Results for 'Engineering models'

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  1.  70
    The Role of Non-Epistemic Values in Engineering Models.Sven Diekmann & Martin Peterson - 2013 - Science and Engineering Ethics 19 (1):207-218.
    We argue that non-epistemic values, including moral ones, play an important role in the construction and choice of models in science and engineering. Our main claim is that non-epistemic values are not only “secondary values” that become important just in case epistemic values leave some issues open. Our point is, on the contrary, that non-epistemic values are as important as epistemic ones when engineers seek to develop the best model of a process or problem. The upshot is that (...)
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  2.  28
    Ethical Issues in Engineering Models: An Operations Researcher’s Reflections.J. Kleijnen - 2011 - Science and Engineering Ethics 17 (3):539-552.
    This article starts with an overview of the author’s personal involvement—as an Operations Research consultant—in several engineering case-studies that may raise ethical questions; e.g., case-studies on nuclear waste, water management, sustainable ecology, military tactics, and animal welfare. All these case studies employ computer simulation models. In general, models are meant to solve practical problems, which may have ethical implications for the various stakeholders; namely, the modelers, the clients, and the public at large. The article further presents an (...)
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  3.  30
    Diagrammatic Models in the Engineering Sciences.Mieke Boon - 2008 - Foundations of Science 13 (2):127-142.
    This paper is concerned with scientific reasoning in the engineering sciences. Engineering sciences aim at explaining, predicting and describing physical phenomena occurring in technological devices. The focus of this paper is on mathematical description. These mathematical descriptions are important to computer-aided engineering or design programs (CAE and CAD). The first part of this paper explains why a traditional view, according to which scientific laws explain and predict phenomena and processes, is problematic. In the second part, the reasons (...)
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  4.  75
    Physical Pictures: Engineering Models Circa 1914 and in Wittgenstein’s Tractatus.Susan G. Sterrett - 2000 - Vienna Circle Institute Yearbook 9:121-135.
    Today I want to talk about an element in the milieu in which Ludwig Wittgenstein conceived the Tractatus Logico-Philosophicus that has not been recognized to date: the generalization of the methodology of experimental scale models that occurred just about the time he was writing it. I find it very helpful to keep in mind how this kind of model portrays when reading the Tractatus — in particular, when reading the statements about pictures and models, such as:That a picture (...)
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  5.  6
    Scale Models, Similitude and Dimensions: Aspects of Mid-Nineteenth-Century Engineering Science.Thomas Wright - 1992 - Annals of Science 49 (3):233-254.
    This paper examines the type of theory used to justify the application of physical scale modelling to the solution of mid-nineteenth century engineering problems. To do this, it discusses three particular examples: the initial Britannia Bridge breaking experiments of E. Hodgkinson, the vibrating railway bridge experiments of R. Willis and G. G. Stokes; and the ship resistance experiments of W. Froude. The theory invoked in these case histories is viewed against the background of the response of the contemporary (...) community and compared with the notion of engineering science as proposed by W. J. M. Rankine. (shrink)
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  6.  20
    Models in Science and Engineering: Imagining, Designing and Evaluating Representations.Michael Poznic - 2017 - Dissertation, Delft University of Technology
    The central question of this thesis is how one can learn about particular targets by using models of those targets. A widespread assumption is that models have to be representative models in order to foster knowledge about targets. Thus the thesis begins by examining the concept of representation from an epistemic point of view and supports an account of representation that does not distinguish between representation simpliciter and adequate representation. Representation, understood in the sense of a representative (...)
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  7.  15
    Risks in the Making: The Mediating Role of Models in Water Management and Civil Engineering in the Netherlands.Matthijs Kouw - 2017 - Berichte Zur Wissenschaftsgeschichte 40 (2):160-174.
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  8. Using Ontologies and STEP Standards for the Semantic Simplification of CAD Models in Different Engineering Domains.Jorge Posada, Carlos Toro, Stefan Wundrak & Andre Stork - 2006 - Applied Ontology 1 (3):263-279.
