• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.49-58
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• 2006

In this paper, a curve-fitting channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system in a time-varying frequency-selective fading channel. The method can greatly improve channel state information (CSI) estimation accuracy by performing smoothing and interpolation through consecutive curve-fitting processes in both time domain and frequency domain. It first evaluates least-squares (LS) estimates using pilot symbols and then the estimates are approximated to a polynomial with proper degree in the LS error sense, starting from one preferred domain in which pilots we densely distributed. Smoothing, interpolation, and prediction are performed subsequently to obtain CSI estimates for data transmission. The channel estimation processes are completed by smoothing and interpolating CSI estimates in the other domain once again using the channel estimates obtained in one domain. The performance of proposed method is influenced heavily on the time variation and frequency selectivity of channel and pilot arrangement. Hence, a proper degree of polynomial and an optimum approximation interval according to various system and channel conditions are required for curve-fitting. From extensive simulation results in various channel environments, we see that the proposed method performs better than the conventional methods including the optimal Wiener filtering method, in terms of the mean square error (MSE) and bit error rate (BER).

• Honam Mathematical Journal
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• v.40 no.4
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• pp.771-783
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• 2018

This paper, we investigate a strongly damped nonlinear Klein-Gordon equation with nonlinearities of variable exponent type $$u_{tt}-{\Delta}u-{\Delta}u_t+m^2u+{\mid}u_t{\mid}^{p(x)-2}u_t={\mid}u{\mid}^{q(x)-2}u$$ associated with initial and Dirichlet boundary conditions in a bounded domain. We obtain a nonexistence of solutions if variable exponents p (.), q (.) and initial data satisfy some conditions.

• Journal of Navigation and Port Research
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• v.42 no.3
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• pp.201-206
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• 2018

The purpose of this study is to estimate a proper Domain Watch between anchored vessels in order to propose a method for the efficient management of VTS(Vessel Traffic Service) of the N-anchorage in Busan harbor, which is the largest port in Korea. For this purpose, we proposed the calculation method of Domain Watch and investigated the ship length(L), the distance between anchored vessels ($D_{ij}$), the domain radius(R), and the domain radius vs L(R/L) during the peak time of the vessels in the latest usage of anchorage. As a result of technical analysis for the surveyed data, the minimum R/L for securing the safety distance between anchored vessels was selected based on 2.85 corresponding to the 70th percentile of the total data. This result was applied to the N-anchorage of Busan and compared with the 'Guidelines of Port and Harbor Design(2014)', and we have confirmed that it is reasonable to set the Domain radius with the minimum 2.85L or more in VTS. This study considers the safety management of anchorage for VTS. This study could contribute to the safety of vessels using anchorage and the safety management plan of VTS when it is applied to other ports in operation such as it was in Busan.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.297-307
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• 2021

In the vibrant environment, documentation and managing systems are maintained autonomously through education foundations, book materials and libraries at the same time as information are not voluntarily accessible in a centralized location. At the moment Libraries are providing online resources and services for education activities. Moreover, libraries are applying outlets of social media such as Facebook as well as Instagrams to preview their services and procedures. Librarians with the assistance of promising tools and technology like analytics software are capable to accumulate more online information, analyse them for incorporating worth to their services. Thus Libraries can employ big data to construct enhanced decisions concerning collection developments, updating public spaces and tracking the purpose of library book materials. Big data is being produced due to library digitations and this has forced restrictions to academicians, researchers and policy creator's efforts in enhancing the quality and effectiveness. Accordingly, helping the library clients with research articles and book materials that are in line with the users interest is a big challenge and dispute based on Taibah university in Saudi Arabia. The issues of this domain brings the numerous sources of data from various institutions and sources into single place in real time which can be time consuming. The most important aim is to reduce the time that lapses among the authentic book reading and searching the specific study material.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.324-329
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• 2003

Spectral analysis is an important signal processing tool for time series data. The transformation of a time series into the frequency domain is the basis for a significant number of processing algorithms and interpretive methods. Recently developed transforms based on the new mathematical field of wavelet analysis bypass the resolution limitation and offer superior spectral decomposition. The discrete wavelet transform of Sonar data provides spectral localization of noises, hence noises can be filtered out successfully.

