• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.411-419
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• 2019

Nowadays we are not able to consider and imagine anything without taking into account what is called Artificial Intelligence. Even broadcasting media technologies could not be thought of outside this newly emerging technology of A.I.. Since the last part of 20th century, this technology seemingly is accelerating it's development thanks to an unbelievably enormous computational capacity of data information treatments. In conjunction with the firmly established worldwide platform companies like GAFA(Google, Amazon, Facebook, Apple), the key cutting edge technologies dubbed NBIC(Nanotech, Biotech, Information Technology, Cognitive science) converge to change the map of the current civilization by affecting the human relationship with the world and hence modifying what is essential in humans. Under the sign of the converging technologies, the relatively recently coined concepts such as 'trans(post)humanism' are emerging in the academic sphere in the North American and Major European regions. Even though the so-called trans(post)human movements are prevailing in the major technological spots, we have to say that these terms do not yet reach an unanimous acceptation among many experts coming from diverse fields. Indeed trans(post)humanism as a sort of obscure term has been a largely controversial trend. Because there have been many different opinions depending on scientific, philosophical, medical, engineering scholars like Peter Sloterdijk, K. N. Hayles, Neil Badington, Raymond Kurzweil, Hans Moravec, Laurent Alexandre, Gilbert Hottois just to name a few. However, considering the highly dazzling development of artificial intelligence technology basically functioning in conjunction with the cybernetic communication system firstly conceived by Nobert Wiener, MIT mathematician, we can not avoid questioning what A. I. signifies and how it will affect the current media communication environment.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.1
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• pp.25-32
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 200 buildings that KEPCO headquarter and branch offices use. And K-BEMS system is composed of PV, battery, and hybrid PCS. KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. In this paper, the results of the project are shown. 9 modes of test results of K-BEMS system and are operational problems were analyzed. And measures to cure the trouble are also suggested. Batteries are operated more than 20% of SOC, and less than 20% of SOC battery protection switches are automatically shutting down the system and the system no longer respond to EMS, ending the supply of PV, and so therefore to continue the PV power supply it was turn out to be necessary that the EMS should automatically change its policy to change PV only supply mode automatically when the Battery Switch automatically operated. To operate the system continuously and automatically, it is necessary to modify the minimum operational SOC value, and in addition to that the EMS computer must remember the last shut-down SOC and Voltage which interrupted the system and add some margin to reflect the measurement error in the system.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.131-139
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• 2019

From 2019, software education has become a required subject for all elementary school students. However, many teachers are still unfamiliar with how the classes should be instructed. So this paper presented the meaning, detailed competencies and achievement standard in order to help in the collection, analysis and representation of data among the computational thinking that are key to software education. And it also suggested the applicability of the classes. The full course of the paper is summarized as follows. First, existing studies have summarized the meaning, detail and achievement standard of data related competencies. Based on this, a preliminary investigation was instructed. Pilot study carried out both FGI and closed questions at the same time. This was done in response to the survey's questionnaire reflecting the opinions of experts. Second, the results of the questionnaire generated as a result of the above were verified for validity, stability, and reliability among the PhD, PhD courses, software education teachers, and software education workers. Third, I developed and applied the five lessons as a class objective as 'Choosing collection method-Select the collection method according to the problem situation.', 'Searching for meaning of data-Understand what the analyzed data mean..', 'Using various expression methods-Use a variety of expression tools.' using the backward design model to integrate education, class, and assessment. As a result, the detailed competencies of data collection, analysis, and representation and achievement standard were presented. This may help in setting specific and specific criteria for what direction classes are recommended when planning data-related classes in elementary schools.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2895-2905
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• 2018

We present a mixed multiplicative quantitative randomized response model which added a unrelated quantitative attribute and forced answer to the multiplicative model suggested by Bar-Lev et al. (2004). We also try to set up theoretical grounds for estimating sensitive quantitative attribute according to circumstances whether or not the information for unrelated quantitative attribute is known. We also extend it into the stratified mixed multiplicative quantitative randomized response model for stratified population along with two allocation methods, proportional and optimum allocation. We can see that the various quantitative randomized response models such as Eichhorn-Hayre's model (1983), Bar-Lev et al.'s model (2004), Gjestvang-Singh's model (2007) and Lee's model (2016a), are one of the special occasions of the suggested model. Finally, We compare the efficiency of our suggested model with Bar-Lev et al.'s (2004) and see that the bigger the value of $C_z$, the more the efficiency of the suggested model is obtained.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.285-290
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• 2021

In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.101-111
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• 2021

Irregular workers, which have recently caused various socio-economic issues and conflicts, generally have low loyalty to the organization and job satisfaction due to anxiety about employment. As a way to improve this, this study attempted to analyze the effect of organizational communication satisfaction of irregular workers on job satisfaction and organizational commitment. Among the 7th Human Capital Companies panel survey data, irregular workers survey data were collected and analyzed using the structural equation model analysis. The results were as follows: First, it was analyzed that organizational communication recognized by irregular workers had a positive(+) effect on job satisfaction and organizational commitment. Second, it was analyzed that job satisfaction had a positive(+) effect on organizational commitment. Third, it was analyzed that job satisfaction plays a mediating role in the relationship between communication satisfaction and organizational commitment. This study is significant in that it expanded the research subject to irregular workers from the existing service industry-oriented research, and that it included more diverse industries. The results of this study suggest that mission and vision sharing and communication activation system are needed to improve organizational effectiveness of irregular workers.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.500-507
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• 2021

