• Asian Journal of Innovation and Policy
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• 제5권3호
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• pp.275-292
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• 2016

Many countries set growth engine technologies and industries for economic growth and job creation. Each country always wants to know their technological or industrial position in the world in these industries. This study aims at identifying the worldwide position of 19 growth engine industries defined in Korean government. The methods are quantitative by counting the number of startup companies in the world. The ORBIS database was used to extract the number. Therefore, this article may be the first research for the world appearance of growth engine industries and its comparison between world and G7, and between G7 countries. Also, this may be the first study using the ORBIS database on the analysis of certain technology industries. Further, we showed a method to identify world features of technology industries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1690-1707
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• 2021

Precipitation prediction during flood season has been a key task of climate prediction for a long time. This type of prediction is linked with the national economy and people's livelihood, and is also one of the difficult problems in climatology. At present, there are some precipitation forecast models for the flood season, but there are also some deviations from these models, which makes it difficult to forecast accurately. In this paper, based on the measured precipitation data from the flood season from 1993 to 2019 and the precipitation return data of CWRF, ANN cycle modeling and a weighted integration method is used to correct the CWRF used in today's operational systems. The MAE and TCC of the precipitation forecast in the flood season are used to check the prediction performance of the proposed algorithm model. The results demonstrate a good correction effect for the proposed algorithm. In particular, the MAE error of the new algorithm is reduced by about 50%, while the time correlation TCC is improved by about 40%. Therefore, both the generalization of the correction results and the prediction performance are improved.

• 한국운동역학회지
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• 제32권3호
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• pp.69-79
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• 2022

Objective: The purpose of this study is to analyze trends related to sports and artificial intelligence (AI) to understand the trends and how they change according to time, and to establish methods to apply AI in sports. Both macro and micro perspectives related to sports utilization of AI were analyzed. Method: In this study, after analyzing and discussing various information related to the use of artificial intelligence in the sports through a search of academic journals, papers, books, and websites published recently at nationally and internationally, the application plan of artificial intelligence in the sports field was presented. Results: 1) Motion analysis technology using artificial intelligence is effective in sports where posture is important, and if it provides systematic feedback and training methods, it can help improve performance. 2) The introduction of a sports referee judgment system using artificial intelligence is expected to improve performance by restoring factual judgment and objective fairness in sports games. 3) Artificial intelligence will provide coaching staff and players with a variety of information to help improve performance through systematic coaching and improving feedback and enhanced training methods. 4) It is judged that artificial intelligence-related to sports ethics, sports ICT, sports marketing, sports prediction, etc. We think that based on the current AI research trends will have a positive impact on all sports-related areas, helping to revitalize sports. Conclusion: Motion analysis technology using artificial intelligence, sports referee judgment system, coaching using artificial intelligence, and artificial intelligence are judged to have a positive effect on all sports-related areas and help revitalize sports.

• 한국산업정보학회논문지
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• 제23권3호
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• pp.87-95
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• 2018

최근 인공지능(Artificial Intelligence; A.I.)의 기술 발전과 함께 이에 대한 관심이 증가하고 있으며 관련 시장도 비약적으로 확대되고 있다. 아직은 초기단계이지만 2000년 이후 현재까지 계속 확장되고 있는 인공지능 기술 분야의 연구방향과 투자 분야에 대한 불확실성을 줄이는 것이 중요한 시점이다. 이러한 기술 변화와 시대적 요구에 따라서 본 연구는 빅데이터(Big Data) 분석방법 중 텍스트 마이닝(Text Mining)과 토픽모델링(Topic Modeling)을 활용하여 기술동향을 살펴보고, 핵심기술과 성장 가능성이 있는 연구의 향후 방향성을 제시하였다. 본 연구의 결과로부터 인공지능의 기술동향에 대한 이해를 바탕으로 향후 연구 방향에 대한 새로운 시사점을 도출할 수 있으리라 기대한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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• pp.2328-2344
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• 2022

2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.

• ETRI Journal
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• 제45권2호
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• pp.254-266
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• 2023

This paper investigates the effect of hardware impairments (HIs) and imperfect channel state information (ICSI) on a SWIPT-assisted adaptive nonorthogonal multiple access (NOMA)/orthogonal multiple access (OMA) system over independent and nonidentical Rayleigh fading channels. In the NOMA mode, the energy-constrained near users act as a relay to improve the performance for the far users. The OMA transmission mode is adopted to avoid a complete outage when NOMA is infeasible. The best user selection scheme is considered to maximize the energy harvested and avoid error propagation. To characterize the performance of the proposed systems, closed-form and asymptotic expressions of the outage probability for both near and far users are studied. Moreover, exact and approximate expressions of the ergodic rate for near and far users are investigated. Simulation results are provided to verify our theoretical analysis and confirm the superiority of the proposed NOMA/OMA scheme in comparison with the conventional NOMA and OMA protocol with/without HIs and ICSI.

