• International Journal of Contents
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• 제3권2호
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• pp.18-24
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• 2007

Biological sequences such as DNA and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of more than hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological datasets with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with a fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. The experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Journal of information and communication convergence engineering
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• 제1권3호
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• pp.104-108
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• 2003

A biologically inspired fuzzy multilayer perceptron is proposed in this paper. The proposed algorithm is established under consideration of biological neuronal structure as well as fuzzy logic operation. We applied this suggested learning algorithm to benchmark problem in neural network such as exclusive OR and 3-bit parity, and to digit image recognition problems. For the comparison between the existing and proposed neural networks, the convergence speed is measured. The result of our simulation indicates that the convergence speed of the proposed learning algorithm is much faster than that of conventional backpropagation algorithm. Furthermore, in the image recognition task, the recognition rate of our learning algorithm is higher than of conventional backpropagation algorithm.

• Journal of Microbiology and Biotechnology
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• 제14권6호
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• 대한안전경영과학회지
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• 제21권4호
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• pp.1-6
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• 2019

This study relates to acquiring biological signal without attaching directly to the user using UWB(Ultra Wide Band) radar. The collected information is the respiratory rate, heart rate, and the degree of movement during sleep, and this information is used to measure the sleep state. A breathing measurement algorithm and a sleep state detection algorithm were developed to graph the measured data. Information about the sleep state will be used as a personalized diagnosis by connecting with the medical institution and contribute to the prevention of sleep related diseases. In addition, biological signal will be linked to various sensors in the era of the 4th industrial revolution, leading to smart healthcare, which will make human life more enriching.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2911-2914
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• 2003

Conventionally, biological manipulations have been performed manually with long training and pretty low success rates. To overcome this problem, a novel biological manipulation system has been developed to manipulate biological cells without any interference of a human operator, In this paper, we demonstrate a development of tole-autonomous Cell Manipulation System (CMS) using an image processing at a remote site. The CMS consists of two manipulators, a plane stage, and an optical microscope. We developed deformable template-model-matching algorithm for micro objects and pattern matching algorithm of end effect for these manipulators in order to control manipulators and the stage. Through manipulation of biological cells using these algorithms, the performance of the CMS is verified experimentally.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.109-114
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• 2007

Fingerprints have been widely used in the biometric authentication because of its performance, uniqueness and universality. Lately, the speed of identification has become a very important aspect in the fingerprint-based security applications. Also, the reliability still remains the main issue in the fingerprint identification. A fast and reliable fingerprint matching algorithm based on the process of the 'self-nonself' discrimination in the biological immune system was proposed. The proposed algorithm is organized by two-matching stages. The 1st matching stage utilized the self-space and MHC detector string set that are generated from the information of the minutiae and the values of the directional field. The 2nd matching stage was made based on the local-structure of the minutiae. The proposed matching algorithm reduces matching time while maintaining the reliability of the matching algorithm.

• 정보처리학회논문지D
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• 제15D권2호
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• pp.155-162
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• 2008

DNA 염기 서열이나 단백질 아미노산 서열과 같은 생물학적 서열 데이터들은 일반적으로 많은 수의 항목들을 가지고 있다. 생물학적 데이터 서열들에는 보통 빈번하게 발생하는 수 백개의 항목으로 이루어진 연속된 서열들이 존재한다. 이들 서열들에서 빈번하게 발생하는 연속 서열을 검색하는 것은 생물학적 서열 분석에서 중요한 부분을 차지하고 있다. 이전에는 순차 패턴을 효과적으로 발견하고자 하는 많은 연구들이 수행되었으며 대부분의 기존 순차패턴 마이닝 기법들은 Apriori 알고리즘을 기반으로 한다. PrefixSpan 알고리즘은 Apriori 기반의 가장 효율적인 순차패턴 마이닝 기법이다. 하지만 이 알고리즘은 길이-1인 빈발 패턴들로 부터 서열 패턴을 확장해나가는 방식이다. 따라서 길이가 긴 연속 서열을 포함하는 생물학적 데이터서열들에 대한 검색방법으로는 적합하지 않다. 최근에는 기존의 PrefixSpan방식을 이용하면서도 반복적인 처리과정을 줄인 MacosVSpan이 제안되었다. 하지만 이 알고리즘 또한 길이가 긴 생물학적 데이터 서열들로부터 빈번하게 발생하는 연속 서열들을 검색하기에는 효율적이지 않다. 본 논문에서는 많은 양의 생물학적 데이터 서열들로부터 빈번한 연속서열을 고정길이 확장 트리를 이용하여 효과적으로 찾아내는 방법을 제안한다. 그리고 다양한 환경에서 실험을 통해 제안하는 방식이 MacosVSpan알고리즘에 비해 검색성능이 보다 우수함을 보인다.

