• 한국세라믹학회지
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• 제54권5호
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• pp.366-379
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• 2017

Nanostructured materials have attracted considerable research interest over the recent decades because of their potential applications in nanoengineering and nanotechnology. On the other hand, the developments in nanotechnology are strongly dependent on the availability of new materials with novel and engineered morphologies. Among the novel nanomaterials reported thus far, composite nanofibers (NFs) have attracted considerable attention in recent years. In particular, metal oxide NFs have great potential for the development of gas sensors. Highly sensitive and selective gas sensors can be developed by using composite NFs owing to their large surface area and abundance of grain boundaries. In composite NFs, gas sensing properties can be enhanced greatly by tailoring the conduction channel and surface properties by compositional modifications using the synergistic effects of different materials and forming heterointerfaces. This review focuses on the gas sensing properties of composite NFs synthesized by an electrospinning (ES) method. The synthesis of the composite NFs by the ES method and the sensing mechanisms involved in different types of composite NFs are presented along with the future perspectives of composite NFs.

• Bulletin of the Korean Chemical Society
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• 제35권9호
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• pp.2765-2768
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• 2014

Flower-like Au nanoparticles, so-called Au nanoflowers (AuNFs), were synthesized by simply adding ascorbic acid to a gold acid solution in the presence of a chitosan biopolymer. The chitosan-entangled AuNFs exhibited strong plasmon absorption in the near-infrared (NIR) wavelength due to the aggregation of primary Au nanoparticles. The chitosan-entangled AuNFs were preferentially adsorbed by Raman-active 2-chlorothiophenol (CTP) molecules, and the CTP-encoded AuNFs (AuNF-CTPs) were subsequently coated with a thin silica layer by a sol-gel reaction with Si alkoxides. The silica-coated AuNFs (AuNF-CTPs@silica) exhibited the distinct Raman signals of adsorbed CTP molecules, as a potential nanoprobe with surface-enhanced Raman scattering (SERS).

• 전자통신동향분석
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• 제26권5호
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• pp.55-65
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• 2011

요즘 신산업으로 떠오르고 있는 개인 유전체 분석이나 차세대 시퀀싱 기술과 같은 고성능 컴퓨팅 응용들은 data-intensive한 작업들을 요구하며, 이러한 응용을 지원하기 위한 고성능 파일 시스템 기술에 대한 연구들이 다수 진행 중이다. 그러나 그 결과물들은 업체별로 보유한 고유 기술로서, 상호 호환성 등의 문제로 인해 표준화의 필요성이 제기되어 왔다. 현재 파일 시스템과 관련하여 거의 모든 IT 업체에서 사용하고 있는 실질적인 표준은 NFS(Network File System)이다. IETF(Internet Engineering Task Force)에서는 이러한 요구사항들을 반영하여 2010년에 NFSv4.1 표준을 공표하였고, 특히 I/O 성능을 향상시키기 위한 pNFS(parallel NFS)는 NFSv4.1의 핵심 기능으로서 다수업체들과 연구기관들에서 많은 관심을 받고 있다. 본 고에서는 pNFS 표준화 및 연구개발 동향과 관련된 이슈들에 대해 기술하고자 한다.

• 식품기술
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• 제10권1호
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• pp.102-114
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• 1997

발효식품에서 분리한 젖산균인 Lactobacillus plantarum(NFS #6-6과 S #3)의 발효소시지에서 starter culture로의 이용가능성을 알아보기 위하여 상업용 혼합 starter culture인 SL(Staphylococcus carnosus+ Lactobacillus pentosus)을 비교구로하여 발효소시지를 제조하고 그 특성을 상호 비교하였다. 발효 및 숙성 중 변화에서 starter culture의 종류에 관계없이 최종 43~45%의 수분이 증발되었다. PH는 SL 처리구가 가장 낮은 4.3 수준이었으며 수분활성도 역시 0.88로 SL 처리구가 가장 낮았다. 색도에서 적색도는 SL 처리구보다 NFS #6-6과 S #3 처리구가 더 높았으며 텍스쳐, 지방산, 그리고 유리아미노산의 변화에서 starter culture에 따른 차이점은 없었다. 관능평가시 색깔에서는 NFS #6-6 처리구가 SL 처리구에 비하여 낮았으나 향기, 맛, 텍스쳐와 기호도에있어서는 SL과 비슷한 결과를 나타내었다. 유산균수는 발효 2일째 급격히 증가하는 추세($10^8 cfu/g이상)였으나 S #3과 NFS #6-6이 더욱 빠른 성장을 보였으며 Step. aureus는 모든 처리구에서 검출되지 않았다. 장내세균의 경우 SL 처리구에 비하여 우수하여 S #3 처리구는 3일째, NFS #6-6 처리구는 8일째부터 검출되지 않았으며 Listeria 역시 SL처리구보다 우수한 억제력을 나타내었다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2008년도 추계학술발표대회
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• pp.940-942
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• 2008

분산되어 있는 스토리지 자원을 하나의 클러스터로 구성하여 분산 파일 시스템으로 구성하고자 하는 경우, 기존의 네트워크 파일 시스템만을 이용하기에는 여러 가지 제약이 존재한다. 특히 Parallel Striped Access는 IO데이터를 스토리지에 나누어 분산시키고 클라이언트가 직접 접근하는 방식으로 병렬 파일 시스템과 같은 HPC 용 특수 파일 시스템에서는 이미 사용되는 기법이나, 일반적인 시스템을 대상으로 한 표준안의 부재가 제약이 된다. pNFS(Parallel NFS)는 이러한 문제를 해결하기 위해서 제시되는 새로운 NFS 기술이다. 본 연구에서는 pNFS의 연구 동향과 더불어 소규모 클러스터 시스템에서 나타나는 성능적 특징을 조사하였다.

