• Structural Engineering and Mechanics
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• v.88 no.3
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• pp.221-238
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• 2023

This paper developed and examined a novel passive vibration isolator (i.e., "X-inerter") motivated by combining a bio-inspired structure and a rack-pinion inerter. The bio-inspired structure provided nonlinear stiffness and damping owing to its geometric nonlinearity. In addition, the behavior was further enhanced by a gear inerter that produced a special nonlinear inertia effect; thus, an X-inerter was developed. As a result, the X-inerter can achieve both high-static-low-dynamic stiffness (HSLDS) and quasi-zero stiffness (QZS), obtaining ultra-low frequency isolation. Furthermore, the installed inerter can produce a coupled nonlinear inertia and damping effect, leading to an anti-resonance frequency near the resonance, wide isolation region, and low resonance peak. Both static and dynamic analyses of the proposed isolator were conducted and the structural parameters' influence was comprehensively investigated. The X-inerter was proven to be comparatively more stable in the ultra-low frequency than the benchmarking QZS isolator due to the nonlinear damping and inertia properties. Moreover, the inertia effect could suppress the bio-inspired structure's super- and sub-harmonic resonance. Therefore, the X-inerter isolator generally possesses desirable nonlinear stiffness, nonlinear damping, and unique nonlinear inertia, designed to achieve the ultra-low natural frequency, the anti-resonance property, and a wide isolation region with a low resonance peak.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.59-60
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.53-54
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• 2013

• Advances in robotics research
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• v.2 no.1
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• pp.1-11
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• 2018

To monitor the environment and determine the source of a pollutant gradient using a multiple robot swarm, we propose a hybrid algorithm that combines two bio-inspired algorithms mimicking chemotaxis and pheromones of bacteria. The algorithm is implemented in virtual robot agents in a simulator to evaluate their feasibility and efficiency in gradient maps with different sizes. Simulation results show that the chemotaxis controller guided robot agents to the locations with higher pollutant concentrations, while the pheromone marked in a virtual field increased the efficiency of the search by reducing the visiting redundancy. The number of steps required to reach the target point did not increase proportionally as the map size increased, but were less than those in the linear whole-map search method. Furthermore, the robot agents could function with simple sensor composition, minimum information about the map, and low calculation capacity.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.506-516
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• 2015

Wireless sensor networks (WSNs) are generally comprised of densely deployed sensor nodes, which results in highly redundant sensor data transmissions and energy waste. Since the sensor nodes depend on batteries for energy, previous studies have focused on designing energy-efficient medium access control (MAC) protocols to extend the network lifetime. However, the energy-efficient protocols induce an extra end-to-end delay, and therefore recent increase in focus on WSNs has led to timely and reliable communication protocols for mission-critical applications. In this paper, we propose an energy efficient and delay guaranteeing node scheduling scheme inspired by biological systems, which have gained considerable attention as a computing and problem solving technique.With the identification of analogies between cellular signaling systems and WSN systems, we formulate a new mathematical model that considers the networking challenges of WSNs. The proposed bio-inspired algorithm determines the state of the sensor node, as required by each application and as determined by the local environmental conditions and the states of the adjacent nodes. A control analysis shows that the proposed bio-inspired scheme guarantees the system stability by controlling the parameters of each node. Simulation results also indicate that the proposed scheme provides significant energy savings, as well as reliable delay guarantees by controlling the states of the sensor nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1273-1293
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• 2010

Immune-inspired intrusion detection is a promising technology for network security, and well known for its diversity, adaptation, self-tolerance, etc. However, scalability and coverage are two major drawbacks of the immune-inspired intrusion detection systems (IIDSes). In this paper, we propose an IIDS framework, named GEP-IIDS, with improved basic system elements to address these two problems. First, an additional bio-inspired technique, gene expression programming (GEP), is introduced in detector (corresponding to detection rules) representation. In addition, inspired by the avidity model of immunology, new avidity/affinity functions taking the priority of attributes into account are given. Based on the above two improved elements, we also propose a novel immune algorithm that is capable of integrating two bio-inspired mechanisms (i.e., negative selection and positive selection) by using a balance factor. Finally, a pruning algorithm is given to reduce redundant detectors that consume footprint and detection time but do not contribute to improving performance. Our experimental results show the feasibility and effectiveness of our solution to handle the scalability and coverage problems of IIDS.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.57-66
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• 2014

This paper describes the design concept of a bio-inspired legged underwater and estimating its performance by implementing simulations. Especially the leg structure of an underwater organism, diving beetles, is fully adopted to our designing to employ its efficiency for swimming. To make it possible for the robot to both walk and swim, the transformable kinematic model according to applications of the leg is proposed. To aid in the robot development and estimate swimming performance of the robot in advance, an underwater simulator has been constructed and an approximated model based on the developing robot was set up in the simulation. Furthermore, previous work that we have done, the swimming locomotion produced by a swimming patten generator based on the control parameters, is briefly mentioned in the paper and adopted to the simulation for extensive studies such as path planning and control techniques. Through the results, we established the strategy of leg joints which make the robot swim in the three dimensional space to reach effective controls.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2205-2217
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• 2015

Bio-inspired routing protocol uses a principle of swarm intelligence, which finds the optimal path to the destination in a distributed and autonomous way in dynamic environments, so that it can maximize routing performances, reduce control overhead, and recover a path failure quickly according to the change of network topology. In this paper, we propose a bio-inspired routing protocol for mobile ad hoc networks. The proposed scheme uses a function of overhearing via wireless media in order to obtain the routing information without additional overhead. Through overhearing, the pheromone is diffused around the shortest path between the source and destination. Based on this diffused pheromone, a probabilistic path exploration is executed and the useful alternative routes between the source and destination are collected. Therefore, the proposed routing protocol can ensure the up-to-date routing information while reducing the control overhead. The simulation results show that the proposed scheme outperforms the typical AODV and AntHocNet protocols in terms of routing performances and significantly decreases the routing overhead against the AntHocNet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.74-90
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• 2014

Routing in mobile wireless sensor networks (MWSNs) is an extremely challenging issue due to the features of MWSNs. In this paper, we present a novel bio-inspired trusted routing protocol (B-iTRP) based on artificial immune system (AIS), ant colony optimization (ACO) and Physarum optimization (PO). For trust mechanism, B-iTRP monitors neighbors' behavior in real time and then assesses neighbors' trusts based on AIS. For routing strategy, each node proactively finds routes to the Sink based on ACO. When a backward ant is on the way to return source, it senses the energy residual and trust value of each node on the discovered route, and calculates the link trust and link energy of the route. Moreover, B-iTRP also assesses the availability of route based on PO to maintain the route table. Simulation results show how B-iTRP can achieve the effective performance compared to existing state-of-the-art algorithms.