Highly stretchable electric circuits from a composite material of silver nanoparticles and elastomeric fibres.

Park, Minwoo,Im, Jungkyun,Shin, Minkwan,Min, Yuho,Park, Jaeyoon,Cho, Heesook,Park, Soojin,Shim, Mun-Bo,Jeon, Sanghun,Chung, Dae-Young,Bae, Jihyun,Park, Jongjin,Jeong, Unyong,Kim, Kinam Nature Pub. Group 2012 Nature nanotechnology Vol.7 No.12

<P>Conductive electrodes and electric circuits that can remain active and electrically stable under large mechanical deformations are highly desirable for applications such as flexible displays, field-effect transistors, energy-related devices, smart clothing and actuators. However, high conductivity and stretchability seem to be mutually exclusive parameters. The most promising solution to this problem has been to use one-dimensional nanostructures such as carbon nanotubes and metal nanowires coated on a stretchable fabric, metal stripes with a wavy geometry, composite elastomers embedding conductive fillers and interpenetrating networks of a liquid metal and rubber. At present, the conductivity values at large strains remain too low to satisfy requirements for practical applications. Moreover, the ability to make arbitrary patterns over large areas is also desirable. Here, we introduce a conductive composite mat of silver nanoparticles and rubber fibres that allows the formation of highly stretchable circuits through a fabrication process that is compatible with any substrate and scalable for large-area applications. A silver nanoparticle precursor is absorbed in electrospun poly (styrene-block-butadiene-block-styrene) (SBS) rubber fibres and then converted into silver nanoparticles directly in the fibre mat. Percolation of the silver nanoparticles inside the fibres leads to a high bulk conductivity, which is preserved at large deformations (σ???2,200?S?cm(-1) at 100% strain for a 150-?m-thick mat). We design electric circuits directly on the electrospun fibre mat by nozzle printing, inkjet printing and spray printing of the precursor solution and fabricate a highly stretchable antenna, a strain sensor and a highly stretchable light-emitting diode as examples of applications.</P>

급발진 추정사고를 통한 자율주행자동차 교통사고 선행연구

박종진(Jongjin Park),인병덕(Byungduk In),박정우(Jungwoo Park),박하선(Hasun Park) 한국자동차공학회 2022 한국자동차공학회 부문종합 학술대회 Vol.2022 No.6

Machine learning model of facial expression outperforms models using analgesia nociception index and vital signs to predict postoperative pain intensity: a pilot study

Park Insun,Park Jae Hyon,Yoon Jongjin,나효석,오아영,유정희,Koo Bon-Wook 대한마취통증의학회 2024 Korean Journal of Anesthesiology Vol.77 No.2

Background: Few studies have evaluated the use of automated artificial intelligence (AI)-based pain recognition in postoperative settings or the correlation with pain intensity. In this study, various machine learning (ML)-based models using facial expressions, the analgesia nociception index (ANI), and vital signs were developed to predict postoperative pain intensity, and their performances for predicting severe postoperative pain were compared.Methods: In total, 155 facial expressions from patients who underwent gastrectomy were recorded postoperatively; one blinded anesthesiologist simultaneously recorded the ANI score, vital signs, and patient self-assessed pain intensity based on the 11-point numerical rating scale (NRS). The ML models’ area under the receiver operating characteristic curves (AUROCs) were calculated and compared using DeLong’s test.Results: ML models were constructed using facial expressions, ANI, vital signs, and different combinations of the three datasets. The ML model constructed using facial expressions best predicted an NRS ≥ 7 (AUROC 0.93) followed by the ML model combining facial expressions and vital signs (AUROC 0.84) in the test-set. ML models constructed using combined physiological signals (vital signs, ANI) performed better than models based on individual parameters for predicting NRS ≥ 7, although the AUROCs were inferior to those of the ML model based on facial expressions (all P < 0.050). Among these parameters, absolute and relative ANI had the worst AUROCs (0.69 and 0.68, respectively) for predicting NRS ≥ 7.Conclusions: The ML model constructed using facial expressions best predicted severe postoperative pain (NRS ≥ 7) and outperformed models constructed from physiological signals.

