• Composites Research
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• v.36 no.6
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• pp.408-415
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• 2023

The formation of bonding configurations such as pyridinic-N, pyrrolic-N, and graphitic-N by nitrogen doping plays a crucial role in imparting distinct physical properties to carbon nanomaterials. In this study, we propose a simple and cost-effective approach to regulate nitrogen dopant configurations in carbon nanotubes (CNTs) by mixing melamine as a dopant source. We employed three distinct mechanical mixing techniques, namely magnetic stirring, bath sonication and tip sonication. The higher the ratio of melamine to CNT, the higher the ratio of Pyrrolic-N, and when mixed through stirring, the highest ratio of Pyridinic-N was shown. The facile method proposed in this study, which can easily form various types of nitrogen dopants in carbon nanotubes, is expected to facilitate the application of nitrogen-doped carbon nanomaterials.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.324-333
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• 2001

In this paper we present a novel color image segmentation algorithm based on a Gaussian Mixture Model(GMM). It is introduced a Deterministic Annealing Expectation Maximization(DAEM) algorithm which is developed using the principle of maximum entropy to overcome the local maxima problem associated with the standard EM algorithm. In our approach, the GMM is used to represent the multi-colored objects statistically and its parameters are estimated by DAEM algorithm. We also develop the automatic determination method of the number of components in Gaussian mixtures models. The segmentation of image is based on the maximum posterior probability distribution which is calculated by using the GMM. The experimental results show that the proposed DAEM can estimate the parameters more accurately than the standard EM and the determination method of the number of mixture models is very efficient. When tested on two natural images, the proposed algorithm performs much better than the traditional algorithm in segmenting the image fields.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.181-188
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• 2005

Chinese Postman Problem (CPP) is a problem that finds a shortest tour traversing all edges or arcs at least once in a given network. The Chinese Postman Problem on Mixed networks (MCPP) is a Practical generalization of the classical CPP and it has many real-world applications. The MCPP has been shown to be NP-complete. In this paper, we transform a mixed network into a symmetric network using virtual arcs that are shortest paths by Floyd's algorithm. With the transformed network, we propose a Genetic Algorithm (GA) that converges to a near optimal solution quickly by a multi-directional search technique. We study the chromosome structure used in the GA and it consists of a path string and an encoding string. An encoding method, a decoding method, and some genetic operators that are needed when the MCPP is solved using the Proposed GA are studied. . In addition, two scaling methods are used in proposed GA. We compare the performance of the GA with an existing Modified MDXED2 algorithm (Pearn et al. , 1995) In the simulation results, the proposed method is better than the existing methods in case the network has many edges, the Power Law scaling method is better than the Logarithmic scaling method.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.268-272
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• 2009

In this paper, we propose a Gaussian Mixture Model (GMM) based incremental robust adaptation with a forgetting factor for the speaker verification. Speaker recognition system uses a speaker model adaptation method with small amounts of data in order to obtain a good performance. However, a conventional adaptation method has vulnerable to the outlier from the irregular utterance variations and the presence noise, which results in inaccurate speaker model. As time goes by, a rate in which new data are adapted to a model is reduced. The proposed algorithm uses an incremental robust adaptation in order to reduce effect of outlier and use forgetting factor in order to maintain adaptive rate of new data on GMM based speaker model. The incremental robust adaptation uses a method which registers small amount of data in a speaker recognition model and adapts a model to new data to be tested. Experimental results from the data set gathered over seven months show that the proposed algorithm is robust against outliers and maintains adaptive rate of new data.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.228-228
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• 2021

