Auswahl der wissenschaftlichen Literatur zum Thema „Ecosystemic Hypergraph“

Compared with the conventional industrial product–service system, the smart industrial service ecosystem (SISE) mentioned in this study contains more service activity according to the characteristics of the industrial context, participation of various stakeholders and smart interconnected technologies. This study proposes a detailed modularization design framework for SISE, which can be referenced in various industrial contexts. Firstly, the context-based smart industrial service identification blueprint (SISIB) is proposed to describe the operation model of SISE and identify the service components. The SISIB can ensure that the designers understand the service and work process of the system and improve or carry out the smart industrial service (SIS) component identification. In the case of this article, SIS components from different industrial levels can be systematically identified. Secondly, smart collaboration and sustainable development principles are proposed for measuring the correlation degree among the service components. Considering the complexity and multi-level distribution nature of service components, the hyperedge concept is presented to realize the correlation comparison among the service components, and the evaluation linguistics is applied to handle the decision uncertainties. With this method, the effective correlation comparison between service components can be formed with few hyperedges. Thirdly, the hypergraph clustering theory is applied to define the SISE service module partition. The triangular fuzzy number is first used in hyperedge strength evaluation to comply with the vague linguistics from service design experts. The normalized hypergraph cut principle is realized using the K nearest neighbors (kNN) algorithm, and with this method, the new unified hypergraph and related Laplace matrix can be obtained. Then, the relevant eigenvalue of that Laplace matrix is gained, and the component clustering visualization is realized using the k-means algorithm. After the clustering is performed, several modular design schemes can be gained. In order to select the best modularization scheme, we referenced the modularity concept and realized the quality measurement for the modular design using hypergraph modularity criteria. Regarding these three steps, a detailed modularization case study for a renewable electricity service ecosystem design is presented to verify the viability and feasibility of the study in service modular design. The result showed that the framework in this study can realize the visible and clearance service component identification in a smart connected multi-level industrial context. The modular design scheme based on hypergraph can also achieve high modularity with a more convenient correlation evaluation.

Materialized View Selection is one of the most studied problems in the database field, covering SQL and NoSQL technologies as well as different deployment infrastructures (centralized, parallel, cloud). This problem has become more complex with the arrival of data warehouses, being coupled with the physical de sign phase that aims at optimizing query performance. Selecting the best set of materialized views to optimize query performance is a challenging task. Given their importance and the complexity of their selection, several research efforts both from academia and industry have been conducted. Results are promising - some solutions are being implemented by commercial and open-source DBMSs -, but they do not factor in the following properties of nowadays analytical queries: (i) large scale queries, (ii) their dynamicity, and (iii) their high interaction. Studies to date fail to consider that complete set of properties. Considering the three properties simultaneously is crucial regarding today?s analytical requirements, which involve dynamic and interactive queries. In this paper, we first present a concise state of the art of the materialized view selection problem (VSP) by analyzing its ecosystem. Secondly, we propose a proactive re-selection approach that considers the three properties concurrently. It features twomain phases: offline and online. In the offline phase, we manage a set of the first queries based on a given threshold _ by selecting materialized views through a hypergraph structure. The second phase manages the addition of new queries by scheduling them, updates the structure of the hypergraph, and selects new views by eliminating the least beneficial ones. Finally, extensive experiments are conducted using the Star Schema Benchmark data set to evaluate the effectiveness and efficiency of our approach.

