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In this paper, a three-dimensional size-dependent constitutive model of SMP Timoshenko micro-beam is developed to describe the micromechanical properties.

According to the Hamilton's principle, the equilibrium equations and boundary conditions of the model are established and according to the modified couple stress theory, the model is available to capturing the size effect because of the material length scale parameter. Based on the model, the simply supported beam was taken for example to be solved and simulated.

Results show that the size effect of SMP micro-beam is more obvious when the dimensionless beam height is similar or the larger of the value of loading time. The rigidity and strength of the SMP beam decrease with the increasing of the dimensionless beam height or the loading time. The viscous property of SMP micro-beam plays a more important role with the larger dimensionless beam height. And the smaller the dimensionless beam height is, the more obvious the shape memory effect of the SMP micro-beam is.

This work implies prediction of size-dependent thermo-mechanical behaviors of the SMP micro-beam and will provide a theoretical basis for design SMP microstructures in the field of micro/nanomechanics.

Although the prior literature has identified the relevance of dealer participation for multinational enterprises (MNEs), it is unclear whether such participation could also be an important means for local dealers to learn from MNEs. By adopting local firms’ viewpoint, our study draws on organizational learning theory to examine how local dealers benefit from their participation with foreign suppliers in Africa.

The empirical setting is a combinative dataset of secondary data and primary survey of 164 small- and medium-sized local dealers with nine subsidiaries of a Chinese motorcycle company in six countries of Sub-Saharan Africa.

This research shows that dealer participation is positively associated with dealer performance, and this positive effect is stronger when local dealers operate in regions with low government corruption and high government support. However, the positive relationship is weaker when local dealers use the local tongue extensively but becomes stronger when their foreign suppliers have a high dealer coverage.

By taking a local-participant perspective, our study extends the participation literature to show how firms from a resource-constrained region may benefit from their proactive participation with foreign counterparts. Additionally, we identify the boundary conditions of institutional factors and strategic choices of local dealers and foreign suppliers, providing a nuanced understanding of firm behaviors in complex and uncertain markets.

This paper aims to investigate the bonding of the photonic integrated circuit (PIC) chip with the heat sink using the AlNi self-propagating soldering method.

Compared to industrial optical modules, optical modules for aerospace applications require better reliability and stability, which is hard to achieve via the dispensing adhesive process that is used for traditional industrial optical modules. In this paper, 25 µm SAC305 solder foils and the AlNi nanofoil heat source were used to bond the back of the PIC chip with the heat sink. The temperature field and temperature history were analyzed by the finite element analysis (FEA) method. The junction-to-case thermal resistance is 0.0353°C/W and reduced by 85% compared with the UV hybrid epoxy joint.

The self-propagating reaction ends within 2.82 ms. The maximum temperature in the PIC operating area during the process is 368.5°C. The maximum heating and cooling rates of the solder were 1.39 × 107°C/s and −5.15 × 106°C/s, respectively. The microstructure of SAC305 under self-propagating reaction heating is more refined than the microstructure of SAC305 under reflow. The porosity of the heat sink-SAC305-PIC chip self-propagating joint is only 4.7%. Several metastable phases appear as AuSn3.4 and AgSn3.

A new bonding technology was used to form the bonding between the PIC chip with the heat sink for the aerospace optical module. The reliability and thermal resistance of the joint are better than that of the UV hybrid epoxy joint.

This study aims to suggest and develops a global sensitivity analysis-assisted multi-level sequential optimization method for the heat transfer problem.

Compared with other surrogate-assisted optimization methods, the distinctive characteristic of the suggested method is to decompose the original problem into several layers according to the global sensitivity index. The optimization starts with the several most important design variables by the support vector regression-based efficient global optimization method. Then, when the optimization process progresses, the filtered design variables should be involved in optimization one by one or the setting value. Therefore, in each layer, the design space should be reduced according to the previous optimization result. To improve the accuracy of the global sensitivity index, a novel global sensitivity analysis method based on the variance-based method incorporating a random sampling high-dimensional model representation is introduced.

