• 디지털산업정보학회논문지
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• 제13권4호
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• pp.13-23
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• 2017

In order to protect personal information and important information (confidential information, sales information, user information, etc.) in the internal network, companies and organizations apply encryption to the Server-To-Server or Server-To-Client communication section, And are experiencing difficulties due to the increasing number of known attacks and intelligent security attacks. In order to apply the existing S / W encryption technology, it is necessary to modify the application. In the financial sector, "Comprehensive Measures to Prevent the Recurrence of Personal Information Leakage in the Domestic Financial Sector" has been issued, and standard guidelines for financial computing security have been laid out, and it is required to expand the whole area of encryption to the internal network. In addition, even in environments such as U-Health and Smart Grid, which are based on the Internet of Things (IoT) environment, which is increasingly used, security requirements for each collection gateway and secure transmission of the transmitted and received data The requirements of the secure channel for the use of the standard are specified in the standard. Therefore, in this paper, we propose a secure encryption algorithm through mutual authentication and grouping for each node through H / W based Network Control Server (NCS) applicable to internal system and IoT environment provided by enterprises and organizations. We propose a protocol design that can set the channel.

• PNF and Movement
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• 제15권1호
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• pp.51-56
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• 2017

Purpose: The purpose of this study was to examine the effects of the PNF stabilization technique for the hip joint and the bridging exercise on the trunk stabilizer muscles in healthy adults. Methods: Twenty-eight healthy adults were randomly allocated to either a PNF stabilization exercise group (n = 12) or a bridging exercise group (n = 16). The outcome measures included the contraction thickness ratio in the transversus abdominis (TrA), internal oblique (IO), and external oblique (EO), and the TrA lateral slide was assessed during the abdominal drawing-in maneuver using b-mode ultrasound. The researcher measured the abdominal muscle thickness of each participant before the therapist began the intervention and at the moment that the intervention was applied. Between-group comparisons were performed using the Mann-Whitney U test. The level of statistical significance was set at 0.05. Results: The PNF intervention program showed a significant increase in the trunk stabilizer muscle. The percentage of change in the TrA thickness showed a significant interaction between intervention. However, there were no significant differences in the IO and EO between the two groups. Conclusion: The PNF stabilization technique for the hip joint can be used effectively to improve the IO and TrA muscles in healthy adults.

• 서비스연구
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• 제7권4호
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• pp.39-50
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• 2017

본 연구의 목적은 서비스 제공자(개발자)와 서비스 수혜자(고객)집단 간에 느끼는 디자인 컨셉 가치에 대한 비교연구로서 양압기(CPAP)를 중심으로 진행된 IoT기반 U-헬스케어 및 사용자 환경기반 서비스모델을 제시하여 사례연구로 진행하였다. 더블다이아몬드(Double Diamond)연구방법을 활용하여 울산에 소재한 U병원 이비인후과와 공동으로 사례 연구를 진행하였으며, 수면 무호흡 수면 환자들을 대상으로 진단부터 구매 후 사용까지 다양한 의미 있는 경험을 발췌하고 고객 유형별 차이점을 분류 하였다. 최종적으로 제시한 13개의 서비스 시나리오 모델을 대상으로 고객은 카노(Kano)만족도와 잠재적 고객만족 개선 지수(PCSI)평가를 진행하였고 개발에 참여한 서비스제공자 집단을 대상으로 스코어모델(+-)평가와 컨셉포지션(Concept Position)평가를 진행하였다. 본 연구를 통하여 도출한 결과는 총 12가지 문항에서 7가지 문항은 수혜자와 공급자 사이에서의 가치적 견해의 일치가 나타났으며 이는 사용자 환경기반 서비스모델 속성 이었으며, 반대로 가치적 견해가 상의한 결과인 5가지 문항은 IoT기반 U-헬스케어 서비스 모델 속성에 포함 되어 있었다는 것을 알 수 있었다.

• 한국수자원학회논문집
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• 제52권11호
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• pp.947-950
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• 2019

이 논문의 주요 특징은 초기강우 유입 시 일차 침전지 처리효율을 개선하기 위한 운전제어 전략을 제공하는 것이다. 최근 IoT 기술과 센싱 기술이 발전함에 따라 하수처리시설 운전제어를 위한 기반이 개선되고 있으며, 온라인 측정결과를 활용한 일차침전지 처리효율 개선에 따라 미처리 하수의 하천 유출을 최소화하고, 하수처리시설 운영효율 개선에기여할 수 있다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.884-885
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• 2014

The use of Radio Frequency Identification technology (RFID) in medical context enables not only drug identification, but also a rapid and precise identification of patients, physicians, nurses or any other health care related staffs. The combination of RFID tag identification with structured and secured Internet of Things (IoT) solutions enables ubiquitous and easy access to medical related records, while providing control and security to all interactions. This paper surveyed a basic security architecture, easily deployable on mobile platforms, which would allow to establish and manage a medication prescription service in mobility context making use of electronic personal health records.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.300-302
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• 2022

Palm vein identification has attracted attention due to its distinct characteristics and excellent recognition accuracy. However, many contactless palm vein identification systems suffer from the issue of having low-quality palm images, resulting in degradation of recognition accuracy. This paper proposes the use of U-Net architecture to correctly segment the vascular blood vessel from palm images. Attention gate mechanism and residual block are also utilized to effectively learn the crucial features of a specific segmentation task. The experiments were conducted on CASIA dataset. Hessian-based Jerman filtering method is applied to label the palm vein patterns from the original images, then the network is trained to segment the palm vein features from the background noise. The proposed method has obtained 96.24 IoU coefficient and 98.09 dice coefficient.

