Relevant bibliographies by topics / Information dynamics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Information dynamics'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Information dynamics"

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Golan, Amos. "Information Dynamics." Minds and Machines 24, no. 1 (October 1, 2013): 19–36. http://dx.doi.org/10.1007/s11023-013-9326-2.

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Stevens, Ronald, Trysha Galloway, Ann Willemson-Dunlap, Jamie Gorman, and Donald Halpin. "Making Sense of Team Information." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 114–18. http://dx.doi.org/10.1177/1541931218621026.

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This paper describes how meaning can be extracted from large-scale dynamical data to make inferences about teamwork that are useful in both the theoretical and practical sense. The dynamics of an anesthesiology team are viewed from the perspectives of: 1) changes in the team’s neurodynamic organizations with large and small changes in the task; 2) how team member’s neurodynamics contribute to team neurodynamics; 3) the relationships between task events, heart-rate and neural dynamic organizations; 4) the linkages between speech flow, team and team member neurodynamics and topic discussions during Debriefing; and, 5) the micro-scale neural dynamics reflecting the involvement of the parietal lobes and gamma frequencies. These examples show how different sources of team data can contribute to multi-modal understandings of individual and teams dynamics that span micro and macro scales of teamwork.
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Kadomtsev, Boris B. "Dynamics and information." Uspekhi Fizicheskih Nauk 164, no. 5 (1994): 449. http://dx.doi.org/10.3367/ufnr.0164.199405a.0449.

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Kadomtsev, Boris B. "Dynamics and information." Physics-Uspekhi 37, no. 5 (May 31, 1994): 425–99. http://dx.doi.org/10.1070/pu1994v037n05abeh000109.

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Zenil, Hector, Narsis Kiani, Felipe Abrahão, and Jesper Tegnér. "Algorithmic Information Dynamics." Scholarpedia 15, no. 7 (2020): 53143. http://dx.doi.org/10.4249/scholarpedia.53143.

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Fox, Robert. "Information fluid dynamics." OCLC Systems & Services: International digital library perspectives 27, no. 2 (May 30, 2011): 87–94. http://dx.doi.org/10.1108/10650751111135382.

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CIORUŢA, Alin-Andrei, and Bogdan CIORUŢA. "REGARDING THE POPULATION DYNAMICS INVESTIGATION USING ENVIRONMENTAL INFORMATION SYSTEMS." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (June 24, 2016): 411–16. http://dx.doi.org/10.19062/2247-3173.2016.18.1.56.

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Warren, Kenneth S. "FROM INFORMATION STATICS TO INFORMATION DYNAMICS." Infectious Disease Clinics of North America 9, no. 2 (June 1995): 367–75. http://dx.doi.org/10.1016/s0891-5520(20)30666-8.

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Sun, Zejun, Jinfang Sheng, Bin Wang, Aman Ullah, and FaizaRiaz Khawaja. "Identifying Communities in Dynamic Networks Using Information Dynamics." Entropy 22, no. 4 (April 9, 2020): 425. http://dx.doi.org/10.3390/e22040425.

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Identifying communities in dynamic networks is essential for exploring the latent network structures, understanding network functions, predicting network evolution, and discovering abnormal network events. Many dynamic community detection methods have been proposed from different viewpoints. However, identifying the community structure in dynamic networks is very challenging due to the difficulty of parameter tuning, high time complexity and detection accuracy decreasing as time slices increase. In this paper, we present a dynamic community detection framework based on information dynamics and develop a dynamic community detection algorithm called DCDID (dynamic community detection based on information dynamics), which uses a batch processing technique to incrementally uncover communities in dynamic networks. DCDID employs the information dynamics model to simulate the exchange of information among nodes and aims to improve the efficiency of community detection by filtering out the unchanged subgraph. To illustrate the effectiveness of DCDID, we extensively test it on synthetic and real-world dynamic networks, and the results demonstrate that the DCDID algorithm is superior to the representative methods in relation to the quality of dynamic community detection.
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Matsuno, Koichiro. "Dynamics of time and information in dynamic time." Biosystems 46, no. 1-2 (April 1998): 57–71. http://dx.doi.org/10.1016/s0303-2647(97)00081-6.

