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This book addresses the physical phenomenon of events that seem to occur spontaneously and without any known cause. These are to be contrasted with events that happen in a (pre)determined, predictable, lawful, and causal way.All our knowledge is based on selfreflexive theorizing, as well as on operational means of empirical perception. Some of the questions that arise are the following: are these limitations reflected by our models? Under what circumstances does chance kick in? Is chance in physics merely epistemic? In other words, do we simply not know enough, or use too crude levels of description for our predictions? Or are certain events "truly", that is, irreducibly, random? The book tries to answer some of these questions by introducing intrinsic, embedded observers and provable unknowns; that is, observables and procedures which are certified (relative to the assumptions) to be unknowable or undoable. A (somewhat iconoclastic) review of quantum mechanics is presented which is inspired by quantum logic. Postulated quantum (un)knowables are reviewed. More exotic unknowns originate in the assumption of classical continua, and in finite automata and generalized urn models, which mimic complementarity and yet maintain value definiteness. Traditional conceptions of free will, miracles and dualistic interfaces are based on gaps in an otherwise deterministic universe.
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The last few years have been characterized by a tremendous development of quantum information and probability and their applications, including quantum computing, quantum cryptography, and quantum random generators. In spite of the successful development of quantum technology, its foundational basis is still not concrete and contains a few sandy and shaky slices. Quantum random generators are one of the most promising outputs of the recent quantum information revolution. Therefore, it is very important to reconsider the foundational basis of this project, starting with the notion of irreducible quantum randomness. Quantum probabilities present a powerful tool to model uncertainty. Interpretations of quantum probability and foundational meaning of its basic tools, starting with the Born rule, are among the topics which will be covered by this issue. Recently, quantum probability has started to play an important role in a few areas of research outside quantum physics—in particular, quantum probabilistic treatment of problems of theory of decision making under uncertainty. Such studies are also among the topics of this issue.
quantum logic  groups  partially defined algebras  quasigroups  viable cultures  quantum information theory  bit commitment  protocol  entropy  entanglement  orthogonality  quantum computation  Gram–Schmidt process  quantum probability  potentiality  complementarity  uncertainty relations  Copenhagen interpretation  indefiniteness  indeterminism  causation  randomness  quantum information  quantum dynamics  entanglement  algebra  causality  geometry  probability  quantum information theory  realism  reality  entropy  correlations  qubits  probability representation  Bayes’ formula  quantum entanglement  threequbit random states  entanglement classes  entanglement polytope  anisotropic invariants  quantum random number  vacuum state  maximization of quantum conditional minentropy  quantum logics  quantum probability  holistic semantics  epistemic operations  Bell inequalities  algorithmic complexity  Borel normality  Bayesian inference  model selection  random numbers  quantumlike models  operational approach  information interpretation of quantum theory  social laser  social energy  quantum information field  social atom  Bose–Einstein statistics  bandwagon effect  social thermodynamics  resonator of social laser  master equation for socioinformation excitations  quantum contextuality  Kochen–Specker sets  MMP hypergraphs  Greechie diagrams  quantum foundations  probability  irreducible randomness  random number generators  quantum technology  entanglement  quantumlike models for social stochasticity  contextuality
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Entropy theory has wide applications to a range of problems in the fields of environmental and water engineering, including river hydraulic geometry, fluvial hydraulics, water monitoring network design, river flow forecasting, floods and droughts, river network analysis, infiltration, soil moisture, sediment transport, surface water and groundwater quality modeling, ecosystems modeling, water distribution networks, environmental and water resources management, and parameter estimation. Such applications have used several different entropy formulations, such as Shannon, Tsallis, Reacutenyi Burg, Kolmogorov, Kapur, configurational, and relative entropies, which can be derived in time, space, or frequency domains. More recently, entropybased concepts have been coupled with other theories, including copula and wavelets, to study various issues associated with environmental and water resources systems. Recent studies indicate the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering, including establishing and explaining physical connections between theory and reality. The objective of this Special Issue is to provide a platform for compiling important recent and current research on the applications of entropy theory in environmental and water engineering. The contributions to this Special Issue have addressed many aspects associated with entropy theory applications and have shown the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering.
complexity  streamflow  water level  composite multiscale sample entropy  trend  Poyang Lake basin  fourparameter exponential gamma distribution  principle of maximum entropy  precipitation frequency analysis  methods of moments  maximum likelihood estimation  flood frequency analysis  generalized gamma (GG) distribution  principle of maximum entropy (POME)  entropy theory  principle of maximum entropy (POME)  GB2 distribution  flood frequency analysis  nonpoint source pollution  ANN  entropy weighting method  datascarce  multievents  spatiotemporal variability  soil water content  entropy  arid region  joint entropy  NDVI  temperature  precipitation  groundwater depth  Hei River basin  turbulent flow  canopy flow  randomness  coherent structures  Shannon entropy  Kolmogorov complexity  entropy  information transfer  optimization  radar  rainfall network  water resource carrying capacity  forewarning model  entropy of information  fuzzy analytic hierarchy process  projection pursuit  accelerating genetic algorithm  entropy production  conditional entropy production  stochastic processes  scaling  climacogram  turbulence  water resources vulnerability  connection entropy  changing environment  set pair analysis  Anhui Province  crossentropy minimization  land suitability evaluation  spatial optimization  monthly streamflow forecasting  Burg entropy  configurational entropy  entropy spectral analysis time series analysis  entropy  water monitoring  network design  hydrometric network  information theory  entropy applications  hydrological risk analysis  maximum entropycopula method  uncertainty  Loess Plateau  entropy  water engineering  Tsallis entropy  principle of maximum entropy  Lagrangian function  probability distribution function  flux concentration relation  uncertainty  information  informational entropy  variation of information  continuous probability distribution functions  confidence intervals  precipitation  variability  marginal entropy  crop yield  Hexi corridor  flow duration curve  Shannon entropy  entropy parameter  modeling  spatial and dynamics characteristic  hydrology  tropical rainfall  statistical scaling  Tsallis entropy  multiplicative cascades  BetaLognormal model  rainfall forecast  cross entropy  ant colony fuzzy clustering  combined forecast  information entropy  mutual information  kernel density estimation  ENSO  nonlinear relation  scaling laws  power laws  water distribution networks  robustness  flow entropy  entropy theory  frequency analysis  hydrometeorological extremes  Bayesian technique  rainfall  entropy ensemble filter  ensemble model simulation criterion  EEF method  bootstrap aggregating  bagging  bootstrap neural networks  El Niño  ENSO  neural network forecast  sea surface temperature  tropical Pacific  entropy  cross elasticity  mean annual runoff  water resources  resilience  quaternary catchment  complement  substitute  entropy theory  complex systems  hydraulics  hydrology  water engineering  environmental engineering
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