Journal of The Korean Association For Science Education
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v.42
no.1
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pp.19-32
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2022
The need for polar education was further emphasized, depending on the importance of the pole, which is the best place for climate change detection and prediction, and treasure trove of future technology and resources. Therefore, this study analyzed the general cognitive and affective characteristics of elementary school students' polar literacy, and in addition, analyzed the cognitive and affective characteristics according to the level of diversity about polar experience. The items developed for the study were revised through a pilot survey of 43 fifth graders. They consisted of questions about gender, polar experience, scientific literacy, polar knowledge, polar literacy skills, polar literacy beliefs, and polar literacy attitudes. The types of questions used are selectable, reliable, and Likert (4 points), for a total of 66 questions. The students who participated in the study were 323 fifth grade elementary students. The study found that students were more interested in the dramatic consequences of polar changes than the scientific causes and processes associated with it. This is confirmed through the fact that they are more interested in and familiar with polar creatures suffering from polar changes than understanding ice, which is the main feature of and the central mechanism of polar changes. Students also recognized the issue of polar climate change as a global issue other than their own. They believe that what happens in the Arctic and Antarctica will affect the whole world, but not significantly to himself and his community. The level of knowledge about polar region and the ability to analyze and infer were not significantly related to each other, and students with a higher level of diversity of experience about polar region had a better understanding of polar science and technology. In this research, it is meaningful to check the characteristics related to the students' polar region and to use it as a basic data to show the direction in which polar literacy education should proceed in the future.
Journal of the Korean Institute of Traditional Landscape Architecture
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v.40
no.2
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pp.24-33
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2022
The travel notes and nature poems found in historic literary men's works can be considered historical records related to scenic sites. Such travel notes and nature poems are based on the writers' personal characters, experiences, learning and etc. Such works clearly show the characters of each literature, information of the related objects and the writers' thoughts of the objects. This study, thus, looked into Euisang on Xīsāishān Mountain that could be the origin of Eobusa(漁父詞) loved and sung by Korean historic literary men, and found that the Korean and Chinese literary men's thoughts were shown through their ways to enjoy Xīsāishān Mountain and their Euisang on the mountain, which was different between the Korean and Chinese literary men depending on the geographical locations described in their poems. In detail, the study results are: 1. Such difference of the ways to enjoy Xīsāishān Mountain, the scenic site described in historic Korean and Chinese literary men's work is broadly classified into the ways to enjoy the scenic site by seeing it in person and the ways to enjoy it under the mental structure of speculation. 2. Xīsāishān Mountain in Wuxing is the background of Yújiāzi(漁家子) of the painting Zhāngzhìhé, is boasting its distinguished beautiful nature, and is the place where the Confucian Study of Hú(湖學) was originated. It is also the place known of its warmhearted climate. Therefore, Euisang on Xīsāishān Mountain under such beautiful and warmhearted circumstance are realized as the complete freedom and seclusion in Taoism and the satisfaction with the given environment and position in Confucianism. 3. Xīsāishān Mountain in Wǔchāng is a military strategic point with rugged mountain terrain and scenery that has been a historic ferocious battlefield and related with the loyal civil servant Qū Yuán. The Euisang on Xīsāishān Mountain in Wǔchāng, therefore, represents the nature scenery of a rugged fortress and patriotism of Confucianism. 4. The Korean literary men's way to enjoy Xīsāishān Mountain is Shinyu(神遊: spiritual travel), so that their Euisang is formed according to the direction of the writer's values. Especially it is noted that Korean Euisang on Xīsāishān Mountain is originally based on the painting Zhāngzhìhé that shows the complete free mood of Taoism; and the Euisang on Xīsāishān Mountain that came from the mindful image by the poet monk Qíjǐ of Tang dynasty and Kim Si-seup appears with such Buddhist ways to seek the truth as SakGongIlYeo(色空一如: Being full is essentially as same as being vacant) and GyeonSeongSeongBul(見性成佛: Everybody can become Buddha by enlightenment).
