• 한국분말재료학회지
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• 제26권1호
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• pp.58-69
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• 2019

High performance lithium-ion batteries (LIBs) have attracted considerable attention as essential energy sources for high-technology electrical devices such as electrical vehicles, unmanned drones, uninterruptible power supply, and artificial intelligence robots because of their high energy density (150-250 Wh/kg), long lifetime (> 500 cycles), low toxicity, and low memory effects. Of the high-performance LIB components, cathode materials have a significant effect on the capacity, lifetime, energy density, power density, and operating conditions of high-performance LIBs. This is because cathode materials have limitations with respect to a lower specific capacity and cycling stability as compared to anode materials. In addition, cathode materials present difficulties when used with LIBs in electric vehicles because of their poor rate performance. Therefore, this study summarizes the structural and electrochemical properties of cathode materials for LIBs used in electric vehicles. In addition, we consider unique strategies to improve their structural and electrochemical properties.

• 대한의용생체공학회:의공학회지
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• 제28권1호
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• pp.17-23
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• 2007

Long-term potentiation (LTP) of synaptic transmission is the most widely studied model for learning and memory. However its mechanisms are not clearly elucidated and are a subject for intense investigation. Previous attempts to decipher cellular mechanisms and network properties involved a current-source density analysis (CSDA) of the LTP from small animal hippocampus measured with a limited number of microelectrodes (typically <3), only revealing limited nature of spatiotemporal dynamics. Recent advancement in multi-electrode array (MEA) technology allows continuous and simultaneous recordings of LTP with more than 60 electrodes. However CSDA via the standard Laplacian transform is still limited due to its relatively high sensitivity toward noise, inability of resolving overlapped current sources and sinks, and its requirement for tissue conductivity values. In this study, we propose a new methodology for improved CSDA. Independent component analysis and its joint use (i.e., Joint-ICA) are applied to extract spatiotemporal components of LTP. The results show that ICA and Joint-ICA are capable of extracting independent spatiotemporal components of LTP generators. The ICs of LTP indicate the reversing roles of current sources and sinks which are associated with LTP.

• Journal of Ginseng Research
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• 제42권3호
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• pp.298-303
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• 2018

Background: Panax ginseng is one of the most commonly used medicinal herbs worldwide for a variety of therapeutic properties including neurocognitive effects. Ginsenoside Rg1 is one of the most abundant active chemical constituents of this herb with known neuroprotective, anxiolytic, and cognition improving effects. Methods: We investigated the effects of Rg1 on the medial prefrontal cortex (mPFC), a key brain region involved in cognition, information processing, working memory, and decision making. In this study, the effects of systemic administration of Rg1 (1 mg/kg, 3 mg/kg, or 10 mg/kg) on (1) spontaneous firing of the medial prefrontal cortical neurons and (2) long-term potentiation (LTP) in the hippocampal-medial prefrontal cortical (HP-mPFC) pathway were investigated in male Sprague-Dawley rats. Results: The spontaneous neuronal activity of approximately 50% the recorded pyramidal cells in the mPFC was suppressed by Rg1. In addition, Rg1 attenuated LTP in the HP-mPFC pathway. These effects were not dose-dependent. Conclusion: This report suggests that acute treatment of Rg1 impairs LTP in the HP-mPFC pathway, perhaps by suppressing the firing of a subset of mPFC neurons that may contribute to the neurocognitive effects of Rg1.

• 재무관리연구
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• 제24권3호
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.

• 소성∙가공
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• 제9권6호
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• pp.653-662
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• 2000

Wrinkling is one of the major defects in sheet metal products together with tearing, springback and other geometric and surface defects. The initiation and growth of wrinkles are influenced by many factors such as stress ratios, mechanical properties of the sheet material, geometry of the workpiece, contact condition, etc. It is difficult to analyze the wrinkling initiation and growth considering all the factors because the effects of the factors are very complex and the wrinkling behavior may show a wide scatter of data even for small deviations of factors. The finite element analyses of the wrinkling initiation and growth in the sheet metal forming process provide the detailed information about the wrinkling behavior of sheet metal. The direct analyses of the wrinkling initiation and growth, however, bring about a little difficulty in complex industrial problems because it needs large memory size and long computation time. In the present study, therefore, a global-local analysis technique is introduced for the computational efficiency. Through the analysis of wrinkling in the door inner stamping process, the efficiency of the global-local analysis technique is investigated.

• Journal of Ginseng Research
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• 제45권5호
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• pp.599-609
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• 2021

Ginseng has long been considered as an herbal medicine. Recent data suggest that ginseng has antiinflammatory properties and can improve learning- and memory-related function in the central nervous system (CNS) following the development of CNS neuroinflammatory diseases such as Alzheimer's disease, cerebral ischemia, and other neurological disorders. In this review, we discuss the role of ginseng in the neurovascular unit, which is composed of endothelial cells surrounded by astrocytes, pericytes, microglia, neural stem cells, oligodendrocytes, and neurons, especially their blood-brain barrier maintenance, anti-inflammatory effects and regenerative functions. In addition, cell-cell communication enhanced by ginseng may be attributed to regeneration via induction of neurogenesis and angiogenesis in CNS diseases. Thus, ginseng may have therapeutic potential to exert cognitive improvement in neuroinflammatory diseases such as stroke, traumatic brain injury, multiple sclerosis, Parkinson's disease, and Alzheimer's disease.