Feasibility of Deep Learning-Based Analysis of Auscultation for Screening Significant Stenosis of Native Arteriovenous Fistula for Hemodialysis Requiring Angioplasty

Park Jae Hyon,Park Insun,한기창,Yoon Jongjin,Sim Yongsik,Kim Soo Jin,원종윤,Lee Shina,Kwon Joon Ho,Moon Sungmo,김경민,김만득 대한영상의학회 2022 Korean Journal of Radiology Vol.23 No.10

Objective: To investigate the feasibility of using a deep learning-based analysis of auscultation data to predict significant stenosis of arteriovenous fistulas (AVF) in patients undergoing hemodialysis requiring percutaneous transluminal angioplasty (PTA). Materials and Methods: Forty patients (24 male and 16 female; median age, 62.5 years) with dysfunctional native AVF were prospectively recruited. Digital sounds from the AVF shunt were recorded using a wireless electronic stethoscope before (pre-PTA) and after PTA (post-PTA), and the audio files were subsequently converted to mel spectrograms, which were used to construct various deep convolutional neural network (DCNN) models (DenseNet201, EfficientNetB5, and ResNet50). The performance of these models for diagnosing ≥ 50% AVF stenosis was assessed and compared. The ground truth for the presence of ≥ 50% AVF stenosis was obtained using digital subtraction angiography. Gradient-weighted class activation mapping (Grad-CAM) was used to produce visual explanations for DCNN model decisions. Results: Eighty audio files were obtained from the 40 recruited patients and pooled for the study. Mel spectrograms of “pre-PTA” shunt sounds showed patterns corresponding to abnormal high-pitched bruits with systolic accentuation observed in patients with stenotic AVF. The ResNet50 and EfficientNetB5 models yielded an area under the receiver operating characteristic curve of 0.99 and 0.98, respectively, at optimized epochs for predicting ≥ 50% AVF stenosis. However, Grad- CAM heatmaps revealed that only ResNet50 highlighted areas relevant to AVF stenosis in the mel spectrogram. Conclusion: Mel spectrogram-based DCNN models, particularly ResNet50, successfully predicted the presence of significant AVF stenosis requiring PTA in this feasibility study and may potentially be used in AVF surveillance.

Interannual variability of winter precipitation linked to upper ocean heat content off the east coast of Korea

Park, JongJin,Nam, SungHyun John Wiley Sons, Ltd 2018 International Journal of Climatology Vol. No.

<P><B>ABSTRACT</B></P><P>We present a link between highly variable winter precipitation (e.g. occasional heavy snow) in the mountainous cities along the east coast of Korea and upper ocean heat content (OHC) in the western part of the East Sea (Japan Sea). After removing annual climatological cycle, OHC (as well as sea surface temperature, SST) variability coherent with the winter sea surface wind (SSW) is extracted using maximum covariance analysis (MCA). The first‐mode MCA pattern, explaining 68% of the total covariance, indicates that the stronger westerly (easterly) winter SSW links to larger (smaller) OHC in the upper 400 m or higher (lower) SST of the western part of the sea. Time series of the first‐mode MCA are comparable to winter precipitation variability at three local cities along the coast (Gangneung, Donghae, and Uljin) with significantly high correlation coefficients (0.84, 0.68, and 0.56, respectively). The links between OHC and SSW and between SSW and precipitation are discussed because zonal contrast of OHC drives zonal tilt of northerly monsoonal wind in winter by canonical turbulent momentum exchange within the marine planetary boundary layer (MPBL). The momentum exchange within the MPBL yields the interannual variability of SSW and thus, winter precipitation in the coastal cities.</P>

Ensemble UNet 3+ for Medical Image Segmentation

JongJin Park 한국인터넷방송통신학회 2023 International Journal of Internet, Broadcasting an Vol.15 No.1

In this paper, we proposed a new UNet 3+ model for medical image segmentation. The proposed ensemble(E) UNet 3+ model consists of UNet 3+s of varying depths into one unified architecture. UNet 3+s of varying depths have same encoder, but have their own decoders. They can bridge semantic gap between encoder and decoder nodes of UNet 3+. Deep supervision was used for learning on a total of 8 nodes of the E-UNet 3+ to improve performance. The proposed E-UNet 3+ model shows better segmentation results than those of the UNet 3+. As a result of the simulation, the E-UNet 3+ model using deep supervision was the best with loss function values of 0.8904 and 0.8562 for training and validation data. For the test data, the UNet 3+ model using deep supervision was the best with a value of 0.7406. Qualitative comparison of the simulation results shows the results of the proposed model are better than those of existing UNet 3+.

