• 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.

• Food Science and Industry
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• v.53 no.1
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• pp.2-32
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• 2020

In recent years, significant importance has been given to chitooligosaccharides (COS) due to its potent notable biological applications. COS can be derived from chitosan which is commonly produced by partially hydrolyzed products from crustacean shells. In order to produce COS, there are several approaches including chemical and enzymatic methods which are the two most common choices. In this regard, several new methods were intended to be promoted which use the enzymatic hydrolysis with a lower cost and desired properties. Hence, the dual reactor system has gained more attention than other newly developed technologies. Enzymatic hydrolysis derived COS possesses important biological activities such as anticancer, antioxidant, anti-hypersentive, anti-dementia (Altzheimer's disease), anti-diabeties, anti-allergy, anti-inflammatory, etc. Results strongly suggest that properties of COS can be potential materials for nutraceutical, pharmaceutical, and cosmeceutical product development.

• The Southeast Asian review
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• v.27 no.2
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• pp.245-271
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• 2017

The purpose of this study is to examine and assess the major characteristics and changes of politics, economy, and diplomacy in Thailand in 2016. Specifically, it reviewed the New Constitution that was passed in 2016, the confrontation between different political forces and the trend of military regime around the New Constitution, and the political instability caused by the accession of the new king to the throne. This study also set out to figure out changes to the economy and foreign relations of the country, including its relations with South Korea, under the military regime and make predictions for the impact and future prospects of King Bhumibol Adulyadej's death on the politics and economy of the country. In 2016, the politics of Thailand took a step further toward the transfer of power to civil government and established a foundation for an authoritarian system. The draft of the New Constitution, which does not seem to be democratic, was approved by a referendum and enabled the military authorities to continue their political interventions, even after the general election. The New Constitution, in particular, reduces the power of political parties itself in addition to simply keeping the Thaksin's party in check; thus, anticipating ongoing conflicts between the military authorities and political parties. In this situation, the absence of King Bhumibol Adulyadej, who used to play a decisive role in promoting the political stability of the country, and the accession of the new king to the throne raise concerns about the acceleration of political instability, which has continued after the coup and influenced the diplomatic relations of the country. Today, Thailand is distancing itself from Western nations that do not recognize the current military regime including the U.S.A. and EU member states and instead maintains a rapidly friendly and close relation with China. In 2016, the economy of Thailand made a gradual recovery rather than high growth. The death of King Bhumibol Adulyadej has exerted limited direct economic impacts only on individual consumption and tourism and is not likely to cause a recession. An economic crisis will, however, be unavoidable if the political confrontations escalate before the general election to transfer power to the civil government.

• The Southeast Asian review
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• v.27 no.4
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• pp.1-40
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• 2017

This study aims to examine the electricity/energy regime of Thailand, the largest energy-hungry country in the Mekong region. This study examined how the electricity/energy regime of Thailand has been shaped and changed up to the present, not only at the national level but also at the sub-regional level covering the Mekong region. Meanwhile, according to the Paris Agreement in 2015, which will get in to effect from 2020, developing countries as well as developed countries have been given voluntary responsibilities and reduction obligations in response to global climate change. Under the post 2020 Climate Change Regime, Thailand also needs to revise its existing electricity/energy policy. We reviewed the recent energy policy of Thailand and evaluated the possibility of transition to a sustainable energy system based on Energy Trilemma's analysis framework. And we examined the roles and impacts of the Thai civil society on the national power and energy planning as well as in the future climate change policy. As a result of the analysis, it can be seen that Thailand's electricity/energy regime has grown rapidly through the support of the West countries under the Cold War era. In particular, Electricity Generating Authority of Thailand(EGAT) played the key role in Thailand's energy policy. In addition, Thailand's geopolitical location and relatively high economic level compared to neighboring countries will continue to be of importance in the future construction of power grids in the region. Meanwhile, in the frame of Energy Trilemma, Thailand has still been vulnerable to environmental sustainability. Thai NGOs have resisted to as well as collaborated with the government to influence the existing electricity/energy policy in the various dimensions but their influence has weakened considerably since the coup in 2014. In conclusion, this study suggests to cooperate with government as well as civil society for sustainable energy transformation of Thailand and Mekong region.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.3
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• pp.220-237
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• 2021

