• Convergence Security Journal
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• v.22 no.1
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• pp.149-158
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• 2022

R.o.K Marine Corps was established on April 15, 1949 at Deoksan Air Base in Jinhae. When they fought in the Korean War and the Vietnam War, they were sure to win, so they were loved and trusted by the people. Strong combat power is only possible when an advanced barracks culture is established. Today's new generation of soldiers have strong characteristics ; self-centered and individualistic. R.o.K Marine Corps officers must understand the characteristics of the new generation of soldiers and strive to develop creative leadership in order to make them utilize their characteristics. In addition, as cutting-edge science and technology develops along with the 4th industrial revolution, R.o.K Marine Corps officers should work hard to acquire professional tactical knowledge and self-development. Therefore, Marine Corps officers should do their best to understand the characteristics of the new generation of soldiers and demonstrate leadership to become a strong force trusted by the people.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.47-57
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• 2020

This paper aims to show the development pattern of the impact of artificial intelligence on the arts and culture according to the scenario analysis, and suggests the direction of the arts and culture content industry in the future. We assume four scenarios based on creativity of artificial intelligence beyond humans and controllability for them, then explore the path leading to each scenario. In addition, for the most ideal route to coexist with artificial intelligence, we propose the provision of safety system for human and artificial intelligence, innovation of the education system, and preemptive investment from now on.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.223-234
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• 2021

Recent advances in the 4th Industrial Revolution have accelerated the change of the shopping behavior from offline to online. Search queries show customers' information needs most intensively in online shopping. However, there are not many search query research in the field of search, and most of the prior research in the field of search query research has been studied on a limited topic and data-based basis based on researchers' qualitative judgment. To this end, this study defines the type of search query with data-based quantitative methodology by applying machine learning to search research query field to define the 15 topics of search query by conducting topic modeling based on search query and clicked document information. Furthermore, we present a new classification system of new search query types representing searching behavior characteristics by extracting key variables through principal component analysis and analyzing. The results of this study are expected to contribute to the establishment of effective search services and the development of search systems.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.385-392
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• 2022

Our society, which has arrived in the 4th industrial revolution, emphasizes covergence education to cultivate creative convergence talents. Therefore, this study is to develop a convergence education program consistent with the direction of the 2019 revised Nuri course and to help teachers who want to implement convergence education. In order to achieve this purpose, in this study, voluntary questions that occurred in play using the educational robot 'Turtle' were classified as STEAM elements. After that, frequency analysis and correlation analysis were conducted. Therefore, this study is meaningful in collecting children's questions about the same robot by age, and it is valuable in establishing future convergence education directions by analyzing the correlation by STEAM elements.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.15-22
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• 2020

The 4th industrial revolution and the rapid change in the data environment revealed technical limitations in the existing relational database(RDB). As a new analysis method for unstructured data in all fields such as IDC/finance/insurance, interest in graph database(GDB) technology is increasing. The graph database is an efficient technique for expressing interlocked data and analyzing associations in a wide range of networks. This study extended the existing RDB to the GDB model and applied machine learning algorithms (pattern recognition, clustering, path distance, core extraction) to detect new abnormal signs. As a result of the performance analysis, it was confirmed that the performance of abnormal behavior(about 180 times or more) was greatly improved, and that it was possible to extract an abnormal symptom pattern after 5 steps that could not be analyzed by RDB.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.674-679
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• 2017

As the importance of the 4th industrial revolution and ICT technology increased, it became a software centered society. Existing software training was limited to the composition of the learning environment, and a lot of costs were incurred early. In order to solve these problems, a learning method using a web compiler was developed. The web compiler supports various software languages and shows compilation results to the user via the web. However, Web compilers that support artificial intelligence technology are missing. In this paper, we designed and implemented a tensor flow based web compiler, Google's artificial intelligence library. We implemented a system for learning artificial intelligence by building a meteorJS based web server, implementing tensor flow and tensor flow serving, Python Jupyter on a nodeJS based server. It is expected that it can be utilized as a tool for learning artificial intelligence in software centered society.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.135-142
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• 2020

In the recent farming industry, there is a growing diffusion of drones, which are recognized as a crucial technology of the 4 th industrial revolution to cope with aging. Especially, filming and pest control using drones are representative fields that have different age groups for obtaining a national license of multicopter that is a ultra-light flying device, and can create profits after getting a license. However, pest control technology using drones has different spray effects depending on levels of operational proficiency, since this highly relies on an operator's operating skills. It is anticipated that if this issue is supplemented, the use of drones for pest control in the farming industry will diversify. For analysis of spraying characteristics of agricultural pest control drones, this study aims to formulate effective spraying hours and effective spraying intervals and suggest an algorithm, which facilitates an accurate calculation of pest control area depending on the kinds of pest control drones. This algorithm can be used in the field of pest control by improving scatterling issues caused by drone flight methods of drone pest controllers and building an optimum pest control manual in future.