A new perspective on origin of the East Sea Intermediate Water: Observations of Argo floats

Park, JongJin,Lim, Byunghwan Elsevier 2018 Progress in oceanography Vol.160 No.-

<P><B>Abstract</B></P> <P>The East Sea Intermediate Water (ESIW), defined as the salinity minimum in the East Sea (hereafter ES) (Sea of Japan), is examined with respect to its overall characteristics and its low salinity origin using historical Argo float data from 1999 to 2015. Our findings suggest that the ESIW is formed in the western Japan Basin (40–42°N, 130–133°E), especially west of the North Korean front in North Korean waters, where strong negative surface wind stress curl resides in wintertime. The core ESIW near the formation site has temperatures of 3–4 °C and less than 33.98 psu salinity, warmer and fresher than that in the southern part of the ES. In order to trace the origin of the warmer and fresher water at the sea surface in winter, we analyzed the data in three different ways: (1) spatial distribution of surface water properties using monthly climatology from the Argo float data, (2) seasonal variation of heat and salt contents at the formation site, and (3) backtracking of surface drifter trajectories. Based on these analyses, it is likely that the warmer and fresher surface water properties found in the ESIW formation site are attributed to the low-salinity surface water advected from the southern part of the ES in autumn.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The ESIW is likely formed in North Korean waters of the western Japan Basin
. </LI> <LI> The ESIW near the formation site has warmer and fresher properties. </LI> <LI> Origin of the ESIW mostly comes from the low salinity Tsushima warm water. </LI> </UL> </P>

Monoclonal antibody K312-based depletion of pluripotent cells from differentiated stem cell progeny prevents teratoma formation

( Jongjin Park ),( Dong Gwang Lee ),( Na Geum Lee ),( Min-gi Kwon ),( Yeon Sung Son ),( Mi-young Son ),( Kwang-hee Bae ),( Jangwook Lee ),( Jong-gil Park ),( Nam-kyung Lee ),( Jeong-ki Min ) 생화학분자생물학회 2022 BMB Reports Vol.55 No.3

Human pluripotent stem cells (PSCs) have been utilized as a promising source in regenerative medicine. However, the risk of teratoma formation that comes with residual undifferentiated PSCs in differentiated cell populations is most concerning in the clinical use of PSC derivatives. Here, we report that a monoclonal antibody (mAb) targeting PSCs could distinguish undifferentiated PSCs, with potential teratoma-forming activity, from differentiated PSC progeny. A panel of hybridomas generated from mouse immunization with H9 human embryonic stem cells (hESCs) was screened for ESC-specific binding using flow cytometry. A novel mAb, K312, was selected considering its high stem cell-binding activity, and this mAb could bind to several human induced pluripotent stem cells and PSC lines. Cell-binding activity of K312 was markedly decreased as hESCs were differentiated into embryoid bodies or by retinoic acid treatment. In addition, a cell population negatively isolated from undifferentiated or differentiated H9 hESCs via K312 targeting showed a significantly reduced expression of pluripotency markers, including Oct4 and Nanog. Furthermore, K312-based depletion of pluripotent cells from differentiated PSC progeny completely prevented teratoma formation. Therefore, our findings suggest that K312 is utilizable in improving stem cell transplantation safety by specifically distinguishing residual undifferentiated PSCs. [BMB Reports 2022; 55(3): 142-147]

급발진 추정사고에서 운전자의 페달 오조작에 관한 사례 연구

박종진(Jongjin Park),박정만(Jeongman Park),이연섭(Yeonsub Lee) 한국자동차공학회 2019 한국자동차공학회 부문종합 학술대회 Vol.2019 No.5

기계 학습을 이용한 소프트웨어 성능 변화의 빅 데이터 분석과 공정 제어

박종진(Park, Jongjin) 대한전기학회 2019 정보 및 제어 심포지엄 논문집 Vol.2019 No.10