• 산업경영시스템학회지
• /
• 제44권3호
• /
• pp.86-97
• /
• 2021

As mechatronic systems have various, complex functions and require high performance, automatic fault detection is necessary for secure operation in manufacturing processes. For conducting automatic and real-time fault detection in modern mechatronic systems, multiple sensor signals are collected by internet of things technologies. Since traditional statistical control charts or machine learning approaches show significant results with unified and solid density models under normal operating states but they have limitations with scattered signal models under normal states, many pattern extraction and matching approaches have been paid attention. Signal discretization-based pattern extraction methods are one of popular signal analyses, which reduce the size of the given datasets as much as possible as well as highlight significant and inherent signal behaviors. Since general pattern extraction methods are usually conducted with a fixed size of time segmentation, they can easily cut off significant behaviors, and consequently the performance of the extracted fault patterns will be reduced. In this regard, adjustable time segmentation is proposed to extract much meaningful fault patterns in multiple sensor signals. By considering inflection points of signals, we determine the optimal cut-points of time segments in each sensor signal. In addition, to clarify the inflection points, we apply Savitzky-golay filter to the original datasets. To validate and verify the performance of the proposed segmentation, the dataset collected from an aircraft engine (provided by NASA prognostics center) is used to fault pattern extraction. As a result, the proposed adjustable time segmentation shows better performance in fault pattern extraction.

• 대한본초학회지
• /
• 제36권5호
• /
• pp.1-14
• /
• 2021

Objectives : From January 2020, when the first confirmed case of COVID-19 in Korea, the use of health information using the Internet is expected to increase. It is expected that there will be a significant change in the general public's interest in Korean herbal medicines for health care. Therefore, in this study, we tried to confirm the change in the search trend of Korean herbal medicines after the COVID-19 epidemic. Methods : Using the "Naver DataLab (http://datalab.naver.com)" service of a Korean portal site Naver, search volume was investigated with 606 Korean herbal medicines as keywords. The search period was from January 2020, right after the onset of COVID-19, to June 2021. The search results were sorted by the peak search volume and the total search volume. Results : 'Cheonsangap (천산갑, 穿山甲, Manitis Squama)' was the most searched Korean herbal medicine in the peak search volume and total search volume with least bias. Conclusions : The problem of supply and demand of Korean herbal medicines of high public interest was identified. Broadcasting and media exposure were the factors that had a big impact on the search volume for Korean herbal medicines. As it was confirmed that the search volume for Korean herbal medicines increased rapidly due to media exposure, it is necessary to provide correct information about Korean herbal medicines, improve public awareness, and manage stable supply and demand based on continuous search trend monitoring.

• International journal of advanced smart convergence
• /
• 제8권2호
• /
• pp.18-29
• /
• 2019

In the field of Human-Computer Interaction design, persuasive design has gradually been applied to the system development and design process, especially for mobile application design. However, most mobile applications have hitherto a very short using lifecycle. Especially, design features with long-term persuasive effectiveness remain to be further researched and developed. In this study, we focused on investigating and identifying the durative persuasive design characteristics through a data mining process and evaluating the durative effectiveness through a long-term observation process. Total five hundred healthcare-related mobile applications were selected from Apple iTunes Store and a mixed method was conducted to extract the most common persuasive design characteristics. Based on the results of extraction, a representative healthcare-related mobile application was selected as experimental subject. Total one hundred and twenty participants were observed during a six-months experiment and the monitoring data of app usage of all participants was collected once a week. According to the evaluation model for behavior change identification process, participants with habit formation features were proved to have a significant long-term perception level for ten persuasive design characteristics. Further interview research was performed to investigate the participant's long-term perceptions on those characteristics for the purpose of identifying the durative persuasions. The results indicated that a long-term durative effectiveness can be observed and healthcare-related apps designed with those characteristics could have durative effectiveness. This study may contribute to the improvement of future mobile application designs in user experience and durative persuasion, as well as bringing future benefits for both mobile application developers and users.

• Healthcare Informatics Research
• /
• 제24권4호
• /
• pp.253-262
• /
• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.

• 한국멀티미디어학회논문지
• /
• 제22권5호
• /
• pp.613-625
• /
• 2019

The rise of the Internet of Things (IoT) devices have greatly influenced many industries and one of them is healthcare where wearable devices started to track all your daily activities for better health monitoring accuracy and even down to tracking daily food intake in some cases. With the amounts of data that are being tracked and shared between from these devices, questions were raised on how to uphold user's data privacy when data is shared between these IoT devices and third party. With the blockchain platforms started to mature since its inception, the technology can be implemented according to a variety of use case scenarios. In this paper, we present a system architecture based on the healthcare system and IoT network by leveraging on multiple blockchain networks as the medium in between that should enable users to have direct authority on data accessibility of their shared data. We provide proof of concept implementation and highlight the results from our testing to show how the efficiency and scalability of the healthcare system improved without having a significant impact on the performance of the Electronic Medical Record (EMR) that mostly affected by the previous solution since these solutions directly connected to a public blockchain network and which resulted in significant delays and high cost of operation when a large amount of data or complicated functions are involved.

