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Book part
Publication date: 4 March 2024

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Managing Destinations
Type: Book
ISBN: 978-1-83797-176-3

Book part
Publication date: 31 January 2024

Mairi Gunn, Irene Hancy and Tania Remana

This chapter reports on research that explores new and emerging extended reality [XR] technologies and how they might provide opportunities to trial, investigate, and put into…

Abstract

This chapter reports on research that explores new and emerging extended reality [XR] technologies and how they might provide opportunities to trial, investigate, and put into practice their potential to reverse processes of atomisation, polarisation, and intercultural discomfort, in our contemporary society. This transdisciplinary practice-led research was underpinned by disciplines of computer science and engineering, social sciences, history, diverse community economics, human ecology, and Indigenous psychology. The collaboration between these various disciplines with the Māori and non-Māori community members allowed researchers to understand current societal stressors, prioritise relationality, and explore our shared values in the creation of XR experiences for exhibition in the galleries, libraries, archives, and museums [GLAM] sector.

A discursive design framework motivated, inspired, provoked, persuaded, and reminded inspiring collaborators, and visitors to the exhibitions, the value of (re)connecting with people and overcoming interracial awkwardness through these curated experiences. The XR technologies provided women a platform to discuss and reimagine first encounters between people from different cultural backgrounds. The technologies included a 180° stereoscopic projection, Common Sense, in which Māori Elder Irene Hancy shared her insight about social engagement and haptic HONGI in which visitors were greeted by a Māori woman Tania Remana via augmented reality. This research has been motivated by a desire to promote and support intercultural understanding in Aotearoa New Zealand, and it extends research by other non-Māori and Māori scholars.

Details

Data Curation and Information Systems Design from Australasia: Implications for Cataloguing of Vernacular Knowledge in Galleries, Libraries, Archives, and Museums
Type: Book
ISBN: 978-1-80455-615-3

Keywords

Article
Publication date: 27 September 2023

Veera Harsha Vardhan Jilludimudi, Daniel Zhou, Eric Rubstov, Alexander Gonzalez, Will Daknis, Erin Gunn and David Prawel

This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that…

Abstract

Purpose

This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects.

Design/methodology/approach

A set of sensors was created to collect real-time, in situ data from polymer ME 3D printing. A variance analysis was completed to identify an “acceptable” range for filament diameter on a popular desktop 3D printer. These data were used as the basis of a quality evaluation process to non-destructively identify spatial regions of printed parts in multi-part builds that contain defects.

Findings

Anomalous parts were correctly identified non-destructively using only in situ collected data.

Research limitations/implications

This methodology was developed by varying the filament diameter, one of the most common reasons for print failure in ME. Numerous other printing parameters are known to create faults in melt extruded parts, and this methodology can be extended to analyze other parameters.

Originality/value

To the best of the authors’ knowledge, this is the first report of a non-destructive evaluation of 3D-printed part quality using only in situ data in ME. The value is in improving part quality and reliability in ME, thereby reducing 3D printing part errors, plastic waste and the associated cost of time and material.

Article
Publication date: 5 October 2023

Kaikai Shi, Hanan Lu, Xizhen Song, Tianyu Pan, Zhe Yang, Jian Zhang and Qiushi Li

In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn…

Abstract

Purpose

In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions.

Design/methodology/approach

This paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss.

Findings

The data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%.

Originality/value

The originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 34 no. 1
Type: Research Article
ISSN: 0961-5539

Keywords

Book part
Publication date: 25 March 2024

Heather Yaxley

Informal conversational encounters are explored using free indirect discourse (FID) as a novel storytelling method to gain a multi-generational understanding of the experiences of…

Abstract

Informal conversational encounters are explored using free indirect discourse (FID) as a novel storytelling method to gain a multi-generational understanding of the experiences of women working in public relations (PR) in 1960s/1970s Britain.

Echoing a literary tradition, anonymised transcripts of recordings provide impressionist accounts that immerse the reader in the thoughts and feelings of novelistic characters. An informal network of women narrate their stories with a much younger listener enabling exploration of intergenerational relationships and the intersection of gender and age.

