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The purpose of this paper is to describe a new method for sensorless hysteresis direct torque control (HDTC) algorithm for permanent magnet synchronous motor to minimize torque ripple and electromagnetic interference (EMI) noises.

The design methodology is based on space vector modulation of electrical machines with digital vector control. MATLAB simulations supported with experimental study under C++ are used.

The simulation and experimental results of this proposed algorithm show adequate dynamic torque performance and considerable torque ripples reduction as well as lower current ripples, lower EMI noise level as compared to traditional HDTC.

This research is limited to PMSM, however the research can be extended to include induction motor as well. In addition, the actual mathematical relation between the torque ripple and flux ripple can be studied to set the flux and torque bands width in reasonable value, and this relationship can be used to select switching time of the active selected vectors.

The implementation of the proposed algorithm in microcontroller embedded systems is described. It requires no PI controller in the torque control loop In addition, based on existence direct torque control equipment, it is only required to change the software switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15 kHz and the system is supplied with timers.

The algorithm used in this work utilizes the output of two hysteresis controllers used in the traditional HDTC to determine two adjacent switching vectors per one sample time. The algorithm also uses the magnitude of the torque error, magnitude of the flux error and stator flux position to select the switching time for the selected vectors to control the applied average voltage level in such a way that the torque ripple is minimized. The selection of the switching time of the selected active vectors utilizes novel table structure which reduces the complexity of calculation. This work is directed to designers of ac motor drive system who seek smooth torque performance as well as low EMI noise level.

The paper seeks to provide an adaptive fuzzy logic controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple.

The design methodology is based on vector control analysis. MATLAB simulations supported with experimental study under C++ are used to execute the proposed work.

The results show that considerable torque ripple reduction as well as considerable current ripple reduction can be achieved by utilizing adaptive fuzzy switching algorithm to fire the inverter supplying the PMSM.

This research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied, the effects of harmonics in control signals on the torque ripple. Digital and active filters as solution to these harmonics can be also addressed. The actual mathematical relation between the torque ripple and flux ripple can be studied to set the flux and torque bands width in reasonable value.

Based on existence DTC control system, it is only required to change the software‐switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15 kHz and the system is supplied with timers. In addition, a relatively higher DC voltage may be required to achieve higher speed compared with the traditional DTC.

In this paper, the stator flux position, and errors due to deviations from reference values of the torque and stator flux are used to select two active vectors while at the same time the absolute value of the torque error and the stator flux position are fuzzified to adapt the switching of the inverter in order to control the applied average voltage level in such a way as to minimize the torque ripple, so instead of fixed time table structure, a fuzzy logic is used to calculate the switching time for the selected vectors and no PI controller is used as the case in the traditional‐space vector modulation. This work is directed to motor drive system designers who seek highly smooth torque performance with fast response.

This study aims to investigate and analyze the impact of soft total quality management (TQM) practices on employees’ organizational commitment in Sudanese governmental petroleum organizations and to propose targeted strategies on how to enrich the soft TQM practices.

The study used questionnaires to gather data from employees at Sudanese governmental petroleum organizations that adopt quality programs. A stratified random sampling procedure was followed and generated a sample size of 253. Data were analyzed via regression.

The study examined the relationship between employee’s organizational commitment and five soft TQM practices, namely training and education, top management commitment, employee empowerment, involvement and teamwork. These practices collectively explain most of the variance in the employees’ organizational commitment in Sudanese governmental petroleum organizations with R² = 75%. All independent variables are positively and statistically significant at a 5% significance level. Training/education was inferred as the most influencing factor, and teamwork was the least important among the five practices.

The positive relationship between soft TQM practices and organizational commitment suggests several actionable strategies for organizations. By fostering a culture that emphasizes continuous learning, empowerment and involvement, organizations can improve not only the quality of their products and services but also overall productivity. High levels of organizational commitment reduce turnover rates, which in turn lowers recruitment and training costs associated with replacing employees. Encouraging teamwork and employee involvement fosters a collaborative environment where innovation can thrive. Finally, policymakers could use these findings to advocate for the adoption of TQM practices in public sector organizations.

The findings from this study underscore the importance of soft TQM practices – specifically training and education, top management commitment, employee empowerment, involvement and teamwork – in enhancing employees’ organizational commitment. This focus on human-centric practices provides an important contribution to existing literature, particularly in contexts that are underrepresented in TQM research, such as developing countries and governmental organizations. It demonstrates how abstract TQM principles translate into practical outcomes like increased employee commitment, which is a crucial factor for organizational success.

Cracks are prevalent signs of pavement distress found on highways globally. The use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly considered as an optimal solution. Consequently, this paper introduces a novel, fully connected, optimised convolutional neural network (CNN) model using feature selection algorithms for the purpose of detecting cracks in highway pavements.