• Convergence Security Journal
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• v.18 no.4
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• pp.62-71
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• 2018

The rapid growth of virtual reality technology in the era of the 4th Industrial Revolution has accelerated scientification of combat training systems in addition to ICT(information and communications technology) in military field. Recently, research and development of simulators based on virtual reality have been actively conducted in order to solve sensitive issues such as increase of civil complaints due to the noise of a shooting range, prevention of shooting accident, and reduction of training cost. In this paper, we propose two key solutions: spatial synchronization method and modified point mass trajectory model with small angle approximation to overcome technical limitations of a current training simulator. A trainee who wears a haptic vest in a mixed reality environment built in MARS(medium-range assault rifle shooting simulator) is able to conduct not only precision shooting but also two-way engagement with virtual opponents. It is possible for trainee to receive more reliable evaluations in the MARS than an existing rifle simulator based on laser.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.491-491
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• 2021

댐·보 운영은 과거부터 많은 양의 데이터를 근간으로 분석 및 의사결정을 진행하였으나, 자연 현상의 복잡성 및 다양한 영향 관계로 인해 기술개발은 답보 상태에 머물러 있다. 또한 댐·보 운영의 기술개발은 개별적인 일부 요소기술에 국한되어 있는 실정으로 댐·보 운영의 전체 의사결정체계에 대한 미래의 방향성에 대한 전략이 부재한 상황이다. 이에 기후변화, 물관리일원화, 환경대응용수의 활용, 복합적 제약사항 도출 등 최적 댐·보 운영을 위한 의사결정지원 고도화에 대한 사회적 니즈가 증가를 반영하고, 기존의 재래적 의사결정지원 시스템 및 홍수분석기술에서 탈피하여 AI, Big Data 등 혁신 기술적용 및 최신기술 트렌드를 반영한 미래 물관리 로드맵의 제시가 필요한 상황이다. 본 연구의 목적은 홍수기 댐운영을 위해 기존 반복 분석하는 일련의 절차 자동화와 운영자의 경험에 따라 달라지는 운영방법의 일반화를 위한 AI의 도입에 있다. 기존 홍수분석체계를 살펴보면 저수지 홍수분석, 저수지 수위계산, 방류량 결정, 분석결과와 제약사항의 비교 같은 일련의 절차에 대해서 합리적인 결과가 도출될 때까지 반복 분석을 수행하여야 한다. 분석모형간 연계와 재래적 방법의 자동화를 도입하면 홍수분석에 소요되는 시간을 줄일 수 있어, 사전에 대비할 수 있는 시간을 추가적으로 확보할 수 있게 된다. 또한 홍수기 댐운영 방법이 운영자의 경험에 의존하다 보니 운영자마다 다른 운영방법을 도출하게 되는데, 과거사례의 최적 운영방안을 학습시킨 AI를 도입하게 되면 일관성있는 최적 댐운영이 가능할 것으로 판단된다. 이에 본 연구에서는 홍수분석 절차의 자동화, DB 및 통계모형 구축, 분석결과 및 제약사항의 직관적인 표출화, AI 도입을 통한 운영방안의 일반화 등 기존 재래기술의 개선을 통해 최적 댐운영 의사결정지원시스템의 고도화를 추진하고자 한다.

• Journal of Venture Innovation
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• v.4 no.3
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• pp.125-139
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• 2021

As the 4th industrial revolution progresses, new technologies and services are being born, growing, and maturing. Now, beyond the mobile era, the metaverse is being discussed as a new paradigm. Therefore, in this study, in preparation for the metaverse era, we tried to analyze what factors have an important influence when consumers want to use new technologies. In particular, the research was conducted focusing on how the context in which consumers use the technology changes depending on whether they are B2C or B2B. For this, augmented reality (AR) was selected in the B2C context by linking the research subject with the metaverse era, and the smart factory was selected in the B2B context. The research model for the analysis was established by deriving and setting common influence variables by reflecting the characteristics of the research target technology based on the modified extended unified theory of acceptance and use of technology. A survey was conducted for empirical analysis, and 150 AR and 150 smart factory subjects were analyzed. The empirical study results are as follows. The relationship between performance expectancy and intention to use, technology readiness and intention to use was found to have a significant positive (+) effect on both AR and smart factory. On the other hand, it was found that effort expectancy, social influence, and trust had a positive (+) effect on intention to use only in AR. Only in smart factory, facilitating conditions had a significant positive (+) effect on intention to use. It was also found that the perceived risk had a significant negative (-) effect on the intention to use only in the smart factory. The results of this study are academically significant in that we empirically test that influencing factors of technology use varies depending on the context in which it is used by consumers. In practice, it provided an implication of what to focus on first is being implemented.