• International Journal of Internet, Broadcasting and Communication
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• 제16권1호
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• pp.182-190
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• 2024

Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

• 한국컴퓨터정보학회논문지
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• 제26권1호
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• pp.275-281
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• 2021

본 연구의 목적은 인공지능예술작품 구매할 때 소비자들이 어떤 감지가 있는지, 그리고 구매의 향과 어떤 관계가 있는지 살펴보는데 있다. 본 연구에서 고객감지가치가 제품감지가치, 서비스감지가치 그리고 사회감지가치 총 3가지를 제시하였다. 이를 바탕으로 고객감지가치와 구매의향 간의 모델을 구축하였다. 연구를 위해 데이터 수집은 온라인 설문 조사를 실시하였다. SPSS24.0와 AMOS24.0을 통해 수집한 데이터의 신뢰성, 타당성 및 구조 방정식 분석을 통해 가설 검증을 하였다. 검정결과를 보면 제품인지가치와 서비스인지가치는 소비자의 온라인 구매의향에 긍정적인 영향을 미친다. 그러나 사회인지가치가 소비자의 구매의향에 영향을 주지 않는 결과가 나타났다.

• 근관절건강학회지
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• 제28권3호
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• pp.217-222
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• 2021

Background: The reaction of nurses to the advent of artificial intelligence (AI) during the fourth industrial revolution era remains questionable. Understanding Florence Nightingale's achievements may provide valuable lessons that will be helpful to contemporary nurses. Aims: To understand Nightingale's nursing philosophy and methods and provide suggestions for future nursing practice, education, research, and health policy. Source of evidence: Literature. Discussion/Conclusion: Just as Nightingale captured the situation of her time and introduced latest scientific methods, modern nurses need to learn from Nightingale's drastic actions to meet social needs. Nursing can regain a solid humanistic foundation by returning to core values of nursing and humanities, while simultaneously adopting state-of-the-art technologies. Implications for Nursing Policy: AI-driven technologies will advance nursing services and provide greater human-centered and personalized care by eliminating iterative and labor-intensive tasks. Nursing educational policy should support the advancement of nursing curricula to develop AI competencies and specialists within the nursing field.

• ETRI Journal
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• 제46권3호
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• pp.501-512
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• 2024

With an explosive increase of data produced annually, researchers have been attempting to develop solutions for systems that can effectively handle large amounts of data. Single-operating-system (OS) non-uniform memory access (NUMA) abstraction technology is an important technology that ensures the compatibility of single-node programming interfaces across multiple nodes owing to its higher cost efficiency compared with scale-up systems. However, existing technologies have not been successful in optimizing user performance. In this paper, we introduce a single-OS NUMA abstraction technology that ensures full compatibility with the existing OS while improving the performance at both hypervisor and guest levels. Benchmark results show that the proposed technique can improve performance by up to 4.74× on average in terms of execution time compared with the existing state-of-the-art opensource technology.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.85-91
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• 2024

Currently, generative artificial intelligence is a hot topic around the world. Generative artificial intelligence creates various images, art, video clips, advertisements, etc. The problem is that it is very difficult to verify the internal work of artificial intelligence. As a requirements engineer, I attempt to create a toon image by applying linguistic mechanisms to the current issue. This is combined with the UML object model through the semantic role analysis technique of linguists Chomsky and Fillmore. Then, the derived properties are linked to the toon creation template. This is to ensure productivity based on reusability rather than creativity in toon engineering. In the future, we plan to increase toon image productivity by incorporating software development processes and reusability.

• Clinical Endoscopy
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• 제55권5호
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• pp.594-604
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• 2022

Over the past decade, technological advances in deep learning have led to the introduction of artificial intelligence (AI) in medical imaging. The most commonly used structure in image recognition is the convolutional neural network, which mimics the action of the human visual cortex. The applications of AI in gastrointestinal endoscopy are diverse. Computer-aided diagnosis has achieved remarkable outcomes with recent improvements in machine-learning techniques and advances in computer performance. Despite some hurdles, the implementation of AI-assisted clinical practice is expected to aid endoscopists in real-time decision-making. In this summary, we reviewed state-of-the-art AI in the field of gastrointestinal endoscopy and offered a practical guide for building a learning image dataset for algorithm development.

• Steel and Composite Structures
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• 제53권1호
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• pp.115-121
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• 2024

The present paper deals with a comprehensive study about dynamic performance and educational economic assessment of nanocomposite structures, while it focuses on truncated conical shells. Advanced structure dynamic behavior has been analyzed by means of AI techniques, which allow one to predict and optimize their performances with good accuracy for different loading and environmental conditions. The incorporation of the AI method significantly enhances the computational efficiency and is a powerful tool in designing nanocomposites and for their structural analysis. Further, an educational assessment is provided in the context of cost and practicality related to such structures in engineering education. This study showcases the capabilities of AI-enabled methods with regard to cost reduction, improvement of structural efficiency, and enhancement of learning engagement for students through certain practical examples on state-of-the-art nanocomposite technology. The results also confirm a remarkable capability of artificial intelligence regarding the optimization of both dynamic and economic aspects, which could be highly valued for further development of nanocomposite structures.