High quality rapeseed cultivars including Nojeokchae, Yeongsanyuchae Halla-yuchae and Tamrayuchae have been released and recommended as a zero erucic acid variety to Cheju farmers for 13 years, where is a major rapeseed production area in korea. However, rapeseeds produced in Cheju island in 1992 and 1993 contained 47.7% and 37.0% of erucic acid respectively resulting in poor quality oil being not adequate for edible oil. It was considered that the zero erucic acid varieties did not have an opportunity to be cultivated in Cheju island by farmers living in the Island. Thus, the new rapeseed varieties without erucic acid should be bred and recommended to the farmers of southern area of Korea as a multiple cropping crop just after rice harvest, and for large scale mechanized and labour-serving rapeseed culture. The change of rapeseed breeding goal would be desirable for fatty acid composition improvement of rapeseed to develop varieties adaptable to southern part of Korea, and to produce rapeseed oil directly used as an edible oil safely.
COVID-19, which started in Wuhan, China in November 2019, spread beyond China in 2020 and spread worldwide in March 2020. It is important to prevent a highly contagious virus like COVID-19 in advance and to actively treat it when confirmed, but it is more important to identify the confirmed fact quickly and prevent its spread since it is a virus that spreads quickly. However, PCR test to check for infection is costly and time consuming, and self-kit test is also easy to access, but the cost of the kit is not easy to receive every time. Therefore, if it is possible to determine whether or not a person is positive for COVID-19 based on the sound of a cough so that anyone can use it easily, anyone can easily check whether or not they are confirmed at anytime, anywhere, and it can have great economic advantages. In this study, an experiment was conducted on a method to identify whether or not COVID-19 was confirmed based on a cough sound. Cough sound features were extracted through MFCC, Mel-Spectrogram, and spectral contrast. For the quality of cough sound, noisy data was deleted through SNR, and only the cough sound was extracted from the voice file through chunk. Since the objective is COVID-19 positive and negative classification, learning was performed through XGBoost, LightGBM, and FCNN algorithms, which are often used for classification, and the results were compared. Additionally, we conducted a comparative experiment on the performance of the model using multidimensional vectors obtained by converting cough sounds into both images and vectors. The experimental results showed that the LightGBM model utilizing features obtained by converting basic information about health status and cough sounds into multidimensional vectors through MFCC, Mel-Spectogram, Spectral contrast, and Spectrogram achieved the highest accuracy of 0.74.
In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.
Journal of Korea Entertainment Industry Association
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v.13
no.2
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pp.27-36
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2019
Today, the Korean wave headed by K-pop is newly named as 'New Korean Wave' in that it has been extended to United States, Europe and Russia. K-POP, the main player of the new Korean wave, has been successful in SNS marketing channels. Furthermore, the content of K-pop has attracted the attention of the global audience. The media and public attention on the Korean Wave is meaningful because it is not merely a cultural export. It also makes Korean people feel national pride, seeing the mental influence of its culture on other regions. Moreover, the development of the cultural industry in our society, which is different from industrial or material development, is a proof that Korean society is at the center of globalization. Until the 20th century, Korean culture had been rather receptive than dominant. In other words, it was focused more on acceptance of other cultures than active creation or outflow of its own. Now, however, K-POP is not anymore copying Western culture. It is creating its own unique characters, which makes K-pop very competitive. Korean culture has been formed for a long time in Korea's unique historical background. Korean popular culture also has to establish a solid foothold in world markets through its distinctive and traditional feature. The positive consumer response to Korean pop culture will create the added value of Korean contents and their derivatives, which will heighten Korea's national image also. In other words, if traditional art and K-POP are converged and equipped with our own unique and highly artistic culture, they will take the lead in the global cultural art market. In this study, we will recognize the possibility, growth and development of K-pop culture and analyze the cases of combining K-pop and Korean traditional art. First, we have to blend traditional art and other various genres to create diverse contents, and we have to actively utilize media channels. Second, we must improve people's awareness of the copyrights of traditional art. Also, we have to mitigate the copyrights of creative dance to expand the disclosure of contents which can be utilized. Third, we have to learn about traditional arts from younger age. Fourth, we will expand traditional arts to the whole of Korean cultural policies, which can enhance the nation's cultural value and create economic benefits. These four are expected to be effective ways to preserve the identity of traditional art and at the same time, globalize Korean culture.
