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Journal articles on the topic 'Control Boolean network'

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Published: 25 May 2024

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1

CHEN, HONGWEI, YANG LIU, and JIANQUAN LU. "SYNCHRONIZATION CRITERIA FOR TWO BOOLEAN NETWORKS BASED ON LOGICAL CONTROL." International Journal of Bifurcation and Chaos 23, no. 11 (November 2013): 1350178. http://dx.doi.org/10.1142/s0218127413501782.

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This paper investigates the complete synchronization of two Boolean networks via logic control. Both feedback control and open-loop control are proposed to make the slave network completely synchronized with the master Boolean network. Using the algebraic state-space representation of Boolean networks, we derive several necessary and sufficient conditions for complete synchronization between two Boolean networks. Two examples are given to illustrate the obtained results.

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2

Li, Zhiqiang, Jinli Song, and Huimin Xiao. "Reachability and Controllability Analysis of Periodic Switched Boolean Control Networks." Journal of Robotics and Mechatronics 26, no. 5 (October 20, 2014): 573–79. http://dx.doi.org/10.20965/jrm.2014.p0573.

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The reachability and controllability of switched Boolean (control) network are discussed in this paper. Based on semi-tensor product, using the vector form of Boolean logical variable, the switched Boolean (control) network is expressed as a discrete time system with state and control variables. For the switched Boolean network without control, the stabilization by suitable switching signal is discussed. Also, the controllability of the periodic switching signal is learned, and the conditions for stability and controllability of periodic switched Boolean networks avoiding states setCare obtained.

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3

Gao, Bo, Haipeng Peng, Dawei Zhao, Wenguang Zhang, and Yixian Yang. "Attractor Transformation by Impulsive Control in Boolean Control Network." Mathematical Problems in Engineering 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/674571.

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Boolean control networks have recently been attracting considerable interests as computational models for genetic regulatory networks. In this paper, we present an approach of impulsive control for attractor transitions in Boolean control networks based on the recent developed matrix semitensor product theory. The reachability of attractors is estimated, and the controller is also obtained. The general derivation proposed here is exemplified with a kind of gene model, which is the protein-nucleic acid interactions network, on numerical simulations.

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4

Shi, Wenping, Bo Wu, and Jing Han. "A Note on the Observability of Temporal Boolean Control Network." Abstract and Applied Analysis 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/631639.

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Temporal Boolean network is a generalization of the Boolean network model that takes into account the time series nature of the data and tries to incorporate into the model the possible existence of delayed regulatory interactions among genes. This paper investigates the observability problem of temporal Boolean control networks. Using the semi tensor product of matrices, the temporal Boolean networks can be converted into discrete time linear dynamic systems with time delays. Then, necessary and sufficient conditions on the observability via two kinds of inputs are obtained. An example is given to illustrate the effectiveness of the obtained results.

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5

Zhao, Yin, Bijoy K. Ghosh, and Daizhan Cheng. "Control of Large-Scale Boolean Networks via Network Aggregation." IEEE Transactions on Neural Networks and Learning Systems 27, no. 7 (July 2016): 1527–36. http://dx.doi.org/10.1109/tnnls.2015.2442593.

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6

Wang, Cailu, and Yuegang Tao. "Conversion between Logic and Algebraic Expressions of Boolean Control Networks." Applied Sciences 10, no. 20 (October 15, 2020): 7180. http://dx.doi.org/10.3390/app10207180.

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The conversion between logic and algebraic expressions of Boolean control networks plays a worthy role in the analysis and design of digital circuits. In this paper, for a single Boolean function, a direct conversion between the minterm canonical form and the structure matrix is provided. For a Boolean control network consisting of systems of Boolean functions, two algorithms are developed to achieve the mutual conversion between the logic and algebraic expressions. The presented algorithms decrease exponentially the complexity of the semi-tensor product based method. Some numerical examples are given to demonstrate the algorithms and to compare our method with the existing ones.

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7

Li, Fangfei, Xiwen Lu, and Zhaoxu Yu. "Optimal control algorithms for switched Boolean network." Journal of the Franklin Institute 351, no. 6 (June 2014): 3490–501. http://dx.doi.org/10.1016/j.jfranklin.2014.03.008.

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8

Wei, Qiang, Cheng-jun Xie, Xu-ri Kou, and Wei Shen. "Delay Partial Synchronization of Mutual Delay Coupled Boolean Networks." Measurement and Control 53, no. 5-6 (April 15, 2020): 870–75. http://dx.doi.org/10.1177/0020294019882967.

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This paper studies the delay partial synchronization for mutual delay-coupled Boolean networks. First, the mutual delay-coupled Boolean network model is presented. Second, some necessary and sufficient conditions are derived to ensure the delay partial synchronization of the mutual delay-coupled Boolean networks. The upper bound of synchronization time is obtained. Finally, an example is provided to illustrate the efficiency of the theoretical analysis.

