Results for 'computational'

975 found
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  1. Randomness and Recursive Enumerability.Siam J. Comput - unknown
    One recursively enumerable real α dominates another one β if there are nondecreasing recursive sequences of rational numbers (a[n] : n ∈ ω) approximating α and (b[n] : n ∈ ω) approximating β and a positive constant C such that for all n, C(α − a[n]) ≥ (β − b[n]). See [R. M. Solovay, Draft of a Paper (or Series of Papers) on Chaitin’s Work, manuscript, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, 1974, p. 215] and [G. J. (...)
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  2. Extending Ourselves: Computational Science, Empiricism, and Scientific Method.Paul Humphreys - 2004 - New York, US: Oxford University Press.
    Computational methods such as computer simulations, Monte Carlo methods, and agent-based modeling have become the dominant techniques in many areas of science. Extending Ourselves contains the first systematic philosophical account of these new methods, and how they require a different approach to scientific method. Paul Humphreys draws a parallel between the ways in which such computational methods have enhanced our abilities to mathematically model the world, and the more familiar ways in which scientific instruments have expanded our access (...)
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  3. Computational models of emotion. Marsella, S., Gratch, J., Petta & P. - 2010 - In Klaus R. Scherer, Tanja Bänziger & Etienne Roesch (eds.), A Blueprint for Affective Computing: A Sourcebook and Manual. Oxford University Press.
  4.  26
    Comparative, continuity, and computational evidence in evolutionary theory: Predictive evidence versus productive evidence.David M. W. Powers - 2006 - Behavioral and Brain Sciences 29 (3):294-296.
    Of three types of evidence available to evolution theorists – comparative, continuity, and computational – the first is largely productive rather than predictive. Although comparison between extant species or languages is possible and can be suggestive of evolutionary processes, leading to theory development, comparison with extinct species and languages seems necessary for validation. Continuity and computational evidence provide the best opportunities for supporting predictions.
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  5. Computational Intelligence Approaches and Methods for Security Engineering-Development of an Attack Packet Generator Applying an NP to the Intelligent APS.Wankyung Kim & Wooyoung Soh - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes In Computer Science. Springer Verlag. pp. 4252--709.
  6.  10
    Überblick Computational Intelligence.Oliver Kramer - 2009 - In L. Magnani (ed.), computational intelligence. pp. 1--12.
  7.  27
    A Computational Model of Oncogenesis using the Systemic Approach.Sorinel A. Oprisan - 2006 - Axiomathes 16 (1):155-163.
    A new theoretical model of oncogenesis that incorporates a systemic view of biodynamics was developed and analyzed. According to our model, the emergent behavior at the cell population level is the result of nonlinear interactions between the neoplastic and immune subsystems. Our approach allows subsequent extensions of the model to span multiple levels of biological organization. The model opens the possibility of a flexible connection between the molecular and tissue level descriptions of oncogenesis.
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  8. (1 other version)Language and mentality: Computational, representational, and dispositional conceptions.James H. Fetzer - 1989 - Behaviorism 17 (1):21-39.
    The purpose of this paper is to explore three alternative frameworks for understanding the nature of language and mentality, which accent syntactical, semantical, and pragmatical aspects of the phenomena with which they are concerned, respectively. Although the computational conception currently exerts considerable appeal, its defensibility appears to hinge upon an extremely implausible theory of the relation of form to content. Similarly, while the representational approach has much to recommend it, its range is essentially restricted to those units of language (...)
     
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  9.  6
    A Model for Proustian Decay.Computer Lars - 2024 - Nordic Journal of Aesthetics 33 (67).
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  10.  22
    Hector freytes, Antonio ledda, Giuseppe sergioli and.Roberto Giuntini & Probabilistic Logics in Quantum Computation - 2013 - In Hanne Andersen, Dennis Dieks, Wenceslao J. Gonzalez, Thomas Uebel & Gregory Wheeler (eds.), New Challenges to Philosophy of Science. Springer Verlag. pp. 49.
