Results for 'System control'

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  1.  21
    How does the nervous system control the equilibrium trajectory?S. V. Adamovich - 1992 - Behavioral and Brain Sciences 15 (4):704-705.
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  2.  58
    What muscle variable(s) does the nervous system control in limb movements?R. B. Stein - 1982 - Behavioral and Brain Sciences 5 (4):535-541.
    To controlforceaccurately under a wide range of behavioral conditions, the central nervous system would either require a detailed, continuously updated representation of the state of each muscle (and the load against which each is acting) or else force feedback with sufficient gain to cope with variations in the properties of the muscles and loads. The evidence for force feedback with adequate gain or for an appropriate central representation is not sufficient to conclude that force is the major controlled variable (...)
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  3.  9
    Episodic Knowledge in System Control.Klaus B. Bærentsen - 1996 - In Roland Posner, Heinz Klein, Peter B. Andersen & Berit Holmqvist (eds.), Signs of Work: Semiosis and Information Processing in Organisations. De Gruyter. pp. 283-324.
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  4.  15
    The motor system controls what it senses.William A. MacKay - 1982 - Behavioral and Brain Sciences 5 (4):557-557.
  5.  25
    System structure and cognitive ability as predictors of performance in dynamic system control tasks.Jan Hundertmark, Daniel V. Holt, Andreas Fischer, Nadia Said & Helen Fischer - 2015 - Journal of Dynamic Decision Making 1 (1).
    In dynamic system control, cognitive mechanisms and abilities underlying performance may vary depending on the nature of the task. We therefore investigated the effects of system structure and its interaction with cognitive abilities on system control performance. A sample of 127 university students completed a series of different system control tasks that were manipulated in terms of system size and recurrent feedback, either with or without a cognitive load manipulation. Cognitive abilities assessed (...)
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  6.  41
    A speech-motor-system perspective on nervous-system-control variables.James H. Abbs - 1982 - Behavioral and Brain Sciences 5 (4):541-542.
  7.  12
    Regulation of division of labour between cognitive systems controlling action.E. Adi-Japha - 2000 - Cognition 76 (1):1-11.
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  8.  22
    Systems analysis in the study of the motor-control system: Control theory alone is insufficient.R. E. Kearney & I. W. Hunter - 1982 - Behavioral and Brain Sciences 5 (4):553-554.
  9. Temporal sequences patterns learning and dynamic system control (DSC).M. Pandin, G. Didone & S. Bicciato - 2000 - Consciousness and Cognition 9 (2):S80 - S81.
  10.  23
    Approaches to Cognitive Modeling in Dynamic Systems Control.Daniel V. Holt & Magda Osman - 2017 - Frontiers in Psychology 8.
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  11.  10
    Eingesandte Literatur : Technological Concepts and Mathematical Models in the Evolution of Modern Engineering Systems. Controlling— Managing— Organizing von Mario Lucertini, Ana Millán Gasca und Fernando Nicolò.F. Krafft - 2004 - Berichte Zur Wissenschafts-Geschichte 27 (2):148-148.
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  12.  67
    Recommendation Systems as Technologies of the Self: Algorithmic Control and the Formation of Music Taste.Nedim Karakayali, Burc Kostem & Idil Galip - 2018 - Theory, Culture and Society 35 (2):3-24.
    The article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utilize the website to receive guidance about music products but also to examine and transform an aspect of their self, i.e. their ‘music taste’. The capacity of assisting users in self-cultivation practices, however, is not unique to (...)
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  13.  60
    Moral control and ownership in AI systems.Raul Gonzalez Fabre, Javier Camacho Ibáñez & Pedro Tejedor Escobar - 2021 - AI and Society 36 (1):289-303.
    AI systems are bringing an augmentation of human capabilities to shape the world. They may also drag a replacement of human conscience in large chunks of life. AI systems can be designed to leave moral control in human hands, to obstruct or diminish that moral control, or even to prevent it, replacing human morality with pre-packaged or developed ‘solutions’ by the ‘intelligent’ machine itself. Artificial Intelligent systems (AIS) are increasingly being used in multiple applications and receiving more attention (...)
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  14. A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network.Ran Wang, Chunbiao Li, Serdar Çiçek, Karthikeyan Rajagopal & Xin Zhang - 2021 - Complexity 2021:1-17.
