Jawad Ahmad Dar, Kamal Kr Srivastava and Sajaad Ahmad Lone
The Covid-19 prediction process is more indispensable to handle the spread and death occurred rate because of Covid-19. However early and precise prediction of Covid-19 is more…
Abstract
Purpose
The Covid-19 prediction process is more indispensable to handle the spread and death occurred rate because of Covid-19. However early and precise prediction of Covid-19 is more difficult because of different sizes and resolutions of input image. Thus these challenges and problems experienced by traditional Covid-19 detection methods are considered as major motivation to develop JHBO-based DNFN.
Design/methodology/approach
The major contribution of this research is to design an effectual Covid-19 detection model using devised JHBO-based DNFN. Here, the audio signal is considered as input for detecting Covid-19. The Gaussian filter is applied to input signal for removing the noises and then feature extraction is performed. The substantial features, like spectral roll-off, spectral bandwidth, Mel-frequency cepstral coefficients (MFCC), spectral flatness, zero crossing rate, spectral centroid, mean square energy and spectral contract are extracted for further processing. Finally, DNFN is applied for detecting Covid-19 and the deep leaning model is trained by designed JHBO algorithm. Accordingly, the developed JHBO method is newly designed by incorporating Honey Badger optimization Algorithm (HBA) and Jaya algorithm.
Findings
The performance of proposed hybrid optimization-based deep learning algorithm is estimated by means of two performance metrics, namely testing accuracy, sensitivity and specificity of 0.9176, 0.9218 and 0.9219.
Research limitations/implications
The JHBO-based DNFN approach is developed for Covid-19 detection. The developed approach can be extended by including other hybrid optimization algorithms as well as other features can be extracted for further improving the detection performance.
Practical implications
The proposed Covid-19 detection method is useful in various applications, like medical and so on.
Originality/value
Developed JHBO-enabled DNFN for Covid-19 detection: An effective Covid-19 detection technique is introduced based on hybrid optimization–driven deep learning model. The DNFN is used for detecting Covid-19, which classifies the feature vector as Covid-19 or non-Covid-19. Moreover, the DNFN is trained by devised JHBO approach, which is introduced by combining HBA and Jaya algorithm.
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Aneel Manan, Pu Zhang, Shoaib Ahmad and Jawad Ahmad
The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete…
Abstract
Purpose
The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete structure. However, FRP bars are not practically used due to a lack of standard codes. Various codes, including ACI-440-17 and CSA S806-12, have been established to provide guidelines for the incorporation of FRP bars in concrete as reinforcement. The application of these codes may result in over-reinforcement. Therefore, this research presents the use of a machine learning approach to predict the accurate flexural strength of the FRP beams with the use of 408 experimental results.
Design/methodology/approach
In this research, the input parameters are the width of the beam, effective depth of the beam, concrete compressive strength, FRP bar elastic modulus and FRP bar tensile strength. Three machine learning algorithms, namely, gene expression programming, multi-expression programming and artificial neural networks, are developed. The accuracy of the developed models was judged by R2, root means squared and mean absolute error. Finally, the study conducts prismatic analysis by considering different parameters. including depth and percentage of bottom reinforcement.
Findings
The artificial neural networks model result is the most accurate prediction (99%), with the lowest root mean squared error (2.66) and lowest mean absolute error (1.38). In addition, the result of SHapley Additive exPlanation analysis depicts that the effective depth and percentage of bottom reinforcement are the most influential parameters of FRP bars reinforced concrete beam. Therefore, the findings recommend that special attention should be given to the effective depth and percentage of bottom reinforcement.
Originality/value
Previous studies revealed that the flexural strength of concrete beams reinforced with FRP bars is significantly influenced by factors such as beam width, effective depth, concrete compressive strength, FRP bars’ elastic modulus and FRP bar tensile strength. Therefore, a substantial database comprising 408 experimental results considered for these parameters was compiled, and a simple and reliable model was proposed. The model developed in this research was compared with traditional codes, and it can be noted that the model developed in this study is much more accurate than the traditional codes.
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Aneel Manan, Zhang Pu, Jawad Ahmad and Muhammad Umar
Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are…
Abstract
Purpose
Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.
Design/methodology/approach
An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R2), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.
Findings
The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.
Originality/value
This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.
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In this chapter, the relations between Muslim migrant women's bodily appearances at Western workplaces, their work choices and career development are examined through the lens of…
Abstract
In this chapter, the relations between Muslim migrant women's bodily appearances at Western workplaces, their work choices and career development are examined through the lens of embodied intersectionality. This chapter draws on exiting research reports and empirical research to also reflect on the scope of Muslim female migrants' labour market integration in the United Kingdom.
