• 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.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.95-103
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• 2024

The purpose of this study was to examine the perceptions and beliefs of physical education teachers regarding learner-centered physical education and to qualitatively explore the stories of physical education teachers that appear in the field of practicing physical education curriculum. The research method was qualitative research, and data were collected and recorded through semi-structured questionnaires, individual interviews, group interviews, and metaphor records, and the data were analyzed through domain analysis and classification analysis. The study was able to derive results by dividing them into 'learner focus', 'overall development', and learning evaluation' in relation to physical education teachers' meaning construction of learner-centered physical education. And the practice of learner-centered physical education and its limitations were presented. In conclusion, the holistic development of learner-centered physical education includes addressing physical, cognitive, social, and emotional aspects. It is believed that this approach will not only measure student progress but also actively contribute to their development as individuals.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.221-228
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• 2023

Physical and mental changes caused by emotions can affect various behaviors, such as driving or learning behavior. Therefore, recognizing these emotions is a very important task because it can be used in various industries, such as recognizing and controlling dangerous emotions while driving. In this paper, we attempted to solve the emotion recognition task by implementing a multimodal model that recognizes emotions using both audio and video data from different domains. After extracting voice from video data using RAVDESS data, features of voice data are extracted through a model using 2D-CNN. In addition, the video data features are extracted using a slowfast feature extractor. And the information contained in the audio and video data, which have different domains, are combined into one feature that contains all the information. Afterwards, emotion recognition is performed using the combined features. Lastly, we evaluate the conventional methods that how to combine results from models and how to vote two model's results and a method of unifying the domain through feature extraction, then combining the features and performing classification using a classifier.

• Management & Information Systems Review
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• v.39 no.1
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• pp.93-114
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• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.