• 과학기술학연구
• /
• 제19권1호
• /
• pp.53-90
• /
• 2019

본 연구는 공공연구기관에서 선도적으로 추진되고 있는 사회문제 해결형 연구개발 사례를 분석하고 그 의미를 논의한다. 사례 분석의 대상은 위생과 환경문제에 대응하여 자원순환형 음식물쓰레기 처리시스템을 구축하는 연구개발사업이다. 사례연구를 통해 드러난 특징은 다음과 같다. 동 사업에서는 빠른 시스템 개발을 위해 C&SD(connect and solution development) 전략을 사용하였다. 그리고 시스템의 경제 사회적 수용성을 높이기 위해 시민, 기존 업체, 지자체와 밀도 있는 네트워크를 형성했다. 또 법 제도 개선 문제도 작은 문제부터 해결해나가는 접근을 취했다. 하향식으로 새로운 시스템을 개발하는 방식보다는 문제해결을 빠르고 쉽게 하기 위해 기존의 기술과 주체들을 활용하는 재조합 혁신 방식을 택했다.

• 한국의료질향상학회지
• /
• 제24권2호
• /
• pp.41-61
• /
• 2018

Purpose: Falls are one of the most frequent health events in medical institutions, however, they can be predicted and prevented. The Quality Improvement Nurse Society clinical practice guideline Steering Committee developed the Clinical Practice Guideline for the assessment and prevention of falls in adult people. The purpose of this study was to assess the risk factors for falls in adults aged 19 years and older, to present an evidence for preventing falls, formulate a recommendations, and indicators for applying the recommendations. Methods: This clinical practice guideline was developed using a 23-step adaptation method according to the Handbook for clinical practice guideline developer (version 1.0) by National Evidence-based Healthcare Collaborating Agency. Evidence levels and recommendation ratings were established in accordance to SIGN 2011 (The Scottish Intercollegiate Guidelines Network). Results: The final 15 recommendations from four domains were derived from experts' advice; 1) assessment of risk factor for falls in adult 2) preventing falls and reducing the risks of falls or falls-related injury 3) management and reassessment after a person falls 4) leadership and culture. Conclusion: This clinical practice guideline can be used as a basis for evaluation and prevention of fall risk factors for adults, to formulate recommendations for fall risk assessment and fall prevention, and to present monitoring indicators for applying the recommendations.

• 정보교육학회논문지
• /
• 제24권6호
• /
• pp.633-641
• /
• 2020

인공지능으로 구현되는 지능과 데이터 및 네트워크 기술에 기반한 지능정보기술의 발전은 사회 전반에 혁신을 유발하고 광범위한 사회, 경제적 파급력을 보여주고 있다. 이에 국외는 물론 국내에서도 다가오는 미래사회를 이끌어갈 인재 양성을 위해 AI 교육을 서두르고 있는 실정이다. 데이터는 인공지능의 중요한 부분으로서 데이터를 수집, 처리, 분석하여 데이터 기반의 의사결정을 할 수 있는 데이터 리터러시는 AI 소양과 더불어 함께 신장시켜야 할 중요한 역량으로 볼 수 있다. 따라서 본 연구에서는 초등학생의 데이터 리터러시를 키워줄 수 있는 AI 데이터과학 교육 프로그램을 개발하여 이를 실험반에 적용, 사전-사후 대응표본 t-test를 통해 그 효과성을 검증하였다. 그 결과 데이터 리터러시의 네 가지 세부 역량인 데이터 이해, 수집, 분석, 표현에서 모두 통계적으로 유의미하게 향상된 결과를 나타내어 AI 데이터과학 교육 프로그램이 학생들의 데이터 리터러시 향상에 효과적임을 알 수 있었다.

• Human Ecology Research
• /
• 제59권3호
• /
• pp.353-367
• /
• 2021

The purpose of this study was to examine the mediating effect of middle school students'self-deprecation in the relationship between upward social comparison in social network service (SNS) and depression and the moderated mediating effect of cognitive flexibility. The participants were 288 middle school students, in the first to third grades from four middle schools located in Seoul, Gyeong-gi, and Jeonnam. The date were analyzed with descriptive statistics, Pearson's correlation coefficients and the Process Macro Model 4, 1, and 14. The results of this study are as follows. First, an upward comparison in SNS has a significant positive influence on students'depression, and students' self-deprecation of students mediated the relation between two. Second, the level of control, which is a sub-factor of cognitive flexibility, moderated the mediating effect of self-deprecation. That is, if students are more likely to perceive difficult situations as controllable, upward social comparison in SNS mediated by self-deprecation has smaller effect on depression. Based on these results, we suggest practical interventions to reduce depression among middle school students by decreasing upward social comparison in SNS and self-deprecation. In addition, helping students perceive difficult situations as controllable could be another effective way of reducing depression among those students who have a high level of self-deprecation in upward social comparison in SNS.

