• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.259-259
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• 2007

층상구조의 전이금속 산화물($LiMO_2$, M=Co, Ni, Mn)은 리튬이차전지용 양극재료로 활발한 연구가 진행되고 있다. 차세대 리튬이차전지 시스템의 개발 및 고성능화를 위해서는 전지의 용량을 결정하는 핵심 부품인 양극재료의 고용량화 및 고안정화는 필수 불가결하다. 따라서 본 연구에서는 상업적으로 큰 장점이 있는 고상반응 공정을 이용하여 리튬이차전지용 양극소재를 제조하고, 소재의 전기화학적, 구조적인 특성을 평가하였으며, 다음과 같은 주제를 가지고 연구를 진행하였다. $LiCoO_2$ 양극재료는 리튬이온전지로 널리 사용되고 있다. 높은 에너지 밀도의 리튬이온전지를 얻기 위해서는 $LiCoO_2$ 양극재료가 고용량화 및 고밀도화를 가져야 한다. 여기서 $LiCoO_2$ 분말이 irregular particle morphology를 가지면 tap density가 $2.2-2.4gcm^{-3}$로 에너지 밀도가 낮으나, 구형 $LiCoO_2$의 정극재료는 tap density가 $2.6-2.8gcm^{-3}$로 상대적으로 energy density가 높아지는 효과가 있다. 구형 $LiCoO_2$ 양극재료를 합성하기 위해서는 chelating agent를 이용한 "controlled crystallization" 침전법을 사용하여 합성한 구형 코발트 수화물을 사용하고 있다. "controlled crystallization" 침전법에서 사용되는 chelating agent로는 주로 ammonia가 이용되고 있다. 본 연구에서는 chelating agent로 ethylene diamine을 사용하여 sodium hydroxides를 precipitation으로 침전 반응하여 구형 코발트 수화물을 합성하였다. 상기 방법으로 합성된 코발트 수화물과 리튬 수화물($LiOH{\cdot}H_2O$-고순도화학(高殉道化學))을 사용하여 고상법을 통하여 $LiCoO_2$를 합성하였다. 제조된 분말의 결정구조와 전기화학적 특성분석은 X-선 회절분석 및 리트벨트 구조정산, 그리고 충/방전 싸이클링을 수행하였으며, 분말의 미세구조 변화를 SEM을 이용하여 분석하였다.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.209-221
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• 2009

Travel time estimation under given traffic conditions is important for providing drivers with travel time prediction information. But the present expressway travel time estimation process cannot calculate a reliable travel time. The objective of this study is to estimate the path travel time spent in a through lane between origin tollgates and destination tollgates on an expressway as a prerequisite result to offer reliable prediction information. Useful and abundant toll collection system (TCS) data were used. When estimating the path travel time, the path travel time is estimated combining the link travel time obtained through a preprocessing process. In the case of a lack of TCS data, the TCS travel time for previous intervals is referenced using the linear interpolation method after analyzing the increase pattern for the travel time. When the TCS data are absent over a long-term period, the dynamic travel time using the VDS time space diagram is estimated. The travel time estimated by the model proposed can be validated statistically when compared to the travel time obtained from vehicles traveling the path directly. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variaty of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.5
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• pp.333-340
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• 2019

Tests using a middle velocity propulsion impact machine (MVPIM) were performed to verify the impact resistance capability of sandwich concrete panels (SCP) in a modular liquefied natural gas (LNG) outer tank, and numerical models were constructed and analyzed. $2{\times}2m$ specimens with plain sectional characteristics and specimens including a joint section were used. A 51 kg missile was accelerated above 45 m/s and impacted to have the design code kinetic energy. Impact tests were performed twice according to the design code and once for the doubled impact speed. The numerical models for simulating impact behaviors were created by LS-DYNA. The external steel plate and filled concrete of the panel were modeled as solid elements, the studs as beam elements, and the steel plates as elasto-plastic material with fractures; the CSCM material model was used for concrete. The front plate deformations demonstrated good agreement with those of other tests. However the rear plate deformations were less. In the doubled speed test for the plain section specimen, the missile punctured both plates; however, the front plate was only fractured in the numerical analysis. The impact energy of the missile was transferred to the filled concrete in the numerical analysis.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1301-1308
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• 2018