• 대한의용생체공학회:의공학회지
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• 제41권1호
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• pp.55-61
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• 2020

Recently, there have been many research on fever management using u-healthcare technology. Especially, fever of infants requires continuous monitoring of body temperature by parents. For infants between 4 weeks and under 5 years old, it is recommended to use an electronic thermometer or chemical thermometer in the axilla, or to use an infrared thermometer. However, in order to overcome the reality of not being able to waste significant time on continuous monitoring, there have been demands of patch type thermometers with the internet of things (IoT) and wireless communication technologies. Existing IoT thermometers are difficult to attach to infants' body because they do not take into account its size, and their interoperability is not guaranteed because they do not comply with standards in communication. Therefore, in this study, a patch-type thermometer with a diameter of 20 mm and a weight of 2.9 g was developed to manage the fever of infants, while it communicates wirelessly with Bluetooth Low Energy (BLE) communication protocol and complies with IEEE 11073 PHD(Personal Health Device) at the same time. We verified its performance under the requirements of thermometers regulated by the Korean Ministry of Food and Drug Safety.

• Imaging Science in Dentistry
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• 제52권4호
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• pp.351-357
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• 2022

Purpose: Convolutional neural networks (CNNs) have rapidly emerged as one of the most promising artificial intelligence methods in the field of medical and dental research. CNNs can provide an effective diagnostic methodology allowing for the detection of early-staged diseases. Therefore, this study aimed to evaluate the performance of a deep CNN algorithm for apical lesion segmentation from panoramic radiographs. Materials and Methods: A total of 1000 panoramic images showing apical lesions were separated into training (n=800, 80%), validation (n=100, 10%), and test (n=100, 10%) datasets. The performance of identifying apical lesions was evaluated by calculating the precision, recall, and F1-score. Results: In the test group of 180 apical lesions, 147 lesions were segmented from panoramic radiographs with an intersection over union (IoU) threshold of 0.3. The F1-score values, as a measure of performance, were 0.828, 0.815, and 0.742, respectively, with IoU thresholds of 0.3, 0.4, and 0.5. Conclusion: This study showed the potential utility of a deep learning-guided approach for the segmentation of apical lesions. The deep CNN algorithm using U-Net demonstrated considerably high performance in detecting apical lesions.

• 대한원격탐사학회지
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• 제37권5_1호
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• pp.1149-1161
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• 2021

컴퓨터 비전 기술이 위성영상에 적용되면서, 최근 들어 딥러닝 영상인식을 이용한 구름 탐지가 관심을 끌고 있다. 본연구에서는 SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset과 영상자료증대 기법을 활용하여 U-Net 구름탐지 모델링을 수행하고, 10폴드 교차검증을 통해 객관적인 정확도 평가를 수행하였다. 512×512 화소로 구성된 1800장의 학습자료에 대한 암맹평가 결과, Accuracy 0.821, Precision 0.847, Recall 0.821, F1-score 0.831, IoU (Intersection over Union) 0.723의 비교적 높은 정확도를 나타냈다. 그러나 구름그림자 중 14.5%, 구름 중 19.7% 정도가 땅으로 잘못 예측되기도 했는데, 이는 학습자료의 양과 질을 보다 더 향상시킴으로써 개선 가능할 것으로 보인다. 또한 최근 각광받고 있는 DeepLab V3+ 모델이나 NAS(Neural Architecture Search) 최적화 기법을 통해 차세대중형위성 1, 2, 4호 등의 구름탐지에 활용 가능할 것으로 기대한다.

• 한국융합학회논문지
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• 제6권4호
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• pp.243-248
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• 2015

U-Healthcare는 언제, 어디서나 환자의 건강을 검사하고 관리하며 유지할 수 있도록 하는 의료와 IT가 융합된 서비스이다. U-Healthcare 서비스에서 이루어지는 통신은 검진한 분석 결과나 긴급 데이터를 무선 통신방식을 이용하여 병원 서버에 전송하는 방식이 활용되고 있다. 이 때 악의적인 접근을 수행하는 자(공격자)가 U-Healthcare기기나 BS(Base Station)에 DRDoS(Distributed Reflection DoS)공격을 하면 위급한 환자의 상황 정보가 병원 서버까지 전송되지 않는 다양한 피해가 예상된다. 이를 대응하기 위해 DRDoS 공격 시나리오와 DRDoS에 대한 대응방안을 제안하고 대량의 패킷을 처리할 수 있는 빅데이터와 융합한다. 공격자가 U-Healthcare 기기나 BS(Base Station)를 공격 시 DB와 연동하여 일치하면 공격을 막는다. 본 논문은 원격의료 서비스인 U-Healthcare기기나 BS에서 나타날 수 있는 공격방법을 분석하고, 빅데이터를 활용하여 보안 위협에서의 대응방안을 제안한다.