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Book part
Publication date: 19 November 2018

Crystal Abidin and Megan Lindsay Brown

Although the early conversations of microcelebrity centered on Anglo-centric theories and context despite the varied backgrounds and cultural context of microcelebrity, this…

Abstract

Although the early conversations of microcelebrity centered on Anglo-centric theories and context despite the varied backgrounds and cultural context of microcelebrity, this compilation of chapters seeks to assess and reframe the applications and uptake of microcelebrity around the world. Each of the chapters in this anthology contribute to expand the theoretical concept and contextualize the history and cultural affairs of those who are famous online. The case studies provide examples of how a microcelebrity emerges to fame because of their exposure and interaction within a group of niche users, a specific online community, or a specific cultural and geographical context through the social networks that emerge online. Academic scholarship on microcelebrity has crossed methodologies, disciplines and platforms demonstrating the wide appeal as the influence of these figures are on the rise. As preparation for the reader, this chapter offers a brief history of current scholarship, with an emphasis on shifting knowledge production away from an Anglo and Global North perspective. The introduction chapter serves as a road map for the reader breaking down each of the three sections of the book – norms, labors, and activism. Lastly, the co-editors have outlined different ways to read the text group chapters according to reader interest.

Details

Microcelebrity Around the Globe
Type: Book
ISBN: 978-1-78756-749-8

Keywords

Open Access
Article
Publication date: 17 April 2020

Mpho Edward Mashau, Afam Israel Obiefuna Jideani and Lucy Lynn Maliwichi

The purpose of this paper is to determine the effect of adding Aloe vera powder (AVP) in the production of mahewu with the aim of determining its shelf-life and sensory qualities.

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Abstract

Purpose

The purpose of this paper is to determine the effect of adding Aloe vera powder (AVP) in the production of mahewu with the aim of determining its shelf-life and sensory qualities.

Design/methodology/approach

Mahewu was produced at home (Sample B) and in the laboratory (Sample C) using a standard home-made procedure with the addition of AVP. A control mahewu (Sample A) was produced without AVP. Shelf-life was determined by following the chemical, microbiological, physical properties at 36 ± 2 °C for 60 days and the sensory properties of the products were also evaluated.

Findings

Physicochemical analysis revealed decreases in pH ranging between 3.3 and 2.4 from day 15–60 days of storage in all three samples. There was a significant increase (p < 0.05) in titratable acidity (0.2–1.8%) of all mahewu samples during storage. Total soluble solids were different amongst the samples from day 15 to day 60. The colour of the products was significantly different (p = 0.05) with respect to L*, a* and b* throughout the storage period. Microbiological results revealed an increase in coliforms bacteria, lactic acid bacteria, and yeast during storage. Sensory analysis showed that the control mahewu was more preferred than AVP added mahewu.

Practical implications

The study may help small-scale brewers to increase the shelf-life of mahewu.

Originality/value

Results of this study showed that the addition of AVP extended shelf-life of mahewu up to 15 days at 36 ± 2 °C.

Details

British Food Journal, vol. 122 no. 11
Type: Research Article
ISSN: 0007-070X

Keywords

Open Access
Article
Publication date: 14 September 2023

Ömer Tuğsal Doruk

This study aims to use a comparative analysis to examine the channel of deferring cash commitments, which can be seen as a strategic solution to mitigate the impact of COVID-19 on…

Abstract

Purpose

This study aims to use a comparative analysis to examine the channel of deferring cash commitments, which can be seen as a strategic solution to mitigate the impact of COVID-19 on Moldova's service sector.

Design/methodology/approach

This paper uses the Oaxaca–Blinder decomposition analysis. The World Bank's post-COVID-19 survey is used. The methodology takes into account heterogeneity among firms.

Findings

The results of the Oaxaca–Blinder decomposition analysis show that service firms use deferred cash commitments more than industrial firms, corporate governance and their pandemic-related strategies are also effective in the post-COVID Moldovan economy. The results are robust to different modeling alternatives.

Originality/value

COVID-19 can be considered a key source of uncertainty for firms, especially those operating in economies where financial frictions occasionally occur in a transition economy. Therefore, this study can shed new light on the impact of COVID-19 on financial strategies in a transition economy.

Details

Journal of Money and Business, vol. 3 no. 2
Type: Research Article
ISSN: 2634-2596

Keywords

Open Access
Article
Publication date: 25 February 2020

Richa Awasthy, Shayne Flint, Ramesh Sankarnarayana and Richard L. Jones

The purpose of this paper is to propose a framework to improve the effectiveness of university–industry collaboration (UIC). This work enhances the existing body of literature and…

42536

Abstract

Purpose

The purpose of this paper is to propose a framework to improve the effectiveness of university–industry collaboration (UIC). This work enhances the existing body of literature and knowledge regarding collaboration and offers concrete steps to be taken for effective collaboration between universities and industries.

