• Journal of Service Research and Studies
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• v.10 no.3
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• pp.55-66
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• 2020

This study was attempted to demonstrate the service performance of non-face-to-face real-time video lecture service conducted in the coronavirus crisis in early 2020. Lecture service is divided into service production and service delivery from a service system perspective, and its role of lecture service system and the relationship between lecture service benefits and service satisfaction perceived by learners is demonstrated. In order to demonstrate this structural impact relationship, the result of analysis through a questionnaire survey on a total of 268 undergraduate students at G University, showed that the role and level of the non-face-to-face real-time video lecture service system affects the service convenience and service satisfaction. In the additional analysis, the learning orientation learners group perceived the service system level or role in the lecture service and the service benefit itself higher than the relationship orientation learners group. In the past, when a face-to-face class was conducted, learners group who attended a lot of extra curriculum activities perceived the benefits of coronavirus prevention lower than those of a group that did not. In this way, it is necessary to supplement the lecture service system by identifying the role expectation in the lecture service for the high relationship orientation group and the preferring extra curriculum activity group after detail research.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.157-168
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• 2014

From a complex systems perspective, ecohydrological systems in forests may be characterized with (1) large networks of components which give rise to complex collective behaviors, (2) sophisticated information processing, and (3) adaptation through self-organization and learning processes. In order to demonstrate such characteristics, we applied the recently proposed 'process networks' approach to a temperate deciduous forest in Gwangneung National Arboretum in Korea. The process network analysis clearly delineated the forest ecohydrological systems as the hierarchical networks of information flows and feedback loops with various time scales among different variables. Several subsystems were identified such as synoptic subsystem (SS), atmospheric boundary layer subsystem (ABLS), biophysical subsystem (BPS), and biophysicochemical subsystem (BPCS). These subsystems were assembled/disassembled through the couplings/decouplings of feedback loops to form/deform newly aggregated subsystems (e.g., regional subsystem) - an evidence for self-organizing processes of a complex system. Our results imply that, despite natural and human disturbances, ecosystems grow and develop through self-organization while maintaining dynamic equilibrium, thereby continuously adapting to environmental changes. Ecosystem integrity is preserved when the system's self-organizing processes are preserved, something that happens naturally if we maintain the context for self-organization. From this perspective, the process networks approach makes sense.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.155-166
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• 2021

Most object detection algorithms are studied based on RGB images. Because the RGB cameras are capturing images based on light, however, the object detection performance is poor when the light condition is not good, e.g., at night or foggy days. On the other hand, high-quality infrared(IR) images regardless of weather condition and light can be acquired because IR images are captured by an IR sensor that makes images with heat information. In this paper, we performed the object detection algorithm based on the compression ratio in RGB and IR images to show the detection capabilities. We selected RGB and IR images that were taken at night from the Free FLIR Thermal dataset for the ADAS(Advanced Driver Assistance Systems) research. We used the pre-trained object detection network for RGB images and a fine-tuned network that is tuned based on night RGB and IR images. Experimental results show that higher object detection performance can be acquired using IR images than using RGB images in both networks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.128-136
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• 2019

This study was conducted to investigate the relationship among professional self-concept, moral sensitivity and elderly care performance nurses in geriatric hospitals, as well as to clarify factors that affect nurses' elderly care performance. Participants consisted of 153 nurses working in geriatric hospital in G Province were evaluated. Date were collected from September 15 to October 15, 2018 and analyzed using the SPSS/WIN 23.0 program. The mean of professional self-concept was $2.87{\pm}0.35$ out of 4, that of moral sensitivity was $4.70{\pm}0.47$ out of 7 and that of elderly care performance $3.51{\pm}0.41$ out of 4. Elderly care performance was siginificantly positively correlated with professional self-concept (r=.48, p<.001) and moral sensitivity (r=.31, p<.001). Factors influencing elderly care performance were professional self-concept (${\beta}=.32$, p=.001), moral sensitivity (${\beta}=.18$, p=.021), educational experience of geriatric nursing (${\beta}=.17$, p=.029), which explained 31.6% of elderly care performance. The results of this study suggest that supporting systems should be arranged to provide various learning opportunities as a way to increase the professional self-concept of nurses with short career as well as intervention strategies may be necessary to make education of geriatric nursing obligatory.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.8
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• pp.783-790
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• 2019

Cognitive science attempts to explain human intelligence on the basis of success of artificial neural network, which is called connectionism. The neural network, e.g., deep learning, seemingly promises connectionism to go beyond what it is. But those(Fodor & Pylyshyn, Fodor, & McLaughlin) who advocate classical computationalism, or symbolism claim that connectionism must fail since it cannot represent the relation between human thoughts and human language. The neural network lacks systematicity, so any output of neural network is at best association or accidental combination of data plugged in input units. In this paper, I first introduce structure of artificial neural network and what connectionism amounts to. Second, I shed light on the problem of systematicity the classical computationalists pose for the connectionists. Third, I briefly introduce how those who advocate connectionism respond to the criticism while noticing Smolensky's theory of vector product. Finally, I examine the debate of computationalism and connectionism on systematicity, and show how the problem of systematicity contributes to the development of connectionism and computationalism both.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.37-44
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• 2021

A study was conducted on the effects of improving concentration by obscuring the peripheral vision using a blindfold that only covers the left and right sides of the field of view. The blindfold was trapezoidal in shape (5 × 4.8 cm in length and width) and was fixed to the left and right sides of the glasses with fixing clips. The material was a black-colored polypropylene (PP) and weighed 2.3 g including the clip. Qualitative and quantitative evaluations were performed on 50 healthy college students during the 15 days of using a blindfold. The qualitative analysis was performed utilizing a questionnaire regarding the improvement of concentration and the structure of the blindfold. EEG was measured while watching a learning video that required attention for quantitative analysis, and signal power and ERD/S analyses were performed for the mid β band (15-20 Hz) at the F4 position, which was the frontal lobe. The results showed that 40 of the 50 people reported improved concentration when they wore a vision shield, and 80% of the total subjects found it to be effective. From the quantitative evaluation, the ERS peak (p = 0.023) and the ERD + ERS peak value showed a significant difference (p = 0.017). In conclusion, concentration still improved even if only the left and right visual fields were used. Thus, it is expected that blindfolding could be used in various environments that require concentration.