• 한국방사선학회논문지
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• 제7권1호
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• pp.25-30
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• 2013

본 논문은 1998년부터 2011년까지 강릉 지역의 지방 방사능 측정소에서 측정된 공간 감마선량률의 통계 적인 성질을 조사하였다. Autocorrelation Function Analysis(ACF), Rescaled Range Analysis(R/S Analysis), Detrended Fluctuation Analysis(DFA)의 방법들이 사용되었으며, 이 중 DFA는 non-stationary한 시계열의 장거리 상관성을 보여주는 좋은 방법으로 알려져 있다. 우리는 이 연구를 통해 다음의 사실을 알았다. 첫 번째, 공간 감마선량률은 두 가지 다른 경향을 갖는 크로스 오버가 나타난다. 이것은 연중 공간 감마선량률은 강한 장기 기억 특성이 나타나는데 비해 연간으로 넘어가면 상관성이 사라지는 것을 의미한다. 두 번째, 각 분석 방법들의 지수들이 있는데 이 지수들 사이의 관계식이 맞음을 확인 하였다.

• 한국재료학회지
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• 제27권11호
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• pp.590-596
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• 2017

We demonstrated a CNT synaptic transistor by integrating 6,6-phenyl-C61 butyric acid methyl ester(PCBM) molecules as charge storage molecules in a polyimide(PI) dielectric layer with carbon nanotubes(CNTs) for the transistor channel. Specifically, we fabricated and compared three different kinds of CNT-based synaptic transistors: a control device with $Al_2O_3/PI$, a single PCBM device with $Al_2O_3/PI:PCBM$(0.1 wt%), and a double PCBM device with $Al_2O_3/PI:PCBM$(0.1 wt%)/PI:PCBM(0.05 wt%). Statistically, essential device parameters such as Off and On currents, On/Off ratio, device yield, and long-term retention stability for the three kinds of transistor devices were extracted and compared. Notably, the double PCBM device exhibited the most excellent memory transistor behavior. Pulse response properties with postsynaptic dynamic current were also evaluated. Among all of the testing devices, double PCBM device consumed such low power for stand-by and its peak current ratio was so large that the postsynaptic current was also reliably and repeatedly generated. Postsynaptic hole currents through the CNT channel can be generated by electrons trapped in the PCBM molecules and last for a relatively short time(~ hundreds of msec). Under one certain testing configuration, the electrons trapped in the PCBM can also be preserved in a nonvolatile manner for a long-term period. Its integrated platform with extremely low stand-by power should pave a promising road toward next-generation neuromorphic systems, which would emulate the brain power of 20 W.

• 한국컴퓨터정보학회논문지
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• 제26권10호
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• pp.179-184
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• 2021

본 논문에서는 딥러닝 기반의 순환신경망을 이용하여 선박 연료유 예측을 시도하였다. 해운업에서는 선박 운항비에서 연료유가 차지하는 비중이 가장 크고 가격 변동성도 크기 때문에, 해운 기업은 합리적이고 과학저인 방법으로 연료유를 예측하여 시장경쟁력을 확보할 수 있다. 본 논문에서는 순환신경망 모델 3가지(RNN, LSTM, GRU)를 이용하여 싱가폴의 HSFO 380CST 벙커유 가격을 단기 예측하였다. 예측결과, 첫째, 선박 연료유 단기적 예측을 위해서는 장기 메모리를 사용하는 LSTM, GRU보다는 일반적인 RNN 모델의 성능이 우수한 것으로 분석되어, 장기적 정보의 예측 기여가 낮은 것으로 분석되었다. 둘째, 계량경제학 모델을 사용한 선행연구와 비교하여 순환신경망 모델의 예측성능이 우수한 것으로 분석되어 연료유가의 비선형적 특성을 고려한 순환신경망 모델을 통한 예측 연구의 필요성을 확인하였다. 연구의 결과는 선박 연료유의 단기 예측을 통하여 해운기업의 선박 연료유 수급 결정과 같은 의사결정에 도움이 될 수 있을 것으로 기대된다.

• 한국수자원학회논문집
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• 제54권spc1호
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• pp.1195-1204
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• 2021

최근 이상기후로 인한 국지성호우가 잦아져 하천변 사회기반시설을 포함한 인적·물적 피해가 급증하고 있다. 본 연구에서는 해당 시설들의 침수 피해를 예측·방지하고자 기계학습 중 시계열자료에 특화된 LSTM(Long Short- term Memory)기법을 활용하여 수위 예측 알고리즘을 개발하였다. 연구대상지는 잠수교로 연구기간은 총 6년(2015년~2020년)의 6, 7, 8월로 3시간 후의 잠수교 수위를 예측하였다. 입력자료(Input data)는 잠수교 수위(EL.m), 팔당댐 방류량(m³/s), 강화대교 조위(cm), 서울시 트윗의 개수로 기존 연구에 주로 사용된 정형자료뿐만 아니라 워드클라우드를 통해 구축된 비정형자료도 함께 사용하여 상호 보완형 자료를 구축하고, 비정형자료 활용 유무의 비교·분석을 통해 비정형자료의 역할도 제시하였다. 잠수교의 수위 예측 시 상호 보완형의 자료가 정형자료만을 사용한 경우에 비해 예측 정확도가 향상하였는 데, 이는 인명 피해를 감소시킬 수 있는 보수적인 예/경보가 가능함을 알 수 있었다. 본 연구에서는 하천변 사회기반시설의 이용자 안전 및 편의 제공에 상호 보완형 자료의 사용이 보다 효과적이라 판단하였다. 향후에는 비정형자료의 종류를 추가하거나 입력자료의 세밀한 전처리를 통하여 더욱 정확한 수위 예측을 기대해본다.