Systems Theory"
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Advances in Social Science, Education and Humanities Research, volume 124 International Conference on Contemporary Education, Social Sciences and Humanities (ICCESSH 2017) Information Ecology in Structuring Sociocultural Space of Modern Society Eleonora Barkova Department of History and Philosophy Plekhanov Russian University of Economics (PRUE) Stremyanny per., 36, Moscow, 117997, Russia E-mail: [email protected] Marina Ivleva Elena Agibalova Department of History and Philosophy Department of Foreign Languages № 3 Plekhanov Russian University of Economics (PRUE) Plekhanov Russian University of Economics (PRUE) Stremyanny per., 36, Moscow, 117997, Russia Stremyanny per., 36, Moscow, 117997, Russia Abstract—The article studies potential application of an living, for the ecosystem on all the levels were also identified. information ecology approach for the analysis of a V.A.Kutyrev was right to say that today “it’s important…to contemporary stage in the development of an information suggest some sort of a modus vivendi between realism and society. It is illustrated using the example of this approach modernism that reflects our natural, objective macro world utilized to study a social element – sociocultural space. The and post-modernism as, actually, the ideology of other, article analyses distinctive features of information ecology as a informative-virtual micro and mega worlds. Ecological modern philosophical approach based on holistic and problems that had been referred to nature not long ago, systematic principles which provides -
Fcaglp, Unlp, 2018
Scientific Philosophy Gustavo E. Romero IAR-CONICET/UNLP, Argentina FCAGLP, UNLP, 2018 Epistemology Episteme, as distinguished from techne, is etymologically derived from the Ancient Greek word ἐπιστήμη for knowledge or science, which comes from the verb ἐπίσταμαι, "to know". In Plato's terminology episteme means knowledge, as in "justified true belief", in contrast to doxa, common belief or opinion. The word epistemology, meaning the study of knowledge, is derived from episteme. Plato Epistemology is the general study of cognitive processes and their outcome: knowledge. Knowledge is the product of cognitive operations made by an inquiring subject. It is not a thing or a substance, but a series of brain changes in the knower. Knowledge is not independent of the knowing subject, although we often feign it is for practical reasons. Knowledge is different from belief: I can know a story, for instance, but do not believe it. Belief implies a psychological adherence to some propositions. It is possible to believe something without understanding it, so belief is not necessary associated with neither truth nor justification. Knowledge acquisition requires a modification of the brain of the knower. This can be done in different ways, hence there are different kinds of knowledge. (i) Sensory-motor knowledge: the result of learning from actions. (ii) Perceptual knowledge: the result of perceiving events, either internal or external to the subject. (iii) Conceptual or propositional knowledge: the result of ideation, conjecturing, testing, correcting. Notice that not all knowledge is beneficial: we can learn trivialities, falsehoods, or highly harmful habits The three kind of knowledge are interrelated: conceptual knowledge can improve motor skills and perception; perception is used to evaluate conjectures; motor skills can help to improve perception and build instruments such as books, that enhance the ability to learn. -
Moving Towards a New Urban Systems Science
Ecosystems DOI: 10.1007/s10021-016-0053-4 Ó 2016 Springer Science+Business Media New York 20TH ANNIVERSARY PAPER Moving Towards a New Urban Systems Science Peter M. Groffman,1* Mary L. Cadenasso,2 Jeannine Cavender-Bares,3 Daniel L. Childers,4 Nancy B. Grimm,5 J. Morgan Grove,6 Sarah E. Hobbie,3 Lucy R. Hutyra,7 G. Darrel Jenerette,8 Timon McPhearson,9 Diane E. Pataki,10 Steward T. A. Pickett,11 Richard V. Pouyat,12 Emma Rosi-Marshall,11 and Benjamin L. Ruddell13 1Department of Earth and Environmental Sciences, City University of New York Advanced Science Research Center and Brooklyn College, New York, New York 10031, USA; 2Department of Plant Sciences, University of California, Davis, California 95616, USA; 3Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, Minnesota 55108, USA; 4School of Sustain- ability, Arizona State University, Tempe, Arizona 85287, USA; 5School of Life Sciences and Global Institute of Sustainability, Arizona State University, Tempe, Arizona 85287, USA; 6USDA Forest Service, Baltimore Field Station, Baltimore, Maryland 21228, USA; 7Department of Earth and Environment, Boston University, Boston, Massachusetts 02215, USA; 8Department of Botany and Plant Sciences, University of California Riverside, Riverside, California 92521, USA; 9Urban Ecology Lab, Environmental Studies Program, The New School, New York, New York 10003, USA; 10Department of Biology, University of Utah, Salt Lake City, Utah 84112, USA; 11Cary Institute of Ecosystem Studies, Millbrook, New York 12545, USA; 12USDA Forest Service, Research and Development, District of Columbia, Washington 20502, USA; 13School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona 86001, USA ABSTRACT Research on urban ecosystems rapidly expanded in linchpins in the further development of sustain- the 1990s and is now a central topic in ecosystem ability science and argue that there is a strong need science. -
