• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.819-833
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• 2013

Computing global features based on local features using a bio-inspired framework has shown promising performance. However, for some tough applications with large intra-class variances, a single local feature is inadequate to represent all the attributes of the images. To integrate the complementary abilities of multiple local features, in this paper we have extended the efficacy of the bio-inspired framework, HMAX, to adapt heterogeneous features for global feature extraction. Given multiple global features, we propose an approach, designated as parameterized metric learning, for high dimensional feature fusion. The fusion parameters are solved by maximizing the canonical correlation with respect to the parameters. Experimental results show that our method achieves significant improvements over the benchmark bio-inspired framework, HMAX, and other related methods on the Caltech dataset, under varying numbers of training samples and feature elements.

• Smart Structures and Systems
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• v.7 no.3
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.1022-1032
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• 2012

In OFDMA-based wireless mesh networks, synchronization of carrier frequencies among adjacent nodes is known to be difficult. In this paper, a distributed synchronization technique is proposed to solve the synchronization problem in OFDMA-based wireless mesh networks by using the bio-inspired algorithm. In the proposed approach, carrier frequencies of all nodes in a mesh network are converged into one frequency by locally synchronizing the frequencies of adjacent nodes. It may take a long time to be converged in some topologies since the convergence characteristic of carrier frequencies in a mesh network may vary depending on the size of the network and deployment of nodes. It is shown that fast frequency synchronization, not heavily depending on the topology, can be achieved through the proposed algorithm with an adjustable weight.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

• Bulletin of the Korean Chemical Society
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• v.30 no.9
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• pp.2165-2168
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• 2009

• KIEE International Transactions on Electrophysics and Applications
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• v.4C no.4
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• pp.160-164
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• 2004

In this study, we demonstrate for the first time a bio-inspired Cell-Microsystem to manipulate and detect living cells. Cultured retinal pigment epithelial cell line (ARPE-19) was directed to grow in a pre-defined Cell-Microsystem. The three-dimensional micropillars of 5 ${\mu}{\textrm}{m}$ in height and diameter of the Cell-Microsystem were fabricated. Inhibited DNA synthesis and transformed cell morphology were observed throughout the culture period. The demonstration of manipulating and detecting living cells by the surface topography is a new approach, and it will be very useful for the future design of cell-based biosensors and bioactuators.

• Smart Structures and Systems
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• v.5 no.2
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• pp.139-152
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• 2009

Globally, civil infrastructures are deteriorating at an alarming rate caused by overuse, overloading, aging, damage or failure due to natural or man-made hazards. With such a vast network of deteriorating infrastructure, there is a growing interest in continuous monitoring technologies. In order to provide a true distributed sensor and control system for civil structures, we are developing a Structural Nervous System that mimics key attributes of a human nervous system. This nervous system is made up of building blocks that are designed based on mechanoreceptors as a fundamentally new approach for the development of a structural health monitoring and diagnostic system that utilizes the recently developed piezo-fibers capable of sensing and actuation. In particular, our research has been focused on producing a sensory nervous system for civil structures by using piezo-fibers as sensory receptors, nerve fibers, neuronal pools, and spinocervical tract to the nodal and central processing units. This paper presents up to date results of our research, including the design and analysis of the structural nervous system.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.202-202
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• 2011

The research of 3-dimensional (3-D) scaffold for tissue engineering has been widely investigated as the importance of the 3-D scaffold increased. 3-D scaffold is needed to support for cells to proliferate and maintain their biological functions. Furthermore, its architecture defines the shape of the new bone and cartilage growth. Polycaprolactone (PCL) has been one of the most promising materials for fabricating 3-D scaffold owing to its excellent mechanical property and biocompatibility. However, there are practical problems for using it, in vitro and in vivo; extracellular matrix components and nutrients cannot penetrate into the inner space of scaffold, due to its hydrophobic property, and thus cell seeding and attachment onto the inner surface remain as a challenge. Thus, the surface modification strategy of 3-D PCL scaffold is prerequisite for successful tissue engineering. Herein, we utilized a mussel-inspired approach for surface modification of 3-D PCL scaffold. Modification of 3-D PCL scaffolds was carried out by simple immersion of scaffolds into the dopamine solution and stimulated body fluid, and as a result, hydroxyapatite-immobilized 3-D PCL scaffolds were obtained. After surface modification, the wettability of 3-D PCL scaffold was considerably changed, and infiltration of the pre-osteoblastic cells into the 3-D scaffold followed by the attachment onto the surface was successfully achieved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2225-2239
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• 2021

To assist in data collection, the use of a mobile sink has been widely suggested in the literature. Due to the limited sensor node's storage capacity, this manner to collect data induces huge latencies and drop packets. Their buffers will be overloaded and lead to network congestion. Recently, a new bio-inspired optimization algorithm appeared. Researchers were inspired by the swarming mechanism of salps and thus creating what is called the Salp Swarm Algorithm (SSA). This paper improves the sink mobility to enhance energy dissipation, throughput, and convergence speed by imitating the salp's movement. The new approach, named the Mobile Sink based on Modified Salp Swarm Algorithm (MSSA), is approved in a heterogeneous Wireless Sensor Network (WSN) data collection. The performance of the MSSA protocol is assessed using several iterations. Results demonstrate that our proposal surpass other literature algorithms in terms of lifespan and throughput.

• Smart Structures and Systems
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• v.20 no.3
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• pp.311-328
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• 2017

The characteristics of boundary layers have significant effects on the aerodynamic forces and vibration of the wind turbine blade. The incorporation of active trailing edge flaps (ATEF) into wind turbine blades has been proven as an effective control approach for alleviation of load and vibration. This paper is aimed at investigating the effects of external trailing edge flaps on the flow pattern and velocity distribution within a boundary layer of a NREL 5MW reference wind turbine, as well as designing a new type of velocity sensors for future validation measurements. An aeroelastic-aerodynamic simulation with FAST-AeroDyn code was conducted on the entire wind turbine structure and the modifications were made on turbine blade sections with ATEF. The results of aeroelastic-aerodynamic simulations were combined with the results of two-dimensional computational fluid dynamic simulations. From these, the velocity profile of the boundary layer as well as the thickness variation with time under the influence of a simplified load case was calculated for four different blade-flap combinations (without flap, with $-5^{\circ}$, $0^{\circ}$, and $+5^{\circ}$ flap). In conjunction with the computational modeling of the characteristics of boundary layers, a bio-inspired hair flow sensor was designed for sensing the boundary flow field surrounding the turbine blades, which ultimately aims to provide real time data to design the control scheme of the flap structure. The sensor element design and performance were analyzed using both theoretical model and finite element method. A prototype sensor element with desired bio-mimicry responses was fabricated and validated, which will be further refined for integration with the turbine blade structures.