The currently existing "Bonchojeonghwa (本草精華)" is a manuscript without the preface and the epilogue, composed of 2 books in 2 volumes. This book is a quintessence of knowledge on science of medicinal ingredients (medicinal phytology I herbal science) as well as an trial of new development in Chosun medical science. I.e. this book includes surprising change representing medical science in Chosun dynasty as a single publication on science of medicinal ingredients. It holds a value essential to clinician as a specialized book in medicinal ingredients, and Includes richer content on medicinal ingredients than any other books published before. In addition, it is away from boring list-up of superfluous knowledge as seen in "Bonchokangmok(本草綱目)" published in China, and well summarizes essential knowledge which can be used within a range of medicines available in Korea. This book has an outstanding structure that can be even used in today's textbook on science of medicinal ingredients, as it has clear theory, system and classification. Because it handles essential learning points prior to prescription to disease, it is possible to configure new prescription and adjustment of medicinal materials. Moreover, this book can play a good role for linguistic study at the time of publication, because it describes many drugs in Hangul in many parts of the book. "Bonchojeonghwa" includes a variety of animals, plants and mineral resources in Korea, like "Bonchokangmok" which was recently listed in UNESCO. As such, it has a significance in natural history as well as pharmacy in Korean Medicine. It has various academic relationships all in biologic & abiologic aspects. It has importance in sharing future biological resources, building up international potential, setting up the standard for biologic species under IMF system, and becoming a base for resource diplomacy. We should not only see it as a book on medicinal ingredients in terms of Oriental Medicine, but also make an prudent approach to it in terms of study strengthening Korea's national competitiveness. After bibliographical reviewing on the features & characteristics of the only existing copy of "Bonchojeonghwa" housed in Kyujanggak(奎章閣) of Seoul National University, the followings are noted. First, "Bonchojeonghwa" is a specialized book on medicinal ingredients voluntarily made by private hands to distribute knowledge on drugs in the desolate situation after Imjinoeran (Japanese Invasion in 1592), without waiting for governmental help. Second, it raised accessibility and practicality by new editing. Third, it classified 990 different kinds of drugs into plant, animal, and mineral at large, and dassified more in detail into 15 'Bu' and 48 'Ryu' at 258 pages. Fourth, the publication of this book is estimated to be around 1625~1633, at the time of Injo's reign in 17th century. Fifth, it contains the existing & up-to-date knowledge at the time of publication, and it is possible to see the supply-demand situation by Hangul descriptions in 149 places in the book. By the fact that there are many linguistic evidences of 17th century, explains well when the book was published.
The purpose of this study was to examine the effects of tasks setting for mathematical modelling in the complex real situations. The tasks setting(MMa, MeA) in mathematical modelling was so important that we can't ignore its effects to develop meaning and integrate mathematical ideas. The experimental setting were two groups ($N_1=103$, $N_2=103$) at public high school and non-experimental setting was one group($N_3=103$). In mathematical achievement, we found meaningful improvement for MeA group on modelling tasks, but no meaningful effect on information processing tasks. The statistical method used was ACONOVA analysis. Beside their achievement, we were much concerned about their modelling approach that TSG21 had suggested in Category "Educational & cognitive Midelling". Subjects who involved in experimental works showed very interesting approach as Exploration, analysis in some situation ${\Rightarrow}$ Math. questions ${\Rightarrow}$ Setting models ${\Rightarrow}$ Problem solution ${\Rightarrow}$ Extension, generalization, but MeA group spent a lot of time on step: Exploration, analysis and MMa group on step, Setting models. Both groups integrated actively many heuristics that schoenfeld defined. Specially, Drawing and Modified Simple Strategy were the most powerful on approach step 1,2,3. It was very encouraging that those experimental setting was improved positively more than the non-experimental setting on mathematical belief and interest. In our school system, teaching math. modelling could be a answer about what kind of educational action or environment we should provide for them. That is, mathematical learning.
Recently, the lesson plan document that is imported in the educational area is not provided to the educational information systematically, and the teachers are not easy to compose the lessen plan documentation. So, it needs additional time and effort to develope the lesson plan documents. Because of increasing the distributing network. web-based lesson plan system is required to all of the education area. Therefore, we need to compose the lesson plan that is possible to obtain the various teacher's requirement by providing creation, retrival, and reusability of document using the standard XML on web. In this paper, we developed the system for creating the common DTD (Document Type Definition), providing the standard XML document through the common DTD over the lesson plan analysis. In this system, it provides the editor to compose the lesson plan and supports the searching function to improvement of reusability on the existing lesson plan. We design the searching functions such as the structure base, facet and keyword. The composed lesson plans are interoperated with Database. Consequently, we can share the information on web by composing the lesson plan using the XML and save the time and cost by directly writing the lesson plan on web. We can also provide the improved learning environment.
