• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.249-261
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• 2019

The purpose of this study is to extract empathy factor in scientists' problem-solving process and to examine how the empathy factor influences scientists' problem-solving situation. In this study, we selected six common persons among the scientists mentioned by creativity researchers. And through their autobiographies and biographies, we extracted elements of empathy from their case of problem-solving and categorized them. We analyzed cases from 12 books and 50 papers using Davis' empathy scale as an analysis framework and extracted common factors. As a result, the scientific empathy elements were extracted from a total of 182 cases, and 33 common elements were found. The validity of this case was verified through the content validity test of the science education specialist group. As a result, the I-CVI average was .86 and the S-CVI average was .90. For the empathy elements that scientists used in problem-solving cases, in cognitive empathy, three elements (empathy through other disciplines, empathy from the perspective of the research object, accommodating others' opinions) were extracted in terms of perspective-taking, and three elements (imagination thought experiment based on observation, thought experiment, feeling like part of object) in fantasy. And in affective empathy, three elements (influenced by fellow researchers' motivation, touching from the subject, excitement studying more) were extracted in terms of empathic concern and two elements (heartache for others' failure in their research, sensitivity to problems) in personal depression. This could not be said to be a perfect match for Davis' empathy, but it would be possible to define the scientific empathy elements based on these common elements found in the scientists' cases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.320-323
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• 2014

Today is going with the advancement of intelligent transportation systems and traffic environment and helping to provide safe and convenient service through a mobile device work with the popularization of the vehicle black box. The traffic flow by a variety of causes is constantly changing, it is often unable to prepare the driver, depending on external factors can not be controlled by the power of the public, leading to a major accident. The system needs to pass the real-time weather data in the inter-operator to prevent this. The proposed detection algorithm weather information delivered real-time weather information for this paper. The weather condition is detected by using the contrast between the histogram of the motion of the wiper and the clear day algorithm. In general, the wiper is worked in extreme weather conditions that will have a value different contrast due to rain or snow. Situation was considered clear, snowy conditions, such as using it on a rainy situation. First, designated as ROI (Region Of Interest) of the minimum area that can be detected in order to reduce the amount of calculation for the wiper, the wiper, which was detected through the operation of the threshold Thresholding the brightness of the vehicle wiper. In addition, we distinguish the value of each meteorological situation by using contrast. Results was obtained to 80% for the snow conditions, a rainy situation.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.173-183
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• 2020

In the midst of the aging of underground facilities in urban areas and anxiety about road excavation safety accidents, the Ministry of Land, Infrastructure and Transport began to build Underground Geospatial Infomation Map from 2015 as part of the 「ground subsidence prevention measures」 and efficient use of underground spaces. So, the scope is spreading every year. The current Underground Geospatial Infomation Map information is web-based and is operated in a desktop environment, so it is true that there are some limitations in its use in a field environment such as an excavation construction site. The Underground Geospatial Infomation Map, built and operated in a web-based environment, is a large-scale 3D data. Therefore, in order to service by transmitting data to the field without delay, it is necessary to lighten the Underground Geospatial Infomation Map data. In addition, the current Underground Geospatial Infomation Map is not unified in data formats such as 3DS and COLLADA, and the coordinate system method is also different in relative coordinates and absolute coordinates. In this study, by analyzing domestic and overseas prior research and technical use cases, a mobile Underground Geospatial Infomation Map data format and a lightweight method were presented, and a technology development was conducted to create a mobile underground space integration map in the presented format. In addition, the weight reduction rate was tested by applying 3D data compression technology so that data can be transmitted quickly in the field, and technology was developed that can be used by decompressing 3D data compressed in the field. finally, it aims to supplement the technology experimentally developed in this study and conduct additional research to produce it as software that can be used in the excavation site and use it.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.63-71
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• 2020

