• 대한통합의학회지
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• 제10권3호
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• pp.161-172
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• 2022

Purpose : The study was to promote patient safety by analyzing the effect of dental hygienist's perception of patient safety culture on infection control activities. Methods : The study is based on a survey of 210 dental hygienists in total working in dental settings. To find out infection control activities according to patient safety culture awareness, there were 6 general characteristics, 3 teamwork within the department, 2 infection control systems, 4 surface management, 9 equipment washing, disinfection, and laundry management, 4 infectious wastes, and 3 personal protection phrases.The data was analyzed using the SPSS version 20.0, and p<.05 was adopted to decide on significance. Results : The longer dental hygienists have worked n the dental settings, the more active they become in infection control activities. Among the different types of dental care settings, general (university) hospitals had the largest number of infection control activities, followed by dental clinics, and network dental clinics, in descending order. The dental settings possessing a higher number of dental hygienists were found to conduct more infection control activities than other dental settings. In addition, it was found that when a dental setting adopts a patient safety policy across all the units in the hospital, more systems and procedures for patient safety tend to be established, and that stricter management response to error leads to improvement of infection control activities. Conclusion :In order to enhance infection control activities, infection control activity programs should develop and implement periodic reinforcement of infection control education. regular monitoring of infection control activities.

• 융합신호처리학회논문지
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• 제23권3호
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• pp.150-159
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• 2022

본 논문은 실시간 영상 분석을 통해서 산업현장에서 활동하는 여러 근로자의 영상 객체를 추출해 내고, 추출된 이미지로 부터 개별 영상 분석을 통해 헬멧의 착용 여부와 낙상 사고 여부를 확인하는 방법을 구현한다. 근로자의 영상 객체를 탐지하기 위해서 딥러닝 기반 컴퓨터 비전 모델인 YOLO를 사용하였으며, 추출된 이미지를 이용하여 헬멧의 착용여부를 판단하기 위해 따로 5,000장의 다양한 헬멧 학습 데이터 이미지를 만들어서 사용하였다. 또한, 낙상사고 여부를 판단하기 위해서 Mediapipe의 Pose 실시간 신체추적 알고리즘을 사용하여 머리의 위치를 확인하고 움직이는 속도를 계산하여 쓰러짐 여부를 판단하였다. 결과에 신뢰성을 주기위한 방법으로 YOLO의 바운딩 박스의 크기를 구하여 객체의 자세를 유추하는 방법을 추가하고 구현하였다. 최종적으로 관리자에게 알림 서비스를 위하여 텔레그램 API Bot과 Firebase DB 서버를 구현하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.232-234
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• 2022

빅데이터는 고객 관계 관리, 관계 마케팅, 금융 업무 개선, 신용정보 및 위험 관리 분야에서 크게 활용되고 있다. 더욱이 최근에 COVID-19 바이러스로 인하여 비대면 금융거래가 보다 활발해지면서 고객과의 관계 측면에서 금융 빅데이터의 활용이 더 요구되고 있다. 고객 관계 측면에서 금융 빅데이터는 기술적인 접근보다 감성적적인 접근이 필요한 시기가 도래하였다. 관계 마케팅 측면에서도 인지적, 이성적, 합리적인 면보다는 감성적인 면을 중요시 할 필요성이 대두되었다. 하지만, 기존의 금융 데이터는 텍스트 형태의 고객 거래 데이터, 기업재무정보, 설문지등을 통하여 수집되고 활용되었다. 본 연구는 SNS를 통하여 고객의 문화 활동, 여가 활동 기반의 고객의 감성적인 이미지 데이터 즉, 비정형 데이터를 획득하여 고객의 활동 이미지를 인공지능 CNN 알고리즘으로 분석한다. 활동 분석은 다시 주석을 달은 인공지능에 적용하고, 주석에 나타난 행동 모델을 분석하는 인공지능 빅데이터 모델을 설계한다.

• 벤처혁신연구
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• 제5권2호
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• pp.101-110
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• 2022

플랫폼 비즈니스 모델은 네트워크 효과, 플라이휠 전략 등의 고유 특성으로 인해 선두주자가 시장을 독점하기에 용이한 구조를 가지고 있다. 이에 따라, 플랫폼 사업자에 대한 규제는 최근 독점 규제 논의에서 끊임없이 언급되고 있으나, 전 세계적으로 구체적인 플랫폼 규제 정책이 자리 잡지 못하는 상황이다. 이는 플랫폼의 경제적 가치를 정량적으로 평가하는 방법이 아직 합의되지 않아, 독점이 우려되는 대형 플랫폼과 태동 중인 신흥 플랫폼을 객관적으로 구분할 지표가 마련되어있지 않기 때문이다. 본 연구는 토빈의 Q 이론(Tobin's Q Theory)을 바탕으로, 특정 규모의 플랫폼 보유 여부가 대체비용과 시가총액 간의 관계에 미치는 조절 효과를 측정하여 플랫폼 기업이 가진 플랫폼 가치를 평가하는 방법을 제언하였다. 본 연구의 방법론은 플랫폼 독점 규제 대상을 객관화하여 독점 규제 정책을 정착시킬 수 있는 기반이 될 수 있으며, 동시에 향후 등장할 신흥 플랫폼 기업의 잠재력을 객관적으로 평가하여 활발한 투자시장을 형성하는데 기여할 수 있다.