Journal of the Korean BIBLIA Society for library and Information Science
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v.31
no.2
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pp.203-221
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2020
This study closely analyzed changes in the educational environment and changes in the needs of children's and young people's reading culture programs, which are directly beneficiaries of the promotion of reading culture as they enter the fourth industrial revolution. It also comprehensively evaluated the reading culture promotion project for children and adolescents promoted by the National Children and Youth Library and proposed a reading culture promotion project that meets the needs of the smart era. This study investigated the cases of various domestic and foreign reading culture promotion projects to divulge trends. The authors invited experts from public libraries and school libraries with experience of the reading culture promotion projects and performed Focus Group Interviews (FGI). The authors evaluated individual reading culture program based on the PDCA method (Plan, Do, Check, Act). Based on the data obtained through case studies and expert evaluations, the development plan of reading culture promotion project and the strategy of promoting new projects to be pursued in the National Children and Youth Library were presented. By gathering the results of the research, 'Interactive e-book making platform production / distribution business', 'Game-type reading program production / distribution business', 'Habruta reading culture dissemination project using backward learning method', 'Youth coding branding "Teen-Start -Up"' were proposed as new services.
Mathematically gifted students' emotional changes during Mathematical Olympiad training camp were studied. The emotions of the gifted during the camp were fluctuated significantly by comparing their test scores with other camp attendants, while the morale was high at the beginning. The camp attendants were likely to overcome disappointment resulting from bad scores with putting more efforts on studying, which means their self-assessments for their mathematical talents are not affected by test results. From what characterizes the emotional changes of the gifted, we conclude as follows: First, they tend to be positive on grouping classes depending on the mathematical ability. Second, careful emotional supports and care were needed in ability grouping education. Third, it is important to let the gifted have more chances to communicate with other camp attendants. It is recommended to induce the gifted to put their focus on the learning goal. Fifth, the proper environment helps the gifted be indulged in studying mathematics.
Journal of the Korea Institute of Information Security & Cryptology
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v.21
no.6
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pp.183-190
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2011
In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.
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 Korean Home Economics Education Association
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v.35
no.3
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pp.169-190
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2023
Uzbekistan, one of the top five cotton-producing countries in the world, primarily focuses its textile and fashion industry on raw cotton exports and the sewing industry. For Uzbekistan to achieve high added value, it is essential for the textile and fashion industry, which is currently at the CMT(cut, make, and trim) stage, to upgrade to OEM (original equipment manufacturing), ODM (original design manufacturing), and OBM (original brand manufacturing). South Korea recognizes Uzbekistan as a potential manufacturing base and trading partner and has invested Official Development Assistance (ODA) funds for the development of Uzbekistan's textiles and apparel sector. This study aims to evaluate Uzbekistan's fashion higher education in the context of global competitiveness and measure the need and prospects for education ODA from the Korean government in this field. Comprehensive investigations, including surveys of academics, industry experts, and government officials, in-depth interviews, and focus group interviews, were conducted to understand Uzbekistan's current fashion education environment. According to the research results, despite the textile and fashion sectors playing a pivotal role in the Uzbek economy, there is room for improvement in the curricula and teaching and learning methods of the fashion higher education programs. This study holds significance as foundational data for establishing education ODA strategies.
Korean Journal of Agricultural and Forest Meteorology
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v.12
no.4
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pp.241-263
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2010
KoFlux is a Korean network of micrometeorological tower sites that use eddy covariance methods to monitor the cycles of energy, water, and carbon dioxide between the atmosphere and the key terrestrial ecosystems in Korea. KoFlux embraces the mission of AsiaFlux, i.e. to bring Asia's key ecosystems under observation to ensure quality and sustainability of life on earth. The main purposes of KoFlux are to provide (1) an infrastructure to monitor, compile, archive and distribute data for the science community and (2) a forum and short courses for the application and distribution of knowledge and data between scientists including practitioners. The KoFlux community pursues the vision of AsiaFlux, i.e., "thinking community, learning frontiers" by creating information and knowledge of ecosystem science on carbon, water and energy exchanges in key terrestrial ecosystems in Asia, by promoting multidisciplinary cooperations and integration of scientific researches and practices, and by providing the local communities with sustainable ecosystem services. Currently, KoFlux has seven sites in key terrestrial ecosystems (i.e., five sites in Korea and two sites in the Arctic and Antarctic). KoFlux has systemized a standardized data processing based on scrutiny of the data observed from these ecosystems and synthesized the processed data for constructing database for further uses with open access. Through publications, workshops, and training courses on a regular basis, KoFlux has provided an agora for building networks, exchanging information among flux measurement and modelling experts, and educating scientists in flux measurement and data analysis. Despite such persistent initiatives, the collaborative networking is still limited within the KoFlux community. In order to break the walls between different disciplines and boost up partnership and ownership of the network, KoFlux will be housed in the National Center for Agro-Meteorology (NCAM) at Seoul National University in 2011 and provide several core services of NCAM. Such concerted efforts will facilitate the augmentation of the current monitoring network, the education of the next-generation scientists, and the provision of sustainable ecosystem services to our society.
To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.
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