Journal articles: 'Bioinspired Computation'

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Cui, Zhihua, Rajan Alex, Rajendra Akerkar, and Xin-She Yang. "Recent Advances on Bioinspired Computation." Scientific World Journal 2014 (2014): 1–3. http://dx.doi.org/10.1155/2014/934890.

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Hanif, Muhammad Kashif, Ramzan Talib, Muhammad Awais, Muhammad Yahya Saeed, and Umer Sarwar. "Comparison of Bioinspired Computation and Optimization Techniques." Current Science 115, no. 3 (August 1, 2018): 450. http://dx.doi.org/10.18520/cs/v115/i3/450-453.

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Botella, Guillermo, Antonio Garcia, Manuel Rodriguez-Alvarez, Eduardo Ros, Uwe Meyer-Baese, and María C. Molina. "Robust Bioinspired Architecture for Optical-Flow Computation." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 18, no. 4 (April 2010): 616–29. http://dx.doi.org/10.1109/tvlsi.2009.2013957.

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Gunji, Yukio-Pegio, and Daisuke Uragami. "Breaking of the Trade-Off Principle between Computational Universality and Efficiency by Asynchronous Updating." Entropy 22, no. 9 (September 19, 2020): 1049. http://dx.doi.org/10.3390/e22091049.

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Although natural and bioinspired computing has developed significantly, the relationship between the computational universality and efficiency beyond the Turing machine has not been studied in detail. Here, we investigate how asynchronous updating can contribute to the universal and efficient computation in cellular automata (CA). First, we define the computational universality and efficiency in CA and show that there is a trade-off relation between the universality and efficiency in CA implemented in synchronous updating. Second, we introduce asynchronous updating in CA and show that asynchronous updating can break the trade-off found in synchronous updating. Our finding spells out the significance of asynchronous updating or the timing of computation in robust and efficient computation.

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Chen, Tinggui, Jianjun Yang, Kai Huang, and Qiang Cheng. "Bioinspired Computation and Its Applications in Operation Management." Scientific World Journal 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/356571.

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Demidova, L. A., and A. V. Gorchakov. "Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines." Russian Technological Journal 10, no. 2 (April 3, 2022): 59–74. http://dx.doi.org/10.32362/2500-316x-2022-10-2-59-74.

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Objectives. Recent research in machine learning and artificial intelligence aimed at improving prediction accuracy and reducing computational complexity resulted in a novel neural network architecture referred to as an extreme learning machine (ELM). An ELM comprises a single-hidden-layer feedforward neural network in which the weights of connections among input-layer neurons and hidden-layer neurons are initialized randomly, while the weights of connections among hidden-layer neurons and output-layer neurons are computed using a generalized Moore– Penrose pseudoinverse operation. The replacement of the iterative learning process currently used in many neural network architectures with the random initialization of input weights and the explicit computation of output weights significantly increases the performance of this novel machine learning algorithm while preserving good generalization performance. However, since the random initialization of input weights does not necessarily guarantee optimal prediction accuracy, the purpose of the present work was to develop and study approaches to intelligent adjustment of input weights in ELMs using bioinspired algorithms in order to improve the prediction accuracy of this data analysis tool in regression problems.Methods. Methods of optimization theory, theory of evolutionary computation and swarm intelligence, probability theory, mathematical statistics and systems analysis were used.Results. Approaches to the intelligent adjustment of input weights in ELMs were developed and studied. These approaches are based on the genetic algorithm, the particle swarm algorithm, the fish school search algorithm, as well as the chaotic fish school search algorithm with exponential step decay proposed by the authors. By adjusting input weights with bioinspired optimization algorithms, it was shown that the prediction accuracy of ELMs in regression problems can be improved to reduce the number of hidden-layer neurons to reach a high prediction accuracy on learning and test datasets. In the considered problems, the best ELM configurations can be obtained using the chaotic fish school search algorithm with exponential step decay.Conclusions. The obtained results showed that the prediction accuracy of ELMs can be improved by using bioinspired algorithms for the intelligent adjustment of input weights. Additional calculations are required to adjust the weights; therefore, the use of ELMs in combination with bioinspired algorithms may be advisable where it is necessary to obtain the most accurate and most compact ELM configuration.

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Wang, Zhaocai, Xiaoguang Bao, and Tunhua Wu. "A Parallel Bioinspired Algorithm for Chinese Postman Problem Based on Molecular Computing." Computational Intelligence and Neuroscience 2021 (January 15, 2021): 1–13. http://dx.doi.org/10.1155/2021/8814947.

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The Chinese postman problem is a classic resource allocation and scheduling problem, which has been widely used in practice. As a classical nondeterministic polynomial problem, finding its efficient algorithm has always been the research direction of scholars. In this paper, a new bioinspired algorithm is proposed to solve the Chinese postman problem based on molecular computation, which has the advantages of high computational efficiency, large storage capacity, and strong parallel computing ability. In the calculation, DNA chain is used to properly represent the vertex, edge, and corresponding weight, and then all possible path combinations are effectively generated through biochemical reactions. The feasible solution space is obtained by deleting the nonfeasible solution chains, and the optimal solution is solved by algorithm. Then the computational complexity and feasibility of the DNA algorithm are proved. By comparison, it is found that the computational complexity of the DNA algorithm is significantly better than that of previous algorithms. The correctness of the algorithm is verified by simulation experiments. With the maturity of biological operation technology, this algorithm has a broad application space in solving large-scale combinatorial optimization problems.

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Herrmann, Sven. "Review of bioinspired computation in combinatorial optimization by Frank Neumann and Carsten Witt." ACM SIGACT News 44, no. 2 (June 3, 2013): 22–26. http://dx.doi.org/10.1145/2491533.2491540.

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Chen, Lei, Liyi Zhang, Yanju Guo, Yong Huang, and Jingyi Liang. "Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/484327.

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The computation amount in blind source separation based on bioinspired intelligence optimization is high. In order to solve this problem, we propose an effective blind source separation algorithm based on the artificial bee colony algorithm. In the proposed algorithm, the covariance ratio of the signals is utilized as the objective function and the artificial bee colony algorithm is used to solve it. The source signal component which is separated out, is then wiped off from mixtures using the deflation method. All the source signals can be recovered successfully by repeating the separation process. Simulation experiments demonstrate that significant improvement of the computation amount and the quality of signal separation is achieved by the proposed algorithm when compared to previous algorithms.

