Informatica

Experience shows that Agile project management tools such as Atlassian Jira capture the state of EAS projects by relying solely on expert judgement that is not supported by any knowledge model. Therefore, the assessment of project content against strategic objectives and business domain features are not supported by any tool. This is one of the reasons why Agile project management still does not provide sufficient EAS project delivery results. In order to address this problem, the Enterprise Application Software (EAS) development using Agile project management is summarized in a conceptual model. The model highlights the knowledge used and indicates its nature (empirical or causal digitized). The modified Agile management process we have developed and described in previous works is based on causal knowledge models that supports EAS development and Agile management processes. The purpose of this article is to specify knowledge repository to ensure the Agile management solutions of an EAS project are aligned with strategic goals and business domain causality. It is worth noticing that strategic goals have been identified and specified as capabilities using some enterprise architecture framework (NAF, MODAF, ArchiMate, etc.). The novelty of the proposed method is incorporating the business domain causal knowledge modelling approach into the Agile project management process. The causal knowledge unit is considered as a Management Transaction (MT), which includes closed loop dependence of its components. The modified Agile activity hierarchy (theme, initiative, epic, user story) defines the required content of their mutual interactions. An important new results obtained are the conceptual model of causal knowledge base (KB) and specification of enhanced Agile management tool components: project management database and project state assesment knowledge base. Causal KB includes specification of causal knowledge unit (MT metamodel) and specifications of traditional and causal Agile hierarchy meta-models. These conceptual models define the causal knowledge components necessary to evaluate the state of Agile activities in the EAS development project using intelligent Agile project management tool.

The paper deals with the intelligent functional model for optimizing the product design and its manufacturing process in hybrid manufacturing systems consisting of people, machines and computers. The knowledge‐based framework of an intelligent functional model has been developed. It furnishes the possibility for a product designer and manufacturer to find an optimal production plan in the early stage of the product design. The mathematical model formalization is provided. A consecutive optimization scheme has been applied for selecting an optimal alternative of a product design and its production plan. The proposed model is being implemented both in industry and university education process.

The paper presents a technique that defines creation of ESTELLE/Ag specifications using knowledge bases (KB). Application KB is created using the knowledge acquisition technique joined with a piece‐linear aggregate model. The production rules of the application KB are transformed to decision tables, and the static properties of the KB are checked in PROLOGA system. Further, the application KB is combined with the defined KB of validated properties and validation method, and application KB dynamic properties are checked in the expert system in CLIPS. A validated application KB is used defining a framework of ESTELLE/Ag specification using PRAXIS editor and supplementing PRAXIS generated framework with the application functional description. The technique is illustrated with an example of a single channel queuing system.

The paper deals with the analysis of Research and Technology Development (RTD) in the Central European countries and the relation of RTD with economic and social parameters of countries in this region. A methodology has been developed for quantitative and qualitative ranking and estimates of relationship among multidimensional objects on the base of such analysis. The knowledge has been discovered in four databases: two databases of European Commission (EC) containing data on the RTD activities, databases of USA CIA and The World bank containing economic and social data. Data mining has been performed by means of visual cluster analysis (using the non-linear Sammon's mapping and Kohonen's artificial neural network – the self-organising map), regression analysis and non-linear ranking (using graphs of domination). The results on clustering of the Central European countries and on the relations among RTD parameters with economic and social parameters are obtained. In addition, the data served for testing various features of realisation of the self-organising map. The integration of non-classical methods (the self-organising map and graphs of domination) with classical ones (regress analysis and Sammon' mapping) increases the capacity of visual analysis and allows making more complete conclusions.

A multiextremal problem on the synthesis of external circuit of a tunable subnanosecond pulse TRAPATT-generator was investigated using algorithms of local optimization and cluster analysis.