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Article
Publication date: 1 January 2024

Shrutika Sharma, Vishal Gupta, Deepa Mudgal and Vishal Srivastava

Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to…

Abstract

Purpose

Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates.

Design/methodology/approach

The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R2) and mean absolute error (MAE).

Findings

Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments.

Research limitations/implications

The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study.

Originality/value

This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.

Details

Rapid Prototyping Journal, vol. 30 no. 3
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 24 January 2024

Nirmal Singh, Harmanjit Singh Banga, Jaswinder Singh and Rajnish Sharma

This paper aims to prompt ideas amongst readers (especially librarians) about how they can become active partners in knowledge dissemination amongst concerned user groups by…

Abstract

Purpose

This paper aims to prompt ideas amongst readers (especially librarians) about how they can become active partners in knowledge dissemination amongst concerned user groups by implementing 3D printing technology under the “Makerspace.”

Design/methodology/approach

The paper provides a brief account of various tools and techniques used by veterinary and animal sciences institutions for information dissemination amongst the stakeholders and associated challenges with a focus on the use of 3D printing technology to overcome the bottlenecks. An overview of the 3D printing technology has been provided following the instances of use of this novel technology in veterinary and animal sciences. An initiative of the University Library, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, to harness the potential of this technology in disseminating information amongst livestock stakeholders has been discussed.

Findings

3D printing has the potential to enhance learning in veterinary and animal sciences by providing hands-on exposure to various anatomical structures, such as bones, organs and blood vessels, without the need for a cadaver. This approach enhances students’ spatial understanding and helps them better understand anatomical concepts. Libraries can enhance their visibility and can contribute actively to knowledge dissemination beyond traditional library services.

Originality/value

The ideas about how to harness the potential of 3D printing in knowledge dissemination amongst livestock sector stakeholders have been elaborated. This promotes creativity amongst librarians enabling them to think how they can engage in knowledge dissemination thinking out of the box.

Details

Library Hi Tech News, vol. 41 no. 2
Type: Research Article
ISSN: 0741-9058

Keywords

Article
Publication date: 5 May 2021

Samrat Gupta and Swanand Deodhar

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is…

Abstract

Purpose

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

Design/methodology/approach

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Findings

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

Research limitations/implications

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

Practical implications

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

Social implications

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

Originality/value

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

Details

Information Technology & People, vol. 37 no. 2
Type: Research Article
ISSN: 0959-3845

Keywords

Book part
Publication date: 3 April 2024

Christopher McMahon and Peter Templeton

In recent years, the relationship between Manchester United fans and their club has been put under the spotlight due to the contentious relationship between the fanbase and the…

Abstract

In recent years, the relationship between Manchester United fans and their club has been put under the spotlight due to the contentious relationship between the fanbase and the club’s American owners, the Glazer family. However, the commercialisation of Manchester United and their ramping up of their associated brand accelerated massively during the 1990s, as a result of the coincident timing of the country’s glamour club returning to dominance during a period of ever-greater financial returns for top-flight success. As the undoubted commercial trailblazers in English football (and the first English club to be listed on the Stock Exchange), analysing their development during the 1990s is, arguably, the best way of understanding how and why top-flight football clubs operate the way they do and, in a knock-on effect on the league’s competitiveness, why the clubs below them can so easily fall away.

Details

Contradictions in Fan Culture and Club Ownership in Contemporary English Football: The Game's Gone
Type: Book
ISBN: 978-1-83549-024-2

Keywords

Article
Publication date: 30 October 2023

Muhammad Adnan Hasnain, Hassaan Malik, Muhammad Mujtaba Asad and Fahad Sherwani

The purpose of the study is to classify the radiographic images into three categories such as fillings, cavity and implant to identify dental diseases because dental disease is a…

Abstract

Purpose

The purpose of the study is to classify the radiographic images into three categories such as fillings, cavity and implant to identify dental diseases because dental disease is a very common dental health problem for all people. The detection of dental issues and the selection of the most suitable method of treatment are both determined by the results of a radiological examination. Dental x-rays provide important information about the insides of teeth and their surrounding cells, which helps dentists detect dental issues that are not immediately visible. The analysis of dental x-rays, which is typically done by dentists, is a time-consuming process that can become an error-prone technique due to the wide variations in the structure of teeth and the dentist's lack of expertise. The workload of a dental professional and the chance of misinterpretation can be decreased by the availability of such a system, which can interpret the result of an x-ray automatically.

Design/methodology/approach

This study uses deep learning (DL) models to identify dental diseases in order to tackle this issue. Four different DL models, such as ResNet-101, Xception, DenseNet-201 and EfficientNet-B0, were evaluated in order to determine which one would be the most useful for the detection of dental diseases (such as fillings, cavity and implant).

