Search results

The purpose of this paper is to present a frequency domain technique for the recognition and location of winding movements and mechanical deformations in power transformers. Both, axial and radial coil movements, as well as changes in clamp pressure will be studied.

The developed algorithm is based on using a distributed s‐domain parameter equivalent network, which is cascaded with other sections to constitute a generalized model. The frequency domain transfer admittance is used as the main criterion to recognize, identify and locate the winding movement and deformation.

In order to reduce the number of failures due to winding movements and deformations, it is suggested to measure and store the transfer admittance over frequency range 0‐10 MHz region at normal operation as saved data for comparison with the corresponding data during failure. With the proposed technique, the type and the location of eventual displacement, as well as the number discs involved can be identified.

Although the simulation was based on real experimental data adopted from the literature, the algorithm should be tested for real transformers. Several checks have been conducted in order to validate the mathematical model.

A relatively simple mathematical model has been presented. It can be used for any transformer, to check the integrity of the winding in order to meet certain degree of equipment safety and reliability.

The high lift devices are effective at high angle of attack to increase the coefficient of lift by increasing the camber. But it affects the low angle of attack aerodynamic performance by increasing the drag. Hence, they have made as a movable device to deploy only at high angles of attack, which increases the design and installation complexities. This study aims to focus on the comparison of aerodynamic efficiency of different conventional leading edge (LE) slat configurations with simple fixed bioinspired slat design.

This research analyzes the effect of LE slat on aerodynamic performance of CLARK Y airfoil at low and high angles of attack. Different geometrical parameters such as slat chord, cutoff, gap, width and depth of LE slat have been considered for the analysis.

It has been found that the LE slat configuration with slat chord 30% of airfoil chord, forward extension 8% of chord, dip 3% of chord and gap 0.75% of chord gives higher aerodynamic efficiency (C_l/Cd) than other LE slat configurations, but it affects the low angles of attack aerodynamic performance with the deployed condition. Hence, this optimum slat configuration is further modified by closing the gap between LE slat and the main airfoil, which is inspired by the marine mammal’s nose. Thus increases the coefficient of lift at high angles of attack due to better acceleration over the airfoil nose and as well enhances the aerodynamic efficiency at low angles of attack.

The two-dimensional computational analysis has been done for different LE slat’s geometrical parameters at low subsonic speed.

This bio-inspired nose design improves aerodynamic performance and increases the structural strength of aircraft wing compared to the conventional LE slat. This fixed design avoids the complex design and installation difficulties of conventional movable slats.

The findings will have significant impact on the fields of aircraft wing and wind turbine designs, which reduces the design and manufacturing complexities.

Different conventional slat configurations have been analyzed and compared with a simple fixed bioinspired slat nose design at low subsonic speed.

Significant advances in digital technologies impact both organisations and knowledge workers alike. Organisations are now able to effectively analyse significant amounts of data, while accomplishing actionable insight and data-driven decision-making through knowledge workers that understand and manage greater complexity. For decision-makers to be in a position where sufficient information and data-driven insights enable them to make informed decisions, they need to better understand fundamental constructs that lead to the understanding of deep knowledge and wisdom. In an attempt to guide organisations in such a process of understanding, this research study focuses on the design of an organisational transformation framework for data-driven decision-making (OTxDD) based on the collaboration of human and machine for knowledge work. The OTxDD framework was designed through a design science research approach and consists of 4 major enablers (data analytics, data management, data platform, data-driven organisation ethos) and 12 sub-enablers. The OTxDD framework was evaluated in a real-world scenario, where after, based on the evaluation feedback, the OTxDD framework was improved and an organisational measurement tool developed. By considering such an OTxDD framework and measurement tool, organisations will be able to create a clear transformation path to data-driven decision-making, while applying the insight from both knowledge workers and intelligent machines.

The purpose of this paper is to focus on compressive strength modelling of cementitious mixtures like mortar and Roller-compacted concrete (RCC) containing rubber aggregates from shredded worn tires and filler using adaptive neuro fuzzy inference systems (ANFIS).

The volume substitution contains a ratio of rubber aggregates vs sand in mortar and with crushed sand in RCC and ranges from 0 to 50 per cent. As for the filler, they are substituted with sand by 5 per cent in mortar mixture. The methodology consists of optimizing the percentage of substitution in cementitious mixtures to ensure better mechanical properties of materials like compressive strength. The prediction of compressive strength and the optimization of cementitious mixtures encourage their uses in such construction pavements, in area games or in other special constructions. These cementitious materials are considered as friendly to the environment by focussing on their improved deformability.

