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In order to solve the problem of how to reduce the service delay of edge computing, this paper proposes an edge cloud framework, which contains four groups under different locations between mobile edge nodes and users. A feasible cost scheme can be obtained by calculating the cost in different simulation groups. Furthermore, we give suggestions on how to deploy edge nodes at a reasonable cost for users effectively.

This paper is motivated by the IoT-Cloud framework; they are divided according to whether the nodes have templates required by users and the distance from users to distinguish various consumption levels and classify the testing result. Based on four different groups satisfying reasonable resource allocation, the cost was studied. The work focuses on the unpredictable movement within the test range. For assignment and scheduling of template tasks at each time slot, the Edge-Cloud scheme is proposed to reduce the cost.

According to the simulation results in this paper, the total cost of the four groups is lower when the closest node-set satisfies the user service directly. To improve the probability that the closest node-set can meet general requests of users and provide them with faster and more economical network services, increasing the number of edge nodes within the range of user activities is suggested.

An Edge-Cloud framework is constructed in four groups, and the conclusion of a feasible cost scheme came out.

Different real cases indicate that the quality of a process is better monitored by a functional relationship rather than the traditional statistical process control (SPC) methods. This approach is referred to as profile monitoring. A serious objective in profile monitoring is the sensitivity of a model to very small changes of the process. The rapid progress of the precision manufacturing also indicates the importance of identifying very small shift types of a process/product profile curve. This sensitivity allows one to identify the fault of a process sooner compared to the case of lack of the capability.

This paper proposed a new method to monitor very small shift types of a polynomial profile for phase II of the SPC. The proposed method was named as MGWMA-PF. The performance capability of the proposed approach was evaluated through several numerical examples. A real case study was also used to investigate the capability of the proposed model.

The results addressed that the proposed method was capable of detecting very small shift types effectively. The numerical report based on the average run length (ARL) term revealed the more sensitivity of the proposed model compared to other existing methods of the literature.

This paper proposes a new method to monitor very small shift types of a polynomial profile for phase II of the SPC. The proposed method provides detecting a very small change manifested itself to the process.

The purpose of this paper, starting from a theoretical framework, is to analyze the spillover effects of human capital brought by labor mobility and their influence on the public education investment.

Based on the endogenous growth theory, the paper establishes a regional human capital spillover model to examine the spillover effects of human capital coming along with the regional labor mobility and the changes of public education investment decision brought by the spillover effects in China.

It has been found that the regional mobility of labor has made the developed areas gain the spillover benefits of human capital investment from the underdeveloped areas with their superiority of social and economic environment and restrained the incentives for public education investment in the underdeveloped areas, thus the different areas walk on a different growth path, with the expansion of the difference in the economic and education investment growth.

This paper analyzes the possible influences from the spillover of human capital on the economic growth and educational investment and finds a high possibility for the underdeveloped areas to get into a “low development trap” of education investment. The key to solving the problem is to internalize the externalities by the active public policy, in order to realize equal education, rational investment and balanced development.

This paper aims to model a technique that categorizes the texts from huge documents. The progression in internet technologies has raised the count of document accessibility, and thus the documents available online become countless. The text documents comprise of research article, journal papers, newspaper, technical reports and blogs. These large documents are useful and valuable for processing real-time applications. Also, these massive documents are used in several retrieval methods. Text classification plays a vital role in information retrieval technologies and is considered as an active field for processing massive applications. The aim of text classification is to categorize the large-sized documents into different categories on the basis of its contents. There exist numerous methods for performing text-related tasks such as profiling users, sentiment analysis and identification of spams, which is considered as a supervised learning issue and is addressed with text classifier.

At first, the input documents are pre-processed using the stop word removal and stemming technique such that the input is made effective and capable for feature extraction. In the feature extraction process, the features are extracted using the vector space model (VSM) and then, the feature selection is done for selecting the highly relevant features to perform text categorization. Once the features are selected, the text categorization is progressed using the deep belief network (DBN). The training of the DBN is performed using the proposed grasshopper crow optimization algorithm (GCOA) that is the integration of the grasshopper optimization algorithm (GOA) and Crow search algorithm (CSA). Moreover, the hybrid weight bounding model is devised using the proposed GCOA and range degree. Thus, the proposed GCOA + DBN is used for classifying the text documents.

