The rapid advancement in information and communication technologies (ICTs) has brought enormous business opportunities as well as challenges. One of these challenges is the demand for ICTs skills and expertise in adopting and implementing these emerging technologies. Coping with skills shortage poses a serious challenge across all European countries. Lack of ICTs skills and knowledge is more evident in small-and medium-sized enterprises (SMEs). As training is regarded as the most effective way of improving skills and enhancing knowledge, this paper attempts to address skills shortage at pan-European level by identifying SMEs' needs on ICTs training in the UK, Portugal and Poland. The investigation focuses on the most needed training areas, the required training levels and the preferred training delivery channels. The paper summarises findings from three-country investigations and highlights the implications of findings for the design and development of a Web-based training system for the use of ICTs in SMEs.

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The explosive growth of the Big Data concept and its applications in multiple domains of human activity has increased interest in the benefits it could offer to public services. The paper seeks to emphasise the added value that stems from the use of Big Data in handling heterogeneous data sources accessed by crisis management structures. Authors wants to highlight the ways in which the concept could support decision makers during the crisis management process by showing two cases. First authors' own creation known as Hybrid Decision Support System for Crisis/Disaster Management. Second, showing application of Big Data in security management to illustrate the implications of using Big Data in practice. In case of that the Big Data is a term that is vendor driven and creates more confusing than clarity author's conclusion brings together critical observations and judgments voiced in the paper using SWOT analysis toll and providing a blueprint for further development of the concept of Big Data in the area of Crisis/Disaster management.

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The present paper deals with selected aspects of energy prosumers’ security needs. The analysis reported aim to illustrate the concept of the implementation of intrusion-detection systems (IDS)/intrusion-prevention systems (IPS), as supporting agent systems for smart grids. The contribution proposes the architecture of an agent system aimed at collecting, processing, monitoring, and possibly reacting to changes in the smart grid. Furthermore, an algorithm is proposed to support the construction of a smart-grid-operating profile, based on a set of parameters describing the devices. Its application is presented in the example of data collected from the network, indicating the process of building a device-operation profile and a possible mechanism for detecting its changes. The proposed algorithm for building the operating profile of devices in the smart grid, based on the mechanism of continuous learning by the system, allows for detecting network malfunctions not only in terms of individual events but also regarding limits of the scope of system alerts, by determining the typical behavior of devices in the smart grid. The paper gives recommendations to a software-agent system development, which is dedicated to detecting and preventing anomalies in smart grids.

Abstract-The paper sets out from a proposition that the concept of Case Based Reasoning could improve business decisions and optimize case processing in modern Adaptive Case Management (ACM) systems. While depicting the state of the art in the continued efforts to blend Artificial Intelligence (AI) with Business Process Management (BPM), Knowledge Management (KM) and Adaptive Case Management, the authors take notice of how the classical ACM platform has recently been evolving. The dynamic and adaptive nature of some business processes poses challenges that the classical BPM approach cannot adequately address. Adaptive Case Management has been developed to better cope with such challenges. ACM not only makes it easier to align a business to rapidly changing requirements and conditions, but it also enables organizations to more effectively exploit the potential inherent in the organizational knowledge and information resources. The paper discusses the evolution of ACM systems and proposes to apply Case Based Reasoning (naturally coupled with AI) in optimizing ACM outcomes. I. INTRODUCTIONcompletely new approach employing the existing ACM tools and the Case Based Reasoning model has been developed to address the problem of decision support within business case processing. The idea involves integrating the Case Based Reasoning method into Adaptive Business Case Management.This paper describes an approach that is founded on the application of Case Based Reasoning to deploy decision support and was preceded by a literature based discussion on Artificial Intelligence (i.e. the CBR method) and its application to support Adaptive Business Case Management. Attention is focused on ACM and CBR, with an aim to provide a complete theoretical framework for reflection on their proposed integration and for applying the integrated methods to exploring a set of business problem solutions.The paper advances and investigates the following theses: a) The Case Based Reasoning method may be used to support ACM by providing faster access to the information needed to make business decisions. b) Supporting ACM with Case Based Reasoning makes the process of exploring a set of business problem solutions faster and more effective.The paper deals with the application of the Case Based Reasoning method in supporting the ACM method. Case Based Reasoning (CBR) is an artificial intelligence method based on reusing the outcomes of previously solved problems: when a new problem arises, the problem solving process begins with an effort to find the closest matching solution to the problem within a set of historical solutions. Once a matching solution is found, it is adapted to the specific problem and an attempt is made to apply it. The new solution is too stored in a dedicated repository. With each subsequent problem solved, the repository becomes larger.Adaptive case management processes are of dynamic character, since they are not defined until at runtime. To master the unpredictability of processes and hence facilitate process management in conte...