Informatica

Innovations in technology emerged with digitalization affect all sectors, including supply chain and logistics. The term “digital supply chain” has arisen as a relatively new concept in the manufacturing and service sectors. Organizations planning to utilize the benefits of digitalization, especially in the supply chain area, have uncertainties on how to adapt digitalization, which criteria they will evaluate, what kind of strategies should be developed, and which should be given more importance. Multi-criteria decision making (MCDM) approaches can be addressed to determine the best strategy under various criteria in digital transformation. Because of the need to capture this uncertainty, fermatean fuzzy sets (FFSs) have been preferred in the study to widen the definition domain of uncertainty parameters. Interval-valued fermatean fuzzy sets (IVFFSs) are one of the most often used fuzzy set extensions to cope with uncertainty. Therefore, a new interval-valued fermatean fuzzy analytic hierarchy process (IVFF-AHP) method has been developed. After determining the main criteria and sub-criteria, the IVFF-AHP method has been used for calculating the criteria weights and ranking the alternatives. By determining the most important strategy and criteria, the study provides a comprehensive framework of digital transformation in the supply chain.

Maps are a common tool for visualizing various statistical figures that describe development in our society. Domain experts, journalists, and general public can pose questions on how to emphasize regions where, for instance, most young patients have long stayed in hospitals. One of the visualization’s problems is expressing validities of short-quantified sentences for regions on maps. The truth value of a summary assigns a value from the unit interval, which makes it suitable for interpretation on maps by hues of a selected colour, but it does not reflect the data distribution among regions. To meet this goal, a new quality measure covering data distribution among districts and its aggregation by the ordinal sums of conjunctive and disjunctive functions with the truth value is proposed and documented on examples. The next proposal is a relative quantifier expressing significant proportion of entities. This model is applied to the interpretation of COVID-19 cases development in the Slovak Republic on real data from one health insurance company. Finally, this article discusses the applicability of the proposed approach in other areas where the interpretation of summarized sentences on maps is beneficial.

Blockchain is gaining traction for improving the security of healthcare applications, however, it does not become a silver bullet as various security threats are observed in blockchain-based applications. Moreover, when performing the security risk management (SRM) of blockchain-based applications, there are conceptual ambiguities and semantic gaps that hinder from treating the security threats effectively. To address these issues, we present a blockchain-based healthcare security ontology (HealthOnt) that offers coherent and formal information models to treat security threats of traditional and blockchain-based applications. We evaluate the ontology by performing the SRM of a back-pain patient’s healthcare application case. The results show that HealthOnt can support the iterative process of SRM and can be continually updated when new security threats, vulnerabilities, or countermeasures emerge. In addition, the HealthOnt may assist in the modelling and analysis of real-world situations while addressing important security concerns from the perspective of stakeholders. This work can help blockchain developers, practitioners, and other associated stakeholders to develop secure blockchain-based healthcare applications in the early stages.

The paper presents a secure and usable variant of the Game Changer Password System, first proposed by McLennan, Manning, and Tuft. Unlike the initial proposal based on inadequately secure Monopoly and Chess, we propose an improved version based on a layered “Battleship” game resilient against brute force and dictionary attacks. Since the initially proposed scheme did not check for the memorability and usability of a layered version, we conducted an experiment on the usability and memorability aspects. Surprisingly, layered passwords are just as memorable as single ones and, with an 80% recall rate, comparable to other graphical password systems. The claim that memorability is the most vital aspect of game-based password systems cannot be disproved. However, the experiment revealed that the usability decreased to such a low level that users felt less inclined to use such a system daily or recommend it to others.

Knowledge graphs are commonly represented by ontology-based databases. Tracking the provenance of ontological changes and ensuring ontology consistency is important. In this work, we propose a transaction manager for ontology-based database manipulation that combines blockchain and Semantic Web technologies. The latter is used for the efficient querying and modification of data, whereas the blockchain is used for the secure storage and tracking of changes. The blockchain enables a decentralized setup and data restoration. We evaluate our solution by measuring cost and time. Our solution introduces some overhead for updates whereas querying works at the same speed as the underlying ontology database.