For Muslim women, wearing ethnic or religious dresses such as headscarf/‘hijab’, ‘niqaab’ or ‘burqa’ represents the quintessential identity of women belonging to their particular ethnic group or religion. These highly visible social and cultural markers are also inherently gendered. This chapter delves into understanding how Muslim migrant women wearing ethnic/religious dresses experience/encounter Western workplaces and how their embodied intersectional identities through creating barriers at the workplaces impede the process of their labour market integration, in turn, limit their work choices and further restrict their career progression/development in the long run. The discussion also shows that attention to the Muslim migrant women's workplace experiences funnelled through the process of embodied intersectionality can expose the overall racialised and gendered practices of the society, different forms of social exclusion while simultaneously indicate resistance from and agency of these Muslim women through bodily appearances in transnational contexts. This chapter also sheds lights on how these women's career and workplace experiences need to be understood outside the stereotypical Western description of gendered workplaces and how the discussion needs to be broadened in scope and encompass the spatial dynamics of migration, religion, gender and ethnicity to be able to make sense of Muslim migrant women's work choices and career in the West.
This chapter has a twofold structure – first, it looks at the relationship between self-regulating agency and voice and understanding of the embodiment of intersectional identities by the women themselves in the host country's society and labour market, and, second, how the changing time, space and contexts interact to play a role in terms of the host society and its labour market's acceptance and level of tolerance shown towards this group's embodied intersectional presence.
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The Biden team's renewed focus on Afghanistan will inevitably affect tensions in Kabul, where a plan to replace the current government with an interim administration is back on…
Details
DOI: 10.1108/OXAN-DB259007
ISSN: 2633-304X
Keywords
Geographic
Topical
Mehtab Khan, Adnan Daud Khan, Muhammad Jawad, Zahoor Ahmad, Naveed Ur Rehman and Muhammad Israr
This paper aims to investigates a novel design of a modular moving magnet linear oscillating actuator (MMM-LOA) with the capability of coupling modules, based on their application…
Abstract
Purpose
This paper aims to investigates a novel design of a modular moving magnet linear oscillating actuator (MMM-LOA) with the capability of coupling modules, based on their application and space requirements.
Design/methodology/approach
Proposed design comprised of modules, and modules are separated by using nonmagnetic materials. Movable part of the proposed design of LOA is composed of permanent magnets (PMs) having axial magnetization direction and tubular structure. Stator of the proposed design is composed of one coil individually in a module. Dimensions of the design parameters are optimized through parametric analysis using COMSOL Multi Physics software. This design is analyzed up to three modules and their response in term of electromagnetic (EM) force and stroke are presented. Influence of adding modules is analyzed for both directions of direct current (DC) and alternating input loadings.
Findings
Proposed LOA shows linear increase in magnitude of EM force by adding modules. Motor constant of the investigated LOA is 264 N/A and EM force per PM mass is 452.389 N/kg, that shows significant improvement. Moreover, proposed LOA operates in feasible region of stroke for compressor application. Furthermore, this design uses axially magnetized PMs which are low cost and available in compact tubular structure.
Originality/value
Proposed LOA shows the influence of adding modules and its effect in term of EM force is analyzed for DC and alternating current (AC). Moreover, overall performance and structural topology is compared with state-of-the-art designs of LOA. Improvement with regard of motor constant and EM force per PM mass shows originality and scope of this paper.
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Tamer Koburtay, Ahmad Abualigah, Jawad Syed and Abbas J. Ali
This study seeks to offer a contextual, multilevel perspective on the impact of patriarchal culture and Islamic faith on issues facing women holding leadership positions in a…
Abstract
Purpose
This study seeks to offer a contextual, multilevel perspective on the impact of patriarchal culture and Islamic faith on issues facing women holding leadership positions in a Middle Eastern context.
Design/methodology/approach
Data were collected through 25 in-depth qualitative interviews along with open-ended questions in a paper-based survey. In view of the authors' research objectives, the authors purposively recruited participants who were identified as Muslim scholars (academics) and clerics (practitioners).
Findings
While the study challenges the prevailing stereotype that Islam holds women leaders back by referring to Islamic teachings that support gender equality, it also highlights the adverse impact of gender discriminatory misinterpretations of Islam for women leaders. The study identifies three interconnected, multilevel factors that lead to misinterpretations of Islamic teachings, i.e. (1) cultural factors (macro level – i.e. patriarchal and tribal culture), (2) organizational factors (meso level – i.e. organizational policies) and (3) individual factors (micro level – i.e. interpretations and practices of religion).
