• Steel and Composite Structures
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• v.46 no.6
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• pp.759-772
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• 2023

This manuscript presents a comprehensive mathematical model to investigate buckling stability and postbuckling response of bio-inspired composite beams with helicoidal orientations. The higher order shear deformation theory as well as the Timoshenko beam theories are exploited to include the shear influence. The equilibrium nonlinear integro-differential equations of helicoidal composite beams are derived in detail using the energy conservation principle. Differential integral quadrature method (DIQM) is employed to discretize the nonlinear system of differential equations and solve them via the Newton iterative method then obtain the response of helicoidal composite beam. Numerical calculations are carried out to check the validity of the present solution methodology and to quantify the effects of helicoidal rotation angle, elastic foundation constants, beam theories, geometric and material properties on buckling, postbuckling of bio-inspired helicoidal composite beams. The developed model can be employed in design and analysis of curved helicoidal composite beam used in aerospace and naval structures.

• 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.

• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.325-343
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• 2018

This study aims to propose a performance-based design method of a novel passive base isolation system, BIO isolation system, which is inspired by an energy dissipation mechanism called 'sacrificial bonds and hidden length'. Fragility functions utilized in this study are derived, indicating the probability that a component, element, or system will be damaged as a function of a single predictive demand parameter. Based on PEER framework methodology for Performance-Based Earthquake Engineering (PBEE), a systematic design procedure using performance and fragility objectives is presented. Base displacement, superstructure absolute acceleration and story drift ratio are selected as engineering demand parameters. The new design method is then performed on a general two degree-of-freedom (2DOF) structure model and the optimal design under different seismic intensities is obtained through numerical analysis. Seismic performances of the biologically inspired (BIO) isolation system are compared with that of the linear isolation system. To further demonstrate the feasibility and effectiveness of this method, the BIO isolation system of a 4-storey reinforced concrete building is designed and investigated. The newly designed BIO isolators effectively decrease the superstructure responses and base displacement under selected earthquake excitations, showing good seismic performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.141-142
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• 2012

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.3
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• pp.282-293
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• 2018

This paper attempts to address the motion parameter skip problem associated with three-dimensional trajectory tracking of an underactuated Autonomous Underwater Vehicle (AUV) using backstepping-based control, due to the unsmoothness of tracking trajectory. Through kinematics concepts, a three-dimensional dynamic velocity regulation controller is derived. This controller makes use of the surge and angular velocity errors with bio-inspired models and backstepping techniques. It overcomes the frequently occurring problem of parameter skip at inflection point existing in backstepping tracking control method and increases system robustness. Moreover, the proposed method can effectively avoid the singularity problem in backstepping control of virtual velocity error. The control system is proved to be uniformly ultimately bounded using Lyapunov stability theory. Simulation results illustrate the effectiveness and efficiency of the developed controller, which can realize accurate three-dimensional trajectory tracking for an underactuated AUV with constant external disturbances.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.331-340
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• 2008

Feature Selection is one of methods to improve the classification accuracy of data in the field of machine learning. Many feature selection algorithms have been proposed and discussed for years. However, the problem of finding the optimal feature subset from full data still remains to be a difficult problem. Bio-inspired algorithms are well-known evolutionary algorithms based on the principles of behavior of organisms, and very useful methods to find the optimal solution in optimization problems. Bio-inspired algorithms are also used in the field of feature selection problems. So in this paper we proposed new improved bio-inspired algorithms for feature selection. We used well-known bio-inspired algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to find the optimal subset of features that shows the best performance in classification accuracy. In addition, we modified the bio-inspired algorithms considering the prior importance (prior relevance) of each feature. We chose the mRMR method, which can measure the goodness of single feature, to set the prior importance of each feature. We modified the evolution operators of GA and PSO by using the prior importance of each feature. We verified the performance of the proposed methods by experiment with datasets. Feature selection methods using GA and PSO produced better performances in terms of the classification accuracy. The modified method with the prior importance demonstrated improved performances in terms of the evolution speed and the classification accuracy.

• Advances in nano research
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• v.2 no.2
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• pp.111-119
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• 2014

The chemical synthesis of anisotropic defective polyaniline/Ag composite (PANI/Ag) is explored using silver nitrate ($AgNO_3$) as the precursor material. This study provides a simple method for the formation of PANI/Ag nanocomposites at two different aniline concentrations $5{\mu}l$ (PANC5) and $10{\mu}l$ (PANC10). The composite PANC5 exhibits UV-Visible absorption peaks at 436 nm and 670 nm whereas, PANC10 exhibits absorption peaks at 446 nm and 697 nm. This shift is caused by the strong interaction between polyaniline and silver. The characterized FTIR peaks observed at around $3410cm^{-1}$ (PANC5) and $3420cm^{-1}$ (PANC10) was due to the N-H stretching vibrations. The appearance of a broad band instead of a sharp peak can be attributed due to the presence of a high concentration of N-H groups in the nanocomposite. The TEM images show that the sample contains defective spherical, truncated triangular and rod shaped particles. The results showed that the PANI/Ag nanocomposites are composed of nano-sized particles of 43-53 nm that contain Ag domains of 33-37 nm with polymer thickness 5.7-11.2 nm at two different aniline concentrations.

• 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.

• Steel and Composite Structures
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• v.50 no.1
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• pp.25-43
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• 2024

In this article, a mathematical model is developed to predict the dynamic behavior of bio-inspired composite beam with helicoidal orientation scheme under variable axial load using a unified higher order shear deformation beam theory. The geometrical kinematic relations of displacements are portrayed with higher parabolic shear deformation beam theory. Constitutive equation of composite beam is proposed based on plane stress problem. The variable axial load is distributed through the axial direction by constant, linear, and parabolic functions. The equations of motion and associated boundary conditions are derived in detail by Hamilton's principle. Using the differential quadrature method (DQM), the governing equations, which are integro-differential equations are discretized in spatial direction, then they are transformed into linear eigenvalue problems. The proposed model is verified with previous works available in literatures. Parametric analyses are developed to present the influence of axial load type, orthotropic ratio, slenderness ratio, lamination scheme, and boundary conditions on the natural frequencies of composite beam structures. The present enhanced model can be used especially in designing spacecrafts, naval, automotive, helicopter, the wind turbine, musical instruments, and civil structures subjected to the variable axial loads.

• Smart Structures and Systems
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• v.8 no.1
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• pp.119-137
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• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.