• 한국재료학회지
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• 제26권12호
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• pp.741-750
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• 2016

Nanofibers(NFs), because of their high surface area and nanosized grains, have appropriate morphologies for use in chemiresistive-type sensors for gas detection applications. In this study, a highly sensitive and selective CO gas sensing material based on Au-decorated $SnO_2$ NFs was fabricated by electrospinning. $SnO_2$ NFs were synthesized by electrospinning and subsequently decorated with various amounts of Au nanoparticles(NPs) by sputtering; this was followed by thermal annealing. Different characterizations showed the successful formation of Au-decorated $SnO_2$ NFs. Gas sensing tests were performed on the fabricated sensors, which showed bell-shaped sensing behavior with respect to the amount of Au decoration. The best CO sensing performance, with a response of ~20 for 10 ppm CO, was obtained at an optimized amount of Au (2.6 at.%). The interplay between Au and $SnO_2$ in terms of the electronic and chemical sensitization by Au NPs is responsible for the great improvement in the CO sensing capability of pure $SnO_2$ NFs, suggesting that Au-decorated $SnO_2$ NFs can be a promising material for fabricating highly sensitive and selective chemiresistive-type CO gas sensors.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2009년도 추계학술대회 논문집
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• pp.385-385
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• 2009

Uniform polyaniline nanofibers (PANI NFs), and chemically doped sulfamic acid(SFA) PANI NFs, synthesized via template free interfacial polymerization process, were used as new counter electrodes materials for the fabrication of the highly-efficient dyesensitized solar cells (DSSCs). The PANI NFs based fabricated DSSCs exhibited a solarto-electricity conversion efficiency of ~ 4.02% while, the SFA doped PANI NFs based DSSC demonstrated ~ 27% improvement in the solar-to-electricity conversion efficiency. The obtained solar-to-electricity conversion efficiency for SFA doped PANI NFs based DSSC was 5.47% under 100mW/$cm^2$(AM1.5). The enhancement in the conversion efficiency was due to the incorporation of SFA into the PANI NFs which resulted to the higher electrocatalytic activity for the $I^{3-}/I^-$ redox reaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3333-3354
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• 2022

The 5G Core Network (5GC) is an essential part of the mobile communication network, but its security protection strategy based on the boundary construction is difficult to ensure the security inside the network. For example, the Network Function (NF) mutual authentication mechanism that relies on the transport layer security mechanism and OAuth2.0's Client Credentials cannot identify the hijacked NF. To address this problem, this paper proposes a trust model for 5GC based on NF interaction behavior to identify malicious NFs and improve the inherent security of 5GC. First, based on the interaction behavior and context awareness of NF, the trust between NFs is quantified through the frequency ratio of interaction behavior and the success rate of interaction behavior. Second, introduce trust transmit to make NF comprehensively refer to the trust evaluation results of other NFs. Last, classify the possible malicious behavior of NF and define the corresponding punishment mechanism. The experimental results show that the trust value of NFs converges to stable values, and the proposed trust model can effectively evaluate the trustworthiness of NFs and quickly and accurately identify different types of malicious NFs.

• 전기전자학회논문지
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• 제22권2호
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• pp.510-513
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• 2018

최근 전자파 적합성(EMC: electromagnetic compatibility)의 중요성이 매우 높아짐에 따라 칩 수준에서의 전자파 간섭(EMI: electromagnetic interference) 측정이 자주 요구되고 있다. IEC 61967 및 IEC 62508에서 규정된 근거리 전자장 스캐닝(NFS: near-field scanning) 시스템은 칩 레벨에서의 전자파 간섭을 분석하는 대표적인 방법이다. 칩이 점점 고속화되면서 근거리 전자장 스캐닝 시스템의 측정 주파수는 광대역화되어야 하지만 근거리 전자장 탐침(NFP: near-field probe)의 신호 대 잡음 비(SNR: signal-to-noise ratio)가 저하된다는 문제가 있다. 본 논문에서는 근거리 전자장 스캐닝 시스템에서 광대역 특성을 가지면서도 잡음 대 성능 비를 향상시키는 기술에 대해 살펴본다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.276-287
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• 2014

Neural fuzzy system (NFS) is basically a fuzzy system that has been equipped with learning capability adapted from the learning idea used in neural networks. Due to their outstanding system modeling capability, NFS have been widely employed in various applications. In this article, we intend to discuss several ideas regarding the learning of NFS for modeling systems. The first issue discussed here is about structure learning techniques. Various ideas used in the literature are introduced and discussed. The second issue is about the use of recurrent networks in NFS to model dynamic systems. The discussion about the performance of such systems will be given. It can be found that such a delay feedback can only bring one order to the system not all possible order as claimed in the literature. Finally, the mechanisms and relative learning performance of with the use of the recursive least squares (RLS) algorithm are reported and discussed. The analyses will be on the effects of interactions among rules. Two kinds of systems are considered. They are the strict rules and generalized rules and have difference variances for membership functions. With those observations in our study, several suggestions regarding the use of the RLS algorithm in NFS are presented.