• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.425-426
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• 2021

최근 청소년들의 무면허 운전으로 인한 인재 사고가 빈번하게 발생하고 있다. 무면허 주행은 일부 청소년들의 호기심과 도전의 온상이 되고 있으며 이를 방지하기 위해 가정에서 스마트키를 관리하는 것에도 한계가 있다. 따라서 본 논문에서는 안면인식 알고리즘을 이용하여 운전석에 앉은 운전자의 얼굴을 사전에 저장된 정보와 비교하고 등록된 운전자임을 판단하여 시동을 제어하는 시스템을 설계하였다. 등록된 운전자 인증이 성공 시 매칭 정확도와 Unlock 메시지를 라즈베리파이에 연결된 LCD에 출력하며 미등록자인 경우, Lock 메시지를 출력한다.

• 한국전자통신학회논문지
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• 제19권1호
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• pp.327-334
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• 2024

본 논문에서는 라즈베리파이 기반으로 손바닥 정맥혈관 이미지를 획득하기 위하여 950nm파장을 가지는 근적외선 LED 광원 장치와 손금을 획득하기 위한 백색 LED 광원 장치를 가지는 시스템을 개발하였다. 또한 획득한 정맥 및 손금 이미지에 대하여 영상 전처리 과정(흑백화, 평활화, 이진화, 블러링, 세선화 등)을 통하여 정맥과 손금이 혼합된 위조 방지 및 보안이 강화된 고유 패턴이 추출 가능한 영상처리 기술을 구현하여 보안성이 강화된 시스템에서 활용할 수 있는 원천 기술을 확보하였다.

• 제어로봇시스템학회논문지
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• 제15권3호
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• pp.330-336
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• 2009

This paper studies on the new control algorithm for the mass-flow stabilization in strip head part of a hot strip mill. A new strip tension model in the strip head part is derived using the current deviation of two neighboring stands. The current deviation means a difference between a measured current and a lock-on current, where the lock-on current is set up when a strip tension or a looper angle reaches each target value or time is about 0.4sec, respectively. On the basis of the tension calculation model, a mill velocity of a backward stand is controlled to stabilize a strip mass-flow by PI control algorithm. Therefore, the mass-flow control for strip head part is executed from a metal-in time into a foreward stand till the looper works normally. It is known by the results of a computer simulation and an experiment that the proposed control algorithm is very effective in stabilizing the mass flow of the strip head part.

• 전력전자학회논문지
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• 제20권3호
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• pp.201-208
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• 2015

The effects of dead-time and offset error, which cause output current distortion in single-phase grid-connected inverters are investigated this paper. Offset error is typically generated by measuring phase current, including the voltage unbalance of analog devices and non-ideal characteristics in current measurement paths. Dead-time inevitably occurs during generation of the gate signal for controlling power semiconductor switches. Hence, the performance of the grid-connected inverter is significantly degraded because of the current ripples. The current and voltage, including ripple components on the synchronous reference frame and stationary reference frame, are analyzed in detail. An algorithm, which has the proportional resonant controller, is also proposed to reduce current ripple components in the synchronous PI current regulator. As a result, computational complexity of the proposed algorithm is greatly simplified, and the magnitude of the current ripples is significantly decreased. The simulation and experimental results are presented to verify the usefulness of the proposed current ripple reduction algorithm.

• 전력전자학회논문지
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• 제23권1호
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• pp.66-71
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• 2018

We propose an online parameter estimation method for surface-mounted permanent-magnet synchronous motor (SPMSM) using an affine projection algorithm (APA). The proposed method estimates parameters with two APAs based on the discrete-time model equation of SPMSM during motor operation. The first APA is designed to estimate inductance, and the second APA is designed to estimate resistance and flux linkage. However, in case when the d-axis current is controlled to 0A, the second APA cannot estimate resistance and flux linkage simultaneously because the matrix rank in APA becomes deficient. To overcome this problem, we temporarily inject a negative reference current input to the d-axis control loop, and the matrix in the APA then becomes full rank, which enables the simultaneous estimation of resistance and flux linkage. The proposed method is verified by PSIM simulation and an actual experiment, and the results reveal that SPMSM parameters can be estimated online during motor operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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• pp.4043-4060
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• 2017

