Comparison of key factors in radar-based quantitative precipitation nowcasting using deep learning

Daehyeon Han,Yeji Shin,Jungho Im,Juhyun Lee 한국기상학회 2022 한국기상학회 학술대회 논문집 Vol.2022 No.10

정지궤도 위성과 기계학습 기법을 이용한 대류운 전조 탐지

한대현(Daehyeon Han),이상균(Sanggyun Lee),임정호(Jungho Im) 대한공간정보학회 2018 한국공간정보학회 학술대회 Vol.2018 No.11

ICESat-2 고도계 자료를 활용한 여름철 북극 융빙호 탐지

한대현 ( Daehyeon Han ),김영준 ( Young Jun Kim ),정시훈 ( Sihun Jung ),심성문 ( Seongmun Sim ),김우혁 ( Woohyeok Kim ),장은나 ( Eunna Jang ),임정호 ( Jungho Im ),김현철 ( Hyun-cheol Kim ) 대한원격탐사학회 2021 大韓遠隔探査學會誌 Vol.37 No.5

북극의 융빙호(melt pond)는 해빙 면적 감소 및 북극 빙권 변화에 중요한 역할을 하기 때문에 융빙호의 정확한 관측이 필요하다. 미국 NASA의 차세대 고도계 위성인 Ice, Cloud, and Land elevation Satellite-2 (ICESat-2)는 532 nm의 녹색 레이저를 발사한 뒤 반사되는 광자(photon)의 이동 시간을 계산하여 전 지구적으로 고해상도 고도 정보를 관측한다. ICESat-2는 현재 널리 쓰이고 있는 고도계인 CryoSat-2에 비해 세밀한 관측이 가능하기 때문에, Cryosat-2에서 관측할 수 없는 작은 규모의 융빙호를 탐지할 수 있을 것으로 기대된다. ICESat-2의 기본적인 정보로는 표면 높이(surface height)와 반사되는 광자의 수(photon count)가 있다. 본 연구에서는 각 ICESat-2 지점을 중심으로 10 m 길이의 segment를 생성하여 segment 내의 높이 표준편차와 총 광자 수를 활용한 융빙호 탐지 알고리즘을 제시하였다. 융빙호는 표면이 해빙에 비해 매끄러워서 높이의 분산이 적으므로 높이의 표준편차를 활용하여 일차적으로 융빙호와 해빙을 분류하였다. 그 다음으로는 융빙호 중에서 표면이 물인 융빙호와 얼음 표면인 융빙호를 분류하였다. 표면이 물인 융빙호는 광자를 많이 흡수하기 때문에 단위 segment 내에서 반사되어 수집된 광자의 수가 적으며, 반대로 얼음으로 덮인 융빙호는 반사되는 광자의 수가 많다. 결과적으로 본 연구에서 제시하는 융빙호 탐지 방법을 통해 물과 얼음으로 덮인 융빙호를 구별하여 탐지할 수 있다. Sentinel-2 광학 영상을 활용하여 융빙호 탐지 결과의 정성적인 분석을 하였다. 그 결과 Sentinel-2 광학 영상으로 구분하기 어려운 표면이 물인 융빙호와 얼음인 융빙호를 ICESat-2를 활용해 효과적으로 분류하였다. 마지막으로 고도계 위성 및 광학 영상을 활용한 융빙호 탐지의 고찰을 서술하였다. As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA’s latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt ponds than the melt ponds with the specular ice, the number of photons per segment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.

