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Article
Publication date: 8 March 2024

Feng Zhang, Youliang Wei and Tao Feng

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to…

Abstract

Purpose

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.

Design/methodology/approach

This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.

Findings

Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.

Originality/value

This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

Keywords

Open Access
Article
Publication date: 9 October 2023

Aya Khaled Youssef Sayed Mohamed, Dagmar Auer, Daniel Hofer and Josef Küng

Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are…

Abstract

Purpose

Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today’s sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the art.

Design/methodology/approach

This paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these requirements.

Findings

As no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined requirements.

Originality/value

This paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today’s sophisticated – yet general – requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models.

Details

International Journal of Web Information Systems, vol. 20 no. 1
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 22 February 2024

Ranjeet Kumar Singh

Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The…

32

Abstract

Purpose

Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The purpose of this study is to propose a solution to this problem.

Design/methodology/approach

The current study identifies relevant literature and provides a review of big data adoption in libraries. It also presents a step-by-step guide for the development of a BDA platform using the Apache Hadoop Ecosystem. To test the system, an analysis of library big data using Apache Pig, which is a tool from the Apache Hadoop Ecosystem, was performed. It establishes the effectiveness of Apache Hadoop Ecosystem as a powerful BDA solution in libraries.

Findings

It can be inferred from the literature that libraries and librarians have not taken the possibility of big data services in libraries very seriously. Also, the literature suggests that there is no significant effort made to establish any BDA architecture in libraries. This study establishes the Apache Hadoop Ecosystem as a possible solution for delivering BDA services in libraries.

Research limitations/implications

The present work suggests adapting the idea of providing various big data services in a library by developing a BDA platform, for instance, providing assistance to the researchers in understanding the big data, cleaning and curation of big data by skilled and experienced data managers and providing the infrastructural support to store, process, manage, analyze and visualize the big data.

Practical implications

The study concludes that Apache Hadoops’ Hadoop Distributed File System and MapReduce components significantly reduce the complexities of big data storage and processing, respectively, and Apache Pig, using Pig Latin scripting language, is very efficient in processing big data and responding to queries with a quick response time.

Originality/value

According to the study, there are significantly fewer efforts made to analyze big data from libraries. Furthermore, it has been discovered that acceptance of the Apache Hadoop Ecosystem as a solution to big data problems in libraries are not widely discussed in the literature, although Apache Hadoop is regarded as one of the best frameworks for big data handling.

Details

Digital Library Perspectives, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2059-5816

Keywords

Article
Publication date: 15 March 2024

Florian Rupp, Benjamin Schnabel and Kai Eckert

The purpose of this work is to explore the new possibilities enabled by the recent introduction of RDF-star, an extension that allows for statements about statements within the…

Abstract

Purpose

The purpose of this work is to explore the new possibilities enabled by the recent introduction of RDF-star, an extension that allows for statements about statements within the Resource Description Framework (RDF). Alongside Named Graphs, this approach offers opportunities to leverage a meta-level for data modeling and data applications.

Design/methodology/approach

In this extended paper, the authors build onto three modeling use cases published in a previous paper: (1) provide provenance information, (2) maintain backwards compatibility for existing models, and (3) reduce the complexity of a data model. The authors present two scenarios where they implement the use of the meta-level to extend a data model with meta-information.

Findings

The authors present three abstract patterns for actively using the meta-level in data modeling. The authors showcase the implementation of the meta-level through two scenarios from our research project: (1) the authors introduce a workflow for triple annotation that uses the meta-level to enable users to comment on individual statements, such as for reporting errors or adding supplementary information. (2) The authors demonstrate how adding meta-information to a data model can accommodate highly specialized data while maintaining the simplicity of the underlying model.

Practical implications

Through the formulation of data modeling patterns with RDF-star and the demonstration of their application in two scenarios, the authors advocate for data modelers to embrace the meta-level.

Originality/value

With RDF-star being a very new extension to RDF, to the best of the authors’ knowledge, they are among the first to relate it to other meta-level approaches and demonstrate its application in real-world scenarios.

Details

The Electronic Library , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 13 September 2022

Haixiao Dai, Phong Lam Nguyen and Cat Kutay

Digital learning systems are crucial for education and data collected can analyse students learning performances to improve support. The purpose of this study is to design and…

Abstract

Purpose

Digital learning systems are crucial for education and data collected can analyse students learning performances to improve support. The purpose of this study is to design and build an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet.