Living Systems Theory (Under Construction)
Calhoun: The NPS Institutional Archive Faculty and Researcher Publications Faculty and Researcher Publications 2008-06-30 Living Systems Theory (under construction) Bradley, Gordon http://hdl.handle.net/10945/38246 Living Systems Theory (under construction) Agranoff, B. W. (2003). Obituaries: James Grier Miller. Retrieved May 26, 2008, from University of Michigan: The University Record Online: http://www.ur.umich.edu/0203/Feb03_03/obits.shtml Bertalanffy, Ludwig von. (1968). General System Theory: Foundations, Development, Applications. New York: George Braziller. Crawford, Raymond R. (1981). An Application of Living Systems Theory to Combat Models. Master’s Thesis. Monterey, CA: Naval Postgraduate School. http://stinet.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA101103 Duncan, Daniel M. (1972). James G. Miller's Living Systems Theory: Issues for Management Thought and Practice. The Academy of Management Journal, 15:4, 513-523. http://www.jstor.org/stable/255145?seq=1 Kuhn, Alfred. (1979). Differences vs. Similarities in Living Systems. Contemporary Sociology, 8:5, 691- 696. http://www.jstor.org/sici?sici=0094- 3061(197909)8%3A5%3C691%3ADVSILS%3E2.0.CO%3B2-4 Miller, James Grier. (1979). Response to the Reviewers of Living Systems. Contemporary Sociology, 8:5, 705-715. http://www.jstor.org/sici?sici=0094- 3061(197909)8%3A5%3C705%3ARTTROL%3E2.0.CO%3B2-8 Miller, James Grier. (1995). Living Systems. Niwot: University of Colorado. (out of print) Oliva, Terence A. and R. Eric Reidenbach. (1981). General Living Systems Theory and Marketing: A Framework for Analysis. Journal of Marketing, 45:4, 30-37. http://www.jstor.org/sici?sici=0022- 2429(198123)45%3A4%3C30%3AGLSTAM%3E2.0.CO%3B2-R Parent, Elaine. -
An Information-Theoretic Metric of System Complexity with Application
An Information-Theoretic Metric Douglas Allaire1 of System Complexity With e-mail: [email protected] Application to Engineering Qinxian He John Deyst System Design Karen Willcox System complexity is considered a key driver of the inability of current system design practices to at times not recognize performance, cost, and schedule risks as they emerge. Aerospace Computational Design Laboratory, We present here a definition of system complexity and a quantitative metric for measuring Department of Aeronautics and Astronautics, that complexity based on information theory. We also derive sensitivity indices that indi- Massachusetts Institute of Technology, cate the fraction of complexity that can be reduced if more about certain factors of a sys- Cambridge, MA 02139 tem can become known. This information can be used as part of a resource allocation procedure aimed at reducing system complexity. Our methods incorporate Gaussian pro- cess emulators of expensive computer simulation models and account for both model inadequacy and code uncertainty. We demonstrate our methodology on a candidate design of an infantry fighting vehicle. [DOI: 10.1115/1.4007587] 1 Introduction methodology identifies the key contributors to system complexity and provides quantitative guidance for resource allocation deci- Over the years, engineering systems have become increasingly sions aimed at reducing system complexity. complex, with astronomical growth in the number of components We define system complexity as the potential for a system to and their interactions. With this rise in complexity comes a host exhibit unexpected behavior in the quantities of interest. A back- of new challenges, such as the adequacy of mathematical models ground discussion on complexity metrics, uncertainty sources in to predict system behavior, the expense and time to conduct complex systems, and related work presented in Sec. -
The BRAIN in Space a Teacher’S Guide with Activities for Neuroscience This Page Intentionally Left Blank
Educational Product National Aeronautics and Teachers Grades 5–12 Space Administration The BRAIN in Space A Teacher’s Guide With Activities for Neuroscience This page intentionally left blank. The Brain in Space A Teacher’s Guide With Activities for Neuroscience National Aeronautics and Space Administration Life Sciences Division Washington, DC This publication is in the Public Domain and is not protected by copyright. Permission is not required for duplication. EG-1998-03-118-HQ This page intentionally left blank. This publication was made possible by the National Acknowledgments Aeronautics and Space Administration, Cooperative Agreement No. NCC 2-936. Principal Investigator: Walter W.Sullivan, Jr., Ph.D. Neurolab Education Program Office of Operations and Planning Morehouse School of Medicine Atlanta, GA Writers: Marlene Y. MacLeish, Ed.D. Director, Neurolab Education Program Morehouse School of Medicine Atlanta, GA Bernice R. McLean, M.Ed. Deputy Director, Neurolab Education Program Morehouse School of Medicine Atlanta, GA Graphic Designer and Illustrator: Denise M.Trahan, B.A. Atlanta, GA Technical Director: Perry D. Riggins Neurolab Education Program Morehouse School of Medicine Atlanta, GA This page intentionally left blank. Contributors This publication was developed for the National Aeronautics and Space Administration (NASA) under a Cooperative Agreement with the Morehouse School of Medicine (MSM). Many individu- als and organizations contributed to the production of this curriculum. We acknowledge their support and contributions. Organizations: Joseph Whittaker, Ph.D. Atlanta Public School System Neurolab Education Program Advisory Board: Society for Neuroscience Gene Brandt The Dana Alliance for Brain Initiatives Milton C. Clipper, Jr. Mary Anne Frey, Ph.D. NASA Headquarters: Charles A. -