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Ayton, Lorna J. "Bioinspired aerofoil adaptations: the next steps for theoretical models." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, no. 2159 (October 14, 2019): 20190070. http://dx.doi.org/10.1098/rsta.2019.0070.

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The extended introduction in this paper reviews the theoretical modelling of leading- and trailing-edge noise, various bioinspired aerofoil adaptations to both the leading and trailing edges of blades, and how these adaptations aid in the reduction of aerofoil–turbulence interaction noise. Attention is given to the agreement between current theoretical predictions and experimental measurements, in particular, for turbulent interactions at the trailing edge of an aerofoil. Where there is a poor agreement between theoretical models and experimental data the features neglected from the theoretical models are discussed. Notably, it is known that theoretical predictions for porous trailing-edge adaptations do not agree well with experimental measurements. Previous works propose the reason for this: theoretical models do not account for surface roughness due to the porous material and thus omit a key noise source. The remainder of this paper, therefore, presents an analytical model, based upon the acoustic analogy, to predict the far-field noise due to a rough surface at the trailing edge of an aerofoil. Unlike previous roughness noise models which focus on roughness over an infinite wall, the model presented here includes diffraction by a sharp edge. The new results are seen to be in better agreement with experimental data than previous models which neglect diffraction by an edge. This new model could then be used to improve theoretical predictions for far-field noise generated by turbulent interactions with a (rough) porous trailing edge. This article is part of the theme issue ‘Frontiers of aeroacoustics research: theory, computation and experiment’.

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Lima, Wirlan Gomes, Jasmine Priscyla Leite Leite de Araújo, Fabrício José Brito Barros, Gervásio Protásio Dos Santos Cavalcante, Cássio da Cruz Nogueira, Bruno Souza Lyra Castro, and Miércio Cardoso De Alcântara Neto. "Optimization and synthesis of multilayer frequency selective surfaces via bioinspired hybrid techniques." International Journal for Innovation Education and Research 8, no. 5 (May 1, 2020): 542–61. http://dx.doi.org/10.31686/ijier.vol8.iss5.2371.

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In this study, two bioinspired computation (BIC) techniques are discussed and applied to the project and synthesis of multilayer frequency selective surfaces (FSS) within the microwave band, specifically for C, X and Ku bands. The proposed BIC techniques consist of combining an artificial, general regression neural network to a genetic algorithm (GA) and a cuckoo search algorithm, respectively. The objective is to find the optimal values of separation between the investigated FSS. Numerical analysis of the electromagnetic properties of the device is made possible with the finite integration method (FIT) and validated through the finite element method (FEM), utilizing both softwares CST Microwave Studio and Ansys HFSS respectively. Thus, the BIC-optimized devices present good phase / angular stability for angles 10°, 20°, 30° and 40°, as well as being polarization independent. The cutoff frequencies to control the operating frequency range of the FSS, referring to transmission coefficient in decibels (dB), were obtained at a threshold of –10dB. Numerical results denote good accordance with measured data.

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Sánchez, José L., María T. López, José Manuel Pastor, Ana E. Delgado, and Antonio Fernández-Caballero. "Accelerating bioinspired lateral interaction in accumulative computation for real-time moving object detection with graphics processing units." Natural Computing 18, no. 2 (June 19, 2018): 217–27. http://dx.doi.org/10.1007/s11047-018-9690-1.

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Perera, Ayomi S., and Marc-Olivier Coppens. "Re-designing materials for biomedical applications: from biomimicry to nature-inspired chemical engineering." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, no. 2138 (December 24, 2018): 20180268. http://dx.doi.org/10.1098/rsta.2018.0268.

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Gathering inspiration from nature for the design of new materials, products and processes is a topic gaining rapid interest among scientists and engineers. In this review, we introduce the concept of nature-inspired chemical engineering (NICE). We critically examine how this approach offers advantages over straightforward biomimicry and distinguishes itself from bio-integrated design, as a systematic methodology to present innovative solutions to challenging problems. The scope of application of the nature-inspired approach is demonstrated via examples from the field of biomedicine, where much of the inspiration is still more narrowly focused on imitation or bio-integration. We conclude with an outlook on prospective future applications, offered by the more systematic and mechanistically based NICE approach, complemented by rapid progress in manufacturing, computation and robotics. This article is part of the theme issue ‘Bioinspired materials and surfaces for green science and technology’.

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Bird, Jordan J., Diego R. Faria, Luis J. Manso, Anikó Ekárt, and Christopher D. Buckingham. "A Deep Evolutionary Approach to Bioinspired Classifier Optimisation for Brain-Machine Interaction." Complexity 2019 (March 13, 2019): 1–14. http://dx.doi.org/10.1155/2019/4316548.

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This study suggests a new approach to EEG data classification by exploring the idea of using evolutionary computation to both select useful discriminative EEG features and optimise the topology of Artificial Neural Networks. An evolutionary algorithm is applied to select the most informative features from an initial set of 2550 EEG statistical features. Optimisation of a Multilayer Perceptron (MLP) is performed with an evolutionary approach before classification to estimate the best hyperparameters of the network. Deep learning and tuning with Long Short-Term Memory (LSTM) are also explored, and Adaptive Boosting of the two types of models is tested for each problem. Three experiments are provided for comparison using different classifiers: one for attention state classification, one for emotional sentiment classification, and a third experiment in which the goal is to guess the number a subject is thinking of. The obtained results show that an Adaptive Boosted LSTM can achieve an accuracy of 84.44%, 97.06%, and 9.94% on the attentional, emotional, and number datasets, respectively. An evolutionary-optimised MLP achieves results close to the Adaptive Boosted LSTM for the two first experiments and significantly higher for the number-guessing experiment with an Adaptive Boosted DEvo MLP reaching 31.35%, while being significantly quicker to train and classify. In particular, the accuracy of the nonboosted DEvo MLP was of 79.81%, 96.11%, and 27.07% in the same benchmarks. Two datasets for the experiments were gathered using a Muse EEG headband with four electrodes corresponding to TP9, AF7, AF8, and TP10 locations of the international EEG placement standard. The EEG MindBigData digits dataset was gathered from the TP9, FP1, FP2, and TP10 locations.