하천의 합류부는 서로 다른 지형학적 특성과 수리학적 특성을 가지는 두 개의 하천이 하나로 합쳐지는 구간으로 하천 생태계에서 매우 중요한 역할을 하는 구간 중 하나이다. 이러한 합류부 구간의 혼합의 영향을 분석하기 위해서는 지류에 유입에 따른 본류의 혼합이 발생하는 혼합거리에 대한 분석이 필요하다. 기존에 많은 연구들은 실측의 어려움으로 인해 이송-확산방정식을 활용한 수치 모의를 통해서 다양한 조건에 대한 혼합거리를 분석하였고, 최근에는 첨단 센싱 장비들을 활용하여 간헐적으로 측정된 실측자료를 기반으로 측정시기에 대한 혼합거리에 분석이 수행되고 있다. 하지만, 실무적으로 합류부에서 발생하는 혼합의 양상을 분석하기 위해서는 실제 혼합이 발생하는 혼합거리에 대해 시계열적인 변화를 통해 연중 혼합거리에 대한 분석을 통해서 유황에 따른 혼합거리에 대한 분석이 필요하다. 이에 본 연구에서는 본류와 지류의 유량비에 따른 혼합거리와의 관계식을 개발하여 유량비에 따른 혼합거리를 분석하여 시계열적인 변화를 분석하고자 하였다. 대상지역은 황강과 낙동강의 합류부로 본류와 지류 관측소에서 측정된 유량자료를 활용하여 10분 단위로 측정된 유량비를 산정하였고, 측정시기별로 수행된 합류부 혼합거리 모니터링 결과를 활용하여 관계식을 통한 조견표의 만들어 측정시기의 유량비에 따른 혼합거리에 변화에 대한 분석을 수행하였다. 그리고 수행된 결과를 바탕으로 유황에 따른 혼합거리를 분석하였고, 최대 혼합이 발생하는 거리에 대한 분석을 수행하여 합류부에서 발생하는 연중 혼합거리에 대한 분석을 수행할 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.473-480
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• 2004

In this paper we propose an effective feature compensation scheme based on the speech model in order to achieve robust speech recognition. The proposed feature compensation method is based on parallel combined mixture model (PCMM). The previous PCMM works require a highly sophisticated procedure for estimation of the combined mixture model in order to reflect the time-varying noisy conditions at every utterance. The proposed schemes can cope with the time-varying background noise by employing the interpolation method of the multiple mixture models. We apply the‘data-driven’method to PCMM tot move reliable model combination and introduce a frame-synched version for estimation of environments posteriori. In order to reduce the computational complexity due to multiple models, we propose a technique for mixture sharing. The statistically similar Gaussian components are selected and the smoothed versions are generated for sharing. The performance is examined over Aurora 2.0 and speech corpus recorded while car-driving. The experimental results indicate that the proposed schemes are effective in realizing robust speech recognition and reducing the computational complexities under both simulated environments and real-life conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.75-84
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• 1998

To achieve more accurate information from satellite image data, a research on a technique for mixed pixel ex-traction has been produced. The mixed pixels with only two land covers have been experimented. By analyzing canonical vector in canonical correlation classification, the mixed pixels have been classified. The ratio of the two canonical weighted values-the elements of canonical vector have been used as a threshold to discriminate mixed pixels. In case of the classification for the mixed pixels of bridge and water class in TM data before or after the 1st of September, the threshold for the optimal classification of the mixed pixels is 4.0. That is, if the ratio of the two canonical weighted values is less than 4.0, the pixel is a mixed pixel. Also, using the distribution of canonical weighted values, the constitution percentages of land covers within one mixed pixel can be approximately deducted. The accuracy of mixed pixel extraction for experimental area is 90％ and quite acceptable. Conclusively, a technique for mixed pixel extraction by canonical vector analysis is effective.

• Polymer(Korea)
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• v.37 no.2
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• pp.204-210
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• 2013

Effects of additives (lubricant and antioxidant) and melt-blending condition (temperature, time and rotor speed) on the mechanical properties of polypropylene-based wood polymer composites (WPCs) were investigated. WPCs were prepared by melt-blending followed by compression molding. To understand melt-blending procedure, torque change of the WPC melt-blend was monitored. Maleic anhydride modified PP and nanoclay were used as a compatibilizer and a reinforcing filler, respectively. UTM and izod impact tester were used to measure the mechanical properties of the WPCs and a color-difference meter was used to measure the discoloration of the WPCs according to melt-blending condition. The mechanical properties showed that the optimized melt-blending condition was $170^{\circ}C$, 15 min, and 60 rpm. The mechanical properties of the WPCs decreased with increasing lubricant and antioxidant content. The two step method, adding wood flour later separately during melt-blending, was more effective than the typical one step method for improving the mechanical properties of the WPCs.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.88-88
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• 2020