• Geophysics and Geophysical Exploration
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• v.14 no.4
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• pp.289-297
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• 2011

Chirp sub-bottom profilers (SBP) data are comparatively higher-resolution data than other seismic data and it's raw signal can be used as a final section after conducting basic filtering. However, Chirp SBP signal has possibility to include various noise in high-frequency band and to provide the distorted image for the complex geological structure in time domain. This study aims at the goal to establish the workflow of Chirp SBP data processing for enhanced image and to analyze the proper parameters for the domestic continental shelf. After pre-processing, we include the dynamic S/N filtering to eliminate the high-frequency component noise, the dip scan stack to enhance the continuity of reflection events and finally the post-stack depth migration to correct the distorted structure on the time domain sections. We demonstrated our workflow on the data acquired by domestically widely used equipments and then we could obtain the improved seismic sections of depth domain. This workflow seems to provide the proper seismic section to interpretation when applied to data processing of Chirp SBP that are largely used for domestic acquisition.

• The Journal of Engineering Geology
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• v.7 no.1
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• pp.63-79
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• 1997

In this study, our purpose is to develop a technique to discriminate artificial explosions from local microearthquakes on the basis of time-frequency domain. To obtain spectral features of artificial explosions and microearthquakes, we used 3-d spectrograms(frequency, time and amplitude) because this is a useful tool to study the frequency content of entire seismic waveforms observed at local and regional distances (e. g., Kim et al., 1994). P and S waves from quarry blasts show that frequency content of dominant amplitude appeared above 10 Hz and Rg phases that are observed at near distance ranges. But P and S waves from microearthquakes have more broad frequency content as well as below 10 Hz. And for discrimination, Pg/Lg spectral ratio is performed below 10 Hz. In order to select time windows we computed group velocity using multiple filter method(MFM) and removed free surface effects from all 3-components data for improving on data quality. Next step, we computed Fast-Fourier transform, and a log average spectral amplitude over seven frequency bands : 0.5 to 3, 2 to 4, 3 to 5, 4 to 6, 5 to 7, 6 to 8 and 8 to 10 Hz. The best separation is observed from 6 to 8 Hz.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.363-384
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• 2011

As the complexity of software is increasing, generating an effective test data has become a necessity. This necessity has increased the demand for techniques that can generate test data effectively. This paper proposes a test data generation technique based on adequacy based testing criteria. Adequacy based testing criteria uses the concept of mutation analysis to check the adequacy of test data. In general, mutation analysis is applied after the test data is generated. But, in this work, we propose a technique that applies mutation analysis at the time of test data generation only, rather than applying it after the test data has been generated. This saves significant amount of time (required to generate adequate test cases) as compared to the latter case as the total time in the latter case is the sum of the time to generate test data and the time to apply mutation analysis to the generated test data. We also use genetic algorithms that explore the complete domain of the program to provide near-global optimum solution. In this paper, we first define and explain the proposed technique. Then we validate the proposed technique using ten real time programs. The proposed technique is compared with path testing technique (that use reliability based testing criteria) for these ten programs. The results show that the adequacy based proposed technique is better than the reliability based path testing technique and there is a significant reduce in number of generated test cases and time taken to generate test cases.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.777-782
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• 2010

We introduce some techniques to decompose the impulse (the unit sample) into several dilated pieces in the discrete time domain. From the decomposition of the impulse, we obtain localized moving averages. Thus we construct hybrid Bollinger bands that may give various strategies for stock traders. By simulations, we report that more than 94% of stock prices of companies in KOSPI 200 are inside this hybrid Bollinger band.