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Dissertations / Theses on the topic "Information dynamics"

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Yepez, Jeffrey. "Quantum information dynamics." W&M ScholarWorks, 2010. https://scholarworks.wm.edu/etd/1539623574.

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Presented is a study of quantum entanglement from the perspective of the theory of quantum information dynamics. We consider pairwise entanglement and present an analytical development using joint ladder operators, the sum of two single-particle fermionic ladder operators. This approach allows us to write down analytical representations of quantum algorithms and to explore quantum entanglement as it is manifested in a system of qubits.;We present a topological representation of quantum logic that views entangled qubit spacetime histories (or qubit world lines) as a generalized braid, referred to as a super-braid. The crossing of world lines may be either classical or quantum mechanical in nature, and in the latter case most conveniently expressed with our analytical expressions for entangling quantum gates. at a quantum mechanical crossing, independent world lines can become entangled. We present quantum skein relations that allow complicated superbraids to be recursively reduced to alternate classical histories. If the superbraid is closed, then one can decompose the resulting superlink into an entangled superposition of classical links. Also, one can compute a superlink invariant, for example the Jones polynomial for the square root of a knot.;We present measurement-based quantum computing based on our joint number operators. We take expectation values of the joint number operators to determine kinetic-level variables describing the quantum information dynamics in the qubit system at the mesoscopic scale. We explore the issue of reversibility in quantum maps at this scale using a quantum Boltzmann equation. We then present an example of quantum information processing using a qubit system comprised of nuclear spins. We also discuss quantum propositions cast in terms of joint number operators.;We review the well known dynamical equations governing superfluidity, with a focus on self-consistent dynamics supporting quantum vortices in a Bose-Einstein condensate (BEC). Furthermore, we review the mutual vortex-vortex interaction and the consequent Kelvin wave instability. We derive an effective equation of motion for a Fermi condensate that is the basis of our qubit representation of superfluidity.;We then present our quantum lattice gas representation of a superfluid. We explore aspects of our model with two qubits per point, referred to as a Q2 model, particularly its usefulness for carrying out practical quantum fluid simulations. We find that it is perhaps the simplest yet most comprehensive model of superfluid dynamics. as a prime application of Q2, we explore the power-law regions in the energy spectrum of a condensate in the low-temperature limit. We achieved the largest quantum simulations to date of a BEC and, for the first time, Kolmogorov scaling in superfluids, a flow regime heretofore only obtainably by classical turbulence models.;Finally, we address the subject of turbulence regarding information conservation on the small scales (both mesoscopic and microscopic) underlying the flow dynamics on the large hydrodynamic (macroscopic) scale. We present a hydrodynamic-level momentum equation, in the form of a Navier-Stokes equation, as the basis for the energy spectrum of quantum turbulence at large scales. Quantum turbulence, in particular the representation of fluid eddies in terms of a coherent structure of polarized quantum vortices, offers a unique window into the heretofore intractable subject of energy cascades.
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Tangermann, Ole. "Information Dynamics Informationen, deren Auswirkungen und Managemenent in Wertschöpfungsketten /." [S.l.] : [s.n.], 2007. http://opus.kobv.de/tuberlin/volltexte/2007/1575.

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Roberts, Mark Andrew. "Information and exchange rate dynamics." Thesis, University of Warwick, 1988. http://wrap.warwick.ac.uk/4460/.