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9

Chen, Cheng, and Wei Zhu. "Synchronization Analysis of Boolean Network." Applied Mechanics and Materials 432 (September 2013): 528–32. http://dx.doi.org/10.4028/www.scientific.net/amm.432.528.

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Boolean network and its synchronization have been gradually used to the global behavior analysis of large gene regulatory network. Network synchronization depends mainly on the dynamics of each node and the topology of the network. In this paper, using the semi-tensor product of matrices, a necessary and sufficient condition based on transition matrix for Boolean network complete synchronization is presented. The synchronization of Boolean control network is also discussed. Two examples are given to illustrate the theoretical result.

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10

Sun, Xiaolei, Naiming Qi, and Weiran Yao. "Boolean Networks-Based Auction Algorithm for Task Assignment of Multiple UAVs." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/425356.

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This paper presents an application of Boolean networks-based auction algorithm (BNAA) for task assignment in unmanned aerial vehicles (UAVs) systems. Under reasonable assumptions, the assignment framework consists of mission control system, communication network, and ground control station. As the improved algorithm of consensus-based bundle algorithm (CBBA), the BNAA utilizes a cluster-based combinatorial auction policy to handle multiple tasks. Instead of empirical method based on look-up table about conditional variables, Boolean network is introduced into consensus routine of BNAA for solving the conflict of assignment across the fleet of UAVs. As a new mathematic theory, semitensor product provides the implementation and theoretical proof of Boolean networks. Numerical results demonstrate the effectiveness and efficiency of proposed BNAA method.

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11

Baudin, Alexis, Soumya Paul, Cui Su, and Jun Pang. "Controlling large Boolean networks with single-step perturbations." Bioinformatics 35, no. 14 (July 2019): i558—i567. http://dx.doi.org/10.1093/bioinformatics/btz371.

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Abstract Motivation The control of Boolean networks has traditionally focussed on strategies where the perturbations are applied to the nodes of the network for an extended period of time. In this work, we study if and how a Boolean network can be controlled by perturbing a minimal set of nodes for a single-step and letting the system evolve afterwards according to its original dynamics. More precisely, given a Boolean network (BN), we compute a minimal subset Cmin of the nodes such that BN can be driven from any initial state in an attractor to another ‘desired’ attractor by perturbing some or all of the nodes of Cmin for a single-step. Such kind of control is attractive for biological systems because they are less time consuming than the traditional strategies for control while also being financially more viable. However, due to the phenomenon of state-space explosion, computing such a minimal subset is computationally inefficient and an approach that deals with the entire network in one-go, does not scale well for large networks. Results We develop a ‘divide-and-conquer’ approach by decomposing the network into smaller partitions, computing the minimal control on the projection of the attractors to these partitions and then composing the results to obtain Cmin for the whole network. We implement our method and test it on various real-life biological networks to demonstrate its applicability and efficiency. Supplementary information Supplementary data are available at Bioinformatics online.

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12

Azuma, Shun-ichi. "Robust network structures for conserving total activity in Boolean networks." Control Theory and Technology 18, no. 2 (May 2020): 143–47. http://dx.doi.org/10.1007/s11768-020-9202-6.

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13

Li, Fangfei, and Xiwen Lu. "Minimum energy control and optimal-satisfactory control of Boolean control network." Physics Letters A 377, no. 43 (December 2013): 3112–18. http://dx.doi.org/10.1016/j.physleta.2013.10.002.

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14

Yu, Zongxi, Qinyao Pan, Mengxia Xu, Jie Zhong, and Xiaoxu Liu. "Network Structure and Pinning Control for Stable Behaviors of Boolean Networks." IEEE Transactions on Circuits and Systems II: Express Briefs 69, no. 3 (March 2022): 1482–86. http://dx.doi.org/10.1109/tcsii.2021.3116033.

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15

Wei, Qiang, and Cheng-jun Xie. "Synchronization of mutual time-varying delay-coupled temporal Boolean networks." Measurement and Control 53, no. 7-8 (August 2020): 1504–11. http://dx.doi.org/10.1177/0020294020944951.

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This paper presents mutual time-varying delay-coupled temporal Boolean network model and investigates synchronization issue for mutual time-varying delay-coupled temporal Boolean networks. The necessary and sufficient conditions for the synchronization are given, and the check criterion of the upper bound is presented. An example is given to illustrate the correctness of the theoretical analysis.

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16

Sun, Qilong, and Haitao Li. "Robust Stabilization of Impulsive Boolean Control Networks with Function Perturbation." Mathematics 10, no. 21 (October 30, 2022): 4029. http://dx.doi.org/10.3390/math10214029.

