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The purpose of this paper is to propose a novel serial structure repetitive control scheme for shunt active power filter (SAPF) to improve the steady-state accuracy and dynamic performance of SAPF. The novelty of this scheme lies in the reconfiguration of the pole of repetitive control internal model, so that the dynamic response of the repetitive control is improved greatly.

By analyzing the mathematical model of repetitive control, the repetitive control delay can reduce by giving up the needless poles of the internal model, and the general mk + i repetitive control can be designed through the pole configuration method. The controller can track a set of specific order harmonics.

The experimental results are coincident with the theoretical analyses, which prove the effectiveness of the proposed method on harmonic suppression and great performance in dynamic response.

An APF prototype has been designed with the serial structure repetitive control proposed in this paper, and it can successfully eliminate the harmonics current of nonlinear load with faster dynamic response. Moreover, the proposed controller can be applied to any three-phase system for fast dynamic response and high tracking accuracy.

In this paper, the mathematical model of the repetitive control for specific set of harmonica is developed. A novel serial structure repetitive control is designed, so that the SAPF can eliminate the fundamental reactive current and specific order harmonics and speed up the dynamic response of the repetitive control.

As arc suppression coils (ASCs), magnetically controlled reactors (MCRs) are usually operated in the single-phase mode. Due to the lack of a third order harmonic compensation circuit, the current harmonics are high. The purpose of this paper is to propose a novel structure of MCR and a genetic algorithm (GA) to determine the parameters which will result in minimum total harmonics.

This paper proposes the structure and the working principle of the multi-valve controlled saturable reactor (MCSR). There are several sorts of magnetic valves in the iron cores of the MCSR. The saturation degree of each magnetic valve is different when the same direct component of the magnetic flux is generated in the iron core, therefore current harmonics of different phases emerging, i.e. the total harmonics can be reduced. The magnetization characteristics and the mathematical model of the current harmonics of the MCSR are presented by introducing three parameters. The optimal values of the parameters that result in the smallest total harmonic distortion in the output current are calculated by a GA.

The simulation and experimental results are coincident with the theoretical analyses, which prove the effectiveness of the proposed method on harmonic suppression.

The method proposed in this paper can successfully reduce the current harmonics of the conventional MCR, including but not limited to the ASC. A prototype MCSR (540 kVA/10 kV) has been designed and constructed.

In this paper, a MCSR is proposed. The mathematical model of the MCSR for harmonic analysis is developed. The optimal parameters that result in the smallest THD in the output current are calculated. The mathematical model can be also used for the harmonic analysis of conventional MCRs.

The purpose of this paper is to empirically examine the mediating role of potential and realized absorptive capacity in intellectual capital (IC) and business performance. It also investigates the direct impact of the components of IC on business performance.

Partial least square-structural equation modeling (PLS-SEM) was used to assess the effect of IC dimensions on performance and to analyze the mediating role of absorptive capacity in this relationship. Data were collected from 192 managers using a survey questionnaire with Likert scale items.

The findings of the study show that potential absorptive capacity does not intervene in the relationship between the components of IC and those of business performance. However, realized absorptive capacity, measured as the transformation and exploitation of knowledge, played a positive mediating role in the relationship between the dimensions of IC and those of business performance. Social capital was also noted as a weak predictor of business performance, while human capital and organizational capital had a profound positive influence.

This study contributes to the literature on IC by examining the role of realized and potential absorptive capacity in the relationship between IC components and firm performance. This research also helps practitioners recognize the importance of transformation and the exploitation of knowledge for business performance.

The purpose of this paper is to propose a pressure-, temperature- and acceleration-sensitive structure-integrated inductor-capacitor (LC) resonant ceramic sensor to fulfill the measurement of multi-parameters, such as the measurement of pressure, temperature and acceleration, simultaneously in automotive, aerospace and aeronautics industries.

The ceramic-based multi-parameter sensor was composed of three LC tanks, which have their resonant frequencies sensitive to pressure, temperature and acceleration separately. Two aspects from the specific sensitive structure design to the multiple signals reading technology are considered in designing the multi-parameter ceramic sensor. Theoretical analysis and ANSYS simulation are used in designing the sensitive structure, and MATLAB simulation and experiment are conducted to verify the feasibility of non-coverage of multi-readout signals.

