Emergency decision support modeling for COVID-19 based on spherical fuzzy information

Significant emergency measures should be taken until an emergency event occurs. It is understood that the emergency is characterized by limited time and information, harmfulness and uncertainty, and decision-makers are always critically bound by uncertainty and risk. This paper introduces many novel approaches to addressing the emergency situation of COVID-19 under spherical fuzzy environment. Fundamentally, the paper includes six main sections to achieve appropriate and accurate measures to address the situation of emergency decision-making. As the spherical fuzzy set (FS) is a generalized framework of fuzzy structure to handle more uncertainty and ambiguity in decision-making problems (DMPs). First, we discuss basic algebraic operational laws (AOLs) under spherical FS. In addition, elaborate on the deficiency of existing AOLs and present three cases to address the validity of the proposed novel AOLs under spherical fuzzy settings. Second, we present a list of Einstein aggregation operators (AgOp) based on the Einstein norm to aggregate uncertain information in DMPs. Thirdly, we are introducing two techniques to demonstrate the unknown weight of the criteria. Fourthly, we develop extended TOPSIS and Gray relational analysis approaches based on AgOp with unknown weight information of the criteria. In fifth, we design three algorithms to address the uncertainty and ambiguity information in emergency DMPs. Finally, the numerical case study of the novel carnivorous (COVID-19) situation is provided as an application for emergency decision-making based on the proposed three algorithms. Results explore the effectiveness of our proposed methodologies and provide accurate emergency measures to address the global uncertainty of COVID-19.     

Optimal interval type-2 fuzzy fractional order super twisting algorithm: A second order sliding mode controller for fully-actuated and under-actuated nonlinear systems

In this paper, a novel interval type-2 fuzzy fractional order super twisting algorithm (IT2FFOSTA) which is essentially a second order sliding mode controller is presented. The proposed IT2FFOSTA enhances fractional order super twisting algorithm (FOSTA) by taking advantage of an interval type-2 fuzzy fractional order sliding surface (IT2FFOSS) for some classes of fully-actuated and under-actuated nonlinear systems in presence of uncertainty. The FOSTA significantly reduces the amount of chattering and the IT2FFOSS results in decreasing the tracking error, control effort, and chattering level. In order to control under-actuated systems, a hierarchical sliding surface is employed. The multi-tracker optimization algorithm is utilized to adjust the controller’s parameters; this leads to an optimal performance for the IT2FFOSTA. To examine the performance of the IT2FFOSTA, some simulation and experimental tests on three examples of different classes of fully-actuated and under-actuated systems, including ball and plate, inverted pendulum, and ball and beam systems are carried out. The simulation and experimental results demonstrate the superiority of the IT2FFOSTA in reducing the amount of chattering, tracking error, and control effort compared to those of the other control methods.     

Numerical investigations on the Dish–Stirling engine system

The Stirling engine is an environmentally friendly external combustion heat engine and reduces the complexities of the combustion process, and indirectly helps in reduction of CO₂ emission. Modelling based on cyclic analysis is performed for a Beta configuration Stirling engine of 1.5?kW_e capacity using a rhombic drive for the solar-dish-supported Stirling engine. The analysis helps in estimating the overall efficiency of the system using the experimental correlation of the solar concentrator ARUN160 at the engine operating temperature. The analysis shows that the system will have overall efficiency around 25% in the range of 750–1050?K at the expansion space. The degradation of performance compared to that at an operating temperature of 1025?K is only marginal and makes 750?K a more preferred temperature. The present study evaluates a range of possible design goals and provides suitable alternatives and thus provides a clear understanding of the system design considerations.     

Copy-move forgery detection of duplicated objects using accurate PCET moments and morphological operators

This paper presents a new method for copy-move forgery detection of duplicated objects. A bounding rectangle is drawn around the detected object to form a sub-image. Morphological operator is used to remove the unnecessary small objects. Highly accurate polar complex exponential transform moments are used as features for the detected objects. Euclidian distance and correlation coefficient between the feature vectors are calculated and used for searching the similar objects. A set of 20 forged images with duplicated objects is carefully selected from previously published works. Additional 80 non-forged images are edited by the authors and forged by duplicating different kinds of objects. Numerical simulation is performed where the results show that the proposed method successfully detect different kinds of duplicated objects. The proposed method is much faster than the previously existing methods. Also, it exhibits high robustness to various attacks such as additive white Gaussian noise, JPEG compression, rotation, and scaling.     

Production of reduced‐fat Labneh cheese with inulin and β‐glucan fibre‐based fat replacer

The beneficial role of dietary fibre in human nutrition and effects of properties on fermented dairy products have led to a growing demand for the incorporation of novel fibre‐based fat replacers. The aim of the present work was to investigate the possibility of using inulin and oat‐based β‐glucan in Labneh cheese and to analyse the physico‐chemical, textural and sensory properties of the resulting product. The results showed that the textural and sensory properties of the cheese with addition of inulin increased at a 12% fat ratio. Overall, full‐fat and reduced‐fat Labneh cheeses were firmer and had better flavour than all the low‐fat cheeses. However, inulin and oat β‐glucan, as fermentable fibres, were also degraded as fermentable fibres to produce organic acids and had the potential for use as fat replacers in low‐fat dairy systems.     