Research Methodology

A literature review to study the best practices, impediments to collaboration and the various models proposed in the past for successful UIC was conducted. A workshop and focus-group meetings of practitioners and academic researchers was designed and organised to explore the current state of the university–industry engagement within the Australian Capital Territory (ACT) region and gather inputs regarding possible approaches to improve collaboration. The findings from the literature review and the results from this qualitative research regarding the approaches to improve the effectiveness of the collaboration were analysed.

Results and implications

The study discovers that various measures have been proposed in the form of best practices or models to improve the effectiveness of UIC. However, these measures often address a specific concern such as technology transfer, intellectual property (IP), etc. There is a scope for a comprehensive holistic framework to address many aspects of UIC in order to improve effectiveness and achieve success. A framework for improving the effectiveness of collaboration considering a comprehensive list of factors operating in a broad context within the collaboration system was proposed.

Originality/value

The framework builds on previous literature dealing with measures for successful UIC. However, it is the first of its kind, in the researcher's knowledge, in terms of comprehensiveness of the factors contributing to establishing and sustaining successful collaboration. The value of the individual experience of the participants in this qualitative research, which is on average more than 10 years in the software engineering field, validates the importance and quality of the data collected. The addition of these results to the framework increases its validity.The framework can be utilised by universities and industry practitioners to foster successful and effective collaboration. The results have significant relevance, particularly within the Australian context as the government has intensified the adoption of measures to encourage and improve collaboration between universities and the industry.

Details

Journal of Industry-University Collaboration, vol. 2 no. 1
Type: Research Article
ISSN: 2631-357X

Keywords

Open Access
Article
Publication date: 12 August 2022

Hesham El Marsafawy, Rumpa Roy and Fahema Ali

This study aims to identify the gap between the requirements of the accreditation bodies and the widely used learning management systems (LMSs) in assessing the intended learning…

2020

Abstract

Purpose

This study aims to identify the gap between the requirements of the accreditation bodies and the widely used learning management systems (LMSs) in assessing the intended learning outcomes (ILOs). In addition, this study aims to introduce a framework, along with the evaluation of the functionality of the LMS, for measuring the ILO.

Design/methodology/approach

A qualitative method was deployed to examine the gap between the requirements of the accreditation standards and the LMS functionalities. The researchers collaborated to design a mechanism, develop a system architecture to measure the ILO in alignment with the accreditation standards and guide the development of the Moodle plugin. The appropriateness and effectiveness of the plugin were evaluated within the scope of assessment mapping and design. Focus group interviews were conducted to collect feedback from the instructors and program leaders regarding its implementation.

Findings

The results of this study indicate that there is no standardized mechanism to measure course and program ILO objectively, using the existing LMS. The implementation of the plugin shows the appropriateness and effectiveness of the system in generating ILO achievement reports, which was confirmed by the users.

Originality/value

This study proposed a framework and developed a system architecture for the objective measurement of the ILO through direct assessment. The plugin was tested to generate consistent reports during the measurement of course and program ILO. The plugin has been implemented across Gulf University’s program courses, ensuring appropriate reporting and continuous improvement.

Details

Quality Assurance in Education, vol. 30 no. 4
Type: Research Article
ISSN: 0968-4883

Keywords

Open Access
Article
Publication date: 23 January 2023

Md.Tanvir Ahmed, Hridi Juberi, A.B.M. Mainul Bari, Muhommad Azizur Rahman, Aquib Rahman, Md. Ashfaqur Arefin, Ilias Vlachos and Niaz Quader

This study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining…

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Abstract

Purpose

This study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.

Design/methodology/approach

In this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).

Findings

The optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.

Research limitations/implications

The MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.

Originality/value

Most studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.

Details

International Journal of Industrial Engineering and Operations Management, vol. 5 no. 1
Type: Research Article
ISSN: 2690-6090

Keywords

Open Access
Article
Publication date: 24 February 2020

Nicola Cobelli and Andrea Chiarini

The main purpose of this exploratory study is to investigate the attitude of pharmacists, as small- and medium-sized enterprise (SME) owners, toward new technologies, and more…

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Abstract

Purpose

The main purpose of this exploratory study is to investigate the attitude of pharmacists, as small- and medium-sized enterprise (SME) owners, toward new technologies, and more precisely, toward the adoption of mobile apps for mobile health (mHealth). Such apps are generally used to improve customer satisfaction and loyalty. This study measures pharmacists’ subjective experiences of mobile apps for mHealth and aims to understand how these pharmacists make sense of these apps.

