• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.29-36
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• 2005

The crustal structure of Korean Peninsula is investigated by analyzing phase velocity dispersion data of Rayleigh wave. Earthquakes recorded by three component seismographs during 1999 - 2004 in South Korea are used in this study. The fundamental mode signals of Rayleigh waves are obtained from vertical components of seismograms by multiple filter technique method and phase match filter method. Velocity dispersion curves of surface waves for 14 propagation paths on the great circle are computed from the fundamental mode signals on the great circle path by two-station method. Treating the shear velocity of each layer as an independent parameter, phase velocities of Rayleigh wave are inverted. The result models are regarded as average structure for surface wave propagation paths respectively. All the results can be explained by an earth model of the Korean Peninsula comprising crust of shear-wave velocity increasing from 2.8 to 3.25 km/sec from top to 33 km depth and uppermost mantle of shear-wave velocity between 4.55 and 4.67 km/sec.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of the Korean Magnetics Society
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• v.17 no.4
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• pp.166-171
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• 2007

We report the magneto-transport properties of an individual single crystalline Bi nanowire grown by a spontaneous growth method. We have successfully fabricated a four-terminal device based on an individual 400-nm-diameter nanowire using plasma etching technique to remove an oxide layer forming on the outer surface of the nanowire. The transverse MR (2496% at 110 K) and longitudinal MR ratios (38% at 2 K) for the Bi nanowire were found to be the largest known values in Bi nanowires. This result demonstrates that the Bi nanowires grown by the spontaneous growth method are the highest-quality single crystalline in the literatures ever reported. We find that temperature dependence of Fermi energy ($E_F$) and band overlap (${\triangle}_0$) leads to the imbalance between electron concentration ($n_e$) and hole concentration ($n_h$) in the Bi nanowire, which is good agreement with the calculated $n_e\;and\;n_h$ from the respective density of states, N(E), for electrons and holes. We also find that the imbalance of $n_e\;and\;n_h$ plays a crucial role in determining magnetoresistance (MR) at T<75 K for $R_T$ and at T<205 K for $R_L$, while mean-free path is responsible for MR at T>75 K for $R_T$ and T>205 K for $R_L$.

• Wind and Structures
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• v.13 no.1
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• pp.57-82
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• 2010

The 486m-long roof of Shenzhen Citizens Centre is one of the world's longest spatial lattice roof structures. A comprehensive numerical study of wind effects on the long-span structure is presented in this paper. The discretizing and synthesizing of random flow generation technique (DSRFG) recently proposed by two of the authors (Huang and Li 2008) was adopted to produce a spatially correlated turbulent inflow field for the simulation study. The distributions and characteristics of wind loads on the roof were numerically evaluated by Computational Fluid Dynamics (CFD) methods, in which Large Eddy Simulation (LES) and Reynolds Averaged Navier-Stokes Equations (RANS) Model were employed. The main objective of this study is to explore a useful approach for estimations of wind effects on complex curved roof by CFD techniques. In parallel with the numerical investigation, simultaneous pressure measurements on the entire roof were made in a boundary layer wind tunnel to determine mean, fluctuating and peak pressure coefficient distributions, and spectra, spatial correlation coefficients and probability characteristics of pressure fluctuations. Numerical results were then compared with these experimentally determined data for validating the numerical methods. The comparative study demonstrated that the LES integrated with the DSRFG technique could provide satisfactory prediction of wind effects on the long-span roof with complex shape, especially on separation zones along leading eaves where the worst negative wind-induced pressures commonly occur. The recommended LES and inflow turbulence generation technique as well as associated numerical treatments are useful for structural engineers to assess wind effects on a long-span roof at its design stage.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.592-599
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• 2020

This paper proposes a Convolutional Recurrent Neural Net (CRNN) structure that can simultaneously reflect both static and dynamic characteristics of seismic waveforms for various earthquake events classification. Addressing various earthquake events, including not only micro-earthquakes and artificial-earthquakes but also macro-earthquakes, requires both effective feature extraction and a classifier that can discriminate seismic waveform under noisy environment. First, we extract the static characteristics of seismic waveform through an attention-based convolution layer. Then, the extracted feature-map is sequentially injected as input to a multi-input single-output Long Short-Term Memory (LSTM) network structure to extract the dynamic characteristic for various seismic event classifications. Subsequently, we perform earthquake events classification through two fully connected layers and softmax function. Representative experimental results using domestic and foreign earthquake database show that the proposed model provides an effective structure for various earthquake events classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.77-92
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• 2020

When automatic speech recognition (ASR) is provided as a cloud service, it is easy to collect voice and application domain data from users. Harnessing these data will facilitate the provision of more personalized services. In this paper, we demonstrate our transfer learning-based knowledge service that built with the user-generated data collected through our novel system that deliveries personalized ASR service. First, we discuss the motivation, challenges, and prospects of building up such a knowledge-based service-oriented system. Second, we present a Quadruple Transfer Learning (QTL) method that can learn a classification model from a source domain and transfer it to a target domain. Third, we provide an overview architecture of our novel system that collects voice data from mobile users, labels the data via crowdsourcing, utilises these collected user-generated data to train different machine learning models, and delivers the personalised real-time cloud services. Finally, we use the E-Book data collected from our system to train classification models and apply them in the smart TV domain, and the experimental results show that our QTL method is effective in two classification tasks, which confirms that the knowledge transfer provides a value-added service for the upper-layer mobile applications in different domains.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1624-1624
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• 2001