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  9.  11
    Eric C. Nystrom. Seeing Underground: Maps, Models, and Mining Engineering in America. Xii + 301 Pp., Illus., Maps, Bibl., Index. Reno/Las Vegas: University of Nevada Press, 2014. $39.95. [REVIEW]Kathleen Ochs - 2016 - Isis 107 (2):411-412.
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  10.  8
    Models and « Black Boxes » : Mathematics as an Enabling Technology in the History of Communications and Control Engineering / Modèles Et « Boites Noires » : Les Mathématiques Comme Technologie Constitutive Dans l'Histoire des Télécommunications Et de l'Ingénierie de Contrôle.Chris C. Bissel - 2004 - Revue d'Histoire des Sciences 57 (2):305-338.
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  11.  6
    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.  6
    Models and Black Boxes: Mathematics as an Enabling Technology in the History of Communications and Control Engineering.Chris Bissell - 2004 - Revue d'Histoire des Sciences 57 (2):307-340.
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  13.  3
    From High-Molecular-Weight Protein Models to Enzyme Engineering: Research at the Weizmann Institute of Science.E. Katchalski-Katzir - 1986 - Perspectives in Biology and Medicine 29 (3 Pt 2):S73.
  14. Improved Turbulence Models for Computational Wind Engineering.Gary Easom B. Eng - forthcoming - Philosophy.
     
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  15.  21
    Modeling Organs with Organs on Chips: Scientific Representation and Engineering Design as Modeling Relations.Michael Poznic - 2016 - Philosophy and Technology 29 (4):357-371.
    On the basis of a case study in bioengineering, this paper proposes a novel perspective on models in science and engineering. This is done with the help of two notions: representation and design. These two notions are interpreted as referring to modeling relations between vehicles and targets that differ in their respective directions of fit. The representation relation has a vehicle-to-target direction of fit and the design relation has a target-to-vehicle direction of fit. The case study of an (...)
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  16.  41
    Neither Adaptive Thinking nor Reverse Engineering: Methods in the Evolutionary Social Sciences.Catherine Driscoll - 2015 - Biology and Philosophy 30 (1):59-75.
    In this paper I argue the best examples of the methods in the evolutionary social sciences don’t actually resemble either of the two methods called “Adaptive Thinking” or “Reverse Engineering” described by evolutionary psychologists. Both AT and RE have significant problems. Instead, the best adaptationist work in the ESSs seems to be based on and is aiming at a different method that avoids the problems of AT and RE: it is a behavioral level method that starts with information about (...)
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  17.  50
    Classification and Moral Evaluation of Uncertainties in Engineering Modeling.Colleen Murphy, Paolo Gardoni & Charles E. Harris - 2011 - Science and Engineering Ethics 17 (3):553-570.
    Engineers must deal with risks and uncertainties as a part of their professional work and, in particular, uncertainties are inherent to engineering models. Models play a central role in engineering. Models often represent an abstract and idealized version of the mathematical properties of a target. Using models, engineers can investigate and acquire understanding of how an object or phenomenon will perform under specified conditions. This paper defines the different stages of the modeling process in (...)
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  18.  15
    Comparison of China-US Engineering Ethics Educations in Sino-Western Philosophies of Technology.Gui Hong Cao - 2015 - Science and Engineering Ethics 21 (6):1609-1635.
    Ethics education has become essential in modern engineering. Ethics education in engineering has been increasingly implemented worldwide. It can improve ethical behaviors in technology and engineering design under the guidance of the philosophy of technology. Hence, this study aims to compare China-US engineering ethics education in Sino-Western philosophies of technology by using literature studies, online surveys, observational researches, textual analyses, and comparative methods. In my original theoretical framework and model of input and output for education, six (...)
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  19.  48
    Holistic Engineering Ethics?Eddie Conlon, Diana Adela Martin & Brian Bowe - 2018 - Proceedings of the Engineering Education for Sustainable Development Conference.
    This paper focuses on the question of What kind of engineering ethics (EE) is needed to develop holistic engineers who can practice and promote the principles of sustainable development? -/- It is argued that, given the existence of other models, an approach to EE, as argued for at EESD 2016, centred on “training engineers for handling ethical dilemmas in sustainability contexts” (Lundqvist and Svanstrom 2016) is inadequate to address the sustainability challenge facing engineers.. We contend that while EE (...)