To enhance the accuracy of the CNN model for crack detection, the authors employed a fully connected deep learning layers CNN model along with several optimisation techniques. Specifically, three optimisation algorithms, namely adaptive moment estimation (ADAM), stochastic gradient descent with momentum (SGDM), and RMSProp, were utilised to fine-tune the CNN model and enhance its overall performance. Subsequently, the authors implemented eight feature selection algorithms to further improve the accuracy of the optimised CNN model. These feature selection techniques were thoughtfully selected and systematically applied to identify the most relevant features contributing to crack detection in the given dataset. Finally, the authors subjected the proposed model to testing against seven pre-trained models.

The study's results show that the accuracy of the three optimisers (ADAM, SGDM, and RMSProp) with the five deep learning layers model is 97.4%, 98.2%, and 96.09%, respectively. Following this, eight feature selection algorithms were applied to the five deep learning layers to enhance accuracy, with particle swarm optimisation (PSO) achieving the highest F-score at 98.72. The model was then compared with other pre-trained models and exhibited the highest performance.

With an achieved precision of 98.19% and F-score of 98.72% using PSO, the developed model is highly accurate and effective in detecting and evaluating the condition of cracks in pavements. As a result, the model has the potential to significantly reduce the effort required for crack detection and evaluation.

The proposed method for enhancing CNN model accuracy in crack detection stands out for its unique combination of optimisation algorithms (ADAM, SGDM, and RMSProp) with systematic application of multiple feature selection techniques to identify relevant crack detection features and comparing results with existing pre-trained models.

This paper aims to investigate the influence of the determinants (pricing, type of structure, Shariah auditing, Shariah risk and Shariah documentation) and the sukuk legitimacy among Islamic financial institutions using a qualitative approach. The paper further explained the significance of the determinants on legitimacy, evaluated the relationship between sukuk characteristics and sukuk legitimacy and examined the moderating effect of Shariah Supervisory Board (SSB) on the relationship.

The study used a purposive sampling technique to select the target respondents required for the survey (semi-structured interview). This technique is applied by selecting members of SSBs among Islamic financial institutions. A total number of ten members are selected as the sample size for the study based on their experience and basic knowledge of Fiqh Al-Mua’malat and its application in Islamic financial institutions.

The findings revealed that the determinants have a significant impact on the sukuk legitimacy, meaning that there is a positive and significant relationship between the determinants and the sukuk legitimacy. In addition, this study indicates the empirical evidence of the moderating effect of SSB on the relationship between the determinants and the sukuk legitimacy.

This study has added to the literature by examining the determinants of sukuk legitimacy while evaluating the moderating effect of SSB on the relationship. Besides, this might add benefits to the numerous Islamic financial institutions relating to the amendment of its regulatory frameworks with the view to pushing the sukuk market investors to move toward asset-backed structure. In addition, the SSB in central banks must also focus its attention regarding the sukuk legitimacy and its application among the various Islamic financial institutions.

This study has added a new discussion to the body of knowledge, i.e. examining the sukuk legitimacy and its relationship with sukuk determinants; hence, an approach that is not widely discussed in the previous studies. Furthermore, conducting such research in the field of Islamic finance provides novelty in the literature among both emerging and developed economies including Malaysia. This is because to the best knowledge of the researchers, there was no empirical study (within the literature) that combined these variables and evaluated their empirical significance. Accordingly, this would enlighten the Islamic Ummah and propel the society’s intensity toward contributing to knowledge and might further provide clarification on the determinants and the sukuk legitimacy to prospective scholars, precisely on the moderating effect of SSB on the relationship between determinants and legitimacy of sukuk.

This chapter investigates the presence of a difference in the systemic risk level between Islamic and conventional banks in Bangladesh. The authors compare systemic resilience of three types of banks: fully fledged Islamic banks, purely conventional banks (CB), and CB with Islamic windows. The authors use the market-based systemic risk measures of marginal expected shortfall and systemic risk to identify which type is more vulnerable to a systemic event. The authors also use ΔCoVaR to identify which type contributes more to a systemic event. Using a sample of observations on 27 publicly traded banks operating over the 2005–2014 period, the authors find that CB is the least resilient sector to a systemic event, and is the one that has the highest contribution to systemic risk during crisis times.

The range of applications of the currently available biomass selective laser sintering (SLS) parts is limited and low-quality. This study aims to demonstrate the effects of the various processing parameters on the dimensional accuracy, bending strength, tensile strength, density and impact strength of the Prosopis chilensis/polyethersulfone (PES) composites (PCPCs) that were produced by SLS. The various processing parameters are laser power, scan speed, preheating temperature, scan spacing and layer thickness. In addition, the authors’ studied the effects of PCP particle size on the mechanical properties of the PCPCs.

