Financial Reporting Quality, Corporate Governance, and Idiosyncratic Risk: Evidence from a Frontier Market

We extend current literature by providing empirical evidence on the impacts of financial reporting quality and corporate governance mechanism - two firm-level determinants that are strongly affected by the unique market setting and regulatory framework in emerging/frontier markets - and idiosyncratic risk in Vietnam. Utilizing different panel data analysis techniques, we find high-quality financial reports can mitigate firm-specific risk. Firms with high state ownership tend to have lower idiosyncratic risk too, implying the monitoring role of the government. We also document a positive link between board size and firm specific risk. Our results are thus beneficial for industry regulators and firms in ensuring good governance and reporting framework to better manage firm risk

Synthesis and Investigation of the Physical Properties of Lead-Free BCZT Ceramics

This work presents the structure, microstructure, and physical properties of low sintering temperature lead-free ceramics 0.52(Ba0.7Ca0.3)TiO3-0.48Ba(Zr0.2Ti0.8)O3 doped with nano-sized ZnO particles (noted as BCZT/x, x is the content of ZnO nanoparticles in wt.%, x = 0.00, 0.05, 0.10, 0.15, 0.20, and 0.25). The obtained results of Raman scattering and dielectric measurements have confirmed that Zn2+ has occupied B-site, to cause a deformation in the ABO3-type lattice of the BCZT/x specimens. The 0.15 wt.% ZnO-modified ceramic sintered at 1350°C exhibited excellent piezoelectric parameters: d33 = 420 pC/N, d31 = −174 pC/N, kp = 0.483, kt = 0.423, and k33 = 0.571. The obtained results indicate that the high-quality lead-free BCZT ceramic could be successfully synthesized at a low sintering temperature of 1350°C with an addition of appropriated amount of ZnO nanoparticles. This work also reports the influence of the sintering temperature on structure, microstructure, and piezoelectric properties of BCZT/0.15 compound. By rising sintering temperature, the piezoelectric behaviors were improved and rose up to the best parameters at a sintering temperature of 1450°C (d33 = 576 pC/N and kp = 0.55). The corresponding properties of undoped BCZT ceramics were investigated as a comparison. It also presented that the sintering behavior and piezo-parameters of doped BCZT samples are better than the undoped BCZT samples at each sintering temperature

Damage detection for a cable-stayed Bridge under the effect of moving loads using Transmissibility and Artificial Neural Network

Artificial Neural Network (ANN) has been widely used for Structural Health Monitoring (SHM) in the last decades. To detect damage in the structure, ANN often uses input data consisting of natural frequencies or mode shapes. However, this data is not sensitive enough to accurately identify minor structural defects. Therefore, in this study, we propose to use transmissibility to generate input data for the input layer of ANN. Transmissibility uses output signals exclusively to preserve structural dynamic properties and is sensitive to damage characteristics. To evaluate the efficiency of the proposed approach, a cable-stayed bridge with a wide variety of damage scenarios is employed. The results show that the combination of transmissibility and ANN not only accurately detect damages but also outperforms natural frequencies-based ANN in terms of accuracy and computational cost

Damage detection for a cable-stayed Bridge under the effect of moving loads using Transmissibility and Artificial Neural Network

Artificial Neural Network (ANN) has been widely used for Structural Health Monitoring (SHM) in the last decades. To detect damage in the structure, ANN often uses input data consisting of natural frequencies or mode shapes. However, this data is not sensitive enough to accurately identify minor structural defects. Therefore, in this study, we propose to use transmissibility to generate input data for the input layer of ANN. Transmissibility uses output signals exclusively to preserve structural dynamic properties and is sensitive to damage characteristics. To evaluate the efficiency of the proposed approach, a cable-stayed bridge with a wide variety of damage scenarios is employed. The results show that the combination of transmissibility and ANN not only accurately detect damages but also outperforms natural frequencies-based ANN in terms of accuracy and computational cost

Ranking load in microgrid based on fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution algorithm for load shedding problem

This paper proposes a method to rank the loads in the microgrid by means of a weight that combines the criteria together in terms of both technical and economic aspects. The fuzzy analytic hierarchy process technique for order of preference by similarity to ideal solution (fuzzy AHP TOPSIS) algorithm is used to calculate this combined weight. The criteria to be considered are load importance factor (LIF), voltage electrical distance (VED) and voltage sensitivity index (VSI). The fuzzy algorithm helps to fuzzy the judgment matrix of the analytic hierarchy process (AHP) method, making it easier to compare objects with each other and remove the uncertainty of the AHP method. The technique for order of preference by similarity to ideal solution (TOPSIS) algorithm is used to normalize the decision matrix, determine the positive and negative ideal solutions to calculate the index of proximity to the ideal solution, and finally rank all the alternatives. The combination of fuzzy AHP and TOPSIS algorithms is the optimal combination for decision making and ranking problems in a multi-criteria environment. The 19-bus microgrid system is applied to calculate and demonstrate the effectiveness of the proposed method