Accurate description of thermodynamic, structural, and electronic properties for bulk and surfaces of ceria (CeO₂) necessitates the inclusion of the Hubbard parameter (U) in the density functional theory (DFT) calculations to precisely account for the strongly correlated 4f electrons. Such treatment is a daunting task when attempting to draw a potential energy surface for CeO₂-catalyzed reaction. This is due to the inconsistent change in thermo-kinetics parameters of the reaction in reference to the variation in the U values. As an illustrative example, we investigate herein the discrepancy in activation and reaction energies for steps underlying the partial and full hydrogenation of acetyl

Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the

   The main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits  of( FMOLP)   algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun

The concept of Cech fuzzy soft bi-closure space ( ˇ Cfs bi-csp) ( ˇ U, L1, L2, S) is initiated and studied by the authors in [6]. The notion of pairwise fuzzy soft separated sets in Cfs bi-csp is defined in this study, and various features of ˇ this notion are proved. Then, we introduce and investigate the concept of connectedness in both Cfs bi-csps and its ˇ associated fuzzy soft bitopological spaces utilizing the concept of pairwise fuzzy soft separated sets. Furthermore, the concept of pairwise feebly connected is introduced, and the relationship between pairwise connected and pairwise feebly connected is discussed. Finally, we provide various instances to further explain our findings.

The idea of ech fuzzy soft bi-closure space ( bicsp) is a new one, and its basic features are defined and studied in [1]. In this paper, separation axioms, namely pairwise, , pairwise semi-(respectively, pairwise pseudo and pairwise Uryshon) - fs bicsp's are introduced and studied in both ech fuzzy soft bi-closure space and their induced fuzzy soft bitopological spaces. It is shown that hereditary property is satisfied for , with respect to ech fuzzy soft bi-closure space but for other mentioned types of separations axioms, hereditary property satisfies for closed subspaces of ech fuzzy soft bi-closure space.

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic