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Engineering nanomedicine via biological systems
박지호 한국공업화학회 2014 한국공업화학회 연구논문 초록집 Vol.2014 No.1
Over the past decade, widespread progress in nanotechnology has produced an impressive array of nanodevices with powerful electromagnetic and therapeutic properties. Nonetheless, our capacity to precisely home these materials to regions of disease in vivo has remained very limited and, despite three decades of research, ligand-targeted nanomedicines have yet to provide a benefit to patients. A fundamental limitation of current approaches to nanoparticle targeting is that they lack mechanisms of communication and amplification through which specific targeting events could assist the targeting of materials still in circulation. This presentation will discuss our recent approaches to engineering nanomedicine via biological systems. First, we have developed drug delivery nanosystems where two distinct nanomaterials work in concert within the bloodstream to amplify tumor targeting and improve therapy in vivo, which was inspired by examples of communication in natural targeting systems (e.g. inflammatory cell recruitment to infection). Secondly, we have developed drug delivery nanosystems where tumorderived membrane vesicles, which is an innate biological transport system, were engineered in situ to improve tumor penetration of therapeutic compounds and their therapeutic efficacy.
박지호,박비오,이원구 한국정밀공학회 2019 International Journal of Precision Engineering and Vol.20 No.11
Most user-interactive rollator handles fabricated so far have had errors in classifying users’ walking intentions due to the structure not considering gravity, in addition to their usage not being intuitive. Here, we introduce a smart handle based on ‘arc motion’ horizontal to the ground to classify the user’s walking intentions accurately. In designing the handle, the limit of grip angle is adopted considering the arc motion. This minimizes the deflection of the handle by gravity and can allow the handle to be optimized for the grip motion. Moreover, we applied the results of our analysis of users’ walking intentions in the arc motion to machine learning. In understanding the user’s intentions to walk, we created two support vector machine classifiers from handle data collected through four Hall sensors. This combination of the arc motion and machine learning has significantly reduced classification errors. As a result, we ensured an accuracy of 0.95, which is a widely used standard in control.
MIC시스템의 효율개선을 위한 새로운 Active Clamp 스위칭 기법
박지호,송성근,오승열,최정식,박성준 대한전기학회 2012 대한전기학회 학술대회 논문집 Vol.2012 No.4
태양광 모듈형 전력변환장치인 MIC시스템에 대한 연구가 활발히 진행되면서 스위칭 손실에 따른 효율감소 및 신뢰성이 가장 큰 문제가 되고 있다. 이러한 문제를 해결하기 위해 본 논문에서는 변압기 누설인덕턴스 성분으로 인한 전압스파이크를 제거하여 안정적인 스위칭으로 신뢰성을 확보하고, 손실을 감소시켜 효율개선 할 수 있는 새로운 Active Clamp 스위칭 기법을 제안하였다.
Correlation between spin density and Vth instability of IGZO thin-film transistors
박지호,이소형,이희성,김성기,박권식,윤소영 한국물리학회 2018 Current Applied Physics Vol.18 No.11
The electron spin resonance (ESR) detects point defect of the In-Ga-Zn oxide (IGZO) like singly ionized oxygen vacancies and excess oxygen, and get spin density as a parameter of defect state. So, we demonstrated the spin density measurement of the IGZO film with various deposition conditions and it has linear relationship. Moreover, we matched the spin density with the total BTS and the threshold voltage (Vth) distribution of the IGZO thin film transistors. The total BTS ΔVth and the Vth distribution were degraded due to the spin density increases. The spin density is the useful indicator to predict Vth instability of IGZO TFTs.
박지호,김동식 순천향대학교 부설 산업기술연구소 2021 순천향 산업기술연구소논문집 Vol.27 No.2
Goldman Sachs recently laid off 598 top talents, while Google and NASA established a singularity university. As we enter the era of the 4th Industrial Revolution, each company and university is nurturing talent for the age of artificial intelligence(AI). As factories and various facilities are automated and AI and the Internet of Things (IoT) enter homes and businesses, interest in automation is gradually increasing, and AI robots are replacing human jobs. Therefore, a study was conducted on the implementation of a sorting robot for smart factory automation. The hardware of the robot was realized using TETRIX, and it was configured to recognize the color of blocks and classify the object using NXT color sensors. The color sensor is used to determine the type of a block and a linetracer is to help figure out location, and the block was placed in the right place. The control program was implemented using LabVIEW, and the NXT was implemented to control the robot through the signal obtained from the color sensor.