• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.7 s.361
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• pp.71-80
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• 2007

This paper describes an efficient hardware design of WiBro security processor (WBSec) supporting for the security sub-layer of WiBro wireless internet system. The WBSec processor, which is based on AES (Advanced Encryption Standard) block cipher algorithm, performs data oncryption/decryption, authentication/integrity, and key encryption/decryption for packet data protection of wireless network. It carries out the modes of ECB, CTR, CBC, CCM and key wrap/unwrap with two AES cores working in parallel. In order to achieve an area-efficient implementation, two design techniques are considered; First, round transformation block within AES core is designed using a shared structure for encryption/decryption. Secondly, SubByte/InvSubByte blocks that require the largest hardware in AES core are implemented using field transformation technique. It results that the gate count of WBSec is reduced by about 25% compared with conventional LUT (Look-Up Table)-based design. The WBSec processor designed in Verilog-HDL has about 22,350 gates, and the estimated throughput is about 16-Mbps at key wrap mode and maximum 213-Mbps at CCM mode, thus it can be used for hardware design of WiBro security system.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.375-382
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• 2003

Lip-reading technique based on bimodal is to enhance speech recognition rate in noisy environment. It is most important to detect the correct lip-image. But it is hard to estimate stable performance in dynamic environment, because of many factors to deteriorate Lip-reading's performance. There are illumination change, speaker's pronunciation habit, versatility of lips shape and rotation or size change of lips etc. In this paper, we propose the IIR filtering in time-domain for the stable performance. It is very proper to remove the noise of speech, to enhance performance of recognition by digital filtering in time domain. While the lip-reading technique in whole lip image makes data massive, the Principal Component Analysis of pre-process allows to reduce the data quantify by detection of feature without loss of image information. For the observation performance of speech recognition using only image information, we made an experiment on recognition after choosing 22 words in available car service. We used Hidden Markov Model by speech recognition algorithm to compare this words' recognition performance. As a result, while the recognition rate of lip-reading using PCA is 64%, Time-domain filter applied to lip-reading enhances recognition rate of 72.4%.

• Geophysics and Geophysical Exploration
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• v.18 no.2
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• pp.64-73
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• 2015

Recently, hydraulic fracturing is used in various fields and microseismic monitoring is one of the best methods for judging where hydraulic fractures exist and how they are developing. When locating microseismic events using single vertical well data, distances from the vertical array and depths from the surface are generally decided using time differences between compressional (P) wave and shear (S) wave arrivals and azimuths are calculated using P wave hodogram analysis. However, in field data, it is sometimes hard to acquire P wave data which has smaller amplitude than S wave because microseismic data often have very low signal to noise (S/N) ratio. To overcome this problem, in this study, we developed a grid search algorithm which can find event location using all combinations of arrival times recorded at receivers. In addition, we introduced and analyzed the method which calculates azimuths using S wave. The tests of synthetic data show the inversion method using all combinations of arrival times and receivers can locate events without considering the origin time even using only single phase. In addition, the method can locate events with higher accuracy and has lower sensitivity on first arrival picking errors than conventional method. The method which calculates azimuths using S wave can provide reliable results when the dip between event and receiver is relatively small. However, this method shows the limitation when dip is greater than about $20^{\circ}$ in our model test.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.55-68
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• 2012

In this paper, we propose a novel method to solve the problem of excessive segmentation out of the method of segmenting regions from an image using Homogeneity Threshold($H_T$). The algorithm of the previous image segmentation based on $H_T$ was carried out region growth by using only the center pixel of selected window. Therefore it was caused resulting in excessive segmented regions. However, before carrying region growth, the proposed method first of all finds out whether the selected window is homogeneity or not. Subsequently, if the selected window is homogeneity it carries out region growth using the total pixels of selected window. But if the selected window is not homogeneity, it carries out region growth using only the center pixel of selected window. So, the method can reduce remarkably the number of excessive segmented regions of image segmentation based on $H_T$. In order to show the validity of the proposed method, we carried out multiple experiments to compare the proposed method with previous method in same environment and conditions. As the results, the proposed method can reduce the number of segmented regions above 40% and doesn't make any difference in the quality of visual image when we compare with previous method. Especially, when we compare the image united with regions of descending order by size of segmented regions in experimentation with the previous method, even though the united image has regions more than 1,000, we can't recognize what the image means. However, in the proposed method, even though image is united by segmented regions less than 10, we can recognize what the image is. For these reason, we expect that the proposed method will be utilized in various fields, such as the extraction of objects, the retrieval of informations from the image, research for anatomy, biology, image visualization, and animation and so on.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.227-236
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• 2003

