Search results

The paper aims to study cut resistant property of basic weft plain-knitted fabric for protective clothing.

Effects of fiber materials, fabric direction and knitting technology (sinking-depth) were explored, respectively. Cut process of fabric was tracked and the theoretical analysis was provided to evaluate energy transferring of cutting. Fiber-based cut behavior was observed by SEM images. Deformation energy stored in the loop due to yarn bending was regard as initial elastic potential energy of the fabric, which was related to loop structure.

Cut resistance of the fiber material was the dominant factor for cut resistance of weft plain-knitted fabric, while unit loop structure played a critical role in improving cut resistance.

Cut resistance of the fiber material was the dominant factor for cut resistance of weft plain-knitted fabric, while the unit loop structure played a critical role in improving cut resistance.

The paper provides theoretical support of developing flexible protective clothing.

This study aims to build on equity theory to assess the effect of chief executive officer (CEO) underpayment on the accumulation of firm-specific knowledge, accounting for the moderating effects of the CEO compensation gap and the clarity of the board’s informal hierarchy.

This study starts with all firms listed in the Execucomp database for the period 1992 to 2006. Then, all data sources are merged and entries with missing information are excluded. The final data set used for model estimations includes 1,152 firm-year observations. The command xtreg in Stata 12 with the fixed-effect option (fe) is used to estimate the relationship between CEO underpayment and firm-specific knowledge.

This study proposed and examined the role of CEO underpayment in discouraging CEO willingness to invest firm-specific human capital and, accordingly, to adopt a strategy of accumulating lower levels of firm-specific knowledge assets. The empirical analyses strongly support this argument. Moreover, CEO compensation gaps and the informal hierarchy of boards negatively moderated this relationship. That is, CEO underpayment had a weaker negative effect on firm-specific knowledge when the CEO compensation gap and the clarity of the board’s informal hierarchy were high.

Prior studies from the knowledge-based perspective have focused on the importance of firm-specific knowledge in enabling a firm to achieve superior financial performance. However, relatively little attention has been paid to CEOs’ willingness to accumulate firm-specific knowledge. The present study contributes to the knowledge-based view of the firm. This study integrates equity theory with the knowledge-based view of the firm by highlighting how unfair compensation of CEOs may discourage them to fully realize a firm’s potential to generate specific knowledge. By incorporating the fairness issue of CEO compensation into the knowledge-based view, this study contributes to a deeper understanding of the origins of firm-specific knowledge.

The safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system. Through voiceprint technology, the sounds emitted by the transformer can be monitored in real-time, thereby achieving real-time monitoring of the transformer’s operational status. However, the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer, severely impacting the accuracy and reliability of voiceprint identification. Therefore, effective preprocessing steps are required to identify and separate the sound signals of transformer operation, which is a prerequisite for subsequent analysis.

This paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique (REPET) algorithm to separate and denoise the transformer operation sound signals. By analyzing the Short-Time Fourier Transform (STFT) amplitude spectrum, the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold, effectively distinguishing and extracting stable background signals from transient foreground events. The REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period, then constructs a repeating segment model. Through comparison with the amplitude spectrum of the original signal, repeating patterns are extracted and a soft time-frequency mask is generated.

After adaptive thresholding processing, the target signal is separated. Experiments conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation effects.

A REPET method with adaptive threshold is proposed, which adopts the dynamic threshold adjustment mechanism, adaptively calculates the threshold for blind source separation and improves the adaptability and robustness of the algorithm to the statistical characteristics of the signal. It also lays the foundation for transformer fault detection based on acoustic fingerprinting.