• International Journal of Internet, Broadcasting and Communication
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• 제8권4호
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• pp.39-47
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• 2016

This study is a smart tourism research based on face recognition applied system that manages individual information of foreign tourists to smartphone. It is a way to authenticate by using face recognition, which is biometric information, as a technology applied to identification inquiry, immigration control, etc. and it is designed so that tourism companies can provide customized service to customers by applying algorism to smartphone. The smart tourism system based on face recognition is a system that prepares the reception service by sending the information to smartphone of tourist service company guide in real time after taking faces of foreign tourists who enter Korea for the first time with glasses attached to the camera. The smart tourism based on face recognition is personal information recognition technology, speech recognition technology, sensing technology, artificial intelligence personal information recognition technology, etc. Especially, artificial intelligence personal information recognition technology is a system that enables the tourism service company to implement the self-promotion function to commemorate the visit of foreign tourists and that enables tourists to participate in events and experience them directly. Since the application of smart tourism based on face recognition can utilize unique facial data and image features, it can be beneficially utilized for service companies that require accurate user authentication and service companies that prioritize security. However, in terms of sharing information by government organizations and private companies, preemptive measures such as the introduction of security systems should be taken.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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• pp.53-56
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• 2021

국내 산업화가 들어선 후 산업화 당시 지었던 낙후된 건물의 증가에 따라 구조물의 손상 조사 및 검사 방법의 수요가 늘어나고 있다. 일반적으로 구조물의 손상은 전문 검사원이 현장에서 직접 측량도구와 시각적인 방식으로 검사한다. 그러나 전문 검사원들이 직접 조사하는 수고에 비해 균열을 검사하는 방식 자체가 단순하고, 일반 사람이 검사하기에는 객관성이 떨어지는 한계가 있어 균열을 자동적으로 검출함으로써 객관성과 편의성을 보장할 기술이 필요하다. 본 연구에서는 이미지 기반으로 다양한 환경에서의 외벽 균열을 검출할 수 있는 딥러닝 모델 개발을 소개한다. 균열 검출을 위해 다양한 외벽 균열 관련 데이터셋을 확보 및 구축하고 각 데이터셋의 검출 정보를 보완할 반자동(semi-auto) 라벨링 작업을 수행하였다. 두 번째로 기존 높은 검출 성능을 보였던 모델들을 선정 및 비교하여 YOLO v5 모델을 최종적으로 선정하였고, 도메인이 각각 다른 데이터셋에 대한 교차 학습을 통해 각 데이터셋의 mAP의 편차가 31%에서 11%로 좁히는 작업을 수행하였다. 이를 통해 실제 상황에서의 균열 영상에서 균열을 검출할 수 있는 측량 시스템을 개발함으로써 실질적인 검사의 도구로 활용될 수 있길 기대한다.

• The Journal of Asian Finance, Economics and Business
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• 제9권5호
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• pp.225-237
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• 2022

The term "artificial intelligence" is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study's objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

• 대한통합의학회지
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• 제11권4호
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• pp.115-124
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• 2023

Purpose : This study investigated the effects of nursing students' emotional intelligence and interpersonal competence on their caring efficacy. Methods : This study surveyed 217 junior and senior nursing students from City B in South Korea between June 1 and June 30, 2023. The SPSS 22.0 program was employed to analyze the collected data by computing the frequency, percentage, mean, and standard deviation, as well as by conducting t-test, ANOVA test, Scheffe's test, Pearson correlation coefficient, and a multivariate regression analysis. Results : The nursing students exhibited an average emotional intelligence of 5.31±.78, interpersonal competence of 3.47±.56, and caring efficacy of 4.02±.62. The students' emotional intelligence showed significant differences in terms of satisfaction with their major (p<.001), satisfaction with the clinical practice (p<.001), satisfaction with their relationship with clinical practice instructors (p=.001), and the standard of living (p=.021). Furthermore, a significant difference in interpersonal competence was observed in terms of the students' satisfaction with their major (p=.003), satisfaction with the clinical practice (p=.001), satisfaction with their relationship with clinical practice instructors (p=.002), and subjective mental health (p=.005). Meanwhile caring efficacy demonstrated a significant difference with regard to the grade level (p=.001), satisfaction with the major (p<.001), satisfaction with the clinical practice (p<.001), satisfaction with their relationship with clinical practice instructors (p=.007), subjective mental health (p<.001), and subjective physical health (p=.047). The factors that affected the caring efficacy included interpersonal competence (p=.002), grade level (p<.001), satisfaction with the major (p=.004), and emotional intelligence (p=.020), all of which together accounted for an explanatory power of 22.3 %. Conclusion : Based on the results of this study, it is evident that further research related to the emotional intelligence, interpersonal competence, and caring efficacy of nursing students must be encouraged in the future. Furthermore efforts should be made to develop appropriate programs aimed at enhancing nursing students' caring efficacy by accounting for their emotional intelligence and interpersonal competence.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.204-214
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• 2017

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

• 한국빅데이터학회지
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• 제6권2호
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• pp.99-108
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• 2021