Network Intrusion Detection (NID), an important topic in the field of information security, can be viewed as a pattern recognition problem. The existing pattern recognition methods can achieve a good performance when the number of training samples is large enough. However, modern network attacks are diverse and constantly updated, and the training samples have much smaller size. Furthermore, to improve the learning ability of SVM, the research of kernel functions mainly focus on the selection, construction and improvement of kernel functions. Nonetheless, in practice, there are no theories to solve the problem of the construction of kernel functions perfectly. In this paper, we effectively integrate the advantages of the radial basis function kernel and the polynomial kernel on the notion of the game theory and propose a novel kernel SVM algorithm with game theory for NID, called GTNID-SVM. The basic idea is to exploit the game theory in NID to get a SVM classifier with better learning ability and generalization performance. To the best of our knowledge, GTNID-SVM is the first algorithm that studies ensemble kernel function with game theory in NID. We conduct empirical studies on the DARPA dataset, and the results demonstrate that the proposed approach is feasible and more effective.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1396-1406
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• 2018

Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

• Psychiatry investigation
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• 제15권11호
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• pp.1030-1036
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• 2018

Objective In this study, we aimed to develop a model predicting individuals with suicide ideation within a general population using a machine learning algorithm. Methods Among 35,116 individuals aged over 19 years from the Korea National Health & Nutrition Examination Survey, we selected 11,628 individuals via random down-sampling. This included 5,814 suicide ideators and the same number of non-suicide ideators. We randomly assigned the subjects to a training set (n=10,466) and a test set (n=1,162). In the training set, a random forest model was trained with 15 features selected with recursive feature elimination via 10-fold cross validation. Subsequently, the fitted model was used to predict suicide ideators in the test set and among the total of 35,116 subjects. All analyses were conducted in R. Results The prediction model achieved a good performance [area under receiver operating characteristic curve (AUC)=0.85] in the test set and predicted suicide ideators among the total samples with an accuracy of 0.821, sensitivity of 0.836, and specificity of 0.807. Conclusion This study shows the possibility that a machine learning approach can enable screening for suicide risk in the general population. Further work is warranted to increase the accuracy of prediction.

• Investigative Magnetic Resonance Imaging
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• 제2권1호
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• pp.89-95
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• 1998

목적 : 인($^{31}P$) 자기공명분광법을 사용하여 사립체 근병(mitochondria myopathy) 환자의 대퇴부 근조직의 대사물질의 변화를 정상인과 비교조사하였다. 대상 및 방법 : 사립체 근병환자 10명과 정상인 10명을 대상으로 1.5T MRI/MRS 장비를 사용하여 인($^{31}P$) 자기공명분광법을 적용하였다. 오른쪽 대퇴부위의 근조직에 $4{\;}{\times}{\;}4{\;}{\times}4{\;}cm^{3}$ 의 관심부위 (volume of interest ; VOI)를 선정하여 image selected in vivo spectroscopy (ISIS)를 저용하였다. 인대사불질의 정\ulcorner분석은 Marquart algorithm을 사용하였다. 결과 : 사립체 근병환자의 특징은 정상인과 비교하여 Pe/PCr 대사비율이 상당히 증가하고 (P=0.003), ATP/PCr 대사비율은 상당히 감소하였다(p=0.004). 특히 ATP 중 ${\beta}-ATP/PCr$ 비율의 변화가 가장 심하게 나타났다. 환자군과 정상군의 pH 차이는 통계학적으로 큰 의의는 없었다. 결론 : 인($^{31}P$) 자기 공명분광법은 사립체 근병환자의 대퇴부 근조직의 ATP/PCr 과 Pi/PCr 대사비율을 토대로 유용한 임상 평가 자료를 제공하고, 따라서 근대사물질의 질병을 이해하는데 도움을 줄 것으로 사료된다.

• 한국컴퓨터정보학회논문지
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• 제20권4호
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• pp.95-102
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• 2015

본 논문은 회로 최소화 문제를 간단하게 풀 수 있는 알고리즘을 제안하였다. 회로 최소화 문제는 수기식 방법인 카르노 맵과 전산화가 가능한 휴리스틱 방법인 Quine-McCluskey 알고리즘이 있다. 그러나 Quine-McCluskey 알고리즘은 변수 개수 n이 증가하면 $3^n/n$의 메모리와 수행횟수가 요구되는 단점을 갖고 있다. 제안된 방법은 빈도수에 기반하여 내포 항 표를 이용하여 주어진 부울 함수의 최소 항을 포함하는 주 내포 항을 빠르게 추출하는 방법을 적용하였다. 추출된 주 내포 항들 중에서 중복 선택된 여분의 주 내포 항을 빈도수를 적용하여 제거하는 방법을 제안하였다. 제안된 알고리즘은 비록 변수 개수 n이 증가하여도 다항시간으로 회로를 최소화시킬 수 있는 해를 구할수 있는 장점을 갖고 있다. 제안된 알고리즘을 3-변수와 4-변수의 다양한 사례들에 적용한 결과 해를 빠르고 정확하게 구할 수 있었다.