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This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.

The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.

The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.

An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.

A trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.

Six volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.

The AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

This paper aims to introduce the quasi impedance source inverter (qZSI)-based static compensator (STATCOM), which is incorporated into the hybrid distributed power generation system for enhancement of power quality. The distributed power generation system includes the photovoltaic (PV), wind energy conversion system (WECS) and battery energy storage system.

The WECS is used by the self-excited induction generator (SEIG) and the flywheel energy storage system (FESS). To regulate its terminal voltage and frequency, the SEIG requires adjustable volt-ampere reactive (VAR). A combination of a STATCOM and a fixed condenser bank usually serves to satisfy the VAR demand. The maximum correntropy criterion-based adaptive filter technique (AFT) is proposed to control the qZSI-STATCOM and to guarantee that the voltage at the SEIG terminal is harmonic-free while providing non-linear three-phase and single-phase loads.

The coordinated operation of the suggested voltage control and flywheel control systems ensures that load voltage and frequency are retained in their respective values at very low harmonic distortions regardless of wind speed and load variation. The simulation and experimental studies are carried out under different load conditions to validate the efficiencies of the PV-assisted STATCOM.

To improve system stability and minimize total costs, extra load current sensors can also be avoided. This paper proposes to control the SEIG terminal voltage and harmonic elimination in the standalone WECS systems using maximum correntropy criterion-based AFT with a fuzzy logic controller.

Extensive empirical evidence suggests that procedural justice (PJ) and distributive justice (DJ) are key success factors for achieving durable peace negotiations. This paper aims to investigate how complexity affects these factors and the outcomes in negotiations.

The qualitative study is based on an examination of the peace negotiations that led to the 2016 agreement between the Fuerzas Armadas Revolucionarias de Colombia – Ejército del Pueblo and the Colombian Government. Based on document analysis, the authors examined in detail how and where in the process the principles of PJ and DJ were applied. The authors then examined the implementation progress after 2016 and placed the peace process in the overall context of the Colombian conflict.

The authors found that the principles of PJ and DJ were present in both the negotiation process and the agreement. The negotiations were successful and satisfactory solutions could be found for all issues. The complexity of the conflict is reflected in the limited coverage of the peace negotiations. Not all groups, interests and subconflicts could be included in the negotiations. This limits their contribution to a durable peace in Colombia. Conflicts that remain unresolved also have a negative effect on the implementation of the agreement.

For conflict management, this implies that the negotiations should not be viewed as “one-and-done” but rather as a progressive, ongoing process. The agreement is only the nucleus for achieving total peace. It must be actively advanced and defended.

This study offers new qualitative insights into how PJ and DJ function in negotiations. It also establishes a systematic connection between PJ and DJ and complexity, introduces the notion of coverage and, thereby, opens a new perspective on the management of conflict complexity.

To simplify the circuit design and control complexity of the magnetic coupling resonant wireless charging system, the radio energy transmission constant current and constant voltage charging is realized.

The purpose of this study is to simplify the circuit design and control complexity of the magnetic coupling resonance wireless charging system, in order to achieve constant current and constant voltage charging for wireless energy transmission. First, the principle of LCC/S-S compensation structure is analyzed, and the equivalent mathematical model is established; then, the system characteristics under constant current and constant voltage mode are analyzed, and the design method of system parameters is given; finally, a simulation and experimental system is built to verify the correctness and feasibility of the theoretical analysis.

The results show that the proposed hybrid topology can achieve a constant current output of 2 A and a constant voltage output of 30 V under variable load conditions, and effectively suppress the current distortion problem under light load conditions. The waveform distortion rate of the inverter current is reduced from 33.97% to 10.45%.

By changing the high-order impedance characteristics of the compensation structure, the distortion of the current waveform under light load is suppressed, and the overall stability and efficiency of the system are improved.

Higher education has experienced some significant changes over the past few years including a highly competitive landscape, use of new technology, managing COVID protocols and guiding students to resources that ensure their success. With prior research highlighting the changes in the workforce and poor working conditions of part-time faculty, this study aims to explore full-time perceptions of several employment-related variables to determine how these significant workplace changes have impacted them.

A mixed-methods approach is used. This includes a questionnaire being sent out via e-mail to faculty at a medium-sized, public, regional university located in the USA. This was sent through two separate listservs: full-time faculty listserv and part-time faculty listserv. The questionnaire included quantitative and qualitative questions. A one-way ANOVA was used to detect significant differences between the two groups of interest for the quantitative components. The qualitative portions of the questionnaire provided deeper insights into employee perceptions of their workplace.

This research uncovers some alarming trends for full-time faculty within higher education. Across several different employment variables, full-time faculty perceptions are significantly worse than part-time faculty. This includes work–family conflict, pay perceptions, compensation opportunities, online teaching experiences, overwhelming work activities, technology provided, travel funding provided, perceived satisfaction of a faculty advocate and perceived benefits of a faculty advocate. Qualitative and quantitative results support these findings and provide additional clarification as to why they have these negative workplace perceptions.

