• Journal of Life Science
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• v.29 no.1
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• pp.9-17
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• 2019

As tumors develop, they encounter microenvironmental stress, such as hypoxia and glucose depletion, due to poor vascular function, thereby leading to necrosis, which is observed in solid tumors. Necrotic cells are known to release cellular cytoplasmic contents, such as high mobility group box 1 (HMGB1), into the extracellular space. The release of HMGB1, a proinflammatory and tumor-promoting cytokine, plays an important role in promoting inflammation and metabolism during tumor development. Recently, HMGB1 was shown to induce the epithelial-mesenchymal transition (EMT) and metastasis. However, the underlying mechanism of the HMGB1-induced EMT, invasion, and metastasis is unclear. In this study, we showed that noninvasive breast cancer cells MCF-7 formed tightly packed, rounded spheroids and that the cells in the inner regions of a multicellular tumor spheroid (MTS), an in vitro model of a solid tumor, led to necrosis due to an insufficient supply of O2 and glucose. In addition, after 7 d of MTS culture, the EMT was induced via the transcription factor Snail. We also showed that HMGB1 receptors, including RAGE, TLR2, and TLR4, were induced by MTS culture. RAGE, TLR2, and TLR4 shRNA inhibited MTS growth, supporting the idea that RAGE/TLR2/TLR4 play critical roles in MTS growth. They also prevented MTS culture-induced Snail expression, pointing to RAGE/TLR2/TLR4-dependent Snail expression. RAGE, TLR2, and TLR4 shRNA suppressed the MTS-induced EMT. In human cancer tissues, high levels of RAGE, TLR2, and TLR4 were detected. These findings demonstrated that the HMGB-RAGE/TLR2/TLR4-Snail axis played a crucial role in the growth of the MTS and MTS culture-induced EMT.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.95-103
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• 2019

Temperature and relative humidity are important factors in crop cultivation and should be properly controlled for improving crop yield and quality. In order to control the environment accurately, we need to predict how the environment will change in the future. The objective of this study was to predict air temperature and relative humidity at a future time by using a multilayer perceptron (MLP). The data required to train MLP was collected every 10 min from Oct. 1, 2016 to Feb. 28, 2018 in an eight-span greenhouse ($1,032m^2$) cultivating mango (Mangifera indica cv. Irwin). The inputs for the MLP were greenhouse inside and outside environment data, and set-up and operating values of environment control devices. By using these data, the MLP was trained to predict the air temperature and relative humidity at a future time of 10 to 120 min. Considering typical four seasons in Korea, three-day data of the each season were compared as test data. The MLP was optimized with four hidden layers and 128 nodes for air temperature ($R^2=0.988$) and with four hidden layers and 64 nodes for relative humidity ($R^2=0.990$). Due to the characteristics of MLP, the accuracy decreased as the prediction time became longer. However, air temperature and relative humidity were properly predicted regardless of the environmental changes varied from season to season. For specific data such as spray irrigation, however, the numbers of trained data were too small, resulting in poor predictive accuracy. In this study, air temperature and relative humidity were appropriately predicted through optimization of MLP, but were limited to the experimental greenhouse. Therefore, it is necessary to collect more data from greenhouses at various places and modify the structure of neural network for generalization.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.126-133
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• 2019

In recent years, the deterioration of fruit quality caused by poor coloration and sunburn disorder has become serious problems in apple market, which is a result of the increase of surface temperature due to the abnormal temperature increase during summer season. This study was conducted to investigate the effect of wind net shading and fine water spray using sprinkler on fruit coloration, sunburn damage and overall fruit quality of 'Fuji' and 'Hongro' apples. Fifteen sprinklers (7L/hr) were installed at the orchard of the Chungcheongnam-do Agricultural Research and Extension Services, located in Sinam-myeon Chungcheongnam-do Korea, at a height of 3m above the apple tree of $1.5m{\times}3.5m$ north-south direction. Fine water spraying treatment was divided into day time spray (10:00 am to 6:00 pm) and all day spray (10:00 am to 10:00 pm) from early July to 10 days before harvest in 2017 and 2018 season, respectively. Temperature of the surface of apple fruit, characteristic of fruit, and degree of sunburn damage were investigated. In 'Fuji', the fruit surface temperature checked at 2 pm on August 10 was decreased considerably in the day time spray ($35.6^{\circ}C$) and wind net ($39.0^{\circ}C$) when compared with the untreated control ($44.4^{\circ}C$). Similarly, the fruit surface temperature also decreased considerably in the all day spray ($35.1^{\circ}C$) and wind net ($36.9^{\circ}C$) treatments when compared with the untreated control ($46.5^{\circ}C$) in 'Hongro' apples. The incidence of sunburn disorder was significantly decreased with day time spray (5.0%), all day spray (5.8%) and wind net (7.0%) when compared with untreated control (23.4%) in 'Fuji' apples. As a results, the treatment of fine water spray and wind net consequently showed 26% and 34% increase of redness ($a^*$) value in the skin color difference, respectively, in 'Fuji' apples.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.328-338
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• 2018

