• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.59-67
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• 2012

It was reported that the latest sensor technology allow an 65536 conductive polymer sensor array to be made with broad but overlapping selectivity to different families of chemicals emulating the characteristics found in biological olfaction. However, the supernumerary redundancy always accompanies great error and risk as well as an inordinate amount of computation time and local minima in signal processing, e.g. neural networks. In this paper, we propose a new method to reduce the number of sensor for analysis by reducing redundancy between sensors and by removing unstable sensors using the cosine similarity method and to decide on representative sensor using FCM(Fuzzy C-Means) algorithm. The representative sensors can be just used in analyzing. And, we introduce DWT(Discrete Wavelet Transform) for data compression in the time domain as preprocessing. Throughout experimental trials, we have done a comparative analysis between gas sensor data with and without reduced redundancy. The possibility and superiority of the proposed methods are confirmed through experiments.

• Journal of the Korean Geotechnical Society
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• v.28 no.8
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• pp.55-63
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• 2012

The evaluation of shear modulus (or shear wave velocity) profile of the site is very important in various fields of geotechnical engineering and various surface wave methods have applied to determine the shear wave velocity profiles and showed good performance. Surface wave methods evaluate the dispersion curve in the field and determine the shear wave velocity profile through the inversion process. In this paper, the automated inversion process using the genetic algorithm is developed for HWAW method which is one of surface wave methods recently developed. The proposed method uses the error function based on the wavelength domain dispersion curve and can determine the reliable shear wave velocity profile not only in shallow depth but also in deep depth. To estimate the validity of the proposed method, numerical simulations and field test were performed and the proposed method was applied to determine the shear wave velocity profiles. Through the numerical simulations and field applications, the promising potential of the proposed method was verified.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.337-346
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• 1996

The patency of small size vascular grafts is poor, and the blood flow characteristics in the artery graft anastomosis are suspected as one of the important factors influencing intimal hyperplasia. Disturbed flow patterns caused by sixte and compliance mismatch generate unfavorable flow environment which promotes intimal thickening. Tapered vascular yuts are suggested in order to reduce sudden expansion near the anastomosis. The photochromic flow visualization method is used to measure the flout fields in the end-to-end anastomosis model under the carotid and femoral artery flow wave form. The results show that flow disturbance near the anastomosis is diminished in the tapered grafts comparing to the tubular graft. As the divergent ang1e decreases, we can reduce the low and oscillatory wall shear stress zone which is prone to intimal hyperplasia. The flow wave form effects the wall shear rate dis- tribution significantly. The steep deceleration and back flow in the femoral flow wAve form cause low mean wall shear rate and high oscillatory shear index.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.936-941
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• 2006

To apply object recognition techniques to real environment, illumination compensation method should be developed. As effective illumination compensation model, we focused our attention on Retinex model and illumination-Reflectance model, implemented them, and experimented on their performance. We implemented Retinex model with Single Scale Retinex, Multi-Scale Retinex, and Retinex Neural Network and Multi-Scale Retinex Neural Network, neural network model of Retinex model. Also, we implemented illumination-Reflectance model with reflectance image calculation by calculating an illumination image by low frequency filtering in frequency domain of Discrete Cosine Transform and Wavelet Transform, and Gaussian blurring. We compare their illumination compensation performance to facial images under nine illumination directions. We also compare their performance after post processing using Principal Component Analysis(PCA). As a result, illumination Reflectance model showed better performance and their overall performance was improved when illumination compensated images were post processed by PCA.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.437-451
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• 2003

With the rapid growth of internet technologies and wide availability of multimedia computing facilities, the enforcement of multimedia copyright protection becomes an important issue. Digital watermarking is viewed as an effective way to deter content users from illegal distributions. In recent years, digital watermarking has been intensively studied to achieve this goal. However, when the watermarked media is transmitted over the channels modeled as the additive white Gaussian noise (AWGN) channel, the watermark information is often interfered by the channel noise and produces a large number of errors. So many error-correcting codes have been applied in the digital watermarking system to protect the embedded message from the disturbance of the noise, such as BCH codes, Reef-Solomon (RS) codes and Turbo codes. Recently, low-density parity-check (LDPC) codes were demonstrated as good error correcting codes achieving near Shannon limit performance and outperforming turbo codes nth low decoding complexity. In this paper, in order to mitigate the channel conditions and improve the quality of watermark, we proposed the application of LDPC codes on implementing a fairly robust digital image watermarking system. The implemented watermarking system operates in the spectrum domain where a subset of the discrete wavelet transform (DWT) coefficients is modified by the watermark without using original image during watermark extraction. The quality of watermark is evaluated by taking Into account the trade-off between the chip-rate and the rate of LDPC codes. Many simulation results are presented in this paper, these results indicate that the quality of the watermark is improved greatly and the proposed system based on LDPC codes is very robust to attacks.

• 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.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.3
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• pp.187-199
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• 2013

Umbrella arch method (UAM) used for improving the stability of the tunnel ground condition has been widely applied in the tunnel construction projects due to the advantage of obtaining both reinforcement and waterproof. The purpose of this study is to develop the evaluation technique of the integrity of bore-hole in UAM by using a non-destructive test and to evaluate the possibility of being applied to the field. In order to investigate the variations of frequency depending on grouted length, the specimens with different grouted ratios are made in the two constraint conditions (free boundary condition and embedded condition). The hammer impact reflection method in which excitation and reception occur simultaneously at the head of pipe was used. The guided waves generated by hitting a pipe with a hammer were reflected at the tip and returned to the head, and the signals were received by an acoustic emission (AE) sensor installed at the head. For the laboratory experiments, the specimens were prepared with different grouted ratios (25 %, 50 %, 75 %, 100 %). In addition, field tests were performed for the application of the evaluation technique. Fast Fourier transform and wavelet transform were applied to analyze the measured waves. The experimental studies show that grouted ratio has little effects on the velocities of guided waves. Main frequencies of reflected waves tend to decrease with an increase in the grouted length in the time-frequency domain. This study suggests that the non-destructive tests using guided ultrasonic waves be effective to evaluate the bore-hole integrity of the UAM in the field.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• 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.