• Title, Summary, Keyword: bio-inspired

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Bio-Inspired Object Recognition Using Parameterized Metric Learning

  • Li, Xiong;Wang, Bin;Liu, Yuncai
    • 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.

Optimal design of bio-inspired isolation systems using performance and fragility objectives

  • Hu, Fan;Shi, Zhiguo;Shan, Jiazeng
    • 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.

Bio-inspired neuro-symbolic approach to diagnostics of structures

  • Shoureshi, Rahmat A.;Schantz, Tracy;Lim, Sun W.
    • 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.

Bio-inspired Node Selection and Multi-channel Transmission Algorithm in Wireless Sensor Networks (무선 센서망에서 생체시스템 기반의 전송노드 선택 및 다중 채널 전송 알고리즘)

  • Son, Jae Hyun;Yang, Yoon-Gi;Byun, Hee-Jung
    • Journal of Internet Computing and Services
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    • v.15 no.5
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    • pp.1-7
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    • 2014
  • WireWireless sensor networks(WSNs) are generally comprised of densely deployed sensor nodes, which causes highly redundant sensor data transmission and energy waste. Many studies have focused on energy saving in WSNs. However, delay problem also should be taken into consideration for mission-critical applications. In this paper, we propose a BISA (Bio-Inspired Scheduling Algorithm) to reduce the energy consumption and delay for WSNs inspired by biological systems. BISA investigates energy-efficient routing path and minimizes the energy consumption and delay using multi-channel for data transmission. Through simulations, we observe that the BISA archives energy efficiency and delay guarantees.

Artificial Adhesive Surfaces Mimicking Gecko Setae: Novel Approaches in Surface Engineering

  • Singh, R. Arvind;Yoon, Eui-Sung
    • KSTLE International Journal
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    • v.9 no.1_2
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    • pp.13-16
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    • 2008
  • Surface Engineering is a field closely related to Tribology. Surfaces are engineered to reduce adhesion, friction and wear between moving components in engineering applications. On the contrary, it is also necessary to have high adhesion between surfaces so as to hold/stick surfaces together. In this context, surface engineering plays an important role. In recent times, scientists are drawing inspiration from nature to create effective artificial adhesive surfaces. This article provides some examples of novel surface engineering approaches conducted by various research groups worldwide that have significantly contributed in the creation of bio-inspired artificial adhesive surfaces.