Results for 'Mechanistic models'

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  1. A mechanistic model of three facets of meaning.Deb Roy - 2008 - In Manuel de Vega, Arthur M. Glenberg & Arthur C. Graesser (eds.), Symbols and embodiment: debates on meaning and cognition. New York: Oxford University Press.
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  2. The challenges of purely mechanistic models in biology and the minimum need for a 'mechanism-plus-X' framework.Sepehr Ehsani - 2018 - Dissertation, University College London
    Ever since the advent of molecular biology in the 1970s, mechanical models have become the dogma in the field, where a "true" understanding of any subject is equated to a mechanistic description. This has been to the detriment of the biomedical sciences, where, barring some exceptions, notable new feats of understanding have arguably not been achieved in normal and disease biology, including neurodegenerative disease and cancer pathobiology. I argue for a "mechanism-plus-X" paradigm, where mainstay elements of mechanistic (...)
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  3. Special Attention to the Self: a Mechanistic Model of Patient RB’s Lost Feeling of Ownership.Hunter Gentry - 2021 - Review of Philosophy and Psychology (1):1-29.
    Patient RB has a peculiar memory impairment wherein he experiences his memories in rich contextual detail, but claims to not own them. His memories do not feel as if they happened to him. In this paper, I provide an explanatory model of RB’s phenomenology, the self-attentional model. I draw upon recent work in neuroscience on self-attentional processing and global workspace models of conscious recollection to show that RB has a self-attentional deficit that inhibits self-bias processes in broadcasting the contents (...)
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  4. Model-based Cognitive Neuroscience: Multifield Mechanistic Integration in Practice.Mark Povich - 2019 - Theory & Psychology 5 (29):640–656.
    Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function (e.g., Weiskopf, 2011). In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function (e.g., Piccinini & Craver, 2011; Povich, 2015). In this paper, I show how model-based cognitive neuroscience (MBCN) epitomizes the integrative mechanistic perspective (...)
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  5. HCI Model with Learning Mechanism for Cooperative Design in Pervasive Computing Environment.Hong Liu, Bin Hu & Philip Moore - 2015 - Journal of Internet Technology 16.
    This paper presents a human-computer interaction model with a three layers learning mechanism in a pervasive environment. We begin with a discussion around a number of important issues related to human-computer interaction followed by a description of the architecture for a multi-agent cooperative design system for pervasive computing environment. We present our proposed three- layer HCI model and introduce the group formation algorithm, which is predicated on a dynamic sharing niche technology. Finally, we explore the cooperative reinforcement learning and fusion (...)
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  6. Mechanist idealisation in systems biology.Dingmar van Eck & Cory Wright - 2020 - Synthese 199 (1-2):1555-1575.
    This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on (...)
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  7. Minimal models of consciousness: Understanding consciousness in human and non-human systems.Wanja Wiese - manuscript
    Should models of consciousness be detailed _mechanistic_ models of particular types of systems, or should they be _minimal_ models that abstract away from the underlying mechanistic details and provide generalisations? Detailed mechanistic models may afford a complete and precise account of consciousness in human beings and other, physiologically similar mammals. But they do not provide a good model of consciousness in other animals, such as non-vertebrates, let alone artificial systems. Minimal models can be (...)
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  8. Minds, models and mechanisms: a new perspective on intentional psychology.Eric Hochstein - 2012 - Journal of Experimental & Theoretical Artificial Intelligence 24 (4):547-557.
    In this article, I argue that intentional psychology (i.e. the interpretation of human behaviour in terms of intentional states and propositional attitudes) plays an essential role in the sciences of the mind. However, this role is not one of identifying scientifically respectable states of the world. Rather, I argue that intentional psychology acts as a type of phenomenological model, as opposed to a mechanistic one. I demonstrate that, like other phenomenological models in science, intentional psychology is a methodological (...)
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  9. How and when are topological explanations complete mechanistic explanations? The case of multilayer network models.Beate Krickel, Leon de Bruin & Linda Douw - 2023 - Synthese 202 (1):1-21.
