• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.235-242
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• 2022

The purpose of this study is to propose an effective class of College English, one of the essential liberal arts subjects of S University, and to analyze the learning effect. This subject targets students with different majors in the first grade, and the learning goal is to improve their reading skills by analyzing students' English skills, especially sentences, as grammatical elements in everyday situations. This thesis examines how College English classes can be conducted in the form of convergence class in the COVID-19 era to induce students' learning motivation and create learning effects. The form of this convergence class is as follows. First, lecture videos, second, Webex real-time non-face-to-face classes, and third, face-to-face classes. In this study, the class procedure of the first class among the classes that were actually conducted during the semester was presented as an example. The researcher specifically surveyed the pre-class questionnaire and conducted the class by grasping the students' English skills and characteristics of the learners through the results. And after taking the course, the questionnaire was surveyed into 30 items and the results were analyzed. Specifically, the results of satisfaction with the composition of the lecture, satisfaction with the lecture video, satisfaction with the face-to-face class, interaction with students, and learning effects were analyzed. This class proposal is a learner-centered model in the form of convergence.

• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.41-58
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• 2022

This study aims to provide lesson plans that can simultaneously achieve both the learning goals of the 'Human Development & Family' domain of the 2015 revised Technology & Home Economics curriculum and the Sustainable Development Goals. Four steps including analysis, design, development, and evaluation and revision were followed. In the analysis step, the 'Changing Families and Healthy Families' unit was selected as it is relevant to the nine subgoals of the SDGs. In the design step, three sessions were planned with a problem-solving project approach. In the development step, three lesson plans for each session, individual and group activity worksheets for students, and guidelines for teachers were constructed. In the evaluation and revision step, criteria for evaluating the lesson plans were developed reflecting both the goals of the Home Economic curriculum and the SDGs. The validity of the lesson plans was reviewed by a panel of experts. Then, the revised lesson plans were finalized. This study provides an illustrative example of the lesson plans in the secondary education context that can be used to achieve the learning goals of the Home Economic curriculum and the Sustainable Development Goals at the same time.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.126-135
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• 2020

Recently, with the development of the 4th Industrial Revolution era and the popularization of technologies the maker movement is spreading worldwide in various ways for education, entrepreneurship, and solving social problems. This paper introduces a case of establishing and operating a maker space in Tanzania, East Africa, one of the developing countries. iTEC Tech-shop was established in the first half of 2018 at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania by Innovative Technology and Energy Center (iTEC), and has been operating for nearly two years. With the allocation of empty warehouse space from NM-AIST, physical facilities were established through the purchase and installation of equipment and hand tools. Based on the advice from Idea Factory of Seoul National University and Fab-Lab Seoul, iTEC Tech-shop operational system were established. Through a total of 7 technical workshops, iTEC Tech-shop provided training courses for about 180 local personnel. In addition, the smart Techshop test-bed project was promoted in order to improve the operation level along with securing sustainability of the Techshop. The case of the iTEC Tech-shop could be a useful case for institutions or organizations promoting the maker movement to developing countries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.538-544
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• 2021

Technology readiness assessment is a procedure for managing defense project risk factors based on the preemptive identification of technical risks. Under current regulations, technology readiness is determined based on considerations of the ratings of factors itemized on a checklist, whether unsatisfied factors have a fatal impact on the project, and whether countermeasures for unsatisfied factors have been established. However, objective criteria for assessing the impact of unsatisfied factors have not been presented, and thus, at present, the results of technology readiness level determinations are largely subjective. In addition, the importance of questions on the checklist is dependent on individual project characteristics and this is not considered during the assessment process. In this paper, we propose an improved technology readiness assessment procedure that considers the characteristics of each project. Using the proposed procedure, we quantitatively determined the importance of each checklist item using a weighting method. We found the devised procedure improved the reliability and objectivity of technology readiness assessment results. A case analysis of a complex weapons system is presented to demonstrate these improvements.

• Journal of Conservation Science
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• v.36 no.6
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• pp.511-518
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• 2020

There have been reports that the "jeongcho (定礎)" letters of the foundation stone at the historical site No. 280 of the "Main Building of the Bank of Korea in Seoul" were written by Prince Ito Hirobumi (伊藤博文), the first Resident-General of Japan in Korea. An on-site investigation by an advisory group consisting of three experts in calligraphy; revealed that the two characters of '定礎' inscribed on the foundation stone are the characteristics of Ito Hirobumi's handwriting, judging from the writing style and habits observed in the collections of the Central Library of Hamamatsu City, Japan. It was reported that his writing was confirmed by the experts, but no basis was provided. To provide more objective and quantitative supporting data, rather than qualitative judgment based on feeling, it is necessary to present the basis for judgment through quantitative image comparison results through image analysis. In this paper, using image analysis software, Ito Hirobumi's calligraphy writing and the inscribed characters of the foundation stone were compared and analyzed to confirm the contents of the press release. The character comparison process and character area measurement results are a good example showing that if objective judgment basis data are needed in a similar situation, an objective judgment basis can be prepared through quantification using image analysis.