수심평균 2차원 혼합모형은 하천환경에서 다양한 용존성 오염물질의 혼합현상을 모의하기 위해 널리 활용되어왔다. 2차원 혼합모형에서 분산계수는 하천의 전단 흐름에 의해 야기되는 오염물질의 퍼짐 현상을 표현하는 중요한 인자로서 작용하기 때문에 정교한 오염물질 혼합거동을 모의하기 위해서는 적합한 분산계수를 산정하는 것이 필수적이다. 분산계수를 실험적으로 산정하는 방법으로는 크게 모멘트법과 추적법으로 나뉘며, 비정상상태의 혼합거동에 대해 종방향 및 횡방향 분산계수를 동시에 산정할 수 있는 방법은 추적법 계열의 2차원 유관추적법(2D STRP)이 유일하다. 본 연구에서는 하천에 유입된 오염물질의 2차원 혼합해석을 위한 수치모형을 개발하였으며, 개발된 모형의 수치해를 바탕으로 다양한 Peclet 수의 범위에 대해 기존연구에서 제시된 2D STRP의 적용범위 및 성능을 정량적으로 분석하였다. 분석된 정보를 바탕으로 기존 2D STRP의 한계를 극복하기 위한 개선된 2차원 유관추적법(2D STRP-i)을 개발하고, 사행하천을 모형화한 실규모 하천실험시설에서 검증하였다. 기존 2D STRP의 성능평가 결과, Peclet 수가 낮은 조건일수록 농도분포의 예측 정확도가 감소하는 경향을 보였으며, 하안 경계에 도달하는 농도가 증가할수록 부정확한 결과를 초래하는 것으로 나타났다. 본 연구에서는 기존 2D STRP의 한계를 보완하여 더욱 정확한 분산계수를 산정하고자 하안 경계면 조건을 고려한 2차원 유관추적법(2D STRP-i)을 개발하였다. 2D STRP-i는 직교-곡선좌표계 기반의 2차원 이송-분산 방정식을 바탕으로 횡방향 유속분포 및 하안 경계조건을 고려할 수 있도록 개선되었다. 2D STRP-i는 공간적으로 상이한 이송효과 및 하안경계 조건을 적절히 반영함으로써 농도분포의 예측 정확도를 개선 시키는 것으로 평가되었으며, 하안경계면에서 농도가 증가하는 구간에서 기존 2D STRP의 결과와 비교하여 더욱 정확한 농도분포 및 분산계수를 제공하는 것으로 밝혀졌다.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.11 no.1
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• pp.11-21
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• 2013

The Geyoungju Ca-bentonite with dry density of 1.6 g/$cm^3$ has been considered as a standard buffer material for the disposal of high level waste in KAERI disposal system design. But it had relatively lower thermal conductivity compared with other surrounding materials, that was one of key parameters to limit the increase of the disposal density in the disposal system. In this study, various additives were selected and mixed with the Ca-bentonite in different mixing methods in order to increase the thermal conductivity from 0.8 W/mK to 1.0 W/mK. As an additive, CNT (Cabon Nano Tube), graphite, alumina, CuO, and $Fe_2O_3$ were selected, which are chemically stable and have good thermal conductivity. As mixing methods, dry hand-mixer mixing, wet milling and dry ball mill mixing were applied for the mixing. Above all, the ball mill mixing was proved to be most effective since the produced mixture was most homogeneous and showed higher increase in the thermal conductivity. From this study, it was confirmed that the thermal conductivity for the Geyoungju Ca-bentonite could be improved by adding small amount of highly thermal conductive material to 1.0 W/mk. In conclusion, it was believed that the experimental results will be valuable in the disposal system design if the additive effects on the swelling and permeability on the compact bentonite are also approved in further studies.