• Asian Journal of Atmospheric Environment
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• v.6 no.3
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• pp.222-233
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• 2012

The nocturnal low-level jet makes a significant impact on carbon and water exchanges and turbulent mixing processes in the atmospheric boundary layer. This study reports a case study of nocturnal surface fluxes such as $CO_2$ and water vapor in the surface layer observed at a flat and homogeneous site in the presence of low-level jets (LLJs). In particular, it documents the temporal evolution of the overlying jets and the coincident response of surface fluxes. The present study highlights several factors linking the evolution of low-level jets to surface fluxes: 1) wavelet analysis shows that turbulent fluxes have similar time scales with temporal scale of LLJ evolution; 2) turbulent mixing is enhanced during the transition period of low-level jets; and 3) $CO_2$, water vapor and heat show dissimilarity from momentum during the period. We also found that LLJ activity is related not only to turbulent motions but also to the divergence of mean flow. An examination of scalar profiles and turbulence data reveal that LLJs transport $CO_2$ and water vapor by advection in the stable boundary layer, suggesting that surface fluxes obtained from the micrometeorological method such as nocturnal boundary layer budget technique should carefully interpreted in the presence of LLJs.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1462-1471
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• 2005

Recently, the medical image has been digitized by the development of computer science and digitization of the medical devices. There are needs for database service of the medical image and long term storage because of the construction of PACS(picture archiving and communication system) following DICOM(digital imaging communications in medicine) standards, telemedicine, and et al. However, it also caused some kinds of problems, such as illegal reproduction of medical image, proprietary rights and data authentication. In this paper, we propose the new digital watermarking technique for medical image based on public key encryption algorithm for integrity verification. It prevents illegal forgery that can be caused after transmitting medical image data remotely. The watermark is the value of bit-plane in wavelet transform of the original image for certification method of integrity verification. We proposed the embedding regions are randomly chosen considering ROI, and a digital signature is made using hash function of MD5 which input is a secret key. The experimental results show that the watermark embedded by the proposed algorithm can survive successfully in image processing operations and that the watermark's invisibility is good.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.542-549
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• 2000

This Paper presents the development of multiresolution model for the analysis and visualization of two-dimensional flows over curvilinear grids. Multiresolution analysis provides a useful and efficient tool to represent shape and to analyze features at multiple level of detail. Applying multiresolution analysis to vector field visualization is very useful and powerful as the vector field's data sets are usually huge and complex. Using approximation at lower resolution, brief outline of topology can be extracted in short periods of time. Local reconstruction allows the user to zoom in or out, only by reconstructing the portion of interest. This new model is based upon nested spaces of piecewise defined function over nested curvilinear grid domains. The nested domains are selected so as to maintain the original geometry of the inner boundary. This paper presents the refinement and decomposition equations for Haar wavelet over these domains and shows some examples.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.163-170
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• 2017

Internet of things (IoT) is a new paradigm for collecting, processing and analyzing various contents in order to detect anomalies and to monitor particular patterns in a specific environment. The collected data can be used to discover new patterns and to offer new insights. IoT-enabled data mashup is a new technology to combine various types of information from multiple sources into a single web service. Mashup services create a new horizon for different applications. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations may utilize IoT - enabled data mashup service to merge different types of datasets from different IoT sensor networks in order to leverage their data analytics performance and the accuracy of the predictions. This paper presents an IoT - enabled data mashup service, where the multimedia data is collected from the various IoT platforms, then fed into an environmental cognition service which executes different image processing techniques such as noise removal, segmentation, and feature extraction, in order to detect interesting patterns in hazardous areas. The noise present in the captured images is eliminated with the help of a noise removal and background subtraction processes. Markov based approach was utilized to segment the possible regions of interest. The viable features within each region were extracted using a multiresolution wavelet transform, then fed into a discriminative classifier to extract various patterns. Experimental results have shown an accurate detection performance and adequate processing time for the proposed approach. We also provide a data mashup scenario for an IoT-enabled environmental hazard detection service and experimentation results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.7
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• pp.308-316
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• 2002

