• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.176-181
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• 2010

The evaluation of shear modulus (or shear wave velocity) profile of the site is very important in various fields of geotechnical engineering. In the field, there exist spatial variations of shear modulus that case uncertainty in the geotechnical analysis or design. So it is necessary to evaluate the spatial variation of shear wave velocities of the soil site. In this study, the HWAW method is applied to the determination of a 3-D Vs map of soil site. The HWAW method, which is based on harmonic wavelet transforms, has been developed to determine phase and group velocities of waves. The HWAW method uses only the signal portion of the maximum local signal/noise ratio to evaluate the phase velocity in order to minimize the effect of the noise. The field testing of this method is relatively simple and fast because only one experimental setup, which consists of one pair of receivers on the surface, is needed using a short receiver spacing setup (1~3m). These characteristics make it possible to determine detailed local Vs profile in the site with lateral Vs variation and to evaluate 3-D Vs map by performing a series of tests on the grid. To estimate the applicability of the proposed method, field tests were performed. Through field applications validity and applicability of the proposed method were verified.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.59-68
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• 2009

This paper addresses a hybrid multi-focus image fusion scheme using the recent curvelet transform constructions. Hybridization is obtained by combining the MS fusion rule with a novel "copy" method. The proposed scheme use MS rule to fuse the m most significant terms in spectrum of an image at each decomposition level. The scheme is dubbed in this work as m-term fusion in adherence to its use of the MSC (most significant coefficients) in the transform set at any given scale, orientation, and translation. We applied the edge-sensitive objective quality measure proposed by Xydeas and Petrovic to evaluate the method. Experimental results show that the proposed scheme is a potential alternative to the redundant, shift-invariant Dual-Tree Complex Wavelet transforms. In particular, it was confirmed that a 50% m-term fusion produces outputs with no visible quality degradation.

• Smart Structures and Systems
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• v.7 no.4
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• pp.241-262
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• 2011

Cast iron pipe has been used as a water distribution technology in North America since the early nineteenth century. The first cast iron pipes were made of grey cast iron which was succeeded by ductile iron as a pipe material in the 1940s. These different iron alloys have significantly different microstructures which give rise to distinct mechanical properties. Insight into the non-destructive structural condition assessment of aging pipes can be advantageous in developing mitigation strategies for pipe failures. This paper examines the relationship between the small-strain and large-strain properties of exhumed cast iron water pipes. Nondestructive and destructive testing programs were performed on eight pipes varying in age from 40 to 130 years. The experimental program included microstructure evaluation and ultrasonic, tensile, and flexural testing. New applications of frequency domain analysis techniques including Fourier and wavelet transforms of ultrasonic pulse velocity measurements are presented. A low correlation between wave propagation and large-strain measurements was observed. However, the wave velocities were consistently different between ductile and grey cast iron pipes (14% to 18% difference); the ductile iron pipes showed the smaller variation in wave velocities. Thus, the variation of elastic properties for ductile iron was not enough to define a linear correlation because all the measurements were practically concentrated in single cluster of points. The cross-sectional areas of the specimens tested varied as a result of minor manufacturing defects and levels of corrosion. These variations affect the large strain testing results; but, surface defects have limited effect on wave velocities and may also contribute to the low correlations observed. Lamb waves are typically not considered in the evaluation of ultrasonic pulse velocity. However, Lamb waves were found to contribute significantly to the frequency content of the ultrasonic signals possibly resulting in the poor correlations observed. Therefore, correlations between wave velocities and large strain properties obtained using specimens manufactured in the laboratory must be used with caution in the condition assessment of aged water pipes especially for grey cast iron pipes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1113-1124
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• 2004

In this paper, we proposed a hardware(H/W) structure which can compress and recontruct the input image in real time operation and implemented it into a FPGA platform using VHDL(VHSIC Hardware Description Language). All the image processing element to process both compression and reconstruction in a FPGA were considered each of them was mapped into H/W with the efficient structure for FPGA. We used the DWT(discrete wavelet transform) which transforms the data from spatial domain to the frequency domain, because use considered the motion JPEG2000 as the application. The implemented H/W is separated to both the data path part and the control part. The data path part consisted of the image processing blocks and the data processing blocks. The image processing blocks consisted of the DWT Kernel fur the filtering by DWT, Quantizer/Huffman Encoder, Inverse Adder/Buffer for adding the low frequency coefficient to the high frequency one in the inverse DWT operation, and Huffman Decoder. Also there existed the interface blocks for communicating with the external application environments and the timing blocks for buffering between the internal blocks The global operations of the designed H/W are the image compression and the reconstruction, and it is operated by the unit of a field synchronized with the A/D converter. The implemented H/W used the 69%(16980) LAB(Logic Array Block) and 9%(28352) ESB(Embedded System Block) in the APEX20KC EP20K600CB652-7 FPGA chip of ALTERA, and stably operated in the 70MHz clock frequency. So we verified the real time operation of 60 fields/sec(30 frames/sec).