Central Asia (Uzbekistan, Kazakhstan, Kyrgyzstan) is a hot and arid continental climate, with most areas (68%) consisting of barren vegetation, desert, and meadows. The main agricultural areas for crop production include irrigated farmland, non-irrigated farmland, grassland, prairie and mountain. We are experiencing climate change with recent climate variability increasing. Agriculture is one of major economic sectors and provides a means of livings for the rural population of Central Asia, especially the poor. In the past two decades, Central Asia has experienced a high population growth rate, with Kazakhstan at 16.8%, Uzbekistan at 34.5% and Kyrgyzstan at 28.4%. As a major industry, Kazakhstan has the largest share of exports of agricultural products followed by petroleum, mineral resources, steel, and chemicals. Uzbekistan is the fifth largest cotton exporter as well as the sixth largest cotton producer in the world. Kyrgyzstan exports ores, stones, cultured pearls, and minerals. These three countries are rich in mineral resources, agricultural products, and energy resources. However, not only do they have difficulties in economic development due to the weakness of logistics and industrial infrastructure, but they also have imperceptible cooperation and investment among countries due to insufficient research and development. Through this study, we will investigate national outlook, economic indicators, major agricultural products, import and export status, and agricultural technology cooperation status, and study how Korean agricultural industry advances into these countries through SWOT analysis. Through this, we hope to contribute to the basic data of Central Asian studies and cooperation and investment in agriculture in each country. In addition, in order to increase cooperative exchange and investment in these countries, we will prepare a Central Asia logistics hub for the rapidly changing interKorean railroad era.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.558-568
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• 2021

Poor supervision and tourism activities have resulted in forest degradation in islands in Korea. Since the southern coastal region of the Korean peninsula was originally dominated by warm-temperate evergreen broad-leaved forests, it is desirable to restore forests in this region to their original vegetation. In this study, we identified suitable areas to be restored as evergreen broad-leaved forests by analyzing the environmental factors of existing evergreen broad-leaved forests in the islands of Jeollanam-do. We classified forest lands in the study area into six vegetation types from Sentinel-2 satellite images using a deep learning algorithm and analyzed the tolerance ranges of existing evergreen broad-leaved forests by measuring the locational, topographic, and climatic attributes of the classified vegetation types. Results showed that evergreen broad-leaved forests were distributed more in areas with a high altitudes and steep slope, where human intervention was relatively low. The human intervention has led to a higher distribution of evergreen broad-leaved forests in areas with lower annual average temperature, which was an unexpected but understandable result because an area with higher altitude has a lower temperature. Of the environmental factors, latitude and average temperature in the coldest month (January) were relatively less contaminated by the effects of human intervention, thus enabling the identification of suitable restoration areas of the evergreen broad-leaved forests. The tolerance range analysis of evergreen broad-leaved forests showed that they mainly grew in areas south of the latitude of 34.7° and a monthly average temperature of 1.7℃ or higher in the coldest month. Therefore, we predicted the areas meeting these criteria to be suitable for restoring evergreen broad-leaved forests. The suitable areas cover 614.5 km², which occupies 59.0% of the total forest lands on the islands of Jeollanamdo, and 73% of actual forests that exclude agricultural and other non-restorable forest lands. The findings of this study can help forest managers prepare a restoration plan and budget for island forests.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.487-499
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• 2021

Purpose:The purpose of the paper is to review the problems of performance enhancement of safety certification standards and to suggest directions for improvement in order to rationalize safety certification standards for future industrial development and environmental changes. Method: The problems and limitations of the safety certification system are summarized through literature review and interview with manager, and the status of safety certification standards is classified into design standards, performance standards, and detailed standards, and the status analysis is performed. In addition, by synthesizing the results of the investigation and analysis, improvements are suggested to improve the performance of the safety certification standards. Result: Through the survey, the problems and limitations of safety certification could be grouped into six categories: government-led certification system operation, standardized certification standards, long time required to improve certification, poor certification standards preparation system, and lack of reflection of industry opinions. And, as a result of analyzing the certification standards by dividing them into performance and design standards, in the case of machinery, equipment, and protection devices, the design standards were high at 69.7% and 64.9%, whereas in the case of protective equipment, the performance standards were high at 61.1%. In order to improve the performance of safety certification standards centered on design standards, it is necessary to determine the possibility of performance enhancement of the certification standards and determine the feasibility of the inspection test method. In order to improve performance, it was reviewed that it was necessary to establish a systemic foundation and infrastructure, such as strengthening the Product Liability Act, systematizing market monitoring, etc., distributing certification test tasks, and participating in the preparation of certification standards by the private sector. Conclusion: Through this study, the problems and limitations of Korea's safety certification system were summarized and the necessity for performance improvement was reviewed. Performance improvement of safety certification standards is a matter that requires preparatory work, such as legislative revision and infrastructure construction, and requires mid-to-long-term promotion. In addition, rather than improving the overall safety certification standards, the performance requirements for each item subject to certification should be reviewed and promoted, and details should be specified through additional research.