    An amplitude controllable hyperjerk system is constructed for chaos producing by introducing a nonlinear factor of memristor. In this case, the amplitude control is realized from a single coefficient in the memristor. The hyperjerk system has a line of equilibria and also shows extreme multistability indicated by the initial value-associated bifurcation diagram. FPGA-based circuit realization is also given for physical verification. Finally, the proposed memristive hyperjerk system is successfully predicted with artificial neural networks for AI based (...)
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  15. Biological regulation: controlling the system from within.Leonardo Bich, Matteo Mossio, Kepa Ruiz-Mirazo & Alvaro Moreno - 2016 - Biology and Philosophy 31 (2):237-265.
    Biological regulation is what allows an organism to handle the effects of a perturbation, modulating its own constitutive dynamics in response to particular changes in internal and external conditions. With the central focus of analysis on the case of minimal living systems, we argue that regulation consists in a specific form of second-order control, exerted over the core regime of production and maintenance of the components that actually put together the organism. The main argument is that regulation requires a (...)
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  16. Meaningful Human Control over Smart Home Systems: A Value Sensitive Design Approach.Steven Umbrello - 2020 - Humana.Mente Journal of Philosophical Studies 13 (37):40-65.
    The last decade has witnessed the mass distribution and adoption of smart home systems and devices powered by artificial intelligence systems ranging from household appliances like fridges and toasters to more background systems such as air and water quality controllers. The pervasiveness of these sociotechnical systems makes analyzing their ethical implications necessary during the design phases of these devices to ensure not only sociotechnical resilience, but to design them for human values in mind and thus preserve meaningful human control (...)
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  17.  23
    Metacognitive Control of Categorial Neurobehavioral Decision Systems.Gordon R. Foxall - 2016 - Frontiers in Psychology 7.
  18.  69
    Memory systems and the control of skilled action.Wayne Christensen, John Sutton & Kath Bicknell - 2019 - Philosophical Psychology 32 (5):692-718.
    ABSTRACTIn keeping with the dominant view that skills are largely automatic, the standard view of memory systems distinguishes between a representational declarative system associated with cognitive processes and a performance-based procedural system. The procedural system is thought to be largely responsible for the performance of well-learned skilled actions. Here we argue that most skills do not fully automate, which entails that the declarative system should make a substantial contribution to skilled performance. To support this view, we (...)
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  19. Self-control, Attention, and How to live without Special Motivational Powers.Sebastian Watzl - 2022 - In M. Brent & Lisa Miracchi (eds.), Mental Action and the Conscious Mind. Routledge. pp. 272-300.
    It has been argued that the explanation of self-control requires positing special motivational powers. Some think that we need will-power as an irreducible mental faculty; others that we need to think of the active self as a dedicated and depletable pool of psychic energy or – in today more respectable terminology – mental resources; finally, there is the idea that self-control requires postulating a deep division between reason and passion – a deliberative and an emotional motivational system. (...)
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  20.  58
    A Control and Management Network for Wireless ATM Systems.Stephen Bush, Jagannath F., Evans Sunil, B. Joseph, Victor Frost, Gary Minden & K. Sam Shanmugan - 1997 - Acm-Baltzer Wireless Networks 3:267--283.
    This paper describes the design of a control and management network (orderwire) for a mobile wireless Asynchronous Transfer Mode (ATM) network. This mobile wireless ATM network is part of the Rapidly Deployable Radio Network (RDRN). The orderwire system consists of a packet radio network which overlays the mobile wireless ATM network, each network element in this network uses Global Positioning System (GPS) information to control a beamforming antenna subsystem which provides for spatial reuse. This paper also (...)
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  21.  39
    Meaningful Human Control Over Smart Home Systems: A Value Sensitive Design Approach.Steven Umbrello - 2020 - Humana.Mente Journal of Philosophical Studies 13 (37):40-65.
    The last decade has witnessed the mass distribution and adoption of smart home systems and devices powered by artificial intelligence systems ranging from household appliances like fridges and toasters to more background systems such as air and water quality controllers. The pervasiveness of these sociotechnical systems makes analyzing their ethical implications necessary during the design phases of these devices to ensure not only sociotechnical resilience, but to design them for human values in mind and thus preserve meaningful human control (...)
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  22.  99
    Control & intervention in complex adaptive systems: From biology to biogen.Andy Clark - unknown
    Markets, companies and various forms of business organizations may all (we have argued) be usefully viewed through the lens of CAS -- the theory of complex adaptive systems. In this chapter, I address one fundamental issue that confronts both the theoretician and the business manager: the nature and opportunities for control and intervention in complex adaptive regimes. The problem is obvious enough. A complex adaptive system, as we have defined it, is soft assembled and largely self-organizing. This means (...)
