• Plant Breeding and Biotechnology
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• v.5 no.2
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• pp.123-133
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• 2017

AP2/EREBP gene family consists of transcription factor genes with a conserved AP2 DNA-binding domain and is involved in various biological processes. AP2/EREBP gene families were identified through genome-wide searches in five Cucurbitaceae species including cucumber, wild cucumber, melon, watermelon, and bitter gourd, which consisted of more than 100 genes in each of the five species. The gene families were further divided into five groups including four subfamilies (ERF, DREB, AP2 and RAV) and a soloist group. Among the subfamilies, DREB subfamily which is known to be related to abiotic stress response was more analyzed and a total of 25 genes were identified as Cucurbitaceae homologues of Arabidopsis CBF/DREB1 genes which are important for abiotic stress-response and tolerance. In silico expression profiling using RNA-Seq data revealed diverse expression patterns of cucumber AP2/EREBP genes. AP2/EREBP gene families identified in this study will be valuable for understanding the stress response mechanism as well as facilitating molecular breeding in Cucurbitaceae crops.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.223-246
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• 2019

This research makes the metadata element design for Korean medicine research data management and re-use. Derived metadata elements are verified in research data of Korea Institute of Oriental Medicine. TTAK.K0-10.0976 Standard, DataCite metadata Schema and National Research Data Platform of KISTI were analyzed to derive the metadata elements. Including Identifier, 27 elements were derived as top-level elements with 29 mandatory elements, 13 recommended elements and 31 optional elements. The degree of elements' necessity and new metadata elements were investigated and suggested in the survey by six domain experts in korean medicine field. In this study subject classification for the korean medicine research data are suggested. The final version of metadata schema was tested and verified by comparing with the legacy metadata fields. The research results can be used to describe the Korean medicine research data: items and files.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.74-85
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• 2021

Global Navigation Satellite System (GNSS) receivers are intrinsically vulnerable to radio frequency jamming signals due to the fundamental property of radio navigation systems. A GNSS jamming monitoring system that is capable of jamming detection, classification and localization is essential for infrastructure for autonomous driving systems. For these 3 functionalities, a GNSS jamming monitoring network consisting of a multiple of low-cost GNSS receivers distributed in a certain area is needed, and the precise time synchronizaion between multiple independent GNSS receivers in the network is an essential element. This paper presents a precise time synchronization method based on the direct use of Time Difference of Arrival (TDOA) technique in signal domain. A block interpolation method is additionally incorporated into the method in order to maintain the precision of time synchronization even with the relatively low sampling rate of the received signals for computational efficiency. The feasibility of the proposed approach is verified in the numerical simualtions.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.319-328
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• 2021

Parallel administration of numerous drugs increases Drug-Drug Interaction (DDI) because one drug might affect the activity of other drugs. DDI causes negative or positive impacts on therapeutic output. So there is a need to discover DDI to enhance the safety of consuming drugs. Though there are several DDI system exist to predict an interaction but nowadays it becomes impossible to maintain with a large number of biomedical texts which is getting increased rapidly. Mostly the existing DDI system address classification issues, and especially rely on handcrafted features, and some features which are based on particular domain tools. The objective of this paper to predict DDI in a way to avoid adverse effects caused by the consumed drugs, to predict similarities among the drug, Drug pair similarity calculation is performed. The best optimal weight is obtained with the support of KHA. LSTM function with weight obtained from KHA and makes bets prediction of DDI. Our methodology depends on (LSTM-KHA) for the detection of DDI. Similarities among the drugs are measured with the help of drug pair similarity calculation. KHA is used to find the best optimal weight which is used by LSTM to predict DDI. The experimental result was conducted on three kinds of dataset DS1 (CYP), DS2 (NCYP), and DS3 taken from the DrugBank database. To evaluate the performance of proposed work in terms of performance metrics like accuracy, recall, precision, F-measures, AUPR, AUC, and AUROC. Experimental results express that the proposed method outperforms other existing methods for predicting DDI. LSTMKHA produces reasonable performance metrics when compared to the existing DDI prediction model.

