• Journal of Coastal Disaster Prevention
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• 제5권4호
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• pp.163-172
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• 2018

To propose the design technique and the execution manual of the LWFS(Lightweight Foamed Soil) method using dredged soil, the operation system for the test-bed integrated management, and to establish an amendment for the domestic quantity per unit and specifications, and a strategy for its internationalization. In order to utilize the dredged soil from the coastal area as a construction material, we constructed the embankment with LWFS on soft ground and monitored its behavior. As a result, it can be expected that the use of LWFS as an embankment material on the soft ground can improve the economic efficiency by reducing the depth and period of soil improvement as well as the uses of nearby dredged soil. To verify the utilization of the dredged soil as a material for light-weighted roadbed, soft ground and foundation ground, and surface processing, perform an experimental construction for practical structures and analyze the behavior. It is expected to be able to improve the soft ground with dredged soil and develop technique codes and manuals of the dredged soil reclamation by constructing a test-bed in the same size of the fields, and establish the criteria and manual of effective dredged soil reclamation for practical use. The application technology of the dredged soil reclamation during harbor constructions and dredged soil reclamation constructions can be reflected during the working design stage. By using the materials immediately that occur from the reclamation during harbor and background land developments, the development time will decrease and an increase of economic feasibility will happen. It is expected to be able to apply the improved soil at dredged soil reclamation, harbor and shore protection construction, dredged soil purification projects etc. Future-work for develop the design criteria and guideline for the technology of field application of dredged soil reclamation is that review the proposed test-bed sites, consult with the institutions relevant with the test-bed, establish the space planning of the test-bed, licensing from the institutions relevant with the test-bed, select a test-bed for the dredged soil disposal area.

• Journal of Korea Entertainment Industry Association
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• 제15권4호
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• Journal of Digital Convergence
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• 제20권5호
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• pp.227-232
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• 2022

This study is an exploratory study on the sustainable management of MICE events, and was conducted using the FGI method. Twelve experts in the MICE field, industry, and academia were selected as the subjects of the study. The reason is that understanding and specialty of those targets provides research reliability and validity. The study period was 3 months from June to August 2021. As a result, it is very important to prepare a sustainable development strategy in the MICE industry, and in particular, the need for guidelines to be practiced during event operation from the organizer's point of view was derived. In addition, to derive items that can be used in practice based on the theoretical basis, and it was necessary to derive research results using internationally recognized Sustainable Development Goals (UNSDGs) and sustainable MICE research developed in the fields of tourism and MICE. Therefore, through the verification of such experts in the field of MICE, theoretical and practical guidelines from the perspective of the organizer that can be used when holding MICE were developed. The results of the study will provide implications for establishing more effective strategies for hosting sustainable MICE events in the future.

• Korean Association of Arts Management
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• 제53호
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• pp.207-247
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• 2020

is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

• Journal of the Korea institute for structural maintenance and inspection
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• 제25권6호
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• pp.154-160
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• 2021

Recently, there have been increasing construction works carried out in urban centers, which are inducing frequent artificial vibration in the vicinity of existing structures due to such construction works. moreover, in case of industrial estates, vibration is induced due to operation of machines in the surrounding areas, thereby causing problems. meanwhile, in case of ordinary concrete that compose structure has low level of damping capability for vibration. accordingly, there are difficulties in blocking a wide range of vibrations delivered to the structures from outside including not only vibrations generated in the structures themselves but also ground vibration. recently, numerous studies are being carried out actively on high-damping system that markedly enhanced the damping performances of structures by utilizing polymer concrete in order to block the vibrations delivered to the structures through ground. therefore, this study compared the performances of polymer concrete with those of ordinary concrete, polyurethane pad and foamed rubber pad in order to review its performances in reducing ground vibration. for this purpose, review of FRF and vibration acceleration as dynamic characteristics was made. after comparative verification on the dynamic characteristics is made when polymer concrete and other aforementioned materials are applied to underground structures, the possibility of application of polymer concrete to structures is reviewed.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제32권5호
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• pp.1019-1034
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• 2022

Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

• The Journal of the Korea institute of electronic communication sciences
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• 제18권1호
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• pp.45-52
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• 2023

The power generation method using expensive diesel has operation problems such as high cost diesel generator and a lack of reserved power due to increase of power demand in some islands, requiring expansion of power generation facilities. To solve this problems, it is necessary to improve the efficiency of power generation facilities through an ORC(Organic Rankin Cycle) system application that uses waste heat as a heat source. Therefore, localized application technology of price competitive and highly reliable ORC power generation system is needed, and optimization technology of generators is having great effect, so this study performed two generator designs to get a high-efficiency generator with an optimized 30kW output. The comparison of simulation data for two designed models showed that a generator with SPM factor of 46.2% had an efficiency of 92.1% and a power ouput of about 23.2kW based on 12,000rpm, a generator with SPM factor of 44.46%, had a power output of 27.9kW and efficiency of 93.6% based on above rpm. For the verification of improved design model with SPM factor of 44.46%, the prototype test system with 110kW motor dynamometer was installed and got to the efficiency of 92.08% with conditions of the rated capacity 25kW at 12,000rpm, the test results of prototype generator showed the validity of generator design.

• Journal of the Society of Disaster Information
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• 제19권1호
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• pp.195-203
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• 2023

Purpose: This study intends to check validity of tools for awareness of Business Continuity through measurement and analysis on the sub factors of Business Continuity by employees of railway-related organizations. Method: Based on the preceding study, sub factors of the awareness of Business Continuity are divided into 7 and the total of 29 questions were delivered to employees of railway-related organizations for investigation and analysis through the online survey tool. Result: According to EFA result, the number of factors of awareness of Business Continuity based on the theoretical ground was reduced to 7 and the total coefficient of determination was 82.616%. Checking the questions by factor, all the questions were loaded as intended. Conclusion: Validity of measurement tools of Business Continuity whose sub factors are the Context of Organization, Leadership, Planning, Operation, Support, Performance evaluation, and Improvement for railway organizations were secured through the Exploratory Factor Analysis of this study. As for the further tasks, studies on the structural relationship among internalization of business continuity, organization effectiveness, learning support environment, etc are required.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제16권1호
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• KIPS Transactions on Software and Data Engineering
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• 제12권4호
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.