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This paper studies the robust stabilization of impulsive Boolean control networks (IBCNs) with function perturbation. A Boolean control network (BCN) with a state-dependent impulsive sequence is converted to an equivalent BCN by the semi-tensor product method. Based on the equivalence of stabilization between the IBCN and the corresponding BCN, several criteria are proposed for the robust stabilization of IBCNs. Furthermore, when the IBCN is not robustly stabilizable after the function perturbation, an algorithm is presented to modify the control or the impulse-triggered set. Finally, an example is given to verify the obtained results.

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17

Li, Bin Yong, Lin Fu Sun, and Ran Tian. "Multi-Level Complex Network Control System Based on Cloud Services Platform." Applied Mechanics and Materials 571-572 (June 2014): 389–94. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.389.

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Aiming at the access control problem of the cloud service platform, puts forward the control scheme of multi-level system for multi type coordination.By the definition of cloud services platform multi access control object system,constructs multidimensional Boolean relation matrix. The semantic relation of Boolean matrices, design of large-scale complex network node control system model, and simulate the hierarchical network loop control model.Through the analysis of network model, shows that the research results can better support for cloud services platform in multi-level access, dynamic authorization complexity problems in management control.

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18

JOY, MALIACKAL POULO, DONALD E. INGBER, and SUI HUANG. "CHAOTIC MEAN FIELD DYNAMICS OF A BOOLEAN NETWORK WITH RANDOM CONNECTIVITY." International Journal of Modern Physics C 18, no. 09 (September 2007): 1459–73. http://dx.doi.org/10.1142/s0129183107011467.

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Random Boolean networks have been used as simple models of gene regulatory networks, enabling the study of the dynamic behavior of complex biological systems. However, analytical treatment has been difficult because of the structural heterogeneity and the vast state space of these networks. Here we used mean field approximations to analyze the dynamics of a class of Boolean networks in which nodes have random degree (connectivity) distributions, characterized by the mean degree k and variance D. To achieve this we generalized the simple cellular automata rule 126 and used it as the Boolean function for all nodes. The equation for the evolution of the density of the network state is presented as a one-dimensional map for various input degree distributions, with k and D as the control parameters. The mean field dynamics is compared with the data obtained from the simulations of the Boolean network. Bifurcation diagrams and Lyapunov exponents for different parameter values were computed for the map, showing period doubling route to chaos with increasing k. Onset of chaos was delayed (occurred at higher k) with the increase in variance D of the connectivity. Thus, the network tends to be less chaotic when the heterogeneity, as measured by the variance of connectivity, was higher.

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19

Kabir, M. Humayun, and M. Robiul Hoque. "Context-Aware System Modeling Based on Boolean Control Network." Open Journal of Applied Sciences 05, no. 11 (2015): 661–68. http://dx.doi.org/10.4236/ojapps.2015.511065.

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20

Li, Fangfei, and Jitao Sun. "Controllability and optimal control of a temporal Boolean network." Neural Networks 34 (October 2012): 10–17. http://dx.doi.org/10.1016/j.neunet.2012.06.002.

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21

Sarvi, Batoul. "Multimedia communications for autonomous drones." Boolean 2022 VI, no. 1 (December 6, 2022): 52–58. http://dx.doi.org/10.33178/boolean.2022.1.9.

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In recent years, there has been significant growth in multimedia communication on drones. The first thing that comes to every researcher’s mind is what requirements are for multimedia communication to be acceptable for existing scenarios on UAVs? Because of the noisy wireless channel and long distance between UAVs, providing reliable and real-time multimedia communications on UAVs stands at the top of the requirements list. To the best of our knowledge, mobile edge computing and cross-layer error control have significant possibilities to provide a better quality of multimedia communication on UAVs. Finally, utilizing the aforementioned edge network techniques can increase the efficiency of the overall system, enhance the video quality, maximize the usage of network resources, and save energy in multimedia communication on UAV networks.

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22

Newby, Eli, Jorge Gómez Tejeda Zañudo, and Réka Albert. "Structure-based approach to identifying small sets of driver nodes in biological networks." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 6 (June 2022): 063102. http://dx.doi.org/10.1063/5.0080843.

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In network control theory, driving all the nodes in the Feedback Vertex Set (FVS) by node-state override forces the network into one of its attractors (long-term dynamic behaviors). The FVS is often composed of more nodes than can be realistically manipulated in a system; for example, only up to three nodes can be controlled in intracellular networks, while their FVS may contain more than 10 nodes. Thus, we developed an approach to rank subsets of the FVS on Boolean models of intracellular networks using topological, dynamics-independent measures. We investigated the use of seven topological prediction measures sorted into three categories—centrality measures, propagation measures, and cycle-based measures. Using each measure, every subset was ranked and then evaluated against two dynamics-based metrics that measure the ability of interventions to drive the system toward or away from its attractors: To Control and Away Control. After examining an array of biological networks, we found that the FVS subsets that ranked in the top according to the propagation metrics can most effectively control the network. This result was independently corroborated on a second array of different Boolean models of biological networks. Consequently, overriding the entire FVS is not required to drive a biological network to one of its attractors, and this method provides a way to reliably identify effective FVS subsets without the knowledge of the network dynamics.