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Theoretical models of the exchange rate are developed where information on the model is not fully available to agents. It is an application of Benjamin Friedman's (1979) theme that full rational expectations may be a possibility only in the long-run, even for completely rational individuals. The thesis attempts to develop the theory of exchange rate behaviour by considering some neglected informational issues. The three substantive chapters each consider specific aspects of relevance to the determination of the exchange rate from an asset market view of perfect capital mobility. These are the possible current account inter-relationship, the persistence of interest rate differentials between the two currencies and the subjectivity of and the regress in beliefs across a decentralised market. Generally, limited information on the model will give rise to erroneous beliefs, on the one hand, and encourage the acquistion of information and the revision of beliefs, on the other. Erroneous beliefs will cause correlations between variables, which may not normally occur inside full rational expectations. The revision of beliefs will bring a particular source of non-stationarity to the data. And the stability of certain learning forms may require limitations on the degree of capital mobility. These conclusions would suggest that any empirical work on modelling the exchange rate may gain from relaxing certain a priori restrictions, which properly belong to models with stronger assumptions on the availability of information.
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Hoshi, Tomohiro. "Epistemic dynamics and protocol information /." May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Whiting, Stewart William. "Temporal dynamics in information retrieval." Thesis, University of Glasgow, 2015. http://theses.gla.ac.uk/6850/.

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The passage of time is unrelenting. Time is an omnipresent feature of our existence, serving as a context to frame change driven by events and phenomena in our personal lives and social constructs. Accordingly, various elements of time are woven throughout information itself, and information behaviours such as creation, seeking and utilisation. Time plays a central role in many aspects of information retrieval (IR). It can not only distinguish the interpretation of information, but also profoundly influence the intentions and expectations of users' information seeking activity. Many time-based patterns and trends - namely temporal dynamics - are evident in streams of information behaviour by individuals and crowds. A temporal dynamic refers to a periodic regularity, or, a one-off or irregular past, present or future of a particular element (e.g., word, topic or query popularity) - driven by predictable and unpredictable time-based events and phenomena. Several challenges and opportunities related to temporal dynamics are apparent throughout IR. This thesis explores temporal dynamics from the perspective of query popularity and meaning, and word use and relationships over time. More specifically, the thesis posits that temporal dynamics provide tacit meaning and structure of information and information seeking. As such, temporal dynamics are a ‘two-way street’ since they must be supported, but also conversely, can be exploited to improve time-aware IR effectiveness. Real-time temporal dynamics in information seeking must be supported for consistent user satisfaction over time. Uncertainty about what the user expects is a perennial problem for IR systems, further confounded by changes over time. To alleviate this issue, IR systems can: (i) assist the user to submit an effective query (e.g., error-free and descriptive), and (ii) better anticipate what the user is most likely to want in relevance ranking. I first explore methods to help users formulate queries through time-aware query auto-completion, which can suggest both recent and always popular queries. I propose and evaluate novel approaches for time-sensitive query auto-completion, and demonstrate state-of-the-art performance of up to 9.2% improvement above the hard baseline. Notably, I find results are reflected across diverse search scenarios in different languages, confirming the pervasive and language agnostic nature of temporal dynamics. Furthermore, I explore the impact of temporal dynamics on the motives behind users' information seeking, and thus how relevance itself is subject to temporal dynamics. I find that temporal dynamics have a dramatic impact on what users expect over time for a considerable proportion of queries. In particular, I find the most likely meaning of ambiguous queries is affected over short and long-term periods (e.g., hours to months) by several periodic and one-off event temporal dynamics. Additionally, I find that for event-driven multi-faceted queries, relevance can often be inferred by modelling the temporal dynamics of changes in related information. In addition to real-time temporal dynamics, previously observed temporal dynamics offer a complementary opportunity as a tacit dimension which can be exploited to inform more effective IR systems. IR approaches are typically based on methods which characterise the nature of information through the statistical distributions of words and phrases. In this thesis I look to model and exploit the temporal dimension of the collection, characterised by temporal dynamics, in these established IR approaches. I explore how the temporal dynamic similarity of word and phrase use in a collection can be exploited to infer temporal semantic relationships between the terms. I propose an approach to uncover a query topic's "chronotype" terms -- that is, its most distinctive and temporally interdependent terms, based on a mix of temporal and non-temporal evidence. I find exploiting chronotype terms in temporal query expansion leads to significantly improved retrieval performance in several time-based collections. Temporal dynamics provide both a challenge and an opportunity for IR systems. Overall, the findings presented in this thesis demonstrate that temporal dynamics can be used to derive tacit structure and meaning of information and information behaviour, which is then valuable for improving IR. Hence, time-aware IR systems which take temporal dynamics into account can better satisfy users consistently by anticipating changing user expectations, and maximising retrieval effectiveness over time.
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Sardanyés, i. Cayuela Josep. "Dynamics, evolution and information in nonlinear dynamical systems of replicators." Doctoral thesis, Universitat Pompeu Fabra, 2009. http://hdl.handle.net/10803/7182.