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Shova, Sergiu, Angelica Vlad, Maria Cazacu, J. Krzystek, Andrew Ozarowski, Michal Malček, Lukas Bucinsky, et al. "Dinuclear manganese(iii) complexes with bioinspired coordination and variable linkers showing weak exchange effects: a synthetic, structural, spectroscopic and computation study." Dalton Transactions 48, no. 18 (2019): 5909–22. http://dx.doi.org/10.1039/c8dt04596h.

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Ravankar, Abhijeet, Ankit Ravankar, Yukinori Kobayashi, and Yohei Hoshino. "A Bio-Inspired Algorithm for Autonomous Task Coordination of Multiple Mobile Robots." Proceedings 4, no. 1 (November 14, 2018): 1. http://dx.doi.org/10.3390/ecsa-5-05760.

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Efficient task co-ordination is an important problem in multirobot systems. The explicit programming of each robot to perform specific tasks (e.g., cleaning) is too cumbersome and inefficient, as the areas to serve in a map may vary with time. Moreover, the number of available robots to serve may also vary, as some of the robots may be charging and not available. Improper task division can cause two or more robots to serve the same areas of the map, which is a waste of computation and resources. Hence, there is a need for a simpler scheme for the autonomous task co-ordination of multiple robots without the need for explicit programming. This paper presents a bioinspired algorithm that uses the attractive and repelling behavior of pheromones for autonomous task co-ordination. The proposed algorithm uses a node representation of navigational paths for autonomous exploration. This repelling mechanism also allows robots to capture areas or subareas of the map so that there is efficient task co-ordination, and robots work without interruption from other robots. We show through experiments that the proposed scheme enables multiple service robots to intelligently perform co-operative tasks without any explicit programming or commands.

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Falanga, Davide, Kevin Kleber, and Davide Scaramuzza. "Dynamic obstacle avoidance for quadrotors with event cameras." Science Robotics 5, no. 40 (March 18, 2020): eaaz9712. http://dx.doi.org/10.1126/scirobotics.aaz9712.

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Today’s autonomous drones have reaction times of tens of milliseconds, which is not enough for navigating fast in complex dynamic environments. To safely avoid fast moving objects, drones need low-latency sensors and algorithms. We departed from state-of-the-art approaches by using event cameras, which are bioinspired sensors with reaction times of microseconds. Our approach exploits the temporal information contained in the event stream to distinguish between static and dynamic objects and leverages a fast strategy to generate the motor commands necessary to avoid the approaching obstacles. Standard vision algorithms cannot be applied to event cameras because the output of these sensors is not images but a stream of asynchronous events that encode per-pixel intensity changes. Our resulting algorithm has an overall latency of only 3.5 milliseconds, which is sufficient for reliable detection and avoidance of fast-moving obstacles. We demonstrate the effectiveness of our approach on an autonomous quadrotor using only onboard sensing and computation. Our drone was capable of avoiding multiple obstacles of different sizes and shapes, at relative speeds up to 10 meters/second, both indoors and outdoors.

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Prieto, Alberto, Joan Cabestany, and Francisco Sandoval. "Computational intelligence and bioinspired systems." Neurocomputing 70, no. 16-18 (October 2007): 2701–3. http://dx.doi.org/10.1016/j.neucom.2006.06.009.

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Owoseni, T. A., S. G. Olukole, A. I. Gadu, I. A. Malik, and W. O. Soboyejo. "Bioinspired Design." Advanced Materials Research 1132 (December 2015): 252–66. http://dx.doi.org/10.4028/www.scientific.net/amr.1132.252.

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Bioinspired design involves the use of concepts observed in natural biological materials in engineering design. The hope is that the leveraging of biological materials in the engineering domain can lead to many technological innovations and novel products. This work presents the initial material characterization of kinixys erosa tortoise shell using a combination of x-ray diffraction, optical/scanning electron microscopy and micro-mechanical testing. The results were used in the analytical/computational modelling of shell structures. The potential implications or the results were then discussed to give fundamental understanding of deformation and stress responses of shell structures

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Geder, Jason D., Ravi Ramamurti, Dan Edwards, Trent Young, and Marius Pruessner. "Development of an Unmanned Hybrid Vehicle Using Artificial Pectoral Fins." Marine Technology Society Journal 51, no. 5 (September 1, 2017): 56–70. http://dx.doi.org/10.4031/mtsj.51.5.4.

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AbstractAn unmanned vehicle has been developed for dual use as both an aircraft and a submersible. To achieve long-range emplacement of a highly maneuverable underwater asset to a target environment, the Flimmer (Flying-Swimmer) vehicle is designed for both high-speed flight and low-speed swimming. Building on previous research in bioinspired propulsion and control systems, the vehicle employs a unique set of artificial flapping fins for underwater maneuvering, which must be considered when evaluating the flight and water landing capabilities. This paper describes the computational analysis and experimental results for all three phases of vehicle operation—flight, landing, and swimming. Computational fluid dynamics simulation results predict aero- and hydrodynamic characteristics and demonstrate landing loads on and trajectory of the vehicle. Experimental data demonstrate flight and swimming performance and validate the computational results, and experimental testing of water landing provides a comparison with computations. Results and analyses of the Flimmer vehicle performance demonstrate the operational capabilities of an unmanned hybrid vehicle for long-range flight and low-speed swimming.

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Srivatsa, Shreyas, Paweł Paćko, Leon Mishnaevsky, Tadeusz Uhl, and Krzysztof Grabowski. "Deformation of Bioinspired MXene-Based Polymer Composites with Brick and Mortar Structures: A Computational Analysis." Materials 13, no. 22 (November 17, 2020): 5189. http://dx.doi.org/10.3390/ma13225189.