Warren Mcculloch and the British Cyberneticians
Warren McCulloch and the British cyberneticians Article (Accepted Version) Husbands, Phil and Holland, Owen (2012) Warren McCulloch and the British cyberneticians. Interdisciplinary Science Reviews, 37 (3). pp. 237-253. ISSN 0308-0188 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/id/eprint/43089/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher’s version. Please see the URL above for details on accessing the published version. Copyright and reuse: Sussex Research Online is a digital repository of the research output of the University. Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available. Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. http://sro.sussex.ac.uk Warren McCulloch and the British Cyberneticians1 Phil Husbands and Owen Holland Dept. Informatics, University of Sussex Abstract Warren McCulloch was a significant influence on a number of British cyberneticians, as some British pioneers in this area were on him. -
Control Theory
Control theory S. Simrock DESY, Hamburg, Germany Abstract In engineering and mathematics, control theory deals with the behaviour of dynamical systems. The desired output of a system is called the reference. When one or more output variables of a system need to follow a certain ref- erence over time, a controller manipulates the inputs to a system to obtain the desired effect on the output of the system. Rapid advances in digital system technology have radically altered the control design options. It has become routinely practicable to design very complicated digital controllers and to carry out the extensive calculations required for their design. These advances in im- plementation and design capability can be obtained at low cost because of the widespread availability of inexpensive and powerful digital processing plat- forms and high-speed analog IO devices. 1 Introduction The emphasis of this tutorial on control theory is on the design of digital controls to achieve good dy- namic response and small errors while using signals that are sampled in time and quantized in amplitude. Both transform (classical control) and state-space (modern control) methods are described and applied to illustrative examples. The transform methods emphasized are the root-locus method of Evans and fre- quency response. The state-space methods developed are the technique of pole assignment augmented by an estimator (observer) and optimal quadratic-loss control. The optimal control problems use the steady-state constant gain solution. Other topics covered are system identification and non-linear control. System identification is a general term to describe mathematical tools and algorithms that build dynamical models from measured data. -
Introduction to Cyber-Physical System Security: a Cross-Layer Perspective
IEEE TRANSACTIONS ON MULTI-SCALE COMPUTING SYSTEMS, VOL. 3, NO. 3, JULY-SEPTEMBER 2017 215 Introduction to Cyber-Physical System Security: A Cross-Layer Perspective Jacob Wurm, Yier Jin, Member, IEEE, Yang Liu, Shiyan Hu, Senior Member, IEEE, Kenneth Heffner, Fahim Rahman, and Mark Tehranipoor, Senior Member, IEEE Abstract—Cyber-physical systems (CPS) comprise the backbone of national critical infrastructures such as power grids, transportation systems, home automation systems, etc. Because cyber-physical systems are widely used in these applications, the security considerations of these systems should be of very high importance. Compromise of these systems in critical infrastructure will cause catastrophic consequences. In this paper, we will investigate the security vulnerabilities of currently deployed/implemented cyber-physical systems. Our analysis will be from a cross-layer perspective, ranging from full cyber-physical systems to the underlying hardware platforms. In addition, security solutions are introduced to aid the implementation of security countermeasures into cyber-physical systems by manufacturers. Through these solutions, we hope to alter the mindset of considering security as an afterthought in CPS development procedures. Index Terms—Cyber-physical system, hardware security, vulnerability Ç 1INTRODUCTION ESEARCH relating to cyber-physical systems (CPS) has In addition to security concerns, CPS privacy is another Rrecently drawn the attention of those in academia, serious issue. Cyber-physical systems are often distributed industry, and the government because of the wide impact across wide geographic areas and typically collect huge CPS have on society, the economy, and the environment [1]. amounts of information used for data analysis and decision Though still lacking a formal definition, cyber-physical making. -
