• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.273-279
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• 1998

An immune system has powerful abilities such as memory, recognition and learning to respond to invading antigens, and is applied to many engineering algorithm recently. In this paper, the combined optimization algorithm is proposed for multi-optimization problem by introducing the capability of the immune system that controls the proliferation of clones to the genetic algorithm. The optimizing ability of the proposed optimization algorithm is identified by using two multi-peak functions which have many local optimums and optimization of the unbalance response function for rotor model.

• Journal of Information Technology Services
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• v.8 no.4
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• pp.129-140
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• 2009

The accurate estimation of software reliability is important to a successful development in software engineering. Until recent days, the models using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software reliability using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying immune algorithm, changing the number of generations, memory cells, and allele. The proposed IA-SVR model outperforms some recent results reported in the literature.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.120.2-120
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• 2002

In this paper auto-tuning scheme of weight function in the neural networks has been suggested by immune algorithm for nonlinear process. A number of structures of the neural networks are considered as learning methods for control system. A general view is provided that they are the special cases of either the membership functions or the modification of network structure in the neural networks. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also. It can provi..

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2278-2282
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, a general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, the immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1531-1536
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, A general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, The immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.261-268
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• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

• Korean Management Science Review
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• v.26 no.1
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• pp.171-182
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• 2009

We consider the inventory replenishment problem and the vehicle routing problem simultaneously in the vending machine operation. This problem is known as the inventory routing problem. We design a memory cell in the clonal selection algorithm. The memory cell store the best solution of previous solved problem and use an initial solution for next problem. In general, the other clonal selection algorithm used memory cell for reserving the best solution in current problem. Experiments are performed for testing efficiency of the memory cell in demand uncertainty. Experiment result shows that the solution quality of our algorithm is similar to general clonal selection algorithm and the calculations time is reduced by 20% when the demand uncertainty is less than 30%.

• IMMUNE NETWORK
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• v.3 no.1
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• pp.29-37
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• 2003

Background: CC chemokine receptor (CCR) 7 and cognate CCR7 ligands, CCL21 (formerly secondary lymphoid tissue chemokine [SLC]) and CCL19 (formerly Epstein-Barr virus-induced molecule 1 ligand chemokine [ELC]), were known to establish microenvironment for the initiation of immune responses in secondary lymphoid tissue. As described previously, coadministration of DNA vaccine with CCR7 ligand-encoding plasmid DNA elicited enhanced humoral and cellular immunity via increasing the number of dendritic cells (DC) in secondary lymphoid tissue. The author hypothesized here that CCR7 ligand DNA could effectively expand memory CD4+ T cells to protect from viral infection likely via increasing DC number. Methods: To evaluate the effect of CCR7 ligand DNA on the expansion of memory CD4+ T cells, DO11.10.BALB/c transgenic (Tg)-mice, which have highly frequent ovalbumin $(OVA)_{323-339}$ peptide-specific CD4+ T cells, were used. Tg-mice were previously injected with CCR7 ligand DNA, then immunized with $OVA_{323-339}$ peptide plus complete Freund's adjuvant. Subsequently, memory CD4+ T cells in peripheral blood lymphocytes (PBL) were analyzed by FACS analysis for memory phenotype ($CD44^{high}$ and CD62 $L^{low}$) at memory stage. Memory CD4+ T cells recruited into inflammatory site induced with OVA-expressing virus were also analyzed. Finally, the protective efficacy against viral infection was evaluated. Results: CCR7 ligand DNA-treated Tg-mice showed more expanded $CD44^{high}$ memory CD4+ T cells in PBL than control vector-treated animals. The increased number of memory CD4+ T cells recruited into inflammatory site was also observed in CCR7 ligand DNA-treated Tg-mice. Such effectively expanded memory CD4+ T cell population increased the protective immunity against virulent viral infection. Conclusion: These results document that CCR7 and its cognate ligands play an important role in intracellular infection through establishing optimal memory T cell. Moreover, CCR7 ligand could be useful as modulator in DNA vaccination against viral infection as well as cancer.

• Journal of Life Science
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• v.29 no.7
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• pp.817-823
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• 2019

Immune system provides defense integrity of body against external invaders. In order to accomplish the important defending role immune system is composed of many different components which are regenerated continuously during lifespan. The key components are professional killing cells such as macrophage, neutrophil, natural killer cell, and cytotoxic T cell and professional blocking molecule, antibody, which is produced by plasma cell, the terminal differentiated B cell. Immune response is orchestrated harmoniously by all these components mediated through antigen presenting cells such as dendritic cells. Immune responses can be divided into two ways: innate immune response and adaptive immune response depending on induction mechanism. Aging is a broad spectrum of physiological changes. Likewise other physiological changes, the immune components and responses are wane as aging is progressing. Immune responses become decline and dysregulating, which is called immunosenescense. Immune components of both innate and adaptive immune response are affected as aging progresses leading to increased vulnerability to infectious diseases. Numbers of immune cells and amounts of soluble immune factors were decreased in aged animal models and human and also functional and structural alterations in immune system were reduced and declined. Cellular intrinsic changes were discovered as well. Recent researches focusing on aging have been enormously growing. Many advanced tools were developed to bisect aging process in multi-directions including immune system area. This review will provide a broad overview of aging-associated changes of key components of immunity.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.475-486
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• 2004

The interaction of HIV and human immune system was studied in the perspective of dynamics. We summarized the recent researches on drug scheduling using optimal control theory for HIV treatment. The drug treatment to make immune system to work properly is investigated based on mathematical models including memory CTLp. In the simulation results, it was verified that stopping medication after a certain period of treatment can lead a patient to be cured naturally by one s immune system. Also, we summarized and categorized the advantages and disadvantages of each HIV drug scheduling method. In conclusion, model-based predictive control is more efficient for making decision of drug dose than other methods, when there exist uncertainties on model parameters or state variables.