We investigate a connection between recent results in 3D quantum gravity,providing an effective noncommutative-spacetime description, and some earlierheuristic descriptions of a quantum-gravity contribution to the fuzziness ofthe worldlines of particles. We show that 3D-gravity-inspired spacetimenoncommutativity reflects some of the features suggested by previous heuristicarguments. Most notably, gravity-induced worldline fuzziness, whileirrelevantly small on terrestrial scales, could be observably large forpropagation of particles over cosmological distances.
In this work, we present definition of intuitionistic fuzzy parameterized(IFP) intuitionistic fuzzy soft set and its operations. Then we defineIFP-aggregation operator to form IFP-intuitionistic fuzzy soft-decision-makingmethod which allows constructing more efficient decision processes.
It has been found that the quantum-to-classical transition can be observedindependent of macroscopicity of the quantum state for a fixed degree offuzziness in the coarsened references of measurements. Here, a generalsituation, that is the degree of fuzziness can change with the rotation anglebetween two states (different rotation angles represent different references),is researched based on the reason that the fuzziness of reference can come fromtwo kinds: the Hamiltonian (rotation frequency) and the timing (rotation time).Our results show that, for the fuzziness of Hamiltonian alone, the degree offuzziness for reference will change with the rotation angle between two statesand the quantum effects can still be observed no matter how much degree offuzziness of Hamiltonian; for the fuzziness of timing, the degree of coarseningreference is unchanged with the rotation angle. Moreover, during the rotationof the measurement axis, the decoherence environment can also help theclassical-to-quantum transition due to changing the direction of measurementaxis.
Continuous weak or fuzzy measurement of the Rabi oscillation of a two levelatom subjected to a $\pi-$pulse of a resonant light field is simulatednumerically. We thereby address the question whether it is possible to measurecharacteristic features of the motion of the state of a single quantum systemin real time. We compare two schemes of continuous measurement: continuousmeasurement with constant fuzziness and with fuzziness changing in the courseof the measurement. Because the sensitivity of the Rabi atom to the influenceof the measurement depends on the state of the atom, it is possible to optimizethe continuous fuzzy measurement by varying its fuzziness.
In view of the data gathered in September 1997, we review the flux valuescollected so far for the "fuzziness" seen in the optical counterpart ofGRB970228. Comparison between the ground based data collected in March and thedata of September 1997 suggests a fading of the fuzz. Given the diversity ofthe data in hand, the magnitude of the effect and its significance are not easyto quantify. Only new images, both from the ground and with the SpaceTelescope, directly comparable to the old ones could settle this problem.
We study the stability of the noncommutative Schwarzschild black holeinterior by analysing the propagation of a massless scalar field between thetwo horizons. We show that the spacetime fuzziness triggered by the fieldhigher momenta can cure the classical exponential blue shift divergence,suppressing the emergence of infinite energy density in a region nearby theCauchy horizon.
Reasoning, the most important human brain operation, is charactrized by adegree fuzziness. In the present paper we construct a fuzzy model for thereasoning process giving through the calculation of the possibilities of allpossible individuals' profiles a quantitative/qualitative view of theirbehaviour during the above process and we use the centroid defuzzificationtechnique for measuring the reasoning skills. We also present a number ofclassroom experiments illustrating our results in practice.
Fuzziness and randomicity widespread exist in natural science, engineering,technology and social science. The purpose of this paper is to present a newlogic - uncertain propositional logic which can deal with both fuzziness bytaking truth value semantics and randomicity by taking probabilistic semanticsor possibility semantics. As the first step for purpose of establishing a logicsystem which completely reflect the uncertainty of the objective world, thislogic will lead to a set of logical foundations for uncertainty theory as whatclassical logic done in certain or definite situations or circumstances.
Fuzzy clustering methods identify naturally occurring clusters in a dataset,where the extent to which different clusters are overlapped can differ. Mostmethods have a parameter to fix the level of fuzziness. However, theappropriate level of fuzziness depends on the application at hand. This paperpresents Entropy $c$-Means (ECM), a method of fuzzy clustering thatsimultaneously optimizes two contradictory objective functions, resulting inthe creation of fuzzy clusters with different levels of fuzziness. This allowsECM to identify clusters with different degrees of overlap. ECM optimizes thetwo objective functions using two multi-objective optimization methods,Non-dominated Sorting Genetic Algorithm II (NSGA-II), and MultiobjectiveEvolutionary Algorithm based on Decomposition (MOEA/D). We also propose amethod to select a suitable trade-off clustering from the Pareto front.Experiments on challenging synthetic datasets as well as real-world datasetsshow that ECM leads to better cluster detection compared to the conventionalfuzzy clustering methods as well as previously used multi-objective methods forfuzzy clustering.