This unstructured approach develops a complex yet natural flow to create unique withness-understandings. The author/narrator introduces a conception of informal conversational encounters, supporting an organic approach of interweaving storying, everyday performance, situated accountings, narrative unfoldings and inside/outside points of view.

An interplay of multiple female voices reveals a degree of symmetry in fractal patterns of women's early career experiences over the duration of a generation. Facilitation of sense-making through intergenerational conversations connects with Mannheim's theory of generational unity.

Women's beginnings of PR careers in 1960s/1970s Britain demonstrate a liberal feminist perspective in taking responsibility for their careers and enjoyment beyond the workplace in a man's world.

Book part
Publication date: 22 January 2024

Özcan Zorlu, Ali Avan and Ahmet Baytok

The objective of this study is to make a conceptual analysis of Community-based tourism (CBT). CBT, one of the tourism activities that internalised sustainability, has several…

Abstract

The objective of this study is to make a conceptual analysis of Community-based tourism (CBT). CBT, one of the tourism activities that internalised sustainability, has several common threads with nature-based tourism activities. However, these similarities/common elements must be more understandable between those relevant tourism activities. From this fact, this research aims to assign a theoretical framework for CBT and reveal the differences between CBT activities from other tourism types.

Tourism, unavoidably, is one of the critical sectors that require sustainable usage of resources. Because visiting natural, historical and cultural values/attractions constitute the primary reason for tourists' travel motivations, making those values/attractions sustainable for the future is essential. However, the sustainable usage of those values/attractions can be enabled with protection and maintenance balance. On the other hand, this philosophy will only come true if obtaining the locals support it. Therefore, CBT propounds that local people should make the most of tourism at all levels, especially the economic contribution. Within this context, the importance and necessity of these issues will be manifested in this chapter, presenting a conceptual framework. Additionally, this chapter will support other researchers in constituting the conceptual framework and will guide policymakers and other stakeholders to understand the importance of CBT.

Book part
Publication date: 16 January 2024

Monika Prakash, Mohammed Ashraf, Pinaz Tiwari and Nimit Chowdhary

Although the concept of destination is often described as an economic term that describes places of interest for tourists and visitors, currently, there is still little awareness…

Abstract

Although the concept of destination is often described as an economic term that describes places of interest for tourists and visitors, currently, there is still little awareness in the extant literature about regional, city, village, resort, or even standalone tourist destinations. This chapter aims to clarify the meaning of destinations. It distinguishes the differences between common locations and tourist destinations. It uses case studies to describe places, placemaking, and the experiencescapes of various destinations. This contribution implies that tourist attractions differentiate themselves from other places, as they offer accessible attractions with amenities.

Details

Tourism Planning and Destination Marketing, 2nd Edition
Type: Book
ISBN: 978-1-80455-888-1

Keywords

Article
Publication date: 4 October 2022

Dhruba Jyoti Borgohain, Raj Kumar Bhardwaj and Manoj Kumar Verma

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is…

1825

Abstract

Purpose

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

Design/methodology/approach

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

Findings

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

Practical implications

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

Originality/value

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

Details

Library Hi Tech, vol. 42 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

Book part
Publication date: 29 January 2024

Benjamin Apelojg

Student interest and learning success is an important component of teaching learning research. However, while the impact of emotions and psychological needs on students'…

Abstract

Purpose

Student interest and learning success is an important component of teaching learning research. However, while the impact of emotions and psychological needs on students' achievements has been a focus of research, the impact of their physiological needs has been under studied. In this explorative study, I examine what impact the physiological and psychological needs of student teachers have on their feelings, motivation, and interest in different learning settings.

Approach

The research method used was the daily reconstruction method and included the Felix-App, a new digital research and feedback tool that allows the measurement of feelings, needs, motivation, and interest in real time.

Findings

The results suggest the importance of physiological needs for perceived emotions, motivation, and interest in the learning subject. The psychological needs, on the other hand, are of less importance.

Originality

The Felix-App is an innovative tool to learn more about learners' emotions and needs in real learning settings. The importance of physiological needs has been known since Maslow, but should be considered much more in the context of teaching and learning research in the future. There is a need for further research on the importance of physical aspects in learning.

Abstract

Details

A New Left Economics: An Economy with a Social Conscience
Type: Book
ISBN: 978-1-80455-402-9

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