• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.227-238
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• 2022

This study is the case of non-face-to-face teaching-learning in the subject of "Research and Guidance on Early Childhood Materials" in the pre-child teacher training program. The study conducted a non-face-to-face teaching-learning model for 18 students at B University in region C who took lectures on 'Research and Guidance on Early Childhood Materials' in the first semester of 2021. As a non-face-to-face teaching-learning model, it consisted of video lectures, real-time zoom classes, and various forms of 'communication' through frequent feedback and interaction and 'participation'. As a teaching-learning strategy for the participation of pre-service early childhood teachers, comment on questions related to early childhood materials, in-depth reflection on early childhood materials through writing reflective journals and observation reports, and step-by-step presentation of making childhood materials plans, processes, and results were carried out. As a result of exploring the experience of making early childhood materials for pre-service early childhood teachers, factors such as "growth experience through trial and error," "thinking from child's point of view", "Increase efficiency and reduce burden through communication", "Process rather than result" and "The importance of communication and interaction in non-face-to-face classes"

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.1-6
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• 2022

As the demand for wearable devices increases, many studies have been studied on the development of flexible electrode materials recently. In particular, the development of high-performance flexible electrode materials is very important for wearable sensors for healthcare because it is necessary to continuously monitor and accurately detect body information such as body temperature, heart rate, blood glucose, and oxygen concentration in real time. In this study, we fabricated the nonenzymatic glucose sensor based on polyaniline/carbon nanotube fiber (PANI/CNT fiber) electrode. PANI layer was synthesized on the flexible CNT fiber electrode through electrochemical polymerization process in order to improve the performance of a flexible CNT fiber based electrode material. Surface morphology of the PANI/CNT fiber electrode was observed by scanning electron microscopy. And its electrochemical characteristics were investigated by chronoamperometry, cyclic voltammetry, electrochemical impedance spectroscopy. Compared to bare CNT fiber electrode, this PANI/CNT fiber electrode exhibited small electron transfer resistance, low peak separation potential and large surface area, resulting in enhanced sensing properties for glucose such as wide linear range (0.024~0.39 and 1.56~50 mM), high sensitivity (52.91 and 2.24 ㎂/mM·cm²), low detection limit (2 μM) and good selectivity. Therefore, it is expected that it will be possible to develop high performance CNT fiber based flexible electrode materials using various nanomaterials.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.38-43
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• 2022

Smart sewage treatment plant means creating a safe and clean water environment by establishing an ICT-based real-time monitoring, remote control management and intelligent system for the entire sewage treatment process. The core technology of such a smart sewage treatment plant can be operation control technology using measuring instruments. This research team analyzed and suggested the operation control technologies necessary for the establishment of the intelligent business by referring to the intelligent research projects of the sewage treatment plant in progress in Korea. As a result of the analysis, a total of six removal technologies were presented, including control by scale, reflow water control, linked treated water control, chemical quantity control, winter operation control, and total organic carbon control. By size, standards that can be classified into small and medium-sized large-scale are presented, and in the case of reflow water control, the location of water quality and flow sensors capable of managing reflow water is suggested. In the case of the linked treated water control, the influence and control points of the linked treated water on the sewage treatment plant were presented, and in the case of the chemical injection volume control, a system capable of optimizing the amount of chemical injection according to the introduction of an intelligent sewage treatment plant was presented. In the case of winter operation, the sensors and pumps to be controlled are suggested when considering the decrease in nitrification due to the decrease in water temperature. In the case of total organic carbon control, an interlocking system considering the total amount of pollution in the future was proposed. These operation control scenarios are expected to be used as basic data to be used in intelligent sewage treatment algorithms and scenarios in the future.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.351-357
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• 2021

IoT devices, which are used in various ways in distributed environments, are becoming more important in data transmitted and received from IoT devices as fields of use such as medical, environment, transportation, bio, and public places are diversified. In this paper, as a method to ensure the reliability of IoT data, an autoencoder-based IoT-linked processing technique is proposed to classify and process numerous data by various important attributes. The proposed technique uses correlation indices for each IoT data so that IoT data is grouped and processed by blockchain by characteristics for IoT linkage processing based on autoencoder. The proposed technique expands and operates into a blockchain-based n-layer structure applied to the correlation index to ensure the reliability of IoT data. In addition, the proposed technique can not only select IoT data by applying weights to IoT collection data according to the correlation index of IoT data, but also reduce the cost of verifying the integrity of IoT data in real time. The proposed technique maintains the processing cost of IoT data so that IoT data can be expanded to an n-layer structure.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.725-735
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• 2022