    The relationship between topological explanation and mechanistic explanation is unclear. Most philosophers agree that at least some topological explanations are mechanistic explanations. The crucial question is how to make sense of this claim. Zednik (Philos Psychol 32(1):23–51, 2019) argues that topological explanations are mechanistic if they (i) describe mechanism sketches that (ii) pick out organizational properties of mechanisms. While we agree with Zednik’s conclusion, we critically discuss Zednik’s account and show that it fails as a general account (...)
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  10. New Mechanistic Explanation and the Need for Explanatory Constraints.L. R. Franklin-Hall - 2016 - In Ken Aizawa & Carl Gillett (eds.), Scientific Composition and Metaphysical Ground. London: Palgrave-Macmillan. pp. 41-74.
    This paper critiques the new mechanistic explanatory program on grounds that, even when applied to the kinds of examples that it was originally designed to treat, it does not distinguish correct explanations from those that blunder. First, I offer a systematization of the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: they must 1) represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Second, (...)
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  11. Mechanistic Explanation in Psychology.Mark Povich - forthcoming - In Hank Stam & Huib Looren De Jong (eds.), The SAGE Handbook of Theoretical Psychology. (Eds.) Hank Stam and Huib Looren de Jong. Sage.
    Philosophers of psychology debate, among other things, which psychological models, if any, are (or provide) mechanistic explanations. This should seem a little strange given that there is rough consensus on the following two claims: 1) a mechanism is an organized collection of entities and activities that produces, underlies, or maintains a phenomenon, and 2) a mechanistic explanation describes, represents, or provides information about the mechanism producing, underlying, or maintaining the phenomenon to be explained (i.e. the explanandum phenomenon) (...)
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  12. The Elusive Higgs Mechanism.Chris Smeenk - 2006 - Philosophy of Science 73 (5):487-499.
    The Higgs mechanism is an essential but elusive component of the Standard Model of particle physics. Without it Yang‐Mills gauge theories would have been little more than a warm‐up exercise in the attempt to quantize gravity rather than serving as the basis for the Standard Model. This article focuses on two problems related to the Higgs mechanism clearly posed in Earman’s recent papers (Earman 2003, 2004a, 2004b): what is the gauge‐invariant content of the Higgs mechanism, and what does it mean (...)
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  13. Mechanistic trends in chemistry.Louis Caruana - 2018 - Substantia 2 (1):29-40.
    During the twentieth century, the mechanistic worldview came under attack mainly because of the rise of quantum mechanics but some of its basic characteristics survived and are still evident within current science in some form or other. Many scholars have produced interesting studies of such significant mechanistic trends within current physics and biology but very few have bothered to explore the effects of this worldview on current chemistry. This paper makes a contribution to fill this gap. It presents (...)
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  14. Functional Analyses, Mechanistic Explanations, and Explanatory Tradeoffs.Sergio Daniel Barberis - 2013 - Journal of Cognitive Science 14:229-251.
    Recently, Piccinini and Craver have stated three theses concerning the relations between functional analysis and mechanistic explanation in cognitive sciences: No Distinctness: functional analysis and mechanistic explanation are explanations of the same kind; Integration: functional analysis is a kind of mechanistic explanation; and Subordination: functional analyses are unsatisfactory sketches of mechanisms. In this paper, I argue, first, that functional analysis and mechanistic explanations are sub-kinds of explanation by scientific (idealized) models. From that point of view, (...)
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  15. Phenomenological Laws and Mechanistic Explanations.Gabriel Siegel & Carl F. Craver - 2024 - Philosophy of Science 91 (1):132-150.
    In light of recent criticisms by Woodward (2017) and Rescorla (2018), we examine the relationship between mechanistic explanation and phenomenological laws. We disambiguate several uses of the phrase “phenomenological law” and show how a mechanistic theory of explanation sorts them into those that are and are not explanatory. We also distinguish the problem of phenomenological laws from arguments about the explanatory power of purely phenomenal models, showing that Woodward and Rescorla conflate these problems. Finally, we argue that (...)