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23

Kobayashi, Koichi, and Kunihiko Hiraishi. "Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/968341.

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One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs.

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24

Liu, Zejiao, Yu Wang, Yang Liu, and Qihua Ruan. "Reference trajectory output tracking for Boolean control networks with controls in output." Mathematical Modelling and Control 3, no. 3 (2023): 256–66. http://dx.doi.org/10.3934/mmc.2023022.

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<abstract><p>This article investigates the reference trajectory output tracking issue of Boolean control networks (BCNs) that have controls in the output. Firstly, to solve the problem, some necessary and sufficient conditions are obtained. The tracking problem is studied from the perspective of set and matrix calculation. Next, an algorithm for determining whether the output tracking issue is solvable is proposed. Furthermore, the controller design algorithm satisfying the solvability condition is given. Using our methods, we can track some trajectories that cannot be tracked in BCNs without controls in output. In addition, for better application in practice, the corresponding changes in the network transition matrix and output matrix under state, transition, and input constraints are considered. Finally, some examples are presented to illustrate the validity of our results.</p></abstract>

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25

EASTON, GEOFF, ROGER J. BROOKS, KRISTINA GEORGIEVA, and IAN WILKINSON. "UNDERSTANDING THE DYNAMICS OF INDUSTRIAL NETWORKS USING KAUFFMAN BOOLEAN NETWORKS." Advances in Complex Systems 11, no. 01 (February 2008): 139–64. http://dx.doi.org/10.1142/s0219525908001544.

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Industrial networks offer a prime example of the tension between system stability and change. Change is necessary as a response to environmental variation, whereas stability provides the underpinning for long-term investment and the exploitation of efficiencies. Whilst one of the key themes in industrial network research has been the dynamics of change, relatively little work, empirical or theoretical, has been devoted to the dynamics of stability. This paper presents a new approach to this problem by using Boolean networks, which were originally devised by Stuart Kauffman as an abstract model of genetic networks. The elements in the model are connected by rules of Boolean logic, and a novel aspect of this research is that the elements represent the industrial network exchanges rather than stock entities (the organizations). The model structure consists of interactions between the exchanges, and the results represent the pattern of exchange episodes. A total of 42 networks were modeled and the dynamics analyzed in detail, and five of these cases are presented in this paper. The models produced realistic behavior and provided some insights into the reasons for stability in industrial networks.

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26

HOU, WENPIN, TAKEYUKI TAMURA, WAI-KI CHING, and TATSUYA AKUTSU. "FINDING AND ANALYZING THE MINIMUM SET OF DRIVER NODES IN CONTROL OF BOOLEAN NETWORKS." Advances in Complex Systems 19, no. 03 (May 2016): 1650006. http://dx.doi.org/10.1142/s0219525916500065.

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We study the minimum number of driver nodes control of which leads a Boolean network (BN) from an initial state to a target state in a specified number of time steps. We show that the problem is NP-hard and present an integer linear programming-based method that solves the problem exactly. We mathematically analyze the average size of the minimum set of driver nodes for random Boolean networks with bounded in-degree and with a small number of time steps. The results of computational experiments using randomly generated BNs show good agreements with theoretical analyses. A further examination in realistic BNs demonstrates the efficiency and generality of our theoretical analyses.

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27

Kobayashi, Koichi, and Kunihiko Hiraishi. "Optimal Control of Gene Regulatory Networks with Effectiveness of Multiple Drugs: A Boolean Network Approach." BioMed Research International 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/246761.

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Developing control theory of gene regulatory networks is one of the significant topics in the field of systems biology, and it is expected to apply the obtained results to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of gene regulatory networks, and gene expression is expressed by a binary value (0 or 1). In the control problem, we assume that the concentration level of a part of genes is arbitrarily determined as the control input. However, there are cases that no gene satisfying this assumption exists, and it is important to consider structural control via external stimuli. Furthermore, these controls are realized by multiple drugs, and it is also important to consider multiple effects such as duration of effect and side effects. In this paper, we propose a BN model with two types of the control inputs and an optimal control method with duration of drug effectiveness. First, a BN model and duration of drug effectiveness are discussed. Next, the optimal control problem is formulated and is reduced to an integer linear programming problem. Finally, numerical simulations are shown.

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28

Zhu, Dingju. "Boolean discrete network and dynamic equations to control parking fees." Journal of Difference Equations and Applications 23, no. 1-2 (September 13, 2016): 297–311. http://dx.doi.org/10.1080/10236198.2016.1224864.

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29

郭, 向东. "The Application of Characteristic Polynomial Theory in Boolean Control Network." Dynamical Systems and Control 07, no. 03 (2018): 214–25. http://dx.doi.org/10.12677/dsc.2018.73023.