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In this work, the deformation behavior of MXene-based polymer composites with bioinspired brick and mortar structures is analyzed. MXene/Polymer nanocomposites are modeled at microscale for bioinspired configurations of nacre-mimetic brick-and-mortar assembly structure. MXenes (brick) with polymer matrix (mortar) are modeled using classical analytical methods and numerical methods based on finite elements (FE). The analytical methods provide less accurate estimation of elastic properties compared to the numerical one. MXene nanocomposite models analyzed with the FE method provide estimates of elastic constants in the same order of magnitude as literature-reported experimental results. Bioinspired design of MXene nanocomposites results in an effective increase of Young’s modulus of the nanocomposite by 25.1% and strength (maximum stress capacity within elastic limits) enhanced by 42.3%. The brick and mortar structure of the nanocomposites leads to an interlocking mechanism between MXene fillers in the polymer matrix, resulting in effective load transfer, good strength, and damage resistance. This is demonstrated in this paper by numerical analysis of MXene nanocomposites subjected to quasi-static loads.

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Agbehadji, Israel Edem, Richard C. Millham, Simon James Fong, and Hongji Yang. "Bioinspired Computational Approach to Missing Value Estimation." Mathematical Problems in Engineering 2018 (2018): 1–16. http://dx.doi.org/10.1155/2018/9457821.

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Missing data occurs when values of variables in a dataset are not stored. Estimating these missing values is a significant step during the data cleansing phase of a big data management approach. The reason of missing data may be due to nonresponse or omitted entries. If these missing data are not handled properly, this may create inaccurate results during data analysis. Although a traditional method such as maximum likelihood method extrapolates missing values, this paper proposes a bioinspired method based on the behavior of birds, specifically the Kestrel bird. This paper describes the behavior and characteristics of the Kestrel bird, a bioinspired approach, in modeling an algorithm to estimate missing values. The proposed algorithm (KSA) was compared with WSAMP, Firefly, and BAT algorithm. The results were evaluated using the mean of absolute error (MAE). A statistical test (Wilcoxon signed-rank test and Friedman test) was conducted to test the performance of the algorithms. The results of Wilcoxon test indicate that time does not have a significant effect on the performance, and the quality of estimation between the paired algorithms was significant; the results of Friedman test ranked KSA as the best evolutionary algorithm.

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Maghsoudi-Ganjeh, Mohammad, Liqiang Lin, Xingzi Yang, and Xiaowei Zeng. "Computational modeling and simulation of bioinspired nacre-like composites." Journal of Materials Research 36, no. 13 (February 16, 2021): 2651–61. http://dx.doi.org/10.1557/s43578-021-00124-6.

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Ling, Jacky, and Felicia Wong Yen Myan. "Assessing Bioinspired Topographies for their Antifouling Potential Control Using Computational Fluid Dynamics (CFD)." MATEC Web of Conferences 152 (2018): 02004. http://dx.doi.org/10.1051/matecconf/201815202004.

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Biofouling is the accumulation of unwanted material on surfaces submerged or semi submerged over an extended period. This study investigates the antifouling performance of a new bioinspired topography design. A shark riblets inspired topography was designed with Solidworks and CFD simulations were antifouling performance. The study focuses on the fluid flow velocity, the wall shear stress and the appearance of vortices are to be noted to determine the possible locations biofouling would most probably occur. The inlet mass flow rate is 0.01 kgs-1 and a no-slip boundary condition was applied to the walls of the fluid domain. Simulations indicate that Velocity around the topography averaged at 7.213 x 10-3 ms-1. However, vortices were observed between the gaps. High wall shear stress is observed at the peak of each topography. In contrast, wall shear stress is significantly low at the bed of the topography. This suggests the potential location for the accumulation of biofouling. Results show that bioinspired antifouling topography can be improved by reducing the frequency of gaps between features. Linear surfaces on the topography should also be minimized. This increases the avenues of flow for the fluid, thus potentially increasing shear stresses with surrounding fluid leading to better antifouling performance.

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Villuendas-Rey, Yenny, José L. Velázquez-Rodríguez, Mariana Dayanara Alanis-Tamez, Marco-Antonio Moreno-Ibarra, and Cornelio Yáñez-Márquez. "Mexican Axolotl Optimization: A Novel Bioinspired Heuristic." Mathematics 9, no. 7 (April 3, 2021): 781. http://dx.doi.org/10.3390/math9070781.

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When facing certain problems in science, engineering or technology, it is not enough to find a solution, but it is essential to seek and find the best possible solution through optimization. In many cases the exact optimization procedures are not applicable due to the great computational complexity of the problems. As an alternative to exact optimization, there are approximate optimization algorithms, whose purpose is to reduce computational complexity by pruning some areas of the problem search space. To achieve this, researchers have been inspired by nature, because animals and plants tend to optimize many of their life processes. The purpose of this research is to design a novel bioinspired algorithm for numeric optimization: the Mexican Axolotl Optimization algorithm. The effectiveness of our proposal was compared against nine optimization algorithms (artificial bee colony, cuckoo search, dragonfly algorithm, differential evolution, firefly algorithm, fitness dependent optimizer, whale optimization algorithm, monarch butterfly optimization, and slime mould algorithm) when applied over four sets of benchmark functions (unimodal, multimodal, composite and competition functions). The statistical analysis shows the ability of Mexican Axolotl Optimization algorithm of obtained very good optimization results in all experiments, except for composite functions, where the Mexican Axolotl Optimization algorithm exhibits an average performance.

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Del Ser, Javier, Eneko Osaba, Javier Sanchez-Medina, Iztok Fister, and Iztok Fister. "Bioinspired Computational Intelligence and Transportation Systems: A Long Road Ahead." IEEE Transactions on Intelligent Transportation Systems 21, no. 2 (February 2020): 466–95. http://dx.doi.org/10.1109/tits.2019.2897377.

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Buso, Carla, Plínio Zanini, and Silvia Titotto. "Bioinspired design proposal for a new external bone fixator device." Biomedical Physics & Engineering Express 8, no. 3 (March 11, 2022): 035008. http://dx.doi.org/10.1088/2057-1976/ac5092.

