• The Journal of Asian Finance, Economics and Business
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• 제9권8호
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• pp.89-97
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• 2022

The e-commerce market faces significant credit risks due to the complexity of the industry and information asymmetries. Therefore, credit risk has started to stymie the growth of e-commerce. However, there is no reliable system for evaluating the creditworthiness of e-commerce companies. Therefore, this paper constructs a credit risk evaluation index system that comprehensively considers the online and offline behavior of online retail enterprises, including 15 indicators that reflect online credit risk and 15 indicators that reflect offline credit risk. This paper establishes an integration method based on a fuzzy integral support vector machine, which takes the factor analysis results of the credit risk evaluation index system of online retail enterprises as the input and the credit risk evaluation results of online retail enterprises as the output. The classification results of each sub-classifier and the importance of each sub-classifier decision to the final decision have been taken into account in this method. Select the sample data of 1500 online retail loan customers from a bank to test the model. The empirical results demonstrate that the proposed method outperforms a single SVM and traditional SVMs aggregation technique via majority voting in terms of classification accuracy, which provides a basis for banks to establish a reliable evaluation system.

• 한국항공운항학회지
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• 제31권1호
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• pp.118-132
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• 2023

This study aimed to analyze the relationship between the learning perception of aviation service subjects using role play on the interpersonal competence, learning satisfaction, and learning outcomes of college students majoring in aviation service. A survey was conducted targeting 217 university students majoring in aviation service who are enrolled in universities in the metropolitan area and Chungcheong area and have experience in class using role play. In addition, the hypothesis is verified using the structural equation model. Among the perceptions of role play classes experienced by university students majoring in aviation service, 'inter-dependency' was found to have a positive (+) effect on all sub-factors of interpersonal competence. And 'usefulness' confirmed the positive (+) influence relationship with 'temperament for others' and 'communication' except for 'relationship promotion' of interpersonal ability. Among sub-factor of interpersonal competence, it is confirmed that only the factors of 'temperament for others' and 'communication' had an effect on learning satisfaction. And it is proved that learning satisfaction is an important determinant of learning outcomes. Therefore, this study is expected to serve as a basis for deriving an efficient and optimal learning method for practical subjects in aviation service majors.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1708-1717
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• 2023

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F₁ score for both types of ores is greater than 0.9.

• 공업화학
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• 제16권3호
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• pp.337-341
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• 2005

본 논문은 니켈이 담지된 촉매를 이용하여 메탄의 이산화탄소 개질반응에서 발생하는 탄소퇴적의 속도와 반응온도에 따른 카본생성 경로를 연구하였다. 개질 반응이 진행되는 동안 촉매 위에 발생하는 탄소퇴적과 그 속도측정을 위한 반응장치로는 열분석기를 이용하였다. 메탄의 이산화탄소 개질반응에서 반응기체 조성을 달리하여 실험한 결과 코크형성의 반응차수가 1.33($CH_4$)과 -0.52($CO_2$)임을 확인하였다. 또한, 탄소퇴적속도를 이용한 모델식을 근거로 반응온도에 따른 반응속도인자를 계산한 결과 $600^{\circ}C$ 미만에서는 메탄의 분해반응만이 주로 발생하며 $600{\sim}700^{\circ}C$ 사이에서는 메탄의 분해반응과 더불어 이산화탄소 해리반응이 동시에 진행됨을 알았다.

• 한국전기전자재료학회논문지
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• 제17권7호
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• pp.691-696
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• 2004

The electronic state and chemical bonding of $\beta$-MnO$_2$ with transition metal dopants were theoretically investigated by DV-X$_{\alpha}$ (the discrete variational X$_{\alpha}$) method, which is a sort of the first principles molecular orbital method using the Hartree-Fock-Slater approximation. The calculations were performed with a $_Mn_{14}$ MO$_{56}$ )$^{-52}$ (M = transition metals) cluster model. The electron energy level, the density of states (DOS), the overlap population, the charge density distribution, and the net charges, were calculated. The energy level diagram of MnO$_2$ shows the different band structure and electron occupancy between the up spin states and down spin states. The dopant levels decrease between the conduction band and the valence band with the increase of the atomic number of dopants. The covalency of chemical bonding was shown to increase and ionicity decreased in increasing the atomic number of dopants. Calculated results were discussed on the basis of the interaction between transition metal 3d and oxygen 2p orbital. In conclusion it is expected that when the transition metals are added to MnO$_2$ the band gap decreases and the electronic conductivity increases with the increase of the atomic number of dopants. the atomic number of dopants.