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  11.  70
    Marr’s Computational Level and Delineating Phenomena.Oron Shagrir & William Bechtel - unknown
    A key component of scientific inquiry, especially inquiry devoted to developing mechanistic explanations, is delineating the phenomenon to be explained. The task of delineating phenomena, however, has not been sufficiently analyzed, even by the new mechanistic philosophers of science. We contend that Marr’s characterization of what he called the computational level provides a valuable resource for understanding what is involved in delineating phenomena. Unfortunately, the distinctive feature of Marr’s computational level, his dual emphasis on both what is computed (...)
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  12. The computational and the representational language-of-thought hypotheses.David J. Chalmers - 2023 - Behavioral and Brain Sciences 46:e269.
    There are two versions of the language-of-thought hypothesis (LOT): Representational LOT (roughly, structured representation), introduced by Ockham, and computational LOT (roughly, symbolic computation) introduced by Fodor. Like many others, I oppose the latter but not the former. Quilty-Dunn et al. defend representational LOT, but they do not defend the strong computational LOT thesis central to the classical-connectionist debate.
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  13. Computational capacity of pyramidal neurons in the cerebral cortex.Danko D. Georgiev, Stefan K. Kolev, Eliahu Cohen & James F. Glazebrook - 2020 - Brain Research 1748:147069.
    The electric activities of cortical pyramidal neurons are supported by structurally stable, morphologically complex axo-dendritic trees. Anatomical differences between axons and dendrites in regard to their length or caliber reflect the underlying functional specializations, for input or output of neural information, respectively. For a proper assessment of the computational capacity of pyramidal neurons, we have analyzed an extensive dataset of three-dimensional digital reconstructions from the NeuroMorphoOrg database, and quantified basic dendritic or axonal morphometric measures in different regions and layers (...)
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  14. Epistemic issues in computational reproducibility: software as the elephant in the room.Alexandre Hocquet & Frédéric Wieber - 2021 - European Journal for Philosophy of Science 11 (2):1-20.
    Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often (...)
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  15.  65
    Computational Perspectives in the History of Science: To the Memory of Peter Damerow.Manfred D. Laubichler, Jane Maienschein & Jürgen Renn - 2013 - Isis 104 (1):119-130.
    Computational methods and perspectives can transform the history of science by enabling the pursuit of novel types of questions, dramatically expanding the scale of analysis , and offering novel forms of publication that greatly enhance access and transparency. This essay presents a brief summary of a computational research system for the history of science, discussing its implications for research, education, and publication practices and its connections to the open-access movement and similar transformations in the natural and social sciences (...)
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  16. Computational Representation of Practical Argument.Katie Atkinson, Trevor Bench-Capon & Peter McBurney - 2006 - Synthese 152 (2):157-206.
    In this paper we consider persuasion in the context of practical reasoning, and discuss the problems associated with construing reasoning about actions in a manner similar to reasoning about beliefs. We propose a perspective on practical reasoning as presumptive justification of a course of action, along with critical questions of this justification, building on the account of Walton. From this perspective, we articulate an interaction protocol, which we call PARMA, for dialogues over proposed actions based on this theory. We outline (...)
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  17. The computational philosophy: simulation as a core philosophical method.Conor Mayo-Wilson & Kevin J. S. Zollman - 2021 - Synthese 199 (1-2):3647-3673.
    Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.
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  18.  85
    Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization.Richard L. Lewis, Andrew Howes & Satinder Singh - 2014 - Topics in Cognitive Science 6 (2):279-311.
    We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the (...)
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  19.  53
    Dynamic Imagery: A Computational Model of Motion and Visual Analogy.David Croft & Paul Thagard - unknown
    This paper describes DIVA (Dynamic Imagery for Visual Analogy), a computational model of visual imagery based on the scene graph, a powerful representational structure widely used in computer graphics. Scene graphs make possible the visual display of complex objects, including the motions of individual objects. Our model combines a semantic-network memory system with computational procedures based on scene graphs. The model can account for people’s ability to produce visual images of moving objects, in particular the ability to use (...)