A convenience sample was used, where data was only gathered from one university. Future research could replicate finding with more universities varying in their make-up and location to determine if these results hold across the USA and internationally. Some measures did not use established scales in the literature, and some were single-item measures. Future research could replicate findings using established scales with multi-item measures to provide more confidence the results produced that are reliable and valid.

These results suggest alarming concerns for higher education institutions regarding their full-time faculty. Human resource managers and administrators at universities should respond to “the alarm” from this research and internal employee satisfaction surveys they have conducted with their employees. Changes should be made at higher education institutions to improve employee workplace perceptions in hopes of retaining valuable employees and improving worker morale to increase productivity. The recent workplace changes and challenges for full-time faculty are negatively impacting their workplace perceptions.

As a result of full-time faculty having significantly worse perceptions across all measured employment variables than their part-time colleagues, who already had poor perceptions, the authors may see more “good” employees leaving the industry for other more lucrative options. Others may become “dead wood” in the university and engage in “quite quitting” resulting in less productivity. With the tenure process protecting professors, this may result in universities being “stuck” with many unmotivated professors and hurt the quality of educational services provided. Some professors may even act out negatively toward the university. This could damage the quality of education provided at universities and perceptions of higher education by society.

To the best of the authors’ knowledge, this is the first study comparing full-time and part-time faculty workplace perceptions across several variables. After previous study has highlighted the poor work conditions and perceptions of part-time faculty, this study adds to the discussion showing that significant changes in the workplace have resulted in full-time faculty now perceiving their employment to be significantly worse than their part-time colleagues. This can have significant short-term and long-term ramifications for the industry that will make it more difficult for universities to attract talented individuals to choose a career in education and retaining their best workers based on current employment perceptions.

Fixed mode noise and random mode noise always exist in the image sensor, which affects the imaging quality of the image sensor. The charge diffusion and color mixing between pixels in the photoelectric conversion process belong to fixed mode noise. This study aims to improve the image sensor imaging quality by processing the fixed mode noise.

Through an iterative training of an ergoable long- and short-term memory recurrent neural network model, the authors obtain a neural network model able to compensate for image noise crosstalk. To overcome the lack of differences in the same color pixels on each template of the image sensor under flat-field light, the data before and after compensation were used as a new data set to further train the neural network iteratively.

The comparison of the images compensated by the two sets of neural network models shows that the gray value distribution is more concentrated and uniform. The middle and high frequency components in the spatial spectrum are all increased, indicating that the compensated image edges change faster and are more detailed (Hinton and Salakhutdinov, 2006; LeCun et al., 1998; Mohanty et al., 2016; Zang et al., 2023).

In this paper, the authors use the iterative learning color image pixel crosstalk compensation method to effectively alleviate the incomplete color mixing problem caused by the insufficient filter rate and the electric crosstalk problem caused by the lateral diffusion of the optical charge caused by the adjacent pixel potential trap.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

The wireless power transmission (WPT) system with an embedded coil will achieve a more flexible charging operation and higher system efficiency. However, the comprehensive analysis considering cross-coupling for WPT with embedded coil is rarely investigated. This study aims to improve the system efficiency of WPT with the embedded coil based on circuit analysis and optimization of embedded coil loops.

The circuit model of WPT system with the non-resonant compensated embedded coil is developed by taking the cross-coupling of all coils and the circuit compensation degree of the embedded coil into consideration. On the basis of system characteristics analysis, optimization of embedded coil position and non-resonant compensation are proposed to improve the efficiency of WPT system with embedded coil. Experimental studies demonstrate the correctness of theoretical research.

The WPT system with embedded coil designed by optimizing the position and non-resonant compensation achieves higher efficiency than those of the system with two-coil mode and the three-coil system with a resonant compensated embedded coil.

A WPT system with embedded coil could be more efficient by using a non-resonant compensated coil embedded into the buffer material of the storage box for sophisticated electrical equipment.

The cross-coupling between all coils is considered in circuit analysis for WPT system with embedded coil. Optimization of the position and non-resonant compensation of embedded coil achieves higher efficiency.

This study examines the effect of stable institutional investors on firms' product quality failures. Furthermore, the authors investigate the channels through which institutional ownership stability enhances product quality management.

This study uses probit, ordered probit and negative binomial regression frameworks to investigate the research questions. In addition, the authors utilize the three-stage least-squares to address the endogeneity issues.

Using a sample of product recall incidents from 2012 to 2021, the authors find that firms with more stable institutional ownership have a lower probability, frequency and severity of recall incidents and adopt a proactive product recall strategy. Institutional investors with significant and persistent holdings improve quality management by reducing overinvestment and the use of option-linked and relative performance executive compensations. Furthermore, the influence of stable institutional owners on product quality failures is more pronounced in firms with low managerial ability and specialist CEOs. Lastly, the empirical evidence demonstrates that stable holdings by active investors have a more substantial impact on reducing product recalls than passive and other stable institutional holdings.

This study is the first to examine the impact of institutional ownership stability on firms' product recalls. The authors contribute to the literature on the benefits of stable institutional ownership on firm outcomes and the determinants of product quality failures.