• 문화기술의 융합
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• 제9권5호
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• pp.951-956
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• 2023

체계적이고 적극적인 재난관리가 중요해지는 현 상황에서 국내 도서관은 독자적인 재난관리계획이나 지원체계 등이 부재한 것이 현실이다. 이러한 문제점을 개선하기 위해 본 연구에서는 해외사례를 살펴보았다. 그 중에서도 지정학적으로 다양한 재난에 노출되어 있어 관련 사례와 연구가 활발히 진행되고 있는 일본을 중심으로 살펴보았다. 특히, 동일본대지진 이후 구축된 민관 협력 사례들을 중심으로 살펴보았다. 일본도서관협회의 도서관재해대책위원회와 자발적으로 결집된 전문가 네트워크인 saveMALK을 중심으로 2개의 사례를 분석하였다. 그 결과, 일본도서관협회에서 조직한 도서관재해대책위원회는 기부와 자원봉사활동을 체계적으로 수행할 수 있도록 중심 역할을 수행하였으며, saveMALK는 관련 전문가들이 집단지성을 형성하여 정보를 수집·공유하는 역할을 수행한 것을 알 수 있었다. 이러한 일본 사례분석을 통해 협력형 재난관리 체계 구축에 긍정적 시사점을 발견할 수 있다.

• Smart Structures and Systems
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• 제33권1호
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• 대한통합의학회지
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• 제12권1호
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• pp.109-124
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• 2024

Purpose : The purpose of this study was to examine the effects of a virtual reality-based complex cognitive training program for depression, cognitive function, and digital divide reduction in the elderly who have not been diagnosed with dementia or MCI. Methods : We enrolled 16 participants who were over 65 years old and not been diagnosed with dementia or MCI. We randomly divided into three groups (A, B, C). Participants underwent an 8-week virtual reality-based complex cognitive training program (60 minutes each session, twice per week). At a baseline, all participants completed questionnaires on general features, depression and cognitive function. After four weeks, all participants completed questionnaires on depression and cognitive function. After the end of the last program, participants conducted questionnaires on depression, cognitive function, and usability evaluation. Results : At the 8-week follow-up, 16 participants completed the program. Compared to the baseline, the average score of cognitive function was increased (from 26.5 to 28.5), although it was not statistically significant (p<.061). There were no significant differences between baseline and post-training evaluations on depression scores. The average score of usability evaluation was 75.56, which corresponds to good. Conclusion : Even though the results showed no statistically significant findings in cognitive function and depression after the virtual reality-based complex cognitive training intervention, this pilot study proposed the possibility of utilizing the virtual reality program as a tool that provides active learning opportunities for the elderly and helps improve their cognitive function through multi-sensory components. Also, the findings of this study suggested a positive reevaluation of the elderly's digital access capabilities while reducing the digital divide. A virtual reality-based complex cognitive training program improved the social network of the elderly. We expect that it will expand in size and help with their social participation of the elderly.

• 한국IT서비스학회지
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• 제23권1호
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• pp.1-10
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• 2024

The IT environment is changing due to the acceleration of digital transformation in enterprises and organizations. This expansion of the digital space makes centralized cybersecurity controls more difficult. For this reason, cyberattacks are increasing in frequency and severity and are becoming more sophisticated, such as ransomware and digital supply chain attacks. Even in large organizations with numerous security personnel and systems, security incidents continue to occur due to unmanaged and unknown threats and vulnerabilities to IT assets. It's time to move beyond the current focus on detecting and responding to security threats to managing the full range of cyber risks. This requires the implementation of asset Inventory for comprehensive management by collecting and integrating all IT assets of the enterprise and organization in a wide range. IT Asset Management(ITAM) systems exist to identify and manage various assets from a financial and administrative perspective. However, the asset information managed in this way is not complete, and there are problems with duplication of data. Also, it is insufficient to update of data-set, including Network Infrastructure, Active Directory, Virtualization Management, and Cloud Platforms. In this study, we, the researcher group propose a new framework for automated 'Comprehensive IT Asset Management(CITAM)' required for security operations by designing a process to automatically collect asset data-set. Such as the Hostname, IP, MAC address, Serial, OS, installed software information, last seen time, those are already distributed and stored in operating IT security systems. CITAM framwork could classify them into unique device units through analysis processes in term of aggregation, normalization, deduplication, validation, and integration.

• IMMUNE NETWORK
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• 제22권3호
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• pp.26.1-26.18
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• 2022

IL-22, a pleiotropic cytokine, is known to have a profound effect on the regeneration of damaged intestinal barriers. The tissue-protective properties of IL-22 are expected to be potentially exploited in the attenuation and treatment of colitis. However, because of the disease-promoting role of IL-22 in chronic inflammation, a comprehensive evaluation is required to translate IL-22 into the clinical domain. Here, we present the effective production of soluble human IL-22 in bacteria to prove whether recombinant IL-22 has the ability to ameliorate colitis and inflammation. IL-22 was expressed in the form of a biologically active monomer and non-functional oligomers. Monomeric IL-22 (mIL-22) was highly purified through a series of 3 separate chromatographic methods and an enzymatic reaction. We reveal that the resulting mIL-22 is correctly folded and is able to phosphorylate STAT3 in HT-29 cells. Subsequently, we demonstrate that mIL-22 enables the attenuation of dextran sodium sulfate-induced acute colitis in mice, as well as the suppression of pro-inflammatory cytokine production. Collectively, our results suggest that the recombinant mIL-22 is suitable to study the biological roles of endogenous IL-22 in immune responses and can be developed as a biological agent associated with inflammatory disorders.

• Structural Engineering and Mechanics
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• 제90권1호
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.