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Libri sul tema "SimulationX"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 1 febbraio 2022

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1

Simulating war: Studying conflict through simulation games. London: Continuum, 2012.

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2

Simulating security returns: A filtered historical simulation approach. New York City, NY: Palgrave Pivot, 2014.

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3

Acél, Peter Paul. Methode zur Durchführung betrieblicher Simulationen: Effiziente Optimierung der diskreten Simulation. Zürich: Eidgenössische Technische Hochschule, 1996.

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4

Coquillard, Patrick. Modélisation et simulation d'écosystèmes: Des modèles déterministes aux simulations à événements discrets. Paris: Masson, 1997.

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5

Successful simulation: A practical approach to simulation projects. London: McGraw-Hill, 1994.

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6

Dahl, Martin. Simulating Europe: A role play simulation of the EU Council of Ministers. San Domenico (FI) Italy: European University Institute, 1999.

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7

Dahl, Martin. Simulating Europe: A role play simulation of the EU Council of Ministers. Badia Fiesolana, San Domenico (FI): European University Institute, 2000.

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8

Geostatistical, Simulation Workshop (1993 Fontainebleau France). Geostatistical simulations: Proceedings of the Geostatistical Simulation Workshop, Fontainebleau, France, 27-28 May 1993. Dordrecht: Kluwer Academic Publishers, 1994.

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9

Ross, Sheldon M. Simulation. 2a ed. San Diego: Academic Press, 1997.

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10

Lucot, Hubert. Simulation. [Paris]: Impr. nationale, 1990.

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11

Ross, Sheldon M. Simulation. 4a ed. Amsterdam: Elsevier Academic Press, 2006.

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12

Ross, Sheldon M. Simulation. 3a ed. San Diego: Academic Press, 2002.

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13

Lenhard, Johannes, Günter Küppers e Terry Shinn, a cura di. Simulation. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/1-4020-5375-4.

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14

Robinson, Stewart. Simulation. London: Macmillan Education UK, 2014. http://dx.doi.org/10.1007/978-1-137-32803-8.

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15

Thompson, James R., a cura di. Simulation. Hoboken, NJ, USA: John Wiley & Sons, Inc., 1999. http://dx.doi.org/10.1002/9780470317068.

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16

Gleiniger, Andrea, e Georg Vrachliotis, a cura di. Simulation. Berlin, Boston: DE GRUYTER, 2008. http://dx.doi.org/10.1515/9783034610353.

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17

Johnston, Lindsay C., e Lillian Su, a cura di. Comprehensive Healthcare Simulation: ECMO Simulation. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-53844-6.

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18

Carstens, Patricia K., Paul Paulman, Audrey Paulman, Marissa J. Stanton, Brian M. Monaghan e Douglas Dekker, a cura di. Comprehensive Healthcare Simulation: Mobile Medical Simulation. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33660-8.

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19

Danby, J. M. A. Astrophysics simulations. New York: Wiley, 1995.

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20

Fischer, Max W. Geography simulations. Huntington Beach, CA: Teacher Created Materials, Inc., 1995.

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21

Ken, Jones. Graded simulations. [London]: Lingual House, 1985.

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22

Bonomi, Massimiliano, e Carlo Camilloni, a cura di. Biomolecular Simulations. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9608-7.

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23

Bluestein, Howard B. Tornadoes and Their Parent Convective Storms. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190676889.013.15.

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Abstract (sommario):
In the past four decades much has been discovered about tornado formation and structure from observations, laboratory models, and numerical-simulation experiments. Observations include nearby movies and photographs of tornadoes, fixed-site, airborne, and ground-based mobile Doppler radar remote measurements, and in situ measurements using instrumented probes. Laboratory models are vortex chambers and numerical-simulations are based on the governing fluid dynamical equations. However, questions remain: How and why do tornadoes form? and How does the wind field associated with them vary in space and time? Recent studies of tornadoes based on observations, particularly by radar, are detailed. The major aspects of numerically simulating a tornado and its formation are reviewed, and the dynamics of tornado formation and structure based on both observations and laboratory and numerical-simulation experiments are described. Finally, future avenues of research and suggested instrument development for furthering our knowledge are discussed.
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24

Bluestein, Howard B. Tornadoes and Their Parent Convective Storms. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190699420.013.15.

