• Clean Technology
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• v.27 no.3
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• pp.207-216
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• 2021

Major anthropogenic emissions of elemental mercury (Hg⁰) occur from coal-fired power plants, and the emissions can be controlled successfully using NH₃-SCR (selective catalytic reduction) systems with catalysts. Although the catalysts can easily convert the gaseous mercury into Hg²⁺ species, the reactions are greatly dependent on the flue gas constituents and SCR conditions. Numerous deNO_xing catalysts have been proposed for considerable reduction in power plant mercury emissions; however, there are few studies to date of elemental mercury oxidation using SCR processes with MW- and full-scale coal-fired boilers. In these flue gas streams, the chemistry of the mercury oxidation is very complicated. Coal types, deNO_xing catalytic systems, and operating conditions are critical in determining the extent of the oxidation. Of these parameters, halogen element levels in coals may become a key vehicle for obtaining better Hg⁰ oxidation efficiency. Such halogens are Cl, Br, and F and the former one is predominant in coals. The chlorine exists in the form of salts and is transformed to gaseous HCl with a trace amount of Cl₂ during the course of coal combustion. The HCl acts as a very powerful promoter for high catalytic Hg⁰ oxidation; however, this can be strongly dependent on the type of coal because of a wide variation in the chlorine contents of coal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.707-725
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• 2021

Energy management systems (EnMS) contribute to sustainable energy saving and greenhouse gas reduction by emphasizing the role of energy management in production-oriented economies. Although understanding the methods used to measure energy performance is a key factor in constructing successful EnMS, few attempts have been made to examine these methods, their applicability, and their utility in practice. To fill this research gap, this study aimed to deepen the understanding of energy performance measures by focusing on four energy performance indicators (EnPIs) proposed by ISO 50006, namely the measured energy value, ratio between measured values, linear regression model, and nonlinear regression model. This paper presents policy and managerial implications to facilitate the effective use of these measures. An analytic hierarchy process (AHP) analysis was conducted with 41 experts to analyze the preference for EnPIs and their key selection criteria by the industry sector, and organization and user type. The findings suggest that the most preferred EnPI is the ratio between the measured values followed by the measured energy value. The ease of use was considered to be most important while choosing EnPIs.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.213-219
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• 2022

The purpose of this study is the construction and internal validation of DT ISD model that incorporates Design Thinking process into Instructional Systems Design. The study proceeded in 3 steps. Firstly, literature review was conducted to examine the process and components of Instructional Systems Design model such as ADDIE. Design Thinking models were also reviewed to determine the probability of integrating Design Thinking with ISD. Secondly, DT ISD model was constructed by adopting 3 principles of Design Thinking to ISD process. Thirdly, the internal validation research was conducted through 3 rounds delphi study and DT ISD model was finally validated by experts of instructional technology and lifelong education. DT ISD model is based upon constructionism in learning theory rather than behavioral or cognitive learning theory such as ADDIE. Hence, DT ISD model is an effective instructional design model for adult lifelong education program. It is suggested that action research is necessary to examine the external validation of DT ISD model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.57-58
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• 2023

The working time for loading and transporting containers in the container terminal is one of the factors directly related to port productivity, and minimizing working time for these operations can maximize port productivity. Among working time for container operations, the working time of yard tractors(Y/T) responsible for the transportation of containers between berth and yard is a significant portion. However, it is difficult to estimate the working time of yard tractors quantitatively, although it is possible to estimate it based on the practical experience of terminal operators. Recently, a technology based on IoT(Internet of Things), one of the core technologies of the 4th industrial revolution, is being studied to monitoring and tracking logistics resources within the port in real-time and calculate working time, but it is challenging to commercialize this technology at the actual port site. Therefore, this study aims to develop yard tractor working time prediction model to enhance the operational efficiency of the container terminal. To develop the prediction model, we analyze actual port operation data to identify factors that affect the yard tractor's works and predict its working time accordingly.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.589-594
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• 2023