• Journal of the Korean Society of Floral Art and Design
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• no.45
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• pp.31-46
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• 2021

With the advent of the post-COVID19 era, people must maintain social distancing to quarantine. However, this rule deprives people of freedom. Therefore, this study proposes a new normal plan for urban park design using drive-thru to recreate space for people to maintain and enjoy their previous lives while complying with quarantine rules. Olympic Park has a large floating population, and is one of the places where drive-thru is available. Therefore, the study designed this place to be the only cafe that could be operated if other cafes were shut down due to social distancing. The cafes in the park were designed into five spaces based on Olympic Park's flag motifs. The results were as follows. The cafe's name is CUPPY (Cup+Coffee), while each logo letter is expressed using the colors of the Olympic flag: blue, yellow, black, green, and red. The cafe spaces were divided into five continents (Europe, Asia, Africa, Oceania, and America), as symbolized by the Olympic flag, with the driving route shaped like the Olympic logo to match the five spaces. Human beings need change and adaptation in various fields to live in a post-COVID19 era that they have never experienced before. Just as the New Normal changes with time, and should, research is essential for presenting a New Normal in urban park design that reflects this disaster situation following the COVID-19 crisis. On this very point, we expect that this research will serve as a reference for urban park design. Additionally, it is believed that continuous suggestions and research will be necessary to apply the model to more diverse environments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1215-1225
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• 2021

Although Artificial Intelligence (AI) techniques have shown impressive performance in various fields, they are vulnerable to adversarial examples which induce misclassification by adding human-imperceptible perturbations to the input. Previous studies to defend the adversarial examples can be classified into three categories: (1) model retraining methods; (2) input transformation methods; and (3) adversarial examples detection methods. However, even though the defense methods against adversarial examples have constantly been proposed, there is no research to classify the type of adversarial attack. In this paper, we proposed an adversarial attack family classification method based on dimensionality reduction and clustering. Specifically, after extracting adversarial perturbation from adversarial example, we performed Linear Discriminant Analysis (LDA) to reduce the dimensionality of adversarial perturbation and performed K-means algorithm to classify the type of adversarial attack family. From the experimental results using MNIST dataset and CIFAR-10 dataset, we show that the proposed method can efficiently classify five tyeps of adversarial attack(FGSM, BIM, PGD, DeepFool, C&W). We also show that the proposed method provides good classification performance even in a situation where the legitimate input to the adversarial example is unknown.

• Journal of the Korean Chemical Society
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• v.67 no.1
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• pp.42-53
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• 2023

The purpose of this study is to obtain basic data for constructing a modeling practice program integrated with meta-modeling knowledge by analyzing the cognition level for each meta-modeling knowledge components through modeling practice in the context of the chemistry discipline content. A chemistry teacher conducted inquiry-based modeling practice including anomalous phenomena for 16 students in the second year of a science gifted school, and in order to analyze the cognition level for each of the three meta-modeling knowledge components such as model variability, model multiplicity, and modeling process, the inquiry notes recorded by the students and observation note recorded by the researcher were used for analysis. The recognition level was classified from 0 to 3 levels. As a result of the analysis, it was found that the cognition level of the modeling process was the highest and the cognition level of the multiplicity of the model was the lowest. The cause of the low recognitive level of model variability is closely related to students' perception of conceptual models as objective facts. The cause of the low cognitive level of model multiplicity has to do with the belief that there can only be one correct model for a given phenomenon. Students elaborated conceptual models using symbolic models such as chemical symbols, but lacked recognition of the importance of data interpretation affecting the entire modeling process. It is necessary to introduce preliminary activities that can explicitly guide the nature of the model, and guide the importance of data interpretation through specific examples. Training to consider and verify the acceptability of the proposed model from a different point of view than mine should be done through a modeling practice program.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.366-375
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• 2022

The monitoring of electricity consumption using Internet of Things (IoT) technology is attracting attention as a technology to reduce operation costs of smart farms. In this study, we propose a method to apply a real-time electrical consumption monitoring system (the e-Gauge system) and utilization of the collected data real-time while a melon-producing smart farm is in operation. For this purpose, the electrical consumption data for the individual smart-farm facilities such as boilers, nutrient distribution systems, automatic controllers, circulation fans, boiler controllers, and other IoT-related utilities were collected during three months of melon cultivation period. By using the monitoring results, the electrical energy consumption pattern was analyzed as an example, and necessary considerations needed to optimally utilize the measurement data were suggested. This paper will be useful in lowering the technological implementation barriers for new researchers to build a electrical consumption monitoring system and reducing trial and errors in the usage of the generated data.