• 방송공학회논문지
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• 제26권5호
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• pp.533-542
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• 2021

본 연구에서는 한국 전통예술 중 하나인 진도 북춤을 다양한 인공지능 기술을 이용하여 디지털 아트로 재창조하는 과정을 제안하였다. 인공지능 언어 분석 기술을 통해 정량화된 관객들의 감정 데이터는 프로젝션 맵핑 공연에서 다양한 오브젝트 형태로 개입하여 큰 스토리에 변화를 주지 않는 선에서 영향을 준다. 대부분의 인터렉티브 아트들이 공연자와 영상 간의 소통을 표현한 것이라면, 본 공연은 인공지능 감정분석 기술을 중심으로 관객이 작품과 직접 소통할 수 있는 새로운 형태의 반응형 공연이 된다. 이는 한국 전통예술에서만 흔히 나타나는 관객이 공연에 직간접적으로 개입하여 영향을 끼치는 퍼포먼스인 '추임새'에서 시작된다. 공연자의 '프롤로그'에 담긴 감정 정보를 기반으로 관객의 감정 정보와 결합하여, 공연에 쓰이는 이미지와 파티클의 형태로 변환함으로서 공연에 관객이 간접적으로 참여하고 변화를 줄 수 있는 형태가 된다.

• ETRI Journal
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• 제44권6호
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• pp.1004-1019
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• 2022

For autonomous driving without high-definition maps, we present a model capable of generating multiple plausible paths from egocentric images for autonomous vehicles. Our generative model comprises two neural networks: feature extraction network (FEN) and path generation network (PGN). The FEN extracts meaningful features from an egocentric image, whereas the PGN generates multiple paths from the features, given a driving intention and speed. To ensure that the paths generated are plausible and consistent with the intention, we introduce an attentive discriminator and train it with the PGN under a generative adversarial network framework. Furthermore, we devise an interaction model between the positions in the paths and the intentions hidden in the positions and design a novel PGN architecture that reflects the interaction model for improving the accuracy and diversity of the generated paths. Finally, we introduce ETRIDriving, a dataset for autonomous driving, in which the recorded sensor data are labeled with discrete high-level driving actions, and demonstrate the state-of-the-art performance of the proposed model on ETRIDriving in terms of accuracy and diversity.

• 실천공학교육논문지
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• 제13권2호
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• pp.221-232
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• 2021

본 연구는 코로나 19로 인하여 발생한 비대면 수업 환경에서 학습자들의 요구 분석을 토대로 플립 러닝과 메이커 교육 기반 인공지능 융합 교양 교과목의 설계 방향을 탐색하는데 그 목적이 있다. 이를 위해 메이커 교육 기반 인공지능융합 교양 교과목을 수강한 학생들과 수강하지 않은 학생들을 대상으로 플립 러닝에 대한 학생들의 인식과 함께 학습자의 교육 요구도를 조사하였다. 이를 바탕으로 Borich 교육 요구도와 The Locus for Focus Model 모델을 활용하여 교과목 내용 요소에 대한 우선 순위를 분석함으로써 교과목 설계를 위한 기초 자료로 활용하였다. 연구 결과는 다음과 같다. 첫째, 메이커 교육 기반의 인공지능 교양 교과목 내용 요소는 총 9개 영역으로 구성되었으며 플립 러닝을 활용하는 수업으로 설계되었다. 둘째, 교육 요구가 가장 높은 영역은 '인공지능 이론', '인공지능 프로그래밍 실습', '피지컬 컴퓨팅 이론', '피지컬 컴퓨팅 실습'이, 차 순위는 '융합프로젝트', '3D 프린팅 이론', '3D 프린팅 실습'으로 결정되었다. 셋째, 플립 러닝을 활용하여 메이커 교육 기반 인공지능융합 교양 교과목을 운영하는 것은 수강 경험의 유무와 상관없이 대부분 긍정적인 응답이었으며 수강 경험이 있는 학생들의 경우에는 만족도가 매우 높았다. 이를 바탕으로 플립러닝과 메이커교육을 활용한 인공지능 기반의 융합 교양 교과목이 설계되었다. 이는 학생들의 요구를 반영하여 교양 교육에서 인공지능 융합 교육의 기초를 마련하고 대학생의 인공지능 소양 함양의 기회를 제공한다는데 의의가 있다.