Unexpectedly high energy density of a Li-Ion battery by oxygen redox in LiNiO₂ cathode: First-principles study

Choi, Daehyeon,Kang, Joonhee,Han, Byungchan Elsevier 2019 ELECTROCHIMICA ACTA Vol.294 No.-

<P><B>Abstract</B></P> <P>Conventionally neglected mechanism of reversible redox reactions by oxygen ions in lithium-nickel oxide materials (LNO; Li<SUB>2<I>x</I> </SUB>Ni<SUB>2-2<I>x</I> </SUB>O<SUB>2</SUB>, 0 < <I>x</I> < 1) is proposed as a primary cause of unexpectedly high energy density of Li-ion battery. Using first-principles density functional theory calculations, cluster expansion theory, and Monte Carlo simulations, we unveil the underlying mechanism that is ascribed to the phase transition between layered and rocksalt structures initiated by cation disordering of Li and Ni at certain Li composition. At <I>x</I> = 0.5, the oxygen ions are put under specific chemical bondings of straight-linear type LiOLi configuration. They enable an active oxygen redox reaction involving peroxo (O<SUB>2</SUB> <SUP>2−</SUP>) and superoxo (O<SUB>2</SUB> <SUP>−</SUP>) ions, shown to dramatically increase the energy density of the LNO cathode. Using Monte Carlo simulations, we identify the proportional information to find the LiOLi configurations around the synthetic temperature of LNO materials. Our results indicate that the cation-disorder is a driving force for the oxygen redox via formation of the specific bondings. On the basis of our study, it is expected to provide useful guidelines for the design of Li-ion batteries with high energy densities beyond conventional ones.</P> <P><B>Graphical abstract</B></P> <P>Using first-principles calculations, we unveil the underlying mechanism that is ascribed to the high energy density of LiNiO<SUB>2</SUB> initiated by cation disordering of Li and Ni at certain Li composition.</P> <P>[DISPLAY OMISSION]</P>

DME 도입의 경제성 평가

김대현(Daehyeon Kim),정회인(Hyein Jung),한종훈(Chonghun Han) 한국가스학회 2009 한국가스학회 학술대회논문집 Vol.2009 No.4

First-principles study on thermodynamic stability of the hybrid interfacial structure of LiMn₂O₄ cathode and carbonate electrolyte in Li-ion batteries

Choi, Daehyeon,Kang, Joonhee,Park, Jinwoo,Han, Byungchan The Royal Society of Chemistry 2018 Physical chemistry chemical physics Vol.20 No.17

<P>The solid electrolyte interphase (SEI) of Li-ion batteries (LIBs) has been extensively studied, with most research focused on the anode, because of its significant impact on the prolonged cycle life, initial capacity loss, and safety issues. Using first-principles density functional theory (DFT) calculations and <I>ab initio</I> molecular dynamics (AIMD) simulations with the Hubbard correction, we examine the thermodynamic structure prediction and electrochemical stability of a spinel LiMn2O4 cathode interfaced with a carbonate electrolyte. The electronic energy levels of frontier orbitals of the electrolyte and the work function of the cathode offer clear characterization of the interfacial reactions. Our results based on both DFT calculations and AIMD simulations propose that the proton transfer mechanism at the hybrid interface is essential for initiating the SEI layer formation on the LiMn2O4 surface. Our results can be useful for identifying design concepts in the development of stable and high capacity LIBs with optimized electrodes and high-performance electrolytes.</P>

부생수소 활용 발전용 연료전지 경제성 평가

김대현(Daehyeon Kim),정창현(Changhyun Jung),정회인(Hyein Jung),한종훈(Chonghun Han),이상욱(Sangwook Lee) 한국가스학회 2008 한국가스학회 학술대회논문집 Vol.2008 No.4

Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images

Yoo, Cheolhee,Han, Daehyeon,Im, Jungho,Bechtel, Benjamin Elsevier 2019 ISPRS journal of photogrammetry and remote sensing Vol.157 No.-

