• 전자통신동향분석
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• 제32권6호
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• pp.57-65
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• 2017

Neural network based AI computing is a promising technology that reflects the recognition and decision operation of human beings. Early AI computing processors were composed of GPUs and CPUs; however, the dramatic increment of a floating point operation requires an energy efficient AI processor with a highly parallelized architecture. In this paper, we analyze the trends in processor architectures for AI computing. Some architectures are still composed using GPUs. However, they reduce the size of each processing unit by allowing a half precision operation, and raise the processing unit density. Other architectures concentrate on matrix multiplication, and require the construction of dedicated hardware for a fast vector operation. Finally, we propose our own inAB processor architecture and introduce domestic cutting-edge processor design capabilities.

• 공학교육연구
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• 제26권5호
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• pp.17-28
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• 2023

Generative AI has arrived and it's here. Education, research, industry, and labor are all on edge about the changes it will bring. It is noteworthy that while there is a wide range of optimistic and pessimistic predictions about the impact of generative AI, there is more concern than hope when it comes to education. This paper focuses on the lack of discussion on the impact of AI in higher education. First, we reviewed the process of the emergence of generative AI and introduced how the impact of AI is being understood from various perspectives. Second, we classified work areas based on expertise and efficiency and analyzed the impact of AI on work in each area. Finally, the study found that the educational perception of generative AI and the way it is perceived for engineering education purposes can be very different. It also argued that there is a lack of active discussion and debate on areas that need to be specifically discussed around generative AI. This has led to a phenomenon known as professors' delayed indifference. We emphasized that it is time for a serious and realistic discussion on the connection and integration of AI and education.

• 4차산업연구
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• 제2권1호
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• pp.9-17
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• 2022

Purpose -In general, elementary school is the time to take the first social step away from family relationships with parents or siblings. Recently, AI technology has been widely used in everyday life and society. The purpose of this study is to propose a program that can cultivate AI literacy and self-expression for elementary school students according to the trend of the times. Research design, data, and methodology - In this study, prior to developing a self-expression class program for cultivating AI literacy, we looked at the related literature on what AI literacy is. In addition, the digital learning program was analyzed considering that the current AI literacy is based on the cutting edge of digital technology and is located in the same area as digital literacy. Result -This study developed a curriculum for self-expression and AI literacy cultivation. The main feature of this study is that the education program of this study allows 3rd, 4th, and 5th graders of elementary school to express themselves and to express their career problems by combining culture and art with AI programs. Conclusion -Self-expression activity education for cultivating AI literacy should be oriented toward holistic education and should be education as a way to express oneself in order to improve the quality of life of learners

• ETRI Journal
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• 제32권4호
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• pp.614-617
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• 2010

For an antenna-in-package (AiP), via holes are used to connect the antenna ground and system ground. In this letter, a dual-frequency AiP with a U-slot embedded in the patch is proposed. By properly arranging three via holes under the non-radiating edge, an AiP with two resonant frequencies is realized. Then a U-slot is embedded in the patch to further improve the bandwidth of the AiP. To validate the proposed design, an AiP with the bandwidth of 4.49% at 2.45 GHz and 6.02% at 5.32 GHz is achieved and fabricated. The measured results agree with the simulated results.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 춘계학술발표대회
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• pp.78-80
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• 2022

최근 딥러닝을 이용한 영상 분석은 자율주행, 감시카메라 등 다양한 서비스에 필수적으로 활용되고 있으며 실시간 처리 및 보안 요소를 만족하기 위해 기존의 클라우드 컴퓨팅 방식의 단점을 개선한 클라우드 엣지 컴퓨팅 방식을 적용하는 사례가 크게 증가하고 있다. 하지만 사용자 및 단말과 가까운 위치에서 딥러닝 추론을 진행하는 클라우드 엣지 서버는 클라우드 서버와 비교하여 컴퓨팅 자원이 충분하지 않을 경우가 많으며 기존의 딥러닝 모델을 그대로 클라우드 엣지 환경에 적용하는 것은 자원 활용 측면에서 여러가지 문제점들을 갖고 있다. 따라서 본 논문에서는 마이크로서비스 구조를 통해 자원을 보다 유연하게 활용할 수 있도록 개선된 딥러닝 모델로 대규모의 클라이언트 요청을 처리 가능한 동영상 데이터 추론 서비스인 G-Edge AI 추론 서비스 개발에 대해 설명한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.81-83
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• 2023

태양 에너지 수집형 IoT 기기는 주기적으로 재충전되는 태양 에너지의 특성상, 에너지 소모를 최소화하기보다는 수집된 에너지를 최대한 유용하게 사용하는 것이 중요하다. 한편, 데이터 기밀성과 프라이버시, 응답속도, 비용 등의 이유로 클라우드가 아닌 데이터 소스 근처에서 머신러닝을 수행하는 엣지 AI에 대한 연구도 활발한데, 그 중 하나는 여러 IoT 장치들이 수집한 오디오 데이터를 활용하여, 다양한 AI 응용들을 IoT 엣지 컴퓨팅 환경에서 제공하는 것이다. 그러나, 이와 관련된 많은 연구에서, IoT 기기들은 에너지의 제약으로 인하여, 엣지 서버(IoT 서버)로의 센싱 데이터 전송만을 수행하고, 데이터 전처리를 포함한 모든 AI 과정은 엣지 서버에서 수행한다. 이 경우, 엣지 서버의 과부하 문제 뿐 아니라, 학습 및 추론에 불필요한 데이터까지도 서버에 그대로 전송되므로 네트워크 과부하 문제도 야기한다. 또한, 이를 해결하고자, 데이터 전처리 과정을 각 IoT 기기에 모두 맡긴다면, 기기의 에너지 부족으로 정전시간이 증가하는 또 다른 문제가 발생한다. 본 논문에서는 각 IoT 기기의 에너지 상태에 따라 데이터 전처리 여부를 결정함으로써, 기기들의 정전시간 증가 문제를 완화시키면서 서버 집중형 엣지 AI 환경의 문제들(엣지 서버 및 네트워크 과부하)을 완화시키고자 한다. 제안기법에서 IoT 장치는 기기가 기본적으로 동작하는 데 필요한 에너지 외의 여분의 에너지 양을 예측하고, 이 여분의 에너지가 있는 경우에만 이를 사용하여 기기에서 전처리 과정, 즉 수집 대상 소리 판별과 잡음 제거 과정을 거친 후 서버에 전송함으로써, IoT기기의 정전시간에 영향을 주지 않으면서, 에너지 적응적으로 데이터 전처리 위치(IoT기기 또는 엣지 서버)를 결정하여 수행한다.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제11권10호
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• pp.323-332
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• 2022

