• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.119-129
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• 2021

The process of constructing the DB in the current geotechnical information DB system needs a lot of human and time resource consumption. In addition, it causes accuracy problems frequently because the current input method is a person viewing the PDF and directly inputting the results. Therefore, this study proposes building an automatic digital DB using AI (artificial intelligence) of boring logs. In order to automatically construct DB for various boring log formats without exception, the boring log forms were classified using the deep learning model ResNet 34 for a total of 6 boring log forms. As a result, the overall accuracy was 99.7, and the ROC_AUC score was 1.0, which separated the boring log forms with very high performance. After that, the text in the PDF is automatically read using the robotic processing automation technique fine-tuned for each form. Furthermore, the general information, strata information, and standard penetration test information were extracted, separated, and saved in the same format provided by the geotechnical information DB system. Finally, the information in the boring log was automatically converted into a DB at a speed of 140 pages per second.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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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.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.1-6
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• 2020

In this paper, we propose a new program for university student's IT leadership renovation. Automation and Artificial Intelligence(AI) are changing the nature of work. According to MGI report, they will change the skills needed in the workforce. Leadership is one of the skills needed more of in the future at workplace including IT industry. Leadership could be defined as having 5 level leadership. According to the 5 level leadership, a program was formulated to renovate university student's self-leadership, teamwork, team leadership and finally global leadership. We named the program as Stepping-Stone Platform for Student's IT Leadership Renovation(SSP-SLR). Each level of four stepping stones consists of one semester. Student can raise their leadership skills by the program step by step. Various instruction learning methodologies are adopted to the program, including Flipped learning which has been proved effective in many ways in the field of education recently.

• Speech Sciences
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• v.9 no.1
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• pp.149-171
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• 2002

After establishing the rules for the phonetic transcription in French, quantitative analysis on the given text, Waiting for Godot, is performed. Analyzing the text by investigating the influence of phoneme distribution is very interesting in the phonostylistic point of view. Since the phonetic transcription rules are useful for its automation, the rules are carefully established in this paper. From the results of the phonetic transcription, we can investigate the distribution of individual phonemes and the different phoneme groups between dialogues and scenery indications for various characters.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.407-408
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• 2017

최근 IoT, AI, Big-data 등 4차 산업혁명기술이 다양한 산업영역에 적용되고 있다. 건설산업에도 4차 산업혁명기술 도입을 위한 다양한 연구들이 진행되고 있으며, 토목 및 건축을 포함한 다양한 건설사업 초기단계에 적용되는 토공사의 자동화를 위한 연구가 국내외에서 활발히 진행되고 있다. 본 연구에서는 토공사 자동화를 위한 기초정보를 제공하기 위해 지반지형을 디지털화하고 이를 건설산업 초기 단계에 활용하기 위한 형태를 제시하고자 한다. 지반지형 디지털화를 위해서는 현장계측, 계측데이터 정합, 건설정보 입력, 분석단위 생성 등의 기능이 요구된다. 토공지형 디지털화 기술은 향후 토공사 자동화를 위한 건설장비군의 효율적 운영을 위해 활용될 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.894-897
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• 2014

The speed of processes and the extremely large amount of data to be used in Intelligence Transportations System (ITS) cannot be handling by humans without considerable automation. However, it is difficult to develop software with conventional fixed algorithms (hard-wired logic on decision making level) for effectively manipulate dynamically evolving real time transportation environment. This situation can be resolved by applying methods of artificial intelligence and data mining that provide flexibility and learning capability. This paper presents a brief introduction of data mining and artificial intelligence (AI) applications in Intelligence Transportation System (ITS), analyzing the prospects of enhancing the capabilities by means of knowledge discovery and accumulating intelligence to support in decision making.

• Journal of Engineering Education Research
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• v.24 no.2
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• pp.61-67
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• 2021

The creative problem-solving becomes one of the most important cognitive skills in the engineering education. As AI and automation technology(of 4th Industrial Revolution) penetrate our everyday life, its role as a human ability is highlighted. In this paper, we examine the relation between the creative problem-solving and the critical thinking, and the usefulness of the latter in the engineering education. To sum up, the critical thinking is the pre-conditon of the creative problem-solving.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1478-1481
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• 2019

As core technologies(IoT, 5G, Cloud, Bigdata, AI etc) leading the Fourth Industrial Revolution promote smart convergence across the national socio-economic infrastructure, the threat of new forms of cyber attacks is increasing and the possibility of massive damage is also increasing. Reflecting this trend, cyber security is expanding from simple information protection to CPS(Cyber Physical System) protection that combines safety and security that implements hyper-connectivity and ultra-reliability. This study introduces the recent evolution of cyber attacks and looks at the next generation cyber security technologies based on the conceptual changes of cyber security technologies such as SOAR(Security Orchestration, Automation and Response) and Zero Trust.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.1-12
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• 2021

The competition to lead the next generation of mobile technologies, 6G, is underway while the deployment of 5G has not been implemented worldwide. ITU-R plans to develop technical requirements and standards after completing the 6G Vision by 2023. It can be considered too early to have a concrete view of the 6G core network architecture from this timeline. However, major stakeholders have started making their presence felt by publishing their views. From updated analysis on the technology and service trends proposed, we present a list of research directions on 6G core network from several perspectives: distribution of network functions to nearer edge locations; future fixed-mobile convergence, including low earth orbit satellites; highly-precise QoS guarantee; supporting an extremely wide variety of service requirements; AI-native automation and intelligence; and aligning with the evolution of radio access network.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.5
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• pp.241-248
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• 2023

GAN (Generative Adversarial Networks) creates highly sophisticated counterfeit products by learning real images or text and inferring commonalities. Therefore, it can be useful in fields that require the creation of large-scale images or graphics. In this paper, we implement GAN-based game character creation AI that can dramatically reduce illustration design work costs by providing expansion and automation of game character image creation. This is very efficient in game development as it allows mass production of various character images at low cost.