• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.222-227
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• 2006

Recently the research for Traveling Salesman Problem (TSP) using DNA computing with massive parallelism has been. However, there were difficulties in real biological experiments because the conventional method didn't reflect the precise characteristics of DNA when it express graph. Therefore, we need DNA sequence generation algorithm which can reflect DNA features and reduce biological experiment error. In this paper we proposed a DNA sequence generation algorithm that applied DNA coding method of evolution model to DNA computing. The algorithm was applied to TSP, and compared with a simple genetic algorithm. As a result, the algorithm could generate good sequences which minimize error and reduce the biologic experiment error rate.

• Journal of Biomedical Engineering Research
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• v.10 no.1
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• pp.17-24
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• 1989

This papaer presents a new algorithm for the P-wave detection in the ECG signal. Digital differentiation method (7-point derivative) is used for detecting P-waves exactly. This algorithm can detect various parameters of PR, PP, RR interval, which are important to diagnosis AV blocks and WPW syndrome. Especially, this algorithm can detect P-waves very efficiently not only in well-preprocessed waves but in pccr waves with noise and artifact. And it enables to develope more reliable automatic diagnosis algorithm.

• The Journal of Information Technology
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• v.6 no.3
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• pp.35-44
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• 2003

This study shows the implementation of the computer algorithm of active filter less than or equal to the 10th order for biological signals which is indispensably used as the interfaces for biological signal instrumentation of human body. Applications in the field of medial science are proposed by improving the weak point of manually calculated design which takes a lot of time and the complexity to design the active filter.

• Journal of Biomedical Engineering Research
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• v.26 no.2
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• pp.87-93
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• 2005

A new method for real-time estimating left ventricular relaxation time constant (T) from the left ventricular (LV) pressure waveform, based on the isovolumic relaxation model, is proposed. The presented method uses a recursive least squares (RLS) algorithm to accomplish real-time estimation. A new criterion to detect the end-point of the isovolumic relaxation period (IRP) for the estimation of T is also introduced, which is based on the pattern analysis of mean square errors between the original and reconstructed pressure waveforms. We have verified the performance of the new method in over 4,600 beats obtained from 70 patients. The results demonstrate that the proposed method provides more stable and reliable estimation of τ than the conventional 'off-line' methods.

• Genomics & Informatics
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• v.2 no.1
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• pp.19-29
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• 2004

Gene expression profiles may offer more information than morphology and provide an alternative to morphology- based tumor classification systems. Informative gene selection is finding gene subsets that are able to discriminate between tumor types, and may have clear biological interpretation. Gene selection is a fundamental issue in gene expression based tumor classification. In this report, techniques for selecting informative genes are illustrated and supervised shaving introduced as a gene selection method in the place of a clustering algorithm. The supervised shaving method showed good performance in gene selection and classification, even though it is a clustering algorithm. Almost selected genes are related to leukemia disease. The expression profiles of 3051 genes were analyzed in 27 acute lymphoblastic leukemia and 11 myeloid leukemia samples. Through these examples, the supervised shaving method has been shown to produce biologically significant genes of more than $94\%$ accuracy of classification. In this report, SVM has also been shown to be a practicable method for gene expression-based classification.

• The Journal of Information Technology
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• v.9 no.1
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• pp.33-39
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• 2006

This study is for the contents of development to the hardware system and software driving algorithm to implement the frequency band of about 7KHz los pass digital filter which has the cut-off frequency of 392Hz by interfacing of a microprocessor with its peripheral analog-to-digital converter chip and digital-to-analog converter chip. The simplicity of digital filter design without difficulty and the implementation of programmed digital filter can be realized by providing the interfacing method to implement the law pass digital filter for the biological signals and the realization method of computer algorithm by a microprocessor.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.647-651
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• 1987

Yeast biomass in a biological continuous stirred tank reactor was controlled with an APPLE II microcomputer using adaptive control theory of bilinear systems. The controller used is as simple as a PID controller, but required less information. Cell concentration was well controlled by adjusting the inlet flow rate following the algorithm.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.129-135
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• 2004

In the home health management system, we often face the situation to handle biological signals that are frequently measured from normal subjects. In such a case, it is necessary to decide whether the signal at a certain moment is normal or abnormal. Since ECC is one of the most frequently measured biological signals, we describe algorithms that detect QRS-complex and decide whether it is normal or abnormal. The developed QRS detection algorithm is a simplified version of the conventional algorithm providing enough performance for the proposed application. The developed classification algorithm that detects abnormal from mostly normal beats is based on QRS width, R-R interval and QRS shape parameter using Karhunen-Loeve transformation. The simplified QRS detector correctly detected about 99% of all beats in the MTT/BIH ECG database. The classification algorithm correctly classified about 96% of beats as normal or abnormal. The QRS detection and classification algorithm described in this paper could be used in home health management system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2349-2351
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• 2010

Photo Acoustic Tomography (PAT) is a hybrid imaging modality which combines high contrast of optical imaging and spatial resolution of ultrasound imaging, thus it is suitable to image biological tissue noninvasively. Laser-induced photoacoustic signals were measured from a sample by means of an unfocused ultrasound transducer, then PAT image was reconstructed based on a universal back-projection algorithm. To evaluate the feasibility of our system, phantom test was performed, consequently, the PAT images obtained using our system showed highly analogous shape and volume with those of the phantom. This result demonstrated that our system can provide a powerful tool for imaging the substructure of biological tissue in non-invasive manner.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.185-188
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• 2001

According as many people use a computer newly, damage of computer virus and hacking is rapidly increasing by the crucial users. To block hacking that is intrusion of a person's computer and the computer virus that destroys data, a study for intrusion-detection of system and virus detection using a biological immune system is in progress. In this paper, we make a model of positive selection and negative selection of self-recognition process that is ability of T-cytotoxic cell that plays an important part in biological immune system. So we embody a self-nonself distinction algorithm in computer. To prove the efficacy of self-recognition algorithm, we use simulations by a cell change and a string change of self file.