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  16. Intentional Models as Essential Scientific Tools.Eric Hochstein - 2013 - International Studies in the Philosophy of Science 27 (2):199-217.
    In this article, I argue that the use of scientific models that attribute intentional content to complex systems bears a striking similarity to the way in which statistical descriptions are used. To demonstrate this, I compare and contrast an intentional model with a statistical model, and argue that key similarities between the two give us compelling reasons to consider both as a type of phenomenological model. I then demonstrate how intentional descriptions play an important role in scientific methodology as (...)
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  17. Model Organisms are Not (Theoretical) Models.Arnon Levy & Adrian Currie - 2015 - British Journal for the Philosophy of Science 66 (2):327-348.
    Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have (...)
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  18. Mechanisms and Model-Based Functional Magnetic Resonance Imaging.Mark Povich - 2015 - Philosophy of Science 82 (5):1035-1046.
    Mechanistic explanations satisfy widely held norms of explanation: the ability to manipulate and answer counterfactual questions about the explanandum phenomenon. A currently debated issue is whether any nonmechanistic explanations can satisfy these explanatory norms. Weiskopf argues that the models of object recognition and categorization, JIM, SUSTAIN, and ALCOVE, are not mechanistic yet satisfy these norms of explanation. In this article I argue that these models are mechanism sketches. My argument applies recent research using model-based functional magnetic (...)
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  19. Equilibrium explanation as structural non-mechanistic explanation: The case long-term bacterial persistence in human hosts.Javier Suárez & Roger Deulofeu - 2019 - Teorema: International Journal of Philosophy 3 (38):95-120.
    Philippe Huneman has recently questioned the widespread application of mechanistic models of scientific explanation based on the existence of structural explanations, i.e. explanations that account for the phenomenon to be explained in virtue of the mathematical properties of the system where the phenomenon obtains, rather than in terms of the mechanisms that causally produce the phenomenon. Structural explanations are very diverse, including cases like explanations in terms of bowtie structures, in terms of the topological properties of the system, (...)
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  20. Dissertation Abstract - Math Over Mechanism: Proposing the Rational-Relational Theory of Scientific Explanation in Light of Impinging Constraints of New Mechanism.Jenny Nielsen - forthcoming - In ProQuest.
    In this dissertation I achieve the following: (1) I present motivating criteria for a general comprehensive theory of scientific explanation. I review historical approaches to modeling explanation in light of these criteria. (2) I present New Mechanist Explanation ("NME") as the leading candidate for a contemporary, complete theory of scientific explanation. (3) I present constraints on the applicability of New Mechanism in modeling biology, chemistry, and physics. I argue for the unsuitability of NME as a candidate for a general theory (...)
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  21. The Limits of New Mechanism as a General Theory of Scientific Explanation.Nielsen Jenny - forthcoming - Dissertation, University of Kansas
    Dissertation Prospectus. Exploring the limits of New Mechanism as a general theory of scientific explanation, limiting its scope and proposing constraints.
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  22. Synthetic Modeling and Mechanistic Account: Material Recombination and Beyond.Tarja Knuuttila & Andrea Loettgers - 2013 - Philosophy of Science 80 (5):874-885.
    Recently, Bechtel and Abrahamsen have argued that mathematical models study the dynamics of mechanisms by recomposing the components and their operations into an appropriately organized system. We will study this claim through the practice of combinational modeling in circadian clock research. In combinational modeling, experiments on model organisms and mathematical/computational models are combined with a new type of model—a synthetic model. We argue that the strategy of recomposition is more complicated than what Bechtel and Abrahamsen indicate. Moreover, synthetic (...)
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  23. Evaluating Artificial Models of Cognition.Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue (...)
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  24. Prediction and Topological Models in Neuroscience.Bryce Gessell, Matthew Stanley, Benjamin Geib & Felipe De Brigard - 2020 - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New Challenges in the Philosophy of Neuroscience. Springer.
    In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue (...)
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  25. Beyond Formal Structure: A Mechanistic Perspective on Computation and Implementation.Marcin Miłkowski - 2011 - Journal of Cognitive Science 12 (4):359-379.