• Korean Journal of Plant Resources
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• v.34 no.4
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• pp.287-296
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• 2021

Recently, the pace of global climate change has tremendously increased, causing extreme damage to crop production. Here, we aimed to examine the growth characteristics and useful components of Angelica gigas under extreme heat stress, providing fundamental data for its efficient cultivation. Plants were exposed to various experimental temperatures (28℃, 34℃, and 40℃), and their growth characteristics and content of useful components were analyzed. At the experimental site, the ambient and soil temperature were 19.38℃ and 21.34℃, ambient and soil humidity were 81.3 % and 0.18 m³/m³, solar radiation was 162.05 W/m². Moreover, the soil was sandy-clay-loam (pH 6.65), with 2.66% organic matter, 868.52 mg/kg soil available phosphate, and 0.14% nitrogen. Values of most growth characteristics, including the survival rate (85%), plant height (38.66cm), and fresh and dry weight (41.3 g and 14.24 g), were the highest at 28℃. Although the highest content of useful components was observed at 34℃ (3.24%), there were no significant differences across temperatures. Growth characteristics varied across temperatures due to detrimental effects of heat stress, such as accelerated tissue aging, reduced photosynthesis, and delay of growth. Similar content of useful components across temperatures may be due to poor accumulation of anabolic products caused by impaired growth at extremely high temperatures.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.146-154
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• 2021

This study was conducted to determine the degree of reduction in the yield of sweetpotato subjected to different shading treatments according to the growing season of the typical viscous sweetpotato 'Hogammi' and the powdery sweetpotato 'Jinyulmi'. Shading was provided using commercially available shading nets (55% and 75% shading level), and the treatments were applied at the following stages of storage root growth: SFS: the storage root formation stage (planting-50^th day), SSS: the storage root swelling stage (50-90^th day), and SAS: the storage root actively swelling Stage (90-120^th day). The growth characteristics according to shading treatments during each growth period, the number of tubers obtained at harvest, and sugar contents were investigated. For both assessed cultivars, there was no significant difference between the control group and the 55% shading treated group with respect to the maximum quantum yield (Fv/Fm) of photosystem II under different shading treatments, whereas the 75% shading group showed slightly higher values than the control group. In both cultivars, the contents of chlorophyll a and b tended to increase in plants subjected to shading treatments compared with the control plants, particularly that of chlorophyll b. Compared with the control group, the chlorophyll b content of 'Hogammi' subjected to 55% and 75% shading increased by 47% and 41%, respectively, whereas that of 'Jinyulmi' increased by 39% and 34%, respectively. We also detected reductions in the dry weights of the above- and belowground parts of the two varieties in response to shading compared with the control, with the reduction in the dry weight of belowground parts being significant. Furthermore, in both varieties, the T/R rate tended to increase in response to shading treatment. Owing to the lack of sunlight, both cultivars tended to suppress the formation and enlargement of tuber roots. Consequently, post-harvest yield analysis revealed that under shading treatments, both cultivars were characterized by poor tuber root growth according to growing season, with the yield of 'Hogammi' showing a greater reduction compared with that of 'Jinyulmi'. In addition, we found that the higher shading level also significantly reduced yields. Compared with the storage root formation and storage root actively swelling stages, shading treatments during the storage root swelling stage significantly affected yield reduction in both varieties.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.45-54
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• 2021

This study was written to create educational content in non-destructive fields based on Mixed Reality. Currently, in the field of radiation, there is almost no content for educational Mixed Reality-based educational content. And in the field of non-destructive inspection, the working environment is poor, the number of employees is often 10 or less for each manufacturer, and the educational infrastructure is not built. There is no practical training, only practical training and safety education to convey information. To solve this, it was decided to develop non-destructive worker education content based on Mixed Reality. This content was developed based on Microsoft's HoloLens 2 HMD device. It is manufactured based on the resolution of 1280 ⁎ 720, and the resolution is different for each device, and the Side is created by aligning the Left, Right, Bottom, and TOP positions of Anchor, and the large image affects the size of Atlas. The large volume like the wallpaper and the upper part was made by replacing it with UITexture. For UI Widget Wizard, I made Label, Buttom, ScrollView, and Sprite. In this study, it is possible to provide workers with realistic educational content, enable self-directed education, and educate with 3D stereoscopic images based on reality to provide interesting and immersive education. Through the images provided in Mixed Reality, the learner can directly operate things through the interaction between the real world and the Virtual Reality, and the learner's learning efficiency can be improved. In addition, mixed reality education can play a major role in non-face-to-face learning content in the corona era, where time and place are not disturbed.