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.208-212
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• 2010

The high-speed railway consists of tracks, gravel ballast and subgrade, and the dynamic load is passed to subgrade through track and gravel ballast. The relaxation condition of the gravel ballast is able to be evaluate relatively and to be repaired through a continuous management, but it is difficult to evaluate the condition of subgrade, which is final part of supporting dynamic load and to repair it when made a problem. The gravel ballast and subgrade are evaluated by determining shear wave velocity. To evaluate ballast and subgrade, a good method to determine shear wave velocity is a non-destructive experiment such as surface wave tests providing a prompt experiment because an experiment in railway has a lot of tests which are carried out following railway directions and needs to prevent damage of the system. In general, a railway has limitation of an experimental space by narrow width, sleeper and etc., and background noise by a reflector exists. The existing surface wave tests need a minimum space, and it is difficult to get a reliable test results on account of background noise effect. Therefore, it is difficult or impossible to apply to existing surface wave test of subgrade and ballast. In this study, the HWAW method is applied to determine a shear wave velocity profile of the underground. The HWAW method is the experiment which is able to be carried out on a narrow space, and it determines share wave velocity of a site by measuring the wave from surface sources on the same spot. In addition, it removes effects of background noise accordingly to a signal processing using harmonic wavelet transforms, so it is useful to evaluate subgrade of a high-speed railway in the narrow space and the situation of background noise. In order to check an application of the HWAW method, an experiment is carried out on a high-speed railway field and a test result is compared to boring results.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.182-187
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• 2010

In the various fields of Civil Engineering, shear modulus is very important input parameters to design many constructions and to analyze ground behaviors. In general, a shear wave velocity profile is decided by various experiments before constructing a structure and, analysis and design are carried out by using decided shear wave velocity profile of the site. However, if civil structures are started to construct, the shear wave velocity will be increased more than before constructions because of confining pressure increase by the load of structure. The evaluation of the change in shear wave velocity profile is used very importantly when maintaining, managing, reinforcing and regenerating existing structures. In this study, a non-destructively geotechnical investigation method by using the HWAW method is applied to an evaluation of change in properties of the site according to construction. Generally, the space for experiments is narrow when underground of existing or on-going structures is evaluate, so a prompt non-destructive experiment is required. This prompt non-destructive experiment would be performed by various in-situ seismic methods. However, most of in-situ seismic methods need more space for experiments, so it is difficult to be applied. The HWAW method using the Harmonic wavelet transforms, which is based on time-frequency analysis, determines shear wave velocity profile. It consists of a source as well as short receiver spacing that is 1~3m, and is able to determine a shear wave velocity profile from surface to deep depth by one test on a space. As the HWAW method uses only the signal portion of the maximum local signal/noise ratio to determine a profile, it provides reliability shear modulus profile such as under construction or noisy situation by minimizing effects of noise from diverse vibration on a construction site or urban area. To estimate the applicability of the proposed method, field tests were performed in the change of geotechnical properties according to constructing a minimized modeling bent. Through this study, the change of geotechnical properties of the site was effectively evaluated according to construction of a structure.

• Composites Research
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• v.24 no.1
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• pp.24-30
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• 2011

Low-velocity impact can cause various damages which are mostly hidden inside the laminates or occur in the opposite side. Thus, these damages cannot be easily detected by visual inspection or conventional NDT systems. And if they occurred between the scheduled NDT periods, the possibilities of extensive damages or structural failure can be higher. Due to these reasons, the built-in NDT systems such as real-time impact monitoring system are required in the near future. In this paper, we studied the impact monitoring system consist of impact location detection and damage assessment techniques for composite flat and stiffened panel. In order to acquire the impact-induced acoustic signals, four multiplexed FBG sensors and high-speed FBG interrogator were used. And for development of the impact and damage occurrence detections, the neural networks and wavelet transforms were adopted. Finally, these algorithms were embodied using MATLAB and LabVIEW software for the user-friendly interface.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.