<P><B>Abstract</B></P> <P>The Local Climate Zone (LCZ) scheme is a classification system providing a standardization framework to present the characteristics of urban forms and functions, especially for urban heat island (UHI) research. Landsat-based 100 m resolution LCZ maps have been classified by the World Urban Database and Portal Tool (WUDAPT) method using a random forest (RF) machine learning classifier. Some studies have proposed modified RF and convolutional neural network (CNN) approaches. This study aims to compare CNN with an RF classifier for LCZ mapping in great detail. We designed five schemes (three RF-based schemes (S1–S3) and two CNN-based ones (S4–S5)), which consist of various combinations of input features from bitemporal Landsat 8 data over four global mega cities: Rome, Hong Kong, Madrid, and Chicago. Among the five schemes, the CNN-based one with the incorporation of a larger neighborhood information showed the best classification performance. When compared to the WUDAPT workflow, the overall accuracies for entire land cover classes (OA) and for urban LCZ types (i.e., LCZ1-10; OA<SUB>urb</SUB>) increased by about 6–8% and 10–13%, respectively, for the four cities. The transferability of LCZ models for the four cities were evaluated, showing that CNN consistently resulted in higher accuracy (increased by about 7–18% and 18–29% for OA and OA<SUB>urb</SUB>, respectively) than RF. This study revealed that the CNN classifier classified particularly well for the specific LCZ classes in which buildings were mixed with trees or buildings or plants were sparsely distributed. The research findings can provide a basis for guidance of future LCZ classification using deep learning.</P>

Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery

Kim, Miae,Lee, Junghee,Han, Daehyeon,Shin, Minso,Im, Jungho,Lee, Junghye,Quackenbush, Lindi J.,Gu, Zhu IEEE 2018 IEEE journal of selected topics in applied earth o Vol.11 No.12

<P>Researchers constantly seek more efficient detection techniques to better utilize enhanced image resolution in accurately detecting and monitoring land cover. Recently, convolutional neural networks (CNNs) have shown high performances comparable to or even better than widely used and adopted machine learning techniques. The aim of this study is to investigate the application of CNNs for land cover classification by using two-dimensional (2-D) spectral curve graphs from multispectral satellite images. The land cover classification was conducted in Concord, New Hampshire, USA, and South Korea by using multispectral images acquired from 30-m Landsat-8 and 500-m Geostationary Ocean Color Imager images. For the construction of input data specific to CNNs, two seasons (winter and summer) of multispectral bands were transformed into 2-D spectral curve graphs for each class. Land cover classification results of CNNs were compared with the results of support vector machines (SVMs) and random forest (RFs). The CNNs model showed higher performance than RFs and SVMs in both study sites. The examination of land cover classification maps demonstrates a good agreement with reference maps, Google Earth images, and existing global scale land cover map, especially for croplands. Using the spectral curve graph could incorporate the phenological cycles on classifying the land cover types. This study shows that the use of a new transformation of spectral bands into a 2-D form for application in CNNs can improve land cover classification performance.</P>

Multifaceted C-terminus of HSP70-interacting protein regulates tumorigenesis via protein quality control

서진호,Su Yeon Han,Daehyeon Seong,Hyun-Ji Han,Jaewhan Song 대한약학회 2019 Archives of Pharmacal Research Vol.42 No.1

C-terminus of heat shock protein 70 (HSP70)-interacting protein (CHIP) is an E3 ligase involved in a variety of protein homeostasis events implicated in diverse signaling pathways. Its involvement in varied and even opposite signaling circuits might be due to its hallmark signature of associating with molecular chaperones, including HSP90 and HSP70. Together, these proteins may be pivotal in implementing protein quality control. A curious and puzzling aspect of the function of CHIP is its capability to induce protein degradation via the proteasome- or lysosome-dependent pathways. In addition, these pathways are combined with ubiquitin-dependent or -independent pathways. This review focuses on the role of CHIP in the development or suppression of tumorigenesis. CHIP can act as a tumor suppressor by downregulating various oncogenes. CHIP also displays an oncogenic feature involving the inhibition of diverse tumor suppressors, including proteins related to intrinsic and extrinsic apoptotic pathways. The ability of CHIP to exhibit dual roles in determining the fate of cells has not been studied analytically. However, its association with various proteins involved in protein quality control might play a major role. In this review, the mechanistic roles of CHIP in tumor formation based on the regulation of diverse proteins are discussed.