In this paper, we propose a fire detection technology using YOLOv3 and EfficientDet, the most reliable artificial intelligence detection algorithm recently, an alert service that simultaneously transmits four kinds of notifications: text, web, app and e-mail, and an AWS system that links fire detection and notification service. There are two types of our highly accurate fire detection algorithms; the fire detection model based on YOLOv3, which operates locally, used more than 2000 fire data and learned through data augmentation, and the EfficientDet, which operates in the cloud, has conducted transfer learning on the pretrained model. Four types of notification services were established using AWS service and FCM service; in the case of the web, app, and mail, notifications were received immediately after notification transmission, and in the case of the text messaging system through the base station, the delay time was fast enough within one second. We proved the accuracy of our fire detection technology through fire detection experiments using the fire video, and we also measured the time of fire detection and notification service to check detecting time and notification time. Our AI fire detection and notification service system in this paper is expected to be more accurate and faster than past fire detection systems, which will greatly help secure golden time in the event of fire accidents.

• The Journal of Korean Philosophical History
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• no.50
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• pp.171-200
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• 2016

The full-scaled study of Joseon conducted by Japan in the 1910s was part of its colonial policy, while the native Joseon studies against it contained political aspiration to recover the national rights and independence. Accordingly, the conceptual meaning of 'Joseon' varied according to its subject of speech. The establishment of modern nation-state failed along with the extinction of Korean Empire, but 'Joseon' was newly discovered within national ideology. It became a historical concept in which the experience of the past and the expectation toward the future could be united. The so-called 'Joseon Studies' was only limited to intellectuals in the academic circle, but 'Joseon' embraced the articulations from more various social agents. Furthermore, it is only natural that 'Joseon Studies' should be interpreted within the historical semantics of 'Joseon', considering the connection between concept and discourse. In his The History of Joseon Civilization, An Hwak encompassed the history from the times of ancient mythology to the contemporary times under the banner of 'Joseon'. Opposing Japanese distortion of history carried out in the name of historical positivism, he idealized Joseon history as comparable to that of the Western democracy. He extended the study of 'Joseon' into culture at large, foreshadowing a kind of Joseon philosophy. In his An Overview of Joseon Philosophical Ideas, the first description of 'Joseon philosophy' as an independent field, he proposed philosophy as one of three sources of pride in Joseon and asserted its uniqueness and originality compared to the West. It was an attempt to grasp the peculiarity of Joseon ideas from a perspective of the history of universal human civilization. He considered 'Jong'(倧) as an ideological foundation held from the ancient to the modern times, and the acceptance of Buddhism and Confucianism as beneficial to 'Joseon philosophy'. The birth of 'Joseon philosophy', the modern transformation of the traditional knowledge system, was an intellectual experiment to apply traditional knowledge to the modern disciplinary classification system.

• Journal of Platform Technology
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• v.8 no.3
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• pp.10-21
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• 2020

Partial discharge occurs a lot in high-voltage power equipment such as switchgear, transformers, and switch gears. Partial discharge shortens the life of the insulator and causes insulation breakdown, resulting in large-scale damage such as a power outage. There are several types of partial discharge that occur inside the product and the surface. In this paper, we design a predictive model that can predict the pattern and probability of occurrence of partial discharge. In order to analyze the designed model, learning data for each type of partial discharge was collected through the UHF sensor by using a simulator that generates partial discharge. The predictive model designed in this paper was designed based on CNN during deep learning, and the model was verified through learning. To learn about the designed model, 5000 training data were created, and the form of training data was used as input data for the model by pre-processing the 3D raw data input from the UHF sensor as 2D data. As a result of the experiment, it was found that the accuracy of the model designed through learning has an accuracy of 0.9972. It was found that the accuracy of the proposed model was higher in the case of learning by making the data into a two-dimensional image and learning it in the form of a grayscale image.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.603-610
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• 2021

The purpose of this study was to develop a Youth Future Career Program for adolescents and to look into the effects of the program on the future efficacy. Through the program, adolescents would predict the future, explore alternative futures to solve future problems, find the shape of the future society they want and desire. In addition, they will discover or create future jobs. In this study, the Youth Future Career Program was developed into four modules: Future Understanding, Future Participation, Future-self, and Future Management. Ninety-three students in K University's Gifted Education Center participated in the Future Career Program (62 males and 31 females, 62 middle school students, and 31 high school students). The students responded to 14 questions about the future efficacy of the Youth before and after the program. Statistically significant differences were observed in 8 out of 14 questions (p<.05). In particular, the abilities of the participants were improved as follows: to apply newly learned things to society, to evaluate the current problems, to develop critical thinking to solve the problem, and to communicate with members of society.

