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Surgical robotics: A look-back of latest advancement and bio-inspired ways to tackle existing challenges

Yang LIU, Jing LIU

Frontiers of Mechanical Engineering 2012, Volume 7, Issue 4,   Pages 376-384 doi: 10.1007/s11465-012-0352-1

Abstract: perform an exhaustive evaluation, we would emphasize more on the new insight by digesting the emerging bio-inspiredAs an alternative, bio-inspired methods or materials may shed light on new innovations.

Keywords： minimally invasive surgery     surgical robotics     haptic feedback     miniaturization     bio-inspiration     bionics    

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Engineering platelet-mimicking drug delivery vehicles

Quanyin Hu, Hunter N. Bomba, Zhen Gu

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 4,   Pages 624-632 doi: 10.1007/s11705-017-1614-6

Abstract: Platelets dynamically participate in various physiological processes, including wound repair, bacterial clearance, immune response, and tumor metastasis. Recreating the specific biological features of platelets by mimicking the structure of the platelet or translocating the platelet membrane to synthetic particles holds great promise in disease treatment. This review highlights recent advancements made in the platelet-mimicking strategies. The future opportunities and translational challenges are also discussed.

Keywords： drug delivery     platelets     nanomedicine     bio-inspired     biomimetic    

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Dolphin swarm algorithm Article

Tian-qi WU,Min YAO,Jian-hua YANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 8,   Pages 717-729 doi: 10.1631/FITEE.1500287

Abstract: By adopting the distributed problem-solving strategy, swarm intelligence algorithms have been successfully applied to many optimization problems that are difficult to deal with using traditional methods. At present, there are many well-implemented algorithms, such as particle swarm optimization, genetic algorithm, artificial bee colony algorithm, and ant colony optimization. These algorithms have already shown favorable performances. However, with the objects becoming increasingly complex, it is becoming gradually more difficult for these algorithms to meet human’s demand in terms of accuracy and time. Designing a new algorithm to seek better solutions for optimization problems is becoming increasingly essential. Dolphins have many noteworthy biological characteristics and living habits such as echolocation, information exchanges, cooperation, and division of labor. Combining these biological characteristics and living habits with swarm intelligence and bringing them into optimization problems, we propose a brand new algorithm named the ‘dolphin swarm algorithm’ in this paper. We also provide the definitions of the algorithm and specific descriptions of the four pivotal phases in the algorithm, which are the search phase, call phase, reception phase, and predation phase. Ten benchmark functions with different properties are tested using the dolphin swarm algorithm, particle swarm optimization, genetic algorithm, and artificial bee colony algorithm. The convergence rates and benchmark function results of these four algorithms are compared to testify the effect of the dolphin swarm algorithm. The results show that in most cases, the dolphin swarm algorithm performs better. The dolphin swarm algorithm possesses some great features, such as first-slow-then-fast convergence, periodic convergence, local-optimum-free, and no specific demand on benchmark functions. Moreover, the dolphin swarm algorithm is particularly appropriate to optimization problems, with more calls of fitness functions and fewer individuals.

Keywords： Swarm intelligence     Bio-inspired algorithm     Dolphin     Optimization    

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Bio-inspired cryptosystem on the reciprocal domain: DNA strands mutate to secure health data Research Articles

S. Aashiq Banu, Rengarajan Amirtharajan,aashiqbanu@sastra.ac.in,amir@ece.sastra.edu

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 7,   Pages 940-956 doi: 10.1631/FITEE.2000071

Abstract: The proposed chaos- cryptic system operates on the integer wavelet transform (IWT) domain and a bio-inspired

Keywords： 医学图像加密；DNA；混沌吸引子；交叉；突变；电子医疗    

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Learning Rat-Like Behavior for a Small-Scale Biomimetic Robot

Zihang Gao, Guanglu Jia, Hongzhao Xie, Qiang Huang, Toshio Fukuda, Qing Shi

Engineering 2022, Volume 17, Issue 10,   Pages 232-243 doi: 10.1016/j.eng.2022.05.012

Abstract: rat has six typical behaviors in the open
field, and each kind of behavior contains different bio-inspired

Keywords： Biomimetic     Bio-inspired robot     Neural network learning system     Behavior generation    

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Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification None

Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM, Naveed Ishtiaq CHAUDHARY, Wasim Ullah KHAN

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 2,   Pages 246-259 doi: 10.1631/FITEE.1601028

Abstract: In this study, hybrid computational frameworks are developed for active noise control (ANC) systems using an evolutionary computing technique based on genetic algorithms (GAs) and interior-point method (IPM), following an integrated approach, GA-IPM. Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for optimization of coefficients for the linear finite-impulse response filter, but are likely to become trapped in local minima (LM). This issue is addressed with the proposed GA-IPM computing approach which is considerably less prone to the LM problem. Also, there is no requirement to identify a secondary path for the ANC system used in the scheme. The design method is evaluated using an ANC model of a headset with sinusoidal, random, and complex random noise interferences under several scenarios based on linear and nonlinear primary and secondary paths. The accuracy and convergence of the proposed scheme are validated based on the results of statistical analysis of a large number of independent runs of the algorithm.

