• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of Life Science
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• v.32 no.12
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• pp.947-955
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• 2022

Silkworms, which have recently shown promise as functional health foods, show functional differences between varieties; therefore, the need for variety identification is emerging. In this study, we analyzed the whole silkworm genome to identify 10 unique silkworm varieties (Baekhwang, Baekok, Daebaek, Daebak, Daehwang, Goldensilk, Hansaeng, Joohwang, Kumkang, and Kumok) using single nucleotide polymorphisms (SNP) present in the genome as biomarkers. In addition, nine SNPs were selected to discriminate between varieties by selecting SNPs specific to each variety. We subsequently created a decision tree capable of cross-verifying each variety and classifying the varieties through sequential analysis. Restriction fragment length polymorphism (RFLP) was used for SNP867 and SNP9183 to differentiate between the varieties of Daehwang and Goldensilk and between Kumkang and Daebak, respectively. A tetra-primer amplification refractory (T-ARMS) mutation was used to analyze the remaining SNPs. As a result, we could isolate the same group or select an individual variety using the nine unique SNPs from SNP780 to SNP9183. Furthermore, nucleotide sequence analysis for the region confirmed that the alleles were identical. In conclusion, our results show that combining SNP analysis of the whole silkworm genome with the decision tree is of high value as a discriminative marker for classifying silkworm varieties.

• 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.

• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.5-24
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• 2022

The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.489-496
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• 1997

This study was carried out to develop and investigate integrated mechanization system on polyethylene(P.E.) film mulching culture in sesame. Field trials were carried out to develop optimum mechanics for each step of manual operation in sesame culture and demonstrated those developed mechanics of sesame dibbling vinyl mulcher, sesame binder, sesame thresher and sesame grader at the farmer, s field of Hwasong (Kyunggi-do) in 1994 and 1995. Newly developed sesame dibbling vinyl mulcher brought saving manpower 280 hrs /ha for sowing and P.E. film mulching with it's 98％ of labour saving for the harvesting operation of sesame. Sesame Binder showed 93％ labour saving for cutting and binding with only 22 hrs /ha compared to 330 hrs /ha that of conventional. Sesame thresher was appeared to have 85％ effects of labour saving for threshing with completely dry sesame bundles at one time by 23 hrs /ha compared to 151 hrs /ha that of conventional. Sesame grader was appeared to have 72％ effects for sesame grain grading with 12 hrs /ha compared to that of conventional 54 hrs /ha. Grain yield of integrated mechanization culture system showed 6％ higher than that of coventional. Integrated mechanization culture system (sesame dibbling vinyl mulcher ＋ sesame binder ＋ sesame thresher ＋ sasame grader) showed 62％ of labour saving effects through whole steps of sesame culture by 472 hrs /ha compared to that of conventional 1, 230 hrs /ha.

• Journal of Mushroom
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• v.21 no.3
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• pp.93-100
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• 2023

In this study, research trends in mushroom science were examined using North Korean journal articles published in 1978-2023. Researchers in each field reviewed 450 papers and finally selected 429 papers, excluding 21 papers classified in different fields. The number of researchers was 872, and the number of authors per paper was 2.03. Kim Cheol-Hak published the most academic papers in the field of mushroom science in North Korea, with 12 papers. The number of research articles increased annually, from 7 in 1985, 12 in 1998, 11 in 2008, and 27 in 2020, and has especially increased rapidly since the mid-2010s. The study by mushroom type was as follows: 42 pine mushrooms (17.8 %), 25 oyster mushrooms (10.6 %), 23 Ganoderma sp. (9.8 %), 19 shiitake mushrooms (8.1 %), 17 button mushrooms (7.2 %), and 16 manna lichens (6.8 %). This study is considered meaningful in reviewing the research status and technology level in North Korea through analyzing North Korean academic journals in the field of mushroom science for the first time.