K-POP plays a key role in the Korean Wave and is becoming more popular over time. In K-POP, K-POP dance plays an important role in increasing public interest and support and reflects the taste of the audience according to the rapidly changing times. In addition, it has a variety of unique choreography forms, such as point choreography and dance that is perfectly in sync associated with the lyrics of the song, so it has sufficient possibility to raise its status independently. In order to examine the fact that K-POP dance is not an element included in K-POP, this researcher tried to investigate the case of interest in -K-POP dance in various ways and to clarify the meaning of the existence of K-POP dance once again. K-POP dance is gaining international interest and support through the mass media through various examples, raising the awareness of choreographers. In addition, created the integration of various races and ages. It also continues to help the country's economic growth while expanding to education. It also serves as a cultural notification in that it promotes Korean culture and manners along with -K-POP dance. However, this researcher emphasizes that for the continuous growth and independence of K-POP dance in the future, a program to cultivate systematic educators are needed, and the efforts of K-POP dance educators and choreographers are needed accordingly.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Journal of Industrial Convergence
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• v.22 no.5
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• pp.23-37
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• 2024

The purpose of this study is to investigate various factors affecting the relationship between digital leadership and digital transformation in companies. In particular, focusing on the mediating effect of dynamic digital capabilities that quickly sensing and seizing advanced and convergent digital technologies and apply them to the organization, this study also intends to examine the moderating effect of the organization's acceptance intention. The hypotheses were verified with a sample of 258 copies of data collected by conducting a survey on companies participating in mini-clusters in industrial complexes nationwide. As a result of the study, dynamic digital capabilities showed a significant mediating effect in the relationship between digital leadership and digital transformation, and the effect of dynamic digital capabilities on the level of digital transformation differed according to the organization's digital acceptance intention. This study presented a new concept and measurement items of digital dynamic capabilities, and how to consider digital leadership, dynamic digital capabilities and acceptance level of organization when promoting digital transformation in companies.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.411-417
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• 2024

In the event of a disaster, it is essential to establish a disaster recovery plan and disaster recovery system to minimize disruption to major IT infrastructure and provide continuous business services. In the process of building a disaster recovery system, data replication is a key element of data recovery to provide uninterrupted and continuous business services in the event of a disaster. The data replication method can be determined depending on the system configuration environment and disaster recovery goal level. In this paper, we present a method for determining a data replication method suitable for the configuration environment and disaster recovery target level when building a disaster recovery system. In addition, the replication method decision procedure is applied to build a disaster recovery system and analyze the construction results. After establishing the disaster recovery system, a test was conducted to determine whether the service was transferred to the disaster recovery center in a disaster situation and normal service was provided, and the results were analyzed. As a result, it was possible to systematically select the optimal data replication method during the disaster recovery system construction phase. The established disaster recovery system has an RTO of 3.7 hours for service conversion to the disaster recovery center to provide continuous business services, and the disaster recovery level, which was Tier 2, has been improved to the target level within 4 hours of RTO and RPO=0.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.891-899
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• 2024

The Fourth Industrial Revolution is centered on a personalized demand fulfillment economy and is all about transformation and flexible processing that can deliver what customers want in real time across space and time. This paper implements the construction and operation of a packaging platform that can instantly procure the required packaging products based on real-time orders and evaluates its performance. The components of customer satisfaction are flexible and dependent on the situation which requires efficient management of enterprise operational processes based on an e-SCM platform. An OMS optimized for these conditions plays an important role in maximizing and differentiating the efficiency of a company's operations and improving its cost advantage. OMS is a system of mass customization that provides efficient MOT(Moment of Truth) logistics services to meet the eco-friendly issues of many individual customers and achieve optimized logistics operation goals to enhance repurchase intentions and sustainable business. OMS precisely analyzes the collected data to support information and decision-making related to efficiency, productivity, cost and provide accurate reports. It uses data visualization tools to express data visually and suggests directions for improvement of the operational process through statistics and prediction analysis.