• Journal of Plant Biotechnology
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• v.29 no.1
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• pp.41-44
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• 2002

During the phloem development from parenchyma cells in a suspension culture of Streptanthus induced sucrose carrier and glucose carrier disappeared. Sieve element area and sieve pore induced suspension culture of Streptanthus were formed almost at the last period of the synthesis of sieve endoplasmic reticulum (SER) and p-protein. The new synthesized cell wall begann to digeste only after the new cell wall was surrounded by SER. The digested region of the cell wall and the formed region of sieve pore were regular comparatively. The completed sieve pore was an oval form, and the outer portion of sieve pore varied, ca 1.2 ${\mu}{\textrm}{m}$~1.6 ${\mu}{\textrm}{m}$ in longitudinal, 0.8 ${\mu}{\textrm}{m}$~1.3 ${\mu}{\textrm}{m}$ in tangential, and the inner size of sieve pore was irregular form of a star-like shape. The number of sieve pore between sieve cells was ca 2~7 per ${\mu}{\textrm}{m}$$^2$ and the sieve pore wall with callose was 0.05 ${\mu}{\textrm}{m}$~0.07 ${\mu}{\textrm}{m}$ in thickness. The energy for the formation of sieve element area and sieve pore might be supplied by mitochondria near the new cell wall and the role of SER remains to be illucidated.

• Journal of Convergence for Information Technology
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• v.8 no.4
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• pp.73-80
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• 2018

The purpose of this study was to investigate the effect of motion-based dance game on static and dynamic balance in elderly women. The participants were randomly divided into 2 group, Motion Based dance game group(n=10), control group(n=10). After they were divided into an Motion Based dance game group and a control group the Motion Based dance game group participated in six-week period of time, three times a week, 60 minutes each, and the control group didn't exercise outside of their daily lives. To evaluated the balance ability of exercise, it was evaluated by using Berg Balance Scale(BBS), Functional Reach Test(FRT), Timed Up and Go test(TUG). The data was analysis using a paired t-test and independent t-test to determine the statistical significance. The results of this study between BBS, FRT, TUG and Motion Based dance game group had statistically significant difference rather than control group(p<.05). In conclusion, the Motion based Dance Game showed improvement on the balance ability in the elderly. Regular maintenance of the Dance Game "Dance Central" program for the elderly will assistance improve the balance. Consequently, studies on the development of dance games suitable for the elderly are believed to be necessary.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.71-85
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• 2021

A variety of methods have been proposed through a number of studies on sophisticated demand forecasting models that can reduce logistics costs. These studies mainly determine the applicable demand forecasting model based on the pattern of demand quantity and try to judge the accuracy of the model through statistical verification. Demand patterns can be broadly divided into regularity and irregularity. A regular pattern means that the order is regular and the order quantity is constant. In this case, predicting demand mainly through regression model or time series model was used. However, this demand is called "intermittent demand" when irregular and fluctuating amount of order quantity is large, and there is a high possibility of error in demand prediction with existing regression model or time series model. For items that show intermittent demand, predicting demand is mainly done using Croston or HOLTS. In this study, we analyze the demand patterns of various items of air cargo with intermittent patterns and apply the most appropriate model to predict and verify the demand. In this process, intermittent optimal demand forecasting model of air cargo is proposed by analyzing the fit of various models of air cargo by item and region.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.15-25
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• 2019

The development of reliable and objective definitions as well as automated processes for the detection of health care-associated infections (HAIs) is crucial; however, transformation to an automated surveillance system remains a challenge. Early outbreak identification usually requires clinicians who can recognize abnormal events as well as ongoing disease surveillance to determine the baseline rate of cases. The system screens the laboratory information system (LIS) data daily to detect candidates for health care-associated bloodstream infection (HABSI) according to well-defined detection rules. The system detects and reserves professional autonomy by requiring further confirmation. In addition, web-based HABSI surveillance and classification systems use discrete data elements obtained from the LIS, and the LIS-provided data correlates strongly with the conventional infection-control personnel surveillance system. The system was timely, acceptable, useful, and sensitive according to the prevention guidelines. The surveillance system is useful because it can help health care professionals better understand when and where the transmission of a wide range of potential pathogens may be occurring in a hospital. A national plan is needed to strengthen the main structures in HAI prevention, Healthcare Associated Prevention and Control Committee (HAIPCC), sterilization service (SS), microbiology laboratories, and hand hygiene resources, considering their impact on HAI prevention.