• 디지털융복합연구
• /
• 제20권4호
• /
• pp.133-145
• /
• 2022

연구 목적은 데이터 거버넌스의 연구 동향을 파악하고자 하였다. 연구 대상은 데이터 거버넌스 개념과 전략이 제시되기 시작한 2009년부터 2021년까지의 논문 158편을 대상으로 하였다. 주요 연구방법은 텍스트 마이닝을 활용하였고, 주요 방법은 빈도분석, 워트클라우드, 네트워크 분석 및 토픽 모델링 기법을 사용하여 분석하였다. 연구 결과 최빈 키워드는 정보, 빅데이터, 관리, 정책, 정부, 법률, 스마트가 확인되었다. 또한 네트워크 분석 결과 데이터 산업 정책, 데이터 거버넌스 성과, 국방, 거버넌스, 데이터 공공 등의 주제로 연관된 연구 수행이 이루어지고 있었다. 토픽 모델링을 통해 도출된 4개 토픽은 "데이터 거버넌스 정책", "데이터 거버넌스 플랫폼", "데이터 거버넌스 관련 법률", "데이터 거버넌스 구현"이며, 이중 "데이터 거버넌스 플랫폼" 관련 연구는 증가 추세를 보였고, "데이터 거버넌스 구현"은 축소되고 있는 경향이었다. 본 연구는 데이터 거버넌스 관련 연구를 종합적으로 정리하였다. 데이터 거버넌스는 조직 차원의 데이터 경영 및 데이터 통합 정책, 관련 기술 등 관련 분야와 다양한 시각에서 연구영역 확대가 필요하다. 향후 해외데이터 거버넌스들을 대상으로 한 분석 대상을 확대하고 4차산업혁명, 인공지능, 메타버스 등 데이터 기반 미래 산업이 요구되는 산업 분야에서의 연구 방향과 정책 방향 수립 관련 후속 연구를 기대할 수 있다.

• 한국IT서비스학회지
• /
• 제20권6호
• /
• pp.63-81
• /
• 2021

Joint financial network of Korea Financial Telecommunications and Clearings Institute, which is an essential facility with a natural monopoly, maintained its closedness as monopoly/public utility model, but it has evolved in the form of open banking in order to obtain domestic fintech competitiveness in the rapidly changing digital financial ecosystem such as the acceleration of Big Blur. In accordance with digital transformation strategy of financial institutions, various ICT companies are actively participating in the financial industries, which has been exclusive to banks, through the link technology called Open API. For this reason, there has been a significant change in the financial service supply chain in which ICT companies participate as users. The level of security in the financial service supply chain is determined based on the weakest part of the individual components according to the law of minimum. In addition, there is a perceived risk of personal information and financial information leakage among the main factors that affect users' intention to accept services, and appropriate protective measures against perceived security risks can be a catalyst, which increases the acceptance of open banking. Therefore, this is a study on factors affecting the introduction of open banking to achieve financial innovation by developing an open banking security control model for financial institutions, as a protective measures to user organizations, from the perspectives of cyber financial security and customer information protection, respectively, and surveying financial security experts. It is expected, from this study, that effective information protection measures will be derived to protect the rights and interests of financial customers and will help promote open banking.

• 한국농공학회논문집
• /
• 제63권3호
• /
• pp.1-12
• /
• 2021

Optimal water management is to efficiently and equally supply an appropriate amount of water by using irrigation facilities. Therefore, it is necessary to evaluate water supply capacity through distribution simulation between the designed distribution rate and re-distributed rate according to the changed farming conditions. In this study, we recalculated the agricultural water supply amount of Geumcheon main canal, which beneficiary area was reduced due to the development of Gwangju-Jeonnam innovation city, and we constructed a canal network using the SWMM model to simulate the change in supply rate of each main canal according to the re-distributed rate. Even though the supply amount of the Geumcheon main canal was reduced from 1.20 m³/s to 0.90 m³/s, it showed a similar supply rate to the current, and the reduced quantity could be supplied to the rest of the main canal. As a result, the arrival time at the ends of all main canal, except for the Geumcheon main canal, decreased from 1 to 3 hours, and the supply rate increased from 4 to 17.0% at the main canal located at the end of the beneficiary area of Naju reservoir.

