Memory and communication efficient algorithm for decentralized counting of nodes in networks

Node counting on a graph is subject to some fundamental theoretical limitations, yet a solution to such problems is necessary in many applications of graph theory to real-world systems, such as collective robotics and distributed sensor networks. Thus several stochastic and naïve deterministic algorithms for distributed graph size estimation or calculation have been provided. Here we present a deterministic and distributed algorithm that allows every node of a connected graph to determine the graph size in finite time, if an upper bound on the graph size is provided. The algorithm consists in the iterative aggregation of information in local hubs which then broadcast it throughout the whole graph. The proposed node-counting algorithm is on average more efficient in terms of node memory and communication cost than its previous deterministic counterpart for node counting, and appears comparable or more efficient in terms of average-case time complexity. As well as node counting, the algorithm is more broadly applicable to problems such as summation over graphs, quorum sensing, and spontaneous hierarchy creation.

Multi-information analysis for recommendation of flooded-irrigated rice for adaptability and phenotypic stability

The GxE interaction is one of the major difficulties of plant breeding programs, both in the selection phase and in the recommendation of cultivars. To assess adaptability and stability, various statistical methods are used. The simultaneous use of some methodologies, using multi-information criteria for cultivar’s recommendation, can extract information that cannot be observed using each methodology separately. The aim of this work was to perform a large description of the behavior of flooded-irrigated rice genotypes, responding to environmental variations, using methods already established in the literature, but exploring the particularities of each methodology that together establish an information criterion for cultivar recommendation. To this end, 18 rice genotypes belonging to flood-irrigated rice breeding program were evaluated over four agricultural years, 2012/2013 to 2015/2016, totaling 12 environments (3 sites × 4 years). Multi-information estimates were performed to adaptability and stability analysis. There was no sign for the effect of the genotypes, and there was the significance of the effects of environment and GxE interaction. The aggregation of information and the large description of the behavior of the flooded rice genotypes demonstrated to be an efficient tool for studies of adaptability and stability.

Model of Social Influence in Analysis of Socio-engineering Attacks

The purpose of this study is to study the modernization of the model of an attacker’s social engineering attack on a user, taking into account a wider range of factors influencing the success of a social engineering attack associated with the principles of social influence. Methods. To achieve this goal, the approaches to social influence and the components of social influence were analyzed. An integrated circuit of social influence is built, grounding in the context of socio-engineering attacks. Results. A model of social influence is proposed, built in the context of an attacker’s social engineering attack on a user. A new interpretation of the term user vulnerability in the context of information security has been proposed. Conclusion. The result obtained forms the potential of filling the user and attacker models with specific vulnerabilities and competencies, which will lead to a more accurate assessment of the success of the attacker’s social engineering attack on the user, due to the aggregation of information from incidents that have occurred.

Picture Fuzzy Maclaurin Symmetric Mean Operators and Their Applications in Solving Multiattribute Decision-Making Problems

To evaluate objects under uncertainty, many fuzzy frameworks have been designed and investigated so far. Among them, the frame of picture fuzzy set (PFS) is of considerable significance which can describe the four possible aspects of expert’s opinion using a degree of membership (DM), degree of nonmembership (DNM), degree of abstinence (DA), and degree of refusal (DR) in a certain range. Aggregation of information is always challenging especially when the input arguments are interrelated. To deal with such cases, the goal of this study is to develop the notion of the Maclaurin symmetric mean (MSM) operator as it aggregates information under uncertain environments and considers the relationship of the input arguments, which make it unique. In this paper, we studied the theory of MSM operators in the layout of PFSs and discussed their applications in the selection of the most suitable enterprise resource management (ERP) scheme for engineering purposes. We developed picture fuzzy MSM (PFMSM) operators and investigated their validity. We developed the multiattribute decision-making (MADM) algorithm based on the PFMSM operators to examine the performance of the ERP systems using picture fuzzy information. A numerical example to evaluate the performance of ERP systems is studied, and the effects of the associated parameters are discussed. The proposed aggregated results using PFMSM operators are found to be reliable as it takes into account the interrelationship of the input information, unlike traditional aggregation operators. A comparative study of the proposed PFMSM operators is also studied.