• Korean Journal of Heritage: History & Science
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• v.51 no.1
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• pp.100-125
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• 2018

The Japanese colonial authority investigated and institutionalized Korea's cultural properties for the purpose of governance. This process was conducted by Japanese officials and scholars, and systematized after making some changes. The Reservation Rule (1916) and the cultural properties designated in 1934 were actually the starting point for Korea's current cultural property policy. In the view of lineup of 'committee' that consider all of cultural property and changing of 'cultural property list', this study discusses the cultural property policy implemented by Joseon's Government-General, which can be summarized as follows. First, Joseon's Government-General formed a committee (Preservation Society) to formulate the cultural property policy, and had the policy implemented by appointing Governor officials who accounted for more than half the total number of officials of the institution. Although some Koreans were concerned about this, they had no influence on the matter. Second, the cultural properties listed by Joseon's Government-General are divided into three periods according to the lists. The compilation of the first list was led by Sekino Tadashi, who represented the grading system (1909~1916); while that of the second list (1917~1933) was led by Guroita Gatsumi, who represented listing (1917~1933). Guroita Gatsumi tried to erase Sekino Tadashi's list by formulating the cultural property policy and the list - a situation that was revealed in the system and the actual contents of the list. The third list was made as a list of designated cultural properties in 1934. This list also reflected the results of Sekino Tadashi investigation of the important cultural properties at existing temples that had been excluded from the previous regulations (1934~1945). In this way, a basic framework for the listing of Korean cultural properties was established in 1934.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.25-32
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• 2020

The seed, the most basic component, is an important factor in increasing production and efficiency in agriculture. Seeds with superior genes can be expected to improve agricultural productivity, crop survival, and reproduction. Currently, however, screening of superior seeds depends mostly on manual work, which requires a lot of time and manpower. In this paper, we propose a system that can extract the characteristics of seed phenotypes by using computer image processing technology, so that even a small number of people and a short period of time are needed to extract the characteristics of seeds. The proposed system detects individual seeds from images containing large quantities of seeds, and extracts and stores various characteristics such as representative colors, area, perimeter and roundness for each individual seed. Due to the regularity of input images, the accuracy of individual seed extraction in the proposed system is 99.12% for soybean seeds and 99.76% for rice seeds. The extracted data will be used as basic data for various data analyses that reflect the opinions of experts in the future, and will be used as basic data to determine the expressive nature of each seed.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Journal of Christian Education in Korea
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• v.68
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• pp.279-306
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• 2021

This paper intends to say that children's worship as a liturgy for children living in modern society is an important place to support children's personal development and experience of coziness necessary for their personal development. To this end, this thesis first regards modern society as an unstable society, analyzes fluid society and individualism as the causes, and deals with changes in educational style accordingly. In a fluid society, children are not provided with a solid form and lasting environment that supports personality development, and the education style changed under the influence of individualism and pluralism requires a heavy task of determining the direction of one's life and constantly making choices and decisions. Therefore, children need rules and forms that help them live together, and they need a space that can give them comfort that helps them develop their personality. As an argument for this, second, this paper deals with the concept and function of the liturgy in order to understand the worship of children as the liturgy. The third deals with the elements necessary for the development of children's personality that can be experienced in children's worship. First, it deals with the meaning of religious, aesthetic, and communal driving forces that children can experience in children's worship, focusing on Eberhard's research. In addition, it deals with the meaning of language and expression methods provided in children's worship, and finally, it says that children's worship can be a space where you can experience stability and coziness. Through this, it is emphasized that children's worship can play an important role in supporting the personal development of children living in modern times.

• The Journal of Bigdata
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• v.7 no.1
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• pp.213-224
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• 2022

In logistics and distribution, Market Basket Analysis (MBA) is used as an important means to analyze the correlation between major sales products and to increase internal operational efficiency. In particular, the results of market basket analysis are used as important reference data for decision-making processes such as product purchase prediction, product recommendation, and product display structure in stores. With the recent development of e-commerce, the number of items handled by a single distribution and logistics company has rapidly increased, And the existing analytical methods such as Apriori and FP-Growth have slowed down due to the exponential increase in the amount of calculation and applied to actual business. There is a limit to examining important association rules to overcome this limitation, In this study, at the Main-Category level, which is the highest classification system of products, the utility item set mining technique that can consider the sales volume of products together was used to first select a group of products mainly sold together. Then, at the sub-category level, the types of products sold together were identified using FP-Growth. By using this sequential layer filtering technique, it may be possible to reduce the unnecessary calculations and to find practically usable rules for enhancing the effectiveness and profitability.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.