• Journal of Korean Biological Nursing Science
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• v.23 no.4
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• pp.257-266
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• 2021

Purpose: The purpose of this study was to analyze the content of nursing interventions applied to patients with thoracic injury who visited a trauma emergency room (TER) or an emergency room (ER). Methods: Of 3,938 trauma patients admitted to this hospital between January 1, 2019 and December 31, 2020, 320 adult patients with thoracic injury (94 to TER, 226 to ER) who met the inclusion criteria were enrolled. Patients' data were acquired from their electronic medical records. General and clinical characteristics of these subjects along with nursing interventions were analyzed. Results: There were statistically significant differences in the length of stay, treatment outcome, and level of consciousness between thoracic injury patients who visited TER and ER. Average thoracic Abbreviated Injury Scale score and average Injury Severity Score of thoracic injury patients who visited TER were 3.13 and 13.54, respectively, which were significantly higher than those of patients who visited ER. The numbers of nursing actions applied was 4,819 for TER and 3,944 for ER, which were classified into five domains, 18 classes, and 56 interventions. The most domain of interventions carried out in both TER and ER was physiological: complex. Classes including Crisis management and Thermoregulation were not carried out in ER. On average, 16 more types of interventions were carried out in TER than in ER. Conclusion: This study demonstrated characteristics of thoracic injury patients and nursing interventions by emergency room type. Based on results of this study, standardized nursing interventions need be applied to thoracic injury patients visiting TER and ER.

• Journal of Korea Game Society
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• v.21 no.6
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• pp.31-40
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• 2021

Go has a history of more than 2,500 years, and the life-and-death problems in Go is a fundamental problem domain that must be solved when implementing a computer Go. We attempted to determine the numbers of prototypical eye shapes with 3, 4, 5, and 6 eyes that are directly related to the life-and-death problems, and to classify the prototypical eye shapes represented in 4-tuple forms. Experiment was conducted by Monte-Carlo method and point pattern matching. According to the experimental results, the numbers of prototypical eye shapes were 2 for 3-eye, 5 for 4-eye, 12 for 5-eye, and 35 for 6-eye shapes. Further, using a 4-tuple form, we classified prototypical eye shapes into 1 for 3-eye, 3 for 4-eye, 4 for 5-eye, and 8 for 6-eye shapes.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.1-8
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• 2022

This work provides a reliable and classified stocks dataset merged with Saudi stock news. This dataset allows researchers to analyze and better understand the realities, impacts, and relationships between stock news and stock fluctuations. The data were collected from the Saudi stock market via the Corporate News (CN) and Historical Data Stocks (HDS) datasets. As their names suggest, CN contains news, and HDS provides information concerning how stock values change over time. Both datasets cover the period from 2011 to 2019, have 30,098 rows, and have 16 variables-four of which they share and 12 of which differ. Therefore, the combined dataset presented here includes 30,098 published news pieces and information about stock fluctuations across nine years. Stock news polarity has been interpreted in various ways by native Arabic speakers associated with the stock domain. Therefore, this polarity was categorized manually based on Arabic semantics. As the Saudi stock market massively contributes to the international economy, this dataset is essential for stock investors and analyzers. The dataset has been prepared for educational and scientific purposes, motivated by the scarcity of data describing the impact of Saudi stock news on stock activities. It will, therefore, be useful across many sectors, including stock market analytics, data mining, statistics, machine learning, and deep learning. The data evaluation is applied by testing the data distribution of the categories and the sentiment prediction-the data distribution over classes and sentiment prediction accuracy. The results show that the data distribution of the polarity over sectors is considered a balanced distribution. The NB model is developed to evaluate the data quality based on sentiment classification, proving the data reliability by achieving 68% accuracy. So, the data evaluation results ensure dataset reliability, readiness, and high quality for any usage.

