• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.415-421
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• 1999

Altman의 연구(1965, 1977)나 Beaver의 연구(1986)와 같은 전통적 예측모형은 분석자의 판단에 따른 예측도가 높은 재무비율을 선정하여 다변량판별분석(MDA： multiple discriminant analysis), 로지스틱회귀분석 등과 같은 통계기법을 주로 이용해 왔으나 1980년 후반부터 인공지능 기법인 귀납적 학습방법, 인공신경망모형, 유전모형 둥이 부실기업예측에 응용되기 시작했다. 최근 연구에서는 인공신경망을 활용한 변수 및 모형개발에 관한 보고가 있다. 그러나 지금까지의 연구가 주로 기업의 재무적 비율지표를 고려한 모형에 치중되었으며 정성적 자료인 비재무지표에 대한 검증과 선정이 자의적으로 이루어져온 경향이었다. 또한 너무 많은 입력변수를 사용할 경우 다중공선성 문제를 유발시킬 위험을 내포하고 있다. 본 연구에서는 부실기업예측모형을 수립하기 위하여 정량적 요인인 재무적 지표변수와 정성적요인인 비재무적 지표변수를 모두 고려하였다. 재무적 지표변수는 상관분석 및 요인분석들을 통하여 유의한 변수들을 도출하였으며 비재무적 지표변수는 조직생태학내에서의 조직군내 조직사멸과 관련된 생태적 과정에 대한 요인들 중 조직군 내적요인으로 조직의 연령, 조직의 규모, 조직의 산업밀도를 도출하여 4개의 실험집단으로 분류하여 비재무적 지표변수를 보완하였다. 인공신경망은 다층퍼셉트론(multi-layer perceptrons)과 역방향 학습(back-propagation )알고리듬으로 입력변수와 출력변수, 그리고 하나의 은닉층을 가지는 3층 퍼셉트론(three layer perceptron)을 사용하였으며 은닉충의 노드(node)수는 3개를 사용하였다. 입력변수로 안정성, 활동성, 수익성, 성장성을 나타내는 재무적 지표변수와 조직규모, 조직연령, 그 조직이 속한 산업의 밀도를 비재무적 지표변수로 산정하여 로지스틱회귀 분석과 인공신경망 기법으로 검증하였다. 로지스틱회귀분석 결과에서는 재무적 지표변수 모형의 전체적 예측적중률이 87.50%인 반면에 재무/비재무적 지표모형은 90.18%로서 비재무적 지표변수 사용에 대한 개선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적 중률을 나타내었다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.

• Journal of the korean academy of Pediatric Dentistry
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• v.43 no.3
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• pp.327-333
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• 2016

Tourette's syndrome is a chronic neuropsychiatric disorder characterized by the presence of vocal and multiple motor tics. Tics are defined as brief, intermittent, repetitive, unpredictable, purposeless, and stereotyped movements or sounds. Some patients experience physical pain from intense and complex tics. In addition, motor tics can result in self-injury which is a common feature of Tourette's syndrome. A 9-year-old boy was referred by the department of neuropsychiatry because of a severe tongue laceration. His parents reported that he had been biting his tongue irregularly for 2 months before referral and suffered from an intense burning sensation. The repeated biting resulted in ulcers on the tongue, which quickly worsened and led to progressive difficulty chewing and swallowing food. We offered to give him a two-piece removable appliance to limit tongue biting; it was made of soft silicone and fitted to both the maxillary and mandibular arches. As we emphasized that the device could help alleviate his pain, he agreed to accept it and adapted well. Just 3 weeks later, his tongue lesions had healed significantly.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.1-12
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• 1998

In this paper, a design and implementation of VHDL-to-C mapping in the VHDL compiler back-end is described. The analyzed data in an intermediate format(IF), produced by the compiler front-end, is transformed into a C-code model of VHDL semantics by the VHDL-to-C mapper. The C-code model for VHDL semantics is based on a functional template, including declaration, elaboration, initialization and execution parts. The mapping is carried out by utilizing C mapping templates of 129 types classified by mapping units and functional semantics, and iterative algorithms, which are combined with terminal information, to produce C codes. In order to generate the C program, the C codes are output to the functional template either directly or by combining the higher mapping result with intermediate mapping codes in the data queue. In experiments, it is shown that the VHDL-to-C mapper could completely deal with the VHDL analyzed programs from the compiler front-end, which deal with about 96% of major VHDL syntactic programs in the Validation Suite. As for the performance, it is found that the code size of VHDL-to-C is less than that of interpreter and worse than direct code compiler of which generated code is increased more rapidly with the size of VHDL design, and that the VHDL-to-C timing overhead is needed to be improved by the optimized implementation of mapping mechanism.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.131-143
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• 2011

Previous alerting service based on LBS was caused severe overload problem of server by using the method to confirm the location of each moving object on server. In this paper, by loading an App on smart moving object, we proposed a novel algorithm named ADAS(Active Disaster Alert Service) for accessing to the server site with oneself location information as needed and implemented the disaster alerting service system with visualization for user. In the proposed method, running App access to the server periodically with the present location coordinate gained from GPS module or network module and the ID of moving object. Then, the server compare the present location coordinate of moving object and the coordinates of disasters registered in DIDB and transmit the n NDIs existed in near distance orderly from the coordinate of present moving object to the client. The App compares the coordinate of present location for moving object and the coordinates of NDI is transmitted from server by real time and executes the service with classifying levels of alert into three steps such as danger, carefulness and safety. And new NDIs are gained by accessing DIDB on Server periodically during running App. Therefore, this will be become a novel method for reducing fundamentally the server overload problem in comparison with previous alerting service that the career of moving object is managed on server.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of Chest Surgery
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• v.32 no.4
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• pp.353-357
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• 1999