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Abstract (sommario):
In the past four decades much has been discovered about tornado formation and structure from observations, laboratory models, and numerical-simulation experiments. Observations include nearby movies and photographs of tornadoes, fixed-site, airborne, and ground-based mobile Doppler radar remote measurements, and in situ measurements using instrumented probes. Laboratory models are vortex chambers and numerical-simulations are based on the governing fluid dynamical equations. However, questions remain: How and why do tornadoes form? and How does the wind field associated with them vary in space and time? Recent studies of tornadoes based on observations, particularly by radar, are detailed. The major aspects of numerically simulating a tornado and its formation are reviewed, and the dynamics of tornado formation and structure based on both observations and laboratory and numerical-simulation experiments are described. Finally, future avenues of research and suggested instrument development for furthering our knowledge are discussed.
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25

H, Abou-Kassem Jamal, a cura di. Reservoir simulations handbook: Understanding reservoir simulation development. Houston, TX: Gulf Pub. Co., 2006.

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26

Lenhard, Johannes. Computer Simulation. A cura di Paul Humphreys. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199368815.013.42.

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Abstract (sommario):
This article interprets computer simulation modeling as a new type of mathematical modeling that comprises a number of interdependent components, among them experimentation, visualization, and adaptability. Furthermore, it is argued, simulation modeling can be characterized as a particular style of reasoning, namely a combinatorial style, that assembles and balances elements from different other styles. Two examples are discussed that exemplify the transformative force of this style: what counts as “understanding phenomena” and what counts as a “solution.” Both are seminal pieces of traditional mathematical modeling and both are transformed, if not inverted, in simulation modeling. Finally, some challenges are considered that computer simulations pose for philosophy of science.
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27

Lioce, Lori, a cura di. Healthcare Simulation Dictionary. Agency for Healthcare Research and Quality, 2020. http://dx.doi.org/10.23970/simulationv2.

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28

Triantafyllidis, Theodoros. Holistic Simulation of Geotechnical Installation Processes: Benchmarks and Simulations. Springer, 2015.

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29

Willamette University. Center for Dispute Resolution., a cura di. Negotiation simulation exercises, 1998: Eight simulations with teaching notes. Salem, OR: Willamette University College of Law, 1998.

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30

Triantafyllidis, Theodoros. Holistic Simulation of Geotechnical Installation Processes: Benchmarks and Simulations. Springer, 2016.

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31

Allen, Michael P., e Dominic J. Tildesley. Computer Simulation of Liquids. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.001.0001.

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Abstract (sommario):
This book provides a practical guide to molecular dynamics and Monte Carlo simulation techniques used in the modelling of simple and complex liquids. Computer simulation is an essential tool in studying the chemistry and physics of condensed matter, complementing and reinforcing both experiment and theory. Simulations provide detailed information about structure and dynamics, essential to understand the many fluid systems that play a key role in our daily lives: polymers, gels, colloidal suspensions, liquid crystals, biological membranes, and glasses. The second edition of this pioneering book aims to explain how simulation programs work, how to use them, and how to interpret the results, with examples of the latest research in this rapidly evolving field. Accompanying programs in Fortran and Python provide practical, hands-on, illustrations of the ideas in the text.
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32

Gilbert, Nigel. Simulating Societies: The Computer Simulation of Social Phenomena. Taylor & Francis Group, 1994.

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33

Nigel, Gilbert G., e Doran Jim, a cura di. Simulating societies: The computer simulation of social phenomena. London: UCL Press, 1994.

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34

Simulating societies: The computer simulation of social phenomena. London: UCL Press, 1994.

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35

Allen, Michael P., e Dominic J. Tildesley. Some tricks of the trade. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0005.

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Abstract (sommario):
This chapter concentrates on practical tips and tricks for improving the efficiency of computer simulation programs. This includes the effect of using truncated and shifted potentials, and the use of table look-up and neural networks for calculating potentials. Approaches for speeding up simulations, such as the Verlet neighbour list, linked-lists and multiple timestep methods are described. The chapter then proceeds to discuss the general structure of common simulation programs; in particular the choice of the starting configuration and the initial velocities of the particles. The chapter also contains details of the overall approach to organising runs, storing the data, and checking that the program is working correctly.
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36

Allen, Michael P., e Dominic J. Tildesley. Statistical mechanics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0002.

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Abstract (sommario):
This chapter contains the essential statistical mechanics required to understand the inner workings of, and interpretation of results from, computer simulations. The microcanonical, canonical, isothermal–isobaric, semigrand and grand canonical ensembles are defined. Thermodynamic, structural, and dynamical properties of simple and complex liquids are related to appropriate functions of molecular positions and velocities. A number of important thermodynamic properties are defined in terms of fluctuations in these ensembles. The effect of the inclusion of hard constraints in the underlying potential model on the calculated properties is considered, and the addition of long-range and quantum corrections to classical simulations is presented. The extension of statistical mechanics to describe inhomogeneous systems such as the planar gas–liquid interface, fluid membranes, and liquid crystals, and its application in the simulation of these systems, are discussed.
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37

MEDI-SIM. Fetal Demise Simulation 2 (CLINICAL SIMULATIONS IN WOMEN'S HEALTH NURSING 3). Lippincott Williams & Wilkins, 1994.