• Journal of People, Plants, and Environment
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• v.24 no.5
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• pp.485-498
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• 2021

Background and objective: This study was conducted to find out the status of plant utilization in the current textbooks by analyzing the plants by grade and subject in the national textbooks for all elementary school grades in the 2015 revised curriculum in Korea. Methods: The data collected was analyzed using Microsoft Office Excel to obtain the frequency and ratio of collected plant data and SPSS for Windows 26.0 to determine learning content areas by grade and the R program was used to visualize the learning content areas. Results: A total of 232 species of plants were presented 1,047 times in the national textbooks. Based on an analysis of the plants presented by grade, the species that continued to increase in the lower grades tended to decrease in the fifth and sixth grades, the upper grades of elementary school. As for the number and frequency of plant species by subject, Korean Language had the highest number and frequency of plant species. The types of presentation of plants in textbooks were mainly text, followed by illustrations and photos of plants, which were largely used in first grade textbooks. In addition, as for the area of learning contents in which plants are used, in the lower grades, plants were used in the linguistic domain, and in the upper grades, in the botanical and environmental domains of the natural sciences. Herbaceous plants were presented more than woody plants, and according to an analysis of the plants based on the classification of crops, horticultural crops were presented the most, followed by food crops. Out of horticultural crops, flowering plants were found the most diversity with 63 species, but the plants that appeared most frequently were fruit trees that are commonly encountered in real life. Conclusion: As a result of this study, various plant species were included in elementary school textbooks, but most of them were horticultural crops encountered in real life depending on their use. Nevertheless, plant species with high frequency have continued a similar trend of frequency from the previous curriculums. Therefore, in the next curriculum, plant learning materials should be reflected according to social changes and students' preference for plants.

• Journal of Daesoon Thought and the Religions of East Asia
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• v.2 no.2
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• pp.73-99
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• 2023

The dragon is a special imaginary figure created by the people of East Asia. Its archetypes appeared primarily as totemic symbols of different tribes and groups in the region. The formation of early dynasties probably generated the molding of the dragon symbol. Dragon symbols carried deep imprints of nature. They concealed alternative messages of how ancient people at different locations dealt with or interacted with nature. Under pressure to standardize in the medieval and late imperial periods, the popular dragon had to transform physically and ideologically. It became imposed, unified, and framed, conveying ideas of caste classification and power, and losing itsecological implications. The dragon transitioned from a semi-ecological domain into a total social caste system. However, many people considered the "standardized" dragon as the symbol of the oppressor. Because of continuous orthopraxy and calls for imperial reverence, especially under orthopractic agenda and the surveillance of local elites, the popularized dragon was imbued within local artworks or hidden under the sanctity of Buddhas or popular gods in order to survive. Through disguise, the popular dragon partially maintained its ecological narratives. When the imperial dynasties ended in East Asia (1910 in Korea, 1911 in China, 1945 in Vietnam), the dragon was dramatically decentralized. However, trends of re-standardization and re-centralization have emerged recently in China, as the country rises in the global arena. In this newly-emerging "re-orthopraxy", the dragon has been superimposed with a more externally political discourse ("soft power" in international relations) rather than the old-style standardization for internal centralization in the late imperial period. In the contemporary world, science and technology have advanced humanity's ability to improve the world; however, it seems that people have abused science and technology to control nature, consequently damaging the environment (pollution, global warming, etc.). The dragon symbol needs to be re-defined, "re-molded", re-evaluated and reinterpreted accordingly, especially under the newly-emerging lens-the New Confucian "anthropocosmic" view.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.182-196
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• 2024

This study introduces driving pattern analysis and change detection methods using smartphone sensors, based on contrastive learning. These methods characterize driving patterns without labeled data, allowing accurate classification with minimal labeling. In addition, they are robust to domain changes, such as different vehicle types. The study also examined the applicability of these methods to smartphones by comparing them with six lightweight deep-learning models. This comparison supported the development of smartphone-based driving pattern analysis and assistance systems, utilizing smartphone sensors and contrastive learning to enhance driving safety and efficiency while reducing the need for extensive labeled data. This research offers a promising avenue for addressing contemporary transportation challenges and advancing intelligent transportation systems.