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Bukowski L.A.,Business Center Poland
International Conference on Industrial Logistics, ICIL 2014 - Conference Proceedings | Year: 2014

Supply chain risk can be seen as any event that might affect continuity of materials and information flow. The risks within the supply chain occur when unexpected events disrupt the flow of materials on their way from initial suppliers to the final customers. In the broad perspective risk exists as a concept embracing two major components: consequences of an activity and associated with it uncertainties. The objective of this paper is to come up with a new framework of disruption risk management for the global supply networks. The core idea of the overall concept is based on the transdisciplinary approach. Copyright © FSB, Zagreb, Croatia, 2014. Source


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Communications in Computer and Information Science | Year: 2011

The aim of this paper is to investigate, formulate, and analyse the general rules and principles that govern the evolution of key factors that influence the development of decision support systems (DSS) and models. In order to ela borate a model suitable for medium-term forecasts and recommendations, we have defined eight major elements of Information Society that characterise the evolution of the corresponding digital economy. The evolution of the overall system is described by a discrete-continuous-event system, where the mutual impacts of each of the elements are represented within state-space models. Technological trends and external economic decisions form inputs, while feedback loops allow us to model the influence of technological demand on IT, R&D, production, and supply of DSS. The technological characteristics of the product line evolution modelled in this way can provide clues to software providers about future demand. They can also give R&D and educational institutions some idea on the most likely directions of develop¬ment and demand for IT professionals. As an example, we will model the evolution of decision-support systems and recommenders for 3D-internet-based e-commerce, and their impact on technological progress, consumption patterns and social behaviour. The re sults presented here have been obtained during an IS/IT foresight project carried out in Poland since 2010 and financed by the ERDF. © 2011 Springer-Verlag. Source


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

This paper presents the theoretical foundations of an intelligent on-line modelling tool capable of processing heterogeneous information on complex techno-economical systems. Its main functionality is to investigate, elicit, and apply rules and principles that govern the development processes of technologies and related markets. Specifically, we will focus on applications of the tool to model the evolution of information technology (IT). We will distinguish several relevant subsystems of the system under study, which describe the demographic, education, global economic trends, as well as specific market factors that determine the demand for and use of IT. The group modelling techniques are implemented in the new tool to enable the collaborative and distributed model building with intelligent verification of entries called 'model wiki'. Based on the information elicited from experts, gathered from the web and professional databases, a discrete-time control model of technological evolution emerges, coupled with a controlled discrete-event system. The latter processes qualitative information and models the influence of external events and trends on the discrete-time control system parameters. We propose novel uncertainty handling techniques capable of processing and combining different types of uncertain information, coming i.a. from Delphi research and forecasts. The quantitative information is dynamically updated by autonomous webcrawlers, following an adaptive intelligent strategy. The resulting model can be used to simulate long-term future trends and scenarios. Its ultimate goal is to perform an optimization process and derive recommendations for decision makers, for example when selecting IT investment strategies in an innovative enterprise. © 2012 Springer-Verlag. Source


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI | Year: 2015

Numerous attempts have been made to assess the complexity and predictability of a time series. In AI applications, the latter may be used to determine or classify the origin of an unknown signal. This paper presents the theoretical background to an empirical time series analysis methodology based on the monotonic aggregation transform. For any given time series, its extrema are assumed to contain more information than intermediate data, which is supported empirically for long-memory financial and technological data. Based on this assumption, properties of k-th order minima and maxima are studied as well as their mutual relations. The latter have allowed us to construct a binary decomposition tree and an extremal hull of a time series observation set. It will be proven that the natural characteristic of decomposition trees can be interpreted as an entropy function of the corresponding observation set. Furthermore, the maximum height as well as the sum of all node orders of a decomposition tree is a measure of its information contents. When considered as a function of a sliding time window of constant length in a stationary time series, the above characteristics give us clues as regards the predictability of the original time series, its differences or integrands. We will show the practical implications of the above method in analyzing various kinds of temporal data. © 2014 IEEE. Source


Skulimowski A.M.J.,AGH University of Science and Technology | Skulimowski A.M.J.,Business Center Poland
Advances in Intelligent Systems and Computing | Year: 2016

This paper presents a methodological background and selected final results of a foresight project concerning the role of creativity in the development of intelligent decision technologies. Technological trends and scenarios have been generated via a simulation of a hybrid system consisting of discrete-time control and discrete-event components. Both form a complex information society model, which describes the evolution of social, economic and scientific factors relevant to the production and adoption of intelligent technologies. The trends and scenarios derived are then discussed and refined during cooperative expert activities. Specifically, we have investigated the development of intelligent decision technologies, with special attention paid to web-based decision support systems, neurocognitive and autonomous systems, as well as artificial creativity aspects. The overall project is outlined in Sect. 2. In Sect. 3, we will present selected trends related to the development of creative technologies in the context of overall progress in information and communication technologies (ICT) and computer science (CS). The discussion of the future role of creativity in the design and implementation of intelligent systems is based on the results of a Delphi study carried out within the recent foresight project SCETIST. © Springer International Publishing Switzerland 2016. Source

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