• Journal of Science Education
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• v.32 no.2
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• pp.71-86
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• 2008

The purpose of this study was to apply After-school programs related to sub-chapter 'The Change of Weather', and thereby to investigate the effect of After-school program on science-related attitude and learning achievement of students, and interaction between treatment methods and students' learning ability. The subjects of study consisted of 2nd grade students of sixty four students in high school. Sixty four students were divided into two categories by experimental and control groups on the basis of midterm examination before teaching treatment. The experimental groups have received four After-school programs including making models of a weather front, measurement of wind, measurement of temperature and the dew point, making a three-dimensional weather chart which were developed by researcher for six times. The control groups have received the instruction through the conventional teaching methods. Seventy questions within seven frameworks of TOSRA have been used in this study as an evaluation instrument of science-related attitude. Learning achievement has been evaluated using an instrument developed by researcher. The scores of both pre-test and post-test were estimated by ANCOVA. The results of this study can be summarized as follows. (1) After-school programs were more effective in progressing the three categories of science related attitude of high school students i.e. pleasure of science class(p<.05), reception of scientific attitude(p<.01), attitude about a science research(p<.05) than conventional teaching methods. (2) Experimental groups showed statistically significant improvement on learning achievement than control groups(p<.05). (3) The effect of treatment methods on students' learning ability has been improved in experimental groups more positively than control groups(p<.05). High level students in experimental groups showed significant improvement on learning achievement than low level students according to the representing profile plot. But there were no significant interaction between treatment methods and students' learning ability(p>.05) In conclusion, the After-school programs have positive effect on the improvement of science related attitude and learning achievement.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.3
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• pp.48-57
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• 2018

In this study, we conducted an analysis on the actual field materials and the ancient text of January 2017. First, Yuyin ShanFang is one of the famous garden in the Lingnan Region, and its total area is $1598m^2$. Wobin called the name 'Yuyin(餘蔭)' meaning the virtues of his ancestors. Second, if we analyze the poem written by Wobin, we can classify it as a phrase expressing the world beyond the future, a poem expressing the ideas of family and romantic ideas. Third, the space spread to the south around the shrine building in the middle of the site was largely a residential space, according to the analysis of the site's layout and spatial composition. Fourth, the spatial component of the hydronic acid is analyzed. The pavilion area is the Hanchwi-Pavilion, which is designated in the Wongrim, and Gyesang-Pavilion, which is a unique range that describes the peak of the garden. Fifth, Yuyin ShanFang has five ponds that are very diverse in shape. It is characteristic of us to stand on a technical boundary. Sixth, Seokgasan was referred to as Gyeongbansan, which was named after The builder Wobin and his descendants who passed it. Seventh, Hwachang is characterized by a wooden bull window and a compound glass. Eighth, the alumni style is not as diverse as the alumni style of the Suzhou traditional garden, but it features various forms and colorful pictures on the front of the alumni. Ninth, the one-piece sculptures of the interior of a building are expressed themes such as Gilsang, Sukjeong, Daoism, Palseom, and others. Finally, Trees planted in Yuyin ShanFang are mostly tropical plants, and some of them have symbolic meaning. Because the weather here is good for growing fruit, so planted a lot of fruit trees.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.218-222
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• 2006

In making 3D animation with digital technology, it is necessary to increase productivity and reusability by managing production pipeline systematically through standardization of animation content. For this purpose, we try to develop the animation content management system that can manage all kind of information on the production pipeline, based on SCORM of e-teaming by considering production, publication and re-editing. A scene as the unit of visual semantics is standardize into an object that contains meta-data of place, cast, weather, season, time and viewpoint about the scene. The meta-data of content includes a lot of information of copyright, publication, description, etc, so that it plays an important role on the management and the publication. If an effective management system of meta-data such as ontology will be implemented, it is possible to search multimedia contents powerfully. Hence, it will bring on production and publication of UCC. Using the meta-data of content object, user and producer can easily search and reuse the contents. Hence, they can choose the contents object according to their preference and reproduce their own creative animation by reorganizing and packaging the selected objects.