Design/methodology/approach

A Learning Box has been build based on minicomputer and a web learning management system (LMS). This study presents different options to create such a system and discusses various approaches for data syncing. The structure of the final setup is a Moodle (Modular Object Oriented Developmental Learning Environment) LMS on a Raspberry Pi which provides a Wi-Fi hotspot. The authors worked with lecturers from X University who work in remote Northern Territory regions to test this and provide feedback. This study also considered suitable data collection and techniques that can be used to analyse the available data to support learning analysis by the staff. This research focuses on building an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet. Digital learning systems are crucial for education, and data collected can analyse students learning performances to improve support.

Findings

The resultant system has been tested in various scenarios to ensure it is robust when students’ submissions are collected. Furthermore, issues around student familiarity and ability to use online systems have been considered due to early feedback.

Research limitations/implications

Monitoring asynchronous collaborative learning systems through analytics can assist students learning in their own time. Learning Hubs can be easily set up and maintained using micro-computers now easily available. A phone interface is sufficient for learning when video and audio submissions are supported in the LMS.

Practical implications

This study shows digital learning can be implemented in an offline environment by using a Raspberry Pi as LMS server. Offline collaborative learning in remote communities can be achieved by applying asynchronized data syncing techniques. Also asynchronized data syncing can be reliably achieved by using change logs and incremental syncing technique.

Social implications

Focus on audio and video submission allows engagement in higher education by students with lower literacy but higher practice skills. Curriculum that clearly supports the level of learning required for a job needs to be developed, and the assumption that literacy is part of the skilled job in the workplace needs to be removed.

Originality/value

To the best of the authors’ knowledge, this is the first remote asynchronous collaborative LMS environment that has been implemented. This provides the hardware and software for opportunities to share learning remotely. Material to support low literacy students is also included.

Details

Interactive Technology and Smart Education, vol. 21 no. 1
Type: Research Article
ISSN: 1741-5659

Keywords

Article
Publication date: 13 October 2023

Hyun Ji Rim

This paper aims to provide a case study of complex conflict management within the arms race on the Korean Peninsula. Exploring the complex nexus of nuclear weapons, asymmetry and…

Abstract

Purpose

This paper aims to provide a case study of complex conflict management within the arms race on the Korean Peninsula. Exploring the complex nexus of nuclear weapons, asymmetry and a qualitative arms race, the study explains how the arms race between Seoul and Pyongyang has promoted stability on the Korean Peninsula.

Design/methodology/approach

Presenting the limits of arguments that the US security guarantee is the factor that saved the two Koreas from going to war again, this paper explores the utility of the inter-Korean arms race as a stabilizer that promotes indirect negotiations. While presenting Korean anomalies, this paper analyzes the three stages of the inter-Korean arms race – especially its nuclear weapons, its asymmetry and the nature of arms races – and provides extant explanations on the causes and consequences of the qualitative arms race. These key elements drive the states’ strategic motives.

Findings

Using the case of the inter-Korean qualitative arms race and US extended nuclear deterrence on the Korean Peninsula, the study shows the complexities of conflict management today. This paper identifies three contributing factors – US nuclear weapons, asymmetry and the qualitative characteristic of the arms race – to explain the enduring stability on the peninsula despite the arms race’s intensification. The paper finds that although US nuclear-extended deterrence plays a critical role, it does not capture the full context of the ongoing, dynamic inter-Korean arms race; a prolonged arms race between the two Koreas has become a new regularity; the qualitative characteristic of the inter-Korean arms race, which is driven by technological advancement, contributes to stability in the arms race; and as the constant mismatch in priority technologies becomes more severe, the changes to the existing asymmetry could increase instability.

Originality/value

This paper offers a diverse perspective to the literature on conflict management and captures the complexities of 21st-century conflict management. Through a thorough examination of the inter-Korean arms race, it brings readers’ attention to the nested dynamics within the arms race and shows how an intensifying arms race can promote stability. Furthermore, the paper explains the implications for potential instability – fueled by the comprehensive mix of a dynamic qualitative arms race and the US extended nuclear deterrence – in the Indo-Pacific region.

Details

International Journal of Conflict Management, vol. 35 no. 1
Type: Research Article
ISSN: 1044-4068

Keywords

Article
Publication date: 4 October 2022

Akanksha Jaiswal, Santoshi Sengupta, Madhusmita Panda, Lopamudra Hati, Verma Prikshat, Parth Patel and Syed Mohyuddin

The COVID-19 pandemic and technological advancements have enabled employees to telework. Referring to this emerging phenomenon, the authors aim to examine how employees' levels of…

1502

Abstract

Purpose

The COVID-19 pandemic and technological advancements have enabled employees to telework. Referring to this emerging phenomenon, the authors aim to examine how employees' levels of trust in management mediated by psychological well-being impact their performance as they telework. Deploying the theoretical lens of person-environment misfit, the authors also explore the role of technostress in the trust-wellbeing-performance relationship.