The aim of the study. In modern conditions of changing the global “educational landscape”, the leading trend in building a new educational process management system is the personalization of the educational process in the electronic environment. New pedagogical technologies and innovative forms of organizing personalized learning in the electronic environment are developing, one of which is adaptive learning. The development of the structure and content of adaptive e-learning courses, the design and implementation of an educational strategy, teaching methods, and approaches to assessing results is determined by the model of its subject domain - the model of learning content. The aim of the study is to develop an approach to constructing the learning content model of an adaptive e-learning course that provides a formalized presentation of the educational material of the discipline and the construction of a logically based strategy for its study. Materials and methods. Methodological basis of research methods make up the logical-epistemological analysis and graph theory, and comparative analysis of psychological and pedagogical, scientific and methodical works, analysis of regulatory documents on research issues, professional and federal educational standards of higher education. Results. A feature of the author's approach is structuring of the subject domain in the form of a sequence of terms (training objects) of the learning content, studied in a certain order and presented in several versions of the presentation. The presented model for constructing the learning content of the academic discipline differs from the wellknown ones by the presence of logical ordering of concepts based on the integration of logic methods of concept analysis, using logical and epistemological methods for correlating the volume and content of concepts with the methods of graph theory and hypergraphs. The definition of educational objects of a tree (hypergraphic tree) of terms is obtained on the basis of a concept tree of discipline with a further determination of the sequence of their study, as well as the inclusion of a phenomenological and structural model in the content of the educational object, which allows to identify and disclose the essence of each studied concept within the framework of the subject domain of discipline. Conclusion. The proposed approach has been tested in the educational process of the program 09.03.02 – “Information systems and technologies” at the Siberian Federal University. Analysis of observations and evaluating the effectiveness of adaptive e-learning course in the educational process was carried out using the Kruskal-Wallis test by ranks. As a result of the experiment, it was revealed that at the end of the experiment, the control and experimental groups were statistically significantly different, which allowed us to conclude that the adaptive e-learning course developed in the educational process was effective. Adaptive e-learning courses, which are based on the approach proposed by the authors, made it possible to present educational content in the form of logically integral micro portions, which allow the adaptation of the educational environment to the individual characteristics of students. In the future, the proposed approach can contribute to development of personalized adaptive learning university ecosystems under digitalization formation.

De nombreux problèmes de vérification des systèmes concurrents ont été traités avec succès par diverses méthodes au fil des ans, en particulier les dépliages de réseaux de Petri. Cependant, les questions de comportement et de stabilisation à long terme ont reçu relativement peu d'attention. Par exemple, les caractéristiques cruciales de la dynamique à long terme des écosystèmes, telles que les bassins d'attraction et les points de basculement, restent difficiles à identifier et à quantifier avec une bonne couverture. L'une des principales raisons en est l'accent mis, dans la modélisation écologique, sur les modèles continus, qui fournissent des simulations raffinées mais ne permettent généralement pas d'étudier la manière dont l'évolution du système serait modifiée en cas d'événements supplémentaires ou dans des situations différentes. Dans ce travail, nous visons à fournir une boîte à outils pour l'analyse et la modélisation de la dynamique des écosystèmes. Nous proposons des réseaux de Petri à réinitialisation sûre pour la modélisation, car ils ont le potentiel de donner une vue d'ensemble exhaustive des différents scénarios d'évolution possibles. Le dépliage des réseaux de Petri nous fournit les bons outils pour déterminer les trajectoires du système menant à l'effondrement et/ou à la survie, et finalement caractériser les actions ou inactions qui aident à soutenir la stabilisation de l'écosystème. Cette caractérisation de la production/consommation de jetons a été utilisée pour séparer les configurations minimalement condamnées des configurations libres, c'est-à-dire les exécutions conduisant inévitablement à l'effondrement du système même si ces exécutions ne sont pas identifiées a priori comme mauvaises et les exécutions qui maintiennent le système stable, en excluant les états mauvais ou condamnés, respectivement. Le déploiement des réseaux de réinitialisation sûrs et la partie algorithmique permettant de trouver des configurations minimalement condamnées ont été mis en œuvre avec succès dans un outil logiciel appelé Ecofolder et testés à l'aide de quelques ex- emples intrigants
Many verification problems for concurrent systems have been successfully addressed by a variety of methods over the years, in particular, Petri net unfoldings. However, questions of long-term behaviour and stabilisation have received relatively little attention. For instance, crucial features of the long-term dynamics of ecosystems, such as basins of attraction and tipping points, remain difficult to identify and quantify with good coverage. A central reason for this is the focus, in ecological modeling, on continuous models, which provide refined simulations but do not in general allow to survey how the system evolution would be altered under additional events, or in otherwise different situations. In this work we aimed to provide toolkit for modeling and analyzing ecosystem dynamics. We advocate for safe reset Petri nets for modeling since them have the potential to give an exhaustive possibilistic overview of the different evolution scenarios that are feasible. The unfolding of Petri nets provides us the right tools to determine system trajectories leading to collapse and/or survival, and eventually characterize those actions or inactions that help to support ecosystem stabilisation. This characterization of token's production/consumption was used to separate minimally doomed configurations from free ones, meaning executions leading inevitably to the system's collapse even though these executions are not identified a priori as bad ones and executions that keep the system stable, excluding bad or doomed states, respectively. Both the unfolding of safe reset nets and the algorithmic part for finding minimally doomed configurations have been successfully implemented in a software tool called Ecofolder and tested with some intriguing examples