Informatica

We study the burst ratio of packet loss processes in networking. This parameter characterizes the inclination of packet losses to form long, consecutive sequences. Such long sequences of losses may have a negative impact on multimedia streams, particularly those of real-time type. In packet networks, the burst ratio is often elevated due to overflows of packet buffers, which are present in all routers and switches. In the article, we investigate the burst ratio in the per-flow manner, i.e. individually for every flow of packets traversing a network node. We first confront all the per-flow burst ratios with each other, as well as with the burst ratio computed for the multiplexed traffic. Next, we study the influence of different features of the system on these burst ratios. In particular, the influence of rates of flows and their proportions, the standard deviation of interarrival times, the capacity of the buffer, the system load and the distribution of the service time, is studied. Special attention is paid to models with non-Poisson flows, which are not analytically tractable.

This contribution presents a brief survey of clipping and intersection algorithms in ${E^{2}}$ and ${E^{3}}$ with a nearly complete list of relevant references. Some algorithms use the projective extension of the Euclidean space and vector-vector operations, which support GPU and SSE use.

The focus of this paper is on the criteria weight approximation in Multiple Criteria Decision Making (MCDM). An approximate weighting method produces the weights that are surrogates for the exact values that cannot be elicited directly from the DM. In this field, a very famous model is Rank Order Centroid (ROC). The paper shows that there is a drawback to the ROC method that could be resolved. The paper gives an idea to develop a revised version of the ROC method called Improved ROC (IROC). The behaviour of the IROC method is investigated using a set of simulation experiments. The IROC method could be employed in situations of time pressure, imprecise information, etc. The paper also proposes a methodology including the application of the IROC method in a group decision making mode, to estimate the weights of the criteria in a tree-shaped structure. The proposed methodology is useful for academics/managers/decision makers who want to deal with MCDM problem. A study case is examined to show applicability of the proposed methodology in a real-world situation. This case is engine/vehicle selection problem, that is one of the fundamental challenges of road transport sector of any country.

The coordinated integration of heterogeneous TinyML-enabled elements in highly distributed Internet of Things (IoT) environments paves the way for the development of truly intelligent and context-aware applications. In this work, we propose a hierarchical ensemble TinyML scheme that permits system-wide decisions by considering the individual decisions made by the IoT elements deployed in a certain scenario. A two-layered TinyML-based edge computing solution has been implemented and evaluated in a real smart-agriculture use case, permitting to save wireless transmissions, reduce energy consumption and response times, at the same time strengthening data privacy and security.

In this study, Intuitionistic Fuzzy Consistency Method (IF-FUCOM) and Grey Relation Analysis (GRA) were combined to assess the effects of Bacillus subtilis bacteria on concrete properties, as well as to determine the optimal bacteria concentration and curing day. Three different concentrations of bacteria were added to the mortar mixes, like 103, 105, and 107 cells/ml of water. Mortar samples were left to cure for 7 days, 14 days, and 28 days to evaluate compressive strength, water absorption, crack healing. According to the proposed algorithm, 105 bacteria are the optimal concentration, while 28 days is the ideal curing time.

Due to the popularity of mobile communication, many computing devices are exposed to remote environments without physical protection so that these devices easily suffer from leakage attacks (e.g., side-channel attacks). Under such leakage attacks, when a computing device performs some cryptographic algorithm, an adversary may acquire partial bits of secret keys participated in this cryptographic algorithm. To resist leakage attacks, researchers offer leakage-resilient cryptography as a solution. A signcryption scheme combines signing and encrypting processes to simultaneously provide both authentication and confidentiality, which is an important cryptographic primitive. Indeed, many leakage-resilient signcryption schemes under various public key system (PKS) settings were proposed. Unfortunately, these schemes still have two shortcomings, namely, bounded leakage resilience and conditionally continuous leakage resilience. In this paper, a “fully” continuous leakage-resilient certificate-based signcryption (FCLR-CBSC) scheme is proposed. Security analysis is formally proved to show that our scheme possesses both authentication and confidentiality against two types of adversaries in the certificate-based PKS setting. Performance analysis and simulation experience show that our scheme is suited to run on both a PC and a mobile device.

Innovation can be the greatest hope of overcoming economic challenges. This paper aims to evaluate countries concerning their innovation performances. We introduce an innovation performance evaluation methodology by considering objective factors and applying seven reliable MCDM methods: MEREC, CODAS, MABAC, MARCOS, CoCoSo, WASPAS, and MAIRCA. MEREC calculates the relative weights of indicators considered, while the other techniques decide the ranking order of G7 countries. The Borda rule is then employed to gain an aggregated ranking order. “Business sophistication” is the most critical indicator, whereas the US has the best position regarding the overall ranking. Sensitivity control is as well conducted.

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.