The PCPC specimens were printed using an AFS SLS machine (additive manufacturing). The bending, tensile and impact strengths of the specimens were measured using a universal tensile tester. The dimensional accuracy of the bending specimens was determined by a Vernier caliper. The formability of the PCPC at various mixing ratios of the raw materials was earlier investigated by single-layer sintering experiments (Idriss et al., 2020b). The microstructure and particle distribution of the various PCPC specimens were analyzed by scanning electron microscopy (SEM).

The mechanical strengths (bending, tensile and impact strengths and density) and the dimensional accuracy of the PCPC SLS parts were directly and inversely proportional, respectively, to the laser power and preheating temperature. Furthermore, the mechanical strengths and dimensional accuracy of the PCPC SLS parts were inversely and directly proportional, respectively, to the scanning speed, scan spacing and layer thickness.

PCPC is an inexpensive, energy-efficient material that can address the drawbacks of the existing SLS parts. It is also eco-friendly because it lowers the pollution and CO₂ emissions that are associated with waste disposal and SLS, respectively. The optimization of the processing parameters of SLS in this study produced high-quality PCPC parts with high mechanical strengths and dimensional accuracy that could be used for the manufacture of the roof and wooden floors, construction components and furniture manufacturing.

To the best of the authors’ knowledge, this study is among the first to elucidate the impact of the various SLS processing parameters on the mechanical properties and dimensional accuracy of the sintered parts. Furthermore, novel PCPC parts were produced in this study by SLS.

This paper aims to examine how an alternative accounting system developed by a marginalised group of women enables them to counter oppressive systems built at the intersections of gender, class and race.

The authors draw on diary notes taken over a period of 13 years in France and Senegal in the context of the first author's family interactions with a community of ten Black immigrant women. The paper relies on Black feminist perspectives, namely, Lorde's work on difference and survival to illuminate how this community of women uses the creative power of its “self-defined differences” to build its own accounting system – a tontine – and work towards its emancipation.

The authors find that to fight oppressive marginalising structures, the women develop a tontine, an autonomous, self-managed, women-made banking system providing them with cash and working on the basis of trust. This alternative accounting scheme endeavours to fulfil their “situated needs”: to build a home of their own in Senegal. The authors conceptualise the tontine as a “situated accounting” scheme built on the women's own terms, on the basis of sisterhood and opacity. This accounting system enables the women to work towards their “situated emancipation”, alleviating the burden of their marginalisation.

This paper gives visibility to vulnerable women's agentic capacities through accounting. As no single story captures the nuances and complexities of accounting, further exploration is encouraged.

This paper contributes to the counter-accounting literature that engages with vulnerable, “othered” populations, shedding light on the counter-practices of accounting within a community of ten Black precarious women. In so doing, this study problematises these counter-practices as intersectional and built on “survival skills”. The paper further outlines the emancipatory potential of alternative systems of accounting. It ends with some reflections on doing research through activist curiosity and the need to rethink academic research and knowledge in opposition to dominant epistemic standards of knowledge creation.

The purpose of this study is to propose and develop a zakat model for digital assets from the Sharīʿah perspective.

This research adopts a qualitative research method while studying the literature thoroughly, and it analyzes the data through an exploratory research approach to propose a zakat model for the digital assets.

This research aims to develop a zakat model for digital assets within the framework of Sharīʿah. Using a qualitative research method, the study thoroughly examines existing literature and uses an exploratory research approach to propose this zakat model. The findings suggest that digital assets hold the potential to be considered for zakat in the contemporary digital age. Previous studies indicate that both commodity-based and currency-based digital assets meet the criteria for zakat imposition. Given zakat’s significant impact on socioeconomic development, it is imperative to carefully manage these assets to maximize their potential benefits. However, variations in interpretations by different jurisdictions and Sharīʿah scholars regarding the understanding and classification of digital assets lead to ongoing scrutiny from legal and religious perspectives. This research aims to contribute to the discourse by proposing a zakat model for digital assets and identifying potential assets eligible for zakat.

This research seems to be the pioneer in providing a zakat model for digital assets, combining different segments of digital assets.

This study aims to review the current literature on the positive and negative effects of digitalisation in preventing corruption. It analyses existing research patterns and provides recommendations for future studies.

This paper employed bibliometric analysis and systematic review to scrutinise 190 papers from the Web of Science database from 2000 to 2023. Biblioshiny on R Studio was used for advanced bibliometric analysis to determine publication dynamics, influential journals, publications and impactful authors and a three-field plot to analyse relationships among countries, keywords and journals.

This study provides a bibliometric analysis of the past and actual developments in the field related to the effects of digitalisation on corruption. Based on the systematic literature review on a sample of the 50 most influential articles, this study identified background theories employed, the primary research methodologies adopted and valuable insights into both the positive and negative aspects of the impact of digitalisation on corruption.

This study provides an extended overview of the effects of digitalisation on corruption and advances new avenues for further research related to this field. The white and dark sides of the effects of digitalisation on corruption are highlighted. Furthermore, the study identifies the need for further research in this field to gain a more in-depth understanding of the nexus between digitalisation and corruption.