Journal of Automation, Mobile Robotics & Intelligent Systems. 2018, Vol. 12 Issue 2, p61-81. 21p.
GRAPH grammars and PATTERN perception
Further results of research into parsable graph grammars used for syntactic pattern recognition (Pattern Recognition: 21, 623-629 (1988); 23, 765-774 (1990); 24, 12-23 (1991); 26, 1-16 (1993); 43, 2249-2264 (2010), Com put. Vision Graph. Image Process. 47, 1-21 (1989), Computer-Aided Design 27, 403-433 (1995), Theoret. Comp. Sci. 201, 189-231 (1998), Pattern Analysis Applications bf 17, 465-480 (2014)) are presented in the paper. The generative power of reduction-based parsable ETPR(k) graph grammars is investigated. The analogy between the triad ofCF- LL(k) - LR(k) string languages and the triad ofNLC - ETPL(k) - ETPR(k) graph languages is discussed. [ABSTRACT FROM AUTHOR]
Flasiński,, Mariusz, Flasiński,, Piotr, and Konduracka, Ewa
Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. 2013, p591-599.
On the Use of Programmed Automata for a Verification of ECG Diagnoses The recent results into constructing a formal model of a syntactic pattern recognition-based System for Teaching ElectroCardioGraphy (STECG) [...]
A research into a syntactic pattern recognition model based on (edNLC) graph grammars (introduced and investigated in Janssens and Rozenberg Inform. Sci. 20 (1980), 191-216, and Janssens, Rozenberg and Verraedt Comp. Vis. Graph. Image Process. 18 (1982), 279-304) has resulted in defining the efficient, O(n^2), parsing schemes for the ETPL(k) subclass of these grammars and applying it for scene analysis, CAD/CAMobject analysis and constructingAI systems (Flasiński Patt. Recogn. 21 (1988), 623-629, Flasiński Comp. Vis. Graph. Image Process. 47 (1989), 1-21, Flasiński Patt. Recogn. 26 (1993), 1-16, Flasiński Comp. Aided-Des. 27 (1995), 403-433, Flasiński Theor. Comp. Sci. 201 (1998), 189-231). In the paper the grammatical inference method for the parsable ETPL(k) graph grammars is defined, completing the development of this syntactic pattern recognition model. [ABSTRACT FROM AUTHOR]
Business Processes, Graph Grammars, and ERP Systems
Methods of ERP (Enterprise Resource Planning) systems modelling are presented in the paper. The modelling is necessary to adapt and ERP system to a company in such a way, that it fully supports a management at the operational level, i.e. it supports the business processes in the best possible way. The choice of methods (business process and graph grammarbased)described in the paper is based on the authors’ experiences in several dozen of implementation projects, realized in large Polish enterprises. Themethods can be used to select the best ERP system for a company, to designits implementation, and to customize the system accordingly to the requirementsof a company.