Gyanesh Govindarajan, K.A. Geetha, Santosh K. Patra and T.T. Sreekumar
This article attempts to highlight the defining role that community media engagements play during times of the pandemic. It is argued that the outbreak of COVID-19 pandemic forced…
Abstract
Purpose
This article attempts to highlight the defining role that community media engagements play during times of the pandemic. It is argued that the outbreak of COVID-19 pandemic forced community news media houses to reinvent their news reporting practices to cover issues pertaining to the marginalized and underprivileged sections of the society. It explores the role of community media in engaging and empowering the citizens during the COVID-19 pandemic.
Design/methodology/approach
Central to our study is the analysis of the news model of “Video Volunteers” (henceforth VV), an independent community-based online news platform based in India. To understand the level of citizen participation and engagement in the making and dissemination of news during the pandemic, the authors conducted 13 interviews with different stakeholders of VV, including founders and news audiences.
Findings
It seeks to reveal that when the mainstream media have failed to represent the issues of a local community, it is the independent media platforms like VV which function as a veritable source of information and sharing of knowledge. Most importantly, this paper emphasizes that the communicative model of independent community-based online platforms has been most successful in the coverage of the pandemic and the level of engagement with the citizenry.
Originality/value
The study contributes to the aspects of reciprocity and collaborative journalism in community news media and its potential impacts on news creation and dissemination.
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Saima Habib, Zulfiqar Ali Raza, Farzana Kishwar and Sharjeel Abid
Present study aimed to nanosilver-treat some commercially dyed denim fabric using an eco-friendly cross-linker of citric acid for possible application in the fabrication of…
Abstract
Purpose
Present study aimed to nanosilver-treat some commercially dyed denim fabric using an eco-friendly cross-linker of citric acid for possible application in the fabrication of sustainable antibacterial and nontoxic surgical gowns.
Design/methodology/approach
The conventional untreated surgical gowns are prone to bacterial attack making them unprotective and infection carriers. Thereby, nanosilver finishing of the surgical-grade dyed denim fabric was achieved via citrate cross-linking under the pad-dry-cure method. The hence treated denim fabrics were characterized for surface chemical, crystalline, textile, color and antibacterial attributes using both conventional and advanced analytical approaches.
Findings
The results expressed that the prepared denim specimens contained surface roughness at the nanoscale besides some alterations in their textile and color parameters. Both textile and comfort properties of the finished fabric remained in the acceptable range with effective antibacterial activity.
Practical implications
The silver nano-finished dyed denim expressed broad-spectrum antibacterial activity and qualified as a potential substrate in the fabrication of surgical gowns. Such sustainable application of nanosilver finishing could be perused for industrial implications.
Originality/value
This study presents citric acid as a crosslinking agent to impregnate the commercially dyed denim fabric for potential application in the fabrication of surgical gowns. The application of nanosilver on prior citrated dyed-grown fabrics could be a novel approach. This study used approximately all the reagents and auxiliaries as bio-based to ensure the nontoxicity and sustainability of the resultant fabric.
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Sandeep Kumar Reddy Thota, C. Mala and Geetha Krishnan
A wireless body area network (WBAN) is a collection of sensing devices attached to a person’s body that is typically used during health care to track their physical state. This…
Abstract
Purpose
A wireless body area network (WBAN) is a collection of sensing devices attached to a person’s body that is typically used during health care to track their physical state. This paper aims to study the security challenges and various attacks that occurred while transferring a person’s sensitive medical diagnosis information in WBAN.
Design/methodology/approach
This technology has significantly gained prominence in the medical field. These wearable sensors are transferring information to doctors, and there are numerous possibilities for an intruder to pose as a doctor and obtain information about the patient’s vital information. As a result, mutual authentication and session key negotiations are critical security challenges for wearable sensing devices in WBAN. This work proposes an improved mutual authentication and key agreement protocol for wearable sensing devices in WBAN. The existing related schemes require more computational and storage requirements, but the proposed method provides a flexible solution with less complexity.
Findings
As sensor devices are resource-constrained, proposed approach only makes use of cryptographic hash-functions and bit-wise XOR operations, hence it is lightweight and flexible. The protocol’s security is validated using the AVISPA tool, and it will withstand various security attacks. The proposed protocol’s simulation and performance analysis are compared to current relevant schemes and show that it produces efficient outcomes.
Originality/value
This technology has significantly gained prominence in the medical sector. These sensing devises transmit information to doctors, and there are possibilities for an intruder to pose as a doctor and obtain information about the patient’s vital information. Hence, this paper proposes a lightweight and flexible protocol for mutual authentication and key agreement for wearable sensing devices in WBAN only makes use of cryptographic hash-functions and bit-wise XOR operations. The proposed protocol is simulated using AVISPA tool and its performance is better compared to the existing methods. This paper proposes a novel improved mutual authentication and key-agreement protocol for wearable sensing devices in WBAN.
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Geetha Selvaraj and Jeonghwan Jeon
For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and…
Abstract
Purpose
For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania.
Design/methodology/approach
In recent years, a lot of research work has been done on trapezoidal interval type-2 fuzzy sets (TIT-2 FS), and many research works have been published. The trapezoidal interval type-2 fuzzy set helps effectively to represent the uncertainty comparatively than the type-1 fuzzy set. Taking advantage of this effectiveness, the authors extend the best multi-criteria decision making method (MCDM) for trapezoidal interval type-2 fuzzy sets. Here, ELimination and Choice Expressing REality III (ELECTRE III) method in the trapezoidal interval type-2 fuzzy set environment is proposed.