Research limitations/implications
This study contributes to the existing theory development of religion and women in leadership by presenting a novel model highlighting the interplay between religion, patriarchy and women in leadership.
Practical implications
The study recommends the application of a gender egalitarian system that enables full utilization of women's skills and capabilities by (1) reducing the discriminatory function of tribal culture and (2) identifying steps to reform inegalitarian gender practices in the Arab region.
Originality/value
The research is unique as it is the first time that a study has incorporated Muslim academic scholars' and clerics' views into gender and organization research. The study is thus contextually relevant and offers fresh multilevel insights on the interplay among religion, culture and gender.
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Muhammad Jawad Malik, Mudaser Ahmad, Muhammad Rizwan Kamran, Komal Aliza and Muhammad Zubair Elahi
The purpose of this paper is to investigate the relationships between students’ use of social media, their academic performance and creativity in the digital era.
Abstract
Purpose
The purpose of this paper is to investigate the relationships between students’ use of social media, their academic performance and creativity in the digital era.
Design/methodology/approach
This research used a survey strategy for collecting primary data required for this study from 334 students of undergraduate programs at Chinese universities who were sampled through a non-probability convenience approach.
Findings
The findings of the study reveal that students’ use of social media is positively associated with students’ academic performance and creativity. In addition, intrinsic motivation was found to be a mediating reason in the relationships between students’ use of social media and students’ academic performance and creativity.
Originality/value
This study explored an important role of intrinsic motivation as a mediator in the relationships between students’ use of social media and their positive outcomes. Studying the use of social media by students to their positive study outcomes is also practically important for students, educationalists and other policymakers.
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Syed Jawad Hussain Shahzad, Peter Josef Stauvermann, Ronald Ravinesh Kumar and Tanveer Ahmad
This study aims to examine the impact of terrorism on return and systematic risk of Pakistan’s equity industries. Daily data from 1 January 2000 to 31 December 2014 for 12…
Abstract
Purpose
This study aims to examine the impact of terrorism on return and systematic risk of Pakistan’s equity industries. Daily data from 1 January 2000 to 31 December 2014 for 12 industries based on the specific types of companies listed on Karachi Stock Exchange are used for the empirical analysis.
Design/methodology/approach
A multiplicative (additive) term is introduced in the standard capital asset pricing model to examine the change in systematic risk (industry returns) in response to the terrorist activities. The authors use the multiscale beta approach (Yamada, 2005) and the maximal overlap discrete wavelet transform (MODWT) to test the heterogeneous market hypothesis.
Findings
Terrorism activities increase the systematic risk for most of the industries and the negative impact on returns of banks and the financial industry. It is noted that terrorism positively impacts (increases) the industrial systematic risk mainly in short-run (between two and four days-time horizon).
Originality/value
The paper examines the impact of terrorism on a broad list of industries’ (banks, basic materials, chemicals, construction, consumer goods, consumer services, financials, industrials, minerals, oil and gas, textile and utilities) risk and return in Pakistan, using the multiscale beta approach (Yamada, 2005) and the MODWT methods.
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Ahmad Usman Shahid, Hafiza Sobia Tufail, Jawad Shahid and Aimen Ismail
The purpose of this study is to develop and empirically test a theoretical model of antecedents and consequences of perceived job security of professional accountants. This study…
Abstract
Purpose
The purpose of this study is to develop and empirically test a theoretical model of antecedents and consequences of perceived job security of professional accountants. This study contributes to the literature by examining the mediating role of perceived job security between the reward management system and the ethical job performance of professional accountants.
Design/methodology/approach
A survey was used to collect responses from professional accountants at small- and medium-tier accounting firms in Pakistan. Of the total 313 circulated research instruments, 270 were completed producing a response rate of 86%. The hypotheses were tested by performing structural equation modeling, confirmatory factor analysis and correlation using SPSS 24 and AMOS 25.
Findings
Findings specify that the perceived job security of professional accountants partially and fully mediates the relationship between their ethical job performance and intrinsic and rewards, respectively. Additionally, reward management systems including intrinsic and extrinsic rewards have a significant impact on the ethical job performance of professional accountants.
Practical implications
The findings of this study may have significant implications for researchers for examining the subjects' perceived job security in enhancing the overall performance of the firms. The findings may also benefit domestic and international accounting firms for recognizing the importance of rewards and job security for enhancing the ethical performance of accountants.
Originality/value
This study is the first to provide empirical evidence for the importance of perceived job security for professional accountants in Pakistan. The current research also provides sharper insights into establishing the direct impact of both extrinsic and intrinsic rewards on professional accountants' ethical job performance.