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  23. Extended control systems: A theory and its implications.Hunter R. Gentry - 2021 - Philosophical Psychology 34 (3):345-373.
    Philosophers and cognitive scientists alike have recently been interested in whether cognition extends beyond the boundaries of skin and skull and into the environment. However, the extended cognition hypothesis has suffered many objections over the past few decades. In this paper, I explore the option of control extending beyond the human boundary. My aim is to convince the reader of three things: (i) that control can be implemented in artifacts, (ii) that humans and artifacts can form extended (...) systems, and (iii) that perhaps extended control ought to be preferred over extended cognition. Using the objections to extended cognition as constraints on my own extended theorizing and the example of autofocus systems in cameras, I decompose and localize the components of an autofocus system that realize the central properties of control from a plausible theory of control in the literature. I then provide criteria according to which control can be extended in a system. Finally, I consider how this theory of extended control ought to be preferred to theories of extended cognition. (shrink)
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  24.  13
    Feedback controls and G2 checkpoints: Fission yeast as a model system.Katherine S. Sheldrick & Antony M. Carr - 1993 - Bioessays 15 (12):775-782.
    Dependency relationships within the cell cycle allow cells to arrest the cycle reversibly in response to agents or conditions that interfere with specific aspects of its normal progression. In addition, overlapping pathways exist which also arrest the cell cycle in response to DNA damage. Collectively, these control mechanisms have become known as checkpoints. Analysis of checkpoints is facilitated by the fact that dependency relationships within the cell cycle, such as the dependency of mitosis on the completion of DNA synthesis, (...)
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  25.  9
    Robust Control Design for an Uncertain Macroeconomic Dynamical System with Unknown Characteristics and Inequality Control Constraint.Xiaorui Xie & Ye-Hwa Chen - 2021 - Complexity 2021:1-13.
    The stabilization problem of a macroeconomic dynamical system is considered in this paper. The main features of this system are that the system uncertainties may be unknown functions of state and time but with known bounds. Furthermore, the control inputs are subject to constraints, which is a salient feature in an economic control problem. To ensure that the controls are within the specified boundaries, in our control design procedure, a creative diffeomorphism, which converts bounded (...)
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  26.  12
    System Optimization and Robustness Stability Control for GIS Inspection Robot in Complex Microgrid Networks.Yu Yan, Wei Jiang, Zhiping Luo, Jianjun Zhang & Weidong Liu - 2021 - Complexity 2021:1-12.
    GIS is important equipment in the substation system in a complex microgrid network. Due to the long-term service in harsh operation environments, the electrical performance of GIS equipment will be seriously affected. Therefore, the regular maintenance of GIS equipment in the substation system is a routine task so as to ensure the normal operation of the microgrid networks. The traditional method relies on manual labor, where not only with the low operation efficiency but also regarding some maintenance, labors (...)
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  27. Behavior systems and the contextual control of anxiety, fear, and panic.Mark E. Bouton - 2005 - In Lisa Feldman Barrett, Paula M. Niedenthal & Piotr Winkielman (eds.), Emotion and Consciousness. Guilford Press.
  28.  29
    Adaptive Control Based Harvesting Strategy for a Predator–Prey Dynamical System.Moitri Sen, Ashutosh Simha & Soumyendu Raha - 2018 - Acta Biotheoretica 66 (4):293-313.
    This paper deals with designing a harvesting control strategy for a predator–prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order (...)
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  29.  4
    Living control systems III: the fact of control.William Treval Powers - 2008 - Bloomfield, NJ: Benchmark Publications.
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  30.  17
    Optimal Control for Networked Control Systems with Markovian Packet Losses.Xiao Han, Zhijian Ji & Qingyuan Qi - 2020 - Complexity 2020:1-11.
    This paper is concerned with the optimal output feedback control problem for networked control systems with Markovian packet losses. In this paper, the packet losses occur both between the sensor and controller and between the controller and actuator. Moreover, the packet loss channels are described with two-state Markov chains. Since the precise state information cannot be obtained, thus an optimal recursive estimator is designed. Furthermore, by adopting the dynamic programming approach, we derive the optimal output feedback control, (...)
