• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.903-909
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• 2019

Periodontal disease is observed in many adult persons. However we has not clear know the molecular mechanism and how to treat the disease at the molecular levels. Here, we investigated the molecular differences between periodontal disease and normal controls using gene expression data. In particular, we checked whether the periodontal disease and normal tissues would be classified by machine learning algorithms using gene expression data. Moreover, we revealed the differentially expression genes and their function. As a result, we revealed that the periodontal disease and normal control samples were clearly clustered. In addition, by applying several classification algorithms, such as decision trees, random forests, support vector machines, the two samples were classified well with high accuracy, sensitivity and specificity, even though the dataset was imbalanced. Finally, we found that the genes which were related to inflammation and immune response, were usually have distinct patterns between the two classes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.127-132
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• 2019

Influenza is an infectious disease caused by an influenza virus with symptoms of high fever and headache. Since influenza especially mutates into multiple subtypes in the carrier's body, it is a serious threat for mankind such as Spanish influenza. The treatment of influenza infection mandates the use of antiviral drugs through rapid diagnostic test. Generally, immunochromatography-based rapid influenza diagnostic tests are used for rapid diagnosis in an emergency. In this paper, we propose an influenza analysis algorithm based on image processing to examine a large number of patients suspected of being infected with influenza. Also, we propose a robust influenza analysis algorithm based on the joint cumulative mass function under varying radiometric conditions such as illuminant and exposure differences. Simulation results show that the proposed algorithm significantly reduces the error of influenza diagnosis under different radiometric conditions.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.62-62
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• 2003

Landsat TM 영상을 이용, 명암차가 높은 산악 지역에 적용해왔던 알고리즘을 개선하여 비교적 명암차가 낮고 넓게 분포하는 충적층 지역의 선구조를 추출하는 알고리즘을 개발하였다. 수치지형모델(OEM)에 대하여 Local Enhancement 를 이용해서 평탄한 지역을 선정하여 이로부터 충적층을 추출하였다. Zevenbergen & Thorno's Method를 3×3 moving windowing을 통해서 최대 경사방향과 경사를 구해서 충적층을 지나는 선구조 요소를 추출하고 다시 Hough 변환을 이용해서 1차 선구조를 추출하였다 이를 이용하여 충적층의 직각방향의 지형단면의 경사를 유추해서 spline 보간법을 이용해 단면의 최저점을 구하고 이 구해진 점들을 다시 Hough 변환을 이용해서 최종 선구조를 추출하였다. 본 연구에서 사용한 알고리즘은 기존 알고리즘에서 사용된 소창문보다 훨씬 큰 충적층이 분포하는 지역의 지형 경사가 수렴하는 부분에 선구조가 뚜렷이 나타남을 볼 수 있다. 최대경사방향과 경사를 구해서 얻어진 1 차선구조와 최종 선구조에서 선구조 방향이 다소 차이를 보인다. 1 차 선구조의 수직방향 지형단면의 자료를 이용함에 있어, 지형 단면의 시작정과 끝지점을 임의적으로 결정하는 것이 아니라, 충적층을 가로질러 최고점까지 또는 다음 충적층이 나을 때까지의 자료를 이용해서 보간법을 사용하였고, 충적층의 넓이에 따라 보간할 자료량의 차이에 의한 오차가 발생할 수 있다. 넓은 충적층에서 선구조가 잘 추출되는 반면에 좁은 충적층이 분포하거나 계곡에 해당하는 지역에l서는 경사수렴부와 일치하지 않는 선구조가 추출되었다. 이는 향후 계속적으로 연구해서 보완되어야 할 것으로 사료된다.페클 잡영 제거 정도에 있어 다른 필터들과 큰 차이가 없지만 경계선보존지수는 다른 필터들에 비하여 가장 우수함을 확인할 수 있었다.rbon 탐식효율을 조사한 결과 B, D 및 E 분획에서 유의적인 효과를 나타내었다. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. On the basi

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.5
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• pp.269-276
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• 2014

In recent, autonomous navigation techniques to avoid obstacles have been studied by using unmanned aircraft vehicles(UAVs) since the increment of UAV's interest and utilization. Particularly, autonomous navigation based UAVs are utilized in several areas such as military, police, media, and so on. However, there are still some problems to avoid obstacle when UVAs perform autonomous navigation. For instance, the UAV can not forward in the corner of corridors even though it utilizes the improved vanish point algorithm that makes an autonomous navigation system. Therefore, in this paper, we propose an obstacle avoidance technique based on immune algorithm for autonomous navigation of Quadrotor. The proposed algorithm is consisted of two steps such as 1) single color discrimination and 2) multiple color discrimination. According to the result of experiments, we can solve the previous problem of the improved vanish point algorithm and improve the performance of autonomous navigation of Quadrotor.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.827-836
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• 2001