• 융합정보논문지
• /
• 제11권4호
• /
• pp.1-18
• /
• 2021

본 연구의 목적은 확장된 UTAUT를 활용하여 4차 산업혁명 및 스마트 팩토리 관련 기술의 수용의도와 수용행동에 영향을 미칠 수 있는 영향요인을 연구하는 것이다. 이를 통해 어떠한 영향요인들이 관련 기술의 도입과 수용에 영향을 미치는가를 파악함으로써 제조 기업들의 4차 산업혁명에 대한 대응 및 스마트 팩토리 관련 기술 수용을 위한 전략을 도출하는 것이다. 다양한 제조 기업체들에 대하여 설문조사를 시행하였으며, 167부를 연구에 활용하였다. 연구가설의 검정결과 성과기대, 사회적 영향, 촉진조건, 네트워크 효과, 혁신성은 수용의도에 긍정적이고 유의한 영향을 미친다. 그러나 노력기대는 수용의도에 긍정적인 영향을 미치지만 유의하지 않았다. 수용의도는 수용행동에 긍정적이고 유의한 영향을 미친다. 따라서 4차 산업혁명 대응과 스마트 팩토리 관련 기술의 도입 및 수용과정에서 제조 기업들이 제고하여야 하는 요인들을 명확하게 제시하였다.

• Journal of Animal Science and Technology
• /
• 제63권6호
• /
• pp.1453-1463
• /
• 2021

Feeding is the most important behavior that represents the health and welfare of weanling pigs. The early detection of feed refusal is crucial for the control of disease in the initial stages and the detection of empty feeders for adding feed in a timely manner. This paper proposes a real-time technique for the detection and recognition of small pigs using a deep-leaning-based method. The proposed model focuses on detecting pigs on a feeder in a feeding position. Conventional methods detect pigs and then classify them into different behavior gestures. In contrast, in the proposed method, these two tasks are combined into a single process to detect only feeding behavior to increase the speed of detection. Considering the significant differences between pig behaviors at different sizes, adaptive adjustments are introduced into a you-only-look-once (YOLO) model, including an angle optimization strategy between the head and body for detecting a head in a feeder. According to experimental results, this method can detect the feeding behavior of pigs and screen non-feeding positions with 95.66%, 94.22%, and 96.56% average precision (AP) at an intersection over union (IoU) threshold of 0.5 for YOLOv3, YOLOv4, and an additional layer and with the proposed activation function, respectively. Drinking behavior was detected with 86.86%, 89.16%, and 86.41% AP at a 0.5 IoU threshold for YOLOv3, YOLOv4, and the proposed activation function, respectively. In terms of detection and classification, the results of our study demonstrate that the proposed method yields higher precision and recall compared to conventional methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권12호
• /
• pp.3904-3922
• /
• 2022

As a research hotspot, pedestrian detection has a wide range of applications in the field of computer vision in recent years. However, current pedestrian detection methods have problems such as insufficient detection accuracy and large models that are not suitable for large-scale deployment. In view of these problems mentioned above, a lightweight pedestrian detection and early warning method using a new model called you only look once (Yolov5) is proposed in this paper, which utilizing advantages of Yolov5s model to achieve accurate and fast pedestrian recognition. In addition, this paper also optimizes the loss function of the batch normalization (BN) layer. After sparsification, pruning and fine-tuning, got a lot of optimization, the size of the model on the edge of the computing power is lower equipment can be deployed. Finally, from the experimental data presented in this paper, under the training of the road pedestrian dataset that we collected and processed independently, the Yolov5s model has certain advantages in terms of precision and other indicators compared with traditional single shot multiBox detector (SSD) model and fast region-convolutional neural network (Fast R-CNN) model. After pruning and lightweight, the size of training model is greatly reduced without a significant reduction in accuracy, and the final precision reaches 87%, while the model size is reduced to 7,723 KB.