The performance of the proposed technique is evaluated using accuracy, precision and recall is compared with existing techniques such as naive bayes, k-nearest neighbors, support vector machine and deep convolutional neural network (DCNN) and Stochastic Gradient-CAViaR + DCNN. Here, the proposed GCOA + DBN has improved performance with the values of 0.959, 0.959 and 0.96 for precision, recall and accuracy, respectively.

This paper proposes a technique that categorizes the texts from massive sized documents. From the findings, it can be shown that the proposed GCOA-based DBN effectively classifies the text documents.

We review and synthesize the existing research on directors' and officers’ (D&O) liability insurance. Our objectives are (1) to examine the institutional forces and regulatory requirements that have influenced the development of D&O liability insurance; (2) to identify the factors that influence firms to purchase D&O liability insurance and explore the consequences associated with its usage and (3) to identify gaps in the current literature and provide recommendations for future research on D&O liability insurance.

We perform a systematic literature review (SLR) using the Preferred Reporting Items for a Systematic Review of Meta-Analysis (PRISMA) guidelines to examine archival studies that investigate the determinants and consequences of D&O liability insurance. Using a Boolean search strategy on the “Web of Science” (WoS) and PRISMA selection criteria, we review 64 published archival research articles and three working papers from 1987 to October 2023.

Our review reveals that disclosing detailed information regarding D&O liability insurance, such as total insurance premiums and coverage limit, is predominantly voluntary, except in Taiwan. Our findings suggest that the decision to purchase D&O liability insurance is influenced by litigation risk, which is determined by factors such as firm size, complexity and corporate governance variables. We also find that D&O liability insurance has implications for financial reporting, audit outcomes, investment behavior and capital market performance.

In the post-COVID era, where firms face pressure due to financial constraints, our research emphasizes the practical importance of carefully considering and understanding the impact of D&O liability insurance, particularly as it concerns the demand for such insurance.

To the best of our knowledge, this study represents the first systematic review of previous research on D&O liability insurance. Our review highlights some research gaps, particularly in relation to the implications for financial reporting practices, auditing outcomes, firm investment behavior and capital market consequences.

This paper aims to analyze the morphology transformation on the Cu₃Sn grains during the formation of full Cu₃Sn solder joints in electronic packaging.

Because of the infeasibility of analyzing the morphology transformation intuitively, a novel equivalent method is used. The morphology transformation on the Cu₃Sn grains, during the formation of full Cu₃Sn solder joints, is regarded as equivalent to the morphology transformation on the Cu₃Sn grains derived from the Cu/Sn structures with different Sn thickness.

During soldering, the Cu₃Sn grains first grew in the fine equiaxial shape in a ripening process until the critical size. Under the critical size, the Cu₃Sn grains were changed from the equiaxial shape to the columnar shape. Moreover, the columnar Cu₃Sn grains could be divided into different clusters with different growth directions. With the proceeding of soldering, the columnar Cu₃Sn grains continued to grow in a feather of the width growing at a greater extent than the length. With the growth of the columnar Cu₃Sn grains, adjacent Cu₃Sn grains, within each cluster, merged with each other. Next, the merged columnar Cu₃Sn grains, within each cluster, continued to merge with each other. Finally, the columnar Cu₃Sn grains, within each cluster, merged into one coarse columnar Cu₃Sn grain with the formation of full Cu₃Sn solder joints. The detailed mechanism, for the very interesting morphology transformation, has been proposed.

Few researchers focused on the morphology transformation of interfacial phases during the formation of full intermetallic compounds joints. To bridge the research gap, the morphology transformation on the Cu₃Sn grains during the formation of full Cu₃Sn solder joints has been studied for the first time.

The purpose of this paper is to propose a partitioned approach by coupling the smoothed profile method (SPM) and the Euler tension beam model in simulating a vortex-induced vibration of both rigid and flexible cylinders at various reduced velocities.

For the fluid part, SPM in the framework of the spectral element method is adopted to simulate the flow. The advantage of SPM lies in modelling multiple complex shapes as it uses a fixed computational mesh without conformation to the geometry of the particles. For the structure part, an elastic-mounted rigid cylinder is considered in two-dimensional (2D) simulations, while a flexible cylinder with a Euler tension beam model is used in three-dimensional simulations.

