• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.422-431
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• 2019

Severe droughts in spring have occurred frequently in Korea in recent years, exerting a critical impact on corn yield. Therefore, it is necessary to find physiological and/or molecular indicators of the response to drought stress in maize plants. In this study, we investigated the effects of water-deficit stress on two Korean elite F₁ maize hybrids, Ilmichal and Gwangpyeongok, by withholding water for 10 days at tassel initiation. The water deficit drastically reduced the relative leaf water content, leaf number, leaf area, and stem length, leading to dry matter reduction. Moreover, it reduced the SPAD values and stomatal conductance of leaves in drought-stressed plants of both hybrids. Importantly, the number of leaves and SPAD value were non-destructive and easy to investigate in response to water-deficit stress, suggesting that they may be useful indicators for screening drought-tolerant genetic resources. We detected more than 100 spots that were differentially accumulated under drought stress. Of these spots, a total of 21 protein spots (≥1.5-fold) from drought-exposed maize leaves were successfully analyzed by MALDI-TOF-TOF mass spectrometry. Functional annotation using Gene Ontology analysis revealed that most of the identified proteins were involved in carbohydrate metabolism, stress response fatty acid catabolism, photosynthesis, energy metabolism, and transport. The protein expression levels were increased in both Ilmichal and Gwangpyeongok, except for triosephosphate isomerase, fructose-bisphosphate aldolase, and an uncharacterized protein. The lactoylglutathione lyase delta (3,5)-delta (2,4)-dienoyl-CoA isomerase was overexpressed in Gwangpyeongok only. The results obtained from this study suggest that the drought-specific genes may be useful as molecular markers for screening drought-tolerant maize genotypes.

• Journal of Genetic Medicine
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• v.4 no.1
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• pp.45-52
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• 2007

Purpose : A simple, rapid, and highly sensitive analytical method for Gb3 in plasma was developed without labor-ex tensive pre-treatment by electrospray ionization MS/ MS (ESI-MS/MS). Measurement of globotriaosy lceramide (Gb3, ceramide trihex oside) in plasma has clinical importance for monitoring after enzyme replacement therapy in Fabry disease patients. The disease is an X-linked lipid storage disorder that results from a deficiency of the enzyme ${\alpha}$-galactosidase A (${\alpha}$-Gal A). The lack of ${\alpha}$-Gal A causes an intracellular accumulation of glycosphingolipids, mainly Gb3. Methods : Only simple 50-fold dilution of plasma is necessary for the extraction and isolation of Gb3 in plasma. Gb3 in diluted plasma was dissolved in dioxane containing C17:0 Gb3 as an internal standard. After centrifugation it was directly injected and analyzed through guard column by in combination with multiple reaction monitoring mode of ESI-MS/MS. Results : Eight isoforms of Gb3 were completely resolved from plasma matrix. C16:0 Gb3 occupied 50% of total Gb3 as a major component in plasma. Linear relationship for Gb3 isoforms w as found in the range of 0.001-1.0 ${\mu}g$/mL. The limit of detection (S/N=3) was 0.001 ${\mu}g$/mL and limit of quantification was 0.01 ${\mu}g$/mL for C16:0 Gb3 with acceptable precision and accuracy. Correlation coefficient of calibration curves for 8 Gb3 isoforms ranged from 0.9678 to 0.9982. Conclusion : This quantitative method developed could be useful for rapid and sensitive 1st line Fabry disease screening, monitoring and/or diagnostic tool for Fabry disease.

• The Korean Journal of Archival Studies
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• no.24
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• pp.113-171
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• 2010

The purpose of this study was to examine the characteristics of Seoul Olympic Organizing Committee's official documents. To conduct this work, the fundamental of producing archives were examined by analyzing structure and management of Seoul Olympic Organizing Committee and structure of official document production. After all, simultaneous and synthesis characteristics of Seoul Olympic Organizing Committee's official documents were presented through overall analysis of production fundamental and relationship between their management and remained archives. The result of this study are as follows. Firstly, The Organizing Committee had bicameral organizational structure and matrix organizational format consisting of functional department and project department. Indicating the institutions and development phase of decision making in the committee, most of institutions were in name only. Also, there were many problems occurred in the procedure of decision making since the president of committee exercised all of the authorities. Secondly, It was found that existing official documents of the committee were partial and caused fragment phenomenon and severe situations because of unsystematic archival management department and regulations. Moreover, as the result of investigating production procedure and management of official documents, procedure of production, distribution, preservation and abolition of them were specifically verified. Thirdly, It was verified that the official documents were abolished arbitrarily because of unsystematic archival management department and insufficient regulations. For the actual condition of management, filing or description activity which is essential measure for using and utilizing the official documents has not been conducted yet. Based on these facts, the characteristics of Seoul Olympic Organizing Committee's official documents can be referred as follows. The official archives of the committee have multiplicity of the origin and severe fragment phenomenon damaging the origin and the elementary substance of the archives. Also, the format of existing archives was unbalance. Besides, there was not enough related research since they were in adverse situation to utilize them as the archives which are not assessed or not arranged. Thus, it was hard to grasp the utility value at present and future, and was also limited for usage object.

• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.13-21
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• 2019

A method was developed for the simultaneous detection of an antibiotic fungicide, streptomycin, and its metabolite (dihydrostreptomycin) in agricultural products using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The samples were extracted using methanol adjusted to pH 3 using formic acid, and purified with a HLB (Hydrophilic lipophilic balance) cartridge. The matrix-matched calibration curves were constructed using seven concentration levels, from 0.001 to 0.1 mg/kg, and linearity of five agricultural products (hulled rice, potato, soybean, mandarin, green pepper), with coefficients of determination $(R^2){\geq}0.9906$, for streptomycin and dihydrostreptomycin. The mean recoveries at three fortification levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n = 5) were from 72.0~116.5% and from 72.1~116.0%, and relative standard deviations were less than 12.3% and 12.5%, respectively. The limits of quantification (LOQ) were 0.01 mg/kg, which are satisfactory for quantification levels corresponding with the Positive List System. All optimized results satisfied the criteria ranges requested in the Codex guidelines and the Food Safety Evaluation Department guidelines. The present study could serve as a reference for the establishment of maximum residue limits and be used as basic data for detection of streptomycin and dihydrostreptomycin in food.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.369-376
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• 2021

The purpose of this study is to develop a coaching model which can enhance teaching ability of lifelong educator. To achieve this purpose, this study verifies and analyzes several documentary records related with diverse teaching capabilities, operation reality and coaching method run by lifelong educator. Furthermore, an in-depth interview about teaching capability was undertaken for field experts who have worked at the institutions of lifelong education for more than 10 years. As a result, the study could develop a coaching model to identify teaching capability of lifelong educator by conducting matrix analysis. First, according to the documentary studies, the paradigm for lifelong education has been shifted to centralize learner's demand with the advent of 4th industrial revolution and it suggests coaching capability which could enhance educator's capability should come first. A lifelong educator should have capabilities including identification of vision and goal, creation of mission declaration, development of coaching skill and procedure, management of crisis and coaching capability as an expert in the lifelong education field. Second, a model which can centralize learners could be developed for lifelong teaching capability by adopting a teaching capability suggested by field experts, According to the experts, it is essential to develop a program model to acquire professional knowledge, communication capability, understanding of adult learner, personal relations capability. If there is a model which can develop such capabilities, it is able to strengthen lifelong teaching capability to focus on learner's demand, mainly adult learners, a major consumer of the field. Third, a coaching model to enhance teaching capability for an educator is to acquire and implement sufficient step-by-step teaching capability which has been suggested from a procedure comprised of entrance, progress, critique and return. This, present study suggests, after the critique, a lifelong educator oneself can newly develop and extend a teaching capability basis on pursuing teaching capability as a lifelong educator through the return process.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Explosives and Blasting
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• v.9 no.1
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• pp.3-13
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• 1991

The cautious blasting works had been used with emulsion explosion electric M/S delay caps. Drill depth was from 3m to 6m with Crawler Drill ${\phi}70mm$ on the calcalious sand stone (soft -modelate -semi hard Rock). The total numbers of test blast were 88. Scale distance were induced 15.52-60.32. It was applied to propagation Law in blasting vibration as follows. Propagtion Law in Blasting Vibration $V=K(\frac{D}{W^b})^n$ were V : Peak partical velocity(cm/sec) D : Distance between explosion and recording sites(m) W : Maximum charge per delay-period of eight milliseconds or more (kg) K : Ground transmission constant, empirically determind on the Rocks, Explosive and drilling pattern ets. b : Charge exponents n : Reduced exponents where the quantity $\frac{D}{W^b}$ is known as the scale distance. Above equation is worked by the U.S Bureau of Mines to determine peak particle velocity. The propagation Law can be catagorized in three groups. Cubic root Scaling charge per delay Square root Scaling of charge per delay Site-specific Scaling of charge Per delay Plots of peak particle velocity versus distoance were made on log-log coordinates. The data are grouped by test and P.P.V. The linear grouping of the data permits their representation by an equation of the form ; $V=K(\frac{D}{W^{\frac{1}{3}})^{-n}$ The value of K(41 or 124) and n(1.41 or 1.66) were determined for each set of data by the method of least squores. Statistical tests showed that a common slope, n, could be used for all data of a given components. Charge and reduction exponents carried out by multiple regressional analysis. It's divided into under loom over loom distance because the frequency is verified by the distance from blast site. Empirical equation of cautious blasting vibration is as follows. Over 30m ------- under l00m ${\cdots\cdots\cdots}{\;}41(D/sqrt[2]{W})^{-1.41}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}A$ Over 100m ${\cdots\cdots\cdots\cdots\cdots}{\;}121(D/sqrt[3]{W})^{-1.66}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}B$ where ; V is peak particle velocity In cm / sec D is distance in m and W, maximLlm charge weight per day in kg K value on the above equation has to be more specified for further understaring about the effect of explosives, Rock strength. And Drilling pattern on the vibration levels, it is necessary to carry out more tests.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.141-166
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• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.