• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.263-266
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• 1997

In this paper we will develope the immnized recurrent neural network control system of a robot manipulator with high robustness in dynamically changing environment conditions. Immune system detects and eliminates the non-self materials called antigen such as virus, bacteria and so on which come from inside and outside of the living system, so plays an important role in maintaining its own system against dynamically changing environments. We apply this concept to a robot manipulator and evaluate the effectiveness of the above proposed system.

• Biotechnology and Bioprocess Engineering:BBE
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• v.8 no.2
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• pp.112-116
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• 2003

An immunosensor based on surface plasmon resonance (SPR) onto a protein G layer by Self-assembly technique was developed for detection of Legionella pneumophila. The protein G layer by self-assembly technique was fabricated on a gold (Au) surface by adsorbing the 11-mercaptoundecanoic acid (MUA) and an activation process for the chemical binding of the free amino (-NH$_2$) of protein G and 11-(MUA) using 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDAC) in series. The formation of the protein G layer by self-assembly technique on the Au Substrate and the binding of the antibody and antigen in series were confirmed by SPR spectroscopy. The Surface topographies of the fabricated thin films on an Au substrate were also analyzed by using an atomic force microscope (AFM). Consequently, an immunosensor for the detection of L. pneumophila using SPR was developed with a detection limit of up to 10$^2$CFU per mL.

• Biotechnology and Bioprocess Engineering:BBE
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• v.8 no.4
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• pp.227-232
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• 2003

A self-assembled monolayer of protein G was fabricated to develop an immunosensor based on surface plasmon resonance (SPR), thereby improving the performance of the antibodybased biosensor through immobilizing the antibody molecules (lgG). As such, 11-mercaptoundecanoic acid (11-MUA) was adsorbed on a gold (Au) support, while the non-reactive hydrophilic surface was changed through substituting the carboxylic acid group (-COOH) in the 11-MUA molecule using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrocholide (EDAC). The formation of the self-assembled protein G layer on the Au substrate and binding of the antibody and antigen were investigated using SPR spectroscopy, while the surface topographies of the fabricated thin films were analyzed using atomic force microscopy (AFM). A fabricated monoclonal antibody (Mab) layer was applied for detecting E. coli O157:H7. As a result, a linear relationship was achieved between the pathogen concentration and the SPR angle shift, plus the detection limit was enhanced up to 10$^2$ CFU/mL.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.119-124
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• 2003

In this paper, we modeled positive selection and negative selection that is developing process of cytotoxic T-cell that plays important role in biological immune system. Also, we developed change detection algorithm, which is very Important part in detecting data change by intrusion and data infection by computer virus. Proposed method is the algorithm that produces MHC receptor lot recognizing self and antigen detector for recognizing non-self. Therefore, proposed method detects self and intruder by two type of detectors like real immune system. We show the effectiveness and characteristics of proposed change detection algorithm by simulation about point and block change of self file.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.190-195
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• 2004

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.102-109
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• 1998

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment.For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental codintion changes, a robot select an appropriate beharior stategy. And its behavior stategy is stimulated and suppressed by other robot using communiation. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idotopic network hypothesis. And it is used for decision making of optimal swarm stragegy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.127-130
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• 1998

In this paper, we propose a method of cooperative control(T-cell modeling) and selection of group behavior strategy(B-cell modeling) based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-call respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based of clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.2
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• pp.41-49
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• 2013

Objectives: The purpose of this study was to clarify the association between serum carcinoembryonic antigen (CEA) and type of work in the shipbuilding industry. Methods: 1,072 final study subjects were admitted to a general hospital from April through July 2010 for the purpose of medical examination. Data on general characteristics such as age, smoking history, alcohol history and exercise habits was gathered through structured self-administered questionnaires. Information on job factors was collected from a medical examination, by interview and through company personnel data. Serum CEA levels were measured after eight hours' fasting and were analyzed by a radioimmunoassay. Results: On univariate analysis, the mean serum CEA level was significantly higher among married (p=0.02), older age (p<0.01), longer work time (p<0.01), smokers (p<0.01), lower education (p<0.01), and indirect and direct exposure groups (p<0.01). On multiple regression analysis, serum CEA level was influenced by smoking (p=0.001), duration of work (p=0.019), and direct exposure group (p<0.001). However, among the direct exposure group, serum CEA level was not significantly different between welding, mounting, electro-device constructive work, grinding and cleaning, and painting. Conclusions: The goal of this research was to determine if there were differences between serum CEA levels according to occupational role among shipyard workers. The direct exposure group of shipyard workers had a relatively higher level of serum CEA than did the indirect exposure group and office workers, most likely due to occupational exposure.

• Journal of Sensor Science and Technology
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• v.19 no.4
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• pp.306-312
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• 2010

We have detected deoxynivalenol(DON) using a metal-oxide-semiconductor field-effect-transistor(MOSFET)-based biosensor. The MOSFET-based biosensor is fabricated by a standard complementary metal-oxide-semiconductor(CMOS) process, and the biosensor's electrical characteristics were investigated. The output of the sensor was stabilized by employing a reference electrode that applies a fixed bias to the gate. Au which has a chemical affinity for thiol was used as the gate metal to immobilize a self-assembled monolayer(SAM) made of 16-mercaptohexadecanoic acid(MHDA). The SAM was used to immobilize anti-deoxynivalenol antibody. The carboxyl group of the SAM was bound to the anti- deoxynivalenol antibody. Anti-deoxynivalenol antibody and deoxynivalenol were bound by an antigen-antibody reaction. In this study, it is confirmed that the MOSFET-based biosensor can detect deoxynivalenol at concentrations as low as 0.1 ${\mu}g$/ml. The measurements were performed in phosphate buffered saline(PBS; pH 7.4) solution. To verify the interaction among the SAM, antibody, and antigen, surface plasmon resonance(SPR) measurements were performed.