Findings
This analysis helps to the OECD countries to develop their level of innovation in the criteria. The authors are making this evaluation for the year 2018 based on the 31 criteria. Application of the proposed method expressed by evaluation of the national innovation capability problem. Based on the obtained results, the top five countries are United States, Switzerland, Canada, Germany and Japan.
Originality/value
The authors collected required data from different available data sources like OECD, IMD, USPTO, ITU and surveyed data reported by KISTEP. After collecting all the data from different sources, the authors calculated the standard values as KISTEP. After converting the standard values into trapezoidal interval type-2 fuzzy values, the authors construct a decision matrix based on these values. Then, the authors determined the possibility mean values and preference. Then, they calculated the concordance and discordance credibility degree values. Finally, they ranked OECD countries by the net credibility degree. The results are computed by using the MATLAB software.
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Albert Alexander Stonier, Gnanavel Chinnaraj, Ramani Kannan and Geetha Mani
This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms.
Abstract
Purpose
This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms.
Design/methodology/approach
The optimal modulation index along with the switching angles are calculated for an 11 level inverter. Harmonics are used to estimate the quality of output voltage and measuring the improvement of the power quality.
Findings
The simulation is carried out in MATLAB/Simulink for 11 levels of symmetric MLI and compared with the conventional inverter design. A solar photovoltaic array-based experimental setup is considered to provide the input for symmetric MLI. Field Programmable Gate Array (FPGA) based controller is used to provide the switching pulses for the inverter switches.
Originality/value
Attempted to develop a system with different optimization techniques.
Details
Keywords
Khalid Farooq and Mohd Yusoff Yusliza
This research offered a systematic and comprehensive literature review in analysing current studies on employee ecological behaviour (EEB) strategies and settings to determine…
Abstract
Purpose
This research offered a systematic and comprehensive literature review in analysing current studies on employee ecological behaviour (EEB) strategies and settings to determine various emphasised workplace ecological behaviour areas and contribute a precise mapping for future research.
Design/methodology/approach
This systematic literature review method involved 106 peer-reviewed articles published in reputable academic journals (between 2000 and the first quarter of 2021). This study was confined to a review of empirical papers derived from digital databases encompassing the terms ‘Employee green behaviour’, ‘Green behaviour at workplace’, ‘Employee ecological behaviour’, ‘Employee Pro-environmental behaviour’ and ‘Pro-environmental behaviour at workplace’ in the titles.
Findings
This study identified relevant journal articles (classified as EEB at work) from the current body of knowledge. Notably, much emphasis was identified on EEB over the past two decades. Overall, most studies employing quantitative approaches in both developed and emerging nations. Notably, ecological behaviour application garnered the most significant attention from scholars among the four focus areas in the literature review: (i) EEB concepts, models, or reviews, (ii) EEB application, (iii) EEB determinants and (iv) EEB outcomes.
Practical implications
Significant literature gaps indicate this field to be a relatively novel phenomenon. Thus, rigorous research on the topic proves necessary to develop a holistic understanding of the subject area.
Originality/value
This study expands the current body of knowledge by providing the first comprehensive systematic review on EEB themes, methods, applications, determinants, contextual focus, outcomes and recommending future research agenda.
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Tanveer Kajla, Sahil Raj and Amit Kumar Bhardwaj
The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based…
Abstract
The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.
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Putta Hemalatha and Geetha Mary Amalanathan
Adequate resources for learning and training the data are an important constraint to develop an efficient classifier with outstanding performance. The data usually follows a…
Abstract
Purpose
Adequate resources for learning and training the data are an important constraint to develop an efficient classifier with outstanding performance. The data usually follows a biased distribution of classes that reflects an unequal distribution of classes within a dataset. This issue is known as the imbalance problem, which is one of the most common issues occurring in real-time applications. Learning of imbalanced datasets is a ubiquitous challenge in the field of data mining. Imbalanced data degrades the performance of the classifier by producing inaccurate results.
Design/methodology/approach
In the proposed work, a novel fuzzy-based Gaussian synthetic minority oversampling (FG-SMOTE) algorithm is proposed to process the imbalanced data. The mechanism of the Gaussian SMOTE technique is based on finding the nearest neighbour concept to balance the ratio between minority and majority class datasets. The ratio of the datasets belonging to the minority and majority class is balanced using a fuzzy-based Levenshtein distance measure technique.
Findings
The performance and the accuracy of the proposed algorithm is evaluated using the deep belief networks classifier and the results showed the efficiency of the fuzzy-based Gaussian SMOTE technique achieved an AUC: 93.7%. F1 Score Prediction: 94.2%, Geometric Mean Score: 93.6% predicted from confusion matrix.
Research limitations/implications
The proposed research still retains some of the challenges that need to be focused such as application FG-SMOTE to multiclass imbalanced dataset and to evaluate dataset imbalance problem in a distributed environment.
Originality/value
The proposed algorithm fundamentally solves the data imbalance issues and challenges involved in handling the imbalanced data. FG-SMOTE has aided in balancing minority and majority class datasets.
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Veronica Allegrini and Fabio Monteduro
This chapter aims to contribute to the literature on sustainability in the public sector by discussing how human resource and human resource management can help to integrate…
Abstract
This chapter aims to contribute to the literature on sustainability in the public sector by discussing how human resource and human resource management can help to integrate environmental management into organizations and improve environmental performance. Public sector scholars have neglected the study of Green Human Resource Management (GHRM) until now. Nevertheless, implementing such practices could lead to positive outcomes regarding awareness of environmental issues, organizational reputation and attractiveness, job satisfaction and organizational performance. The authors discuss the relevance and the necessity of developing a field of research on GHRM in public organizations. Starting from a conceptual review of the main literature on GHRM, this chapter provided some directions for future research.