• Proceedings of the Materials Research Society of Korea Conference
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• 2012.05a
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• pp.72-72
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• 2012

Lithium rechargeable batteries have been widely used as key power sources for portable devices for the last couple of decades. Their high energy density and power have allowed the proliferation of ever more complex portable devices such as cellular phones, laptops and PDA's. For larger scale applications, such as batteries in plug-in hybrid electric vehicles (PHEV) or power tools, higher standards of the battery, especially in term of the rate (power) capability and energy density, are required. In PHEV, the materials in the rechargeable battery must be able to charge and discharge (power capability) with sufficient speed to take advantage of regenerative braking and give the desirable power to accelerate the car. The driving mileage of the electric car is simply a function of the energy density of the batteries. Since the successful launch of recent Ni-MH (Nickel Metal Hydride)-based HEVs (Hybrid Electric Vehicles) in the market, there has been intense demand for the high power-capable Li battery with higher energy density and reduced cost to make HEV vehicles more efficient and reduce emissions. However, current Li rechargeable battery technology has to improve significantly to meet the requirements for HEV applications not to mention PHEV. In an effort to design and develop an advanced electrode material with high power and energy for Li rechargeable batteries, we approached to this in two different length scales - Atomic and Nano engineering of materials. In the atomic design of electrode materials, we have combined theoretical investigation using ab initio calculations with experimental realization. Based on fundamental understanding on Li diffusion, polaronic conduction, operating potential, electronic structure and atomic bonding nature of electrode materials by theoretical calculations, we could identify and define the problems of existing electrode materials, suggest possible strategy and experimentally improve the electrochemical property. This approach often leads to a design of completely new compounds with new crystal structures. In this seminar, I will talk about two examples of electrode material study under this approach; $LiNi_{0.5}Mn_{0.5}O_2$ based layered materials and olivine based multi-component systems. In the other scale of approach; nano engineering; the morphology of electrode materials are controlled in nano scales to explore new electrochemical properties arising from the limited length scales and nano scale electrode architecture. Power, energy and cycle stability are demonstrated to be sensitively affected by electrode architecture in nano scales. This part of story will be only given summarized in the talk.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.91-91
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• 2013

Imagine a world where we could biomanufacture hybrid nanomaterials having atomic-scale resolution over functionality and architecture. Toward this vision, a fundamental challenge in materials science is how to design and synthesize protein-like material that can be fully self-assembled and exhibit information-specific process. In an ongoing effort to extend the fundamental understanding of protein structure to non-natural systems, we have designed a class of short peptides to fold like proteins and assemble into defined nanostructures. In this talk, I will talk about new strategies to drive the self-assembled structures designing sequence of peptide. I will also discuss about the specific interaction between proteins and inorganics that can be used for the development of new hybrid solar energy devices. Splitting water into hydrogen and oxygen is one of the promising pathways for solar to energy convertsion and storage system. The oxygen evolution reaction (OER) has been regarded as a major bottleneck in the overall water splitting process due to the slow transfer rate of four electrons and the high activation energy barrier for O-O bond formation. In nature, there is a water oxidation complex (WOC) in photosystem II (PSII) comprised of the earthabundant elements Mn and Ca. The WOC in photosystem II, in the form of a cubical CaMn4O5 cluster, efficiently catalyzes water oxidation under neutral conditions with extremely low overpotential (~160 mV) and a high TOF number. The cluster is stabilized by a surrounding redox-active peptide ligand, and undergo successive changes in oxidation state by PCET (proton-coupled electron transfer) reaction with the peptide ligand. It is fundamental challenge to achieve a level of structural complexity and functionality that rivals that seen in the cubane Mn4CaO5 cluster and surrounding peptide in nature. In this presentation, I will present a new strategy to mimic the natural photosystem. The approach is based on the atomically defined assembly based on the short redox-active peptide sequences. Additionally, I will show a newly identified manganese based compound that is very close to manganese clusters in photosystem II.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Knowledge Management Research
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• v.24 no.4
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• pp.219-235
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• 2023

The advancement of digital technology and the impact of COVID-19 have brought about changes in corporate innovation and organizational culture, thereby highlighting the significance of Smart Learning in the field of HRD (Human Resource Development). This trend has led to an increased interest in personalized Smart Learning among employees due to the growth of hybrid work and the widespread adoption of smart work practices. This study aimed to illuminate the relative importance of the factors that constitute Smart Learning from the perspective of HRD practitioners. Through a review of prior literature, Smart Learning hierarchy and factors most fitting to the current context were identified, and their relative importance was determined using the AHP method. Consequently, in the first-tier factors, importance was confirmed in the order of 'Learning Activities', 'Teaching Activities', 'Learning Content', 'Assessment and Evaluations', and 'Learning Time and Space'. At the second-tier encompassing all factors, 'Pedagogical Strategy', 'Learning Results', 'Learning Tasks', 'Learning Goal', and 'Learning Support' emerged within the top five factors. These findings are significant in that they redefine the concept of smart learning and propose an academic framework for future research. Additionally, from a practical perspective, it is anticipated that this study will contribute valuable insights for HRD practitioners, aiding them in focusing on which factors to prioritize for enhancing and advancing Smart Learning initiatives.