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30

Moradi, Mohammad, Sama Goliaei, and Mohammad-Hadi Foroughmand-Araabi. "A Boolean network control algorithm guided by forward dynamic programming." PLOS ONE 14, no. 5 (May 2, 2019): e0215449. http://dx.doi.org/10.1371/journal.pone.0215449.

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31

Braccini, Michele, Andrea Roli, Edoardo Barbieri, and Stuart A. Kauffman. "On the Criticality of Adaptive Boolean Network Robots." Entropy 24, no. 10 (September 27, 2022): 1368. http://dx.doi.org/10.3390/e24101368.

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Systems poised at a dynamical critical regime, between order and disorder, have been shown capable of exhibiting complex dynamics that balance robustness to external perturbations and rich repertoires of responses to inputs. This property has been exploited in artificial network classifiers, and preliminary results have also been attained in the context of robots controlled by Boolean networks. In this work, we investigate the role of dynamical criticality in robots undergoing online adaptation, i.e., robots that adapt some of their internal parameters to improve a performance metric over time during their activity. We study the behavior of robots controlled by random Boolean networks, which are either adapted in their coupling with robot sensors and actuators or in their structure or both. We observe that robots controlled by critical random Boolean networks have higher average and maximum performance than that of robots controlled by ordered and disordered nets. Notably, in general, adaptation by change of couplings produces robots with slightly higher performance than those adapted by changing their structure. Moreover, we observe that when adapted in their structure, ordered networks tend to move to the critical dynamical regime. These results provide further support to the conjecture that critical regimes favor adaptation and indicate the advantage of calibrating robot control systems at dynamical critical states.

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32

Brim, Luboš, Samuel Pastva, David Šafránek, and Eva Šmijáková. "Parallel One-Step Control of Parametrised Boolean Networks." Mathematics 9, no. 5 (March 6, 2021): 560. http://dx.doi.org/10.3390/math9050560.

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Boolean network (BN) is a simple model widely used to study complex dynamic behaviour of biological systems. Nonetheless, it might be difficult to gather enough data to precisely capture the behavior of a biological system into a set of Boolean functions. These issues can be dealt with to some extent using parametrised Boolean networks (ParBNs), as this model allows leaving some update functions unspecified. In our work, we attack the control problem for ParBNs with asynchronous semantics. While there is an extensive work on controlling BNs without parameters, the problem of control for ParBNs has not been in fact addressed yet. The goal of control is to ensure the stabilisation of a system in a given state using as few interventions as possible. There are many ways to control BN dynamics. Here, we consider the one-step approach in which the system is instantaneously perturbed out of its actual state. A naïve approach to handle control of ParBNs is using parameter scan and solve the control problem for each parameter valuation separately using known techniques for non-parametrised BNs. This approach is however highly inefficient as the parameter space of ParBNs grows doubly exponentially in the worst case. We propose a novel semi-symbolic algorithm for the one-step control problem of ParBNs, that builds on symbolic data structures to avoid scanning individual parameters. We evaluate the performance of our approach on real biological models.

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33

Sidorova, E. A., A. V. Dolgova, and S. P. Zheleznyak. "Automated System of Competencies Indicators’ Formation Control during the Basic Boolean Algebra Studying." Vestnik NSU. Series: Information Technologies 20, no. 3 (February 12, 2023): 51–64. http://dx.doi.org/10.25205/1818-7900-2022-20-3-51-64.

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The eﬀective study of Computer Science is impossible without the widespread use of information technology. Boolean algebra is one of the most fundamental sections of computer science. There is a list of disadvantages of this testing method for the evaluation of the master’s degree students’ knowledge of this topic. This results in development of other interactive tools. This article is devoted to the development and operation features of the automated system “Boolean algebra”, which was designed to control the formation of the competencies’ achievement indicators obtained during studying Boolean algebra. The developed system automatically creates task option and contains three types of tasks. The frst task includes construction of a truth table for three Boolean functions, the second requires Boolean circuit construction, and the third task is focused on Boolean expression simplifying. The system architecture consists of eightindependent modules which realize the new task option synthesis and its design, Boolean functions decomposition, truth tables construction, analysis, and evaluation of the results. The article describes the concept of each module. It describes in detail the synthesis of Boolean functions, as well as the analysis modules and their functioning algorithms. The automated system under operation proved to be eﬀective since it allows one to objectively evaluate user’s theoretical knowledge and ability to apply these methods to the truth tables construction. There are also several advantages of the considered automated system: it requires little space on a hard disk, workes in a network and on local computer, has intuitive interface, generates a large variety of tasks and performs their autocheking.

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You, Tao, Hailun Zhang, Mingyu Yang, Xiao Wang, and Yangming Guo. "Controllability of Boolean networks with intermittent disturbances." Modern Physics Letters B 34, no. 28 (August 5, 2020): 2050309. http://dx.doi.org/10.1142/s0217984920503091.