• Journal of IKEEE
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• v.25 no.4
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• pp.782-785
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• 2021

In this paper, we propose a personalized cooling management system with thermal imaging camera. The proposed equipment uses a thermal imaging camera to control the amount of cold air and the system according to the difference between the user's skin temperature before and after the procedure. When the skin temperature is abnormally low, the cold air supply is cut off to prevent the possibility of a safety accident. It is economical by replacing the skin temperature sensor with a thermal imaging camera temperature measurement, and it can be visualized because the temperature can be checked with the thermal image. In addition, the proposed equipment improves the sensitivity of the sensor that measures the distance to the skin by calculating the focal length by using a dual laser pointer for the safety of a personalized cooling management system to which a thermal imaging camera is applied. In order to evaluate the performance of the proposed equipment, it was tested in an externally accredited testing institute. The first measured temperature range was -100℃~-160℃, indicating a wider temperature range than -150~-160℃(cryo generation/USA), which is the highest level currently used in the field. In addition, the error was measured to be ±3.2%~±3.5%, which showed better results than ±5%(CRYOTOP/China), which is the highest level currently used in the field. The second measured distance accuracy was measured as below ±4.0%, which was superior to ±5%(CRYOTOP/China), which is the highest level currently used in the field. Third, the nitrogen consumption was confirmed to be less than 0.15 L/min at the maximum, which was superior to the highest level of 6 L/min(POLAR BEAR/USA) currently used in the field. Therefore, it was determined that the performance of the personalized cooling management system applied with the thermal imaging camera proposed in this paper was excellent.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.183-200
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• 2022

A variety of simulation approaches based on automated driving technologies have been proposed to develop traffic operations strategies to prevent traffic crashes and alleviate congestion. The maneuver of simulated autonomous vehicles (AVs) needs to be realistic and be effectively differentiated from the behavior of manually driven vehicles (MVs). However, the verification of simulated AV maneuvers is limited due to the difficulty in collecting actual AVs trajectory and interaction data with MVs. The purpose of this study is to develop a methodology to evaluate the suitability of AV maneuvers based on both driving and traffic simulation experiments. The proposed evaluation framework includes the requirements for the behavior of individual AVs and the traffic stream performance resulting from the interactions with surrounding vehicles. A driving simulation approach is adopted to evaluate the feasibility of maneuvering of individual AVs. Meanwhile, traffic simulations are used to evaluate whether the impact of AVs on the performance of traffic stream is reasonable. The outcome of this study is expected to be used as a fundamental for the design and evaluation of transportation systems using automated driving technologies.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1329-1341
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• 2022

Destroying the marine environment and marine ecosystem and causing marine accidents, marine debris is generated every year, and among them, submerged marine debris is difficult to identify and collect because it is on the seabed. Therefore, deep-learning-based semantic segmentation was experimented on waste fish nets and waste ropes using underwater images to identify efficient collection and distribution. For segmentation, a high-resolution network (HRNet), a state-of-the-art deep learning technique, was used, and the performance of each optimizer was compared. In the segmentation result fish net, F1 score=(86.46%, 86.20%, 85.29%), IoU=(76.15%, 75.74%, 74.36%), For the rope F1 score=(80.49%, 80.48%, 77.86%), IoU=(67.35%, 67.33%, 63.75%) in the order of adaptive moment estimation (Adam), Momentum, and stochastic gradient descent (SGD). Adam's results were the highest in both fish net and rope. Through the research results, the evaluation of segmentation performance for each optimizer and the possibility of segmentation of marine debris in the latest deep learning technique were confirmed. Accordingly, it is judged that by applying the latest deep learning technique to the identification of submerged marine debris through underwater images, it will be helpful in estimating the distribution of marine sedimentation debris through more accurate and efficient identification than identification through the naked eye.