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  20.  40
    The computational complexity of hybrid temporal logics.C. Areces, P. Blackburn & M. Marx - 2000 - Logic Journal of the IGPL 8 (5):653-679.
    In their simplest form, hybrid languages are propositional modal languages which can refer to states. They were introduced by Arthur Prior, the inventor of tense logic, and played an important role in his work: because they make reference to specific times possible, they remove the most serious obstacle to developing modal approaches to temporal representation and reasoning. However very little is known about the computational complexity of hybrid temporal logics.In this paper we analyze the complexity of the satisfiability problem (...)
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  21.  95
    Computational Neuroethology: A Provisional Manifesto.D. Cliff - 1990 - In Jean-Arcady Meyer & Stewart W. Wilson (eds.), From Animals to Animats: Proceedings of The First International Conference on Simulation of Adaptive Behavior (Complex Adaptive Systems). Cambridge University Press.
  22. The first computational theory of mind and brain: A close look at McCulloch and Pitts' Logical Calculus of Ideas Immanent in Nervous Activity.Gualtiero Piccinini - 2004 - Synthese 141 (2):175-215.
    Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism in (...)
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  23. Against Computational Perspectivalism.Dimitri Coelho Mollo - 2021 - British Journal for the Philosophy of Science 72 (4):1129-1153.
    Computational perspectivalism has been recently proposed as an alternative to mainstream accounts of physical computation, and especially to the teleologically-based mechanistic view. It takes physical computation to be partly dependent on explanatory perspectives and eschews appeal to teleology in helping individuate computational systems. I assess several varieties of computational perspectivalism, showing that they either collapse into existing non-perspectival views or end up with unsatisfactory or implausible accounts of physical computation. Computational perspectivalism fails, therefore, to be a (...)
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  24. The fortieth annual lecture series 1999-2000.Brain Computations & an Inevitable Conflict - 2000 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 31:199-200.
  25.  13
    Developing Teaching Practice in Computational Thinking in Palestine.Abdel Ghani, David Griffiths, Soheil Salha, Saida Affouneh, Fakher Khalili, Zuheir N. Khlaif & Daniel Burgos - 2022 - Frontiers in Psychology 13.
    Sporadic efforts have been made to introduce computational thinking methods into K-12 education in Palestine, but these have been held back by the challenging educational environment. However, a recent in-service training initiative, funded and organized by the Ministry or Education of Palestine, constitutes a significant effort to embed computational thinking in K-12 practice. The middle school teachers who participated in the training course were invited to participate in the present study, and 38 did so. A qualitative approach involving (...)
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  26.  69
    Distinguishing between the computational and dynamical hypotheses: What difference makes the difference?Steven R. Quartz - 1998 - Behavioral and Brain Sciences 21 (5):649-650.
    Van Gelder seeks to distinguish between the computational and the dynamical hypotheses primarily on the basis of ontic criteria – the kind of systems cognitive agents really are. I suggest that this meets with mixed success. By shifting to epistemic criteria – what kind of explanations we require to understand cognitive agents – I suggest there is an easier and more intuitive way to distinguish between these two competing views of cognitive agents.
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  27.  87
    Quantifiers and Cognition: Logical and Computational Perspectives.Jakub Szymanik - 2016 - Springer.
    This volume on the semantic complexity of natural language explores the question why some sentences are more difficult than others. While doing so, it lays the groundwork for extending semantic theory with computational and cognitive aspects by combining linguistics and logic with computations and cognition. -/- Quantifier expressions occur whenever we describe the world and communicate about it. Generalized quantifier theory is therefore one of the basic tools of linguistics today, studying the possible meanings and the inferential power of (...)
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  28.  8
    A Computational Logic Handbook.Robert S. Boyer & J. Strother Moore - 1988
  29. Computational studies of consciousness.I. Aleksander & H. Morton - 2008 - In Rahul Banerjee & Bikas K. Chakrabarti (eds.), Models of brain and mind: physical, computational, and psychological approaches. Boston: Elsevier.
