• Progress in Medical Physics
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• v.21 no.1
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• pp.22-28
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• 2010

To evaluate the potential value of $^1H$ Magnetic resonance spectroscopy (MRS) for detecting and characterizing invasive ductal carcinoma of breast. We conducted $^1H$ Magnetic resonance spectroscopy (MRS), using a 3.0T MR scanner, on 40 patients who were histologically diagnosed to have invasive ductal carcinoma (IDC); tumor areas of the patients were designated as experimental samples, and non-tumor areas as control samples. The peak at 3.2 ppm is characteristically intense and observed in 34 cases of the total 40 invasive ductal carcinoma (sensitivity 86.2%; specificity 100%; positive predictive value 100%; negative predictive value 60%). In constrast peak at 1.3 ppm is characteristically intense and observed in normal breast (sensitivity 86.2%; specificity 100%; positive predictive value 100%; negative predictive value 60%). The study shows that $^1H$ MRS can effectively discriminate invasive ductal carcinoma from normal breast in most cases. It also demonstrates the feasibility of localized in vivo $^1H$ MRS technique as a new diagnostic modality in the detection of breast tumor.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.111-120
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• 2010

The policy which encourages people to use cars on the road has been based on the growth of economy in Korea. It has also caused the concentration and overcrowding in Seoul. That's because the increasing number of people possessing cars interconnects with the urban development. The transportation is a derived demand; so many scholars have recognized the importance of understanding the relationship between urban land use and transport. Considering such importance, this study theoretically compared the developed urban land use-transportation models each other and outlined the particular models briefly. Models were categorized by 2 types; optimizing model and predictive mode. Predictive model is also defined by static model, entropy based model, spatial-economic model, and activity model. After studying models, we investigated other major cities in America. This process is the pre-step for transport policy assessment. Through careful literature review, we can finally develop the integrated land-use transportation model in Seoul metropolitan area. In addition, we will be able to deal the changes of traffic demand pattern under U-Society. Consequently, the results of this study can be applied to ITS projects in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.35-54
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• 2009

The recent economic crisis not only reduces the profit of department stores but also incurs the significance losses caused by the increasing late-payment rate of credit cards. Under this pressure, the scope of credit prediction needs to be broadened from the simple prediction of whether this customer has a good credit or not to the accurate prediction of how much profit can be gained from this customer. This study classifies the delinquent customers of credit card in a Korean department store into homogeneous clusters. Using this information, this study analyzes the repayment patterns for each cluster and develops the credit prediction system to manage the delinquent customers. The model presented by this study uses Kohonen network, which is one of artificial neural networks of data mining technique, to cluster the credit delinquent customers into clusters. Cox proportional hazard model is also used, which is one of survival analysis used in medical statistics, to analyze the repayment patterns of the delinquent customers in each cluster. The presented model estimates the repayment period of delinquent customers for each cluster and introduces the influencing variables on the repayment pattern prediction. Although there are some differences among clusters, the variables about the purchasing frequency in a month and the average number of installment repayment are the most predictive variables for the repayment pattern. The accuracy of the presented system leaches 97.5%.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.4
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• pp.54-61
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• 2013

UV-IR camera is being used for predictive maintenance of high voltage equipment together with measurement of temperature on localized heat and corona discharge. This paper was suggested the judgement method that is the discharge count, UV image pattern and discharge matching rate to apply the UV-IR camera on power facility. The discharge count method is counted by UV image pixel value. the UV image pattern method is determined by the UV image shape using neural network algorithm method, separated by Sunflower, Jellyfish, Ameba. The UV discharge matching is compare the breakdown the UV image size and measuring UV image size according to distance.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.47-50
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• 1998

