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.     

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.     

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.     

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.     

矿井电动机事故原因分析和预防办法

电动机事故在煤矿生产中居高不下 ,严重影响煤矿安全生产。针对电动机事故的原因进行了分析 ,采取积极有效的措施 ,最大限度地减少电动机事故的发生 ,提高煤矿的经济效益和安全效益     

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。     

敲击-回波法中传感器影响的LTI系统理论分析

利用一维波动方程对理想自由桩在桩顶受冲击力作用的动态过程进行数学仿真，用有限元法程序计算出桩顶处不考虑传感器的速度响应理论时程曲线，并由LTI系统卷积积分及傅立叶变换得出冲击力和速度响应的频域表示；根据LTI系统理论对考虑传感器特性的动态过程进行分析，得出速度响应的频域表示；将典型的传感器频率特性与不考虑传感器的理想自由桩的速度响应在频域进行数字合成，经傅立叶逆交换还原成含有传感器特性的速度响应时程曲线：调节冲击力脉宽，计算与同一传感器特性对应的速度响应，得出冲击力与传感器对速度响应的联合影响规律并举出实例进行验证；最后，提出一种新的变换域抑制法，使速度响应中的传感器特性影响有可能通过计算机程序来抑制。     

基于解析冗余式的风机传动系统故障诊断

为了以系统有序的方法对风机的具体元件参数进行故障诊断,给出一种基于键合图模型的故障诊断方法。键合图模型是一种跨能域的元件级模型,因此能够定位到具体的故障元件。同时键合图模型能够清晰地表明各元件之间的关系,因此适用于推导解析冗余式。通过解析冗余式可以对系统进行故障检测和隔离。为了能够系统地得到尽量多的解析冗余式,提高故障的可隔离性,该方法首先建立风机的键合图模型,然后由键合图模型导出时间因果图,由时间因果图导出变量关系图,最后由变量关系图消除键合图中结点方程的未知变量得到解析冗余式。实验结果验证了采用该方法推导的解析冗余式能够用于风机参数故障的诊断。     

Developing efficient management strategies for a water supply system using system dynamics modelling

In this paper, the causal feedback relationships among the components that make up the working mechanism of water supply systems management, including key factors and their relationship to the management of water pipes, were identified based on the conceptual framework established for water supply systems management. Subsequently, a system dynamics computer simulation model, which can be used to aid efficient management of water supply systems, was developed. The computer model consisted of water supply, pipe maintenance, and water supply business finance sub-models. The model was verified using historical data from a water supply service case study. Using the verified model, long-term managerial and operating conditions of the case study system were predicted under optimistic, basic, and pessimistic management condition scenarios. In addition, sensitivity analyses on major indicators of the case study system have been presented to show that the developed model can facilitate identification of the best policy for achieving a specific management objective of a water supply system.