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Abstract The article presents a new medical device through an authorial and interdisciplinary approach. It consists of a flexible external fixator, whose flexible property may bring advantages over rigid mechanisms. Its design was inspired by the DNA biological mechanism of condensation, while the modeling was based on the pseudo-rigid modeling technique. From the models obtained, this study conducted prototyping and computational tests to obtain a proof-of-concept of the bioinspired theory and dynamic functioning effectiveness. The prototyping relied on hot glue manufacturing and the computational simulations consisted of linear static analysis. The experimental analysis concluded that the prototype with fewer beams and thinner beams delivered better results in all three parameters: flexibility, height variation and rotation arc. In the computational analysis, among the design models with the variation of the number of beams, the model with 8 beams performed better. Concerning thickness variation, the one whose beams measured 8 mm in thickness showed better results. Among the models with length variation, the design made with 100 mm long beams better equilibrated the parameters.

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Jin, Bingyu, Hao Xu, Jicheng Peng, Kelin Lu, and Yuping Lu. "Derivative-Free Observability Analysis for Sensor Placement Optimization of Bioinspired Flexible Flapping Wing System." Biomimetics 7, no. 4 (October 26, 2022): 178. http://dx.doi.org/10.3390/biomimetics7040178.

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Observability analysis of a bioinspired flexible flapping wing system provides a measure of how well the states of flexible flapping wing micro-aerial vehicles can be estimated from real-time measurements during high-speed flight. However, the traditional observability analysis approaches have trouble in terms of lack of quantitative analysis index, high computational complexity, low accuracy, and unavailability in stochastic systems with memory, including bioinspired flexible flapping wing systems. Therefore, a novel derivative-free observability analysis method is proposed here based on the generalized polynomial chaos expansion. By formulating a surrogate model to represent the relationship between the cumulative measurement and the random initial state, the observability coefficient matrix is calculated and the observability rank condition is stated. Consequently, several observability indices are proposed to quantity the observability of the system. Altogether, the proposed method avoids the disadvantages of the traditional approaches, especially in assessing the observability degree of each state and the effect of stochastic noise on observability. The validation of the proposed method is first provided by demonstrating the equivalence between the traditional and proposed methods and subsequently by comparing the observability of the Lorenz system calculated via three different approaches. Finally, the proposed method is applied on a bioinspired flexible wing system to optimize the placement of sensors, which is consistent with the natural configuration of campaniform sensilla on the wing of the hawkmoth.

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de Souza Muñoz, Mauro Enrique, Matheus Chaves Menezes, Edison Pignaton de Freitas, Sen Cheng, Paulo Rogério de Almeida Ribeiro, Areolino de Almeida Neto, and Alexandre César Muniz de Oliveira. "xRatSLAM: An Extensible RatSLAM Computational Framework." Sensors 22, no. 21 (October 29, 2022): 8305. http://dx.doi.org/10.3390/s22218305.

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Simultaneous localization and mapping (SLAM) refers to techniques for autonomously constructing a map of an unknown environment while, at the same time, locating the robot in this map. RatSLAM, a prevalent method, is based on the navigation system found in rodent brains. It has served as a base algorithm for other bioinspired approaches, and its implementation has been extended to incorporate new features. This work proposes xRatSLAM: an extensible, parallel, open-source framework applicable for developing and testing new RatSLAM variations. Tests were carried out to evaluate and validate the proposed framework, allowing the comparison of xRatSLAM with OpenRatSLAM and assessing the impact of replacing framework components. The results provide evidence that the maps produced by xRatSLAM are similar to those produced by OpenRatSLAM when they are fed with the same input parameters, which is a positive result, and that implemented modules can be easily changed without impacting other parts of the framework.

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Kozlov, Alexey V., and Yuri P. Kondratenko. "SEARCH FOR OPTIMAL FUNCTIONS OF FUZZY SYSTEMS BASED ON BIOINSPIRED EVOLUTIONARY ALGORITHMS." Journal of Automation and Information sciences 1 (January 1, 2021): 55–75. http://dx.doi.org/10.34229/0572-2691-2021-1-5.

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Contemporary research in the field of creation and development of intelligent systems based on fuzzy logic is carried out mainly in the direction of developing highly efficient methods for their synthesis and structural-parametric optimization. In recent years, due to the intensive development of information technologies and computer hardware, bioinspired intelligent techniques of global search are quite promising for solving problems of synthesis and optimization of fuzzy systems, which include evolutionary and swarm methods, that simulate the processes of natural selection, as well as collective behavior of various groups of social animals, insects and microorganisms in nature. This paper is devoted to the development and study of a method of optimal membership functions search for fuzzy systems based on bioinspired evolutionary algorithms of global optimization. The obtained method allows finding the optimal membership functions of linguistic terms at solving the compromise problems of multicriteria structural optimization of various fuzzy systems in order to increase their efficiency, as well as to reduce the degree of complexity of further parametric optimization. In the proposed method for finding the global optimum of the problem being solved, the iterative procedures are carried out on the basis of combination of several different bioinspired evolutionary algorithms with subsequent analysis of the results obtained and the choice of the best variant of the membership function vector. The paper outlines the theoretical foundations and information model for the implementation of the computational step-by-step method for structural optimization of fuzzy systems, as well as presents various options for carrying out its search procedures. In particular, the features of the application and adaptation to the search problem to be solved of such bioinspired evolutionary algorithms as genetic, artificial immune systems and biogeographic are discussed.

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Gaudette, Jason E., Jeffrey M. Knowles, Jonathan R. Barchi, and James A. Simmons. "Computational model of a bioinspired broadband receiver for sonar clutter reduction." Journal of the Acoustical Society of America 129, no. 4 (April 2011): 2507. http://dx.doi.org/10.1121/1.3588282.

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Kicinger, Rafal, and Tomasz Arciszewski. "Bioinspired Computational Framework for Enhancing Creativity, Optimality, and Robustness in Design." Journal of Computing in Civil Engineering 23, no. 1 (January 2009): 22–33. http://dx.doi.org/10.1061/(asce)0887-3801(2009)23:1(22).

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SOTO, Sergio, Edmondo BONILLA, Alberto PORTILLA, Jose C. HERNANDEZ, Oscar ATRIANO, and Perfecto M. QUINTERO. "FOOD DELIVERY BASED ON PSO ALGORITHM AND GOOGLE MAPS." Applied Computer Science 16, no. 1 (March 30, 2020): 60–72. http://dx.doi.org/10.35784/acs-2020-05.