Some picture fuzzy Bonferroni mean operators with their application to multicriteria decision making

In this paper, we extend the Bonferroni mean (BM) operator with the picture fuzzy numbers (PFNs) to propose novel picture fuzzy aggregation operators and demonstrate their application to multicriteria decision making (MCDM). On the basis of the algebraic operational rules of PFNs and BM, we introduce some aggregation operators: the picture fuzzy Bonferroni mean, the picture fuzzy normalized weighted Bonferroni mean, and the picture fuzzy ordered weighted Bonferroni mean. Then, a new picture fuzzy MCDM method is proposed with the help of the proposed operators. Lastly, a practical application of proposed model is given to verify the developed model and related results of the proposed model is compared with the results of the existing models to indicate its applicability.     

Effect of Reynolds number and boundary layer thickness on the performance of V-cone flowmeter using CFD

The effect of Reynolds number and boundary layer thickness on the performance of V-cone flowmeter has been evaluated using computational fluid dynamics (CFD). The shear stress transport k-ω (SST k-ω) turbulence model has been adopted for closure. The performance of two V-cone flowmeters with different beta ratios (β) viz., 0.6 and 0.7 for a fixed vertex angle (ϕ) of 60° has been analysed as a function of Reynolds number (Re). The results show that the coefficient of discharge (C_d) increases with Reynolds number in the laminar and transition flow regimes whereas it is nearly constant in turbulent flow regime. From the results, it can be concluded that C_d is independent of Re for values equal to 4000 and beyond. Further, it is also seen that the performance of the V-cone flowmeter is not affected by the upstream boundary layer thickness if the velocity profiles having different boundary layer thickness are extracted from an axial distance of 10D and more are fed at 5D upstream of the meter. However, the meter is sensitive to the extracted velocity profile from an axial distance of 5D and uniform velocity profile being fed at 5D upstream. The value of C_d may be sensitive as a result of the pressure variation due to the obstruction.     

Validity of facial features’ geometric measurements for real-time assessment of mental fatigue in construction equipment operators

Operating construction equipment for extended periods of time may lead to mental fatigue and, as a result, an increased risk of human error-related accidents and jeopardized health problems for the operators. Therefore, to limit the risk of accidents and protect operators' wellbeing, their mental fatigue must be monitored reliably and in real time. Recently, many invasive technologies have been employed to alleviate this problem, but they entail the wearing of physical sensors, which may instigate irritation and discomfort. This study proposes a non-invasive mental fatigue monitoring method using geometric measurements of their facial features that does not require the operators to wear sensors on their body. The study further validates the proposed method by comparing it with wearable electroencephalography (EEG) technology to establish its ecological validity for construction equipment operators. To serve the purpose, a one-hour excavator operation by sixteen construction equipment operators was conducted on a construction site. Ground truth, brain activity using wearable EEG, and geometric measurements of facial features were extracted and analyzed at the baseline and every 20 min for one hour. A considerable temporal variation was found in the reported metrics (eye aspect ratio, eye distance, mouth aspect ratio, face area, and head motion) and were significantly correlated with ground truth and EEG metric. Furthermore, the brain visualization pattern obtained from EEG was also associated with the variations in the facial features. The findings of the study reveal that construction equipment operators’ mental fatigue can be monitored non-invasively using geometrical measurements of facial features.     

自适应有限元不同网格间力学结果传递方法及程序实现

对于依赖于加载历史的自适应有限元分析问题,不同网格间力学结果的传递过程起着重要作用。基于按距离加权平均的改进插值方法,研究分步加载时自适应有限元不同网格间力学结果的继承问题。为使传递结果合理并减小计算工作量,插值方法采取选择邻近数据点、考虑方向影响、适当提高结果场的光滑性并使其通过全部已知数据点等措施;针对开挖过程中结构介质不断改变、开挖工作面不断移动及不同开挖步引入的介质之间场变量不连续等特点,采取分区划分网格并插值方式,构造不同网格间应力及位移结果的传递过程。所述传递过程,能为自适应有限元模拟多步骤开挖及弹塑性增量荷载分析等各种分步加载计算问题的解决提供有利条件。最后,给出2个算例以验证传递过程的可靠性。按增量荷载初应力方法对厚壁筒弹塑性分析表明,其结果与理论解吻合;模拟多步开挖的工程实例计算结果亦展示出所述传递方法的有效性。     

步兵榴弹环境适应性试验设计与评估方法

直接由验前数据获取验前分布可能导致正样机数据"左右"定型试验结论,为了解决此问题,采用混合贝塔分布描述二项分布的验前分布,用相似性因子描述前后两次试验在产品状态和试验条件的差异,运用层次分析法确定了影响步兵榴弹环境适应性试验项目的不同因素的取值范围和相应评语集,给出了基于混合贝塔分布的试验方案设计方法.在获得试验数据后,运用聚类分析方法分析了产品验后分布的环境敏感性.结果表明,该方法参数估计的均方误差更小,估计值更稳健;聚类分析方法能够发现环境因素对产品性能的影响,能够为产品的改进和使用提供数据支撑和指导.