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  20.  30
    Bayesian Reverse-Engineering Considered as a Research Strategy for Cognitive Science.Carlos Zednik & Frank Jäkel - 2016 - Synthese 193 (12):3951-3985.
    Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character (...)
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  21.  33
    Critical Rationalism and Engineering: Ontology.Mark Staples - 2014 - Synthese 191 (10):2255-2279.
    Engineering is often said to be ‘scientific’, but the nature of knowledge in engineering is different to science. Engineering has a different ontological basis—its theories address different entities and are judged by different criteria. In this paper I use Popper’s three worlds ontological framework to propose a model of engineering theories, and provide an abstract logical view of engineering theories analogous to the deductive-nomological view of scientific theories. These models frame three key elements from (...)
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  22.  53
    Adaptationism and Engineering.Tim Lewens - 2002 - Biology and Philosophy 17 (1):1-31.
    The rights and wrongs of adaptationism areoften discussed by appeal to what I call theartefact model. Anti-adaptationistscomplain that the use of optimality modelling,reverse engineering and other techniques areindicative of a mistaken and outmoded beliefthat organisms are like well-designedartefacts. Adaptationists (e.g. Dennett 1995)respond with the assertion that viewingorganisms as though they were well designed isa fruitful, perhaps necessary research strategyin evolutionary biology. Anti-adaptationistsare right when they say that techniques likereverse engineering are liable to mislead. This fact does not undermine (...)
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  23. Framework for Models and Simulations with Agents in Regard to Agent Simulations in Social Sciences: Emulation and Simulation.Franck Varenne - 2010 - In Alexandre Muzy, David R. C. Hill & Bernard P. Zeigler (eds.), Activity-Based Modeling and Simulation. Presses Universitaires Blaise-Pascal.
    The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the core of (...)
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  24.  8
    Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.Erika Palmer & Benedicte Wilson - 2018 - Science and Engineering Ethics 24 (2):419-439.
    Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of (...)
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  25.  13
    Modeling in Chemical Engineering.Jaap van Brakel - 2000 - Hyle 6 (2):101 - 116.
    Models underlying the use of similarity considerations, dimensionless numbers, and dimensional analysis in chemical engineering are discussed. Special attention is given to the many levels at which models and ceteris paribus conditions play a role and to the modeling of initial and boundary conditions. It is shown that both the laws or dimensionless number correlations and the systems to which they apply are models. More generally, no matter which model or description one picks out, what is (...)
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  26.  77
    Models and Inferences in Science.Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.) - 2016 - Springer.
    The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in (...)
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  27.  7
    Understanding Engineers’ Responsibilities: A Prerequisite to Designing Engineering Education.Colleen Murphy & Paolo Gardoni - 2017 - Science and Engineering Ethics:1-4.
    The development of the curriculum for engineering education should be based on a comprehensive understanding of engineers’ responsibilities. The responsibilities that are constitutive of being an engineer include striving to fulfill the standards of excellence set by technical codes; to improve the idealized models that engineers use to predict, for example, the behavior of alternative designs; and to achieve the internal goods such as safety and sustainability as they are reflected in the design codes. Globalization has implications for (...)
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  28.  82
    Models of Machines and Models of Phenomena.Susan G. Sterrett - 2004 - International Studies in the Philosophy of Science 20 (1):69 – 80.
    Experimental engineering models have been used both to model general phenomena, such as the onset of turbulence in fluid flow, and to predict the performance of machines of particular size and configuration in particular contexts. Various sorts of knowledge are involved in the method - logical consistency, general scientific principles, laws of specific sciences, and experience. I critically examine three different accounts of the foundations of the method of experimental engineering models (scale models), and examine (...)
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  29.  17
    Combining Finite and Infinite Elements: Why Do We Use Infinite Idealizations in Engineering?Silvia De Bianchi - 2019 - Synthese 196 (5):1733-1748.
