• Smart Structures and Systems
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• v.8 no.1
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• pp.69-92
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• 2011

This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.

• IE interfaces
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• v.20 no.4
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• pp.458-468
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• 2007

Artificial immune systems (AIS) are one of natural computing inspired by the natural immune system. The fault detection, the pattern recognition, the system control and the optimization are major application area of artificial immune systems. This paper gives a concept of artificial immune systems and useful techniques as like the clonal selection, the immune network theory and the negative selection. A concise survey on the optimization problem based on artificial immune systems is generated. The overall performance of artificial immune systems for the optimization problem is discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.151-151
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• 2000

The objective of this paper is to develop the new robust and adaptive control system against external environments as applying the probabilistic recognition which is one of the inherent properties of immune system, ability of learning and memorization, and regulation theory of immune network to the system under engineering point of view. In this paper, HIA(Humoral Immune Algorithm) PID controller using Neural Network Identifier was proposed to drive the autonomous guided vehicle(AGV) more effectively. To verify the performance of the proposed HIA PID controller, some experiments for the control of steering and speed of that AGV are performed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2732-2753
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• 2019

With the application of wireless sensor networks in the fields of ecological observation, defense military, architecture and urban management etc., the security problem is becoming more and more serious. Characteristics and constraint conditions of wireless sensor networks such as computing power, storage space and battery have brought huge challenges to protection research. Inspired by the danger theory in biological immune system, this paper proposes an intrusion detection model for wireless sensor networks. The model abstracts expressions of antigens and antibodies in wireless sensor networks, defines meanings and functions of danger signals and danger areas, and expounds the process of intrusion detection based on the danger theory. The model realizes the distributed deployment, and there is no need to arrange an instance at each sensor node. In addition, sensor nodes trigger danger signals according to their own environmental information, and do not need to communicate with other nodes, which saves resources. When danger is perceived, the model acquires the global knowledge through node cooperation, and can perform more accurate real-time intrusion detection. In this paper, the performance of the model is analyzed including complexity and efficiency, and experimental results show that the model has good detection performance and reduces energy consumption.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.1-6
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• 2002

In this paper, we propose temperature inference system for indoor and outdoor temperature of the Air-Conditioner with limited sensors. The proposed system based on the network theory of biological immune system consists of indoor and outdoor temperature inference process. It is designed that on-line temperature inference is possible. This system is admirable for unlearned data as well as given input data by making efficient use of previous information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• IMMUNE NETWORK
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• v.1 no.2
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• pp.104-108
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• 2001

Aging is a senescence and defined as a normal physiologic and structural alterations in almost all organ systems with age. As Leonard Hayflick, one of the first gerontologists to propose a theory of biologic aging, indicated that a theory of aging or longevity satisfies the changes of above conditions to be universal, progressive, intrinsic and deleterious. Although a number of theories have been proposed, it is now clear that cell aging (cell senescence) is multifactorial. No single mechanism can account for the many varied manifestations of biological aging. Many theories have been proposed in attempt to understand and explain the process of aging. Aging is effected in individual by genetic factors, diet, social conditions, and the occurrence of age-related diseases as diabetes, hypertension, and arthritis. It involves an endogenous molecular program of cellular senescence as well as continuous exposure throughout life to adverse exogenous influences, leading to progressive infringement on the cell's survivability so called wear and tear. So we could say the basic mechanism of aging depends on the irreversible and universal processes at cellular and molecular level. The immediate cause of these changes is probably an interference in the function of cell's macromolecules-DNA, RNA, and cell proteins-and in the flow of information between these macromolecules. The crucial questions, unanswered at present, concerns what causes these changes in truth. Common theories of aging are able to classify as followings for the easy comprehension. 1. Biological, 1) molecular theories - a. error theory, b. programmed aging theory, c. somatic mutation theory, d. transcription theory, e. run-out-of program theory, 2) cellular theories - a. wear and tear theory, b. cross-link theory, c. clinker theory, d. free radical theory, e. waste product theory, 3) system level theory-a. immunologic/autoimmune theory, 4) others - a. telomere theory, b. rate of living theory, c. stress theory, etc. Prevention of aging is theoretically depending on the cause or theory of aging. However no single theory is available and no definite method of delaying the aging process is possible by this moment. The most popular action is anti-oxidant therapy using vitamin E and C, melatonin and DHEA, etc. Another proposal for the reverse of life-span is TCP-17 and IL-16 administration from the mouse bone marrow B cell line study for the immunoglobulin VDJ rearrangement with RAG-1 and RAG-2. Recently conclusional suggestion for the extending of maximum life-span thought to be the calory restriction.

• Journal of Ginseng Research
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• v.42 no.1
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• pp.98-106
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• 2018

Panax ginseng has been used since ancient times based on the traditional Asian medicine theory and clinical experiences, and currently, is one of the most popular herbs in the world. To date, most of the studies concerning P. ginseng have focused on specific mechanisms of action of individual constituents. However, in spite of many studies on the molecular mechanisms of P. ginseng, it still remains unclear how multiple active ingredients of P. ginseng interact with multiple targets simultaneously, giving the multidimensional effects on various conditions and diseases. In order to decipher the systems-level mechanism of multiple ingredients of P. ginseng, a novel approach is needed beyond conventional reductive analysis. We aim to review the systems-level mechanism of P. ginseng by adopting novel analytical framework-network pharmacology. Here, we constructed a compound-target network of P. ginseng using experimentally validated and machine learning-based prediction results. The targets of the network were analyzed in terms of related biological process, pathways, and diseases. The majority of targets were found to be related with primary metabolic process, signal transduction, nitrogen compound metabolic process, blood circulation, immune system process, cell-cell signaling, biosynthetic process, and neurological system process. In pathway enrichment analysis of targets, mainly the terms related with neural activity showed significant enrichment and formed a cluster. Finally, relative degrees analysis for the target-disease association of P. ginseng revealed several categories of related diseases, including respiratory, psychiatric, and cardiovascular diseases.