Background: Mitral valve replacement(MVR) with chordal preservation in patients with mitral vlavular disease has been proven to be beneficial for left ventricular function and for reduction of postoperative complication. Material and Method: From January 1995 to July 1996, the early postoperative results of mitral valve replacement were compared between 20 patients who underwent chordae resection(classic MVR group) and 10 patients who underwent chordae preservation(preservation MVR group) in the Department of Thoracic and Cardiovascular Surgery, Chunbuk National University Hospital. Result: There was no significant difference between the two groups in age, sex, NYHA functional class, cardiothoracic ratio, echocardiographic finding, cardiopulmonary bypass time and aortic cross clamping time. The difference between preoperative and postoperative cardiothoracic ratio after 3 months was not statistically significant. At echocardiographic left ventricular evaluation, ejection fraction and fractional shortening decreased slightly in the preservation group then preoperative value (p=0.47, p=0.12), however, decreased significantly in the classic MVR group(p=0.03, p=0.04), and were statistically significant between the two groups(p=0.03, p=0.02). Conclusion: We conclude that MVR with chorda preservation seems to have a beneficial effect on postoperative left ventricular performance in mitral valve disease than the classic MVR.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.14 no.1
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• pp.16-25
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• 2003

Background and Objectives : Electroglottography(EGG) is a non-invasive method of monitoring the vocal cord vibration by measuring the variation of physiological impedance across the vocal folds through the neck skin. It reveals especially the vocal fold contact area and is widely used for basic laryngeal researches, voice analysis and synthesis. The purpose of this study is to investigate the effectiveness of EGG parameters in differential diagnosis of laryngeal cancer. Materials and Methods : The author investigated 10 laryngeal cancer and 25 benign laryngeal disease patients who visited at the Department of Otolaryngology, Pusan National University Hospital. The EGG equipment was devised in the author's Department. Among various parameters of EGG, closed quotient(CQ), speed quotient(SQ), speed index(SI), Jitter, Shimmer, Fo were determined by an analysis program made with MATLAB 6.5$^{\circledR}$(Mathwork, Inc.). In order to differentiate various laryngeal diseases from pathologic voice signals, the author has used the electroglottographic parameters using the neural network of multilayer perceptron structure. Results : SQ, SI, Jitter and Shimmer values except those of CQ and Fo showed remarkable differences between benign and malignant laryngeal disease groups. From the artificial neural network, the percentage of differentiating the laryngeal cancer was over 80% in SQ, SI, Jitter, Shimmer except for CQ and Fo. These results indicated that it is possible to discriminate the benign and malignant laryngeal diseases by EGG parameters using the artificial neural network. Conclusion : If parameters of EGG which can reveal for the pathology of laryngeal diseases are additionally developed and the current classification algorithm is improved, the discrimination of laryngeal cancer will become much more accurate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2460-2470
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• 2009

In this study, the parameter extraction for evaluation of the anesthesia depth in each anesthesia stages was conducted. An object of the this experiment study has studied 5 adult patients (mean $\pm$ SD age:$42{\pm}9.13$), ASA classification I and II, undergoing surgery of obstetrics and gynecology. Anaesthesia was maintained with Enflurane. HRV signal was created by R-peak detection algorithm form ECG signal. The HRV data were preprocessing algorithm. It has tried find out the anesthesia parameter which responds the anesthesia events and shows objective anesthesia depth according to anesthesia stage including pre-anesthesia, induction, maintenance, awake and post-anesthesia. In this study, proposed algorithm to analysis the HRV(heart rate variability) signal using wavelet transform in anesthesia stage. Three sorts of wavelet functions applied to PSD. In the result, all of the results were showed similarly. But experiment results of Daubeches 10 is better. Therefore, this parameter is the best parameter in the evaluation of anesthesia stage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3C
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• pp.141-148
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• 2010

Electrical noises like self potential, burst noises and 60-Hz electrical noises are one of the causes to reduce reliability of electrical resistivity survey. Even the PDC-R (Pseudo DC resisitivity) technique, recently developed, is suffering from the problem of low reliability due to electrical noises. That is, both DC-based and AC-based resistivity technique is subject to reliability problem due to electrical noises embedded in urban geotechnical sites. In this research, a new technique to enhance reliability of the PDC-R technique by minimizing influence of electrical noises was proposed. In addition, an automated procedure was also proposed to facilitate data analysis and interpretation of PDC-R measurements. The proposed technique is composed of two steps: 1. to extract information only related with the input current by means of multiple-filter technique, and 2. to undertake a task to sort out signal information only to show stable and reliable characteristics. This automated procedure was verified by a synthetic harmonic wave including DC shift, burst random noises and 60-Hz electrical noises. Also the procedure was applied to site investigation at urban areas for proving its feasibility and accuracy.