• Journal of Forest and Environmental Science
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• v.11 no.1
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• pp.81-101
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• 1995

Random amplified polymorphic DNA (RAPD) technology, a recent approach in molecular genetics, is much usable to select the elite trees and to maximize the genetic gain in forest tree breeding program, providing a clue to determine the genetic marker-trait correlation. This review intorduces research on bark thickness and breeding strategy in Pinus elliottii, Pinus caribaea and their hybrid by Queensland Forest Service and ForBio Research Pty Ltd, University of Queensland, which employ RAPD technology. Genetic linkage map of $F_1$ hybrids includes 186 RAPD markers and 16 linkage groups (1641 cM long in total) and 6 quantitative trait loci are located putatively for bark thickness. Following recent research results and experiences in pine breeding programs, the forseeable stages in the application and development are proposed for marker assisted selectin; stage 1-determination of species specific markers for genes controlling traits of commercial interest, and stage 2-determination of marker-allele association for specific allelic variants within pure species. As pines inherit their megagametophytes from the seed parent and zygotic embryos from both male and female parents, the determination of marker-trait correlation is possible even in embryo stage, eventually making ways for the early selection of elite individuals.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.1
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• pp.37-44
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• 2011

Parthenogenetic embryonic stem (pES) cells could provide a valuable model for research into genomic imprinting and X-linked diseases. In this study, pES cell lines were established from oocytes of hybrid offspring of Kunming and 129/Sv mice, and pluripotency of pES cells was evaluated. The pES cells maintained in the undifferentiated state for more than 50 passages had normal karyotypes with XX sex chromosomes and exhibited high activities of alkaline phosphatase (AKP) and telomerase. Meanwhile, these cells expressed ES cell molecular markers SSEA-1, Oct-4, Nanog, and GDF3 but not SSEA-3 detected by immunohistochemistry and RT-PCR. The pES cells could be differentiated into various types of cells from three germ layers in vitro by analysis of embryoid bodies (EBs) with immunohistochemistry and RT-PCR, and in vivo by observation of pES cell-derived teratoma sections. Therefore, the established pES cell lines contained all features of mouse ES cells. This work provides a new strategy for isolating pES cells from Kunming mice, and the pES cell lines could be applied as the cell model in research into genomic imprinting and epigenetic regulation of Kunming mice.

• Bulletin of the Korean Chemical Society
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• v.26 no.11
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• pp.1653-1668
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• 2005

Assembly of hybrid mesophases through the combination of amphiphilic block copolymers, acting as structuredirecting agents, and silicon sources using low acid catalyst concentration regimes is a versatile strategy to produce large quantities of high-quality ordered large-pore mesoporous silicas in a very reproducible manner. Controlling structural and textural properties is proven to be straightforward at low HCl concentrations with the adjustment of synthesis gel composition and the option of adding co-structure-directing molecules. In this account, we illustrate how various types of large-pore mesoporous silica can easily be prepared in high phase purity with tailored pore dimensions and tailored level of framework interconnectivity. Silica mesophases with two-dimensional hexagonal (p6mm) and three-dimensional cubi (Fm$\overline{3}$m, Im$\overline{3}$m and Ia$\overline{3}$d) symmetries are generated in aqueous solution by employing HCl concentrations in the range of 0.1−0.5 M and polyalkylene oxide-based triblock copolymers such as Pluronic P123 $(EO_{20}-PO_{70}-EO_{20})$ and Pluronic F127 $(EO_{106}-PO_{70}-EO_{106})$. Characterizations by powder X-ray diffraction, nitrogen physisorption, and transmission electron microscopy show that the mesoporous materials all possess high specific surface areas, high pore volumes and readily tunable pore diameters in narrow distribution of sizes ranging from 4 to 12 nm. Furthermore, we discuss our recent advances achieved in order to extend widely the phase domains in which single mesostructures are formed. Emphasis is put on the first synthetic product phase diagrams obtained in $SiO_2$-triblock copolymer-BuOH-$H_2O$ systems, with tuning amounts of butanol and silica source correspondingly. It is expected that the extended phase domains will allow designed synthesis of mesoporous silicas with targeted characteristics, offering vast prospects for future applications.

