• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.473-477
• /
• 2002

세포내에서 특정 단백질이 합성되어 이용되는 것을 단백질의 발현이라 한다. 이러한 단백질의발현을 조사하는 작업은 세포내 대사과정을 밝혀내는 데 있어서 매우 중요한 역할을 담당하고 있다. 단백질의 발현을 조사하기 위해서는 세포로부터 추출하여 정제한 단백질이 어떤 단백질인지를 확인하는 작업이 필요한데 현재로써는 확인하고자 하는 단백질 효소로 분해하여 분해된 조각들의 질량을 측정하여 기존에 알려진 단백질들을 분해했을 때 이론상 나을 수 있는 조각들의 무게와 비교하여 가장 근접한 단백질을 찾아내는 질량분석기법(mass Spectrometry)이 널리 사용된다. 그러나 이 방법은 확인하고자 하는 단백질의 아미노산 서열이 알려져 있을 경우에만 사용할 수 있다는 한계점을 가지고 있다. 본 논문에서는 이러한 한계를 계산적인 방법으로 극복하고자 동일단백질을 여러가지 효소로 분해하여 나오는 조각들의 질량을 측정하고 이들을 조합하여 원래 단백질의 아미노산 서열을 알아낼 수 있는 알고리즘을 제안한다.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.2 no.1
• /
• pp.39-45
• /
• 1997

In this paper, a high speed motor drive system using an indirect adaptive neural network controller is proposed. In the variable high speed motor drives, the speed response can be deteriorated by long settling time and high overshoot. To obtain a good dynamical performance, an adaptive feedforward controller consisted of Neural Network Controller(NNC) and Neural Network Emulator(NNE) is applied. The NNE is used to identify the parameters and characteristics of high speed motor. To train the controller, the weights are dynamically adjusted using the back propagation algorithm. Computer simulation and implementation of the proposed system is described.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.297-300
• /
• 2006

본 논문에서는 비선형 기동표적의 추적에 대한 새로운 접근 방식을 소개한다. 이 논문에서는 표적의 가속도를 시변 변수인 표적의 추가적인 잡음으로 두고 각각의 가속도 간격의 정도에 따라 얻어지는 모든 잡음에 대한 변수에 의해 각각의 하부 모델들을 특성화시켰다. 표적의 기동중에 나타나는 가속도를 효과적으로 다루기 위하여, 잡음의 크기가 급격히 증가할 경우 증가분을 가속도로 인식하여 기동표적 관계식에 이용하였다. 또한 모르는 가속도에 따른 시변 변수를 적응적으로 어립잡기는 어렵기 때문에 정밀한 계산을 위하여 퍼지 뉴럴 네트워크와 적응 상호작용 다중모델 기법을 이용하였다. 퍼지 뉴럴 네트워크의 동정을 위해서는 오차 역전파 학습법을 사용하였다. 그리고 제안된 알고리즘의 수행 가능성을 보여주기 위하여 몇 가지 예를 제시하였다.

• Korean journal of applied entomology
• /
• v.58 no.1
• /
• pp.1-8
• /
• 2019

The genus Nipponopsyche Yazaki is reported from Korea with the species, N. fuscescens Yazaki for the first time. Adult including genitalia, larva, and pupa of the species are redescribed, and DNA barcode for precise identification of the species is also provided.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2004.11a
• /
• pp.21-28
• /
• 2004

모든 생명체의 genetic information에는 보존적 염기서열과 다형적 염기서열이 존재한다. 다형적 염기서열과 보존적 염기서열은 하나의 종(species)을 감별하거나, 여러 종류의 종을 동시에 감별할 수 있는 genotyping의 표지자로 각각 이용될 수 있다. 본 논문은 병원성 감염질환 세균, 식중독 유발 세균, 생물의약품 오염 유발 세균 및 환경오염 세균 등 세균의 존재 유무와 속과 종 감별을 위해 대부분 세균 종의 보존적 염기서열과 다형적인 염기서열을 포함하고 있는 23S rDNA 유전자의 표적 염기 서열로부터 고안된 세균 특이적(bacterial-specific), 속 특이적(genus-specific), 종 특이적(species-specific) 올리고 뉴클레오티드프로브와 프라이머를 디자인하는 시스템을 소개한다. 시스템을 통해서 얻어진 프로브와 프라이머들은 PCR을 통한 검증단계를 거쳐서 디자인 결과의 정확성을 확인하였다. 본 시스템의 이용으로 프로브와 프라이머를 디자인하는데 몇 주가 소요되는 시간을 몇 일 내로 줄일 수 있었으며, 체계적인 데이터의 관리로 결과의 정확성을 높일 수 있었다.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.1 s.33
• /
• pp.93-100
• /
• 2005