• 한국시뮬레이션학회논문지
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• 제19권2호
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• pp.81-89
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• 2010

생물학 데이터 마이닝은 생물학 데이터의 볼륨이 급격하게 증가함에 따라 최근 주목받고 있다. 그리드 기술은 계산 자원과 데이터 공유와 활용을 가능하게 한다. 이 논문에서는 생물학 데이터 마이닝과 그리드 기술을 결합한 혼합형 시스템을 제안한다. 특히, 생물학 데이터 마이닝의 처리 효율성을 위해 결정 범위 조정 알고리즘을 사용한다. 우리는 이 알고리즘을 통해 빠르고 자동으로 신뢰할 만한 데이터 마이닝 인식률을 얻는다. 게다가 그리드 환경에서는 지리적으로 분산된 자원들을 연동하기 때문에 통신량과 자원 할당이 이슈가 된다. 우리는 동적 로드 밸런싱을 제안하고 그리드 기반 생물학 데이터 마이닝 기법에 적용한 다. 성능 평가를 위해 우리는 평균 처리 시간, 평균 통신 시간, 평균 자원 활용도를 측정한다. 측정 실험의 결과는 제안된 두 알고리즘을 적용한 우리의 기법이 처리 시간과 비용 측면에서 이점을 제공한다는 것을 보여준다.

• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.128-137
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• 2016

In mobile communication, air conduction(AC) speech signal had been commonly used, but it was easily affected by ambient noise environment such as emergency, military action and rescue. To overcome the weakness of the AC speech signal, bone conduction(BC) speech signal have been used. The BC speech signal is transmitted through bone vibration, so it is affected less by the background noise. In this paper, we proposed noise cancellation algorithm of the BC speech signal using noise feature of decomposed bands. The proposed algorithm consist of three steps. First, the BC speech signal is divided into 17 bands using perceptual wavelet packet decomposition. Second, threshold is calculated by noise feature during short time of separated-band and compared to absolute average of the signal frame. Therefore, the speech and noise parts are detected. Last, the detected noise parts are removed and then, noise eliminated bands are re-synthesised. In order to confirm the efficiency of the proposed algorithm, we compared the proposed algorithm with conventional algorithm. And the proposed algorithm has better performance than the conventional algorithm.

• 예술인문사회 융합 멀티미디어 논문지
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• 제8권6호
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• pp.957-966
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• 2018

최근 들어 고령화 및 1인 가구 증가로 인해 IoT기반 원격환자모니터링에 대한 요구가 증대되고 있다. 본 논문에서는 원격환자모니터링을 위한 다중의 IR-UWB레이더를 이용한 비접촉식 생체신호측정시스템을 제안하였다. 기존에는 생체신호처리를 위해 배경차분알고리즘을 적용하였으나, 전압노이즈, 계단현상 등의 에러 발생을 없애고자 다중 배경차분 알고리즘을 적용하였다. 다중배경차분알고리즘은 이전 클러터와 현재 클러터의 변화량을 계산하여 신호를 추출하며, 본 연구에서는 SVD알고리즘을 이용하였다. 개선된 다중배경차분알고리즘을 생체신호측정에 응용하여 고속 푸리에 변환을 통해 호흡수를 계산하였다. 제안한 IR-UWB레이더를 이용한 시스템 및 다중배경차분알고리즘의 검증을 위해 호흡수 측정을 진행하였다. Neulog사의 부착형 공기압착식 호흡측정기를 대조군으로 실험한 결과 97.36%의 정밀도를 확보함으로서 본 연구의 타당성을 검증하였다. 구현된 알고리즘은 기존의 접촉식 웨어러블 방식의 불편함을 개선하였다.