The advantage of this method lies in its capability to solve complicated problems with a limited number of sample points. Moreover, to enhance the reliability of optimum, the support vector regression-based global efficient optimization is used to optimize in each layer.

The developed optimization tool is built by MATLAB and can be integrated by commercial software, such as ABAQUS and COMSOL. Lastly, this tool is integrated with COMSOL and applied to the plant-fin heat sink design. Compared with the initial temperature, the temperature after design is over 49°. Moreover, the relationships among all design variables are also disclosed clearly.

The D-MORPH-HDMR is integrated to obtain the coupling relativities among the design variables efficiently. The suggested method can be decomposed into multiplier layers according to the GSI. The SVR-EGO is used to optimize the sub-problem because of its robustness of modeling.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show the usage of this information in financial decision processes.

Need for the Study: Main financial reports such as balance sheets and income statements can be analysed by statistical methods. However, an expanded financial reporting framework needs new analysing methods due to unstructured and big data. The study offers a solution to the analysis problem that comes with non-financial reporting, which is an essential communication tool in corporate reporting.

Methodology: Text mining analysis of annual reports is conducted using software named R. To simplify the problem, we try to predict the companies’ corporate governance qualifications using text mining. K Nearest Neighbor, Naive Bayes and Decision Tree machine learning algorithms were used.

Findings: Our analysis illustrates that K Nearest Neighbor has classified the highest number of correct classifications by 85%, compared to 50% for the random walk. The empirical evidence suggests that text mining can be used by all stakeholders as a financial analysis method.

Practical Implications: Combining financial statement analyses with financial reporting analyses will decrease the information asymmetry between the company and stakeholders. So stakeholders can make more accurate decisions. Analysis of non-financial data with text mining will provide a decisive competitive advantage, especially for investors to make the right decisions. This method will lead to allocating scarce resources more effectively. Another contribution of the study is that stakeholders can predict the corporate governance qualification of the company from the annual reports even if it does not include in the Corporate Governance Index (CGI).

This paper aims to offer a comprehensive examination of the various solutions currently accessible for addressing the challenge of semantic interoperability in cyber physical systems (CPS). CPS is a new generation of systems composed of physical assets with computation capabilities, connected with software systems in a network, exchanging data collected from the physical asset, models (physics-based, data-driven, . . .) and services (reconfiguration, monitoring, . . .). The physical asset and its software system are connected, and they exchange data to be interpreted in a certain context. The heterogeneous nature of the collected data together with different types of models rise interoperability problems. Modeling the digital space of the CPS and integrating information models that support cyber physical interoperability together are required.

This paper aims to identify the most relevant points in the development of semantic models and machine learning solutions to the interoperability problem, and how these solutions are implemented in CPS. The research analyzes recent papers related to the topic of semantic interoperability in Industry 4.0 (I4.0) systems.

Semantic models are key enabler technologies that provide a common understanding of data, and they can be used to solve interoperability problems in Industry by using a common vocabulary when defining these models.

This paper provides an overview of the different available solutions to the semantic interoperability problem in CPS.

The purpose of this study is to present the state of the art for fiber Bragg grating (FBG) acceleration sensing technologies from two aspects: the principle of the measurement dimension and the principle of the sensing configuration. Some commercial sensors have also been introduced and future work in this field has also been discussed. This paper could provide an important reference for the research community.

This review is to present the state of the art for FBG acceleration sensing technologies from two aspects: the principle of the measurement dimension (one-dimension and multi-dimension) and the principle of the sensing configuration (beam type, radial vibration type, axial vibration type and other composite structures).

The current research on developing FBG acceleration sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of a new information detection method. This paper hypothesizes that in the future, the following research trends will be strengthened: common single-mode fiber grating of the low cost and high utilization rate; high sensitivity and strength special fiber grating; multi-core fiber grating for measuring single-parameter multi-dimensional information or multi-parameter information; demodulating equipment of low cost, small volume and high sampling frequency.

The principle of the measurement dimension and principle of the sensing configuration for FBG acceleration sensors have been introduced, which could provide an important reference for the research community.