90/150 CA which are used as key generators of the cipher system have more randomness than LFSRs, but synthesis methods of 90/150 CA are difficult. Therefore, 90/150 CA synthesis methods have been studied by many researchers. In order to synthesize a suitable CA, the analysis of the characteristic polynomial of 90/150 CA should be preceded. In general, the characteristic of polynomial ${\Delta}_n$ of n cell 90/150 CA is obtained by using ${\Delta}_{n-1}$ and ${\Delta}_{n-2}$. Choi et al. analyzed $H_{2^n}(x)$ and $H_{2^n-1}(x)$, where $H_k(x)$ is the characteristic polynomial of k cell 90/150 CA with state transition rule <$10{\cdots}0$>. In this paper, we propose an efficient method to obtain $H_n(x)$ from $H_{n-1}(x)$ and an efficient algorithm to obtain $H_{2^n+i}(x)$ and $H_{2^n-i}(x)$ ($1{\leq}i{\leq}2^{n-1}$) from $H_{2^n}(x)$ by using this method.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.101-125
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• 2022

Recently, with the development of computing technology and the improvement of the cloud environment, deep learning technology has developed, and attempts to apply deep learning to various fields are increasing. A typical example is anomaly detection, which is a technique for identifying values or patterns that deviate from normal data. Among the representative types of anomaly detection, it is very difficult to detect a contextual anomaly that requires understanding of the overall situation. In general, detection of anomalies in image data is performed using a pre-trained model trained on large data. However, since this pre-trained model was created by focusing on object classification of images, there is a limit to be applied to anomaly detection that needs to understand complex situations created by various objects. Therefore, in this study, we newly propose a two-step pre-trained model for detecting abnormal situation. Our methodology performs additional learning from image captioning to understand not only mere objects but also the complicated situation created by them. Specifically, the proposed methodology transfers knowledge of the pre-trained model that has learned object classification with ImageNet data to the image captioning model, and uses the caption that describes the situation represented by the image. Afterwards, the weight obtained by learning the situational characteristics through images and captions is extracted and fine-tuning is performed to generate an anomaly detection model. To evaluate the performance of the proposed methodology, an anomaly detection experiment was performed on 400 situational images and the experimental results showed that the proposed methodology was superior in terms of anomaly detection accuracy and F1-score compared to the existing traditional pre-trained model.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.29-38
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• 2022

Because of the need of actual performance of education, this study aims to understand how the factors of educational content and organizational characteristics affect organizational commitment and work performance, which are organizational effects, through learning transfer. As a result, task value, job relevance, and organizational compensation had a significant effect on learning transfer, learning transfer had a significant effect on organizational commitment and work performance, and organizational commitment had a significant effect on work performance. In order to increase the learning transfer of education, when specifying the connection with the actual job and strengthening the compensation system of the members, the learning transfer can be increased and eventually connected to performance. Since limited variables are considered, a more representative sample or professional group should be extracted through future research. In future studies, it will be possible to closely grasp the relationship between learning transfer and organizational effectiveness by setting representative samples and specifying variables.

• Clean Technology
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• v.28 no.2
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• pp.174-181
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• 2022

Biomass is a sustainable alternative resource for production of liquid fuels and organic compounds that are currently produced from fossil fuels including petroleum, natural gas, and coal. Because the use of fossil fuels can increase the production of greenhouse gases, the use of carbon-neutral biomass can contribute to the reduction of global warming. Although biological and chemical processes have been proposed to produce petroleum-replacing chemicals and fuels from biomass feedstocks, it is difficult to replace completely fossil fuels because of the high oxygen content of biomass. Production of petroleum-like fuels and chemicals from biomass requires the removal of oxygen atoms or conversion of the oxygen functionalities present in biomass derivatives, which can be achieved by catalytic hydrodeoxygenation. Hydrodeoxygenation has been used to convert raw biomass-derived materials, such as biomass pyrolysis oils and lignocellulose-derived chemicals and lipids, into deoxygenated fuels and chemicals. Multifunctional catalysts composed of noble metals and transition metals supported on high surface area metal oxides and carbons, usually selected as supports of heterogeneous catalysts, have been used as efficient hydrodeoxygenation catalysts. In this review, the catalysts proposed in the literature are surveyed and hydrodeoxygenation reaction systems using these catalysts are discussed. Based on the hydrodeoxygenation methods reported in the literature, an insight for feasible hydrodeoxygenation process development is also presented.