    In this article, after presenting the basic idea of causal accounts of implementation and the problems they are supposed to solve, I sketch the model of computation preferred by Chalmers and argue that it is too limited to do full justice to computational theories in cognitive science. I also argue that it does not suffice to replace Chalmers’ favorite model with a better abstract model of computation; it is necessary to acknowledge the causal structure of physical computers that is not (...)
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  26. (1 other version)Social intelligence: how to integrate research? A mechanistic perspective.Marcin Miłkowski - 2014 - Proceedings of the European Conference on Social Intelligence (ECSI-2014).
    Is there a field of social intelligence? Many various disciplines ap-proach the subject and it may only seem natural to suppose that different fields of study aim at explaining different phenomena; in other words, there is no spe-cial field of study of social intelligence. In this paper, I argue for an opposite claim. Namely, there is a way to integrate research on social intelligence, as long as one accepts the mechanistic account to explanation. Mechanistic inte-gration of different explanations, (...)
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  27. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of (...)
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  28. Explanatory completeness and idealization in large brain simulations: a mechanistic perspective.Marcin Miłkowski - 2016 - Synthese 193 (5):1457-1478.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic (...)
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  29. Computational Modelling for Alcohol Use Disorder.Matteo Colombo - forthcoming - Erkenntnis.
    In this paper, I examine Reinforcement Learning modelling practice in psychiatry, in the context of alcohol use disorders. I argue that the epistemic roles RL currently plays in the development of psychiatric classification and search for explanations of clinically relevant phenomena are best appreciated in terms of Chang’s account of epistemic iteration, and by distinguishing mechanistic and aetiological modes of computational explanation.
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  30. The Scope of New Mechanism.Jenny Nielsen - manuscript
    In recent years, New Mechanism has become one of the most popular and widely discussed philosophical accounts of scientific explanation. Some of its proponents see it as a successor to traditional deductive nomological and statistical approaches to the philosophy of explanation. New Mechanists thus argue for the generality of their approach as a model of scientific explanation. Here we will show that the generality of NME as an account of scientific explanation is restricted. Most significantly, NME is widely recognized to (...)
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  31. Models in the Brain (book summary).Dan Ryder - manuscript
    The central idea is that the cerebral cortex is a model building machine, where regularities in the world serve as templates for the models it builds. First it is shown how this idea can be naturalized, and how the representational contents of our internal models depend upon the evolutionarily endowed design principles of our model building machine. Current neuroscience suggests a powerful form that these design principles may take, allowing our brains to uncover deep structures of the world (...)
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  32. Alife models as epistemic artefacts.Xabier Barandiaran & Alvaro Moreno - 2006 - In L. M. Rocha, L. S. Yaeger, M. A. Bedeau, D. Floreano, R. L. Goldstone & Alessandro Vespignani (eds.), Artificial Life X. Mit Press (Cambridge). pp. 513-519.
    Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories of (...)
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  33. (2 other versions)Simulation Models of the Evolution of Cooperation as Proofs of Logical Possibilities. How Useful Are They?Eckhart Arnold - 2013 - Etica E Politica 15 (2):101-138.
    This paper discusses critically what simulation models of the evolution ofcooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” and the modeling tradition it has inspired. Hardly any of the many simulation models of the evolution of cooperation in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. But this (...)
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  34. How could a rational analysis model explain?Samuli Reijula - 2017 - COGSCI 2017: 39th Annual Conference of the Cognitive Science Society,.
    Rational analysis is an influential but contested account of how probabilistic modeling can be used to construct non-mechanistic but self-standing explanatory models of the mind. In this paper, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordances.
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  35. Psychological Mechanism of Corruption: A Comprehensive Review. [REVIEW]Juneman Abraham, Julia Suleeman & Bagus Takwin - forthcoming - Asian Journal of Scientific Research.
    Corruption prevention can be more effective if it does not rely merely on legal enforcement. This theoretical review aimed to propose a hypothetical psychological model capable of explaining the behavior of corruption. Moral disengagement is a variable that is considered ontologically closest in “distance” to the variable of corruption behavior. Counterfeit self, implicit self-theory, ethical mindset and moral emotion are taken into account as the pivotal factors of the corruption behavior and its mechanism of moral disengagement. Counterfeit self along with (...)