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In biological systems, gene expression is an important subject. In order to clarify the specific process of gene expression, mathematical tools are needed to simulate the process. The Boolean network (BN) is a good mathematical tool. In this paper, we study a Boolean network with intermittent perturbations. This is of great significance for studying genetic mutations in bioengineering. The expression of genes in the internal system of a living being is a very complicated process, and it is clear that the process is trans-ageal for humans. Through the intermittent control and pulse control of the BN, we can obtain the trajectory of gene expression better and faster, which will provide a very important theoretical basis for our next research.

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35

Lin, Yih-Lon, Jer-Guang Hsieh, and Jyh-Horng Jeng. "Robust Template Decomposition without Weight Restriction for Cellular Neural Networks Implementing Arbitrary Boolean Functions Using Support Vector Classifiers." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/614543.

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If the given Boolean function is linearly separable, a robust uncoupled cellular neural network can be designed as a maximal margin classifier. On the other hand, if the given Boolean function is linearly separable but has a small geometric margin or it is not linearly separable, a popular approach is to find a sequence of robust uncoupled cellular neural networks implementing the given Boolean function. In the past research works using this approach, the control template parameters and thresholds are restricted to assume only a given finite set of integers, and this is certainly unnecessary for the template design. In this study, we try to remove this restriction. Minterm- and maxterm-based decomposition algorithms utilizing the soft margin and maximal margin support vector classifiers are proposed to design a sequence of robust templates implementing an arbitrary Boolean function. Several illustrative examples are simulated to demonstrate the efficiency of the proposed method by comparing our results with those produced by other decomposition methods with restricted weights.

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36

Kabir, M. Humayun, M. Robiul Hoque, and Sung-Hyun Yang. "Implementation of Boolean Control Network Based Intelligent System in Smart Home." International Journal of Smart Home 10, no. 3 (March 31, 2016): 285–92. http://dx.doi.org/10.14257/ijsh.2016.10.3.27.

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37

Zhao, Yin, Jongrae Kim, and Maurizio Filippone. "Aggregation Algorithm Towards Large-Scale Boolean Network Analysis." IEEE Transactions on Automatic Control 58, no. 8 (August 2013): 1976–85. http://dx.doi.org/10.1109/tac.2013.2251819.

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Stetsyuk, Petro, Oleksii Lykhovyd, Volodymyr Zhydkov, and Anton Suprun. "OPTIMIZATION PROBLEMS OF MODERNIZATION OF THE CAPACITY OF ARCS OF FAULT-TOLERANT NETWORKS." Journal of Automation and Information sciences 5 (September 1, 2021): 5–20. http://dx.doi.org/10.34229/1028-0979-2021-5-1.

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Mathematical models of two classes of problems of modernization of the capacity of arcs of fault-tolerant oriented networks are considered. A network is considered to be fault-tolerant for which it is possible to satisfy all the demands for the transmission of flows when there will be one, but any failure, from all possible single network failures. For the first class of problems (problem A), all possible paths in the network can be used for the transmission of flows. For the second class of problems (problem P), only paths from a predetermined set of paths are used to transfer flows. Mathematical models are represented by linear, Boolean and nonlinear programming problems with a block structure of the constraint matrix.The material of the article is presented in five sections. The first section describes the concepts of a single failure and the scenario of network failures, the content of optimization problems A and P for modernization of capacity of arcs of a fault-tolerant network, a test network (6 vertices and 19 arcs) to test algorithms for solving the problems of modernization of fault-tolerant networks. In the second section, basic models of linear programming problems for finding the capacities of arcs of the fault-tolerant physical structure of a network (problem A) and the fault-tolerant logical structure of a network (problem P) are described, and their properties are considered. The third section describes problems A and P in the form of mixed Boolean linear programming models. Optimal solutions of problem A for various failure scenarios are given for the example of the test network. The solutions were found using the Gurobi program from the NEOS server, where the mathematical model of problem A is described in the AMPL modeling language.The fourth section describes nonlinear convex programming models for problems A and P, developed to find the optimal capacities of fault-tolerant networks according to the selected criterion, and a decomposition algorithm for their solution. The fifth section describes software in the FORTRAN programming language for the decomposition algorithm based on efficient implementations of Shor’s r-algorithms. The decomposition algorithm is compared with the IPOPT program based on the results of solving test problems.

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Chen, Xi, Hao Jiang, Yushan Qiu, and Wai-Ki Ching. "On optimal control policy for probabilistic Boolean network: a state reduction approach." BMC Systems Biology 6, Suppl 1 (2012): S8. http://dx.doi.org/10.1186/1752-0509-6-s1-s8.

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Kabir, M. Humayun, M. Robiul Hoque, Hyungyu Seo, and Sung-Hyun Yang. "Boolean Control Network Based Modeling for Context-Aware System in Smart Home." International Journal of Smart Home 10, no. 4 (April 30, 2016): 65–76. http://dx.doi.org/10.14257/ijsh.2016.10.4.07.

