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양윤지,김세권,박선주 한국수산과학회 2012 Fisheries and Aquatic Sciences Vol.15 No.1
Osteosarcoma is the most common primary malignancy of bone, and patients often develop pulmonary metastasis. The mechanisms underlying osteosarcoma metastasis remain to be elucidated. Recently, anti-inflammatory agents were shown to be useful in the treatment of tumor progression. We previously isolated a natural anti-inflammatory peptide from the seahorse Hippocampus kuda bleeler. Here, we examined the antitumor metastatic activity of this peptide and investigated its mechanism. The peptide significantly inhibited 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced invasive migration of human osteosarcoma MG-63 cells. Its inhibitory effect on invasive migration was associated with reduced expression of matrix metalloproteinases (MMP1 and MMP2). In addition, TPA stimulation increased intracellular reactive oxygen species (ROS) generation and small GTPase Rac1 expression, whereas the peptide decreased ROS generation and Rac1 activation. Taken together, these results suggest that the peptide inhibits invasive migration of MG-63 osteosarcoma cells by inhibiting MMP1 and MMP2 expression through downregulation of Rac1-ROS signaling.
Micro-Doppler signature 를 이용한 연합학습 기반 모션 인식 기법 연구
양윤지(Yunji Yang),홍용기(Yong-Gi Hong),박재현(Jaehyun Park) 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.2
본 논문은 micro-Dopper signature 를 이용한 모션 인식을 위해 딥러닝 기반의 효율적인 학습 방법을 연구하고 있다. CW(continuous wave) radar 로 얻은 data 를 후처리하여 획득한 micro-Doppler signature (m-DS)를 이용하여 모션을 식별하였다. 이때 식별을 위해 연합 학습 (Federated Learning) 기반 타겟 분류 신경망을 설계하고 학습하여 레이더 이미지를 이용한 모션 인식에 있어 효율적이고 보안성이 우수한 방법을 제시하였다. 실측 데이터를 활용하여 제안한 모션인식 시스템에 대해 검증하였다. 특히 다양한 각도에서 바라본 모션에 대해 획득한 실측 데이터에 대해 연합학습을 적용할 경우 그렇지 않은 경우에 비해 모션에 대한 인식률이 높아짐을 확인하였다.
정병구,양윤지,오승주 한국센서학회 2023 센서학회지 Vol.32 No.6
Wearable sensors designed for strain, pressure, and temperature measurements are essential for monitoring human movements, healthstatus, physiological data, and responses to external stimuli. Notably, recent research has led to the development of high-performancewearable sensors using innovative materials and device structures that exhibit ultra-high sensitivity compared with their commercialcounterparts. However, the quest for accurate sensing has identified a critical challenge. Specifically, the mechanical flexibility of thesubstrates in wearable sensors can introduce interference signals, particularly when subjected to varying external stimuli and environmentalconditions, potentially resulting in signal crosstalk and compromised data fidelity. Consequently, the pursuit of non-interferencesensing technology is pivotal for enabling independent measurements of concurrent input signals related to strain, pressure, andtemperature, ensuring precise signal acquisition. In this comprehensive review, we present an overview of the recent advances in noninterferencesensing strategies. We explore various fabrication methods for sensing strain, pressure, and temperature, emphasizing theuse of hybrid composite materials with distinct mechanical properties. This review contributes to the understanding of critical developmentsin wearable sensor technology that are vital for their ongoing application and evolution in numerous fields.
연합 학습 기반 분산 FMCW MIMO Radar를 활용한 모션 인식 알고리즘 개발 및 성능 분석
강종성,이승호,이정한,양윤지,박재현,Kang, Jong-Sung,Lee, Seung-Ho,Lee, Jeonghan,Yang, YunJi,Park, Jaehyun 대한임베디드공학회 2022 대한임베디드공학회논문지 Vol.17 No.3
In this paper, we implement a distributed FMCW MIMO radar system to obtain Micro Doppler signatures of target motions. In addition, we also develop federated learning based motion recognition algorithm based on the Micro-Doppler radar signature collected by the implemented FMCW MIMO radar system. Through the experiment, we have verified that the proposed federated learning based algorithm can improve the motion recognition accuracy up to 90%.