• Journal of the Korean earth science society
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• v.26 no.5
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• pp.417-428
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• 2005

The seasonal variation and frequency of precipitation phenomenon of the Korean Peninsula in summer show strong local weather phenomena because of its topographical and geographical factors in the northeastern area of Asia. The characteristics of the prevailing weather patterns in summer precipitation in Korea have great influences on the variation patterns and the appearances over a ten-day period during the summer precipitation. The purpose of this paper is to induce variation patterns over a period 10 days during the summer precipitation, clarify the variations of their space scales, and study the subdivision of precipitation regions in Korea according to the combinations of precipitation amounts and variation pattern during the period, using the mean values during the years $1991\~2003$ at 78 stations in Korea. The classified precipitation of a period of 10 days of summer precipitation, and the principal component vector and the amplitude coefficient by the principal component analysis were used for this study. The characteristics of variation pattern over the ten-day period can be chiefly divided into two categories and the accumulated contributory rate of these is $64.3\%$. The variation patterns of summer precipitation during period of 10 days in Korea are classified into 9 types from A to K. In addition, regional divisions of summer precipitation in Korea can be classified into 17 types.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.111-117
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• 2017

The purpose of forecasting the traffic accident is to reduce the traffic accident. Therefore, the goal of this study is to provide severity of the accident by Forecasting of Probability of Accident. In Korea, accident data are distributed to the public via internet that includes numbers of accident and fatality as well. And crude level of accident severity in accordance with weather information for metropolitan city level are available by weekly. However, It can not reflect personal needs at specific origin of the travel for a certain traveller. This study aims to consider 68 major intersections with precipitation data, and eventually introduces link based accident severity. In estimating the accident severity both dynamic data such as drivers' characteristics, driving conditions and static data such as geometry of road, intersection characteristics are considered. Also, we identifies accident severity according to the accident type - 'vehicle to vehicle,' 'vehicle to person.' Finally, the outcomes of this study suggests taylor-made accident severity information for a specific traveller for a certain route.

• Korean Journal of Environment and Ecology
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• v.34 no.5
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• pp.446-453
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• 2020

This study built a model to predict the daily number of visitors to 18 trails in the Taebaeksan National Park using the auto-counter system data to analyze the factors affecting the daily number of visitors to each trail and classified the trails by visitors' behaviors. Results of the multiple regression models with the daily number of visitors of the 18 trails indicated that the events, such as the National Foundation Day celebration of Snow Festival, affected the number of visitors of all of the 18 trails and were the most critical factor that determined the daily number of visitors to the Taebaeksan National Park. The long-holidays of three days or longer and other national holidays also affected the daily number of visitors to the trails. Precipitation had a negative impact on the number of visitors of trails where the intention of most visitors was for sightseeing or camping instead of hiking, whereas had no significant impacts on the number of visitors of trails where many visitors intended for hiking. It indicated that visitors who intended for hiking went ahead hiking even if the weather was poor. The effects of temperature had a positive effect on the number of visitors who intended for hiking but a negative effect on the number of visitor to the trails near Danggol Plaza where the Snow Festival was held in each winter, suggesting that the impact of the Snow Festival was the deterministic factor for trail management. Results of K-mean clustering showed that the 18 trails of the Taekbaeksan National Park could be classified into three types: those affected by the Snow Festival (type 1), those that have sightseeing points and so were visited mostly by non-hikers (type 2), and those visited mostly by hikers (type 3). Since visitor behaviors and illegal actions differ according to the trail type, this study's results can be used to prepare a trail management plan based on the trail characteristics.

