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The best way to achieve sustainable construction is to choose materials with a smaller environmental impact. In this regard, specialists and architects are advised to take these factors into account from the very beginning of the design process. This study offers a framework for selecting the optimal sustainable building material. The core goal of this article is to depict a novel structure of a neutrosophic soft expert set hybrid called an interval-valued neutrosophic soft expert set for utilization in construction supply chain management to select a suitable supplier for a construction project. This study applies two different techniques. One is an algorithmic technique, and the other is set-theoretic. The first one is applied for the structural characterization of an interval-valued neutrosophic expert set with its necessary operators like union and OR operations. The second one is applied for the construction of a decision-making system with the help of pre-described operators. The main purpose of the algorithm is to be used in supply chain management to select a suitable supplier for construction. This paper proposes a new model based on interval-valued, soft expert and neutrosophic settings. In addition to considering these settings jointly, this model is more flexible and reliable than existing ones because it overcomes the obstacles of existing studies on neutrosophic soft set-like models by considering interval-valued conditions, soft expert settings and neutrosophic settings. In addition, an example is presented to demonstrate how the decision support system would be implemented in practice. In the end, analysis, along with benefits, comparisons among existing studies and flexibility, show the efficacy of the proposed structure. [ABSTRACT FROM AUTHOR]

In the period of Industries 4.0, cyber-physical systems (CPSs) were amajor study area. Such systems frequently occur inmanufacturing processes and people's everyday lives, and they communicate intensely among physical elements and lead to inconsistency. Due to the magnitude and importance of the systems they support, the cyber quantum models must function effectively. In this paper, an image-processing-based anomalous mobility detecting approach is suggested that may be added to systems at any time. The expense of glitches, failures or destroyed products is decreased when anomalous activities are detected and unplanned scenarios are avoided. The presently offered techniques are not well suited to these operations, which necessitate information systems for issue treatment and classification at a degree of complexity that is distinct from technology. To overcome such challenges in industrial cyber-physical systems, the Image Processing aided Computer Vision Technology for FaultDetection System (IM-CVFD) is proposed in this research. The Uncertainty Management technique is introduced in addition to achieving optimum knowledge in terms of latency and effectiveness. A thorough simulation was performed in an appropriate processing facility. The study results suggest that the IM-CVFD has a high performance, low error frequency, low energy consumption, and low delay with a strategy that provides. In comparison to traditional approaches, the IM-CVFD produces a more efficient outcome. [ABSTRACT FROM AUTHOR]

Effective prioritization plays critical roles in precision medicine. Healthcare decisions are complex, involving trade-offs among numerous frequently contradictory priorities. Considering the numerous difficulties associated with COVID-19, approaches that could triage COVID-19 patients may help in prioritizing treatment and provide precise medicine for those who are at risk of serious disease. Prioritizing a patient with COVID-19 depends on a variety of examination criteria, but due to the large number of these biomarkers, it may be hard for medical practitioners and emergency systems to decide which cases should be given priority for treatment. The aim of this paper is to propose a Multidimensional Examination Framework (MEF) for the prioritization of COVID-19 severe patients on the basis of combined multi-criteria decision-making (MCDM) methods. In contrast to the existing literature, the MEF has not considered only a single dimension of the examination factors; instead, the proposed framework included different multidimensional examination criteria such as demographic, laboratory findings, vital signs, symptoms, and chronic conditions. A real dataset that consists of data from 78 patients with different examination criteria was used as a base in the construction of Multidimensional Evaluation Matrix (MEM). The proposed framework employs the CRITIC (CRiteria Importance Through Intercriteria Correlation) method to identify objective weights and importance for multidimensional examination criteria. Furthermore, the VIKOR (VIekriterijumsko KOmpromisno Rangiranje) method is utilized to prioritize COVID-19 severe patients. The results based on the CRITIC method showed that the most important examination criterion for prioritization is COVID-19 patients with heart disease, followed by cough and nasal congestion symptoms. Moreover, the VIKOR method showed that Patients 8, 3, 9, 59, and 1 are the most urgent cases that required the highest priority among the other 78 patients. Finally, the proposed framework can be used by medical organizations to prioritize the most critical COVID-19 patient that has multidimensional examination criteria and to promptly give appropriate care for more precise medicine. [ABSTRACT FROM AUTHOR]

The objective of the given work is to study the queues resulting in the buffer while self-similar traffic passing through a network nod and to build a mathematical model of an actual traffic. The latest researches of different types of network traffics bring out clearly that network traffic is defined by self-similarity and long-term dependence. The self-similar traffic has specific structure being reserved at various measures -- its realization is characterized by some vast emissions when respecting low medium-scale traffic. This fact degrades the performance significantly (increases, losses and delays) while running through the network nods. Hence, it follows that commonly used methods of simulation and network system calculations rested on traditional assumptions do not reflect the real situation taking place in the network. [L+94, CTB98, PW00, JOB12, L+10]. [ABSTRACT FROM AUTHOR]