AI 기술을 활용한 다양한 서비스가 개발되면서, AI 서비스 운영에 많은 관심이 집중되고 있다. 최근에는 AI 기술도 하나의 ICT 서비스를 보고, 범용적인 AI 서비스 운영을 위한 연구가 많이 진행되고 있다. 본 논문에서는 일반적인 기계학습 개발 절차의 마지막 단계인 기계학습 모델 배포 및 운영에 초점을 두고 AI 서비스 운영을 위한 시스템 측면에서의 연구 결과를 기술하였다. 3대의 서로 다른 Ubuntu 시스템을 구축하고, 이 시스템상에서 서로 다른 AI 모델(RFCN, SSD-Mobilenet)과 서로 다른 통신 방식(gRPC, REST)의 조합으로 2017 validation COCO dataset의 데이터를 이용하여 객체 검출 서비스를 Tensorflow serving을 통하여 AI 서비스를 요청하는 부분과 AI 서비스를 수행하는 부분으로 나누어 실험하였다. 다양한 실험을 통하여 AI 모델의 종류가 AI 머신의 통신 방식보다 AI 서비스 추론 시간에 더 큰 영향을 미치고, 객체 검출 AI 서비스의 경우 검출하려는 이미지의 파일 크기보다는 이미지 내의 객체 개수와 복잡도에 따라 AI 서비스 추론 시간이 더 큰 영향을 받는다는 것을 알 수 있었다. 그리고, AI 서비스를 로컬이 아닌 원격에서 수행하면 성능이 좋은 머신이라고 하더라도 로컬에서 수행하는 경우보다 AI 서비스 추론 시간이 더 걸린다는 것을 확인할 수 있었다. 본 연구 결과를 통하여 서비스 목표에 적합한 시스템 설계와 AI 모델 개발 및 효율적인 AI 서비스 운영이 가능해질 것으로 본다.

• Journal of Chest Surgery
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• 제13권4호
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• pp.455-461
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• 1980

This is one case report of surgically treated ventricular septal defect [VSD] with aortic insufficiency [AI] at department of thoracic and cardiovascular surgery, Hanyang university hospital. He had had progressive dyspnea on exertion and palpitation for 3 years prior to admission to our hospital. On examination, the blood pressure was 120/0 mmHg and the pulse rate 88 times/min. Bobbing motion of the head, Water hammer pulse, Corringan`s pulse, Quincke`s pulse and to and fro murmur were present. The heart murmur was consistent with .VSD and AI. Cardiomegaly was seen in chest X-ray. EKG, echocardiogram, aortogram and right heart catheterization was performed. On Sep. 9, 1980, open heart surgery was performed under the impression of VSD with AI. Infracrystal type VSD measuring 2 x 1.5 cm in diameter was closed with Teflon patch graft through the transverse ventriculotomy. AI was due to prolapsed, elongated right coronary and noncoronary cusp, especially noncoronary cusp. The prolapsed, elongated aortic leaflets were plicated by placing three 8-figure sutures between the free edge and the base of the leaflet [Frater`s method] through a transverse aortotomy. Postoperatively, he made an uneventful recovery, his blood pressure was 120/70 mmHg and showed no signs AI or residual shunt at discharge.

• 드라이브 ㆍ 컨트롤
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• 제18권1호
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

• 4차산업연구
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• 제3권1호
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• pp.1-12
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• 2023

Purpose - In Korea, where 64% of the land is forested, mountaineering is a leisure activity enjoyed by the majority of the people. As new technologies named the 4th industrial revolution spread more after the Covid-19 pandemic, we propose a human and technology convergence curriculum for mountaineering and trekking education to enjoy safety in the field of mountaineering and trekking using cutting-edge technology. Research design, data, and methodology - After examining the current state of the mountaineering industry and preceding studies on mountaineering and camping, and learning about BAC the 100 famous mountains, mountaineering gamification, and Gamification We designed an AI convergence curriculum using. Result - Understanding the topography and characteristics of mountains in Korea, acquiring mountaineering information through AI convergence, selecting mountaineering equipment suitable for the season, terrain, and weather, setting educational goals to safely climb, and deriving term project results. A total of 15 A curricula for teaching was proposed. Conclusion - Artificial intelligence technology is applied to the field of mountaineering and trekking and used as a tool, and it is expected that the base of mountaineering will be expanded through safe, efficient, fun, and sustainable education. Through this study, it is expected that the AI convergence education curriculum for mountaineering and trekking will be developed and advanced through several studies.