• 대한산업공학회지
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• 제24권2호
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• pp.251-260
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• 1998

This paper deals with a simulated annealing neural network model for determining sequences of models inputted into a mixed model assembly line. We first present a energy function fitting to our problem, next determine the value of the parameters of the energy function using convergence ratio and the number of searched feasible solution. Finally we compare our model NMS with the modified Thomopoulos model. The result of the comparison shows that NMS and Thomopoulos offer a similar output in the problems having good smoothness.

• 말소리와 음성과학
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• 제10권3호
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• pp.19-29
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• 2018

We propose to use independent component analysis (ICA) and deep neural network (DNN) to detect music sections in broadcast drama contents. Drama contents mainly comprise silence, noise, speech, music, and mixed (speech+music) sections. The silence section is detected by signal activity detection. To detect the music section, we train noise, speech, music, and mixed models with DNN. In computer experiments, we used the MUSAN corpus for training the acoustic model, and conducted an experiment using 3 hours' worth of Korean drama contents. As the mixed section includes music signals, it was regarded as a music section. The segmentation error rate (SER) of music section detection was observed to be 19.0%. In addition, when stereo mixed signals were separated into music signals using ICA, the SER was reduced to 11.8%.

• 동력기계공학회지
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• 제20권6호
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• pp.51-57
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• 2016

Experiment is carried out to investigate the mixed convective flow in three-dimensional horizontal rectangular channels filled with high viscous fluid. The particle image velocimetry(PIV) with thermo-sensitive liquid crystal tracers is used for visualizing and analysis. Quantitative data of temperature and velocity are obtained by applying the color-image processing to a visualized image, and neural network is applied to the color-to-temperature calibration. In this study, the fluid used is silicon oil(Pr=909), the aspect ratio(channel width to heigh) is 4 and Reynolds number is $2{\times}10^{-2}$. From the present study, we can visualize the quantitative temperature and velocity of mixed convective flow in three-dimensional horizontal rectangular channels simultaneously.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.85-94
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• 2024

In this paper, we present the very first time the generalized notion of (α, β, γ, δ) - convex (concave) function in mixed kind, which is the generalization of (α, β) - convex (concave) functions in 1^st and 2^nd kind, (s, r) - convex (concave) functions in mixed kind, s - convex (concave) functions in 1^st and 2^nd kind, p - convex (concave) functions, quasi convex(concave) functions and the class of convex (concave) functions. We would like to state the well-known Ostrowski inequality via SVN-Riemann Integrals for (α, β, γ, δ) - convex (concave) function in mixed kind. Moreover we establish some SVN-Ostrowski type inequalities for the class of functions whose derivatives in absolute values at certain powers are (α, β, γ, δ)-convex (concave) functions in mixed kind by using different techniques including Hölder's inequality and power mean inequality. Also, various established results would be captured as special cases with respect to convexity of function.

• 한국정보통신학회논문지
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• 제22권6호
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• pp.888-894
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• 2018

본 논문에서는 연선의 성능 측정을 위한 혼합 모드 산란계수 측정시스템을 제안하였다. 연선은 균형 형태의 소자로써 일반적으로 동축 형태로 구현된 네트워크 분석기를 이용하여 특성 측정이 불가능하다. 이때, 발룬을 이용하여 균형 신호와 불균형 신호 간 변환을 통해 측정이 가능하지만 측정 주파수 대역폭이 제한되는 문제가 있다. 제안하는 시스템은 발룬을 사용하지 않고 4포트 벡터 네트워크 분석기와 설계한 고정구를 이용하여 혼합모드 산란계수를 측정하여 연선의 성능을 측정한다. 제안하는 시스템을 이용하여 상용 이더넷 케이블의 성능을 측정해보고 발룬의 이용한 결과와 비교해 보았다. 이를 통해 제안하는 시스템을 이용해 연선의 성능 측정이 가능함을 확인하였다.

