Seed Selection for Spread of Influence in Social Networks: Temporal vs. Static Approach

The problem of finding optimal set of users for influencing others in the social network has been widely studied. Because it is NP-hard, some heuristics were proposed to find sub-optimal solutions. Still, one of the commonly used assumption is the one that seeds are chosen on the static network, not the dynamic one. This static approach is in fact far from the real-world networks, where new nodes may appear and old ones dynamically disappear in course of time. The main purpose of this paper is to analyse how the results of one of the typical models for spread of influence - linear threshold - differ depending on the strategy of building the social network used later for choosing seeds. To show the impact of network creation strategy on the final number of influenced nodes - outcome of spread of influence, the results for three approaches were studied: one static and two temporal with different granularities, i.e. various number of time windows. Social networks for each time window encapsulated dynamic changes in the network structure. Calculation of various node structural measures like degree or betweenness respected these changes by means of forgetting mechanism - more recent data had greater influence on node measure values. These measures were, in turn, used for node ranking and their selection for seeding. All concepts were applied to experimental verification on five real datasets. The results revealed that temporal approach is always better than static and the higher granularity in the temporal social network while seeding, the more finally influenced nodes. Additionally, outdegree measure with exponential forgetting typically outperformed other time-dependent structural measures, if used for seed candidate ranking.     

Upgrading a Granular Computing Based Data Mining Framework to a Relational Case

One of the popular methods to develop an algorithm for mining data stored in a relational structure is to upgrade an existing attribute‐value algorithm to a relational case. Current approaches to this problem have some shortcomings such as (1) a dependence on the upgrading process of the algorithm to be extended, (2) complicated redefinitions of crucial notions (e.g., pattern generality, pattern refinement), and (3) a tolerant limitation of the search space for pattern discovery. In this paper, we propose and evaluate a general methodology for upgrading a data mining framework to a relational case. This methodology is defined in a granular computing environment. Thanks to our relational extension of a granular computing based data mining framework, the three above problems can be overcome.     

Selective oxidation of ammonia to nitrogen on transition metal containing mixed metal oxides

The selective catalytic oxidation of ammonia to nitrogen (NH₃-SCO) has been studied over hydrotalcite derived mixed metal oxides containing Cu, Co, Fe or Ni. XRD, BET, NH₃-TPD and TPR techniques were used for catalysts characterization. Results of NH₃-SCO were compared with those of selective catalytic reduction of NO with NH₃ (NO-SCR). Reaction mechanism was studied by temperature-programmed surface reaction (TPSR) and activity tests with a various contact time. Catalytic performance of the studied samples depends on both kind and loading of transition metals in the mixed metal oxide system. The Cu-containing samples have been found to be the most active catalysts of the NH₃-SCO process. Transition metal loading strongly influences distribution of ammonia oxidation products. The highest selectivity to N₂ was measured for the catalysts with the lowest transition metal content.     

Effect of Mode of Drying on Microstructure of Potato

Potato v. Irga was subjected to blanching, and thereafter was dried by convection, puff-drying, and freeze-drying. Microstructure of raw, blanched, and dried tissue was analyzed under the light microscope using computer image analysis. It was found that the tissue of the investigated variety is built up from cells much smaller than those described in literature for other cultivars. Blanching caused starch gelatinization and increase of cross-sectional area of cells. There was no evidence of broken cell walls. Convective drying resulted in cell shrinkage and some breaking of cell walls. It was estimated that some 12% of cells lost integrity during drying. Limited disintegration of the tissue caused by convective drying is attributed to small size of cells, large contact area, and high cohesive forces between cells. Puff-drying damaged the tissue much more than the convective drying. The most devastating to tissue microstructure was freeze-drying, probably freezing per se.     

