Abstract
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Abstract
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Abstract
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Abstract
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Abstract
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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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Anurag K. Srivastava, Sukumar Kamalasadan, Daxa Patel, Sandhya Sankar and Khalid S. Al‐Olimat
The electric power industry has been moving from a regulated monopoly structure to a deregulated market structure in many countries. The purpose of this study is to…
Abstract
Purpose
The electric power industry has been moving from a regulated monopoly structure to a deregulated market structure in many countries. The purpose of this study is to comprehensively review the existing markets to study advantages, issues involved and lessons learnt to benefit emerging electricity markets.
Design/methodology/approach
The paper employs a comprehensive review of existing competitive electricity market models in USA (California), UK, Australia, Nordic Countries (Norway), and developing country (Chile) to analyze the similarities, differences, weaknesses, and strengths among these markets based on publically available data, literature review and information.
Findings
Ongoing or forthcoming electricity sector restructuring activities in some countries can be better designed based on lessons learnt from existing markets and incorporating their own political, technical and economical contexts. A template for design of successful electricity market has also been presented.
Research limitations/implications
This study is limited to a comparative analysis of five markets and can be extended in the future for other existing and emerging electricity markets.
Practical implications
The discussed weaknesses and strengths of existing electricity markets in this study can be practically utilized to improve the electricity industry market structures leading to several social benefits including lower electricity cost.
Originality/value
The comprehensive review and analysis of five existing markets, physically located in different continents, may be used as an assistance or reference guide to benefit the emerging electricity markets in other countries.
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Mohamed El-Sayed Mousa and Mahmoud Abdelrahman Kamel
This study aims to examine performance assessment of organizational units through psychological empowerment (PE) and employee engagement (EE) approach and whether this…
Abstract
Purpose
This study aims to examine performance assessment of organizational units through psychological empowerment (PE) and employee engagement (EE) approach and whether this relationship differs among efficient and inefficient organization units.
Design/methodology/approach
This study drew on merging the principal component analysis (PCA), data envelopment analysis (DEA) and partial least square-multigroup analysis (PLS-MGA) to benchmark the performance of organizational units affiliated with Zagazig University in Egypt using PE dimensions as inputs and EE as output. Besides investigating whether PE inputs have the same effect among efficient and inefficient units.
Findings
Performance assessment based on independent data showed that all the investigated organizational units are not at the same efficiency level. The results revealed that there are eight efficient units versus seven inefficient ones. Moreover, PLS-MGA results demonstrated that no significant differences concerning the impact of PE inputs on EE between efficient and inefficient units groups. Nevertheless, the effect of these inputs was slightly higher in the former.
Originality/value
Studies on EE performance in the service sector are scarce in the literature, this study is a novel contribution of exploring EE efficiency in Egypt as a developing economy. Specifically, using the PCA-DEA-structural equation modeling approach.
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Natashaa Kaul, Amruta Deshpande, Amit Mittal, Rajesh Raut and Harveen Bhandari
This study aims to examine the research that examines psychological empowerment (PE) and employee engagement (EE) via bibliometric analysis. The study also aims to offer an…
Abstract
Purpose
This study aims to examine the research that examines psychological empowerment (PE) and employee engagement (EE) via bibliometric analysis. The study also aims to offer an overview of the present state of research and indicate potential future research topics.
Design/methodology/approach
The literature on PE and engagement was reviewed using bibliometric analysis based on publications in the Scopus database. The analysis comprises a three-field plot, theoretical framework examination, thematic analysis and quantitative analysis of the most frequently referenced publications, affiliations, countries and authors.
Findings
The study identifies research trends such as the use of the leadership lens, the examination of the different degrees of empowerment, the examination of alternate mechanisms to improve engagement and the impact of supervisor resources on these constructs. The study also suggests areas for future research, such as the influence of leadership and organizational culture on these two factors, the link between PE and EE and the impact of the changing structure of work via the increased use of technology and new work relations like gig work on these concepts.
Originality/value
This study offers a thorough and systematic overview of the state of the research in the area of PE and EE. This study emphasizes the significance of PE and engagement in management by giving a thorough overview of the present state of research and outlining future research possibilities.