The PID controller has been widely applied to the most control systems because of its simple structure and east designing. One of the important points to design the PID control system is to tune the approximate control parameters for the given target system. To find the PID parameters using Ziegler Nichols(ZN) method needs a lot of experience and experiments to ensure the optimal performance. In this paper, CMIA(Cell Mediated Immune Algorithm) controller is proposed to drive the autonomous guided vehicle (AGV) more effectively. The proposed controller is based on specific immune responses of the biological immune system which is the cell mediated immunity. To verify the performance of the proposed CMIA controller, some experiments for the control of steering and speed of that AGV are performed. The tracking error of the AGV is mainly investigated for this purpose. As a result, the capability of realization and reliableness are proved by comparing the response characteristics of the proposed CMIA controllers with those of the conventional PID and NNPID(Neural Network PID) controller.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.169-173
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• 2021

Currently, safety accidents in hospitals are steadily occurring. In particular, safety accidents of elderly patients with weak immunity, such as nursing hospitals, continue to occur, and countermeasures are needed. Most accidents are caused by patient movement. As a method of reducing safety accidents by analyzing and recognizing the sound of the inpatient room according to the movement of the patient, this paper classifies the sound pattern for sound recognition in the hospital inpatient room using DTW (Dynamic Time Warping), an algorithm applicable to time-series pattern recognition. It was analyzed by applying it to the inpatient room environment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• Journal of Veterinary Clinics
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• v.24 no.2
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• pp.77-81
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• 2007

Diagnostic performance of polymerase chain reaction (PCR) for detecting Dirofilaria immitis in dogs was evaluated when no gold standard test was employed. An enzyme-linked immunosorbent assay test kit (SnapTM, IDEXX, USA) with unknown parameters was also employed. The sensitivity and specificity of the PCR from two-population model were estimated by using both maximum likelihood using expectation-maximization (EM) algorithm and Bayesian method, assuming conditional independence between the two tests. A total of 266 samples, 133 samples in each trial, were randomly retrieved from the heartworm database records during the year 2002-2004 in a university animal hospital. These data originated from the test results of military dogs which were brought for routine medical check-up or testing for heartworm infection. When combined 2 trials, sensitivity and specificity of the PCR was 96.4-96.7% and 97.6-98.8% in EM and 94.4-94.8% and 97.1-98% in Bayesian. There were no statistical differences between estimates. This finding indicates that the PCR assay could be useful screening tool for detecting heartworm antigen in dogs. This study was provided further evidences that Bayesian approach is an alternative approach to draw better inference about the performance of a new diagnostic test in case when either gold test is not available.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.388-393
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• 2003

도시화 속도의 증가와 더불어 3차원 자료 획득의 출처가 다양해지연서, 도로 및 건물경계선과 같은 선형 GIS 정보에 대한 신속한 갱신 또한 요구되고 있다. 임의의 출처 자료로부터 대상 자료를 갱신하기 위해서는 가장 먼저 두 자료간의 위치 관계를 결정하여야 하며, 특히 영상정보와 같은 출처 자료와 GIS 자료와 같은 대상 자료간의 위치 관계를 결정하기 위하여 기존에 제시되어온 대부분의 방법들은 두 개 자료간의 관계를 정의 할 수 있는 기준정과 같은 정확한 점 정합 요소(point matching entities)를 요구하고 있다. 따라서 정확한 정합 요소들을 획득할 수 없는 경우 영상과 GIS 자료간의 위치 관계를 결정할 수 없을뿐더러 위치 관계 정립의 결과는 정합 요소들의 분포 및 정확도에 매우 의존하게 된다. 또한 이러한 점 정합 요소들을 정의하기 위해서는 대부분의 경우 수동적으로 이루어질 수밖에 없다. 따라서 본 연구에서는 영상 및 GIS 자료의 선형 정보를 이용하여 정확한 점 정합 요소들을 모르더라도 영상과 GIS 자료간의 위치 관계를 결정할 수 있는 기법을 제시하고자 한다. 사용된 알고리즘은 개선된 Hough 변환(Modified Hough Transform)을 기반으로 다수의 선형 정보 중에 정합되는 요소들을 자동으로 찾아내고 이들을 최소제곱법으로 풀이함으로써 두 데이터간의 기하학적 변환 관계를 결정하는 기법이다. 본 연구에서는 이와 같은 접근을 통해 데이터간의 기하학적 변환 관계를 결정한 후, 영상 상에는 존재하지만 GIS 자료에는 존재하지 않는 선형 정보에 대한 갱신 여부를 확인하고 갱신함으로써 3차원 위치 자료의 자동 생성에 대한 가능성을 제시하고자 한다.로 갈수록 퇴적이 우세한 것으로 관측되었다.보체계의 구축사업의 시각이 행정정보화, 생활정보화, 산업정보화 등 다양한 분야와 결합하여 보다 큰 시너지 효과와 사용자 중심의 서비스 개선을 창출할 수 있는 기반을 제공할 것을 기대해 본다.. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of th