• International Journal of Advanced Culture Technology
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• 제8권1호
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• pp.165-172
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• 2020

Industrial Revolution means the improvement of productivity through technological innovation and has been a driving force of the whole change of economic system and social structure as the characteristic of technology as the tool of this productivity has changed. Since the first industrial revolution of the 18th century, productivity efficiency has been advanced through three industrial revolutions so far, and this fourth industrial revolution is expected to bring about another revolution of production. In this study, the demand for the introduction of artificial intelligence(AI) technology has been increasing in various business fields due to the rapid development of ICT technology, and the classification of HS(harmonized commodity description and coding system) items has been decided using artificial intelligence technology, which is the core of the fourth industrial revolution. And it is enough to construct HS classification system based on AI technology using inference and deep learning. Performing the HS item classification is not an easy task. Implementation of item classification system using artificial intelligence technology to analyze information of HS item classification which is performed manually by the current person more accurately and without any mistake, And the customs administrations, customs offices, and customs agencies, it is expected to be highly utilized in the innovation of trade practice and the customs administration innovation FTA origin agent.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.35-38
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• 2021

The article discusses approaches to the definition and understanding of artificial intelligence, research directions in the field of artificial intelligence; artificial intelligence in the anthropological dimension; the importance of the systems approach as a methodological basis for the design of intelligent systems; structural and functional components of intelligent systems; intelligent systems in the technological aspect; problems and prospects of relations in the system "man - intellectual system".

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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• pp.457-460
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• 2023

본 연구는 시설작물의 병충해 진단을 위해 딥러닝 모델을 응용한 인공지능 서비스 앱, Dr. Vegetable을 제안하고자 한다. 농업 현장에서 숙련된 농부는 한눈에 농작물의 병충해를 판단할 수 있지만 미숙련된 농부는 병충해 피해를 발견하더라도 그 종류와 해결 방법을 찾아내기가 매우 어렵다. 또한 아무리 숙련된 농부라고 할지라도 육안검사만으로 병충해를 조기에 발견하는 것은 쉽지 않다. 한편 시설작물의 경우 병충해에 의한 연쇄피해가 발생할 우려가 있으므로 병충해의 조기 발견 및 방제가 매우 중요하다. 즉, 농부의 경험에 따른 농작물 병해충 진단은 정확성을 장담할 수 없으며 비용과 시간적인 측면에서 위험성이 높다고 할 수 있다. 본 논문에서는 YOLOv5를 활용하여 상추, 고추, 토마토 등 농작물의 병충해를 진단하는 인공지능 서비스를 제안한다. 특히 한국지능정보사회진흥원이 운영하고 있는 AI 통합 플랫폼인 AI 허브에서 제공하는 노지 작물 질병 및 해충 진단 이미지를 사용하여 딥러닝 모델을 학습하였다. 본 연구를 통해 개발된 모바일 어플리케이션을 이용하여 실제 시설농장에서 병충해 진단 서비스를 적용한 결과 약 86%의 정확도, F1 Score 0.84, 그리고 0.98의 mAP 값을 얻을 수 있었다. 본 연구에서 개발한 병충해 진단 딥러닝 모델을 다양한 조도에서 강인하게 동작하도록 개선한다면 농업 현장에서 널리 활용될 수 있을 것으로 기대한다.

• 디지털융복합연구
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• 제18권7호
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• pp.73-84
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• 2020

지능정보기술로 인해 나타날 경제·사회의 혁신적 변화에 대응하기 위해 전 세계가 범국가적으로 다양한 노력을 기울이고 있다. 이에 본 연구는 지능정보사회에서 국가 공무원에게 요구되는 지능정보화 역량을 정의하고, 지능정보화 역량을 구성하는 요소들을 파악하여 역량군과 그에 따른 세부역량을 도출하고자 하였다. 이를 위해 우선 블룸의 디지털 텍사노미에 관한 선행연구, 정보화 역량 및 국가 ICT 관련 정책에 대한 문헌분석을 실시하였고, 블룸의 디지털 텍사노미 관점을 본 연구에 맞게 수정·보완하여 이를 기준으로 지능정보사회에서 국가 공무원에게 요구되는 지능정보화 역량을 정의하고, 잠정적 역량 구성요소를 도출하였다. 그리고 5명의 교육(공)학 및 정보화 전문가, 정보화 업무 담당 공무원을 대상으로 전문가 검토를 실시하였고 그 결과, 7개 역량군에서 22가지 역량이 도출되었다. 본 연구를 통해 도출된 지능정보화 역량은 국가 지능정보화 인적역량개발을 강화하고 활성화하기 위한 기초자료로 유용하게 사용될 것으로 기대한다.