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This article presents a solution to deal with the optimization of delivery routes problem for a mobile application focused on the restaurant sector, by using a bioinspired algorithm (PSO) to minimize delivery costs, maximize a greater number of deliveries and recommend an optional route for food delivery. Different computational experiments are carried out by using Google Maps (API) for showing the best delivery route. The results obtained are very promising for offering a good delivery service.

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Geder, Jason D., John S. Palmisano, Ravi Ramamurti, Marius Pruessner, Banahalli Ratna, and William C. Sandberg. "Bioinspired Design Process for an Underwater Flying and Hovering Vehicle." Marine Technology Society Journal 45, no. 4 (July 1, 2011): 74–82. http://dx.doi.org/10.4031/mtsj.45.4.5.

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AbstractWe review here the results obtained during the past several years in a series of computational and experimental investigations aimed at understanding the origin of high-force production in the flapping wings of insects and the flapping and deforming fins of fish and the incorporation of that information into bioinspired vehicle designs. We summarize the results obtained on pectoral fin force production, flapping and deforming fin design, and the emulation of fish pectoral fin swimming in unmanned vehicles. In particular, we discuss the main results from the computational investigations of pectoral fin force production for a particular coral reef fish, the bird wrasse (Gomphosus varius), whose impressive underwater flight and hovering performance matches our vehicle mission requirements. We describe the tradeoffs made between performance and produceability during the bio-inspired design of an actively controlled curvature pectoral fin and the incorporation of it into two underwater flight vehicles: a two-fin swimming version and four-fin swimming version. We describe the unique computational approach taken throughout the fin and vehicle design process for relating fin deformation time-histories to specified desired vehicle dynamic behaviors. We describe the development of the vehicle controller, including hardware implementation, using actuation of the multiple deforming flapping fins as the only means of propulsion and control. Finally, we review the comparisons made to date between four-fin vehicle experimental trajectory measurements and controller simulation predictions and discuss the incorporation of those comparisons into the controller design.

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Controzzi, Marco, Marco D'Alonzo, Carlo Peccia, Calogero Maria Oddo, Maria Chiara Carrozza, and Christian Cipriani. "Bioinspired Fingertip for Anthropomorphic Robotic Hands." Applied Bionics and Biomechanics 11, no. 1-2 (2014): 25–38. http://dx.doi.org/10.1155/2014/864573.

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Background: An artificial fingertip with mechanical features and appearance similar to the human fingertip could represent a significant step forward towards the development of the next generation artificial hands. However, so far, a fingertip showing a good trade-off among mechanical features, appearance and anthropomorphism, along with its 3D computational model, is still missing.Objective: To explore and develop an artificial fingertip demonstrating a mechanical response similar to the human fingertip, in order to improve the grasp stability of robotic hands.Methods: Taking inspiration from the multi-layered structure of the human finger, novel artificial fingertips, composed of a rigid core and covered by layers of polymeric materials with different degrees of stiffness and topped by a hard nail were developed. An accurate 3D finite element (FE) model was also developed in order to simulate and evaluate the internal mechanical behavior of the prototypes under external indentations. The mechanical response of the prototypes was assessed and compared with that of the human fingertip and the FE model results, under different experimental conditions. Finally, the artificial fingertips were integrated into an anthropomorphic robotic hand and evaluated in grip tests, in order to compare the grasp stability with respect to conventional stiff (metal) fingertips.Results: The developed prototypes demonstrated a response to compression tests similar to the human finger and the FE model showed a discrete accuracy (mean error 7%). Finally, an increased ability (by 96%) in stably holding objects during precision grips with respect to conventional stiff fingers was demonstrated.Conclusion: Multi-layered biomimetic fingertips can improve grasp stability and cosmetic appearance of anthropomorphic robot hands.

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González-Albuixech, VF, M. Rodríguez-Millán, T. Ito, JA Loya, and MH Miguélez. "Numerical analysis for design of bioinspired ceramic modular armors for ballistic protections." International Journal of Damage Mechanics 28, no. 6 (August 21, 2018): 815–37. http://dx.doi.org/10.1177/1056789518795203.

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The exigent requirements for personal protections in terms of energy absorption and ergonomics have led to increasing interest in bioinspired protections. This work focuses on the numerical analysis of ballistic behavior of different bioinspired geometries under impact loadings. Ceramic armors based on ganoid fish scales (the type exhibited by gars, bichirs and reedfishes), placoid fish scales (characterizing sharks and rays) and armadillo natural protection have been considered. Different impact conditions are studied, including perpendicular and oblique impacts to surface protection, different yaw angle, and multiple impacts. Main conclusion is related to the improved efficiency of modular armors against multiple shots exhibiting more localized damage and crack arrest properties. Moreover, its potential ergonomic is a promising characteristic justifying a deeper study.

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Kozlov, Olexey, and Yuri Kondratenko. "SEARCH OF OPTIMAL MEMBERSHIP FUNCTIONS OF FUZZY SYSTEMS BASED ON BIOINSPIRED EVOLUTIONARY ALGORITHMS. PART II. METHOD IMPLEMENTATION AND STUDY OF ITS EFFICIENCY." Journal of Automation and Information sciences 2 (March 1, 2021): 139–59. http://dx.doi.org/10.34229/1028-0979-2021-2-13.

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This article is devoted to the efficiency of a method of optimal membership functions search for fuzzy systems based on bioinspired evolutionary algorithms of global optimization. The proposed method allows finding the optimal membership functions of linguistic terms at solving the compromise problem of minimizing the objective function and reducing computational costs in the process of further parametric optimization of fuzzy systems. To study the effectiveness of the considered method in this work, the search of the optimal membership functions is conducted for a fuzzy controller of the control system of a multi-purpose mobile robot designed to move along inclined and vertical ferromagnetic surfaces, with the implementation of this method based on 3 bioinspired evolutionary algorithms: genetic, artificial immune systems, biogeographic. The analysis of the obtained results of computer modeling showed that the usage of the proposed method of search of optimal membership functions gives the opportunity to increase significantly the efficiency of the mobile robot control, as well as to reduce the total number of parameters at further parametric optimization of linguistic terms, which confirms the high efficiency of the developed method.