Automatic Actionable Information Processing and Trust Management Towards Safer Internet of Things

The security of the Internet of Things (IoT) is a very important aspect of everyday life for people and industries, as well as hospitals, military, households and cities. Unfortunately, this topic is still too little researched and developed, which results in exposing users of Internet of Things to possible threats. One of the areas which should be addressed is the creation of a database of information about vulnerabilities and exploits in the Internet of Things; therefore, the goal of our activities under the VARIoT (Vulnerability and Attack Repository for IoT) project is to develop such a database and make it publicly available. The article presents the results of our research aimed at building this database, i.e., how the information about vulnerabilities is obtained, standardized, aggregated and correlated as well as the way of enhancing and selecting IoT related data. We have obtained and proved that existing databases provide various scopes of information and because of that a single and most comprehensive source of information does not exist. In addition, various sources present information about a vulnerability at different times—some of them are faster than others, and the differences in publication dates are significant. The results of our research show that aggregation of information from various sources can be very beneficial and has potential to enhance actionable value of information. We have also shown that introducing more sophisticated concepts, such as trust management and metainformation extraction based on artificial intelligence, could ensure a higher level of completeness of information as well as evaluate the usefulness and reliability of data.

EDUCATIONAL LANDSCAPES IN THE CONTEXT OF THE DIGITAL EDUCATIONAL ENVIRONMENT

The concept of "educational map", as well as a number of related concepts such as "concept map", have been the subject of numerous studies in the field of pedagogy over the years. They are a tool for describing and analyzing the knowledge of a specific student at a specific point in time. Recently, there has been interest in the problem of generalization and aggregation of information contained in separate individual maps. The concept of "Concept Landscape" was proposed as an approach to solving this problem (Mühling, 2017). However, this concept is focused exclusively on the analysis of the knowledge structure of a group of students. Accordingly, the problem arises of finding a more general and more universal tool that allows us to organically fit aggregated educational maps into the structure of the digital educational environment. We propose to consider this environment as a context that unites all possible educational maps. In accordance with the proposed approach, by the educational landscape we mean the result of the aggregation of several educational maps, united by the digital educational environment as a common context. We also set ourselves the task of identifying technologies for the aggregation of educational maps. We consider superposition, inclusion and absorption as such technologies and disclose the content of these operations in our article. We also establish the main form of the formal description of the educational landscape - a graph with colored vertices and edges. We propose a five-component algorithm for constructing and processing an educational landscape and describe the content of all its stages in the article. In our study, we also give an answer to the question about the role of the educational landscape within the digital educational environment. This role is, in our opinion, multifactorial. The main factors include: the formation of a space of possible individual learning trajectories; analysis and forecasting of the group dynamics of knowledge and skills of students; creation of a tool for supporting the design of an digital educational environment.

Problems of assessing socio-economic damage due to epidemics

Relevance. The sudden epidemiological complications that have emerged in the current century have highlighted the serious difficulties on the part of medical services and States in general in responding to epidemiological emergencies of international significance, which required a comprehensive study of the scale of the problem of the negative socio-economic consequences of epidemics for the modern state. The aim of the work was to study the factors that determine the current configuration of medical and social risks in the pre-epidemic period and form the socio-economic significance of epidemics and pandemics in a developed postindustrial society. The results are based on the monitoring, analysis and aggregation of information from specialized national and international industry publications and online resources (medical, socio-economic), as well as materials from peer-reviewed periodicals, on the practical development of author's approaches and assessments of the functioning of the anti-epidemic preparedness system at the international and national levels. Modern factors that aggravate the negative consequences of the pandemic for demography and the state economy in the absence of immunoprophylaxis and specific therapy are identified. Conclusion. The socio-economic significance of epidemiological events in the modern post-industrial society is significantly higher than the predicted level, based on the calculations of the cost of a clinical case of an infectious disease used in the previous century, namely: without including the costs of sanitary and anti-epidemic measures in the foci of the disease, for the deployment of a hospital base; for ensuring a strict anti-epidemic regime of work in medical institutions, for the rehabilitation and restoration of health of persons who have suffered an infectious disease; for the organization of preventive measures in non-medical organizations and enterprises (including information and explanatory work among the population); for the organization of medical care for persons with somatic pathology.