death, and develop and carry out an effective death education program. Methods: The study method used the Q Methodology which can investigate the subjective structures and types of school age children's perception of death. For Q-population, 20 school age children were used as subjects for neutral interviews and open surveys, and through documentary research, a total of 132 statements were collected, For Q-samples, 23 statements (Q-samples) were derived through a non-structural method. P-samples were 31 school age children (8-13 year olds), Q-sorting was carried out using Q-cards, and the collected data was analyzed using the PC QUANL program. Results: As a result of the study, children's perception of death was divided into five types. The first type was functional type, characterized by prominent subjective perception regarding the elements of death, such as non-reversibility, universality, non-functionality, and causality. The second was after-life type, characterized by a strong, focus on life after death in one's perception of death, and it included children with Christian background and those who had experienced death in their immediate family. The third was religious type, characterized by a strong belief in being able to still watch over one's family and friends after one's death, resulting in a positive faith in the after-life. The fourth was fearful type, characterized by a deeper fear of death in comparison to other types. The fifth was realistic type, characterized by a strong and positive assent to the perception of good death. Conclusion: The significance of the results of this paper's study to Nursing is as follows. In terms of understanding the subjectivity of school age children's perception of death in nursing practice, and understanding the compositional elements of death presented with strong emphasis in existing literature and studies, the results will expand these understandings and allow us to understand the level of perception in school age children regarding the definition of death, after-life, and good death, be utilized as useful material in developing an effective death education program for them according to their type characteristics, and become the fertilizer for enabling the children to live a proper life and preventing the tendency to make light of death that occur in adolescence and the spread of suicides. In terms of nursing theory, the description and examination of the subjective structures and the characteristics of the different, types of school age children's perception of death can be utilized as useful material for building a model of school age children's perception of death, and be further used for teaching respect for life. In terms of nursing research, the results can contribute to research describing the effects of nursing intervention strategies and developing tools for providing psychosocial nursing in terms of giving school age children a positive perception of death according to their types as well respect for life.

• Clean Technology
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• v.28 no.3
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• pp.218-226
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• 2022

As a result of the recent social transformation towards a hydrogen economy and carbon-neutrality, the demands for hydrogen energy have been increasing rapidly worldwide. As such, eco-friendly hydrogen production technologies that do not produce carbon dioxide (CO₂) emissions are being focused on. Among them, ammonia (NH₃) is an economical hydrogen carrier that can easily produce hydrogen (H₂). In this study, Ru/Al₂O₃ catalyst coated onmetallic monolith for hydrogen production from ammonia was prepared by a dip-coating method using a catalyst slurry mixture composed of Ru/Al₂O₃ catalyst, inorganic binder (alumina sol) and organic binder (methyl cellulose). At the optimized 1:1:0.1 weight ratio of catalyst/inorganic binder/organic binder, the amount of catalyst coated on the metallic monolith after one cycle coating was about 61.6 g L^-1. The uniform thickness (about 42 ㎛) and crystal structure of the catalyst coated on the metallic monolith surface were confirmed through scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. Also, a numerical optimization regression equation for NH3 conversion according to the independent variables of reaction temperature (400-600 ℃) and gas hourly space velocity (1,000-5,000 h^-1) was calculated by response surface methodology (RSM). This model indicated a determination coefficient (R²) of 0.991 and had statistically significant predictors. This regression model could contribute to the commercial process design of hydrogen production by ammonia decomposition.