In this paper, we propose a robust digital copyright-protection technique based on the concept of human auditory system. First, we propose a watermarking technique that accepts the various attacks such as, time scaling, pitch shift, add noise and a lot of lossy compression such as MP3, AAC WMA. Second, we implement audio PD(portable device) for copyright protection using proposed method. The proposed watermarking technique is developed using digital filtering technique. Being designed according to critical band of HAS(human auditory system), the digital filers embed watermark without nearly affecting audio quality. Before processing of digital filtering, wavelet transform decomposes the input audio signal into several signals that are composed of specific frequencies. Then, we embed watermark in the decomposed signal (0kHz~11kHz) by designed band-stop digital filer. Watermarking detection algorithm is implemented on audio PD(portable device). Proposed watermarking technology embeds 2bits information per 15 seconds. If PD detects watermark '11', which means illegal song. PD displays "Illegal Song" message on LCD, skips the song and plays the next song, The implemented detection algorithm in PD requires 19 MHz computational power, 7.9kBytes ROM and 10kBytes RAM. The suggested technique satisfies SDMI(secure digital music initiative) requirements of platform3 based on ARM9E core.

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.959-972
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• 2014

In this study, a space-time rainfall grid field generation model based on multifractal theory was verified using nine flood events in the upstream watershed of Chungju dam in South Korea. For this purpose, KMA radar rainfall data sets were analyzed for the space-time multifractal characteristics. Simulated rainfall fields that represent the multifractal characteristics of observed rainfall field were reproduced using the space-time rainfall grid field generation model with log-Poisson distribution and three-dimension wavelet function. Simulated rainfall fields were applied to the S-RAT model as input data and compared with both observed rainfall fields and low-resolution rainfall field runoff. Error analyses using RMSE, RRMSE, MAE, SS, NPE and PTE indicated that the peak discharge increases about 20.03% and the time to peak decreases about 0.81%.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1439-1444
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• 2005

Induction motors are the most commonly used electrical drives because they are rugged, mechanically simple, adaptable to widely different operating conditions, and simple to control. The most common faults in squirrel-cage induction motors are bearing, stator and rotor faults. Surveys conducted by the IEEE and EPRI show that the most common fault in induction motor is bearing failure (${\sim}$40% of failure). Thence, this paper addresses experimental results for diagnosing faults with different rolling element bearing damage via motor current spectral analysis. Rolling element bearings generally consist of two rings, an inner and outer, between which a set of balls or rollers rotate in raceways. We set the experimental test bed to detect the rolling-element bearing misalignment of 3 type induction motors with normal condition bearing system, shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by incipient bearing failure. The failure modes are reviewed and the characteristics of bearing frequency associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT, Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. The test results clearly illustrate that the stator signature can be used to identify the presence of a bearing fault.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.71-80
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• 2012

This paper proposes vehicle detection and tracking algorithm using a CCD camera. The proposed algorithm uses Haar-like wavelet edge detector to detect features of vehicle and estimates vehicle's location using calibration information of an image. After that, extract accumulated vehicle information in continuous k images to improve reliability. Finally, obtained vehicle region becomes a template image to find same object in the next continuous image using SURF(Speeded Up Robust Features). The template image is updated in the every frame. In order to reduce SURF processing time, ROI(Region of Interesting) region is limited on expended area of detected vehicle location in the previous frame image. This algorithm repeats detection and tracking progress until no corresponding points are found. The experimental result shows efficiency of proposed algorithm using images obtained on the road.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.160-167
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• 2014

This paper presents a spliced color image detection method using Benford' Law and color difference. For a suspicious image, after color conversion, the discrete wavelet transform and the discrete cosine transform are performed. We extract the difference between the ideal Benford distribution and the empirical Benford distribution of the suspicious image as features. The difference between Benford distributions for each color component were also used as features. Our method shows superior splicing detection performance using only 13 features. After training the extracted feature vector using SVM classifier, we determine whether the presence of the image splicing forgery. Experimental results show that the proposed method outperforms the existing methods with smaller number of features in terms of splicing detection accuracy.

• 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.