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Botella, Guillermo, Manuel Rodríguez, Antonio García, and Eduardo Ros. "Neuromorphic Configurable Architecture for Robust Motion Estimation." International Journal of Reconfigurable Computing 2008 (2008): 1–9. http://dx.doi.org/10.1155/2008/428265.

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The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM). This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.

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LUO, YUEGUO, HAIJUN TAN, YING ZHANG, and YUN JIANG. "The computational power of timed P systems with active membranes using promoters." Mathematical Structures in Computer Science 29, no. 5 (August 9, 2018): 663–80. http://dx.doi.org/10.1017/s0960129518000282.

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P systems with active membranes are a class of bioinspired computing models, where the rules are used in the non-deterministic maximally parallel manner. In this paper, first, a new variant of timed P systems with active membranes is proposed, where the application of rules can be regulated by promoters with only two polarizations. Next, we prove that any Turing computable set of numbers can be generated by such a P system in the time-free way. Moreover, we construct a uniform solution to the$\mathcal{SAT}$problem in the framework of such recognizer timed P systems in polynomial time, and the feasibility and effectiveness of the proposed system is demonstrated by an instance. Compared with the existing methods, the P systems constructed in our work require fewer necessary resources and RS-steps, which show that the solution is effective toNP-complete problem.

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Wang, Zhi-Cheng, and Xiao-Bei Wu. "Hybrid Biogeography-Based Optimization for Integer Programming." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/672983.

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Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark integer programming problems. Thus we modify the mutation operator and/or the neighborhood structure of the algorithm, resulting in three new BBO-based methods, named BlendBBO, BBO_DE, and LBBO_LDE, respectively. Computational experiments show that these methods are competitive approaches to solve integer programming problems, and the LBBO_LDE shows the best performance on the benchmark problems.

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Mitin, Iliya, Roman Korotaev, Artem Ermolaev, Vasily Mironov, Sergey A. Lobov, and Victor B. Kazantsev. "Bioinspired Propulsion System for a Thunniform Robotic Fish." Biomimetics 7, no. 4 (November 28, 2022): 215. http://dx.doi.org/10.3390/biomimetics7040215.

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The paper describes a bioinspired propulsion system for a robotic fish model. The system is based on a combination of an elastic chord with a tail fin fixed on it. The tail fin is connected to a servomotor by two symmetric movable thrusts simulating muscle contractions. The propulsion system provides the oscillatory tail movement with controllable amplitude and frequency. Tail oscillations translate into the movement of the robotic fish implementing the thunniform principle of locomotion. The shape of the body and the tail fin of the robotic fish were designed using a computational model simulating a virtual body in an aquatic medium. A prototype of a robotic fish was constructed and tested in experimental conditions. Dependencies of fish velocity on the dynamic characteristics of tail oscillations were analyzed. In particular, it was found that the robot’s speed increased as the frequency of tail fin oscillations grew. We also found that for fixed frequencies, an increase in the oscillation amplitude lead to an increase in the swimming speed only up to a certain threshold. Further growth of the oscillation amplitude lead to a weak increase in speed at higher energy costs.

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Bharti, O. P., R. K. Saket, and S. K. Nagar. "Controller Design of DFIG Based Wind Turbine by Using Evolutionary Soft Computational Techniques." Engineering, Technology & Applied Science Research 7, no. 3 (June 12, 2017): 1732–36. http://dx.doi.org/10.48084/etasr.1231.

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This manuscript illustrates the controller design for a doubly fed induction generator based variable speed wind turbine by using a bioinspired scheme. This methodology is based on exploiting two proficient swarm intelligence based evolutionary soft computational procedures. The particle swarm optimization (PSO) and bacterial foraging optimization (BFO) techniques are employed to design the controller intended for small damping plant of the DFIG. Wind energy overview and DFIG operating principle along with the equivalent circuit model is adequately discussed in this paper. The controller design for DFIG based WECS using PSO and BFO are described comparatively in detail. The responses of the DFIG system regarding terminal voltage, current, active-reactive power, and DC-Link voltage have slightly improved with the evolutionary soft computational procedure. Lastly, the obtained output is equated with a standard technique for performance improvement of DFIG based wind energy conversion system.

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Crespo-Cano, Rubén, Sergio Cuenca-Asensi, Eduardo Fernández, and Martínez-Álvarez. "Metaheuristic Optimisation Algorithms for Tuning a Bioinspired Retinal Model." Sensors 19, no. 22 (November 6, 2019): 4834. http://dx.doi.org/10.3390/s19224834.

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A significant challenge in neuroscience is understanding how visual information is encoded in the retina. Such knowledge is extremely important for the purpose of designing bioinspired sensors and artificial retinal systems that will, in so far as may be possible, be capable of mimicking vertebrate retinal behaviour. In this study, we report the tuning of a reliable computational bioinspired retinal model with various algorithms to improve the mimicry of the model. Its main contribution is two-fold. First, given the multi-objective nature of the problem, an automatic multi-objective optimisation strategy is proposed through the use of four biological-based metrics, which are used to adjust the retinal model for accurate prediction of retinal ganglion cell responses. Second, a subset of population-based search heuristics—genetic algorithms (SPEA2, NSGA-II and NSGA-III), particle swarm optimisation (PSO) and differential evolution (DE)—are explored to identify the best algorithm for fine-tuning the retinal model, by comparing performance across a hypervolume metric. Nonparametric statistical tests are used to perform a rigorous comparison between all the metaheuristics. The best results were achieved with the PSO algorithm on the basis of the largest hypervolume that was achieved, well-distributed elements and high numbers on the Pareto front.

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Du, Ganhong, Jun Ling, Fangyu Hu, Keyuan Liu, Long Ye, and Liming Jiang. "Bioinspired Polymer-Bound Organocatalysts for Direct Asymmetric Aldol Reaction: Experimental and Computational Studies." Catalysts 9, no. 5 (April 28, 2019): 398. http://dx.doi.org/10.3390/catal9050398.

