Application loader in the RW. Ring platform

When developing decision support systems in agriculture, the task often arises of creating applications that include a large number of different components. These components can have dependencies on each other, so you need to load them in the correct order. This boils down to solving the classic topological sorting problem. However, in addition to the purely algorithmic part, the loader must correctly interact with the environment, which poses a large number of other technology-specific tasks for its developer. These are the tasks of obtaining and storing information about dependencies, ensuring that components are loaded in the user interface thread where necessary, as well as ensuring the most responsive program behavior so that loading an application does not annoy the user, as well as ensuring the extensibility of the decision support system without recompiling. This work is devoted to the description of the solution of these problems in the RW.Ring platform based on the .NET technological stack and intended for the development of such software systems.

A method for transformation from dynamic fault tree to binary decision diagram

Dynamic fault tree (DFT) is a powerful modeling approach for reliability analysis of complex system with dynamic failure behaviors. In reality, the tree structure may be highly coupled either by shared basic events or by the high-level dynamic gates. Currently, the application of sequential binary decision diagram (SBDD)-based method for quantitative analysis of such highly coupled DFTs is mainly limited to DFTs whose dynamic gates locate in the bottom of the tree. Moreover, there is no efficient way dealing with the dependencies among different nodes of a SBDD 1-path. This paper makes an improvement to the SBDD-based approach. A generation procedure is proposed to directly construct the binary decision diagram (BDD) model for a DFT with arbitrary tree structure. During the construction, the sequential-dependent information of the tree is derived as several BDD nodes, each indicates a binary-sequential event representing the sequence of two occurred basic events. A topological sorting is applied on each 1-path of the resultant BDD to obtain its contained disjoint cut sequences. Based on this, both qualitative and quantitative analysis can be performed on the DFT with no limitations on tree structure, and its minimal cut sequence set (CSS) is obtained as disjoint. Examples are provided for verification and comparison, and the results illustrate the merits of the proposed approach.

TOPOLOGICAL APPROACH TO BLACKHOLES ANOMALY DETECTION IN DIRECTED NETWORKS

In this paper we consider the problem of finding a blackhole pattern in directed unweighted graphs. The problem statement is the same as in an original paper by scientists from University of New-Jersey published in 2010. The paper contributes to the special graph pattern matching, the work results can be used for anomaly detection in finances, natural disasters, urban analysis. This paper aims to propose a novel algorithm for blackhole mining, which would take into account inner structure of the “blackhole” pattern and utilize this knowledge for more efficient mining. This paper reviews previously published solutions and tests them on larger graphs containing up to 1 million of nodes. In particular, an iBlackhole algorithm and its Divide and Conquer modification iBlackholeDC are considered, their weak spots are highlighted and reviewed upon. Graph condensation is introduced as an efficient preprocessing for the problem. This paper provides theorems and definitions describing inner structure of the blackhole pattern. Based on the new theorems, a new approach to enumeration of candidates is introduced as well as rules and heuristics aiming for faster filtration of candidates: they utilize topological sorting of a graph and definition of a “special” node, which is also introduced in this paper. Special nodes properties are described. We propose a novel TopSortBH algorithm. It consists of the graph condensation, candidates enumeration and heuristics for candidates filtration. The algorithm is provided with modification called FastSkip, which allows for more aggressive filtering strategy in time-sensitive cases. All mentioned algorithms are implemented and tested on the IBM Power8 based system. Experimental results show efficiency of the condensation as graph preprocessing for the problem. Strong advantage in found blackholes count is demonstrated for TopSortBH in comparison to iBlackholeDC on RMAT, SSCA2 and UR graphs containing up to 1 million nodes.