Keywords： Active noise control (ANC)     Filtered extended least mean square (FXLMS)     Memetic computing     Genetic algorithms     Interior-point method    

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Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

Frontiers in Energy 2014, Volume 8, Issue 2,   Pages 254-260 doi: 10.1007/s11708-014-0302-1

Abstract: The application of a quantum-inspired firefly algorithm was introduced to obtain optimal power quality

Keywords： quantum-inspired binary firefly algorithm     topological monitor reach area     power quality    

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Creative design inspired by biological knowledge: Technologies and methods

Runhua TAN, Wei LIU, Guozhong CAO, Yuan SHI

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 1,   Pages 1-14 doi: 10.1007/s11465-018-0511-0

Abstract: To identify the technologies and methods that can facilitate the development of biologically inspiredbiological-knowledge-based theories and methods and examines the application of biological-knowledge-inspiredresearch thoroughly examines the four dimensions of key technologies that underlie the biologically inspired

Keywords： creative design     biologically inspired methods     key technologies    

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 3,   Pages 665-681 doi: 10.1007/s11709-021-0713-0

Abstract: The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (Rtest = 0.923) and minimum root mean square error value (RMSEtest = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

Keywords： long contraction scour     prediction     uncertainty     ANFIS model     meta-heuristic algorithm    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 814-828 doi: 10.1007/s11465-021-0650-6

Abstract: this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired

Keywords： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network     decision tree    

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Bio-based Technologies for Resource Recovery

Aijie Wang, David Stuckey

Frontiers of Environmental Science & Engineering 2018, Volume 12, Issue 4, doi: 10.1007/s11783-018-1079-y

Abstract:

Keywords： valign=     top     class=     J_zhaiyao    

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concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 61-79 doi: 10.1007/s11709-020-0684-6

Abstract: Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C–O, C–W, C–F, O–W, O–F, and W–F), trivariate (C–O–W, C–W–F, O–W–F), and four-variate (C–O–W–F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS–DE– (O) (MP= 0.96), ANFIS–PSO– (C-O) (MP= 0.88), ANFIS–DE– (O–W–F) (MP= 0.94), and ANFIS–PSO– (C–O–W–F) (MP= 0.89), respectively. ANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

Keywords： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive    

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Biologically inspired model of path integration based on head direction cells and grid cells

Yang ZHOU,De-wei WU

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 5,   Pages 435-448 doi: 10.1631/FITEE.1500364

Abstract: To provide a bionic approach for the vehicle to achieve path integration, we present a biologically inspired

Keywords： Head direction cells (HDCs)     Grid cells (GCs)     Path integration     Bionic navigation    

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Combustion characteristics and kinetics of bio-oil

Ruixia ZHANG, Zhaoping ZHONG, Yaji HUANG

Frontiers of Chemical Science and Engineering 2009, Volume 3, Issue 2,   Pages 119-124 doi: 10.1007/s11705-009-0068-x

Abstract: The combustion characteristics of bio-oils derived from rice husk and corn were studied by thermogravimetryin air and nitrogen atmosphere, we analyzed the combustion characteristics of different kinds of bio-oilsin different atmospheres and worked out the combustion kinetics parameters of the bio-oil, providingreliable base data for the burning of bio-oil.The thermogravimetry indicated that the combustion process of bio-oil was divided into three stages.

Keywords： bio-oil     combustion characteristics     combustion kinetics    

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Prospect and Technology Progress of Bio-diesel Industry

Ji Xing,Xi Xiaolin,Kong Linhe,Li Junfeng,Li Li

Strategic Study of CAE 2002, Volume 4, Issue 9,   Pages 86-93

Abstract:

The current situation of research, application and development of bio-diesel industry all over theworld is reviewed in this article, and the problem in the preparation and application of bio-dieselThe importance of bio-diesel industry to the national petroleum supply, national economy and re-adjustmentThe prospect and development pattern of bio-diesel industry in China are pointed out as well.

Keywords： bio-diesel     bio-diesel preparation     bio-diesel industry    

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Title Author Date Type Operation

Surgical robotics: A look-back of latest advancement and bio-inspired ways to tackle existing challenges

Yang LIU, Jing LIU

Journal Article

Engineering platelet-mimicking drug delivery vehicles

Quanyin Hu, Hunter N. Bomba, Zhen Gu

Journal Article

Dolphin swarm algorithm

Tian-qi WU,Min YAO,Jian-hua YANG

Journal Article

Bio-inspired cryptosystem on the reciprocal domain: DNA strands mutate to secure health data

S. Aashiq Banu, Rengarajan Amirtharajan,aashiqbanu@sastra.ac.in,amir@ece.sastra.edu

Journal Article

Learning Rat-Like Behavior for a Small-Scale Biomimetic Robot

Zihang Gao, Guanglu Jia, Hongzhao Xie, Qiang Huang, Toshio Fukuda, Qing Shi

Journal Article

Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification

Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM, Naveed Ishtiaq CHAUDHARY, Wasim Ullah KHAN

Journal Article

Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

Journal Article

Creative design inspired by biological knowledge: Technologies and methods

Runhua TAN, Wei LIU, Guozhong CAO, Yuan SHI

Journal Article

Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

Journal Article

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Journal Article

Bio-based Technologies for Resource Recovery

Aijie Wang, David Stuckey

Journal Article

concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Journal Article

Biologically inspired model of path integration based on head direction cells and grid cells

Yang ZHOU,De-wei WU

Journal Article

Combustion characteristics and kinetics of bio-oil

Ruixia ZHANG, Zhaoping ZHONG, Yaji HUANG

Journal Article

Prospect and Technology Progress of Bio-diesel Industry

Ji Xing,Xi Xiaolin,Kong Linhe,Li Junfeng,Li Li

Journal Article