• The Journal of Korean Philosophical History
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• no.42
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• pp.39-70
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• 2014

Neo-Confucianism of Myungjae Yoon Jeung either accepted Yulgok Neo-Confucianism as it was or modified it. In this study, his Neo-Confucianism was divided into acceptance and modification in Yulgok Neo-Confucianism and examined. In the acceptance of Yulgok Neo-Confucianism, it was clarified that Neo-Confucianism of Myungjae Yoon Jeung thoroughly inherited characteristics of Yulgok Neo-Confucianism, including 'Yiguijimyo', 'Yitongguiguk' and 'Guibalyiseungildo'. However, Myungjae was not just satisfied with inheriting Yulgok Neo-Confucianism as it was, but modified and inherited the theory of Yulgok by suggesting his own original preaching. There were three original preaching of his in overall; 'emphasis on the control of Li', 'argument method on a theory of gaining knowledge by the study of things', and 'perception on moral mind, human mind and human desire'. Ultimately, it is concluded that Myungjae modified, inherited and developed Yulgok Neo-Confucianism to adjust a theory of Neo-Confucianism in a position of 'Yiguijimyo', based on 'a theory of Guibalyiseungildo' of Yulgok as a Confucian scholar of Giho school. It is consistent with his life philosophy that he avoided speculative arguments on Neo-Confucianism and pursued solid study(實工) with solid mind(實心). It is also consistent with his view of learning that he believed that theories of ancient sages were already rich that we should read them and practice their true knowledge(眞知), and making an effort on writing regardless of them was not a study of Mushil(務實). However, due to his younger students, he was classified as a scholar who emphasized the control of 'Li' the most in Yulgok school, and a new academic tie of Giho Soron was created. It is the most important significance that Neo-Confucianism of Myungjae has in that of Giho.

• Journal of The Korean Association For Science Education
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• v.41 no.2
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• pp.83-92
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• 2021

The purpose of this study is to investigate elementary school students' understandings about scientific inquiry. Data were collected from 119 elementary students who are in the 4^th grade using the Views About Scientific Inquiry questionnaire for elementary students (VASI-E). We also conducted semi-structured interviews of 21 students from 119 students who responded to VASI-E. Students' responses were analyzed as naive, mixed, or informed views on each aspect of scientific inquiry that VASI-E includes. We found that, first, 53.8% of students have mixed views, and 30.3% of students have informed views, and 16% of students have naive views on the knowledge 'investigation begin with a question'. Second, 54.6% of students have naive views, 37.8% of students have mixed views, and 7.6% of students have informed views on the knowledge 'scientists use many methods to answer their questions.' Third, 47.9% of students have informed views, 34.5% of students have naive views, and 17.6% of students have mixed views on 'procedures guided by question asked.' Fourth, 55.5% of students have mixed views, 42% of students have informed views, and only 2.5% of students have naive views on 'conclusions must be consistent with data and explanations come from data and prior knowledge.' Based on the results, implications for teaching and learning scientific inquiry at elementary level in Korea were discussed.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.437-448
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• 2021

As the core technology of the Fourth Industrial Revolution, AI is applied to various fields of society(e.g. politics, culture, industry, economy, etc.) and causes revolutionary changes. Students who will lead the age of AI need the ability to recognize social changes due to AI, acquire AI related knowledge and utilize AI in various situations. However, it is difficult for elementary school students to understand the concept and principles of AI. Therefore, this study developed an AI education program by selecting educational contents and methods appropriate to the level of elementary school students, and investigated the educational effects of the program by applying it to an actual educational setting. The content selected in this study is 'Social Awareness on AI', 'Understanding AI' and 'Utilizing AI', and eight content elements were selected. To help students learn AI easily and pleasantly at their level, activity-centered education, convergence of subjects and project-based learning were selected as instructional methods, and 20 sessions of education program were developed and implemented. In addition, the effects of the program were analyzed concerning 'perception on AI', 'convergent thinking', 'creative problem-solving' and 'collaboration capability', and positive changes were verified for all four aspects.

• KNOM Review
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• v.23 no.2
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• pp.29-41
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• 2020

Networks are growing faster than ever before causing a multi-domain complexity. The diversity, variety and dynamic nature of network traffic and services require enhanced orchestration and management approaches. While many standard orchestrators and network operators are resulting in an increase of complexity for handling E2E slice orchestration. Besides, there are multiple domains involved in E2E slice orchestration including access, edge, transport and core network each having their specific challenges. Hence, handling of multi-domain, multi-platform and multi-operator based networking environments manually requires specified experts and using this approach it is impossible to handle the dynamic changes in the network at runtime. Also, the manual approaches towards handling such complexity is always error-prone and tedious. Hence, this work proposes an automated and abstracted solution for handling E2E slice orchestration using an intent-based approach. It abstracts the domains from the operators and enable them to provide their orchestration intention in the form of high-level intents. Besides, it actively monitors the orchestrated resources and based on current monitoring stats using the machine learning it predicts future utilization of resources for updating the system states. Resulting in a closed-loop automated E2E network orchestration and management system.