     
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  30.  21
    Computational Models of Ethical Reasoning: Challenges, Initial Steps, and Future Directions.Bruce M. McLaren - 2011 - In Michael Anderson & Susan Leigh Anderson (eds.), Machine Ethics. Cambridge Univ. Press. pp. 297--315.
  31.  2
    A computational model of argumentation schemes for multi-agent systems.Fabrizio Macagno - 2021 - Argument and Computation 12 (3):357-395.
    There are many benefits of using argumentation-based techniques in multi-agent systems, as clearly shown in the literature. Such benefits come not only from the expressiveness that argumentation-based techniques bring to agent communication but also from the reasoning and decision-making capabilities under conditions of conflicting and uncertain information that argumentation enables for autonomous agents. When developing multi-agent applications in which argumentation will be used to improve agent communication and reasoning, argumentation schemes (reasoning patterns for argumentation) are useful in addressing the requirements (...)
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  32. Computational models of episodic memory.Kenneth A. Norman, G. J. Detre & Sean M. Polyn - 2008 - In Ron Sun (ed.), The Cambridge handbook of computational psychology. New York: Cambridge University Press. pp. 189--224.
     
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  33. A Computational Framework for Concept Representation in Cognitive Systems and Architectures: Concepts as Heterogeneous Proxytypes.Antonio Lieto - 2014 - Proceedings of 5th International Conference on Biologically Inspired Cognitive Architectures, Boston, MIT, Pocedia Computer Science, Elsevier:1-9.
    In this paper a possible general framework for the representation of concepts in cognitive artificial systems and cognitive architectures is proposed. The framework is inspired by the so called proxytype theory of concepts and combines it with the heterogeneity approach to concept representations, according to which concepts do not constitute a unitary phenomenon. The contribution of the paper is twofold: on one hand, it aims at providing a novel theoretical hypothesis for the debate about concepts in cognitive sciences by providing (...)
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  34.  15
    Computational Philosophy: Reflections on the PolyGraphs Project.Brian Ball - unknown
    Talk at the Philosophy [in:of:for:and] Digital Knowledge Infrastructures online workshop (08/09/2022).
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  35. BRAIN Journal - Connectionism vs. Computational Theory of Mind.Angel Garrido - unknown
    ABSTRACT Usually, the problems in AI may be many times related to Philosophy of Mind, and perhaps because this reason may be in essence very disputable. So, for instance, the famous question: Can a machine think? It was proposed by Alan Turing [16]. And it may be the more decisive question, but for many people it would be a nonsense. So, two of the very fundamental and more confronted positions usually considered according this line include the Connectionism and the (...) Theory of Mind. We analyze here its content, with their past disputes, and current situation. (shrink)
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  36.  58
    Computational enactivism under the free energy principle.Tomasz Korbak - 2019 - Synthese 198 (3):2743-2763.
    In this paper, I argue that enactivism and computationalism—two seemingly incompatible research traditions in modern cognitive science—can be fruitfully reconciled under the framework of the free energy principle. FEP holds that cognitive systems encode generative models of their niches and cognition can be understood in terms of minimizing the free energy of these models. There are two philosophical interpretations of this picture. A computationalist will argue that as FEP claims that Bayesian inference underpins both perception and action, it entails a (...)
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  37.  21
    Computational insights into human perceptual expertise for familiar and unfamiliar face recognition.Nicholas M. Blauch, Marlene Behrmann & David C. Plaut - 2021 - Cognition 208 (C):104341.
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  38.  90
    Computational Modelling of Culture and Affect.Ruth Aylett & Ana Paiva - 2012 - Emotion Review 4 (3):253-263.
    This article discusses work on implementing emotional and cultural models into synthetic graphical characters. An architecture, FAtiMA, implemented first in the antibullying application FearNot! and then extended as FAtiMA-PSI in the cultural-sensitivity application ORIENT, is discussed. We discuss the modelling relationships between culture, social interaction, and cognitive appraisal. Integrating a lower level homeostatically based model is also considered as a means of handling some of the limitations of a purely symbolic approach. Evaluation to date is summarised and future directions discussed.
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  39.  59
    Rationality from a computational standpoint.Donald E. Campbell - 1978 - Theory and Decision 9 (3):255-266.