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A series of poly(2-oxazoline) (POX) derivatives bearing prolinamide pendants were designed as organocatalysts and evaluated in the direct asymmetric aldol reaction between aromatic aldehydes and cyclic ketones. The structural variation of the alkyl spacer connecting the polymer backbone with the catalytic unit was applied so as to deduce structure–performance relationships combined with comparable experiments from model catalysts. Results showed that the POX-bound prolinamides can promote the aldol reaction more effectively as compared to their small-molecular and non-POX-bound analogs. The catalyst P3 containing the pyrrolidine moiety closer to the tertiary amide backbone exhibited the overall best catalytic efficiency, affording anti-products in 84% yield with 89% ee in the representative aldol addition of cyclohexanone to 4-nitrobenzaldehyde at a 10 mol.% catalyst loading. Furthermore, the influence of trifluoroacetic acid as an additive on the asymmetric transformation was investigated. Theoretical calculations revealed that the protonation of the aldehyde carbonyl group switched the activation mode of the aldol acceptor through hydrogen bond interactions, thereby changing the relative energy barrier of the enamine/aldehyde reaction transition states, which accounted well for the significant improvement in the enantioselectivity of the acidic additives observed experimentally.

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Li, Zhengwei, Yu Wang, and Jianliang Xiao. "Mechanics of bioinspired imaging systems." Theoretical and Applied Mechanics Letters 6, no. 1 (January 2016): 11–20. http://dx.doi.org/10.1016/j.taml.2015.11.011.

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Chai, Zhilei, Wei Song, Qinxin Bao, Feng Ding, and Fei Liu. "Taking advantage of hybrid bioinspired intelligent algorithm with decoupled extended Kalman filter for optimizing growing and pruning radial basis function network." Royal Society Open Science 5, no. 9 (September 2018): 180529. http://dx.doi.org/10.1098/rsos.180529.

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The growing and pruning radial basis function (GAP-RBF) network is a promising sequential learning algorithm for prediction analysis, but the parameter selection of such a network is usually a non-convex problem and makes it difficult to handle. In this paper, a hybrid bioinspired intelligent algorithm is proposed to optimize GAP-RBF. Specifically, the excellent local convergence of particle swarm optimization (PSO) and the extensive search ability of genetic algorithm (GA) are both considered to optimize the weights and bias term of GAP-RBF. Meanwhile, a competitive mechanism is proposed to make the hybrid algorithm choose the appropriate individuals for effective search and further improve its optimization ability. Moreover, a decoupled extended Kalman filter (DEKF) method is introduced in this study to reduce the size of error covariance matrix and decrease the computational complexity for performing real-time predictions. In the experiments, three classic forecasting issues including abalone age, Boston house price and auto MPG are adopted for extensive test, and the experimental results show that our method performs better than PSO and GA these two single bioinspired optimization algorithms. What is more, our method via DEKF achieves the better results in comparison with the state-of-art sequential learning algorithms, such as GAP-RBF, minimal resource allocation network, resource allocation network using an extended Kalman filter and resource allocation network.

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Zhang, Lei, Tianguang Zhang, Haiyan Wu, Alexander Borst, and Kolja Kühnlenz. "Visual Flight Control of a Quadrotor Using Bioinspired Motion Detector." International Journal of Navigation and Observation 2012 (May 8, 2012): 1–9. http://dx.doi.org/10.1155/2012/627079.

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Motion detection in the fly is extremely fast with low computational requirements. Inspired from the fly's vision system, we focus on a real-time flight control on a miniquadrotor with fast visual feedback. In this work, an elaborated elementary motion detector (EMD) is utilized to detect local optical flow. Combined with novel receptive field templates, the yaw rate of the quadrotor is estimated through a lookup table established with this bioinspired visual sensor. A closed-loop control system with the feedback of yaw rate estimated by EMD is designed. With the motion of the other degrees of freedom stabilized by a camera tracking system, the yaw-rate of the quadrotor during hovering is controlled based on EMD feedback under real-world scenario. The control performance of the proposed approach is compared with that of conventional approach. The experimental results demonstrate the effectiveness of utilizing EMD for quadrotor control.

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Fouladi, Kamran, and David J. Coughlin. "CFD Investigation of Trout-Like Configuration Holding Station near an Obstruction." Fluids 6, no. 6 (June 1, 2021): 204. http://dx.doi.org/10.3390/fluids6060204.

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This report presents the development of a fluid-structure interaction model using commercial Computational fluid dynamics software and in-house developed User Defined Function to simulate the motion of a trout Department of Mechanical Engineering, Widener University holding station in a moving water stream. The oscillation model used in this study is based on the observations of trout swimming in a respirometry tank in a laboratory experiment. The numerical simulations showed results that are consistent with laboratory observations of a trout holding station in the tank without obstruction and trout entrained to the side of the cylindrical obstruction. This paper will be helpful in the development of numerical models for the hydrodynamic analysis of bioinspired unmanned underwater vehicle systems.

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Costa, Denis Carlos Lima, Lair Aguiar de Meneses, Mara Líbia Viana de Lima, Heictor Alves de Oliveira Costa, Adriane Cristina Fernandes Reis, Huan Ferreira Brasil Pinheiro, Erick Freitas da Costa, et al. "Thermoelectric generation with reduced pollutants made possible by bio-inspired computing." Research, Society and Development 11, no. 1 (January 2, 2022): e7611124568. http://dx.doi.org/10.33448/rsd-v11i1.24568.

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The debate to establish a balance between the generation of electricity and the preservation of the environment is, extraordinarily, important. This article proposes, as a short-term solution, the replacement of diesel oil by natural gas in thermoelectric generation. Natural gas emits 75% less pollutants to the environment than diesel and has a similar energetic efficiency. As a strategy for this replacement to occur safely, the computational modeling was developed in a Bioinspired Computing methodology, called Genetic Algorithm (GA). The GA incorporated all the variables of the electricity and natural gas networks, presented in the mathematical modeling. The result was a significant reduction in the level of pollutants emitted, with high stability in the electrical power system.

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Buehler, Markus J. "Computational and Theoretical Materiomics: Properties of Biological and de novo Bioinspired Materials." Journal of Computational and Theoretical Nanoscience 7, no. 7 (July 1, 2010): 1203–9. http://dx.doi.org/10.1166/jctn.2010.1474.

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Journal articles on the topic 'Bioinspired Computation'

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