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En aquesta tesi he investigat diversos camps de la biologia que podrien englobar-se en la disciplina general dels sistemes no lineals de replicadors. Els treballs presentats en aquesta tesis investiguen diversos fenomens dinàmics i processos evolutius per virus de RNA, pels anomenats hipercicles i per models generals de replicadors antagonistes. Específicament he investigat les anomenades quasiespècies, utilitzades per a modelitzar poblacions de RNA. Els treballs sobre hipercicles exploren diversos fenomens previs a l'origen de la vida i a l'aparició de la primera cèl.lula vivent. Mitjançant models ecològics com també utilitzant diferents eines computacionals he estudiat l'anomenada hipòtesi de la Reina Roja per entitats replicadores simples amb mutació. Aquests estudis tenen un interès en el contexte de l'evolució prebiòtica i l'ecologia teòrica.
In this thesis I have investigated several fields of biology that can be classified in the general subject of replicator nonlinear systems. The works presented in the thesis investigate several dynamical phenomena and evolutionary processes for RNA viruses, for hypercycles and for general models on antagonistic replicator dynamics. I have specifically investigated the dynamics of so-called quasispecies, used for the modelization of RNA populations. The works on hypercycles explore several phenomena related to previous events to the origin of life and to the appearance of the first living cell. By means of some ecologically-based mathematical models as well as of some computational models we also investigate the so-called Red Queen hypothesis for small, replicating-mutating entities. These studies are of interest in the context of prebiotic evolution and theoretical ecology.
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Sardanyés, Cayuela Josep. "Dynamics, evolution and information in nonlinear dynamical systems of replicators." Doctoral thesis, Universitat Pompeu Fabra, 2009. http://hdl.handle.net/10803/7182.

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En aquesta tesi he investigat diversos camps de la biologia que podrien englobar-se en la disciplina general dels sistemes no lineals de replicadors. Els treballs presentats en aquesta tesis investiguen diversos fenomens dinàmics i processos evolutius per virus de RNA, pels anomenats hipercicles i per models generals de replicadors antagonistes. Específicament he investigat les anomenades quasiespècies, utilitzades per a modelitzar poblacions de RNA. Els treballs sobre hipercicles exploren diversos fenomens previs a l'origen de la vida i a l'aparició de la primera cèl.lula vivent. Mitjançant models ecològics com també utilitzant diferents eines computacionals he estudiat l'anomenada hipòtesi de la Reina Roja per entitats replicadores simples amb mutació. Aquests estudis tenen un interès en el contexte de l'evolució prebiòtica i l'ecologia teòrica.
In this thesis I have investigated several fields of biology that can be classified in the general subject of replicator nonlinear systems. The works presented in the thesis investigate several dynamical phenomena and evolutionary processes for RNA viruses, for hypercycles and for general models on antagonistic replicator dynamics. I have specifically investigated the dynamics of so-called quasispecies, used for the modelization of RNA populations. The works on hypercycles explore several phenomena related to previous events to the origin of life and to the appearance of the first living cell. By means of some ecologically-based mathematical models as well as of some computational models we also investigate the so-called Red Queen hypothesis for small, replicating-mutating entities. These studies are of interest in the context of prebiotic evolution and theoretical ecology.
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Reezek, Iead Arend. "Information dynamics in physiological control systems." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266591.