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  36. On structural accounts of model-explanations.Martin King - 2016 - Synthese 193 (9):2761-2778.
    The focus in the literature on scientific explanation has shifted in recent years towards model-based approaches. In recent work, Alisa Bokulich has argued that idealization has a central role to play in explanation. Bokulich claims that certain highly-idealized, structural models can be explanatory, even though they are not considered explanatory by causal, mechanistic, or covering law accounts of explanation. This paper focuses on Bokulich’s account in order to make the more general claim that there are problems with maintaining (...)
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  37. Testing the mechanistic-universe paradigm using chaotic systems.Yehonatan Knoll - manuscript
    We humans are natural-born engineers. As such, we model after machines not only isolated, naturally occurring systems, but also the basic laws of physics, sharing with machines a local-evolution-of-state `grammar'. However, previous work by the author casts doubt upon this mechanistic paradigm, suggesting that it is to blame for the stubbornness of many open problems in physics. Simple experiments are therefore proposed to identify `non-machines'. In one experiment, `non mechanistic correlations' in the spirit of Bell are sought in (...)
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  38. A model for the solution of the quantum measurement problem.Biswaranjan Dikshit - 2019 - Science and Philosophy 7 (2):59-70.
    The basic idea of quantum mechanics is that the property of any system can be in a state of superposition of various possibilities. This state of superposition is also known as wave function and it evolves linearly with time in a deterministic way in accordance with the Schrodinger equation. However, when a measurement is carried out on the system to determine the value of that property, the system instantaneously transforms to one of the eigen states and thus we get only (...)
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  39. The case for regularity in mechanistic causal explanation.Holly Andersen - 2012 - Synthese 189 (3):415-432.
    How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...)
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  40. Modelling Empty Representations: The Case of Computational Models of Hallucination.Marcin Miłkowski - 2017 - In Gordana Dodig-Crnkovic & Raffaela Giovagnoli (eds.), Representation of Reality: Humans, Other Living Organism and Intelligent Machines. Heidelberg: Springer. pp. 17--32.
    I argue that there are no plausible non-representational explanations of episodes of hallucination. To make the discussion more specific, I focus on visual hallucinations in Charles Bonnet syndrome. I claim that the character of such hallucinatory experiences cannot be explained away non-representationally, for they cannot be taken as simple failures of cognizing or as failures of contact with external reality—such failures being the only genuinely non-representational explanations of hallucinations and cognitive errors in general. I briefly introduce a recent computational model (...)
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  41. The multiplicity of experimental protocols: A challenge to reductionist and non-reductionist models of the unity of neuroscience.Jacqueline A. Sullivan - 2009 - Synthese 167 (3):511-539.
    Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate these (...)
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  42. (1 other version)Design Principles as Minimal Models.W. Fang - 2024 - Studies in History and Philosophy of Science 105:50-58.
    In this essay I suggest that we view design principles in systems biology as minimal models, for a design principle usually exhibits universal behaviors that are common to a whole range of heterogeneous (living and nonliving) systems with different underlying mechanisms. A well-known design principle in systems biology, integral feedback control, is discussed, showing that it satisfies all the conditions for a model to be a minimal model. This approach has significant philosophical implications: it not only accounts for how (...)
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  43. Modelling and Simulation of Vehicle Windshield Wiper System using H infinity Loop Shaping and Robust Pole Placement Controllers.Mustefa Jibril, Messay Tadese & Eliyas Alemayehu Tadese - manuscript
    Vehicle windshield wiper system increases the driving safety by contributing a clear shot viewing to the driver. In this paper, modelling, designing and simulation of a vehicle windshield wiper system with robust control theory is done successfully. H  loop shaping and robust pole placement controllers are used to improve the wiping speed by tracking a reference speed signals. The reference speed signals used in this paper are step and sine wave signals. Comparison of the H  loop shaping and (...)