The purpose of this study was to verify the effects of growth orientation, life satisfaction, perceived stress, positive psychological capital and interpersonal relationships in the group coaching program for the promotion of growth orientation for university students based on the model of the social-cognitive approach to motivation. The program consisted of eight topics: growth orientation, growth mindset and brain plasticity, self-directed goal setting, talent which is a product of ongoing effort, failure attitude and perspective change, positive emotion, thinking and behavior, value of growth orientation and self-coaching, respectively. The program comprised a total of eight sessions, 120 minutes each, and the final program was completed through a preliminary experiment with three university students. In order to verify the effectiveness of the program, 48 university students were divided into 16 in the experimental group, 16 in the comparative group, and 16 in the control group. The experimental group participated in the group coaching program to enhance the growth orientation based on the model of the social-cognitive approach to motivation developed in this study, the comparative group participated in a learning goal orientation improvement program based on an incremental implicit theory, and the control group did not carry out any program. Three groups were tested in pre, post, follow-up1(after 1 month) and follow-up2(after 3 months) in order to growth orientation, life satisfaction, perceived stress, positive psychological capital and interpersonal relationships. We performed analysis to confirm the homogeneity to the data of the three groups and to verify the interaction effects between times and groups. As a result, it was confirmed that the group coaching program to promote growth orientation, life satisfaction, perceived stress, positive psychological capital and interpersonal relationships had statistically significant effect and was more effective than the comparative program due to the larger effective size. Also, we confirmed that the coaching effect was sustained after the program was finished and more effectively maintained than the comparative program. Based on the results of this study, this study has academic implications because it verify the effectiveness of the group coaching for the promotion of the growth orientation by scient ic method.
As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.
Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.
This study was conducted to collect and analyze previous information in order to manage efficience, improve experience effect and promote employment rate. The questionnaire interview with 27 chief of dental Laboratory refered clinical experience in technology department about clinical experience in 14 Jumior colleges were also investigated. The results were summarried as follows : The portion of age of 35-39 among chief of dental Laboratory was 40.7% which was the highest, that of male was 96.3%, that of junior college graduate was 97.5%, that of 10years experience was 92.6% and that of ceramic technician was 85.2%, 63.0% dental laboratory for clinical experience was a bore space of 30pyong. Aspect of dental laboratory management, manufacturing all part of prosthetic restoration was 29.6%, othodontic appliance and ceramic restoration was 7.4%, 3.8%, each. The percentage of 40.7 was having connection with 30-3a dental clinics and referring case per day was 10-19 cases(40.7%), manufacturing time of referred prosthetic restoration was 3-4 days(77.8%), places preparing seminar room for education was 29.6%, above a place of 40pyong was 11.1% 30-34 pyong and 35-39 pyong was 7.4% each. During training of 2 years education course student, 18.5% was rack of thorough occupational career. While 44.4% will want the more salary among 3years education course student, 74.1% will expect the more dental techmicians would engaged in their field, 51.9% will hope improve of their theory and practice, 29.6% be expected better skill and 14.8% be expected better theory. Attitude of clinical experience places was distributed by 59.3% of offering only experience chance, 25.9% of wasting time and 29.0% of annoying. The big emphasis of climical experience was thorough occupational career(44.4%). The clinical experience places of our college were selected after direct visiting, so their condition of management was not that bad but most of dental laboratory were poor in management state and working environment. Therefore it is difficult to choose appropriate places and dental Laboratory are also limited manpower and time as suppliers. So that it recommended to induce flexible management of experience period by interval and rotation of experience places among college and to applicate intern-system for employment ant industry-college cooperation aspect.
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