• Journal of the korean veterinary medical association
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• v.44 no.9
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• pp.803-818
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• 2008

동물의 결핵은 Mycobacterium bovis의 감염에 의한 만성 소모성 질병이며 인수공통전염병이다. 동물로부터 사람으로의 결핵 전염은 생유 섭취하던 시대에 상당히 많이 보고되었다. 우유의 살균처리와 소에서 피내진단에 의한 양성우 살처분 및 보상금 지급 정책을 전개하면서 M. bovis의 사람전염은 급격히 감소하였다. 소 결핵은 우리나라에서 연간 0.15% 내외의 발생을 보이고 있으며, 발생의 주원인으로는 외부입식소, 인근발생농장, 과거발생농장의 사후관리소홀 등이다. 사람 결핵의 주원인균인 M. tuberculosis와 M. bovis는 유전체가 99.9% 유사하며, M. bovis를 M. tuberculosis의 아종으로 분류하기도 한다. 두 세균은 M. tuberculosis complex에 속하며, M. tuberculosis와 M. bovis이외에도 M. africanum, M. canettii, M. microti, M. pinnipedii 등이 있다. M. bovis는 M. tuberculosis complex중에서 가장 넓은 숙주범위를 가진다. M. bovis의 대표적인 숙주는 종이름에도 나타나 있듯이 소이다. 소결핵 전파원으로서는 M. bovis에 감염된 소가 가장 중요하다. 소 이외에도 면양, 산양, 말, 돼지, 사슴, 엘크, 영양 (antelope, kudus, elands, sitatungas, oryxes, addaxes), 개, 고양이, 흰족제비 (ferrets), 낙타, 여우, 밍크, 오소리, 쥐, 영장류, 라마, 맥 (tapirs), 코끼리, 코뿔소 (rhinoceroses), 주머니쥐, 땅다람쥐 (ground squirrels), 수달 (otters), 물개, 산토끼 (hares), 두더쥐 (moles), 너구리 (raccoons), 코요테, 사자, 호랑이, 표범, 살쾡이 (lynx) 등에 감염될 수 있으나, 대부분 종결숙주 (spillover host)로 가축의 결핵방제가 유지되고 있는 국가에서는 야생동물 결핵의 가축 전염이 문제시되고 있다. M. bovis는 주로 호흡기와 소화기를 통하여 감염되며, 결핵결절이 형성되는 부위를 관찰하면 감염경로를 추정할 수 있다. 결핵에 감염되면, 초기에는 뚜렷한 임상증상을 보이지 않으나, 아침, 추운 날씨, 또는 운동 중에 심한 기침을 하며, 호흡곤란을 일으킬 수 있다. 결핵은 감염되어도 대부분 무증상이기 때문에 피내진단, 결핵결절 병리소견, 원인균 분리 등에 의해 진단하여야 한다. 감염된 결핵균은 탐식세포에 탐식되어 특징적인 육아종성 결절 병변으로 진행된다. 현재 결핵은 피내진단과 결핵결절 병리소견 등에 의해 판정하고 있다. 최신 진단법으로는 피내진단을 대체할 수 있는 인터페론 감마 검사법과 우군의 결핵 스크리닝과 말기 결핵 검사에 우수한 항체진단법이 개발되어 있다. 그러나, 소 결핵 근절을 위해서는 일관성있는 진단법과 진단기준을 적용하는 것이 중요한 성공요인중 하나이다. 소결핵 청정국인 호주와 캐나다에서는 피내진단과 도축장 결절검사를 결핵 양성우 색출방법의 근간으로 삼고 있으며, 소결핵 근절의 최종단계에 이르러서는 특이적인 검사법을 적용하였지만, 근절목적상 민감성이 높은 피내진단법을 사용하였다. 이와 더불어, 피내진단 양성우의 부검소견과 원인균 분리를 통해 결핵을 확진하여 출처농장의 역추적 검사를 통하여 결핵 양성소를 제거하였다. 한편, 결핵의 농장간 및 지역간 전파방지를 위해 결핵 청정농장과 결핵 오염농장, 결핵 청정지역과 결핵 오염지역 구분을 통하여 결핵 오염농장과 결핵 오염지역으로부터 결핵 청정농장과 결핵 청정지역으로의 이동전 결핵 검진을 통해 개체 이동에 따른 결핵 전파를 근본적으로 차단하는 시스템을 엄격히 적용한 것이 주요한 성공 요인중 하나였다. 호주 결핵 근절정책 성공요인을 요약하면, 일관성 있는 결핵진단법 적용, 양성우 출처농장의 철저한 역추적 검사, 개체 이동전 결핵 음성증명 확인, 농가단체의 경제적 및 방역상 적극적인 지원 및 협조 결핵의 지속적인 모니터 링과 현장요구에 부응하는 방제신기술의 지속적인 연구개발 등을 들 수 있다. 최근 들어 국내 동물 결핵은 소, 특히, 한우의 결핵발생이 증가하고 있으며, 사슴 결핵발생도 증가하고 있다. 농장간 및 지역간에 결핵 감수성 가축, 특히, 소와 사슴의 거래가 아주 복잡하게 이루어지고 있는 현실을 고려할 때, 결핵전파의 주원인인 결핵감염 소나 사슴의 농장내 반입을 철저히 차단해야 할 것이다. 이때, 개체 검사는 물론이고, 출처농장에 대한 결핵 음성을 확인한 후 입식하여야 할 것이며, 입식 후에도 60일정도 격리사육하면서 피내진단등 결핵검진 후 음성인 경우에만 합사하여야 할 것이다. M. bovis는 사람을 비롯한 거의 모든 온혈동물에서 결핵을 일으킬 수 있기 때문에, 결핵 감염소로 판정된 농장 종사자는 각 시도 보건소의 협조를 받아 결핵검진을 받도록 해야 한다. 농장 가축에 접촉할 수 있는 야생동물의 접촉을 차단하여야 하며, 특히, 농장 사료의 야생동물에 의한 오염을 방지할 수 있는 사료창고관리를 철저히 해야 한다. 결핵 감염소를 다룰 때는 분비물 또는 가검물에 의해 감염될 수 있기 때문에 개인방역장비 - 방역복, 마스크, 비닐장갑, 비닐장화 - 를 착용한 상태에서 다루어야 한다. 특히, 결핵 감염소를 매몰 또는 소각하는 과정에서 결핵 감염소의 배설물 및 분비물 처리를 철저히 하여야 한다. 모든 작업을 마친 후에는 개인방역장비, 매몰 또는 소각에 사용하였던 장비 등을 청소 및 소독하고 필요시 소각 또는 매몰하여야 하며, 개인감염위험과 타인 감염위험을 방지하기 위해 노출부위를 세척하여야 한다.