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  44.  58
    Introducing an Epistemological Paradigm and Its Ontological Origin through the Metaphysical Deconstruction of Language as the Model of Expression.M. Wang - 2024 - Deanandfrancis 1 (9):10.
    The model of language can relatively concretely reveal the mechanism of the epistemology, which is extended by the ontology that takes “person” as the unit. It unveils an intuitable dimension to represent the epistemolog’s paradigm and limitations. Deriving from the inherent relation between epistemology and ontology, the retrospection of the epistemology’s ontological origin can be actualized by locating or grasping the epistemological first person’s ontological essence. Hence, the illusional and frail essence of the ontology behind this epistemology would be uncovered. (...)
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  45. Impact of perceived ease of use, organizational support mechanism, and industry competitive pressure on physicians’ use of liver cancer screening technology in medical alliances.Junhong Lu, Qingwen Deng, Yuehua Chen & Wenbin Liu - 2023 - Frontiers in Public Health 11:1174334.
    Background: Liver cancer is one of the malignant tumors worldwide, while the prevention and control situation is grim at present, and the diffusion of its early screening technology still faces some challenges. This study aims to investigate the influencing mechanism of perceived ease of use, organizational support mechanism, and industry competitive pressure on hepatic early screening technologies use by physicians, so as to promote the wider use of corresponding technologies. -/- Methods: Under the theoretical guidance of technology-organization-environment framework and mindsponge (...)
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  46. Spinoza’s Essentialist Model of Causation.Valtteri Viljanen - 2008 - Inquiry: An Interdisciplinary Journal of Philosophy 51 (4):412 – 437.
    Spinoza is most often seen as a stern advocate of mechanistic efficient causation, but examining his philosophy in relation to the Aristotelian tradition reveals this view to be misleading: some key passages of the Ethics resemble so much what Suárez writes about emanation that it is most natural to situate Spinoza's theory of causation not in the context of the mechanical sciences but in that of a late scholastic doctrine of the emanative causality of the formal cause; as taking (...)
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  47. Philosophy of science in practice in ecological model building.Luana Poliseli, Jeferson G. E. Coutinho, Blandina Viana, Federica Russo & Charbel N. El-Hani - 2022 - Biology and Philosophy 37 (4):0-0.
    This article addresses the contributions of the literature on the new mechanistic philosophy of science for the scientific practice of model building in ecology. This is reflected in a one-to-one interdisciplinary collaboration between an ecologist and a philosopher of science during science-in-the-making. We argue that the identification, reconstruction and understanding of mechanisms is context-sensitive, and for this case study mechanistic modeling did not present a normative role but a heuristic one. We expect our study to provides useful epistemic (...)
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  48. Psychological and Computational Models of Language Comprehension: In Defense of the Psychological Reality of Syntax.David Pereplyotchik - 2011 - Croatian Journal of Philosophy 11 (1):31-72.
    In this paper, I argue for a modified version of what Devitt calls the Representational Thesis. According to RT, syntactic rules or principles are psychologically real, in the sense that they are represented in the mind/brain of every linguistically competent speaker/hearer. I present a range of behavioral and neurophysiological evidence for the claim that the human sentence processing mechanism constructs mental representations of the syntactic properties of linguistic stimuli. I then survey a range of psychologically plausible computational models of (...)
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  49.  64
    Advanced Driver Drowsiness Detection Model Using Optimized Machine Learning Algorithms.S. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):396-402.
    Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic Algorithms (...)
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  50. Minds Everywhere: Margaret Cavendish's Anti-Mechanist Materialism.Stewart Duncan - manuscript
    This paper considers Margaret Cavendish's distinctive anti-mechanist materialism, focusing on her 1664 Philosophical Letters, in which she discusses the views of Hobbes, Descartes, and More, among others. The paper examines Cavendish's views about natural, material souls: the soul of nature, the souls of finite individuals, and the relation between them. After briefly digressing to look at Cavendish's views about divine, supernatural souls, the paper then turns to the reasons for Cavendish's disagreement with mechanist accounts. There are disagreements over the explanation (...)
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