Since the functional importance of marine phytoplankton was firstly advocated from early 1880s massive data on the species composition and abundance were produced by classical microscopic observation and the advanced auto-imaging technologies. Recently, pigment composition resulted from direct chemical analysis of phytoplankton samples or indirect remote sensing could be used for the group-specific quantification, which leads us to more diversified data production methods and for more improved spatiotemporal accessibilities to the target data-gathering points. In quite a few cases of many long-term marine ecosystem monitoring programs the phytoplankton species composition and abundance was included as a basic monitoring item. The phytoplankton data could be utilized as a crucial evidence for the long-term change in phytoplankton community structure and ecological functioning at the monitoring stations. Usability of the phytoplankton data sometimes is restricted by the differences in data producers throughout the whole monitoring period. Methods for sample treatments, analyses, and species identification of the phytoplankton species could be inconsistent among the different data producers and the monitoring years. In-depth study to determine the precise quantitative values of the phytoplankton species composition and abundance might be begun by Victor Hensen in late 1880s. International discussion on the quality assurance of the marine phytoplankton data began in 1969 by the SCOR Working Group 33 of ICSU. Final report of the Working group in 1974 (UNESCO Technical Papers in Marine Science 18) was later revised and published as the UNESCO Monographs on oceanographic methodology 6. The BEQUALM project, the former body of IPI (International Phytoplankton Intercomparison) for marine phytoplankton data QA/QC under ISO standard, was initiated in late 1990. The IPI is promoting international collaboration for all the participating countries to apply the QA/QC standard established from the 20 years long experience and practices. In Korea, however, such a QA/QC standard for marine phytoplankton species composition and abundance data is not well established by law, whereas that for marine chemical data from measurements and analysis has been already set up and managed. The first priority might be to establish a QA/QC standard system for species composition and abundance data of marine phytoplankton, then to be extended to other functional groups at the higher consumer level of marine food webs.

• The Journal of Korean Academy of Sensory Integration
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• v.19 no.1
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• pp.69-82
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• 2021

Objective : This recent work intended to provide basic information for researchers and practitioners related to occupational therapy about Developmental Coordination Disorder (DCD) in South Korea. The previous research of screening DCD and the effects of intervention programs were reviewed. Methods : Peer-reviewed papers relating to DCD and published in Korea from January 1990 to December 2020 were systematically reviewed. The search terms "developmental coordination disorder," "development coordination," and "developmental coordination" were used to identify previous Korean research in this area from three representation database, the Research Information Sharing Service, Korean Studies Information Service System, and Google Scholar. We found a total of 4,878 articles identified through the three search engines and selected seventeen articles for analysis after removing those that corresponded to the overlapping or exclusion criteria. We adopted "the conceptual model" to analyze the selected articles about DCD assessment and intervention. Results : We found that twelve of the 17 studies showed the qualitative level of Level 2 using non-randomized approach between the two groups. The Movement Assessment Battery for Children and its second edition were the most frequently used tools in assessing children for DCD. Among the intervention studies, the eight articles (47%) were adopted a dynamic systems approach; a normative functional skill framework and cognitive neuroscience were each used in 18% of the pieces; and 11% of the articles were applied neurodevelopmental theory. Only one article was used a combination approach of normative functional skill and general abilities. These papers were mainly focused on the movement characteristics of children with DCD and the intervention effect of exercise or sports programs. Conclusion : Most of the reviewed studies investigated the movement characteristics of DCD or explore the effectiveness of particular intervention programs. In the future, it would be useful to investigate the feasibility of different assessment tools and to establish the effectiveness of various interventions used in rehabilitation for better motor performance in children with DCD.

