Novel Symmetric Numerical Methods for Solving Symmetric Mathematical Problems

The mathematical model for many problems is arising in different industries of natural science, basically formulated using differential, integral and integro-differential equations. The investigation of these equations is conducted with the help of numerical integration theory. It is commonly known that a class of problems can be solved by applying numerical integration. The construction of the quadrature formula has a direct relation with the computation of definite integrals. The theory of definite integrals is used in geometry, physics, mechanics and in other related subjects of science. In this work, the existence and uniqueness of the solution of above-mentioned equations are investigated. By this way, the domain has been defined in which the solution of these problems is equivalent. All proposed four problems can be solved using one and the same methods. We define some domains in which the solution of one of these problems is also the solution of the other problems. Some stable methods with the degree p<=8 are constructed to solve some problems, and obtained results are compared with other known methods. In addition, symmetric methods are constructed for comparing them with other well-known methods in some symmetric and asymmetric mathematical problems. Some of our constructed methods are compared with Gauss methods. In addition, symmetric methods are constructed for comparing them with other well-known methods in some symmetric and asymmetric mathematical problems. Some of our constructed methods are compared with Gauss methods. On the intersection of multistep and hybrid methods have been constructed multistep methods and have been proved that these methods are more exact than others. And also has been shown that, hybrid methods constructed here are more exact than Gauss methods. Noted that constructed here hybrid methods preserves the properties of the Gauss method.

Application of Acoustic Agglomeration Technology to Improve the Removal of Submicron Particles from Vehicle Exhaust

The natural processes of interactions between aerosol particles in the ambient air through which they agglomerate is a vast area of chamber research and are inherent to many industries and are often inter-connected with transport engineering. Further improvement of symmetric methods for aerosol particle number and mass concentration reduction made it possible to create various synergic techniques. The study used a 1.9 TDI diesel internal combustion engine, which was supplied with diesel (D100) and second-generation biofuels (NExBTL100) with the EGR exhaust system on and off. Measurements were performed using a Bruel and Kjær “Type 9727” system for measurement of vibrations, a scanning mobility particle sizer (SMPS) and an original agglomeration chamber. The three modes of particle size distributions were observed in the size range from 10 to 470 nm for both D100 and NExBTL100 fuels with and without the use of the EGR system. The application of 21.3 kHz frequency sound with SPL 144.1 dB changed the NExBTL100 generated aerosol particle number concentration but did not sufficiently affect the concentration of D100 emitted particles. The greatest agglomeration effect (21.7 ± 10.0%) was observed in the range of extremely small NExBTL100 derived particles (10–70 nm) when used in combination with an EGR system.

Recipes for customer loyalty: a cross-country study of the hotel industry

Purpose Based on the tenets of complexity theory, the purpose of the study is to identify the causal recipes that can lead to improved customer loyalty. Design/methodology/approach A cross-country sample was drawn from Pakistan, China and Italy to explore customers’ hotel experiences. The study used asymmetrical fuzzy set qualitative comparative analysis (fsQCA) to unearth the recipes of antecedent conditions that can predict high scores in customer loyalty. Findings The study results complementing the major tenets of complexity theory found several recipes in each of the countries that can lead to improved customer loyalty. Practical implications Instead of focusing on individual factors, and how they impact loyalty, the study will help hotel management to understand the complexity of loyalty and it may not be improved through individual focus on antecedent conditions, instead, different pathways/recipes can help improve the loyalty. The study will help managers uncover alternative ways to attain increasing customer loyalty. The results reveal that customers in different countries have varied paths leading to loyalty, showing that hotel administration should not consider all customers as equal, with changing culture there is a change in how high loyalty may be achieved. Originality/value Customer loyalty is a complex construct, and the latest research reveals that symmetric methods have significant limitations, as they view loyalty as an outcome of isolated antecedents. Symmetric methods are less informative and have limited theoretical implications. Drawing on the tenets of complexity theory the study contributes to the loyalty literature in the hotel industry by highlighting the causal configurations leading to improved customer loyalty.

Robust regression with asymmetric loss functions

In robust regression, it is usually assumed that the distribution of the error term is symmetric or the data are symmetrically contaminated by outliers. However, this assumption is usually not satisfied in practical problems, and thus if the traditional robust methods, such as Tukey’s biweight and Huber’s method, are used to estimate the regression parameters, the efficiency of the parameter estimation can be lost. In this paper, we construct an asymmetric Tukey’s biweight loss function with two tuning parameters and propose a data-driven method to find the most appropriate tuning parameters. Furthermore, we provide an adaptive algorithm to obtain robust and efficient parameter estimates. Our extensive simulation studies suggest that the proposed method performs better than the symmetric methods when error terms follow an asymmetric distribution or are asymmetrically contaminated. Finally, a cardiovascular risk factors dataset is analyzed to illustrate the proposed method.

Accuracy of Symmetric Multi-Step Methods for the Numerical Modelling of Satellite Motion

Stability of high-order linear multistep St¨ormer-Cowell and symmetric methods are discussed in detail in this paper. Efficient algorithms for obtaining intervals of absolute stability and periodicity are given for these methods. To demonstrate the accuracy of numerical integration of the orbit over an interval about one year two model problems are considered. First problem is the 3D Kepler problem. Second one is a specially designed 3D model problem that has the exact solution and simulates the Earth-Moon-satellite system

Knowledge management processes, knowledge worker satisfaction, and organizational performance

Purpose Drawing on the knowledge-based view, the purpose of this paper is to investigate the interrelationship between Knowledge Management (KM) processes, Knowledge Worker Satisfaction (KWS) and Organizational Performance (OP). Additionally, the study further seeks to identify the combinations of KM processes and KWS dimensions that can lead to enhanced OP. Design/methodology/approach Data were collected from 248 academics and administration employees of Higher Education Institutions (HEIs). The relationships were tested using SmartPLS 3.2.7. The study also employed fuzzy set Qualitative Comparative Analysis (fsQCA) for examining configurational paths. Findings The results of the study revealed that KM processes significantly affect KWS and KWS enhances OP in HEIs. Based on fsQCA, the results revealed multiple configurational paths to improved OP. Originality/value There is significant lack of research that ascertains the inter-relationship between KM processes, KWS, and OP. This is one of the initial studies that examines the relationship of KM processes, KWS, and OP in HEI’s. From a methodological perspective, the study contributes by combining symmetric and asymmetric statistical tools in KM literature. fsQCA helps to understand the interactions that might not be immediately obvious through traditional symmetric methods.

Damage identification in welded structures using symmetric excitation of Lamb waves

Damage monitoring systems based on Lamb wave health monitoring technology have attracted considerable attention for scientific research and industrial applications. In this article, two types of single-mode Lamb waves are obtained using symmetric and anti-symmetric methods, respectively, to determine a crack identification signal. A numerical simulation of a welded steel plate model was conducted using the ABAQUS/EXPLICIT module, which is a dynamic solver. The propagation process and the corresponding effect of the Lamb waves over the complete and damaged models are simulated. According to the propagation characteristics and with the assistance of the ellipse localization method with MATLAB, the location of crack damage is simulated by the amplitude addition method and the crack damage location is determined. The results show that the simulation results are in good agreement with the actual crack damage. Furthermore, the received signals are compared and analyzed from an energy perspective. Two types of single-mode Lamb wave monitoring methods are also compared. In addition, it is demonstrated that a symmetric excitation can simplify the received waves and recognize crack damage in plates in welded steel structures from an experimental perspective of this work.