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Leifer, Matthew. "Entangled quantum dynamics." Thesis, University of Bristol, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289776.

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Tsalgatidou, Aphrodite. "Dynamics of information systems : modelling and verification." Thesis, University of Manchester, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.257152.

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Books on the topic "Information dynamics"

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NATO, Advanced Study Institute on Information Dynamics (1990 Irsee Germany). Information dynamics. New York: Plenum Press, 1991.

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Deco, Gustavo, and Bernd Schürmann. Information Dynamics. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0127-1.

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Atmanspacher, Harald, and Herbert Scheingraber, eds. Information Dynamics. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2305-9.

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Winter, School of Theoretical Physics (46th 2010 Lądek Zdrój Poland). Quantum dynamics and information. Singapore: World Scientific, 2011.

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Vogiatzis, Chrysafis, Jose L. Walteros, and Panos M. Pardalos, eds. Dynamics of Information Systems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10046-3.

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Hirsch, Michael J., Panos M. Pardalos, and Robert Murphey, eds. Dynamics of Information Systems. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-5689-7.

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Information systems and business dynamics. Reading, Mass: Addison-Wesley Pub. Co., 1990.

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Roberts, Mark A. Information and exchange rate dynamics. [s.l.]: typescript, 1988.

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Ingarden, R. S., A. Kossakowski, and M. Ohya. Information Dynamics and Open Systems. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-017-1882-0.

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Logical dynamics of information and interaction. Cambridge: Cambridge University Press, 2011.

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Book chapters on the topic "Information dynamics"

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Ingarden, R. S., A. Kossakowski, and M. Ohya. "Information Dynamics." In Information Dynamics and Open Systems, 105–20. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-017-1882-0_4.

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Roy, Rahul. "System dynamics." In Information Systems, 273–86. Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge India, 2019. http://dx.doi.org/10.4324/9780429202933-14.

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Haken, Hermann. "Aspects of Information Processing: Information Flow in Synergetic Computers." In Information Dynamics, 195–200. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2305-9_15.

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Galton, Antony. "Dynamic Collectives and Their Collective Dynamics." In Spatial Information Theory, 300–315. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11556114_19.

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Ohya, Masanori, and Igor Volovich. "Information Dynamics and Adaptive Dynamics." In Theoretical and Mathematical Physics, 251–312. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0171-7_10.

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Antoniou, Ioannis E. "Information and Dynamical Systems." In Information Dynamics, 221–36. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2305-9_18.

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Lloyd, Seth. "Causality and Information Flow." In Information Dynamics, 131–42. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2305-9_9.

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Kaye, Brian H., and G. G. Clark. "Formation Dynamics Information." In ACS Symposium Series, 372–85. Washington, DC: American Chemical Society, 1991. http://dx.doi.org/10.1021/bk-1991-0472.ch024.

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Iida, Hiroyuki, and Takeo Nakagawa. "Game Information Dynamics." In Entertainment Computing – ICEC 2011, 403–6. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24500-8_52.

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Klir, George J. "Measures and Principles of Uncertainty and Information: Recent Developments." In Information Dynamics, 1–14. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2305-9_1.

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Conference papers on the topic "Information dynamics"

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Levoniuk, Sergey V., Larisa A. Ginis, and Larisa V. Gordienko. "The development of geographic information system model for information flows monitoring of complex objects." In 2017 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2017. http://dx.doi.org/10.1109/dynamics.2017.8239479.

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Shafeeva, O. P., V. V. Makarov, A. S. Gritsay, D. A. Tyunkov, and D. M. Bogorad. "Error Correction of Transmission of Binary Information." In 2018 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2018. http://dx.doi.org/10.1109/dynamics.2018.8601459.

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Semakhin, Andrei M. "Network Simulation of Information System in Conditions Of Uncertainty." In 2018 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2018. http://dx.doi.org/10.1109/dynamics.2018.8601500.