Firstly, in the flow past a freely vibrating cylinder, the maximum vibration responses of the cylinder are about 0.73D and 0.1D in the y and x directions, respectively, which occur at the point U_r = 5.75 and are much higher than U_r = 5 in 2D simulations. It is found that the numerical results from the SPM solver are very consistent with those from the NEKTAR-Arbitrary Lagrangian Eulerian method (NEKTAR-ALE) solver or the NEKTAR-Fourier solver. Furthermore, the flow past the tandem cylinders is also investigated, where the upstream cylinder is static while the downstream one is free to vibrate. Specifically, the beating behaviour is captured from the vibration response of the freely vibrating cylinder under the reduced velocity of U_r = 6 with a gap distance of L = 3.5D.

The originality of the paper lies in coupling the SEM with the Euler beam model in simulating the vortex induced vibration (VIV) of flexible cylinders.

The purpose of this study is to achieve the dynamic model of outsourcing success factors in project-based companies.

This study is descriptive-survey in terms of method and practical in terms of purpose. To achieve the dynamic model of outsourcing success, 1,000 outsourcing articles published in high-status journals from 2017 to 2019 were first text-mining. Then, using the clustering technique, the factors affecting the success of outsourcing were obtained. To achieve the key variables, the variables obtained by interpretive structural modeling (ISM) were then leveled. Then, the strategic options development and analysis (SODA) technique has been used to achieve a consensus and coordination on factors relationships. Finally, the dynamic model of outsourcing success in GHODRAT CONTROL PARS Company has been modeled and implemented.

In total, five clusters and nine factors were extracted (strategy, management, performance, market, R&D, supplier, product, organizational data and outsourcing findings). In central and domain analysis, two factors, “Strategy” and “R and D,” were recognized as factors that have the most interaction and centrality. The result of the dynamic model indicate that the organization will significantly reduce the construction time of the power plant by improving the “R and D” factor.

In this study, various techniques have been combined. Therefore, one of the aspects of innovation in the present study is the combination of methods that have not been used earlier. The second aspect of this study’s innovation is using SODA technique to design the dynamic model of outsourcing success factors. Given that the scope of this study is the component affecting the success of outsourcing, so extensive research has been conducted in the field of articles worked in the field of outsourcing to get a comprehensive view of the components affecting the success of outsourcing, which has not been reviewed in other articles. In this study, in addition to identifying the effective factors, their identified and also how these variables affect the successful performance of outsourcing in the form of a dynamic model, and then analyzed.

When a reflected shock interacts with the boundary layer in a shock tube, the shock bifurcation occurs near the walls. Although the study of the shock bifurcation has been carried out by many researchers for several decades, little attention has been devoted to investigate the instability pattern of the bifurcation. This research work aims to successfully capture the asymmetry of the whole flow field, and attempt to achieve the instability mechanism of the shock bifurcation by a direct numerical simulation of the reflected shock wave/boundary layer interaction at Ma = 1.9. In addition, the reason for the formation of the bifurcated structure is also explored.

The spatial and temporal evolution of the shock bifurcation is obtained by solving the two-dimensional compressible Navier–Stokes equations using a seventh-order accurate weighted essentially non-oscillatory (WENO) scheme and a three-step Runge–Kutta time advancing approach.

The results show that the formation of shock bifurcation is mainly because of the shock/gradient field interaction, and the height of the bifurcated foot increases with the growth of the shock intensity and the gradient field. The unsteady asymmetry of the upper and bottom shock bifurcated structures is because of the vortex shedding with high frequency in the rear recirculation zone, which leads to the fluctuation of the recirculation area. The vortex shedding process behind the bifurcated structure closely resembles the Karman vortex street formed by the flow around the cylinder. The dimensionless vortex shedding frequency varies between 0.01 and 0.02. In comparison to the scenario at Ma = 1.9, the occurring time of instability is delayed and the upper and bottom bifurcated feet intersect in a relatively short time at Ma = 3.5. The region behind the bifurcated shock is a transitional flow field containing obvious cell structures and “isolated islands.”

This paper discovers an unsteady flow pattern of the shock bifurcation, and the mechanism of this instability in the reflected shock/boundary layer interaction is revealed in detail.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.