Findings

Loss and accuracy curves have been used to analyze the model. However, the EfficientNet-B0 model performed better compared to Xception, DenseNet-201 and ResNet-101. The accuracy, recall, F1-score and AUC values for this model were 98.91, 98.91, 98.74 and 99.98%, respectively. The accuracy rates for the Xception, ResNet-101 and DenseNet-201 are 96.74, 93.48 and 95.65%, respectively.

Practical implications

The present study can benefit dentists from using the DL model to more accurately diagnose dental problems.

Originality/value

This study is conducted to evaluate dental diseases using Convolutional neural network (CNN) techniques to assist dentists in selecting the most effective technique for a particular clinical condition.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 17 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Open Access
Article
Publication date: 23 August 2023

Samuel Wayne Appleton and Diane Holt

Digitalisation is perceived as a new process that may add value to firms. Current theoretical understanding assumes it should be part of a firm's strategy to respond to multiple…

Abstract

Purpose

Digitalisation is perceived as a new process that may add value to firms. Current theoretical understanding assumes it should be part of a firm's strategy to respond to multiple pressures in the business environment. This paper explores the occurrence of digitalisation in a rare context, that of the English agricultural industry in the United Kingdom, a place disproportionality filled with family firms. The general understanding of digitalisation in family firm settings remains embryonic. The authors' explorations make theoretical contributions to research at the intersection of rural entrepreneurship, family business and innovation.

Design/methodology/approach

Utilising a purposive, qualitative approach, primary data was collected from multiple interviews with 28 UK family farms, and secondary data from another 164. Interview transcripts were coded using NVivo, along with secondary data from reports, observations and websites.

Findings

The authors present empirical evidence illustrating how digitalisation manifests incrementally and radically in different types of family farms. The authors present a model that shows the areas of farming that have, and continue to be, digitalised. This increases analytical precision when identifying digitalisation activities that differ depending on the strategy to either scale or diversify. The authors propose that incremental digitalising occurs to a great extent during a scaling strategy, and that radical digitalising occurs to a smaller extent during diversification strategies in family farms.

Research limitations/implications

This research uses a sample of family-run farms from the UK agricultural sector to explore nuanced elements of digitalisation. It should therefore be explored in other types of family firms located in different sectors and geographies.

Practical implications

This research is important because family farms are under increasing pressure and have limited financial resources to deal with the digitalisation agenda. Therefore, empirical evidence helps other farms in similar situations. The authors found digitalisation investments, that tend to be capital intensive, only matter for scalers and less so for diversifiers. Family farms can use the model presented as a tool to evaluate their farm. The tool helps them define what to do, and ideate the potential activities that might be digitalised, to feed into their wider strategy.

Social implications

Family firms, in particular farms, are critical to many economies. The general consenses currently assumes all family firms should digitalise, yet the authors' evidence suggests that this is not the case. It is important to create policies that are sensitive to the needs of different types of businesses, in this case between family firm scalers and diversifiers, instead of simply incentivising digitalisation using a blanket approach usually by offering financial aid. Understanding how digitisation can support (or not) family firm resilience and growth in an effective and efficient manner can have significant benefit to individual firms, and across industries.

Originality/value

The proposed model extends theoretical understanding linking strategy, digitalisation activity and innovation in family farms. It shows that digitalisation is a key building block of scaling strategies, maximising digitalisation to increase efficiency. Yet, diversifying family farms minimise digitalisation, whereby they only digitalise a small amount of the farming activity. This empirical evidence contrasts with the wider narrative that farmers are slower at using new technology. This research found that some are slower because it does not align with their strategy. However, sometimes digitalisation aligns with their strategy during external changes, in which case the diversifiers are quick to act.

Details

International Journal of Entrepreneurial Behavior & Research, vol. 30 no. 2/3
Type: Research Article
ISSN: 1355-2554

Keywords

Article
Publication date: 18 January 2024

Eunhye Son and Ki Han Kwon

This paper aims to in the modern world, possessing an attractive appearance is often considered a highly valued attribute. As such, the perceptions and satisfaction with one’s…

Abstract

Purpose

This paper aims to in the modern world, possessing an attractive appearance is often considered a highly valued attribute. As such, the perceptions and satisfaction with one’s body are shaped by dominant cultural norms. Adolescents, women in particular, who are heavily influenced by media representations, may tend to have a distorted body image (BI), including adopting extreme dieting methods. This study reviews the adverse effects of excessive weight loss associated with this.

