• Title/Summary/Keyword: bio-inspired data analysis

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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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    • 제7권3호
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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.

A Bio-inspired Hybrid Cross-Layer Routing Protocol for Energy Preservation in WSN-Assisted IoT

  • Tandon, Aditya;Kumar, Pramod;Rishiwal, Vinay;Yadav, Mano;Yadav, Preeti
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권4호
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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.

Biologically Inspired Node Scheduling Control for Wireless Sensor Networks

  • Byun, Heejung;Son, Sugook;Yang, Soomi
    • Journal of Communications and Networks
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    • 제17권5호
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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.

Implementation of a bio-inspired two-mode structural health monitoring system

  • Lin, Tzu-Kang;Yu, Li-Chen;Ku, Chang-Hung;Chang, Kuo-Chun;Kiremidjian, Anne
    • Smart Structures and Systems
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    • 제8권1호
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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.

Aeroelastic-aerodynamic analysis and bio-inspired flow sensor design for boundary layer velocity profiles of wind turbine blades with active external flaps

  • Sun, Xiao;Tao, Junliang;Li, Jiale;Dai, Qingli;Yu, Xiong
    • Smart Structures and Systems
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    • 제20권3호
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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.

DNA Chip 데이터의 군집화 성능 향상을 위한 Particle Swarm Optimization 알고리즘의 적용기법 (Applying Particle Swarm Optimization for Enhanced Clustering of DNA Chip Data)

  • 이민수
    • 정보처리학회논문지D
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    • 제17D권3호
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    • pp.175-184
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    • 2010
  • 최근 DNA 칩의 등장으로 유전자 관련 실험과 연구가 매우 용이해졌으며 이를 활용한 다양한 실험 결과로 대량의 데이터가 제공되고 있다. DNA칩에 의해 제공된 데이터는 2차원 행렬로 표현되며 하나의 축은 유전자를 나타내고 다른 하나의 축은 샘플정보를 나타낸다. 이러한 데이터에 대하여 빠른 시간 안에 좋은 품질의 군집화를 수행함으로써 이후의 분석 단계인 분류화 작업의 정확도와 효율성을 높일 수 있다. 본 논문에서는 생태계 모방 알고리즘의 하나인 Particle Swarm Optimization 알고리즘을 사용하여 방대한 양의 DNA칩 데이터에 대한 효율적인 군집화 기법을 제안하였으며 실험을 통해서 PSO 기반의 군집화 알고리즘이 기존의 군집화 알고리즘들보다 수행속도 및 품질 면에서 우수한 성능을 가짐을 보였다.

In vitro antioxidative and anti-inflammatory effects of the compound K-rich fraction BIOGF1K, prepared from Panax ginseng

  • Hossen, Muhammad Jahangir;Hong, Yong Deog;Baek, Kwang-Soo;Yoo, Sulgi;Hong, Yo Han;Kim, Ji Hye;Lee, Jeong-Oog;Kim, Donghyun;Park, Junseong;Cho, Jae Youl
    • Journal of Ginseng Research
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    • 제41권1호
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    • pp.43-51
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    • 2017
  • Background: BIOGF1K, a compound K-rich fraction prepared from the root of Panax ginseng, is widely used for cosmetic purposes in Korea. We investigated the functional mechanisms of the anti-inflammatory and antioxidative activities of BIOGF1K by discovering target enzymes through various molecular studies. Methods: We explored the inhibitory mechanisms of BIOGF1K using lipopolysaccharide-mediated inflammatory responses, reporter gene assays involving overexpression of toll-like receptor adaptor molecules, and immunoblotting analysis. We used the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay to measure the antioxidative activity. We cotransfected adaptor molecules, including the myeloid differentiation primary response gene 88 (MyD88) and Toll/interleukin-receptor domain containing adaptor molecule-inducing interferon-${\beta}$ (TRIF), to measure the activation of nuclear factor (NF)-${\kappa}B$ and interferon regulatory factor 3 (IRF3). Results: BIOGF1K suppressed lipopolysaccharide-triggered NO release in macrophages as well as DPPH-induced electron-donating activity. It also blocked lipopolysaccharide-induced mRNA levels of interferon-${\beta}$ and inducible nitric oxide synthase. Moreover, BIOGF1K diminished the translocation and activation of IRF3 and NF-${\kappa}B$ (p50 and p65). This extract inhibited the upregulation of NF-${\kappa}B$-linked luciferase activity provoked by phorbal-12-myristate-13 acetate as well as MyD88, TRIF, and inhibitor of ${\kappa}B$ ($I{\kappa}B{\alpha}$) kinase ($IKK{\beta}$), and IRF3-mediated luciferase activity induced by TRIF and TANK-binding kinase 1 (TBK1). Finally, BIOGF1K downregulated the NF-${\kappa}B$ pathway by blocking $IKK{\beta}$ and the IRF3 pathway by inhibiting TBK1, according to reporter gene assays, immunoblotting analysis, and an AKT/$IKK{\beta}$/TBK1 overexpression strategy. Conclusion: Overall, our data suggest that the suppression of $IKK{\beta}$ and TBK1, which mediate transcriptional regulation of NF-${\kappa}B$ and IRF3, respectively, may contribute to the broad-spectrum inhibitory activity of BIOGF1K.