Purpose: Few studies in the literature address the success of enterprise Information Systems (IS) projects, namely focusing on how success is influenced by project management practices. This research studied the impact of ISO 21500/PMBOK processes on the success of IS projects, aiming to contribute to a better understanding of management practices importance in the context of this type of projects. Design/methodology/approach: An international survey was used to collect data, which was analysed using descriptive and inferential statistics. Findings: The results show higher levels of success than usually reported in the literature. Furthermore, this research shows that overall success is strongly influenced by ISO/PMBOK project management processes, thus reinforcing the relevance of competent project management to improve the results of IS projects. Originality: Focusing on the specific case of IS projects, this study shows that higher levels of success are achieved by organizations with higher project management maturity.

Multidimensional scaling (MDS) is a widely used technique for mapping data from a high-dimensional to a lower-dimensional space and for visualizing data. Recently, a new method, known as Geometric MDS, has been developed to minimize the MDS stress function by an iterative procedure, where coordinates of a particular point of the projected space are moved to the new position defined analytically. Such a change in position is easily interpreted geometrically. Moreover, the coordinates of points of the projected space may be recalculated simultaneously, i.e. in parallel, independently of each other. This paper has several objectives. Two implementations of Geometric MDS are suggested and analysed experimentally. The parallel implementation of Geometric MDS is developed for multithreaded multi-core processors. The sequential implementation is optimized for computational speed, enabling it to solve large data problems. It is compared with the SMACOF version of MDS. Python codes for both Geometric MDS and SMACOF are presented to highlight the differences between the two implementations. The comparison was carried out on several aspects: the comparative performance of Geometric MDS and SMACOF depending on the projection dimension, data size and computation time. Geometric MDS usually finds lower stress when the dimensionality of the projected space is smaller.

The aim of the article is to identify drivers and limiters of the development of Business Process Management Systems (BPMS) from the point of view of the industry and the academia, and to formulate practical recommendations. Their identification is crucial in order to remove a considerable gap between the approach to knowledge-intensive business processes (kiBPs), which require dynamic management and are decisive with regard to the competitive position of the organization under the conditions of Industry 5.0, as well as the possibilities offered by ICT solution, and the current possibilities and needs of BPM practitioners. The authors applied a methodological approach based on a theoretical literature review and a review of practice through online structured expert interviews with key BPMS solution providers. According to the literature, the main drivers pertain to the enterprises’ efforts to reduce costs and improve their productivity and efficiency, develop technology, and enact changes in business models and business processes. According to vendors, the main drivers for the combination of BPMS and Case Management Systems (CMS) were the users’ expectations, technology identity, and further development perspectives. The main limiters of the decision to combine both classes of systems were technological problems predicted by vendors related to the unification of historically different technologies used in both classes of systems, as well as implementation-based problems related to the likely need to reconfigure the software environments of software users. The article formulated original recommendations for both vendors and users of iBPMS software, including the basic recommendation of the selection of the methodology of implementation of BPM and iBPMS in accordance with the context of the organization’s operations (the nature of its business processes).

We introduce a compact formulation for the fixed-destination multi-depot asymmetric travelling salesman problem (FD-mATSP). It consists of m salesmen distributed among D depots who depart from and return to their respective origins after visiting a set of customers. The proposed model exploits the multi-depot aspect of the problem by labelling the arcs to identify the nodes that belong to the same tour. Our experimental investigation shows that the proposed-two index formulation is versatile and effective in modelling new variations of the FD-mATSP compared with existing formulations. We demonstrate this by applying it for the solution of two important extensions of the FD-mATSP that arise in logistics and manufacturing environments.

This model describes the heat equation in 3D domains, and this problem is reduced to a hybrid dimension problem, keeping the initial dimension only in some parts and reducing it to one-dimensional equation within the domains in some distance from the base regions. Such mathematical models are typical in industrial installations such as pipelines. Our aim is to add two additional improvements into this methodology. First, the economical ADI type finite volume scheme is constructed to solve the non-classical heat conduction problem. Special interface conditions are defined between 3D and 1D parts. It is proved that the ADI scheme is unconditionally stable. Second, the parallel factorization algorithm is proposed to solve the obtained systems of discrete equations. Due to both modifications the run-time of computations is reduced essentially. Results of computational experiments confirm the theoretical error analysis and scalability estimates of the parallel algorithm.