• 한국콘텐츠학회논문지
• /
• 제19권6호
• /
• pp.33-46
• /
• 2019

본 연구는 한류 방송 콘텐츠의 최대 소비 지역이지만 역으로 가장 많은 불법 유통 현상이 발견되고 있는 중국이 어떤 형태로 국내 방송사업자의 권리를 침해하고 있으며, 이에 대한 정책적 대안은 무엇인지 밝히는데 그 목적이 있다. 이를 위해 인터넷 및 모바일 멀티 플랫폼 환경에서 가장 많이 발생하는 저작권 침해 유형의 경로와 방식을 조사하고, 이에 대한 방송사업자의 대응 방식을 심층인터뷰를 통해 조사했다. 연구결과, 복제권과 전송권을 침해하는 방식으로 가장 많이 나타난 유형은 웹과 앱을 통한 링크와 STB 형태의 TV패드를 이용한 방식인 것으로 나타났다. TV패드는 최근 미국소송에서 지상파 연합이 승소했지만 링크는 온라인 불법복제의 만연으로 이를 통제하기 쉽지 않은 상황이다. 특히 국내 사업자들이 개별적으로 대응하는 형태로는 중국내의 불법복제 문제를 해결하기 쉽지 않았고, 이와 관련한 소송 사례도 극히 드문 것으로 나타났다. 향후 정부는 불법복제 근절을 위한 시장조사는 물론이고 꾸준한 모니터링을 통해 한류 방송 콘텐츠에 대한 측면 지원을 해야 할 것으로 판단된다.

• International Journal of Computer Science & Network Security
• /
• 제21권8호
• /
• pp.229-237
• /
• 2021

Cloud of things (CoTs) is a newer idea which combines cloud computing (CC) with the Internet of Things (IoT). IoT capable of comprehensively producing data, and cloud computing can be presented pathways that allow for the progression towards specific destinations. Integrating these technologies leads to the formation of a separate element referred to as the Cloud of Things (CoTs). It helps implement ideas that make businesses more efficient. This technology is useful for monitoring a device or a machine and managing or connecting them. Since there are a substantial amount of machines that can run the IoT, there is now more data available from the IoT that would have to be stored on a local basis for a provisional period, and this is impossible. CoTs is used to help manage and analyze data to additionally create usable information by permitting and applying the development of advanced technology. However, combining these elements has a few drawbacks in terms of how secure the process is. This investigation aims to recent study literature from the past 3 years that talk about how secure the technology is in terms of protecting by authentication, reliability, availability, confidentiality, and access control. Additionally, this investigation includes a discussion regarding some kinds of potential attacks when using Cloud of Things. It will also cover what the various authors recommend and conclude with as well as how the situation can be approached to prevent an attack.

• 한국멀티미디어학회논문지
• /
• 제24권1호
• /
• pp.75-94
• /
• 2021

The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

• 한국식품위생안전성학회지
• /
• 제35권6호
• /
• pp.561-566
• /
• 2020

참돔은 등쪽에 푸른 반점이 흩어져 있고, 홍민어는 꼬리 쪽에 검은 점이 있어 원물 형태는 쉽게 구분할 수 있다. 그러나 횟감이나 필렛으로 이용 시 참돔과 홍민어를 구분하기 어려워, 참돔의 종 특이 primer를 개발 및 검증하고 모니터링을 통해 참돔의 위변조 사례를 조사하고자 하였다. 시료에서 gDNA를 추출하여 PCR을 진행하였으며 참돔 primer의 product size는 468 bp, 홍민어 primer의 product size는 181 bp으로 설계하였다. Multiplex PCR 결과 참돔과 홍민어에 대한 종 특이적 증폭이 확인되었다. 또한, 참돔과 홍민어 PCR 민감도 실험 결과 참돔 primer는 1 ng, 홍민어 primer는 0.1 ng 까지 밴드가 확인되었다. 모니터링 결과 참돔으로 구매한 시료 19건 모두 참돔으로 판정되었다. 따라서 본 연구에서 제작된 참돔과 홍민어 종에 대한 종 특이적 primer는 횟감 등 수산물에도 적용할 수 있어 현재 유통 및 판매되고 있는 참돔 및 홍민어 판별에 적합성을 확인하였다.

• 융합보안논문지
• /
• 제20권5호
• /
• pp.3-10
• /
• 2020

최근 인터넷 그리고 네트워크는 사회를 구성하는 필수적인 인프라로 여겨짐과 동시에 이에 대한 보안 위협 상황이 지속적으로 증대되고 있다. 그러나 네트워크에서 실제 패킷을 전송하는 스위치 단에서는 기본적으로 고정적인 룰에 의한 방화벽 혹은 네트워크 접근 제어를 통해서만 보안 위협을 대응할 수 있어, 보안 위협에 대한 효과적인 대응은 네트워크 자체에서는 극히 제한적이며, 능동적으로 대처하지 못하고 있다. 본 논문에서는 네트워크 데이터 평면 프로그래밍 언어인 P4(Programming Protocol-independent Packet Processor)를 통해 네트워크 내 모든 플로우를 P4 스위치 단에서 실시간으로 모니터링하고, 특정 보안 공격 패킷을 스위치 단에서 처리함으로써, 네트워크 단에서 분산 DDoS 공격, IP Spoofing 공격 등을 대응할 수 있는 인-네트워크 (In-Network) 보안 관리 방법을 제안한다. 또한 네트워크 사용자 혹은 보안 관리자의 운영 정책을 SDN (Software-Defined Networking) 제어기를 통해 P4 스위치에서 적용함으로써, 다양한 네트워크 응용 환경에서의 보안 요구 사항을 반영할 수 있다.