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Yu, Lan,Park, Ji Sun,Lim, Yun-Soo,Lee, Churl Seung,Shin, Kwonwoo,Moon, Ho Jun,Yang, Cheol-Min,Lee, Young Sil,Han, Jong Hun IOP Pub 2013 Nanotechnology Vol.24 No.15
<P>Carbon nanomaterials are generally used to promote the thermal conductivity of polymer composites. However, individual graphene nanoplatelets (GNPs) or carbon nanotubes (CNTs) limit the realization of the desirable thermal conductivity of the composite in both through- and in-plane directions. In this work, we present the thermal conductivity enhancement of the epoxy composite with carbon hybrid fillers composed of CNTs directly grown on the GNP support. The composite with 20 wt% hybrid filler loading showed 300% and 50% through-plane thermal conductivity improvements in comparison with the individual CNTs and GNPs, respectively. Moreover, it showed an enhanced thermal conductivity of up to 12% higher than that of the simply mixed GNP and CNT fillers. In more detail, hybrid fillers, whose CNTs were synthesized on the GNP support (Support C, Fe/Mo–MgO:GNP=1:0.456) for 60 min via chemical vapor deposition process, presented the highest through-plane thermal conductivity of 2.41 W m<SUP>−1</SUP> K<SUP>−1</SUP> in an epoxy composite.</P>
Yu, Lan,Kang, Hyokyung,Lim, Yun-Soo,Lee, Churl Seung,Shin, Kwonwoo,Park, Ji Sun,Han, Jong Hun American Scientific Publishers 2014 Journal of Nanoscience and Nanotechnology Vol.14 No.12
<P>Carbon nanotubes (CNTs) are generally used to promote the electrical conductivity of the polymer nanocomposites. However, in spite of their superior properties, CNT's high cost has limited their commercial application, so far. Thus, the development of hybrid carbon nanomaterials (CNMs) composed of CNTs and cheaper CNMs such as carbon fibers (CFs), expanded graphites (EGs), and graphene nanoplatelets (GNPs) is important in terms of reducing the cost of CNT-based fillers. In this study, we prepared EG/CNT hybrid fillers via direct CNT synthesis on the EG support using modified combustion method and thermal chemical vapor deposition (CVD) method, and investigated the electrical conductivity of the expoxy nanocomposite with EG/CNT hybrid fillers. The epoxy nanocomposites with EG/CNT hybrid fillers at 20 wt% filler loading showed 260% and 170% electrical conductivity enhancement in comparison with the EG and the simply mixed EG and CNT fillers, respectively. Our approach provides various applications including electromagnetic interference (EMI) shielding materials, thermal interface materials (TIMs), and reinforced nanocomposites.</P>
A LFO Suppression Approach for PET-TNCS Based on the Cascaded Nonlinear PI Controller
Yulan Su,Xinglai Ge 전력전자학회 2019 ICPE(ISPE)논문집 Vol.2019 No.5
The voltage low-frequency oscillation (LFO) occurs between the traction network and electric multiple units in high-speed railway system, which significantly deteriorates the stability and reliability of the railway transportation system. In view of this, a transient direct current control strategy based on the cascaded nonlinear PI controller is proposed for the single-phase power electronic transformer (PET)-based railway traction system. The control strategy is not only simple in design, but also can realize the self-adaptive adjustment of PI parameters through nonlinear functions, which enhances the robust performance of the system. The simulation and test results show that the LFO of power electronic transformer-traction network coupling system (PET-TNCS) occurs with the increase of the number of PETs accessed to the traction network under the traditional linear PI controller and the control strategy proposed in this paper can effectively suppress the LFO.
Aster glehni Extract Ameliorates Scopolamine-Induced Cognitive Impairment in Mice
Yulan Liao,배호정,박종훈,Jiabao Zhang,구보경,임미경,한은혜,이상호,정서윤,류재환,류종훈 한국식품영양과학회 2019 Journal of medicinal food Vol.22 No.7
The leaves of Aster glehni Fr. Schm. (Asteraceae) have been used to treat insomnia in Korea. Insomnia is a common adverse effect of therapeutic agents for Alzheimer's disease (AD), and the control of sleep disturbance may prevent dementia. We hypothesized that the leaves of A. glehni can attenuate cognitive dysfunctions observed in AD. We observed the ameliorating effects of the ethanolic extract of leaves of A. glehni (AG-D) on memory dysfunction through the Morris water maze test, the passive avoidance test, and the Y-maze test. We performed acetylcholinesterase (AChE) activity assay and Western blotting to determine the mechanism of action of AG-D. AG-D significantly attenuated memory dysfunction observed in the above behavior studies and inhibited the activity of AChE. AG-D also increased the levels of phosphorylation extracellular signal-regulated kinase (ERK), cAMP response element-binding protein (CREB), phosphatidylinositol 3-kinase (PI3K), protein kinase B (Akt), and glycogen synthase kinase 3β (GSK-3β) and the expression levels of brain-derived neurotrophic factor (BDNF) in the hippocampi. These results suggest that AG-D ameliorates memory impairments by AChE inhibition and activation of ERK-CREB-BDNF and PI3K-Akt-GSK-3β signaling pathways. Taken together, this study suggests that AG-D could be used as a potential treatment for cognitive dysfunction.
Yulan Zheng 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.9
Based on real situations of supply chain network among enterprise alliances, this paper takes certain factors in every round of supply chain into consideration to establish robust model of supply chain network design. Before that, the strategy “decomposition- coordination” is adopted to get solutions optimizing supply chain system, putting focus on the analysis of supplier selection cost and decision-making cost of supply chain facilities, which is integrated and coordinated through activity-based costing. After the model establishment, examples are used to illustrate practicability and effectiveness of the model and algorithm.
A Design on RDF and DB Query Generator for Category Search System
Yulan Cui,Hyunsuk Hwang,Changsoo Kim 한국멀티미디어학회 2008 한국멀티미디어학회 학술발표논문집 Vol.2008 No.2
The search works are common and an essential function whether in database-based system, ontology-based system or the combination of database and ontology system. The query languages like SPARQL for RDF and SQL for database are important parts for accessing information and deciding the accuracy of results. In this paper, we design RDF and DB query generator for category search system based on the database and ontology. The RDF query generator can generate SPARQL query sentences for extracting vital resource depending on defined ontologies and given conditions. The DB query generator can generate SQL query sentences for extracting the results that the user wants using the previous step's vital resource.
Applying Spatial Analysis to Facility Searching in Underground Space
Yulan Cui,Hyunsuk Hwang,Changsoo Kim 한국멀티미디어학회 2009 한국멀티미디어학회 학술발표논문집 Vol.2009 No.1
The utilization of underground space has recently increased with the complication of road, the rise of the land price, and the development of the green technology. Underground space ranges from classical excavations to subway, underground cities, and shopping mall which there always a lot of people around. Meanwhile, various types of the facilities have rapidly grown for preparations of the increasing potential disasters. Therefore, an effective facility searching work is required. In this paper, we designed and implemented a facility information system based spatial analysis to provide convenient and easy searching work to general users who do not know much about related information of facilities. This system has advantages in avoiding fussy searching work with attributes of facilities.
State-of-charge Estimation for Lithium-ion Batteries Using a Multi-state Closed-loop Observer
Yulan Zhao,Haitao Yun,Shude Liu,Huirong Jiao,Chengzhen Wang 전력전자학회 2014 JOURNAL OF POWER ELECTRONICS Vol.14 No.5
Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor?capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.