KINETIC FEATURES OF THE DISSOCIATION PROCESS OF GAS HYDRATE DEPOSITS

The research is aimed at revealing the theoretical features of the kinetics of the process of dissociation of natural gas hydrates, the accounting of which is useful in designing technologies for their development. The process of decomposition of gas hydrates is considered as a heterogeneous process, proceeding at the interface of the phases and contains three consecutive stages. The mathematically grounded speed with which molecules fluctuate around fixed positions and the velocity of their translational motion in the system “gas – rock environment”. The mathematical expression of the constant coefficient of molecular diffusion is made. It has been established that when gas is extracted from gas hydrates, external and internal diffusion zones, as well as diffusion inhibition, are caused, which causes an increase in the decay time of gas hydrate to gas and water. The character of the dependence of the change in the rate of dissociation during its various periods is revealed. It was found that the speed of the dissociation process in these conditions varies with the temperature under the exponential la

Optimizing Associative Information Transfer within Content-addressable Memory

Original article can be found at: http://www.oldcitypublishing.com/IJUC/IJUC.htmlPeer reviewe

Numerical simulation of spacecraft charging phenomena

A numerical simulation program is being constructed having the following features: (1) infinite circular cylindrical geometry with angle-dependence, (2) inclusion of incident particles, photoelectrons, secondary electrons, backscattered electrons, any gun emissions, and any internal current pathways including surface conductive layers, (3) quasistatic time-dependent iteration, in which sheath potential changes during particle transit times are ignored, (4) use of approximate, locally-dependent space charge density expressions in solving Poisson's equation for sheath potentials, with use of numerical orbit-following to determine surface currents, and (5) incident particle velocity distributions isotropic or beam-like, or some superposition of these. Rationales for each of these features are discussed

Prediction of large negative shaded-side spacecraft potentials

A calculation by Knott, for the floating potential of a spherically symmetric synchronous-altitude satellite in eclipse, was adapted to provide simple calculations of upper bounds on negative potentials which may be achieved by electrically isolated shaded surfaces on spacecraft in sunlight. Large (approximately 60 percent) increases in predicted negative shaded-side potentials are obtained. To investigate effective potential barrier or angular momentum selection effects due to the presence of less negative sunlit-side or adjacent surface potentials, these expressions were replaced by the ion random current, which is a lower bound for convex surfaces when such effects become very severe. Further large increases in predicted negative potentials were obtained, amounting to a doubling in some cases

Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks

A number of centrality measures are available to determine the relative importance of a node in a complex network, and betweenness is prominent among them. However, the existing centrality measures are not adequate in network percolation scenarios (such as during infection transmission in a social network of individuals, spreading of computer viruses on computer networks, or transmission of disease over a network of towns) because they do not account for the changing percolation states of individual nodes. We propose a new measure, percolation centrality, that quantifies relative impact of nodes based on their topological connectivity, as well as their percolation states. The measure can be extended to include random walk based definitions, and its computational complexity is shown to be of the same order as that of betweenness centrality. We demonstrate the usage of percolation centrality by applying it to a canonical network as well as simulated and real world scale-free and random networks. © 2013 Piraveenan et al.published_or_final_versio

Gliders2d: Source Code Base for RoboCup 2D Soccer Simulation League

We describe Gliders2d, a base code release for Gliders, a soccer simulation team which won the RoboCup Soccer 2D Simulation League in 2016. We trace six evolutionary steps, each of which is encapsulated in a sequential change of the released code, from v1.1 to v1.6, starting from agent2d-3.1.1 (set as the baseline v1.0). These changes improve performance by adjusting the agents' stamina management, their pressing behaviour and the action-selection mechanism, as well as their positional choice in both attack and defense, and enabling riskier passes. The resultant behaviour, which is sufficiently generic to be applicable to physical robot teams, increases the players' mobility and achieves a better control of the field. The last presented version, Gliders2d-v1.6, approaches the strength of Gliders2013, and outperforms agent2d-3.1.1 by four goals per game on average. The sequential improvements demonstrate how the methodology of human-based evolutionary computation can markedly boost the overall performance with even a small number of controlled steps.Comment: 12 pages, 1 figure, Gliders2d code releas

Local information transfer as a spatiotemporal filter for complex systems

We present a measure of local information transfer, derived from an existing averaged information-theoretical measure, namely transfer entropy. Local transfer entropy is used to produce profiles of the information transfer into each spatiotemporal point in a complex system. These spatiotemporal profiles are useful not only as an analytical tool, but also allow explicit investigation of different parameter settings and forms of the transfer entropy metric itself. As an example, local transfer entropy is applied to cellular automata, where it is demonstrated to be a novel method of filtering for coherent structure. More importantly, local transfer entropy provides the first quantitative evidence for the long-held conjecture that the emergent traveling coherent structures known as particles (both gliders and domain walls, which have analogues in many physical processes) are the dominant information transfer agents in cellular automata.Comment: 12 page

Minimising the kullback-leibler divergence for model selection in distributed nonlinear systems

© 2018 by the authors. The Kullback-Leibler (KL) divergence is a fundamental measure of information geometry that is used in a variety of contexts in artificial intelligence. We show that, when system dynamics are given by distributed nonlinear systems, this measure can be decomposed as a function of two information-theoretic measures, transfer entropy and stochastic interaction. More specifically, these measures are applicable when selecting a candidate model for a distributed system, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic graph (DAG) that characterises the unidirectional coupling between subsystems. Standard approaches to structure learning are not applicable in this framework due to the hidden variables; however, we can exploit the properties of certain dynamical systems to formulate exact methods based on differential topology. We approach the problem by using reconstruction theorems to derive an analytical expression for the KL divergence of a candidate DAG from the observed dataset. Using this result, we present a scoring function based on transfer entropy to be used as a subroutine in a structure learning algorithm. We then demonstrate its use in recovering the structure of coupled Lorenz and Rössler systems

Numerical Modelling of Whispering Gallery Modes in Parallel-plates Type Cylindrical Anisotropic Dielectric Resonators

A parallel-plates-type cylindrical anisotropic dielectric resonator (DR) with whispering gallery modes (WGMs) has been investigated. Numerical modelling of the resonance frequencies, Q-factors and the electric field filling factors of the isotropic and anisotropic DR are presented. Applications of the results for sensing purposes are discussed

Inferring Coupling of Distributed Dynamical Systems via Transfer Entropy

In this work, we are interested in structure learning for a set of spatially distributed dynamical systems, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic graph (DAG) that characterises the unidirectional coupling between subsystems. Standard approaches to structure learning are not applicable in this framework due to the hidden variables, however we can exploit the properties of certain dynamical systems to formulate exact methods based on state space reconstruction. We approach the problem by using reconstruction theorems to analytically derive a tractable expression for the KL-divergence of a candidate DAG from the observed dataset. We show this measure can be decomposed as a function of two information-theoretic measures, transfer entropy and stochastic interaction. We then present two mathematically robust scoring functions based on transfer entropy and statistical independence tests. These results support the previously held conjecture that transfer entropy can be used to infer effective connectivity in complex networks