• Journal of the Daesoon Academy of Sciences
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• v.39
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• pp.137-174
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• 2021

The main theme of this paper centers on how to promote Three Major Works of Daesoon Jinrihoe, charity aid, social welfare, and education projects, during the unification period. Determining the best methods of promotion is crucial because the Three Major Works must be carried out after unification, and the works must remain based on the practice of the philosophy of Haewon-sangsaeng (the Resolution of Grievances for Mutual Beneficence). The idea of Haewon-sangsaeng is in line with the preface of the U.N. Charter and the aim of world peace. North Korean residents are suffering from starvation under their devastated economy, which is certain to face a crisis of materialistic deficiency during reunification. In this study, the peaceful unification of Germany, unification under a period of sudden changes in Yemen, and the militarized unification of Vietnam were taken as case studies to diagnose and analyze the conditions which would affect the implementation of the Three Major Works. These three styles of unification commonly required a considerable budget and other forms of support to carry out the Three Major Works. Especially if unification were to occur after a period of sudden changes, this would require solutions to issues of food, shelter, and medical support due to the loss of numerous lives and the destruction of infrastructure. On the other hand, the UNHCR model was analyzed to determine the implications of expanding mental well prepared and sufficiently qualified professionals, reorganizing standard organizations within complex situations, task direction, preparing sufficient relief goods, budgeting, securing bases in border areas with North Korea, and establishing networks for sponsorship. Based on this, eight detailed tasks in the field of system construction could be used by the operators of the Three Major Works to prepare for unification. Additionally, nine tasks for review were presented in consideration of the timing of unification and the current situation between South and North Korea. In conclusion, in the event of unification, the Three Major Works should not be neglected during the transition period. The manual "Three Major Works during the Unification Period" should include strategic points on organizational formation and mission implementation, forward base and base operation, security and logistics preparation, public relations and external cooperation, safety measures, and transportation and contact systems.

• Journal of Ginseng Culture
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• v.4
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• pp.38-58
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• 2022

Park Wan-seo's novels deal with realistic topics of society, such as women's issues, the capitalist system, and the problems that come with old age. Assuch, her work is used as a tool to analyze social phenomena in various fields, such as women's studies, sociology, and literature. A characteristic style of Park Wan-seo's novels is that she bases them on her own experiences. However, among her novels, the novel Mimang is exceptional. The plot is based on stories that have been passed down from generation to generation. This is to show the spirit of the times through the unforgettable story of her hometown, Gaesong. Mimang is the story of a family chronology that spans four generations centered on Chun Cheu-Man and his family, who became powerful capitalists through the cultivation and commerce of ginseng cultivation. Set in the late 19th century until the end of the Korean War, the novel unravels the essence of the times symbolized by merchants of ginseng and Gaeseong, focusing on the actions of people living in a period of historical turbulence. Gaeseong is the mecca of Korean ginseng, and Gaeseong cannot be portrayed without the story of ginseng and its merchants. Therefore, Mimang, a fictionalized story based on real facts, contains valuable testimony of the history of ginseng, not only as historical values of modern history and personal customs but also as microhistory. In the novel, traces of the times of Gaeseong and the spirit of ginseng merchants, as shown in the Japanese sacking of ginseng during the colonial period, the resistance of ginseng merchants, and the conversion of ginseng capitalism to modern capitalism, are imprinted like fossils. What is especially meaningful is that the stories in the novel correspond to historical facts and constitute a chapter in the history of ginseng. The symbolism of ginseng in the novel can be explained in three main ways. First, it shows the essence of Korean ginseng. It reveals the soul of ginseng through the sincerity and rigor of ginseng farming, as well as the spirit and pride of ginseng. Second, it symbolizes the exploitation of ginseng in Japan as a national issue. The efforts of ginseng merchants to protect this and support the independence movement are presented as important themes to express nationalism. Third, it shows the modern capitalist progressiveness of Gaeseong ginseng merchants, who do not stay in landownership and commercial capital, but convert them to productive capital and contribute to society by modernizing them. The three symbolisms show the spirit of the times of the Gaeseong ginseng merchants, clearly revealing the meaningful relationship between the Korean people and ginseng.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.