Near-infrared spectroscopy (NIRS) was used to investigate the possibility for application in identification of apple cultivars. Three apple cultivars ‘Kamhong, Hwahong, and Fuji’ produced in Korea were scanned over the range of 1100-2500nm using NIRS (Infra Alzer 500). Two types of samples were used for scanning; one was apple with skin and the other was apple without skin. For cultivar identification, the NIR absorbance spectrums were analyzed by qualitative calibration in “Sesame” analysis program, and the various influence properties such as sugar contents, acidity, color, firmness, and micro-structure were compared in scanned samples. The ‘Kamhong’ cultivar could be identified from ‘Hwahong’ and ‘Fuji’ cultivars using the cluster model analysis. The test samples in calibration between ‘Kamhong’ and ‘Fuji’ cultivars could be completely identified. The test samples in calibration between ‘Kamhong’ and ‘Hwahong’ cultivars could be identified most of all. But, ‘Hwahong’ and ‘Fuji’ cultivars could not be quite classified each other. The apple skin influenced the identification process of apple cultivars. The samples without skin were more difficult to classify in calibration than the samples with skin. The physicochemical properties of apple cultivars showed like the result of identification in calibration using NIRS. Some physicochemical properties of ‘Kamhong’ cultivar were different from those of the other cultivars. Those of ‘Hwahong’ and ‘Fuji’ cultivars showed. similar to each other. The sucrose contents of ‘Kamhong’ cultivar were higher and the fructose contents and firmness of skin and flesh were lower than those of the others. The hypodermis layer of skin in ‘Kamhong’ cultivar was thinner than those of the others. In this studies, the identification of all apple cultivars by NIRS was not quite accurate because of the physicochemical properties which were different in the same cultivar, and inconsistent patterns by culivars in some properties. To solve these problems in NIRS application for apple cultivar identification, further study should be focused on the use of peculiar properties among the apple cultivars.

• Journal of Environmental Science International
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• v.1 no.2
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• pp.119-124
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• 1992

Cloud streets were successfully simulated by numerical model (RAMS) including an Isolated mountain near the coast, large sensible heat flux from the sea surface, uniform stratification and wind velocity with low Froude number (0.25) in the inflow boundary The well developed cloud streets between a pair of convective rolls are simulated at a level of 1 km over the sea. The following five results were obtained: 1) port the formation of the pair of convective rolls, both strong static instability and a topographically induced mechanical disturbance are strongly required at the same time. 2) Strong sensible heat flux from the sea surface is the main energy source of the pair of convective rolls, and the buoyancy caused by condensation in the cloud is negligibly small. 3) The pair o( convective rolls is a complex of two sub-rolls. One is the outer roll, which has a large radius, but weak circulation, and the other is the inner roll, which has a small radius, but strong circulation. The outer roll gathers a large amount of moisture by convergence in the lower marine boundary, and the inner roll transfers the convergent moisture to the upper boundary layer by strong upward motion between them. 4) The pair of inner rolls form the line-shaped cloud streets, and keep them narrow along the center-line of the domain. 5) Both by non-hydrostatic and by hydrostatic assumptions, cloud streets can be simulated. In our case, non-hydrostatic processes enhanced somewhat the formation of cloud streets. The horizontal size of the topography does not seem to be restricted to within the small scale where non-hydrostatic effects are important.

• Journal of Soil and Groundwater Environment
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• v.20 no.5
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• pp.34-40
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• 2015

It is reported that the intensity of rainfall will likely increase, on average, over the world on 2000. For water resources security, many studies for flow paths from rainfall or snowmelt to subsurface have been conducted. In Korea, few isotopic studies for characterizations of flow path have been undertaken. For a better understanding of how water derived from atmosphere moves to subsurface and from subsurface to stream, an analysis of precipitation and stream water using oxygen-18 and deuterium isotopes in a small watershed, Dorim-cheon, Seoul, was conducted with high resolution data. Variations of oxygen-18 in precipitation greater than 10‰ (δ¹⁸O_max = −1.21‰, δ¹⁸O_min = −11.23) were observed. Isotopic compositions of old water (groundwater) assumed as the stream water collected in advance were −8.98‰ and −61.85‰ for oxygen and hydrogen, respectively. Using a two-component mixing model, hydrograph separation of the stream water in Dorim-cheon was conducted based on weighted mean value of δ¹⁸O. As a result, except of instant dominance of rainfall, contribution of old water was dominant during the study period. On average, 71.3% of the old water and 28.7% of rainfall contributed to the stream water. The results show that even in the small watershed, which is covered with thin soil layer in granite mountain region, the stream water is considerably influenced by old water inflow rather than rainfall.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.43-65
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• 2015

Technology standard continues to exist as an social agreement throughout all industry. With development of Information and Communication, it is recently considered as a strategic factor for enhancing interoperability and increasing market dominance. Hence, technology standard research(standardization research) have a significance in analyzing the process of standard adoption and its economic effect and deriving theoretical and policy implications. However, as existing relative researches are lack in consideration on indigenous value of technology and its interoperability, there exists limitation in drawing the result of technology centered analysis. The goal of this study is to suggest new technology centered standard method by implying function of technology differentiation rate and technology preference that are deduced by technology network analysis into two stage game theory. As an example of empirical case, we selected wireless pan technology of Internet of Things, and derive its technological structure and implications related to standard.