On the Computational Complexity of Measuring Global Stability of Banking Networks

Threats on the stability of a financial system may severely affect the functioning of the entire economy, and thus considerable emphasis is placed on the analyzing the cause and effect of such threats. The financial crisis in the current and past decade has shown that one important cause of instability in global markets is the so-called financial contagion, namely the spreadings of instabilities or failures of individual components of the network to other, perhaps healthier, components. This leads to a natural question of whether the regulatory authorities could have predicted and perhaps mitigated the current economic crisis by effective computations of some stability measure of the banking networks. Motivated by such observations, we consider the problem of defining and evaluating stabilities of both homogeneous and heterogeneous banking networks against propagation of synchronous idiosyncratic shocks given to a subset of banks. We formalize the homogeneous banking network model of Nier et al. (J. Econ. Dyn. Control 31:2033–2060, 2007) and its corresponding heterogeneous version, formalize the synchronous shock propagation procedures outlined in (Nier et al. J. Econ. Dyn. Control 31:2033–2060, 2007; M. Eboli Mimeo, 2004), define two appropriate stability measures and investigate the computational complexities of evaluating these measures for various network topologies and parameters of interest. Our results and proofs also shed some light on the properties of topologies and parameters of the network that may lead to higher or lower stabilities.     

Unsteady radiative heat transfer within a suspension of ZnO particles undergoing thermal dissociation

An emitting, absorbing, and anisotropically scattering plain medium containing a suspension of ZnO particles is considered, in which the particles are directly exposed to high-flux irradiation and undergo shrinkage during their endothermic dissociation into Zn(g) and O₂ at above 2100 K. The unsteady energy equation that links the rate of radiative heat transfer to the rate of the chemical reaction is formulated and solved numerically by the finite volume technique and the explicit Euler time-integration scheme. The path-length Monte Carlo method is applied for modeling the radiative transfer within the suspension using the absorption/scattering coefficients and the scattering phase function obtained from the Mie theory. It is found that the particle suspension can be heated rapidly from its initial 300 K to over 1800 K in less than 0.1 s, resulting in a more uniform temperature profile as the reaction progresses, particles shrink, and the suspension becomes optically thinner. The chemical conversion increases with decreasing initial particle diameter and volume fraction due to the efficient radiative absorption.     

New method for the on-line signature verification based on horizontal partitioning

Verification of identity based on the analysis of dynamic signatures is an important problem of biometrics. The effectiveness of the verification significantly increases when the dynamic characteristics of signature (e.g. velocity of the pen) are considered. These characteristics are individual for each user and difficult to imitate. The effectiveness of the verification can be further improved by using partitioning. In this paper we propose a new method which uses partitioning. In our method partitions represent areas of high and low speed of signature and high and low pen?s pressure. All selected partitions are used by our algorithm, but more important in the classification process are these partitions, in which the signatures of the user acquired during training phase are more stable. Moreover, final classification is interpretable. In this paper we present the simulation results of the proposed method for the two databases: SVC2004 and BioSecure Database.     

Ionic liquids as electrolytes

Salts having a low melting point are liquid at room temperature, or even below, and form a new class of liquids usually called room temperature ionic liquids (RTIL). Information about RTILs can be found in the literature with such key words as: room temperature molten salt, low-temperature molten salt, ambient-temperature molten salt, liquid organic salt or simply ionic liquid. Their physicochemical properties are the same as high temperature ionic liquids, but the practical aspects of their maintenance or handling are different enough to merit a distinction. The class of ionic liquids, based on tetraalkylammonium cation and chloroaluminate anion, has been extensively studied since late 1970s of the XX century, following the works of Osteryoung. Systematic research on the application of chloroaluminate ionic liquids as solvents was performed in 1980s. However, ionic liquids based on aluminium halides are moisture sensitive. During the last decade an increasing number of new ionic liquids have been prepared and used as solvents. The general aim of this paper was to review the physical and chemical properties of RTILs from the point of view of their possible application as electrolytes in electrochemical processes and devices. The following points are discussed: melting and freezing, conductivity, viscosity, temperature dependence of conductivity, transport and transference numbers, electrochemical stability, possible application in aluminium electroplating, lithium batteries and in electrochemical capacitors.     

Monte Carlo simulation of radiation-induced solid state polymerization

A Monte Carlo method was used for a computer simulation of radiation-induced solid state polymerization. The propagation of polymer chains was simulated by means of self-avoiding random walks on a tetrahedral lattice. The initiation and termination of the chains were modelled by pseudorandom processes. The influence of conditions of the in-source process on the post-polymerization kinetics and on the degree of polymerization of the polymers was studied.