• Journal of Life Science
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• v.33 no.2
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• pp.158-168
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• 2023

Natural products have been used to mitigate the effects of cancer and infectious diseases, as they feature diverse bioactivities, such as antioxidant, antibacterial, anti-inflammatory, and immunomodulatory effects. Here, we chose 10 natural products that are well-known as pulmonary enhancers and investigated their bactericidal effects on Streptococcus pneumoniae. In the disk diffusion assay, the growth of S. pneumoniae was significantly regulated by G. fructus treatment regardless of extraction method used. We first adopted spraying as a novel delivery method for G. fructus. Interestingly, mice exposed to G. fructus three times a day for 2 weeks were resistant to S. pneumoniae intranasal infection (shown both through body weight loss and survival rates compared to the control group). Moreover, we confirmed that exposure to G. fructus regulated the colonization of the bacteria despite the sustained inflammation in the lung after exposure to S. pneumoniae, indicating that migrated inflammatory immune cells may involve a host defense mechanism against pulmonary infectious diseases. While a similar number of granulocytes (CD11b⁺Ly6C⁺Ly6G⁺), neutrophils (CD11b⁺Ly6C^intLy6G⁺), and monocytes (CD11b⁺Ly6C^intLy6G^-) were found between groups, a significantly increased number of alveolar macrophages (CD11b⁺CD11c^hiF4/80⁺) was detected in BAL fluids of mice pre-exposed to G. fructus at 5 days after S. pneumonia infection. Taken together, our data suggest that this usage of G. fructus can induce protective immunity against bacterial infection, indicating that facial spray may be helpful in enhancing the defense mechanism against pulmonary inflammation and in evaluating the efficacy of natural products as immune enhancers against respiratory diseases.

• Korea Trade Review
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• v.42 no.2
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• pp.145-174
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• 2017

Recently, due to the worsening global economic recession, Korea which is a small, export-oriented economy has decreased exports and the domestic economy also continues to stagnate. Therefore, for continued growth of our economy through export growth, we need to analyze the validity of export support system such as export insurance and prepare ways to expand exports. This study is to investigate the effects of Export Insurance on the exports of SMEs as well as LEs. For this purpose, this study conducted Time Series Analysis using data such as export, export insurance acquisition, export price index, exchange rate, and coincident composite index(CCI). First, as a result of the Granger Causality Test, the exports of LEs has found to have a causal relationship with the CCI, and CCI is to have a causal relationship with the short-term export insurance record. Second, the results of VAR analysis show that the export insurance acquisition result and the export price index have a positive effect on the exports of LEs, while the short - term export insurance has a negative effect on the exports of LEs. Third, as a result of variance decomposition, the export of LEs has much more influenced for mid to long term by the short-term export insurance acquisition compared to SMEs. Fourth, short-term export insurance has a positive effect on exports of SMEs. In order to activate short-term export insurance against SMEs, it is necessary to expand support for SMEs by local governments. This study aims to suggest policy implications for establishing effective export insurance policy by analyzing the effects of export insurance on the export of SMEs as well as LEs. It is necessary to carry out a time series analysis on the export results according to the insurance acquisition results by industry to measure the export support effect of export insurance more precisely.

• Korea Trade Review
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• v.48 no.1
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• pp.243-261
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• 2023

This study was conducted with the goal of analyzing the needs of Truckers, who are the main users of the cargo transportation platform, to find a development direction for the improvement and activation of the cargo transportation platform service. For this purpose, this study conducted an empirical analysis through IPA analysis targeting Truckers using domestic cargo transportation platforms. As a result of the IPA analysis, in the case of importance, fair fare presentation, unfair trade prevention measures, transportation payment deadline accuracy, transportation section information provision accuracy, quick interaction, application system quality, ease of use, user-customized service, settlement service support function, Variety of transportation sections, brand image, and additional services were shown in order. In the case of satisfaction, ease of use, settlement service support function, transport section information provision accuracy, application system quality, brand image, additional services, user-customized service, transport section diversity, quick interaction, transport payment deadline accuracy, unfair transaction prevention Measures and fair fares were presented in that order. The analysis results show high satisfaction with the ease of use related to the platform quality and the function to support the settlement work. These results can be seen as the result of a significant investment in system quality improvement for the convenience of users by suppliers in the domestic cargo transportation platform industry, where competition has become fierce. As the factors most urgently needed for improvement, 'observance of payment deadlines', 'prevention of unfair trade', and 'provision of fair fares' were selected, and these are related to chronic problems in the domestic freight transportation industry.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1097-1109
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• 2023

Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.