• Journal of Life Science
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• v.33 no.6
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• pp.523-529
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• 2023

Ubiquitination is a post-translational modification that is involved in the quality control of proteins and responsible for modulating a variety of cellular physiological processes. Protein ubiquitination and deubiquitination are reversible processes that regulate the stability of target substrates. The ubiquitin proteasome system (UPS) helps regulate tumor-promoting processes, such as DNA repair, cell cycle, apoptosis, metastasis, and angiogenesis. The UPS comprises a combination of ubiquitin, ubiquitin-activating enzymes (E1), ubiquitin-conjugating enzymes (E2), and ubiquitin-ligase enzymes (E3), which complete the degradation of target proteins. Ubiquitin-conjugating enzymes (UBE2s) play an inter-mediate role in the UPS process by moving activated ubiquitin to target proteins through E3 ligases. UBE2s consist of 40 members and are classified according to conserved catalytic ubiquitin-conjugating (UBC) domain-flanking extensions in humans. Since UBE2s have specificity to substrates like E3 ligase, the significance of UBE2 has been accentuated in tumorigenesis. The dysregulation of multiple E2 enzymes and their critical roles in modulating oncogenic signaling pathways have been reported in several types of cancer. The elevation of UBE2 expression is correlated with a worse prognosis in cancer patients. In this review, we summarize the basic functions and regulatory mechanisms of UBE2s and suggest the possibility of their use as therapeutic targets for cancer.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.3
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• pp.111-118
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• 2023

MXene, a two-dimensional transition metal carbide or nitride, has recently attracted much attention as a lightweight and flexible electromagnetic shielding material due to its high electrical conductivity, good mechanical strength and thermal stability. In particular, the Ti-based MXene, Ti₃C₂T_x and Ti₂CT_x are reported to have the best electrical conductivity and electromagnetic shielding properties in the vast MXene family. Therefore, in this study, Ti₃C₂T_x and Ti₂CT_x films were prepared by vacuum filtration using Ti₃C₂T_x and Ti₂CT_x dispersions synthesized by interlayer metal etching and centrifugation of Ti₃AlC₂ and Ti₂AlC. The electrical conductivity and electromagnetic shielding efficiency of the films were measured after heat treatment at high temperature. Then, X-ray diffraction and photoelectron spectroscopy were performed to analyze the structural changes of Ti₃C₂T_x and Ti₂CT_x films after heat treatment and their effects on electromagnetic shielding. Based on the results of this study, we propose an optimal structure for an ultra-thin, lightweight, and high performance MXene-based electromagnetic shielding film for future applications in small and wearable electronics.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.6
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• pp.255-260
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• 2023

As demanding the detection of explosive molecules, it is required to develop rapidly and precisely responsive sensors with ultra-high sensitivity. Since two-dimensional semiconductors have an atomically thin body nature where mobile carriers accumulate, the abrupt modulation carrier in the thin body channel can be expected. To investigate the effectiveness of WSe₂ semiconductor materials as a detection material for TNT (Trinitrotoluene) explosives, WSe₂ was synthesized using thermal chemical vapor deposition, and afterward, WSe₂ FETs (Field Effect Transistors) were fabricated using standard photo-lithograph processes. Raman Spectrum and FT-IR (Fourier-transform infrared) spectroscopy reveal that the adsorption of TNT molecules induces the structural transition of WSe₂ crystalline. The electrical properties before and after adsorption of TNT molecules on the WSe₂ surface were compared; as -50 V was applied as the back gate bias, 0.02 μA was recorded in the bare state, and the drain current increased to 0.41 μA with a dropping 0.6% (w/v) TNT while maintaining the p-type behavior. Afterward, the electrical characteristics were additionally evaluated by comparing the carrier mobility, hysteresis, and on/off ratio. Consequently, the present report provides the milestone for developing ultra-sensitive sensors with rapid response and high precision.