• 한국컴퓨터정보학회논문지
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• 제10권1호
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• pp.181-188
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• 2005

Chinese Postman Problem(CPP)는 주어진 네트워크에서 모든 에지나 아크를 적어도 한번씩 경유하는 최단 경로를 찾는 문제이다. 혼합네트워크에서의 CPP(MCPP)는 기존의 CPP를 일반화시킨 문제로 현실 세계에서 많은 응용 부분들을 가지고 있으며, MCPP는 NP-Complete로 알려져 있다. 본 논문에서는 Floyd 알고리즘을 이용하여 구성된 가상 아크를 이용하여 혼합네트워크를 대칭네트워크로 변환 후 근사최적해를 탐색하는데 효율적인 유전자 알고리즘을 적용한다. 본 논문에서는 유전자 알고리즘에 적용하기 위해 경로 문자열과 에지, 아크를 구분하기 위한 문자열의 쌍으로 구성된 염색체 구조, 인코딩 및 디코딩 방법을 제안한다. 또한 보정 방법으로 Power Law 보정 방법과 Logarithmic 보정 방법을 사용하고 비교 분석하였다 본 논문에서는 기존의 MIXED2 알고리즘과 제안된 유전자 알고리즘과의 성능 비교를 하였다. 에지가 많은 혼합 네트워크인 경우 제안된 유전자 알고리즘이 좋은 결과를 얻고, Logarithmic 보정 방법 보다 Power Law보정 방법을 사용할 경우 좋은 결과를 얻을 수 있음을 알 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권12호
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.

• Food Science and Biotechnology
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• 제16권2호
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• pp.183-186
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• 2007

The type of mixed gel network of $\kappa$-carrageenan/agar was determined by applying rheological principles. Apparent Young's modulus of the mixed gels was mathematically analyzed with (a) simply adding the moduli of two component gels, (b) phase-separated type's upper and lower bound models, (c) interpenetrating type's logarithmic model. The experimental data fitted the estimates from the operation (a). Whereas, as for the models (b), the experimental values in the agar-rich region fitted the estimates of the upper bound model, but in the $\kappa$-carrageenan-rich region slightly deviated from those of the lower bound model. It reflected an evidence of a phase-separated type, although it was not typical, that there must be data good-fit in the agar-rich and $\kappa$-carrageenan-rich regions with the upper and lower bound models, respectively. Experimental values disagreed with estimates of the model (c). Gel time was analyzed to evince the phase-separated type. As agar concentrations increased at a fixed amount of $\kappa$-carrageenan, gel time gradually decreased and then sharply increased and decreased again. The pattern of such change in gel time also represented a typical behavior of phase-separated type's mixed gels.

• 융합보안논문지
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• 제11권3호
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• pp.31-37
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• 2011

최근 네트워크상에 익명성을 보장하는 Mixed Network에 관한 연구가 활발히 진행되고 있다. 이는 노드간 암호화 통신을 이용하고 통신 경로도 수시로 변경되는 등 공격자에 대한 역추적 및 대응을 어렵게 만든다. 그럼에도 악의적인 형태의 인터넷 사용을 즐기는 사람들에 의해 지속적으로 진화되고 있으며, 새로운 형태의 기술이 지속적으로 개발되고 있는 상황이다. 이러한 상황에 익명네트워크를 이용하여 국가기관 및 기반시설에 대한 사이버공격이 대규모로 이루어진다면 국가차원에서 엄청난 재앙이 아닐 수 없다. 또한 향후에도 이러한 기술을 응용한 공격기법이 지속적으로 출현할 것으로 예상되고 있으나, 이에 대한 마땅한 대비책이 마련되어 있지 않다. 이에 본 논문에서는 다양한 익명네트워크 기술에 대한 분석 및 이를 이용한 사이버 공격에 효율적 대응을 위한 조기탐지 방안 연구를 진행하고자 한다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.660-667
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• 2003

In this study, a Multiple Objective Mixed Integer Programming (MOMIP) Model is developed for sewer rehabilitation planning by considering cost, inflow/infiltration. A sewer rehabilitation planning model is required to decide the economic life of the sewer by considering trade-off between cost and inflow/infiltration. And it is required to find the optimal rehabilitation timing, according to the cost effectiveness of each sewer rehabilitation within the budget. To develop such a model, a multiple objective mixed integer programming model is formulated based on network flow optimization. The network is composed of state nodes and arcs. The state nodes represent the remaining life and the arcs represent the change of the state. The model consider multiple objectives which are cost minimization and minimization of inflow/infiltration. Using the multiple objective optimization, the trade-off between the cost and inflow/infiltration is presented to the planner so that a proper sewer rehabilitation plan can be selected.