Currently, disasters occurring in Korea are characterized by unpredictability and complexity. Due to these features, property damage and human casualties are increasing. Since the initial response process of these disasters is directly related to the scale and the spread of damage, optimal decision-making is essential, and information of the site must be obtained through timely applicable sensors. However, it is difficult to make appropriate decisions because indiscriminate information is collected rather than necessary information in the currently operated Disaster and Safety Situation Office. In order to improve the current situation, this study proposed a framework that quickly collects various disaster image information, extracts information required to support decision-making, and utilizes it. To this end, a web-based display system and a smartphone application were proposed. Data were collected close to real time, and various analysis results were shared. Moreover, the capability of supporting decision-making was reviewed based on images of actual disaster sites acquired through CCTV, smartphones, and UAVs. In addition to the reviewed capability, it is expected that effective disaster management can be contributed if institutional mitigation of the acquisition and sharing of disaster-related data can be achieved together.

• Journal of Korean Elementary Science Education
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• v.41 no.4
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• pp.725-739
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• 2022

This study aims to analyze what elementary school pre-service teachers focused on and what challenges they faced in designing and producing a guided science inquiry program based on augmented reality (AR) and to provide some implications for teachers' professionalism and teacher education. To this end, focusing on the cases of pre-service teachers who designed and created AR-based guided inquiry programs, the researchers extracted and categorized the pre-service teachers' focus and challenges from the program design and production stages. As a result, in the program design stage, the pre-service teachers tried to construct scenarios that could promote students' active inquiry process. At the same time, drawing on the unique affordances of AR, the pre-service teachers focused on creating vivid visual data in a 3D environment and making meaningful connections between virtual and real-world activities. The pre-service teachers faced challenges in making use of the advantages of AR technology and designing an inquiry program due to a lack of background knowledge about CoSpaces, a content creation program. In the program production stage, the pre-service teachers tried to make their program easy to handle to improve students' concentration on inquiry activities. In addition, challenges of programming using CoSpaces were reported. Based on these results, educational implications were discussed in terms of the pedagogical uses of AR and teachers' professionalism in adopting AR in science inquiry.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.91-100
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• 2022

This study proposes the metaverse content production pipeline using ZEPETO World, one of the representative metaverse platforms in Korea. Based on the Unity 3D engine, the ZEPETO world is configured using the ZEPETO template, and the core functions of the metaverse content that enable multi-user participation such as logic, interaction, and property control are implemented through the ZEPETO script. This study utilizes the basic functions such as properties, events, and components of the ZEPETO script as well as the ZEPETO player which includes avatar loading, character movement, and camera control functions. In addition, based on ZEPETO's properties such as World Multiplayer and Client Starter, it summarizes the core synchronization process required for multiplay metaverse content production, such as object transformation, dynamic object creation, property addition, and real-time property control. Based on this, we check the proposed production pipeline by directly producing multiplay metaverse content using ZEPETO World.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.211-220
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• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.449-460
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• 2021

The development process of cyber literature theory in the 1990s clearly shows the duality of the pursuit of symbolic power and desire through the formation and conflict of literary fields, collective intelligence. All desires are bound to be power-oriented, and cyber literature is meaningful in that network-space critics developed while advocating the humanities of coexistence. The failure of cyber literature theory is due to the conflicting desire of critical power between real and virtual spaces. Cyber literature theory in the 1990s was the first literary response to the birth of artificial nature, although the contradiction of desires revealed in symbolic power and the limitations of barking are clear. Literature discourse has always explored the relationship between the social conditions of the time (including technological progress) and art texts. Producing a new critical discourse encompassing the whole within the literary field of artificial nature is an important task in literature in the era of technology compilation, and humanities and technology must coexist. Through this paper, we examined the impact of the birth of artificial nature on humanities. This study is an important achievement of humanities engineering that understands, interprets, and leads technology.