본 논문은 자동차의 편의성 및 안전성의 동시 확보를 위하여, 보조적 스위치의 조작없이 상시 음성의 입,출력이 가능하도록 하며, band pass filter를 이용하여 잡음환경에서 자동으로 정확하게 음성구간 검출(End Point Detection)을 하게 하였다. Reference Pattern은 Dynamic Multi-Section(DMS)[1] 모델을 사용하였고 차량의 속도에 따라 자동으로 잡음환경에 강인한 모델을 선택하도록 하였으며, 음성의 특징 파라미터와 인식 알고리즘은 Perceptual Linear Predictive(PLP) 13차와 One Stage Dynamic Programming(OSDP)를 사용하였다. 주행중인 자동차 환경(30~70km/h)에서 자주 사용되는 차량제어 명령 33개에 대하여 화자독립 92.98%, 화자종속 94.44% 인식율을 구하였다. 또한 주행중인 차량에서 카폰, 핸드폰 사용으로 인한 사고를 줄이기 위하여 음성으로 전화를 걸 수 있도록 하는 Voice Dialing 기능도 구현하였다.

• International Journal of Safety
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• v.11 no.2
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• pp.22-25
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• 2012

This paper deals with the problem of fault diagnosis for identifying a single fault when the number of assumed faults is larger than that of predictive variables. Principal component analysis (PCA) is employed to isolate and identify a single fault. PCA is a method to extract important information as reducing the number of large dimension in a process. The patterns of all assumed faults can be recognized by PCA and these can be employed whether a new fault is one of predefined faults or not. Through PCA, empirical models for analyzing patterns can be trained. When a single fault occurs, the pattern generated by PCA can be obtained and this is used to identify a fault. The performance of the proposed approach is illustrated in the actuator benchmark problem.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.469-472
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• 1988

This paper deals with signal processing and pattern recognition for the pulsed doppler radar. In order to identify the class of moving targets detected by radar, linear predictive analysis is utilized to extract reflection coefficients of each radar signal as features, and Bayes decision theory is applied to classify them.

• Proceedings of the KIPE Conference
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• 2014.11a
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• pp.121-122
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• 2014

멀티 레벨 인버터는 높은 출력 전압을 갖으며, 낮은 THD(Total harmonic distortion)를 요구하는 시스템에 적합하다. 그 중 cascaded H-brige 멀티레벨 인버터는 H-bridge 셀별 관리가 쉽고, 레벨 수를 증가시키기 쉽다는 장점 때문에 많이 이용되어 왔다. 본 논문에서는 cascaded H-bridge 인버터의 기존 PI (proportional integral) 제어 기반 PWM (pulse width modulation)기법의 스위칭 패턴과 모델 예측 제어의 스위칭 패턴을 비교하고 모델예측 제어 시 셀 별 스위칭 패턴 균형을 위한 방법을 제안한다.

• ETRI Journal
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• v.26 no.4
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• pp.297-306
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• 2004

A plasma is a collection of charged particles and on average is electrically neutral. In fabricating integrated circuits, plasma etching is a key means to transfer a photoresist pattern into an underlayer material. To construct a predictive model of plasma-etching processes, a polynomial neural network (PNN) is applied. This process was characterized by a full factorial experiment, and two attributes modeled are its etch rate and DC bias. According to the number of input variables and type of polynomials to each node, the prediction performance of the PNN was optimized. The various performances of the PNN in diverse environments were compared to three types of statistical regression models and the adaptive network fuzzy inference system (ANFIS). As the demonstrated high-prediction ability in the simulation results shows, the PNN is efficient and much more accurate from the point of view of approximation and prediction abilities.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.147.5-147
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• 2001

This paper describes a gait algorithm and a velocity limitation method for a Leg-Wheel Robot. The gait algorithm enables the robot to preserve continuous locomotion even if the velocity command varies extensively. The velocity limitation method restricts the commanded velocity when it exceeds the mechanical limitation of the robot. Combined use of the velocity limitation method with the gait algorithm ensures the continuity of locomotion, and makes the gait pattern efficient with a long step length and low frequency of leg phase change. These methods can be applied to locomotion on unexplored rough terrain even if the range of roughness is unknown.