The results of this paper show that the performance of the constructed fuzzy method was measured by correlation of experimental and model results of mortar and RCC mixtures containing both rubber aggregates and filler. The comparison between elaborated models through the error and the accuracy calculations confirms the reliability of the ANFIS method.

The purpose of this paper is to assess the performance of the constructed fuzzy model by the ANFIS method for two types of cementitious materials like mortar and RCC containing rubber aggregates and filler. The fuzzy method could predict the compressive strength based on the limited measurement values in the mechanical experiment. Furthermore, the comparison between the elaborated models confirms the reliability of the ANFIS method through the error and the accuracy calculations for the best cementitious material mixtures.

The purpose of this paper is to understand the implications of psychological contract on employees’ intention to leave and their relationship with employee commitment and satisfaction. The study focuses on measuring these attributes in the United Arab Emirates’ (UAE) multicultural workforce.

Data were collected from a total of 373 employees from government, semi-government and private organizations covering different hierarchical levels across various industries. Structural equation modeling was used to test the predicted relationship.

The study reveals that the relational component of psychological contracts plays a significant role in developing strong employer–employee relationships and reducing employee intentions to leave the organization. The study has also demonstrated the partial mediation effect of organizational commitment and employee satisfaction between the independent and dependent variables. Finally, our finding stresses the moderating effect of gender and citizenship demographics on the relationships between the independent and dependent variables.

A limitation of this study was the fact that data collection was conducted in the context of economic crisis which is accompanied by downsizing of organizations. Another factor being the survey is restricted to the UAE which limits the generalizability of the results outside the region.

As little is known about the potential effect of psychological contracts on the intention to leave in the Middle Eastern context, this paper is expected to provide empirical evidences that will make significant contributions to the employee engagement literature in the Middle Eastern contexts.

This paper aims to identify the most common fungal species that grow on paper manuscripts and cause bio-deterioration. It also detects the impact of additive materials on fungal degrading and builds a wide database. Thus, it helps conservators understand this phenomenon.

In total, 15 samples were collected from different paper manuscripts suffering from fungi. The achievement of the study objectives depends on using a variety of analyzes, such as a microbiological study, which indicated that three main fungi grew on the paper samples. Then, a digital microscope and an environmental scanning electron microscope were used to detect the effect of fungi on paper fibers. Fourier transform infrared microscopy was used to identify the binding medium and the X-ray diffraction method was used to measure the crystallinity index of cellulose of the paper samples.

Arabic gum was used as a binder medium with the samples. Aspergillus Niger, Aspergillus Fumigatus and Aspergillus Clavatus were the most common fungal species that grew on the Qur’an papers under investigation. They also caused much common damage to the paper samples. The results of the analyzes also showed that the highest crystallinity index of cellulose was in the samples that contained the lowest rate of fungal growth.

This paper highlights the relationship between fungal degradation and the multi-component nature of paper manuscripts. It builds a wide database that correlates the composition and the degradation of the Qur’an papers.

Following the COVID-19 pandemic, most higher education institutes shifted to online learning as the sole alternative to continuing education while mitigating the risks imposed by the pandemic. This has raised several concerns regarding students’ learning experience, satisfaction and academic achievement, particularly in countries where students have restrained technological resources (i.e. developing nations). The current research aims to investigate the key factors influencing students’ attitudes, satisfaction and academic achievement among university students in an emerging market context (i.e. Morocco). The moderating effect of students’ motivation to study online was also scrutinized.

The authors propose an integrated conceptual framework that combines the technology acceptance model (TAM) with the outcomes of prior literature related to online learning. Based on data collected from 850 Moroccan university students, the authors empirically tested the conceptual model using a partial least squares (PLS) estimation.

First, attitude toward online learning and satisfaction positively impact university students’ academic achievement; at the same time, attitude positively impacts students’ satisfaction with online learning. Second, students’ satisfaction and attitude toward online learning were found to be mainly influenced by instructor performance, ease of use of the online learning platform, information quality, interactivity and perceived usefulness (PU). Finally, student motivation acts as a moderator, e.g. students with higher motivation to learn online are more likely to develop a favorable attitude toward online learning and can, therefore, accomplish better academic performance.

