A New MEMS Stochastic Model Order Reduction Method: Research and Application

Modeling and simulation of MEMS devices is a very complex tasks which involve the electrical, mechanical, fluidic, and thermal domains, and there are still some uncertainties that need to be accounted for during the robust design of MEMS actuators caused by uncertain material and/or geometric parameters. According to these problems, we put forward stochastic model order reduction method under random input conditions to facilitate fast time and frequency domain analyses; the method makes use of polynomial chaos expansions in terms of the random input variables for the matrices of a finite element model of the system and then uses its transformation matrix to reduce the model; the method is independent of the MOR algorithm, so it is seamlessly compatible with MOR method used in popular finite element solvers. The simulation results verify the method is effective in large scale MEMS design process

Earnings Forecasts and Price Efficiency after Earnings Realizations: Reduction in Information Asymmetry through Learning from Price*

When information asymmetry is a major market friction, earnings forecasts can lead to higher price efficiency even after the information in forecasts completely dissipates upon earnings realizations. We show this in an experimental market that features information asymmetry (i.e., some traders possess differential private information). Earnings forecasts reduce information asymmetry and lead to prices that reflect a greater amount of private information. Traders can learn more about others\u27 information from prices. This information learned from past prices continues to reduce information asymmetry and improve price efficiency even after earnings realizations. We contribute to the disclosure literature by showing the evidence that the learning-from-price effect amplifies the impact of public disclosure on price efficiency

Short interest and corporate investment: Evidence from supply chain partners

SOAR at SMU; Lee Kong Chian Professorshi

Home country investor protection, ownership structure and cross-listed firms' compliance with SOX-mandated internal control deficiency disclosures

We examine whether home country investor protection and ownership structure affect cross-listed firms' compliance with SOX-mandated internal control deficiency (ICD) disclosures. We develop a proxy for the likelihood of cross-listed firms' ICD misreporting during the Section 302 reporting regime. For cross-listed firms domiciled in weak investor protection countries, we have three main findings. First, firms whose managers control their firms and have voting rights in excess of cash flow rights are more likely to misreport ICD than other firms during the Section 302 reporting regime. Second, there is a positive association between the likelihood of ICD misreporting and voluntary deregistration from the SEC prior to the Section 404 effective date. Third, for firms that chose not to deregister, there is a positive association between the likelihood of ICD misreporting and the reporting of previously undisclosed ICDs during the Section 404 reporting regime. We do not find similar evidence for cross-listed firms domiciled in strong investor protection countries. Our findings are consistent with the hypothesis that, for cross-listed firms domiciled in weak investor protection countries, managers who have the ability and incentive to expropriate outside minority shareholders are reluctant to disclose ICDs in order to protect their private control benefits. The results of our study should be of interest to regulators who wish to identify noncompliant firms for closer supervision, investors who wish to identify ex ante red flags for poor financial disclosure quality, and researchers who wish to understand the economic forces governing cross-listed firms' financial disclosure behavior

Multi-Functional Loader Steering Hydraulic System model construction and simulation Based on Power Bond Graphs

AbstractHydraulic steering system has been extensively applied in small type of loader and other engineering vehicles do to its special superority, how to forecast its dynamic behavior in design stage is most impotant problem. This paper firstly analyse a typical steering hydraulic system of multi-functional loader, and construct its powder bond graphs, then decuce its state equations.with these equations, some hydraulic component have been encapsulated in soft Mworks, at last, a simpled steering hydraulic dynamaic simulation model was constructed by these components, and some characteristic curves of system can be easily abtained

Pavement Performance Investigation of Nano-TiO₂/CaCO₃ and Basalt Fiber Composite Modified Asphalt Mixture under Freeze‒Thaw Cycles

The objective of this research is to evaluate the pavement performance degradation of nano-TiO2/CaCO3 and basalt fiber composite modified asphalt mixtures under freeze‒thaw cycles. The freeze‒thaw resistance of composite modified asphalt mixture was studied by measuring the mesoscopic void volume, stability, indirect tensile stiffness modulus, splitting strength, uniaxial compression static, and dynamic creep rate. The equal-pitch gray prediction model GM (1, 3) was also established to predict the pavement performance of the asphalt mixture. It was concluded that the high- and low-temperature performance and water stability of nano-TiO2/CaCO3 and basalt fiber composite modified asphalt mixture were better than those of an ordinary asphalt mixture before and after freeze‒thaw cycles. The test results of uniaxial compressive static and dynamic creep after freeze‒thaw cycles showed that the high-temperature stability of the nano-TiO2/CaCO3 and basalt fiber composite modified asphalt mixture after freeze‒thaw was obviously improved compared with an ordinary asphalt mixture