Leaks in underground pipelines can cause social, environmental and economical problems. One of relevant countermeasures against leaks is to find and repair of leak points of the pipes. Leak noise is a good source to identify the location of leak points of the pipelines. Although there have been several methods to detect the leak location with leak noise, such as listening rods, hydrophones or ground microphones, they have not been so efficient tools. In this paper, acoustic emission (AE) sensors and accelermeters are used to detect leak locations which could provide all easier and move efficient method. Filtering, signal processing and algorithm of raw input data from sensors for the detection of leak location are described. A 120m-long pipeline system for experiment is installed and the results with the system show that the algorithm with the AE sensors and accelerometers offers accurate pinpointing of leaks. Theoretical analysis of sound wave propagation speed of water in underground pipes, which is critically important in leak locating, is also described.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.99-106
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• 2008

A synthetic aperture radar (SAR) system is of great interest in many fields of civil and military applications because of all-weather and luminance free imaging capability. SAR image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) can be normally estimated by modeling of impulse response function (IRF) which is obtained from various system design parameters such as altitude, operational frequency, PRF, etc. In modeling of IRF, however, background clutter environment surrounding the IRF is generally neglected. In this paper, analysis method for SAR mage quality is proposed in the real background clutter environment. First of all, SAR raw data of a point scatterer is generated based on various system parameters. Secondly, the generated raw data can be focused to ideal IRF by range Doppler algorithm (RDA). Finally, background clutter obtained from image of currently operating SAR system is applied to IRF. In addition, image quality is precisely analyzed by zooming and interpolation method for effective extraction of IRF, and then the effect of proposed methodology is presented with several simulation results under the assumption of estimation error of Doppler rate.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• Mood & Emotion
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• v.16 no.3
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• pp.123-128
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• 2018

Objectives : The fourth revision of Korean Medication Algorithm Project for Bipolar Disorder (KMAP-BP) was performed to provide more proper guidelines for clinicians. In this study, we evaluated treatment strategies of elderly patients with bipolar disorders of KMAP-BP 2018. Methods : Sixty-one psychiatrists of the review committee with vast clinical experiences in treating bipolar disorders, completed the survey. An expert consensus was obtained, on pharmacological treatment strategies for elderly patients with bipolar disorder. The executive committee analyzed results, and discussed the results to produce the final algorithm. Results : In elderly patients with bipolar disorder, first-line treatment option for acute manic episode is monotherapy, with atypical antipsychotics or mood stabilizer, and a combination of mood stabilizer and atypical antipsychotics. First-line treatment option for acute depressive episode, was a combination of mood stabilizer and atypical antipsychotics, monotherapy with atypical antipsychotic or mood stabilizer, and atypical antipsychotics with lamotrigine. Conclusion : In KMAP-BP 2018, the recommendation for treatment option in elderly patients with bipolar disorder, was newly introduced. We expect this algorithm may provide valuable information, and facilitate treatment of elderly patients with bipolar disorder.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.319-324
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• 2019

A depth-encoding detector module with silicon photomultipliers(SiPMs) using two layers of scintillation crystal array was designed, and the position measurement capability was verified using DETECT2000. The depth of interaction of the crystal pixels with the gamma rays was tracked through the image acquired with the combination of surface treatment of the crystal pixels and reflectors. The bottom layer was treated as a reflector except for the optically coupled surfaces, and the crystals of top layer were optically coupled each other except for the outer surfaces so that the light sharing was made easier than the bottom layer. Flood images were obtained through the combination of specular reflectors and random reflectors, grounded and polished surfaces of crystal pixels, and the positions at which layer images were generated were measured and analyzed. The images were reconstructed using the Anger algorithm, whose the SiPM signals were reduced as the 16-channels to 4-channels. In the combination of the grounded surface and all reflectors, the depth positions were discriminated into two layers, whereas it was impossible to separate the two layers in the all polished surface combinations. Therefore, using the combination of grounded surface crystal pixels and reflectors could improve the spatial resolution at the outside of the field of view by measuring the depth position in preclinical positron emission tomography.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.40-50
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• 2012

In this paper we propose the fast CU (Coding Unit) mode decision method. To reduce computational complexity and save encoding time of HEVC, we divided CU, PU (Prediction Unit) and TU (Transform Unit) decision process into two stages. In the first stage, because $2N{\times}2N$ PU mode is mostly selected among $2N{\times}2N$, $N{\times}2N$, $2N{\times}N$, $N{\times}N$ PU modes, proposed algorithm uses only $2N{\times}2N$ PU mode deciding depth of each CU in the LCU (Largest CU). And then, proposed method decides exact PU and TU modes at the depth level which is decided in the first stage. In addition, early skip decision rule is applied to the proposed method to obtain more efficient computational complexity reduction. The proposed method reduces computational complexity of the HEVC encoder by simplifying a CU depth decision method. We could obtain about 50% computational complexity reduction in comparison with HM 3.3 HEVC reference software while bitrate compressed by the proposed algorithm increases only 2%.