    This contribution sheds light on the role of infinite idealization in structural analysis, by exploring how infinite elements and finite element methods are combined in civil engineering models. This combination, I claim, should be read in terms of a ‘complementarity function’ through which the representational ideal of completeness is reached in engineering model-building. Taking a cue from Weisberg’s definition of multiple-model idealization, I highlight how infinite idealizations are primarily meant to contribute to the prediction of structural behavior (...)
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  30.  6
    Combining Finite and Infinite Elements: Why Do We Use Infinite Idealizations in Engineering?Silvia Bianchi - 2019 - Synthese 196 (5):1733-1748.
    This contribution sheds light on the role of infinite idealization in structural analysis, by exploring how infinite elements and finite element methods are combined in civil engineering models. This combination, I claim, should be read in terms of a ‘complementarity function’ through which the representational ideal of completeness is reached in engineering model-building. Taking a cue from Weisberg’s definition of multiple-model idealization, I highlight how infinite idealizations are primarily meant to contribute to the prediction of structural behavior (...)
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  31.  1
    Understanding Engineers’ Responsibilities: A Prerequisite to Designing Engineering Education: Commentary on “Educating Engineers for the Public Good Through International Internships: Evidence From a Case Study at Universitat Politècnica de València”.Paolo Gardoni & Colleen Murphy - 2019 - Science and Engineering Ethics 25 (6):1817-1820.
    The development of the curriculum for engineering education should be based on a comprehensive understanding of engineers’ responsibilities. The responsibilities that are constitutive of being an engineer include striving to fulfill the standards of excellence set by technical codes; to improve the idealized models that engineers use to predict, for example, the behavior of alternative designs; and to achieve the internal goods such as safety and sustainability as they are reflected in the design codes. Globalization has implications for (...)
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  32.  51
    Model Tuning in Engineering: Uncovering the Logic.Katie Steele & Charlotte Werndl - 2015 - Journal of Strain Analysis for Engineering Design 51 (1):63-71.
    In engineering, as in other scientific fields, researchers seek to confirm their models with real-world data. It is common practice to assess models in terms of the distance between the model outputs and the corresponding experimental observations. An important question that arises is whether the model should then be ‘tuned’, in the sense of estimating the values of free parameters to get a better fit with the data, and furthermore whether the tuned model can be confirmed with (...)
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  33.  99
    Aesthetics and Ethics in Engineering: Insights From Polanyi. [REVIEW]Priyan Dias - 2011 - Science and Engineering Ethics 17 (2):233-243.
    Polanyi insisted that scientific knowledge was intensely personal in nature, though held with universal intent. His insights regarding the personal values of beauty and morality in science are first enunciated. These are then explored for their relevance to engineering. It is shown that the practice of engineering is also governed by aesthetics and ethics. For example, Polanyi’s three spheres of morality in science—that of the individual scientist, the scientific community and the wider society—has parallel entities in engineering. (...)
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  34.  6
    Solutions to Gender Balance in STEM Fields Through Support, Training, Education and Mentoring: Report of the International Women in Medical Physics and Biomedical Engineering Task Group.Gilda Barabino, Monique Frize, Fatimah Ibrahim, Eleni Kaldoudi, Lenka Lhotska, Loredana Marcu, Magdalena Stoeva, Virginia Tsapaki & Eva Bezak - 2020 - Science and Engineering Ethics 26 (1):275-292.
    The aim of this article is to offer a view of the current status of women in medical physics and biomedical engineering, while focusing on solutions towards gender balance and providing examples of current activities carried out at national and international levels. The International Union of Physical and Engineering Scientists in Medicine is committed to advancing women in science and health and has several initiatives overseen by the Women in Medical Physics and Biomedical Engineering Task Group. Some (...)
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  35.  30
    Hans Spemann: Cultural Factors in the Rejection of an Engineering Stance in Embryology.R. G. Rinard - 1992 - Synthese 91 (1-2):73 - 91.
    Hans Spemann's use of the concept double assurance, drawn from engineering models in cytology, is discussed in his work on lens development and the action of the organizer. His transformation of this concept within his neo-Lamarckian program is demonstrated and connected with the cultural factors which shaped engineering and embryology in Weimar Germany.
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  36.  34
    Basic Science Through Engineering? Synthetic Modeling and the Idea of Biology-Inspired Engineering.Tarja Knuuttila & Andrea Loettgers - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (2):158-169.
    Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. (...)
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  37.  43
    Mental Models: An Alternative Evaluation of a Sensemaking Approach to Ethics Instruction.Meagan E. Brock, Andrew Vert, Vykinta Kligyte, Ethan P. Waples, Sydney T. Sevier & Michael D. Mumford - 2008 - Science and Engineering Ethics 14 (3):449-472.
    In spite of the wide variety of approaches to ethics training it is still debatable which approach has the highest potential to enhance professionals’ integrity. The current effort assesses a novel curriculum that focuses on metacognitive reasoning strategies researchers use when making sense of day-to-day professional practices that have ethical implications. The evaluated trainings effectiveness was assessed by examining five key sensemaking processes, such as framing, emotion regulation, forecasting, self-reflection, and information integration that experts and novices apply in ethical decision-making. (...)
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  38.  16
    Basic Science Through Engineering?: Synthetic Modeling and the Idea of Biology-Inspired Engineering.Tarja Knuuttila & Andrea Loettgers - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (2):158-169.
    Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. (...)
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  39. Intrinsic Ethics Regarding Integrated Assessment Models for Climate Management.Erich W. Schienke, Seth D. Baum, Nancy Tuana, Kenneth J. Davis & Klaus Keller - 2011 - Science and Engineering Ethics 17 (3):503-523.
    In this essay we develop and argue for the adoption of a more comprehensive model of research ethics than is included within current conceptions of responsible conduct of research (RCR). We argue that our model, which we label the ethical dimensions of scientific research (EDSR), is a more comprehensive approach to encouraging ethically responsible scientific research compared to the currently typically adopted approach in RCR training. This essay focuses on developing a pedagogical approach that enables scientists to better understand and (...)
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  40.  53
    Design Methodologies and the Limits of the Engineering-Dominated Conception of Synthetic Biology.Tero Ijäs - 2019 - Acta Biotheoretica 67 (1):1-18.
    Synthetic biology is described as a new field of biotechnology that models itself on engineering sciences. However, this view of synthetic biology as an engineering field has received criticism, and both biologists and philosophers have argued for a more nuanced and heterogeneous understanding of the field. This paper elaborates the heterogeneity of synthetic biology by clarifying the role of design and the variability of design methodologies in synthetic biology. I focus on two prominent design methodologies: rational design (...)
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  41.  11
    Empiricism, Sciences, and Engineering: Cognitive Science as a Zone of Integration.Don Ross - 2019 - Cognitive Processing 20 (2):261-267.
    An article by Alexandra Kirsch accepted for publication in Cognitive Processing occasioned debate among reviewers about broad methodological issues in cognitive science. One of these issues is the proper place of Popperian falsificationism in the interdisciplinary cluster. Another is the tension between abstract models and theories that apply to wide classes of cognitive systems, and models of more restricted scope intended to predict specifically human patterns of thought and behavior. The lead editorial in a Commentary debate invited by (...)
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  42.  14
    Humanised Models of Cancer in Molecular Medicine: The Experimental Control of Disanalogy.Paolo Maugeri & Alessandro Blasimme - 2011 - History and Philosophy of the Life Sciences 33 (4).
    This paper explores the epistemology of extrapolation from model organisms to humans in molecular medicine. We take into account two common views on the issue, the homology view and the disanalogy view. In response to both interpretations, we argue that the foundational basis of extrapolations cannot simply be provided by homology and that relevant disanalogies can, thanks to the techniques of molecular biology, be experimentally controlled and exploited to allow useful and reliable extrapolations. The case of "humanised mice" in the (...)
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  43. Incommensurability and Rationality in Engineering Design: The Case of Functional Decomposition.Dingmar van Eck - 2011 - Techné: Research in Philosophy and Technology 15 (2):118-136.
    In engineering design research different models of functional decomposition are advanced side-by-side. In this paper I explain and validate this co-existence of models in terms of the Kuhnian thesis of methodological incommensurability. I advance this analysis in terms of the thesis’ construal of theory choice in terms of values, expanding this notion to the engineering domain. I further argue that the implicated threat of the thesis to rational theory choice has no force in the functional decomposition (...)
