• Journal of the Korean Society of Industry Convergence
• /
• v.21 no.5
• /
• pp.227-234
• /
• 2018

The smart irrigation system using ICT technology is crucial for stable production of upland crops. The objective of this study was to develop a smart irrigation system that can control soil water, depending on irrigation methods, in order to improve crop production. In surface irrigation, three irrigation methods (sprinkler irrigation (SI), surface drip irrigation (SDI), and fountain irrigation (FI)) were installed on a crop field. The soil water contents were measured at 10, 20, 30, and 40 cm depth, and an automatic irrigation system controls a valve to maintain the soil water content at 10 cm to be 30%. In subsurface drip irrigation (SSDI), the drip lines were installed at a depth of 20 cm. Controlled drainage system (CDS) was managed with two ground water level (30 cm and 60 cm). The seasonal irrigation amounts were 96.4 ton/10a (SDI), 119.5 ton/10a (FI), and 113 ton/10a (SI), respectively. Since SDI system supplied water near the root zone of plants, the water was saved by 23.9% and 17.3%, compared with FI and SI, respectively. In SSDI, the mean soil water content was 38.8%, which was 10.8% higher than the value at the control treatment. In CDS, the water contents were greatly affected by the ground water level; the water contents at the surface zone with 30 cm ground water level was 9.4% higher than the values with 60 cm ground water level. In conclusion, this smart irrigation system can reduce production costs of upland crops.

• Journal of Microbiology and Biotechnology
• /
• v.31 no.9
• /
• pp.1231-1240
• /
• 2021

Members of the genus Bacillus are known to play an important role in promoting plant growth and protecting plants against phytopathogenic microorganisms. In this study, 21 isolates of Bacillus spp. were obtained from the root micro-ecosystem of Suaeda glauca. Analysis of the 16S rRNA genes indicated that the isolates belong to the species Bacillus amyloliquefaciens, Bacillus velezensis, Bacillus subtilis, Bacillus pumilus, Bacillus aryabhattai and Brevibacterium frigoritolerans. One of the interesting findings of this study is that the four strains B1, B5, B16 and B21 are dominant in rhizosphere soil. Based on gyrA, gyrB, and rpoB gene analyses, B1, B5, and B21 were identified as B. amyloliquefaciens and B16 was identified as B. velezensis. Estimation of antifungal activity showed that the isolate B1 had a significant inhibitory effect on Fusarium verticillioides, B5 and B16 on Colletotrichum capsici (syd.) Butl, and B21 on Rhizoctonia cerealis van der Hoeven. The four strains grew well in medium with 1-10% NaCl, a pH value of 5-8, and promoted the growth of Arabidopsis thaliana. Our results indicate that these strains may be promising agents for the biocontrol and promotion of plant growth and further study of the relevant bacteria will provide a useful reference for the development of microbial resources.

• Journal of Korea Foundry Society
• /
• v.41 no.1
• /
• pp.26-38
• /
• 2021

The status of Ppuri industry, including foundry industry was analyzed through statistical surveys over the past 10 years from 2009 to 2018, and summarized for each six Ppuri industries' points of view. Various statistics of Ppuri industry defined by the KSIC (Korean Standard Industry Classification) was obtained, and the status of Ppuri industry was identified through a sample survey of 5,000 companies from more than 30,000 target business companies of Ppuri industry. Throughout the analyzing process, we presented a variety of indicators, such as the number of the Ppuri companies and its ratio, regional distribution through Korean provinces, number of workers, characteristics by age group, sales, profit rates, etc. By devising a comparative method to measure the relative strength of Ppuri industry in Korea, Germany, and Japan, we have presented the competitiveness index change over the 10 years of time. The competitiveness index can be effectively and meaningfully used during various activities of the development of Ppuri industry in the forth coming future. With the current obtained data, we figured out the status of each 6 Ppuri industries, regional distribution, status of workers, sales and profit rates. We also suggested various proposals for strategy and policy making for each sector with urging voluntary response from Ppuri industry.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.14 no.3
• /
• pp.184-192
• /
• 2021

Domestic agriculture is facing real problems, such as a decrease in the population in rural areas, a shortage of labor due to an aging population, and increased risks due to the deepening of climate change. Smart farming technology is being developed to solve these problems. In the development of smart agricultural technology, irrigation control plays an important role in creating an optimal growth environment and is an important issue in terms of environmental protection. This paper is about the study of collecting and analyzing the rhizosphere environmental data of domestic paprika farms for the purpose of improving the quality of crops, reducing production costs, and increasing production. Irrigation control modeling presented in this paper Control modeling is to graphically present changes in a medium weight, feed, and drainage due to regional climatic features. To derive the graph, the parameters were determined through data collection and analysis, and the suggested irrigation control modeling method was applied to the collected rhizosphere environmental data to control irrigation in 6 regions (Gangwon-do, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, and Gyeongnam). The parameters were obtained and graphs were derived from them. After that, a study was conducted to analyze the derived parameters to verify the validity of the irrigation control modeling method and to correlate them with climatic features (average temperature and precipitation).

