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  • Decision-Making Problems under the Environment of m-Polar Diophantine Neutrosophic N-Soft Set
  • Abstract Fuzzy models are present everywhere from natural to artificial structures, embodying the dynamic processes in physical, biological, and social systems. As real-life problems are often uncertain on account of inconsistent and indeterminate information, it seems very demanding for an expert to solve those problems using a fuzzy model. In this regard, we develop a hybrid new model m-polar Diophantine neutrosophic N-soft set which is based on neutrosophic set and soft set. Additionally, we define several different sorts of compliments on the proposed set. A proposed set is a generalized form of fuzzy, soft, Pythagorean fuzzy, Pythagorean fuzzy soft, and Pythagorean…
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  • Fluid and Osmotic Pressure Balance and Volume Stabilization in Cells
  • Abstract A fundamental problem for cells with their fragile membranes is the control of their volume. The primordial solution to this problem is the active transport of ions across the cell membrane to modulate the intracellular osmotic pressure. In this work, a theoretical model of the cellular pump-leak mechanism is proposed within the general framework of linear nonequilibrium thermodynamics. The model is expressed with phenomenological equations that describe passive and active ionic transport across cell membranes, supplemented by an equation for the membrane potential that accounts for the electrogenicity of the ionic pumps. For active ionic transport, the model predicts that…
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  • A Survey on Machine Learning in COVID-19 Diagnosis
  • Abstract Since Corona Virus Disease 2019 outbreak, many expert groups worldwide have studied the problem and proposed many diagnostic methods. This paper focuses on the research of Corona Virus Disease 2019 diagnosis. First, the procedure of the diagnosis based on machine learning is introduced in detail, which includes medical data collection, image preprocessing, feature extraction, and image classification. Then, we review seven methods in detail: transfer learning, ensemble learning, unsupervised learning and semi-supervised learning, convolutional neural networks, graph neural networks, explainable deep neural networks, and so on. What’s more, the advantages and limitations of different diagnosis methods are compared. Although the…
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  • A Chaos Sparrow Search Algorithm with Logarithmic Spiral and Adaptive Step for Engineering Problems
  • Abstract The sparrow search algorithm (SSA) is a newly proposed meta-heuristic optimization algorithm based on the sparrow foraging principle. Similar to other meta-heuristic algorithms, SSA has problems such as slow convergence speed and difficulty in jumping out of the local optimum. In order to overcome these shortcomings, a chaotic sparrow search algorithm based on logarithmic spiral strategy and adaptive step strategy (CLSSA) is proposed in this paper. Firstly, in order to balance the exploration and exploitation ability of the algorithm, chaotic mapping is introduced to adjust the main parameters of SSA. Secondly, in order to improve the diversity of the population…
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  • A New Method to Evaluate Linear Programming Problem in Bipolar Single-Valued Neutrosophic Environment
  • Abstract A bipolar single-valued neutrosophic set can deal with the hesitation relevant to the information of any decision making problem in real life scenarios, where bipolar fuzzy sets may fail to handle those hesitation problems. In this study, we first develop a new method for solving linear programming problems based on bipolar singlevalued neutrosophic sets. Further, we apply the score function to transform bipolar single-valued neutrosophic problems into crisp linear programming problems. Moreover, we apply the proposed technique to solve fully bipolar single-valued neutrosophic linear programming problems with non-negative triangular bipolar single-valued neutrosophic numbers (TBSvNNs) and non-negative trapezoidal bipolar single-valued neutrosophic…
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  • Multi-Objective High-Fidelity Optimization Using NSGA-III and MO-RPSOLC
  • Abstract Optimizing the performance of composite structures is a real-world application with significant benefits. In this paper, a high-fidelity finite element method (FEM) is combined with the iterative improvement capability of metaheuristic optimization algorithms to obtain optimized composite plates. The FEM module comprises of ninenode isoparametric plate bending element in conjunction with the first-order shear deformation theory (FSDT). A recently proposed memetic version of particle swarm optimization called RPSOLC is modified in the current research to carry out multi-objective Pareto optimization. The performance of the MO-RPSOLC is found to be comparable with the NSGA-III. This work successfully highlights the use of…
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  • Properties and Applications of Bamboo Fiber–A Current-State-of-the Art
  • Abstract Fibers are used in many forms in engineering applications–one of the most common being used as reinforcement. Due to its renewable short natural growth cycle and abundance of bamboo resources, bamboo fiber has attracted attention over other natural fibers. Bamboo fiber has a complex natural structure but offers excellent mechanical properties, which are utilized in the textile, papermaking, construction, and composites industry. However, bamboo fibers can easily absorb moisture and are prone to corrosion limiting their use in engineering applications. Therefore, a better understanding of bamboo fiber is particularly important. This paper reviews all existing research on the mechanical characterization…
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  • Neutrosophic Mathematical Programming for Optimization of Multi-Objective Sustainable Biomass Supply Chain Network Design
  • Abstract In this paper, a multi-objective sustainable biomass supply chain network under uncertainty is designed by neutrosophic programming method. In this method, for each objective function of the problem, three functions of truth membership, non-determination and falsehood are considered. Neutrosophic programming method in this paper simultaneously seeks to optimize the total costs of the supply chain network, the amount of greenhouse gas emissions, the number of potential people hired and the time of product transfer along the supply chain network. To achieve the stated objective functions, strategic decisions such as locating potential facilities and tactical decisions such as optimal product flow…
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  • Empirical Thermal Investigation of Oil–Immersed Distribution Transformer under Various Loading Conditions
  • Abstract The distribution transformer is the mainstay of the power system. Its internal temperature study is desirable for its safe operation in the power system. The purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading conditions. To achieve this goal, the temperature distribution in the oil, core, and windings are studied at each loading. An experimental study is performed with a 10/0.38 kV, 10 kVA oil–immersed transformer equipped with forty–two PT100 sensors (PTs) for temperature measurement installed inside during its manufacturing process. All possible locations for the hottest spot temperature (HST)…
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  •   Views:550       Downloads:221        Download PDF
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