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  44.  49
    Design Under Randomness: How Variation Affects the Engineering of Biological Systems.Tero Ijäs - 2018 - Biological Theory 13 (3):153-163.
    Synthetic biology offers a powerful method to design and construct biological devices for human purposes. Two prominent design methodologies are currently used. Rational design adapts the design methodology of traditional engineering sciences, such as mechanical engineering. Directed evolution, in contrast, models its design principles after natural evolution, as it attempts to design and improve systems by guiding them to evolve in a certain direction. Previous work has argued that the primary difference between these two is the way (...)
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  45.  14
    From Models-as-Fictions to Models-as-Tools.Adrian Currie - 2017 - Ergo: An Open Access Journal of Philosophy 4.
    Many accounts of scientific modeling conceive of models as fictions: scientists interact with models in ways analogous to various aesthetic objects. Fictionalists follow most other accounts of modeling by taking them to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby (...)
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  46.  21
    The Role of Moral Judgments Within Expectancy-Value-Based Attitude-Behavior Models.Richard Shepherd & Paul Sparks - 2002 - Ethics and Behavior 12 (4):299-321.
    Rational choice models are characterized by the image of the self-interested Homo economicus. The role of moral concerns, which may involve a concern for others' welfare in people's judgments and choices, questions the descriptive validity of such models. Increasing evidence of a role for perceived moral obligation within the expectancy-value-based theory of reasoned action and the theory of planned behavior indicates the importance of moral-normative influences in social behavior. In 2 studies, the influence of moral judgments on attitudes (...)
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  47.  45
    Ecosystem Engineering, Experiment, and Evolution.Trevor Pearce - 2011 - Biology and Philosophy 26 (6):793-812.
    This paper argues that philosophers should pay more attention to the idea of ecosystem engineering and to the scientific literature surrounding it. Ecosystem engineering is a broad but clearly delimited concept that is less subject to many of the “it encompasses too much” criticisms that philosophers have directed at niche construction . The limitations placed on the idea of ecosystem engineering point the way to a narrower idea of niche construction. Moreover, experimental studies in the ecosystem (...) literature provide detailed accounts of particular empirical situations in which we cannot neglect the O term in dE /dt = g (O, E), which helps us get beyond verbal arguments and simple models purporting to show that niche construction must not be ignored as a factor in evolution. Finally, this literature demonstrates that while ecosystem engineering studies may not require us to embrace a new evolutionary process, as niche construction advocates have claimed, they do teach us that the myriad abiotic factors concealed by the abstract term ‘environment’ are often controlled in large part by organisms. (shrink)
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  48.  19
    From Models-as-Fictions to Models-as-Tools.Adrian Currie - 2017 - Ergo: An Open Access Journal of Philosophy 4.
    Many accounts of scientific modeling conceive of models as fictions: scientists interact with models in ways analogous to various aesthetic objects. Fictionalists follow most other accounts of modeling by taking them to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby (...)
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  49.  8
    Rethinking Correspondence: How the Process of Constructing Models Leads to Discoveries and Transfer in the Bioengineering Sciences.Chandrasekharan Sanjay & J. Nersessian Nancy - forthcoming - Synthese:1-30.
    Building computational models of engineered exemplars, or prototypes, is a common practice in the bioengineering sciences. Computational models in this domain are often built in a patchwork fashion, drawing on data and bits of theory from many different domains, and in tandem with actual physical models, as the key objective is to engineer these prototypes of natural phenomena. Interestingly, such patchy model building, often combined with visualizations, whose format is open to a wide range of choice, leads (...)
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    Models, Simulations, Instantiations and Evidence: The Case of Digital Evolution.Robert Pennock - manuscript
    Journal of Experimental and Theoretical Artificial Intelligence What is the difference between a simulation of X and simply another instance of X? Is there a point at which the ‘‘virtual reality’’ of a model becomes the real thing? This paper examines these questions using cases taken from recent developments in evolutionary engineering and artificial life research. By implementing the Darwinian mechanism and setting it to work on a design problem, scientists and engineers find that evolution not only can improve (...)
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