• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1348-1356
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• 2017

Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.280-280
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• 2000

In this paper, we propose a method of constructing equation using bio-inspired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants. Here is. we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting mechanism. The DNA coding method has no limitation in expressing the production rule of L-system. Evolutionary algorithms motivated by Darwinian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it to one step ahead prediction of Mackey-Glass time series.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.405-423
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• 2022

The distance vector-hop (DV-Hop) is one of the emblematic algorithms that use node connectivity for locating, which often accompanies by a large positioning error. To reduce positioning error, the bio-inspired algorithm and weight optimization model are introduced to address positioning. Most scholars argue that the weight value decreases as the hop counts increases. However, this point of view ignores the intrinsic relationship between the error and weight. To address this issue, this paper constructs the relationship model between error and hop counts based on actual communication characteristics of sensor nodes in wireless sensor network. Additionally, we prove that the error converges to 1/6CR when the hop count increase and tendency to infinity. Finally, this paper presents a modified error-oriented weight positioning model, and implements it with genetic algorithm. The experimental results demonstrate excellent robustness and error removal.

• Smart Structures and Systems
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• v.8 no.1
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• pp.93-105
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• 2011

This paper presents a flexible low-profile antenna sensor for fatigue crack detection and monitoring. The sensor was inspired by the sense of pain in bio-systems as a protection mechanism. Because the antenna sensor does not need wiring for power supply or data transmission, it is an ideal candidate as sensing elements for the implementation of engineering sensor skins with a dense sensor distribution. Based on the principle of microstrip patch antenna, the antenna sensor is essentially an electromagnetic cavity that radiates at certain resonant frequencies. By implementing a metallic structure as the ground plane of the antenna sensor, crack development in the metallic structure due to fatigue loading can be detected from the resonant frequency shift of the antenna sensor. A monostatic microwave radar system was developed to interrogate the antenna sensor remotely. Fabrication and characterization of the antenna sensor for crack monitoring as well as the implementation of the remote interrogation system are presented.

• Smart Structures and Systems
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• v.8 no.1
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• pp.53-67
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• 2011

Human state in human-machine systems highly affects the overall system performance, and should be detected and monitored. Physiological cues are essential indicators of human state and useful for the purpose of monitoring. The study presented in this paper was focused on developing a bio-inspired sensing system, i.e., Nano-Skin, to non-intrusively measure physiological cues on human-machine contact surfaces to detect human state. The paper is presented in three parts. The first part is to analyze the relationship between human state and physiological cues, and to introduce the conceptual design of Nano-Skin. Generally, heart rate, skin conductance, skin temperature, operating force, blood alcohol concentration, sweat rate, and electromyography are closely related with human state. They can be measured through human-machine contact surfaces using Nano-Skin. The second part is to discuss the technologies for skin temperature measurement. The third part is to introduce the design and manufacture of the Nano-Skin for skin temperature measurement. Experiments were performed to verify the performance of the Nano-Skin in temperature measurement. Overall, the study concludes that Nano-Skin is a promising product for measuring physiological cues on human-machine contact surfaces to detect human state.

• Smart Structures and Systems
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• v.17 no.3
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• pp.523-539
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• 2016

The ambient vibration measurement is an output-data-only dynamic testing where natural excitations are represented, for instance, by winds and typhoons. The modal identification involving output-only measurements requires the use of specific modal identification techniques. This paper presents the application of a reliable method (the Stochastic Subspace Identification - SSI) implemented in a general purpose software. As a criterion toward the robustness of identified modes, a bio-inspired optimization algorithm, with a highly nonlinear objective function, is introduced in order to find the optimal deployment of a reduced number of sensors across a large civil engineering structure for the validation of its modal identification. The Ting Kau Bridge (TKB), one of the longest cable-stayed bridges situated in Hong Kong, is chosen as a case study. The results show that the proposed method catches eigenvalues and eigenvectors even for a reduced number of sensors, without any significant loss of accuracy.

• Journal of Sensor Science and Technology
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• v.17 no.1
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• pp.15-22
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• 2008

When designing image sensors including a CMOS vision chip for edge detection, resolution is a significant factor to evaluate the performance. It is hard to improve the resolution of a bio-inspired CMOS vision using a resistive network because the vision chip contains many circuits such as a resistive network and several signal processing circuits as well as photocircuits of general image sensors such as CMOS image sensor (CIS). Low resolution restricts the use of the application systems. In this paper, we improve the resolution through layout and circuit optimization. Furthermore, we have designed a printed circuit board using FPGA which controls the vision chip. The vision chip for edge detection has been designed and fabricated by using $0.35{\mu}m$ double-poly four-metal CMOS technology, and its output characteristics have been investigated.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2000.04a
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• pp.6-7
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• 2000

Recently, free radicals such as active oxygen species, nitric oxide, etc are believed to be one of the key substances in physiological and pathological, toxicological phenomena, and oxidative damages, and all organism have defencing system against such as free radicals. Formation and extinction of free radicals may be regulated through bio-redox system, in which various enzymes and compounds should be involved in very complicated manner. Thus, direct and non-invasive measurement of in vivo free radical reactions with living animals must be essential to understand the role of free radicals in pathophysiological phenomena. Electron spin resonance spectroscopy (ESR) is very selective and sensitive technique to detect free radicals, but a conventional ESR spectrometer has large detect in application to living animals, since high frequent microwave is absorbed with water, resulting in generation of high fever in living body. In order to estimate in vivo free radical reactions in living whole animals, we develop in vivo ESR-CT technique using nitroxide radicals as spin probes. Nitroxide radicals and their reduced forms, hydroxylamines, are known to interact with various redox systems. We found that! ! the signal decay due to reduction of nitroxyl radicals is influenced by aging, inspired oxygen concentration, ischemia-referfusion injury, radiation, etc. In the present paper, I will introduce in vivo ESR technique and my laboratory recent results concerning non-invasive evaluation of free radical reactions in living mice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1042-1062
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• 2010

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.