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  31.  6
    Book Reviews : Social Responses to Large Technical Systems: Control or Anticipation, by Todd R. La Porte, ed. London: Kluwer, 1991, 190 + viii pp. $94.00 (cloth. [REVIEW]David Collingridge - 1993 - Science, Technology and Human Values 18 (4):530-531.
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  32.  24
    Impulsive controller for wireless networked control system: Switched system approach.Yuan-Qing Wu, Hongye Su & Kalidass Mathiyalagan - 2016 - Complexity 21 (5):291-299.
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  33.  14
    Robust Control for the Suspension Cable System of the Unmanned Helicopter with Sensor Fault under Complex Environment.Rong Mei - 2021 - Complexity 2021:1-9.
    Aiming at the suspension cable system of an unmanned helicopter with sensor fault under complex environment, this paper studies the robust antiswing tolerant control scheme. To suppress the swing of the hanging load when the unmanned helicopter is in the forward flight state, a nonlinear line motion model is firstly established. Considering the sensor fault of the unmanned helicopter, a sensor fault estimator is developed. By using the fault estimator output, the robust antiswing tolerant controller is proposed using (...)
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  34.  46
    Control of Complex Nonlinear Dynamic Rational Systems.Quanmin Zhu, Li Liu, Weicun Zhang & Shaoyuan Li - 2018 - Complexity 2018:1-12.
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  35.  5
    Automatic control of computer application data processing system based on artificial intelligence.Ashima Kukkar, Amit Sharma, Lixia Hao & Hong Wang - 2022 - Journal of Intelligent Systems 31 (1):177-192.
    To shorten the travel time and improve comfort, the automatic train driving system is considered to replace manual driving. In this article, an automatic control method of computer application data-processing system based on artificial intelligence is proposed. An automatic train operation (ATO) introduced the structure and function of an autopilot system (train), optimized the train running on the target curve, introduced the basic principle of fuzzy generalized predictive control (PC) algorithm, and combined with the characteristics (...)
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  36. Integrating Multicellular Systems: Physiological Control and Degrees of Biological Individuality.Leonardo Bich - 2023 - Acta Biotheoretica 72 (1):1-22.
    This paper focuses on physiological integration in multicellular systems, a notion often associated with biological individuality, but which has not received enough attention and needs a thorough theoretical treatment. Broadly speaking, physiological integration consists in how different components come together into a cohesive unit in which they are dependent on one another for their existence and activity. This paper argues that physiological integration can be understood by considering how the components of a biological multicellular system are controlled and coordinated (...)
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  37.  44
    Experiments on Socio-Technical Systems: The Problem of Control.Peter Kroes - 2016 - Science and Engineering Ethics 22 (3):633-645.
    My aim is to question whether the introduction of new technologies in society may be considered to be genuine experiments. I will argue that they are not, at least not in the sense in which the notion of experiment is being used in the natural and social sciences. If the introduction of a new technology in society is interpreted as an experiment, then we are dealing with a notion of experiment that differs in an important respect from the notion of (...)
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  38.  2
    Système ou contrôle? Milgram face à ses limites : le rôle de la cybernétique dans l’analyse de l’obéissance à l’autorité.Irlande Saurin - 2024 - Philosophia Scientiae 28-2 (28-2):154-174.
    The value and significance of Stanley Milgram’s experiments on Obedience to Authority have been the subject of a controversy that we propose to analyze in the light of the role played by the reference to cybernetics Milgram introduced in his 1974 work. This reference is part of the series of theoretical analyses proposed by Milgram in the core of his book Obedience to Authority (1974). It constitutes the central basis for the formulation of the concept of the “agentic state”. And (...)
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  39.  21
    ?Biologizing? control theory: How to make a control system come alive.John L. Casti - 2002 - Complexity 7 (4):10-12.
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  40. Control of Perception Should be Operationalized as a Fundamental Property of the Nervous System.Warren Mansell - 2011 - Topics in Cognitive Science 3 (2):257-261.
    This commentary proposes that “cognitive control” is neither componential nor emergent, but a fundamental feature of behavior. The term “control” requires an operational definition. This is best provided by the negative feedback loop that utilizes behavior to control perception; it does not control behavior per se. In order to model complex cognitive control, Perceptual Control Theory proposes that loops are organized into a dissociable hierarchical network (PCT; Powers, Clark, & McFarland, 1960; Powers, 1973a, 2008). (...)
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  41. Memory-guided attention: control from multiple memory systems.J. Benjamin Hutchinson & Nicholas B. Turk-Browne - 2012 - Trends in Cognitive Sciences 16 (12):576-579.
