The model of surface subsidence process at subsidence through formation

The character of surface subsidence is different and has its peculiarities at different stages of mining operations. The process of surface subsidence is especially different in the initial period of mining lava comparing with other stages of mining development. The simple graphical model of subsidence is created. This model allows determining the value of subsidence at any point of the earth's surface at any given time. The model is implemented on the basis of contour lines. To construct the trough model the data of instrumental measurements on core lines are used. This “chrono-isoline” model of subsidence trough allows predicting the trough profile and subsidence of individual points on the surface. There is no need to perform complex mathematical calculations. The solution of the problem requires a minimum of input data: the depth of the excavation of a long pillar and its size of a specific date

The model of surface subsidence process at subsidence through formation

The character of surface subsidence is different and has its peculiarities at different stages of mining operations. The process of surface subsidence is especially different in the initial period of mining lava comparing with other stages of mining development. The simple graphical model of subsidence is created. This model allows determining the value of subsidence at any point of the earth's surface at any given time. The model is implemented on the basis of contour lines. To construct the trough model the data of instrumental measurements on core lines are used. This “chrono-isoline” model of subsidence trough allows predicting the trough profile and subsidence of individual points on the surface. There is no need to perform complex mathematical calculations. The solution of the problem requires a minimum of input data: the depth of the excavation of a long pillar and its size of a specific date

Mutual-Excitation of Cryptocurrency Market Returns and Social Media Topics

Cryptocurrencies have recently experienced a new wave of price volatility and interest; activity within social media communities relating to cryptocurrencies has increased significantly. There is currently limited documented knowledge of factors which could indicate future price movements. This paper aims to decipher relationships between cryptocurrency price changes and topic discussion on social media to provide, among other things, an understanding of which topics are indicative of future price movements. To achieve this a well-known dynamic topic modelling approach is applied to social media communication to retrieve information about the temporal occurrence of various topics. A Hawkes model is then applied to find interactions between topics and cryptocurrency prices. The results show particular topics tend to precede certain types of price movements, for example the discussion of 'risk and investment vs trading' being indicative of price falls, the discussion of 'substantial price movements' being indicative of volatility, and the discussion of 'fundamental cryptocurrency value' by technical communities being indicative of price rises. The knowledge of topic relationships gained here could be built into a real-time system, providing trading or alerting signals.Comment: 3rd International Conference on Knowledge Engineering and Applications (ICKEA 2018) - Moscow, Russia (June 25-27 2018

A Regularized Graph Layout Framework for Dynamic Network Visualization

Many real-world networks, including social and information networks, are dynamic structures that evolve over time. Such dynamic networks are typically visualized using a sequence of static graph layouts. In addition to providing a visual representation of the network structure at each time step, the sequence should preserve the mental map between layouts of consecutive time steps to allow a human to interpret the temporal evolution of the network. In this paper, we propose a framework for dynamic network visualization in the on-line setting where only present and past graph snapshots are available to create the present layout. The proposed framework creates regularized graph layouts by augmenting the cost function of a static graph layout algorithm with a grouping penalty, which discourages nodes from deviating too far from other nodes belonging to the same group, and a temporal penalty, which discourages large node movements between consecutive time steps. The penalties increase the stability of the layout sequence, thus preserving the mental map. We introduce two dynamic layout algorithms within the proposed framework, namely dynamic multidimensional scaling (DMDS) and dynamic graph Laplacian layout (DGLL). We apply these algorithms on several data sets to illustrate the importance of both grouping and temporal regularization for producing interpretable visualizations of dynamic networks.Comment: To appear in Data Mining and Knowledge Discovery, supporting material (animations and MATLAB toolbox) available at http://tbayes.eecs.umich.edu/xukevin/visualization_dmkd_201

Are foreign currency markets interdependent? evidence from data mining technologies

This study uses two data mining methodologies: Classification and Regression Trees (C&RT) and Generalized Rule Induction (GRI) to uncover patterns among daily cash closing prices of eight currency markets. Data from 2000 through 2009 is used, with the last year held out to test the robustness of the rules found in the previous nine years. Results from the two methodologies are contrasted. A number of rules which perform well in both the training and testing years are discussed as empirical evidence of interdependence among foreign currency markets. The mechanical rules identified in this paper can usefully supplement other types of financial modeling of foreign currencies.Foreign Currency Markets