This study is to desist and implement an efficient microbial medical image retrieval system based on knowledge and content of them which can make use of more accurate decision on colony as doll as efficient education for new techicians. For this. re first address overall inference to set up flexible search path using rule-base in order U redure time required original microbial identification by searching the fastest path of microbial identification phase based on heuristics knowledge. Next, we propose a color ffature gfraction mtU, which is able to extract color feature vectors of visual contents from a inn microbial image based on especially bacteria image using HSV color model. In addition, for better retrieval performance based on large microbial databases, we present an integrated indexing technique that combines with B+-tree for indexing simple attributes, inverted file structure for text medical keywords list, and scan-based filtering method for high dimensional color feature vectors. Finally. the implemented system shows the possibility to manage and retrieve the complex microbial images using knowledge and visual contents itself effectively. We expect to decrease rapidly Loaming time for elementary technicians by tell organizing knowledge of clinical fields through proposed system.

• Journal of Life Science
• /
• v.33 no.7
• /
• pp.538-548
• /
• 2023

The research has been conducted on the isolation of antimicrobial compounds from plant natural extracts and their potential application in oral health care products. This study aimed to investigate the antimicrobial mechanism by analyzing the changes in gene expression of Streptococcus mutans, a major oral pathogen, in response to complex compounds extracted from Aralia continentalis and Arctii Semen using organic solvents. Transcriptome analysis (RNA-seq) revealed that both natural extracts commonly upregulated or downregulated the expression of various genes associated with different metabolic and physiological activities. Three genes (SMU_1584c, SMU_2133c, SMU_921), particularly SMU_921 (rcrR), known as a transcription activator of two sugar phosphotransferase systems (PTS) involved in sugar transport and biofilm formation, exhibited consistent high expression levels. Additionally, component analysis of the A. continentalis extract was performed to compare its effects on gene expression changes with the A. Semen extract, and two active compounds were identified through gas chromatography-mass spectrometry (GC-MS) analysis of the active fraction. The n-hexane fraction (ACEH) from the A. continentalis extract exhibited antibacterial specificity against S. mutans, leading to a significant reduction in the viable cell counts of Streptococcus sanguinis and Streptococcus gordonii among the tested multi-species bacterial communities. These findings suggest the broad-spectrum antibacterial activity of the A. continentalis extract and provide essential foundational data for the development of customized antimicrobial materials by elucidating the antibacterial mechanism of the identified active compounds.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.7 no.2
• /
• pp.43-50
• /
• 1997

Refuse incineration plant operations involve many kinds of uncertain factors, such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon. This makes it very dificult to apply conventional control methods to the combustion control of the refuse. So most of the refuse incineration plant are operated by operators. In this paper, an multi-variable fuzzy model predictive controller is proposed for the combustion control of the re:fuse. Adaptive network based fuzzy inference system is used for modeling of the refuse incineration plant and multi-variable fuzzy model predictive controller is designed based on the identified fuzzy model. And computer simulation was carried out to evaluate performance of the proposed controller.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.5
• /
• pp.432-441
• /
• 2000

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Genetic algorithm has been used to identifY parameters and structure of fuzzy model because it has the ability to search optimal solution somewhat globally. The genetic algorithm, however, has a problem, which optimization process can be premature convergence in the case of lack of genetic divergence of population. Virus- evolutionary genetic algorithm(VEGA) could be a strategy against this local convergence. Therefore, we use VEGA for fuzzy modeling. In this method, local information is exchanged in population so that population can sustain genetic divergence. finally, to prove the theoretical hypothesis, we provide numerical examples to evaluate the feasibility and generality of fuzzy modeling using VEGA.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.4
• /
• pp.472-478
• /
• 2006

This paper presents a new fuzzy-neural-network based interacting multiple model (FNNBIMM) algorithm for tracking a maneuvering target. To effectively handle the unknown target acceleration, this paper regards it as additional noise, time-varying variance to target model. Each sub model characterized by the variance of the overall process noise, which is obtained on the basis of each acceleration interval. Since it is hard to approximate this time-varying variance adaptively owing to the unknown acceleration, the FNN is utilized to precisely approximate this time-varying variance. The error back-propagation method is utilized to optimize each FNN. To show the feasibility of the proposed algorithm, a numerical example is provided.