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Anikin, Igor V. "Information security risks assessment in telecommunication network of the university." In 2016 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2016. http://dx.doi.org/10.1109/dynamics.2016.7818967.

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Klypin, Dmitry N., Ilya V. Potapov, Dmitry A. Titov, and Antonina A. Garaeva. "The base tasks in development of Biomedical Data Information System." In 2016 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2016. http://dx.doi.org/10.1109/dynamics.2016.7819027.

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Shcherbakov, M. A., and V. V. Sazonov. "SVD-scaling of digital images in the information and communication systems." In 2016 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2016. http://dx.doi.org/10.1109/dynamics.2016.7819083.

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Urakseev, M. A., K. V. Vazhdaev, and A. R. Sagadeev. "Microcontroller information-measuring system of linear movements with acousto-optic modulator." In 2017 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2017. http://dx.doi.org/10.1109/dynamics.2017.8239524.

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Marenko, V. A., and O. N. Luchko. "Cognitive modeling application for management the information flows on the small business." In 2014 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2014. http://dx.doi.org/10.1109/dynamics.2014.7005680.

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Primova, Holida, Dilshodbek Sotvoldiev, and Lola Safarova. "Approaches to solving the problem of risk assessment with fuzzy initial information." In 2018 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2018. http://dx.doi.org/10.1109/dynamics.2018.8601485.

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L'vov, A. A., D. V. Klenov, A. A. Sytnik, O. N. Dolinina, and M. S. Svetlov. "Increasing of information reliability of digital communication channels under conditions of high intensity noise." In 2016 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2016. http://dx.doi.org/10.1109/dynamics.2016.7819025.

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Reports on the topic "Information dynamics"

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Lerman, Kristina. Social Dynamics of Information. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada589259.

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Agrawala, Ashok K., Udaya Shankar, and Ronald Larsen. Information Dynamics and Agent Infrastructure. Fort Belvoir, VA: Defense Technical Information Center, June 2003. http://dx.doi.org/10.21236/ada417453.

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Mikhail Rabinovich and Lev Tsimring. Spatiotemporal Wave Patterns: Information Dynamics. Office of Scientific and Technical Information (OSTI), January 2006. http://dx.doi.org/10.2172/875427.

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Prasad, Sudhakar. Information Dynamics in Image Deconvolution. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada387809.

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Eom, Hyeonsang, Ashok K. Agrawala, Sam H. Noh, and A. U. Shankar. Information Dynamics Applied to Link-State Routing. Fort Belvoir, VA: Defense Technical Information Center, November 2001. http://dx.doi.org/10.21236/ada440518.

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Arcidiacono, Peter, Esteban Aucejo, Arnaud Maurel, and Tyler Ransom. College Attrition and the Dynamics of Information Revelation. Cambridge, MA: National Bureau of Economic Research, June 2016. http://dx.doi.org/10.3386/w22325.

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Acemoglu, Daron, Kostas Bimpikis, and Asuman Ozdaglar. Dynamics of Information Exchange in Endogenous Social Networks. Cambridge, MA: National Bureau of Economic Research, September 2010. http://dx.doi.org/10.3386/w16410.

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Ya, Nong. Information Dynamics and Emergent Behavior of Heterogeneous-Agent Systems. Fort Belvoir, VA: Defense Technical Information Center, December 2001. http://dx.doi.org/10.21236/ada401850.

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Angeletos, George-Marios, Christian Hellwig, and Alessandro Pavan. Information Dynamics and Equilibrium Multiplicity in Global Games of Regime Change. Cambridge, MA: National Bureau of Economic Research, December 2004. http://dx.doi.org/10.3386/w11017.

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Crucini, Mario, Mototsugu Shintani, and Takayuki Tsuruga. Noisy Information, Distance and Law of One Price Dynamics Across US Cities. Cambridge, MA: National Bureau of Economic Research, February 2012. http://dx.doi.org/10.3386/w17815.

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