• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.169-178
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• 2022

Morphemes are most primitive units in a language that lose their original meaning when segmented into smaller parts. In Korean, a sentence is a sequence of eojeols (words) separated by spaces. Each eojeol comprises one or more morphemes. Korean morphological analysis (KMA) is to divide eojeols in a given Korean sentence into morpheme units. It also includes assigning appropriate part-of-speech(POS) tags to the resulting morphemes. KMA is one of the most important tasks in Korean natural language processing (NLP). Improving the performance of KMA is closely related to increasing performance of Korean NLP tasks. Recent research on KMA has begun to adopt the approach of machine translation (MT) models. MT is to convert a sequence (sentence) of units of one domain into a sequence (sentence) of units of another domain. Neural machine translation (NMT) stands for the approaches of MT that exploit neural network models. From a perspective of MT, KMA is to transform an input sequence of units belonging to the eojeol domain into a sequence of units in the morpheme domain. In this paper, we propose a deep learning model for KMA. The backbone of our model is based on the BERT-fused model which was shown to achieve high performance on NMT. The BERT-fused model utilizes Transformer, a representative model employed by NMT, and BERT which is a language representation model that has enabled a significant advance in NLP. The experimental results show that our model achieves 98.24 F1-Score.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1165-1172
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• 2006

The rapid progress of the software has enabled individuals to copy and remark digital contents, which was only done by professionals. As a solution for the problems, contents producer needs to have certification and inspection of its contents and hold the proprietary right. A fragile watermarking method is able to detect the distortion and damage of watermarked image, but the watermark is also fragile on standardized image compression. That is the problem of fragile watermarking technique. We propose semi-fragile watermarking technique that is robust in the image processing such as JPEG compression used on computer, but it is fragile on the addition of noise and other attacks. In the proposed method, we can generate the watermarks of an image from the relationship between two block coefficients, also the generated watermark is inserted into insensible part of HVS(Human Visual System) after processing DCT(Discrete Cosine Transform) and using quantization. As a result, on the spatial domain, high detection of distortion has been possible even in slight changes, and could detect the corrupted blocks on image. Therefore, it is simple to judge the pixels at which some location has been changed in the space.

• Journal of Sensor Science and Technology
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• v.29 no.4
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• pp.249-254
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• 2020

It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.157-162
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• 2010

In this paper we propose a fractal analysis based on the discrete wavelet transform. It is well known that Fourier Transform is widely used for frequency analysis of random signal. However, the frequency domain is not used for expressing the sudden signal change and non-stationary signal at the time-axis by this method. Maximum value in the wavelet modules can be expressed by the Lipschitz exponent, which is useful to represent the characteristics of signal or the edge of an image. It is possible to reconstruct the original image only by using the few maximum points. The v possible image It iusing oil was acquired to interpret the maximum value. ufter that, it was applied to the v possible image of a ship model. In addition, the fractal dimens by by the conlapse process of the sediment particle was examined. In this paper, the fractal dimens by has been obtained by the maximum value and the experiment obtained from the visualized image also acquired the same result as existing methods.

• Journal of KIISE:Software and Applications
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• v.28 no.2
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• pp.141-148
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• 2001

DCT(Discrete Cosine Transform) 변환은 MPEG과 JPEG 표준에 의하여 영상이나 비디오 영상을 압축하는데 사용되어져 왔다. 본 연구에서는 이상적인 경계가 관련된 특성을 유도하고, 실시간 처리를 위하여 모델에 바탕을 둔 DCT 영역에서의 불연속 경계 평가 방법을 제안한다. 이 방법은 방향 검증과 위치 정렬 등의 평가로 구성된다. 두 가지의 평가 방법에 의하여 경계의 다양한 방향과위치를 알 수 있으며, DCT 계수들을 표준화된 형식으로 정렬시킬 수 있고, 표준화된 DCT 계수에서 이상적인 계단 경계의 특성과 비교하여 경계의 크기를 산출할 수 있다. DCT 계수가 8x8의 블록 단위로 이루어져 있어 경계의 표현이 조밀하지는 않지만 처리 시간이 빠르고 잡음에 강한 특성을 가지고 있어 다양한 실시간 응용분야에 사용될 수 있을 것이다.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.157-160
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• 1996

Physical systems axe generally continuous-time in nature. However as the data measured from these systems is generally in the form of discrete samples, and most modern signal processing is performed in the discrete-time domain, discrete-time models are employed. This paper describes methods for estimating the coefficients of continuous-time system within a closed loop control system. The method employs a recursive estimation algorithm to identify the coefficients of a discrete-time bilinear-operator model. The coefficients of the discrete-time bilinear-operator model closely approximate those of the corresponding continuous-time Laplace transform transfer function.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.328-331
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• 2000

In this paper , we propose a texture feature extraction method of reduce the massive computational time on extracting texture, features of large sized medical such as MRI, CT-scan , and an index structure, called GLTFT, to speed up the retrieval performance. For these, the original image is transformed into a compressed image by Wavelet transform , and textural features such as contrast, energy, entropy, and homogeneity of the compressed image is extracted by using GLCM(Gray Level Co-occurrence Metrix) . The proposed index structure is organized by using the textural features. The processing in compressed domain can give the solution of storage space and the reduction of computational time of feature extracting . And , by GLTFT index structure, image retrieval performance can be expected to be improved by reducing the retrieval range . Our experiment on 270 MRIs as image database shows that shows that such expectation can be got.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3E
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• pp.133-140
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• 2003

A time series simulation is presented by a ray approach for the simulating the received waveform of a broadband acoustical signals interacting with the ocean boundaries. The environment is assumed to be horizontally stratified, and the seafloor is described in terms of homogeneous fluid half-space. The ray approach includes the effects of reflection from the air-water, water-sediment interface and phase shifts due to boundaries interaction. To generate time series, we assume that the acoustic energy propagates from source to receiver along eigenrays and represent the action of the bottom on the incident wave by a linear filter and characterized in the frequency domain by the transfer function. As example application, the time series for an explosive source in a shallow water environment is calculated and analyzed in terms of acoustical process. good agreement with measured time series is demonstrated.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.237-240
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• 2004

In this study, the digital image processing with image enhancement based on homomorphic filtering was performed using geophysical imaging data such as gravity, magnetic data and sub-scenes of satellite images such as LANDSAT, IKONOS, and KOMPSAT. Windows application program for executing homomorphic filtering was designed and newly implemented. In general, homomorphic filtering is technique that is based on Fourier transform, which enhances the contrast of image by removing the low frequencies and amplifying the high frequencies in frequency domain. We can enhance the image selectively using homomorphic filtering as compared with the existing method, which enhance the image totally. Through several experiment using remotely sensed imagery and geophysical image with this program, it is concluded that homomorphic filtering is more effective to reveal distinct characteristics for some complicated and multi-associated features on image data.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.871-880
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• 2002

In this paper, I proposed the adaptive watermarking based on the discrete wavelet transform for the very robust watermarking against intentional distortion which attacks on image. A watermark is an binary image such as document(sign), and such watermark image is embedded in the LH and HL band of wavelet transformed domain for copyright protection of image data. To evaluate robustness of the proposed method, we applied some basic algorithm of image processing such as brightening, darkening, sharpening, blurring, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method has the good image quality and the high perceptibility of watermark. It was demonstrated by experiments that the proposed algorithm can provide an excellent protection under various attacks.