Design/methodology/approach

The authors searched journals and the internet for relevant literature using the keywords “eating disorders”, “body image” and “weight stigma”. In the case study field, they added papers that considered “nutrition” to identify the link between dieting behaviour and nutrition. From these reviews, the authors ultimately selected 190 articles that appeared to meet their research objectives. The papers cover a range of studies published between 1995 and 2023.

Findings

Among adolescent girls and young women in their early 20s, there is a social media-driven culture of being extremely thin and petite. Weight stigma puts more pressure on them and makes strange behaviours like pro-ana syndrome a part of the culture. The authors have seen that modern BI standards leave young women vulnerable to eating disorders caused by excessive dieting.

Originality/value

Adolescence is a time of continuous growth, so balanced nutrition is essential. However, biased societal standards of beauty can push adolescent girls who are sensitive to external gaze into excessive dieting and make eating disorders a culture. This review provides a perspective on the behaviours that should be pursued for a healthy BI.

Details

Nutrition & Food Science , vol. 54 no. 2
Type: Research Article
ISSN: 0034-6659

Keywords

Article
Publication date: 4 December 2023

Fred Nimoh, Stephen Prah, Fred Yamoah and Doreen Agyei

In view of the increasing trend in food policies targeting the promotion of consumer interest in locally produced foods and growing developments in willingness-to-pay (WTP…

Abstract

Purpose

In view of the increasing trend in food policies targeting the promotion of consumer interest in locally produced foods and growing developments in willingness-to-pay (WTP) methodologies, the authors investigate consumer preference for packaged traditional drink asaana.

Design/methodology/approach

The study used a simple random sample of 336 consumers to draw on perception index and contingent valuation methods to evaluate consumers' perceptions of the attributes of packaged asaana – a traditional maize-based beverage produced in Ghana (also known as Ghana Coca-Cola). A tobit regression model was employed to analyze consumers’ WTP for the product.

Findings

Analyzing the factors that influence consumers' WTP for packaged asaana using the tobit regression model, the study established the existence of positive health and nutrition, economic benefits and purchasing decision-making perceptions for asaana. While the results further showed that consumers are willing to pay a premium for well-packaged asaana, demographics such as age, income level, labeling, price of the product and savings were found to exert significant influence on consumers’ WTP for packaged asaana. Salient recommendations for food processors and relevant government agencies and food policy implications are identified.

Research limitations/implications

Comprehending WTP provides valuable understanding regarding consumer qualms, actions and WTP for more secure traditional drinks and an examination of how the different factors that influence WTP for local beverages help boost local beverage production and guarantee employment.

Practical implications

Analyzing WTP data for traditional drinks reveals important implications for production, marketing and public health policies. Certification systems for traditional beverages may be beneficial, and the findings can be used to create public awareness campaigns about the safety of local drinks.

Originality/value

Assessing the WTP among Ghanaian consumers for traditional drinks, specifically asaana, is a ground-breaking study. The contingent evaluation (CE) and tobit regression approaches utilized in this research are strong, and the results obtained can guide decisions related to traditional drink production, marketing and the development of public health policies.

Details

British Food Journal, vol. 126 no. 3
Type: Research Article
ISSN: 0007-070X

Keywords

Article
Publication date: 27 March 2024

Ilija Djekic and Nada Smigic

The main purpose of this paper was to evaluate the validation process of food safety control measures.

Abstract

Purpose

The main purpose of this paper was to evaluate the validation process of food safety control measures.

Design/methodology/approach

The validation of control measures has been analyzed at 50 food companies in Serbia. The sample included companies that produce food of both plant and animal origin and have certified food safety management systems. A total of 156 control measures that combat physical hazards (41.6%), followed by microbial hazards (34.0%) and chemical hazards (24.4%), have been analyzed. To enable quantification of the validation protocols, each control measure was assigned a score.

Findings

The validation scores showed that the highest level of validation was observed in large companies, as opposed to small and medium-sized companies (p < 0.05). The type of food safety hazards and the food sector did not reveal any statistical differences in-between the scores. The main approach to validating control measures was referring to the technical documentation of equipment used (52.6%), followed by scientific and legal requirements (30.7%). Less than 20% of the analyzed control measures were validated with operational data collected on-site. No mathematical modeling was observed for the sampled food companies. Future steps should include the development of validation guides for different types of control measures and training modules.

Practical implications

This study can serve as an improvement guide for food safety consultants, food safety auditors, certification bodies, inspection services, food technologists and food managers.

Originality/value

This study is one of the first to provide an insight into how food companies validate their control measures to combat microbial, chemical and physical food safety hazards.

Details

British Food Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0007-070X

Keywords

Abstract

Details

Communicating Climate
Type: Book
ISBN: 978-1-83753-643-6

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