• 한국지능시스템학회논문지
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• 제16권4호
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• pp.472-478
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• 2006

본 논문에서는 기동표적의 추적에 대한 새로운 퍼지 뉴럴 네트워크 기반의 다중모델 기법을 소개한다. 표적의 가속도를 효과적으로 다루기 위하여, 이 논문에서는 표적의 가속도를 시변 변수인 표적의 추가적인 잡음으로 두고 각각의 가속도 간격의 정도에 따라 얻어지는 모든 잡음에 대한 변수에 의해 각각의 하부 모델들을 특성화시켰다. 모르는 가속도에 따른 시변 변수를 적응적으로 어립잡기는 어렵기 때문에 정밀한 계산을 위하여 퍼지 뉴럴 네트워크가 이용되었다. 퍼지 뉴럴 네트워크의 동정을 위해서는 오차 역전파 학습법을 사용하였다. 그리고 제안된 알고리즘의 수행 가능성을 보여주기 위하여 몇 가지 예를 제시하였다.

• 한국환경보건학회지
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• 제31권6호
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• pp.467-474
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• 2005

The runoff characteristics of combined sewer overflow(CSO) in the urban area of Jeonju were investigated and analyzed by using the SWMM (Storm Water Management Model) and GIS. From August to November 2004, investigations on two rainfall events were performed and flowrate, pH, BOD, COD, SS, T-N and T-P were measured. these data were used for model calibration. Using GIS technique, watershed characteristics of study area were calculated. that is, divide into sub_basin, total width, slope, make soil map etc. On the basis of the measured data and the simulation results by SWMM, it could be known that the $80-90\%$ of pollution load are discharged in early-stage storm runoff. SMC(site mean Concentration) for combined sewer system area were BOD 28.1, COD 31.5, SS 186 ppm etc. this is shown that during the rain fall, high concentration of waste was loaded to receiving water. Unit loads of combined sewer system area were BOD 306, COD 410, SS 789, T-N 79, T-P 6.8 kg/ha/yr.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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• pp.893-898
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• 1994

In this paper, the influence of voice source estimation and modeling on speech synthesis and coding is examined and then their new estimation and modeling techniques are proposed and verified by computer simulation. It is known that the existing speech synthesizer produced the speech which is dull and inanimated. These problems are arised from the fact that existing estimation and modeling techniques can not give more accurate voice parameters. Therefore, in this paper we propose a new voice source estimation algorithm and modeling techniques which can not give more accurate voice parameters. Therefore, in this paper we propose a new voice source estimation algorithm and modeling techniques which can represent a variety of source characteristics. First, we divide speech samples in one pitch region into four parts having different characteristics. Second, the vocal-tract parameters and voice source waveforms are estimated in each regions differently using sequential SVD. Third, we propose composite source model as a new voice source model which is represented by weighted sum of pre-defined basis functions. And finally, the weights and time-shift parameters of the proposed composite source model are estimeted uning EM(estimate maximize) algorithm. Experimental results indicate that the proposed estimation and modeling methods can estimate more accurate voice source waveforms and represent various source characteristics.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1101-1113
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• 2021

The rapid growth of sense-and-respond applications and the emerging cloud computing model present a new challenge: providing publish/subscribe middleware as a scalable and elastic cloud service. The publish/subscribe interaction model is a promising solution for scalable data dissemination over wide-area networks. In addition, there have been some work on the publish/subscribe messaging paradigm that guarantees reliability and availability in the face of node and link failures. These publish/subscribe systems are commonly used in information-centric networks and edge-fog-cloud infrastructures for IoT. The IoT has an edge-fog cloud infrastructure to efficiently process massive amounts of sensing data collected from the surrounding environment. In this paper. we propose a quorum-based hierarchical fault-tolerant publish/subscribe systems (QHFPS) to enable reliable delivery of messages in the presence of link and node failures. The QHFPS efficiently distributes IoT messages to the publish/subscribe brokers in fog overlay layers on the basis of proposing extended stepped grid (xS-grid) quorum for providing tolerance when faced with node failures and network partitions. We evaluate the performance of QHFPS in three aspects: number of transmitted Pub/Sub messages, average subscription delay, and subscritpion delivery rate with an analytical model.

• 품질경영학회지
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• 제51권4호
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• pp.497-514
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• 2023

Purpose: This study aims to estimate the demand for various public parking lots in Seoul by clustering similar demand types of parking lots and predicting the demand for new public parking lots. Methods: We examined real-time parking information data and used time series clustering analysis to cluster public parking lots with similar demand patterns. We also performed various regression analyses of parking demand based on diverse heterogeneous data that affect parking demand and proposed a parking demand prediction model. Results: As a result of cluster analysis, 68 public parking lots in Seoul were clustered into four types with similar demand patterns. We also identified key variables impacting parking demand and obtained a precise model for predicting parking demands. Conclusion: The proposed prediction model can be used to improve the efficiency and publicity of public parking lots in Seoul, and can be used as a basis for constructing new public parking lots that meet the actual demand. Future research could include studies on demand estimation models for each type of parking lot, and studies on the impact of parking lot usage patterns on demand.