The virtual reality industry has an opportunity to take another leap forward with the surge in demand for non-face-to-face content and interest in the metaverse after Covid-19. Therefore, in order to popularize virtual reality content along with this trend, high-quality content production and storytelling research suitable for the characteristics of virtual reality should be continuously conducted. In order for content to which virtual reality characteristics are applied to be effectively produced through user feedback, a quantitative index that can evaluate the content is needed. In this study, the process of viewing virtual reality contents was analyzed and head movement was set as a quantitative indicator. Afterwards, the experimenter watched five animations and analyzed the correlation between recorded head movement information and immersion. As a result of the analysis, high immersion was shown when the head movement speed was relatively slow, and it was found that the head movement speed can be used significantly as an index indicating the degree of content immersion. The result derived in this way can be used as a quantitative indicator that can verify the validity of the storytelling method applied after the prototype is produced when the creator creates virtual reality content. This method can improve the quality of content by quickly identifying the problems of the proposed storytelling method and suggesting a better method. This study aims to contribute to the production of high-quality virtual reality content and the popularization of virtual reality content as a basic research to analyze immersion based on the quantitative indicator of head movement speed.

• Journal of Platform Technology
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• v.9 no.3
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• pp.3-17
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• 2021

Advanced persistent threat (APT) attacks are attacks aimed at a particular entity as a set of latent and persistent computer hacking processes. These APT attacks are usually carried out through various methods, including spam mail and disguised banner advertising. The same name is also used for files, since most of them are distributed via spam mail disguised as invoices, shipment documents, and purchase orders. In addition, such Infostealer attacks were the most frequently discovered malicious code in the first week of February 2021. CDR is a 'Content Disarm & Reconstruction' technology that can prevent the risk of malware infection by removing potential security threats from files and recombining them into safe files. Gartner, a global IT advisory organization, recommends CDR as a solution to attacks in the form of attachments. There is a program using CDR techniques released as open source is called 'Dangerzone'. The program supports the extension of most document files, but does not support the extension of HWP files that are widely used in Korea. In addition, Gmail blocks malicious URLs first, but it does not block malicious URLs in mail systems such as Naver and Daum, so malicious URLs can be easily distributed. Based on this problem, we developed a 'Dangerzone' program that supports the HWP extension to prevent APT attacks, and a Chrome extension that performs URL checking in Naver and Daum mail and blocking banner ads.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.49-56
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• 2021

In this study, we investigated the necessary mechanical properties of conductive multifilament yarns for fabricating the electrodes of biosignal measurement pressure and stretch textile sensors using embroidery. When electrodes and circuits for smart wearable products are produced through the embroidery process using conductive multifilament yarns, unnecessary material loss is minimized, and complex electrode shapes or circuit designs can be produced without additional processes using a computer embroidering machine. However, because ordinary missionary threads cannot overcome the stress in the embroidery process and yarn cutting occurs, herein, we analyzed the S-S curve, thickness, and twist structure, which are three types of silver-coated multifilament yarns, and measured the stress in the thread of the embroidery simultaneously. Thus, the required mechanical properties of the yarns in the embroidery process were analyzed. In the actual sample production, cutting occurred in silver-coated multifilament rather than silver-coated polyamide/polyester, which showed the lowest S-S curve. In the embroidery process, the twist was unwound through repetitive vertical movement. Further, we fabricated a piezoresistive pressure/tension sensor to measure gauge factor, which is an index for measuring biological signals. We confirmed that the sensor can be applied to the fabrication of embroidery electrodes, which is an important process in the mass production of smart wearable products.

• Composites Research
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• v.34 no.1
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• pp.8-15
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• 2021

In the shipbuilding and marine industry, as a technology for reducing the weight of parts to reduce energy and improve operational efficiency of ships is required, a method of applying fibers-reinforced composites which is high-strength lightweight materials, as part materials can be considered. In this study, the possibility of applying fibers-reinforced composites to the pipe support clamps was evaluated to reduce the weight of LNGC. The fibers-reinforced composites were manufactured using carbon fibers and glass fibers as reinforcing fibers. Through the computer simulation program, the properties of the reinforcing materials and the matrix materials of the composites were inversely calculated, and the performance prediction was performed according to the change in the properties of each fiber lamination pattern. In addition, the structural analysis of the clamps according to the thickness of the composites was performed through the finite element analysis program. As a result of the study, it was confirmed that attention is needed in selecting the thickness when applying the fibers-reinforced composites of the clamp for weight reduction. It is considered that it will be easy to change the shape of the structure and change the structure for weight reduction in future supplementary design.