It is found that if the parameters of sensitive structure and layout of the LC tanks integrated into the sensor are proper, the implementation of a multi-parameter sensor could be feasible.

The ceramic sensor proposed in the paper can measure pressure, temperature and acceleration simultaneously in harsh environments.

The paper creatively proposes a pressure-, temperature- and acceleration-sensitive structure-integrated LC resonant ceramic sensor for harsh environments and verifies the feasibility of the sensor from sensitive structure design to multiple-signal reading.

This paper aims to present a novel wireless passive pressure sensor based on an aperture coupled microstrip patch antenna embedded with an air cavity for pressure measurement.

In this paper, the sensitive membrane deformed when pressure was applied on the surface of the sensor and the relative permittivity of the mixed substrate changed, resulting in a change in the center frequency of the microstrip antenna. The size of the pressure sensor is determined by theoretical calculation and software simulation. Then, the sensor is fabricated separately as three layers using printed circuit board technology and glued together at last. The pressure test of the sensor is carried out in a sealed metal tank.

The extracted resonant frequency was found to monotonically shift from 2.219 to 1.974 GHz when the pressure varied from 0 to 300 kPa, leading to an average absolute sensitivity of 0.817 MHz/kPa.

This pressure sensor proposed here is mainly to verify the feasibility of this wireless passive maneuvering structure, and when the base material of this structure is replaced with some high-temperature-resistant material, the sensor can be used to measure the pressure inside the aircraft engine.

The sensor structure proposed here can be used to test the pressure in a high-temperature environment when the base material is replaced with some high-temperature-resistant material.

In the digital economy, as artificial intelligence applications increase, big data analytical capability (BDAC) plays a crucial role, and intellectual capital is growing in importance. This study aims to examine the possible benefits and effects of intellectual capital, BDAC and integrations on operational performance.

This study collected data from firms in Asia, and a total of 257 senior managers completed a questionnaire. Confirmatory factor analysis and structural equation modeling (SEM) is used for statistical analysis.

Intellectual capital positively correlates with BDAC, and BDAC positively relates to internal integration but not to external integration. Furthermore, both internal integration and external integration positively correlate with operational performance. This study supports that internal integration is a significant mediator in the influence of BDAC on operational performance.

First, the authors provide empirical evidence that intelligent capital in intangible resources helps firms to build BDAC. Second, this study stresses the importance of BDAC in business, which enhances the integration of the whole supply chain and results in superior operational performance.

This is a first attempt from the perspective of intelligent capital and uses SEM to emphasize the relationships among BDAC, supply chain integration and performance based on unique and irreplaceable intangible resources, thus providing a new perspective on the contributing factors of BDAC.

Existing research on knowledge management processes (KMPs) and absorptive capacity (ACAP) is primarily conceptual and descriptive in nature, and empirical research confirming the real impact of KMPs when developing ACAP is lacking. Furthermore, the relationship between ACAP and organizational performance (OP) has not been adequately studied. Hence, the purpose of this paper is to introduce a comprehensive, delineated and integrated conceptual model which encompasses KMPs, ACAP and OP. Then, an empirical investigation is undertaken to test the relationships among the proposed study model variables.

In total, 245 questionnaires were useable. Partial least square 3.3.3 is utilized to examine the validity of the measurement model and test the hypotheses.

The findings of this study suggest that KMPs influence ACAP and ACAP affects OP. Finally, the results show that KMPs affect OP directly and indirectly through ACAP (mediator).

The results of this study help managers to ascertain the managerial practices that can be employed as well as determine the level of effort and resources necessary to enhance ACAP. Additionally, managers should shed additional light on the ACAP's positive implications for OP.

This study focuses on the conceptualization of KMP and empirically tests the effect of these individual processes on ACAP and on OP. Finally, the relationship between KMPs and OP, although implied, needs to be addressed empirically in the research literature through utilizing ACAP as mediator between KMPs and OP, this appears to be the first study to try to achieve this main objective.