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Chen, Hao, and Jitao Sun. "A new approach for global controllability of higher order Boolean control network." Neural Networks 39 (March 2013): 12–17. http://dx.doi.org/10.1016/j.neunet.2012.12.004.

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Chen, Xi, Hao Jiang, and Wai-Ki Ching. "On Construction of Sparse Probabilistic Boolean Networks." East Asian Journal on Applied Mathematics 2, no. 1 (February 2012): 1–18. http://dx.doi.org/10.4208/eajam.030511.060911a.

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AbstractIn this paper we envisage building Probabilistic Boolean Networks (PBNs) from a prescribed stationary distribution. This is an inverse problem of huge size that can be subdivided into two parts — viz. (i) construction of a transition probability matrix from a given stationary distribution (Problem ST), and (ii) construction of a PBN from a given transition probability matrix (Problem TP). A generalized entropy approach has been proposed for Problem ST and a maximum entropy rate approach for Problem TP respectively. Here we propose to improve both methods, by considering a new objective function based on the entropy rate with an additional term of La-norm that can help in getting a sparse solution. A sparse solution is useful in identifying the major component Boolean networks (BNs) from the constructed PBN. These major BNs can simplify the identification of the network structure and the design of control policy, and neglecting non-major BNs does not change the dynamics of the constructed PBN to a large extent. Numerical experiments indicate that our new objective function is effective in finding a better sparse solution.

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Braccini, Michele, Yuri Gardinazzi, Andrea Roli, and Marco Villani. "Sensory–Motor Loop Adaptation in Boolean Network Robots." Sensors 24, no. 11 (May 24, 2024): 3393. http://dx.doi.org/10.3390/s24113393.

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Recent technological advances have made it possible to produce tiny robots equipped with simple sensors and effectors. Micro-robots are particularly suitable for scenarios such as exploration of hostile environments, and emergency intervention, e.g., in areas subject to earthquakes or fires. A crucial desirable feature of such a robot is the capability of adapting to the specific environment in which it has to operate. Given the limited computational capabilities of a micro-robot, this property cannot be achieved by complicated software but it rather should come from the flexibility of simple control mechanisms, such as the sensory–motor loop. In this work, we explore the possibility of equipping simple robots controlled by Boolean networks with the capability of modulating their sensory–motor loop such that their behavior adapts to the incumbent environmental conditions. This study builds upon the cybernetic concept of homeostasis, which is the property of maintaining essential parameters inside vital ranges, and analyzes the performance of adaptive mechanisms intervening in the sensory–motor loop. In particular, we focus on the possibility of maneuvering the robot’s effectors such that both their connections to network nodes and environmental features can be adapted. As the actions the robot takes have a feedback effect to its sensors mediated by the environment, this mechanism makes it possible to tune the sensory–motor loop, which, in turn, determines the robot’s behavior. We study this general setting in simulation and assess to what extent this mechanism can sustain the homeostasis of the robot. Our results show that controllers made of random Boolean networks in critical and chaotic regimes can be tuned such that their homeostasis in different environments is kept. This outcome is a step towards the design and deployment of controllers for micro-robots able to adapt to different environments.

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Qiu, Tao, Peiliang Xie, Xiufeng Xia, Chuanyu Zong, and Xiaoxu Song. "Aggregated Boolean Query Processing for Document Retrieval in Edge Computing." Electronics 11, no. 12 (June 19, 2022): 1908. http://dx.doi.org/10.3390/electronics11121908.

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Search engines use significant hardware and energy resources to process billions of user queries per day, where Boolean query processing for document retrieval is an essential ingredient. Considering the huge number of users and large scale of the network, traditional query processing mechanisms may not be applicable since they mostly depend on a centralized retrieval method. To remedy this issue, this paper proposes a processing technique for aggregated Boolean queries in the context of edge computing, where each sub-region of the network corresponds to an edge network regulated by an edge server, and the Boolean queries are evaluated in a distributed fashion on the edge servers. This decentralized query processing technique has demonstrated its efficiency and applicability for the document retrieval problem. Experimental results on two real-world datasets show that this technique achieves high query performance and outperforms the traditional centralized methods by 2–3 times.

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Zhong, Jie, Daniel W. C. Ho, Jianquan Lu, and Wenying Xu. "Global robust stability and stabilization of Boolean network with disturbances." Automatica 84 (October 2017): 142–48. http://dx.doi.org/10.1016/j.automatica.2017.07.013.

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Münzner, Ulrike, Tomoya Mori, Marcus Krantz, Edda Klipp, and Tatsuya Akutsu. "Identification of periodic attractors in Boolean networks using a priori information." PLOS Computational Biology 18, no. 1 (January 14, 2022): e1009702. http://dx.doi.org/10.1371/journal.pcbi.1009702.