    Attention is strongly influenced by both external stimuli and internal goals. However, this useful dichotomy does not readily capture the ubiquitous and often automatic contribution of past experience stored in memory. We review recent evidence about how multiple memory systems control attention, consider how such interactions are manifested in the brain, and highlight how this framework for ‘memory-guided attention’ might help systematize previous findings and guide future research.
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  42.  45
    Expert systems and computer-controlled decision making in medicine.Barrie Lipscombe - 1989 - AI and Society 3 (3):184-197.
    The search for “usable” expert systems is leading somemedical researchers to question the appropriate role of these programs. Most current systems assume a limited role for the human user, delegating situated “decision-control” to the machine. As expert systems are only able to replace a narrow range of human intellectual functions, this leaves the programs unable to cope with the “constructivist” nature of human knowledge-use. In returning practical control to the human doctor, some researchers are abandoning focusedproblem-solving in favour (...)
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  43.  17
    Networked Control System Design for Turbofan Aeroengines with Aging and Deterioration.Ruichao Li, Sing Kiong Nguang, Yingqing Guo & Yifeng Chen - 2018 - Complexity 2018:1-13.
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  44.  16
    Distributed Control of a Manufacturing System with One-Dimensional Cellular Automata.Irving Barragan-Vite, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Joselito Medina-Marin & Eva S. Hernandez-Gress - 2018 - Complexity 2018:1-15.
    We present a distributed control modeling approach for an automated manufacturing system based on the dynamics of one-dimensional cellular automata. This is inspired by the fact that both cellular automata and manufacturing systems are discrete dynamical systems where local interactions given among their elements can lead to complex dynamics, despite the simple rules governing such interactions. The cellular automaton model developed in this study focuses on two states of the resources of a manufacturing system, namely, busy or (...)
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  45. Autonomous cognitive systems in real-world environments: Less control, more flexibility and better interaction.Vincent C. Müller - 2012 - Cognitive Computation 4 (3):212-215.
    In October 2011, the “2nd European Network for Cognitive Systems, Robotics and Interaction”, EUCogII, held its meeting in Groningen on “Autonomous activity in real-world environments”, organized by Tjeerd Andringa and myself. This is a brief personal report on why we thought autonomy in real-world environments is central for cognitive systems research and what I think I learned about it. --- The theses that crystallized are that a) autonomy is a relative property and a matter of degree, b) increasing autonomy of (...)
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  46.  8
    Premotor systems, motor learning, and ipsilateral control: Learning to get set.Gary Goldberg - 1987 - Behavioral and Brain Sciences 10 (2):323-329.
  47.  50
    Quantized control for polynomial fuzzy discrete-time systems.Qi Zhou, Ziran Chen, Xinchen Li & Yabin Gao - 2016 - Complexity 21 (2):325-332.
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  48.  21
    Adaptive control of nonlinear complex Holling II predator-prey system with unknown parameters.Mohammad Pourmahmood Aghababa - 2016 - Complexity 21 (6):260-266.
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  49.  13
    Topology Control and Medium Access Control (MAC) Protocol for Wireless Sensor Networks (WSNs) in Cyber-Physical System.Ang Li, Chen Zhang, Baoyu Zheng & Lei Li - 2021 - Complexity 2021:1-12.
    The system reachability set is calculated by covering all possible behaviours of the system through a finite number of simulation steps to ensure that the system trajectory stays within a set safety region. In this paper, the theory of the game method is applied to the design of the controller, a very small controller is designed, and good control results are obtained by simulation. The system gradually shows a divergent trend and cannot achieve stable (...). A multihop channel reservation Medium Access Control protocol based on a parallel mechanism is proposed. The multihop channel reservation mechanism is proposed based on periodic node sleep, and the node uses the reservation frame to make the reservation of the channel and transmits the data according to the reservation information; the parallel mechanism is used to make the reservation information and data transmission simultaneously. (shrink)
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  50.  17
    Meaningful Human Control Over Smart Home Systems.Steven Umbrello - 2020 - Humana Mente 13 (37).
    The last decade has witnessed the mass distribution and adoption of smart home systems and devices powered by artificial intelligence systems ranging from household appliances like fridges and toasters to more background systems such as air and water quality controllers. The pervasiveness of these sociotechnical systems makes analyzing their ethical implications necessary during the design phases of these devices to ensure not only sociotechnical resilience, but to design them for human values in mind and thus preserve meaningful human control (...)
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