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38

An Object-Oriented Discrete-Event Simulation System for Hierarchical Parallel Simulations. Storming Media, 1996.

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39

Handbook Of Simulation And Financial Risk Management Simulations And Case Studies. John Wiley and Sons Ltd, 2013.

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40

MEDI-SIM. Contraceptive Counseling Simulation 1 (CLINICAL SIMULATIONS IN WOMEN'S HEALTH NURSING 3). Lippincott Williams & Wilkins, 1994.

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41

Birks, Daniel. Computer Simulations. A cura di Gerben J. N. Bruinsma e Shane D. Johnson. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190279707.013.36.

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Abstract (sommario):
In recent years, the field of social simulation has been dominated by the individual, or agent-based, computational model (ABM). ABMs provide unique means to explore complex social systems by allowing researchers to construct explicit models of the individual actors and interactions that make them up - people, peer groups, companies, nations, trade, reproduction, victimization, and so on, This chapter aims to provide the reader with a primer in the social simulation method and in particular the application of ABM in the field of environmental criminology. It begins by discussing the rationale behind the ABM approach. Subsequently, drawing on two illustrative simulations, it summarizes fundamental processes involved in designing, constructing, verifying, calibrating, validating, and utilizing ABM. It concludes by discussing some of the overarching strengths and limitations of the approach, and by discussing several areas of research that might aid in furthering the use of ABM within the field of environmental criminology.
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42

McGraw-Hill. Glencoe Accounting: Concepts/Procedures/Applications, Business Simulations, London & Company Simulation, Text-Workbook. 2a ed. Glencoe/McGraw-Hill, 1992.

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43

McGraw-Hill. Glencoe Accounting: Concepts/Procedures/Applications, Business Simulations, London & Company Simulation, Text-Workbook. Glencoe/McGraw-Hill, 1992.

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44

Robinson, Stewart. Successful Simulation: A Practical Approach to Simulation Projects. Mcgraw Hill Book Co Ltd, 1996.

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45

Robinson, Stewart. Successful Simulation: A Practical Approach to Simulation Projects. Mcgraw Hill Book Co Ltd, 1996.

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46

Potchinkov, Alexander. Simulation von Röhrenverstärkern mit SPICE: PC-Simulationen von Elektronenröhren in Audioverstärkern. Vieweg+Teubner Verlag, 2009.

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47

Lewis, Deborah, Marie O’Boyle-Duggan e Susan Poultney. Communication skills education and training in pre-registration BSc Nursing. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198736134.003.0023.

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Abstract (sommario):
Nursing and Midwifery Council educational standards in BSc (Hons) Nursing require students to gain key communication competences to deliver compassionate care in adult, mental health, learning disabilities, and children’s nursing. Competences include using a range of verbal and non-verbal skills to build therapeutic relationships, being respectful of confidential information, addressing diversity issues, and promoting well-being and personal safety. Nurses also need to make reasonable adjustment for patients with disabilities to ensure effective communication. High fidelity simulations using actors and clinical practice scenarios have been evaluated positively with statistically significant results, suggesting the benefits apply to all students in the classroom—although students who participate in a simulation benefit to a greater extent. Other faculty mixed-methods research led to the development of recommendations for communication skills in learning disabilities nursing. Challenges include realistic simulation in children’s nursing and developing adequate numbers of actors and facilitators, partially offset by offering in-house training.
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48

Schwarz, Christian, Gunnar Stiesch, Günter P. Merker e Frank Otto. Simulating Combustion: Simulation of combustion and pollutant formation for engine-development. Springer, 2005.

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49

MEDI-SIM. Vaginal Birth After Cesarean Simulation 3 (CLINICAL SIMULATIONS IN WOMEN'S HEALTH NURSING 3). Lippincott Williams & Wilkins, 1994.

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50

Allen, Michael P., e Dominic J. Tildesley. Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0001.

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Abstract (sommario):
This chapter contains a short review of the development of computer simulation, and its place in research as a complement to experiment and theory. This is followed by an introduction to intermolecular interactions, and the way that they are modelled on a computer, complete with examples of program code. Force fields are introduced to describe the full range of interactions in atomic and molecular fluids and a number of coarsegrained models for exploring liquid-crystalline and polymer systems are also considered. The consequences of performing bulk simulations using finite-size systems are described, along with the way that these problems can be mitigated by the use of periodic boundary conditions.
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