• Geophysics and Geophysical Exploration
• /
• v.24 no.2
• /
• pp.35-44
• /
• 2021

As the execution speed of Python is slower than those of other programming languages (e.g., C, C++, and FORTRAN), Python is not considered to be efficient for writing numerical geodynamic code that requires numerous iterations. Recently, many computational techniques, such as the Just-In-Time (JIT) compiler, have been developed to enhance the calculation speed of Python. Here, we developed two-dimensional (2D) numerical geodynamic code that was optimized for the JIT compiler, based on Python. Our code simulates mantle convection by combining the Particle-In-Cell (PIC) scheme and the finite element method (FEM), which are both commonly used in geodynamic modeling. We benchmarked well-known mantle convection problems to evaluate the reliability of our code, which confirmed that the root mean square velocity and Nusselt number obtained from our numerical modeling were consistent with those of the mantle convection problems. The matrix assembly and PIC processes in our code, when run with the JIT compiler, successfully achieved a speed-up 30× and 258× faster than without the JIT compiler, respectively. Our Python-based FEM-PIC code shows the high potential of Python for geodynamic modeling cases that require complex computations.

• Journal of the Korean Applied Science and Technology
• /
• v.38 no.1
• /
• pp.107-117
• /
• 2021

The purpose of this study is to provide basic data for the development of UV protection products using natural materials. The research method is investigation and analyzation of the current status of the domestic and foreign industries, natural material research trends, and patent status of skin care-related sunscreen. As the result of the study, the U.S. market for sunscreen is the largest one, accounting for about 21% of the world, and the Chinese market is rapidly growing. The top four major types of functional cosmetics in Korea are complex functional products, followed by wrinkle improvement, sunscreen and whitening, and both the global and domestic markets continue to grow continuously. Over the past decade, research trends in natural sunscreen materials have shown that Scutellaria baicalensis, Humulus lupulus L., licorice, Finger root, Green tea, lespedeza cuneata extracts are effective, and in addition, they are also effective in photo-aging, antioxidant, anti-inflammatory, antibacterial, whitening, and wrinkle improvement. The patent registration status is on the rise and the ingredients were secured from plants and seaweeds. As the conclusion of this research, It is expected that natural UV protection material will be able to be used as multi-functional cosmetics material by developing safe and proven natural materials in line with future global trends.

• Journal of Korea Water Resources Association
• /
• v.53 no.12
• /
• pp.1193-1201
• /
• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• The Korea Journal of Herbology
• /
• v.27 no.6
• /
• pp.37-42
• /
• 2012

Objectives : Angelica Gigantis Radix is prescribed as the root of different Angelica species on the pharmacopoeia in Korea, Japan and China. Chemical components and their biological activities were also different according to their species. A study for the development of simple method to compare Angelica roots was needed. In order to classify them, the methods such as DNA sequencing analysis and taste sensor were applied to three Angelica species like Angelica gigas, Angelica acutiloba and Angelica sinensis. Methods : PCR amplification of intergenic transcribed spacer (ITS) region was performed using ITS1 and ITS4 primer from nine Angelica roots, and then nucleotide sequence was determined. Taste pattern of samples were measured using the taste-sensing system SA402B equipped with a sensing unit, which consists of artificial lipid membrane sensor probes of anionic bitterness, astringency, saltiness, umami, and cationic bitterness (C00, AE1, CT0, AAE, and AN0, respectively). Results : As a result of comparing the similarity of the ITS region sequences, A. sinensis was discriminated from the others (A. gigas and A. acutiloba). Equally this genetic result, A. gigas and A. acutiloba showed similar taste pattern as compared to A. sinensis. Sourness, bitterness, aftertaste of bitterness, astringency, and aftertaste of astringency of A. sinensis were significantly high as compared with A. gigas and A. acutiloba. In contrast, richness was significantly low. Conclusions : These taste pattern can be used as a way of comparison of Angelica species and this technic could be applied to establish a taste pattern marker for standardization of herbs in various purposes.

• Smart Media Journal
• /
• v.11 no.10
• /
• pp.65-75
• /
• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.397-412
• /
• 2023

In order for social robots to take root in human life, it is important to consider the technical implementation of social robots and human psychology toward social robots. This study aimed to derive potential social robot clusters based on the emotions consumers feel about social robot appearance design, and to identify and compare important design characteristics and emotional differences of each cluster. In our study, we established a social robot emotion framework to measure and evaluate the emotions consumers feel about social robots, and evaluated the emotions of social robot designs based on the semantic differential method, an kansei engineering approach. We classified 30 social robots into 4 clusters by conducting a multidimensional scaling method and K-means cluster analysis based on the emotion evaluation results, confirmed the characteristics of design elements for each cluster, and conducted a comparative analysis on consumer emotions. We proposed a strategic direction for successful social robot design and development from a human-centered perspective based on the design characteristics and emotional differences derived for each cluster.