This research aims to examine the role of green intellectual capital (GIC) dimensions in promoting sustainable healthcare as reflected by sustainable performance. The mediating effect of green absorptive capacity (GAC) and moderating role of environmental turbulence were also explored.

Structural equation modeling was utilized for hypotheses testing of a survey data set of 387 at healthcare organizations operating in Iraq. The data were collected using purposive sampling with expert judgment from senior managers and professionals.

Contrary to previous studies, the findings showed that only green human and relational capitals predict green performance and only green human capital predicted economic performance. GAC was related to green human capital, green structural capital and performance, and played a significant mediating role on the relationships.

Even though the research was limited to one region of a single country, Iraq, GAC can be modified by managers to enhance GIC for sustainable healthcare performance. This action must be viewed in terms of the future timing of the impact while managers display strong conviction for sustainability commitment. Managers will find GRC least associated with performance, but that GIC dimensions work best in unison.

The examination of GIC with GAC as moderated by environmental turbulence contributes nascent theoretical insights in sustainable healthcare.

The purpose of this study is to identify the impact of intellectual capital on the innovation performance of the Jordanian banking sector and identify the moderating role of big data analytics.

For this study's purposes, 333 questionnaires were analysed. Convergent validity, discriminant validity and reliability tests were performed through structural equation modelling (SEM) in the Smart-PLS program. A bootstrapping technique was used to analyse the data.

Empirical results showed that each of the components of intellectual capital and big data analytics explains 63.5% of the variance in innovation performance and that all components of intellectual capital have a statistically significant impact on innovation performance. The results also revealed that the relationship between structural capital and innovation performance is moderated through big data analytics.

This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalisation of its results, and the results are limited to one country.

This study promotes the idea of focusing on components of intellectual capital to enhance innovation performance in the Jordanian banking sector and knowing the effect of big data analytics in this relationship.

This study makes recommendations for financial policymakers to improve the effectiveness of intellectual capital practices and innovation performance in the context of big data analytics.

This study has important implications for leaders in the Jordanian banking sector, in general, as the study highlights the importance of intellectual capital to enhance the innovation performance, especially in light of the big data analytics in this sector, and thus increase the innovative capabilities of this banks, which leads to an increase in the level of innovation.

Study on knowledge-based systems for scientific publications is growing very broadly. However, most of these studies do not explicitly discuss the knowledge management (KM) component as knowledge management system (KMS) implementation. This background causes academic institutions to face challenges in developing KMS to support scholarly publication cycle (SPC). Therefore, this study aims to develop a new KMS conceptual model, Identify critical components and provide research gap opportunities for future KM studies on SPC.

This study used a systematic literature review (SLR) method with the procedure from Kitchenham et al. Then, the SLR results are compiled into a conceptual model design based on a framework on KM foundations and KM solutions. Finally, the model design was validated through interviews with related field experts.

The KMS for SPC focuses on the discovery, sharing and application of knowledge. The majority of KMS use recommendation systems technology with content-based filtering and collaborative filtering personalization approaches. The characteristics data used in KMS for SPC are structured and unstructured. Metadata and article abstracts are considered sufficiently representative of the entire article content to be used as a search tool and can provide recommendations. The KMS model for SPC has layers of KM infrastructure, processes, systems, strategies, outputs and outcomes.

This study has limitations in discussing tacit knowledge. In contrast, tacit knowledge for SPC is essential for scientific publication performance. The tacit knowledge includes experience in searching, writing, submitting, publishing and disseminating scientific publications. Tacit knowledge plays a vital role in the development of knowledge sharing system (KSS) and KCS. Therefore, KSS and KCS for SPC are still very challenging to be researched in the future. KMS opportunities that might be developed further are lessons learned databases and interactive forums that capture tacit knowledge about SPC. Future work potential could identify other types of KMS in academia and focus more on SPC.

This study proposes a novel comprehensive KMS model to support scientific publication performance. This model has a critical path as a KMS implementation solution for SPC. This model proposes and recommends appropriate components for SPC requirements (KM processes, technology, methods/techniques and data). This study also proposes novel research gaps as KMS research opportunities for SPC in the future.