Design/methodology/approach

The study adopted the narrative inquiry technique combined with critical event analysis. Participants' experiences were categorized based on how they viewed new technology tools. Interpretative inductive analysis identified precise aspects of the sense making illustrative of non-adoption or confused adoption of new technologies by pharmacists.

Findings

This study investigates to what extent new technology tools such as mobile apps affect retailers and more precisely the reasons why mobile apps are and are not adopted by retailers, as potential users, in the pharmaceutical industry. We identified four aspects of sense making that illustrated non-adoption or confused adoption of new technologies by pharmacists. These aspects are deeply discussed in the paper and are referred to the dimensions of confusion to confidence; suspicion to trust; frustration to education; mistrust to cooperation.

Research limitations/implications

The main limitation of the present study is the limited number of territories investigated. This limitation arose because of the exploratory nature of the available research, which is generally based on case studies, and the lack of clear operationalization of the research available at the time of data collection. Another limitation is that the sample included only SMEs operating in the Italian pharmacy industry.

Originality/value

Many studies have highlighted the opportunities related to new mobile apps in the business-to-business market. Several have investigated customer interest in such new technology. If some contributions have indirectly investigated the acceptance of information technology tools, to the best of our knowledge, no study has been conducted to investigate directly and precisely the level of pharmacists' acceptance, use, and willingness to adopt information technology (e.g., mobile apps) for customer service in mHealth and mainly the reasons of non-adoption.

Details

The TQM Journal, vol. 32 no. 6
Type: Research Article
ISSN: 1754-2731

Keywords

Open Access
Article
Publication date: 13 March 2018

Ulla Gain

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human…

1960

Abstract

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human brain functions, for example, recognize the speaker, sense the tone of the text. On this paper, we present the similarities of these with human cognitive functions. We establish a framework which gathers cognitive functions into nine intentional processes from the substructures of the human brain. The framework, underpins human cognitive functions, and categorizes cognitive computing functions into the functional hierarchy, through which we present the functional similarities between cognitive service and human cognitive functions to illustrate what kind of functions are cognitive in the computing. The results from the comparison of the functional hierarchy of cognitive functions are consistent with cognitive computing literature. Thus, the functional hierarchy allows us to find the type of cognition and reach the comparability between the applications.

Details

Applied Computing and Informatics, vol. 16 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

Content available
Article
Publication date: 1 December 1999

45

Abstract

Details

Circuit World, vol. 25 no. 4
Type: Research Article
ISSN: 0305-6120

Open Access
Article
Publication date: 28 July 2020

R. Shashikant and P. Chetankumar

Cardiac arrest is a severe heart anomaly that results in billions of annual casualties. Smoking is a specific hazard factor for cardiovascular pathology, including coronary heart…

2613

Abstract

Cardiac arrest is a severe heart anomaly that results in billions of annual casualties. Smoking is a specific hazard factor for cardiovascular pathology, including coronary heart disease, but data on smoking and heart death not earlier reviewed. The Heart Rate Variability (HRV) parameters used to predict cardiac arrest in smokers using machine learning technique in this paper. Machine learning is a method of computing experience based on automatic learning and enhances performances to increase prognosis. This study intends to compare the performance of logistical regression, decision tree, and random forest model to predict cardiac arrest in smokers. In this paper, a machine learning technique implemented on the dataset received from the data science research group MITU Skillogies Pune, India. To know the patient has a chance of cardiac arrest or not, developed three predictive models as 19 input feature of HRV indices and two output classes. These model evaluated based on their accuracy, precision, sensitivity, specificity, F1 score, and Area under the curve (AUC). The model of logistic regression has achieved an accuracy of 88.50%, precision of 83.11%, the sensitivity of 91.79%, the specificity of 86.03%, F1 score of 0.87, and AUC of 0.88. The decision tree model has arrived with an accuracy of 92.59%, precision of 97.29%, the sensitivity of 90.11%, the specificity of 97.38%, F1 score of 0.93, and AUC of 0.94. The model of the random forest has achieved an accuracy of 93.61%, precision of 94.59%, the sensitivity of 92.11%, the specificity of 95.03%, F1 score of 0.93 and AUC of 0.95. The random forest model achieved the best accuracy classification, followed by the decision tree, and logistic regression shows the lowest classification accuracy.

Details

Applied Computing and Informatics, vol. 19 no. 3/4
Type: Research Article
ISSN: 2634-1964

Keywords

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