Systems Theory
1 Systems Theory BRUCE D. FRIEDMAN AND KAREN NEUMAN ALLEN iopsychosocial assessment and the develop - nature of the clinical enterprise, others have chal - Bment of appropriate intervention strategies for lenged the suitability of systems theory as an orga - a particular client require consideration of the indi - nizing framework for clinical practice (Fook, Ryan, vidual in relation to a larger social context. To & Hawkins, 1997; Wakefield, 1996a, 1996b). accomplish this, we use principles and concepts The term system emerged from Émile Durkheim’s derived from systems theory. Systems theory is a early study of social systems (Robbins, Chatterjee, way of elaborating increasingly complex systems & Canda, 2006), as well as from the work of across a continuum that encompasses the person-in- Talcott Parsons. However, within social work, sys - environment (Anderson, Carter, & Lowe, 1999). tems thinking has been more heavily influenced by Systems theory also enables us to understand the the work of the biologist Ludwig von Bertalanffy components and dynamics of client systems in order and later adaptations by the social psychologist Uri to interpret problems and develop balanced inter - Bronfenbrenner, who examined human biological vention strategies, with the goal of enhancing the systems within an ecological environment. With “goodness of fit” between individuals and their its roots in von Bertalanffy’s systems theory and environments. Systems theory does not specify par - Bronfenbrenner’s ecological environment, the ticular theoretical frameworks for understanding ecosys tems perspective provides a framework that problems, and it does not direct the social worker to permits users to draw on theories from different dis - specific intervention strategies. -
1 Umpleby Stuart Reconsidering Cybernetics
UMPLEBY STUART RECONSIDERING CYBERNETICS The field of cybernetics attracted great attention in the 1950s and 1960s with its prediction of a Second Industrial Revolution due to computer technology. In recent years few people in the US have heard of cybernetics (Umpleby, 2015a, see Figures 1 and 2 at the end of Paper). But a wave of recent books suggests that interest in cybernetics is returning (Umpleby and Hughes, 2016, see Figure at the end of Paper). This white paper reviews some basic ideas in cybernetics. I recommend these and other ideas as a resource for better understanding and modeling of social systems, including threat and response dynamics. Some may claim that whatever was useful has already been incorporated in current work generally falling under the complexity label, but that is not the case. Work in cybernetics has continued with notable contributions in recent years. Systems science, complex systems, and cybernetics are three largely independent fields with their own associations, journals and conferences (Umpleby, 2017). Four types of descriptions used in social science After working in social science and systems science for many years I realized that different academic disciplines use different basic elements. Economists use measurable variables such as price, savings, GDP, imports and exports. Psychologists focus on ideas, concepts and attitudes. Sociologists and political scientists focus on groups, organizations, and coalitions. Historians and legal scholars emphasize events and procedures. People trained in different disciplines construct different narratives using these basic elements. One way to reveal more of the variety in a social system is to create at least four descriptions – one each using variables, ideas, groups, and events (See the figures and tables in Medvedeva & Umpleby, 2015). -
Lessons from Living Systems Governance Pierre Bricage
Education for sustainability: lessons from living systems governance Pierre Bricage To cite this version: Pierre Bricage. Education for sustainability: lessons from living systems governance. 3rd IASCYS international meeting ”Research Development and Education of Systems Science and Cybernetics”, International Academy for Systems and Cybernetic Sciences, Oct 2017, Chengdu, China. halshs- 01705968 HAL Id: halshs-01705968 https://halshs.archives-ouvertes.fr/halshs-01705968 Submitted on 10 Feb 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Public Domain Education for sustainability: lessons from living systems governance. Pierre BRICAGE AFSCET, the French Society for Systems and Cybernetic Sciences, ENSAM, Paris, France, IASCYS, the International Academy for Systems and Cybernetic Sciences, IRSEEM, ESIGELEC, technopôle du Madrillet, 76801 St-Étienne du Rouvray, France E-mail: [email protected] Abstract To survive that is 'to eat and not to be eaten'. Whatever its spatial and temporal level of organisation, every living system, to survive and 'to itself survive its self', owns 7 invariant capacities: the gauge invariance paradigm (figure 1). Emerging by embedments and juxtapositions of previous systems, every living system-of-systems (figure 2) is both dependent and independent from its new global level of organisation (endophysiotope) and past and present local situations of emergence (ecoexotope).