The current study makes a considerable contribution to the literature by contributing to the on-going debate about the potentials and challenges of online learning, particularly in an emerging country where education remains a considerable challenge. The study findings can help higher education institutes gauge the quality of online education programs and design efficient strategies to develop high-quality online learning for students. Our findings have implications not only for educational institutions and instructors in developing markets but also for the vendors of online course delivery software.

The present work aims to prepare biocomposites blend based on linear low density polyethylene/ starch without using harmful chemicals to improve the adhesion between two phases. Also, the efficiency of essential oils as green plasticizers and natural antimicrobial agents were evaluated.

Barrier properties and biodegradation behavior of linear low density polyethylene/starch (LLDPE/starch) blends plasticized with different essential oils including moringa oleifera and castor oils wereassessed as a comparison with traditional plasticizer such as glycerol. Biodegradation behavior forLLDPE/starch blends was monitored by soil burial test. The composted samples were recovered then washed followed by drying, and weighting samples after 30, 60, and 90 days to assess the change in weight loss. Also, mechanical properties including retention values of tensile strength and elongation at break were measured before and after composting. Furthermore, scanning electron microscope (SEM) was used to evaluate the change in the morphology of the polymeric blends. In addition to, the antimicrobial activity of plasticized LLDPE/starch blends films was evaluated using a standard plate counting technique.

The results illustrate that the water vapor transition rate increases from 2.5 g m⁻² 24 h⁻¹ for LLDPE/5starch to 4.21 g m⁻² 24 h⁻¹ and 4.43 g m⁻² 24 h⁻¹ for castor and moringa oleifera respectively. Also, the retained tensile strength values of all blends decrease gradually with increasing composting period. Unplasticized LLDPE/5starch showed highest tensile strength retention of 91.6% compared to the other blends that were 89.61, 88.49 and 86.91 for the plasticized LLDPE/5starch with glycerol, castor and M. oleifera oils respectively. As well as, the presence of essential oils in LLDPE/ starch blends increase the inhibition growth of escherichia coli, candida albicans and staphylococcus aureus.

The objective of this work is to develop cost-effective and environmentally-friendly methods for preparing biodegradable polymers suitable for packaging applications.

The circular economy (CE) represents an industry-wide transition from linear to circular processes. There has been a proliferation of literature on CE in the last decade. However, the existing studies on the adaption of CE in small and medium-sized enterprises (SMEs) are scarce. This study aims to develop a research agenda and the way forward for future researchers focusing on the adoption of CE.

This article analyses the CE concepts through a Systematic Literature Review (SLR). Coding and content analysis are performed to generate emergent themes with the help of “Atlas.ti” software.

The authors uncovered the contemporary significance of adopting CE and the state-of-the-art literature on CE. The study's findings fall into four broad themes: Technical know-how, resource and process optimization, reverse practices and technology and innovation. Ten thought-provoking questions were identified in the four themes that researchers can explore further in embracing CE to achieve sustainability in SMEs.

The study has highlighted the importance of CE adoption and CE's benefits to stakeholders across all three dimensions, i.e. social, economic and ecological. Practitioners can use the agenda in four themes to strengthen the practitioners' existing practices in SMEs to promote CE.

The study's uniqueness is the supply of current knowledge from diverse literature and practical consequences for SMEs. This study opens new lines of inquiry to adopt CE in SMEs, streamlining the existing literature into four themes to focus future research.

This study aims to identify the determinants of customers' green purchasing behaviors. First, the study examines the relationship between green self-identity (GSI) and green peer influence (GPI) on green purchase behavior (GPB). Second, it examines the relationships between both GSI and GPI, and purchasing behavior mediated by green consumption values (functional value (FV) and social value (SV)). Third, it investigates the moderating effect of customer disidentification (CDI) on the relationships between GSI and both green consumption values. Finally, it investigates the indirect relationships between GSI and purchasing behavior moderated by CDI.

A quantitative study is conducted using a survey of 204 Egyptian buyers of organic food products. AMOS and Hayes's PROCESS macro are used to test the hypotheses under investigation.

The customer's peer influence and GSI are found to have a positive impact on green purchasing behavior. Additionally, the mediating impact of values and the moderating impact of CDI are also confirmed.

This study helps organic food companies in identifying the determinants of customers' green purchasing behavior. The results of the study will guide the efforts of green marketing professionals in promoting green products in the Egyptian market.

Since the notion of green consumption is still in its infancy, there is a need for further exploration on the green consumption concept to better understand customers' predictors of that type of consumption; accordingly, the current research was conducted.