25 papers · ranked by Valyu relevance
Adilson E. Motter
An increasing number of complex systems are now modeled as networks of coupled dynamical entities. Nonlinearity and high-dimensionality are hallmarks of the dynamics of such networks but have generally been regarded as obstacles to control. Here I discuss recent advances on mathematical and computational approaches to…
Dave McKenney, Tony White
Background Complex networks are found in many domains and the control of these networks is a research topic that continues to draw increasing attention. This paper proposes a method of network control that attempts to maintain a specified target distribution of the network state. In contrast to many existing network…
Guoqi Li, Lei Deng, Gaoxi Xiao, Pei Tang + 5 more
'Jing Pei' 'Luping Shi' 'H. Eugene Stanley'] Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural…
Lukas Schoenenberger, Radu Tanase
Notwithstanding the usefulness of system dynamics in analyzing complex policy problems, policy design is far from straightforward and in many instances trialand-error driven. To address this challenge, we propose to combine system dynamics with network controllability, an emerging field in network science, to…
Elena Wu-Yan, Richard F. Betzel, Evelyn Tang, Shi Gu + 2 more
'Fabio Pasqualetti' 'Danielle S. Bassett'] The control of networked dynamical systems opens the possibility for new discoveries and therapies in systems biology and neuroscience. Recent theoretical advances provide candidate mechanisms by which a system can be driven from one pre-specified state to another, and…
Zhe-Ming Lu, Xin-Feng Li, Wen-Bo Du
Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model…
Evan D. Anderson, Lav R. Varshney, Babak Hemmatian, Pablo D. Robles-Granda + 5 more
Research in network neuroscience demonstrates that human intelligence is shaped by the structural brain connectome, which enables a globally coordinated and dynamic architecture for general intelligence. Building on this perspective, the network neuroscience theory proposes that intelligence arises from system-wide…
Andrea I. Luppi, S. Parker Singleton, Justine Y. Hansen, Danilo Bzdok + 3 more
Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain’s network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the…
Piotr Gawłowicz, Anatolij Zubow, Mikołaj Chwalisz, Adam Wolisz
lassical control and management plane for computer networks is addressing individual parameters of protocol layers within an individual wireless network device. We argue that this is not sufficient in phase of increasing deployment of highly re-configurable systems, as well as heterogeneous wireless systems co-existing…
Yang Lou, Yaodong He, Lin Wang, Guanrong Chen
—Network controllability measures how well a networked system can be controlled to a target state, and its robustness reflects how well the system can maintain the controllability against malicious attacks by means of node-removals or edgeremovals. The measure of network controllability is quantified by the number of…
Yang Lou, Yaodong He, Lin Wang, Kim Fung Tsang + 1 more
—Network controllability robustness reflects how well a networked system can maintain its controllability against destructive attacks. Its measure is quantified by a sequence of values that record the remaining controllability of the network after a sequence of node-removal or edge-removal attacks. Traditionally, the…
Roberto Bernal Jaquez, Luis Angel Alarcón Ramos, Alexander Schaum
The problem of controlling a spreading process in a two-layer multiplex networks in such a way that the extinction state becomes a global attractor is addressed. The problem is formulated in terms of a Markov-chain based susceptible-infected-susceptible (SIS) dynamics in a complex multilayer network. The stabilization…
Aming Li, Yang‐Yu Liu
Network science has experienced unprecedented rapid development in the past two decades. The network perspective has also been widely applied to explore various complex systems in great depth. In the first decade, fundamental characteristics of complex network structure, such as the smallworldness, scale-freeness, and…
Yumi Shikauchi, Mitsuaki Takemi, Leo Tomasevic, Jun Kitazono + 2 more
The brain can be conceptualized as a control system facilitating transitions between states, such as from rest to motor activity. Applying network control theory to measurements of brain signals enables characterization of brain dynamics through control properties, including controllability. However, most prior studies…
Noah J. Cowan, Erick J. Chastain, Daril A. Vilhena, James S. Freudenberg + 2 more
'James S. Freudenberg' 'Carl T. Bergstrom' 'Frank Emmert-Streib'] Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although…
Xizhe Zhang, Qian Li
Controlling a complex network is of great importance in many applications. The network can be controlled by inputting external control signals through some selected nodes, which are called input nodes. Previous works found that the majority of the nodes in dense networks are either the input nodes or not, which leads…
Julia Elina Stocker, Erfan Nozari, Marieke van Vugt, Andreas Jansen + 1 more
Recent progress in network sciences has made it possible to apply key findings from control theory to the study of networks. Referred to as network control theory, this framework describes how the interactions between interconnected system elements and external energy sources, potentially constrained by different…
Jonathan de C. Silva, Joel J. P. C. Rodrigues, Jalal Al-Muhtadi, Ricardo A. L. Rabêlo + 1 more
Internet of Things (IoT) management systems require scalability, standardized communication, and context-awareness to achieve the management of connected devices with security and accuracy in real environments. Interoperability and heterogeneity between hardware and application layers are also critical issues. To…
Hamidreza Jamalabadi, Agnieszka Zuberer, Vinod Jangir Kumar, Meng Li + 5 more
Brain controllability properties are normally derived from the white matter fiber tracts in which the neural substrate of the actual energy consumption, namely the gray matter, has been widely ignored. Here, we study the relationship between gray matter volume of regions across the whole cortex and their respective…
Subham Dey, Eesha Bharti, Zhi-De Deng
In this paper, we investigate the edge controllability properties of the macaque structural connectome, which is reconstructed using optimal tractography parameters. We derive the expression of edge modal controllability and edge average controllability, providing a mathematical framework to analyze their roles from a…
Simachew Abebe Mengiste, Ad Aertsen, Arvind Kumar
Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex systems show dynamic changes in their network connectivity, it is…
Aliye Hazal Koyuncu, Jacopo Movilli, Sevil Sahin, Dmitrii V. Kriukov + 2 more
This work describes a competing activation network, which is regulated by chemical feedback at the liquid-surface interface. Feedback loops dynamically tune the concentration of chemical components in living systems, thereby controlling regulatory processes in neural, genetic, and metabolic networks. Advances in…
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This paper presents an empirical comparison of process control algorithms, with particular emphasis on classical Proportional–Integral–Derivative (PID) control, Model Predictive Control (MPC), and neural network-based methods in the context of complex industrial plants. Since industrial sectors frequently demand…
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Artificial intelligence (AI) is reshaping chemical engineering. Still, its role in safety-critical operations is limited because we rarely see tools that link physical models with data-driven methods. This study brings together three elements: physics-constrained neural networks, uncertainty quantification, and a…
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Molecular mechanisms governing initiation steps of the assembly of thousands of endogenous multi-protein complexes (EMCs) remain incompletely understood. Here, multiple lines of observations are reported reflecting the biological functions-aligned initiation sequence of hybrid assembly pathways (HAPs) of EMCs. HAPs…