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Boolean networks (BNs) have been developed to describe various biological processes, which requires analysis of attractors, the long-term stable states. While many methods have been proposed to detection and enumeration of attractors, there are no methods which have been demonstrated to be theoretically better than the naive method and be practically used for large biological BNs. Here, we present a novel method to calculate attractors based on a priori information, which works much and verifiably faster than the naive method. We apply the method to two BNs which differ in size, modeling formalism, and biological scope. Despite these differences, the method presented here provides a powerful tool for the analysis of both networks. First, our analysis of a BN studying the effect of the microenvironment during angiogenesis shows that the previously defined microenvironments inducing the specialized phalanx behavior in endothelial cells (ECs) additionally induce stalk behavior. We obtain this result from an extended network version which was previously not analyzed. Second, we were able to heuristically detect attractors in a cell cycle control network formalized as a bipartite Boolean model (bBM) with 3158 nodes. These attractors are directly interpretable in terms of genotype-to-phenotype relationships, allowing network validation equivalent to an in silico mutagenesis screen. Our approach contributes to the development of scalable analysis methods required for whole-cell modeling efforts.

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Rohayani, Hetty, Erick Fernando, and Derist Touriano. "Investigating the Ethernet and Boolean Logic." Indonesian Journal of Electrical Engineering and Computer Science 3, no. 1 (June 4, 2016): 194. http://dx.doi.org/10.11591/ijeecs.v3.i1.pp194-199.

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<p>Write-ahead logging to work. After years of research that are typical in Moore's Law, validate multi-processor investigation, which embodies the principles of intuitive machine learning. Our focus in this paper is not on whether a symmetric encryption can be made metamorphic, probabilistic, adaptive, efficient wearable, and interposable, but rather the introduction of new wireless communication (SCHAH). The properties SCHAH highly dependent on the assumptions inherent in our framework; in this section, we consider the methodology which consists of n access point. Implementation of our applications are replicated, symbiosis, and with large scale yangmemiliki full control over homegrown database, as may be necessary in order to control and access points are not compatible. A collection of shell scripts contains about 85 x86 assembly instructions. Where the engine and is fully compliant courseware follows the sensor network evaluation, although SCHAH not able to give a lot of kernel at a time. </p>

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Bull, Larry. "Evolving Multi-valued Regulatory Networks on Tunable Fitness Landscapes." Complex Systems 32, no. 3 (December 15, 2023): 289–307. http://dx.doi.org/10.25088/complexsystems.32.3.289.

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Random Boolean networks have been used widely to explore aspects of gene regulatory networks. As the name implies, traditionally the model has used a binary representation scheme. This paper uses a modified form of the model to systematically explore the effects of increasing the number of gene states. These random multi-valued networks are evolved within rugged fitness landscapes to explore their behavior. Results suggest the basic properties of the original model remain, regardless of the update scheme or fitness sampling method. Changes are seen in sensitivity to high levels of connectivity, the mutation rate and the ability to vary network size.

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STOCKER, ROB, DAVID CORNFORTH, and DAVID G. GREEN. "A SIMULATION OF THE IMPACT OF MEDIA ON SOCIAL COHESION." Advances in Complex Systems 06, no. 03 (September 2003): 349–59. http://dx.doi.org/10.1142/s0219525903000931.

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One impact of the introduction of television, according to widely held views, is an undermining of traditional values and social organization. In this study, we simulate this process by representing social communication as a Random Boolean Network in which the individuals are nodes, and each node's state represents an opinion (yes/no) about some issue. Television is modelled as having a direct link to every node in the network. Two scenarios were considered. First, we found that, except in the most well connected networks, television rapidly breaks down cohesion (agreement in opinion). Second, the introduction of Hebbian learning leads to a polarizing effect : one subgroup strongly retains the original opinion, while a splinter group adopts the contrary opinion. The system displays criticality with respect to connectivity and the level of exposure to television. More generally, the results suggest that patterns of communication in networks can help to explain a wide variety of social phenomena.

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ALONSO-SANZ, RAMÓN, and JUAN PABLO CÁRDENAS. "EFFECT OF MEMORY ON BOOLEAN NETWORKS WITH DISORDERED DYNAMICS: THE K = 4 CASE." International Journal of Modern Physics C 18, no. 08 (August 2007): 1313–27. http://dx.doi.org/10.1142/s0129183107011340.

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In standard Cellular Automata (CA) and Boolean Networks (BN), the new state of a cell depends on the neighborhood configuration only at the preceding time step. The effect of implementing memory in cells on CA, CA on networks and BN with different degrees of random rewiring is studied in this paper paying attention to the particular case of four inputs. As a rule, memory in cells induces a moderation in the rate of changing cells and in the damage spreading, albeit in the latter case memory turns out ineffective in the control of the damage as the wiring network moves away of the ordered structure that features proper CA.

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