• Journal of Power Electronics
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• v.17 no.2
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• pp.476-489
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• 2017

Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1305-1317
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• 2015

Distributed generation systems (DGSs) have been getting more and more attention in terms of renewable energy use and new generation technologies in the past decades. The self-excited induction generator (SEIG) occupies an important role in the area of energy conversion due to its low cost, robustness and simple control. Unlike synchronous generators, the SEIG has to absorb capacitive reactive power from the outer device aiming to stabilize the terminal voltage at load changes. This paper presents a novel static VAR compensator (SVC) called a magnetic energy recovery switch (MERS) to serve as a voltage controller in SEIG powered DGSs. In addition, many small scale SEIGs, instead of a single large one, are applied and devoted to promote the generation efficiency. To begin with, an expandable mathematic model based on a d-q equivalent circuit is created for parallel SEIGs. The control method of the MERS is further improved with the objective of broadening its operating range and restraining current harmonics by parameter optimization. A hybrid control strategy is developed by taking both of the stand-alone and grid-connected modes into consideration. Then simulation and experiments are carried out in the case of single and double SEIG(s) generation. Finally, the measurement results verify that the proposed DGS with SVC-MERS achieves a better stability and higher feasibility. The major advantages of the mentioned variable reactive power supplier, when compared to the STATCOM, include the adoption of a small DC capacitor, line frequency switching, simple control and less loss.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.271-280
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• 1999

인공신경망을 시계열예측에 적용하는 경우에 고려되어야 할 문제중, 특히 모형에 적합한 입력변수의 생성이 중요시되고 있는데, 이러한 분야는 인공신경망의 모형생성과정에서 입력변수에 대한 전처리기법으로써 다양하게 제시되어 왔다. 가장 최근의 입력변수 전처리기법으로써 제시되고 있는 신호처리기법은 전통적 주기분할처리방법인 푸리에변환기법(Fourier transforms)을 비롯하여 이를 확장시킨 개념인 웨이블릿변환기법(wavelet transforms) 등으로 대별될 수 있다. 이는 기본적으로 시계열이 다수의 주기(cycle)들로 구성된 상이한 시계열들의 집합이라는 가정에서 출발하고 있다. 전통적으로 이러한 시계열은 전기 또는 전자공학에서 주파수영역분할, 즉 고주파 및 저주파수를 분할하기 위한 기법에 적용되어 왔다. 그러나, 최근에는 이러한 연구가 다양한 분야에 활발하게 응용되기 시작하였으며, 그 중의 대표적인 예가 바로 경영분야의 재무시계열에 대한 분석이다 전통적으로 재무시계열은 장, 단기의사결정을 가진 시장참여자들간의 거래특성이 시계열에 각기 달리 가격으로 반영되기 때문에 이러한 상이한 집단들의 고유한 거래움직임으로 말미암아 예를 들어, 주식시장이 프랙탈구조를 가지고 있다고 보기도 한다. 이처럼 재무시계열은 다양한 사회현상의 집합체라고 볼 수 있으며, 그만큼 예측모형을 구축하는데 어려움이 따른다. 본 연구는 이러한 시계열의 주기적 특성에 기반을 둔 신호처리분석으로서 기존의 시계열로부터 노이즈를 줄여 주면서 보다 의미 있는 정보로 변환시켜 줄 수 있는 웨이블릿분석 방법론을 새로운 필터링기법으로 사용하여 현재 많은 연구가 진행되고 있는 인공신경망과의 모형결합을 통해 기존연구와는 다른 새로운 통합예측방법론을 제시하고자 한다. 본 연구에서 제시하는 통합방법론은 크게 2단계 과정을 거쳐 예측모형으로 완성이 된다. 즉, 1차 모형단계에서 원시 재무시계열은 먼저 웨이블릿분석을 통해서 노이즈가 필터링 되는 동시에, 과거 재무시계열의 프랙탈 구조, 즉 비선형적인 움직임을 보다 잘 반영시켜 주는 다차원 주기요소를 가지는 시계열로 분해, 생성되며, 이렇게 주기에 따라 장단기로 분할된 시계열들은 2차 모형단계에서 신경망의 새로운 입력변수로서 사용되어 최종적인 인공 신경망모델을 구축하는 데 반영된다.