최근, 예상치 못하고 지능적인 보다 고도화된 사이버 의료 위협 공격이 증가하고 있는 추세이다. 하지만 다양한 패턴의 사이버 의료 위협 공격 대응에 있어, 물리적인 차단과 의료기기 교체와 같은 규칙 기반 보안방법론은 인력 부족, 고가의 비용 부담 등의 한계를 지닌다. 이를 해결하기 위한 방안으로 최근 의료계에서도 인공지능 기술에 주목하고 있다. 인공지능 기술은 기존의 규칙 기반의 보안 프로그램과는 달리 과거의 이상행태를 스스로 학습하여 보안 위협 감지 및 예측을 가능케 하는 기술이다. 본 연구에서는 의료기관 통합의료정보시스템 내 의료정보 데이터를 수집 및 학습하여 AI 기반 네트워킹 행동 적응형 정보 플랫폼 개발 연구 방법론에 대한 소개를 포함한다. 이를 통해 규칙 기반의 보안 프로그램의 기술적 제반사항 소개와 제약 사항 대비 의료정보분야에서의 인공지능 기술을 활성화하기 위한 전략에 대해 논의한다.

• Asia pacific journal of information systems
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• 제33권4호
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• pp.1058-1092
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• 2023

This study investigates the perception and adoption of ChatGPT (a large language model (LLM)-based chatbot created by OpenAI) among Korean users and assesses its potential as the next disruptive innovation. Drawing on previous literature, the study proposes perceived intelligence and perceived anthropomorphism as key differentiating factors of ChatGPT from earlier AI-based chatbots. Four individual motives (i.e., perceived usefulness, ease of use, enjoyment, and trust) and two societal motives (social influence and AI anxiety) were identified as antecedents of ChatGPT acceptance. A survey was conducted within two Korean online communities related to artificial intelligence, the findings of which confirm that ChatGPT is being used for both utilitarian and hedonic purposes, and that perceived usefulness and enjoyment positively impact the behavioral intention to adopt the chatbot. However, unlike prior expectations, perceived ease-of-use was not shown to exert significant influence on behavioral intention. Moreover, trust was not found to be a significant influencer to behavioral intention, and while social influence played a substantial role in adoption intention and perceived usefulness, AI anxiety did not show a significant effect. The study confirmed that perceived intelligence and perceived anthropomorphism are constructs that influence the individual factors that influence behavioral intention to adopt and highlights the need for future research to deconstruct and explore the factors that make ChatGPT "enjoyable" and "easy to use" and to better understand its potential as a disruptive technology. Service developers and LLM providers are advised to design user-centric applications, focus on user-friendliness, acknowledge that building trust takes time, and recognize the role of social influence in adoption.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.505-508
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• 2022

인공지능은 존재 자체로서 기술의 약진이라는 가치를 가지며, 여러 산업 분야에 이용되어 각종 산업에서 생산하는 상품 및 서비스의 부가 가치를 증진시키는 역할을 한다. 따라서 인공지능과 관련된 규제와 정책에 대해서 보다 넓은 시각에서 고려되어야 한다. 그러나 연구자 간 이해도가 상이하며, 어떻게 인공지능을 규제할지에 대한 합의는 이뤄지지 않고 있다. 이에 인공지능 기술에 대한 정부규제 방향을 탐색적으로 고찰해 본다. 먼저 인공지능 규제의 목표로 책무성, 투명성, 안정성, 공정성을 도출하고 규제 범위로 시스템 자체, 개발과정 및 활용 과정을 설정하며, 이용자와 개발자가 규제의 준수 대상임을 보인다. 본 연구의 학술적 의의는 인공지능 현재 기술수준을 분석하여 이를 바탕으로 향후 일관된 인공지능 규제 논의의 기반을 마련한 것으로 볼 수 있다. 인공지능 개발에서 응용에 이르는 생애주기를 고려할 때, 중요한 것은 인공지능 산업을 촉진하기 위한 진흥 정책과 그에 따른 리스크에 대해 대응하는 규제 정책의 균형이다. 개발자, 기업 및 사용자 등 모든 참여 주체에게 긍정적인 방향으로 인공지능이 수용될 수 있는 체계를 마련하는 것이 인공지능과 관련된 법학의 목표이다.

• 한국산학기술학회논문지
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• 제9권2호
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• pp.431-448
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• 2008

경영패러다임의 변화는 오늘날 기술발전에 따른 정보기술 변화를 기업경영에 적극적으로 수용해야 한다는 것이며, 경영층에서 불확실한 경영환경에 보다 민첩하게 적응하며, 실시간으로 분석되는 정보를 기반으로 의사결정을 하여야 하는 것을 의미한다. 이것은 최근 기업의 효과적 목표달성과 효율적 업무생산성을 확보 할 수 있는 근간이 되며, 이에 따른 기업정보시스템으로써의 비즈니스 인텔리전스의 도입은 기업의 필수적인 요소가 되고 있다. 따라서 비즈니스 인텔리전스 시스템을 구축하고자 하는 기업들에게 경영성과에 보다 효과적으로 영향을 미칠 수 있는 핵심성공요인을 도출해 주는 것은 매우 의미 있을 것이다. 본 연구에서는 이론연구를 바탕으로 설정된 연구모형과 연구가설을 설문조사 및 통계분석을 진행하여 연구가설을 검정하고 그 결과를 분석하여 성공요인들 간의 관계를 규명해 준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1989-2011
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• 2019

Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.