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  40.  28
    The view of a computational animal.Anya Hurlbert - 1992 - Behavioral and Brain Sciences 15 (1):39-40.
  41. Report on the computational dialectics workshop.Ron Loui - manuscript
    Dialectic is the fancy word for debate. AI contributes to the logic and processing of argument and uses ideas of argument in its models of communication; as it continues to do this, the computational study of dialectic, like the computational study of argument, is inevitable.
     
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  42.  25
    Computational Social Choice, 3–5 September.Ulle Endriss - 2008 - The Reasoner 2 (10):9-10.
  43.  35
    Computational Neuroscience: From Biology to Cognition.Randall C. O'Reilly & Yuko Munakata - 2003 - In L. Nadel (ed.), Encyclopedia of Cognitive Science. Nature Publishing Group.
  44.  99
    (1 other version)A computational interpretation of conceptivism.Thomas Macaulay Ferguson - 2014 - Journal of Applied Non-Classical Logics 24 (4):333-367.
    The hallmark of the deductive systems known as ‘conceptivist’ or ‘containment’ logics is that for all theorems of the form , all atomic formulae appearing in also appear in . Significantly, as a consequence, the principle of Addition fails. While often billed as a formalisation of Kantian analytic judgements, once semantics were discovered for these systems, the approach was largely discounted as merely the imposition of a syntactic filter on unrelated systems. In this paper, we examine a number of prima (...)
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  45. (1 other version)Computational models.Paul Humphreys - 2002 - Proceedings of the Philosophy of Science Association 2002 (3):S1-S11.
    A different way of thinking about how the sciences are organized is suggested by the use of cross‐disciplinary computational methods as the organizing unit of science, here called computational templates. The structure of computational models is articulated using the concepts of construction assumptions and correction sets. The existence of these features indicates that certain conventionalist views are incorrect, in particular it suggests that computational models come with an interpretation that cannot be removed as well as a (...)
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  46.  33
    Validating computational models: A critique of Anderson's indeterminacy of representation claim.Zenon W. Pylyshyn - 1979 - Psychological Review 86 (4):383-394.
  47.  24
    (1 other version)Computational semantics for monadic quantifiers in natural language.J. Szymanik - 2007 - Studia Semiotyczne 26:219-244.
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  48.  12
    A computational literary theory: the ultimate products of the brain/mind machine.Akifumi Tokosumi - 2001 - In Tadashi Kitamura (ed.), What Should Be Computed to Understand and Model Brain Function?: From Robotics, Soft Computing, Biology and Neuroscience to Cognitive Philosophy. World Scientific. pp. 3--43.
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  49.  10
    Computer Science Logic: 11th International Workshop, CSL'97, Annual Conference of the EACSL, Aarhus, Denmark, August 23-29, 1997, Selected Papers.M. Nielsen, Wolfgang Thomas & European Association for Computer Science Logic - 1998 - Springer Verlag.
    This book constitutes the strictly refereed post-workshop proceedings of the 11th International Workshop on Computer Science Logic, CSL '97, held as the 1997 Annual Conference of the European Association on Computer Science Logic, EACSL, in Aarhus, Denmark, in August 1997. The volume presents 26 revised full papers selected after two rounds of refereeing from initially 92 submissions; also included are four invited papers. The book addresses all current aspects of computer science logics and its applications and thus presents the state (...)
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  50.  22
    Exploring Computational Thinking Skills Training Through Augmented Reality and AIoT Learning.Yu-Shan Lin, Shih-Yeh Chen, Chia-Wei Tsai & Ying-Hsun Lai - 2021 - Frontiers in Psychology 12.
    Given the widespread acceptance of computational thinking in educational systems around the world, primary and higher education has begun thinking about how to cultivate students' CT competences. The artificial intelligence of things combines artificial intelligence and the Internet of things and involves integrating sensing technologies at the lowest level with relevant algorithms in order to solve real-world problems. Thus, it has now become a popular technological application for CT training. In this study, a novel AIoT learning with Augmented Reality (...)
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