• Journal of Science Education
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• v.42 no.2
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• pp.256-271
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• 2018

The study aimed to investigate how the science gifted connect and integrate science concepts in the process of problem finding. Research subject was sampled from 228 applicants for a science gifted education center affiliated with a university in 2015. A creative problem solving test (CPST) in science, which administered as an admission process, was utilized as a reference to sample two groups. Sixty-seven students from top 30% in test scores were selected for the upper group and 64 students from bottom 30% in test scores were selected for the lower group. The CPST, which was developed by researchers, included one item about how to connect two science concepts among eight science concepts, sound, electricity, weight, temperature, respiration, photosynthesis, weather, and earthquake extracted from elementary science curriculum. As results, there were differences in choosing two concepts among four science major areas. The ways of connecting science concepts were characterized by three categories, relation-based, similarity-based, and dissimilarity-based. In addition, relation-based was characterized by attributes, means, influences, predictions, and causes; similarity-based was by attributes, objects, scientific principles, and phenomena, and dissimilarity-based was by parallel, resource, and deletion. There were significant (p<.000) differences in ways of connecting science concepts between the upper and the lower groups. The upper group students preferred connecting science concepts of inter-science subjects while the lower group students preferred connecting science concepts of intra-science subject. The upper group students showed a tendency to connect the science concepts based on similarity. In contrast, the lower group students frequently showed ways of connecting the science concepts based on dissimilarity. In particular, they simply parallelled science concepts.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.