Design/methodology/approach

The data was collected from 511 full-time service sector employees across Indian organizations through a structured survey questionnaire. The proposed moderation-mediation model for this study was tested using structural equation modeling and bootstrapping method.

Findings

Structural equation modeling results indicate that trust in management significantly impacts employee performance while teleworking. While psychological well-being was observed as a significant mediator, technostress played the moderator role in the trust-performance relationship. The moderated-mediation effect of psychological well-being in the trust-performance relationship was stronger when technostress was low and weaker when technostress was high.

Research limitations/implications

The authors extend the person-environment misfit theory in the context of telework, highlighting the role of technostress that may impact the trust-wellbeing- performance relationship in such work settings.

Practical implications

The study informs leaders and managers on balancing delicate aspects such as employee trust and well-being that significantly impact performance as they telework. The authors also highlight the critical role of managers in respecting employees' personal and professional boundaries to alleviate technostress.

Originality/value

The authors make a novel theoretical contribution to the emerging literature on teleworking by examining the trust-psychological wellbeing-performance link and the role of technostress in this relationship.

Details

International Journal of Manpower, vol. 45 no. 1
Type: Research Article
ISSN: 0143-7720

Keywords

Article
Publication date: 8 May 2023

S.M. Aparna and Sangeeta Sahney

The study aims to explore the effectiveness of performance-oriented practices like high-performance work practices (HPWPs) in higher education (HE), given its explicit focus on…

Abstract

Purpose

The study aims to explore the effectiveness of performance-oriented practices like high-performance work practices (HPWPs) in higher education (HE), given its explicit focus on performance these days.

Design/methodology/approach

The study uses hierarchical linear modeling using statistical package for social sciences (SPSS 22.0) to test the hypotheses. An intertwined framework of the ability–motivation–opportunity (AMO) model and the job demand-resources (JD-R) model was proposed. The study considered strategic hiring, recognition and participatory decision-making as ability, motivation and opportunity-enhancing practices respectively. Further, the study addressed the impact of institutional level moderators, like administrative workload (AWL) and support staff (SS).

Findings

The findings based on the responses of 385 faculties and 443 students from 36 Indian institutes, indicated that HPWPs enhanced the education performance (EP) of HE institutes. Further, results revealed that both AWL and SS had differential effects on the relationship between HPWPs and EP. Contrary to authors’ expectations, SS showed a negative effect of the relationship between HPWPs and EP.

Research limitations/implications

The increased AWL was debilitating the beneficial effects HPWPs. The negative interaction effect of SS sheds light on the hidden issues surrounding SS in HE institutes. Based on findings, the study offered important theoretical and practical implications.

Originality/value

To the best of authors’ knowledge, the impact of innovative human resource (HR) practices in academia remains relatively under-researched, and the current study is an attempt to fill this void.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 3
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 29 March 2024

Sihao Li, Jiali Wang and Zhao Xu

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information…

Abstract

Purpose

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information carried by BIM models have made compliance checking more challenging, and manual methods are prone to errors. Therefore, this study aims to propose an integrative conceptual framework for automated compliance checking of BIM models, allowing for the identification of errors within BIM models.

Design/methodology/approach

This study first analyzed the typical building standards in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage, and a data extraction method based on the Dynamo is designed to obtain checking data files. After that, a matching algorithm is devised to express the logical rules of knowledge graph triples, resulting in automated compliance checking for BIM models.

Findings

Case validation results showed that this theoretical framework can achieve the automatic construction of domain knowledge graphs and automatic checking of BIM model compliance. Compared with traditional methods, this method has a higher degree of automation and portability.

Originality/value

This study introduces knowledge graphs and natural language processing technology into the field of BIM model checking and completes the automated process of constructing domain knowledge graphs and checking BIM model data. The validation of its functionality and usability through two case studies on a self-developed BIM checking platform.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 30 April 2021

Faruk Bulut, Melike Bektaş and Abdullah Yavuz

In this study, supervision and control of the possible problems among people over a large area with a limited number of drone cameras and security staff is established.

Abstract

Purpose

In this study, supervision and control of the possible problems among people over a large area with a limited number of drone cameras and security staff is established.

Design/methodology/approach

These drones, namely unmanned aerial vehicles (UAVs) will be adaptively and automatically distributed over the crowds to control and track the communities by the proposed system. Since crowds are mobile, the design of the drone clusters will be simultaneously re-organized according to densities and distributions of people. An adaptive and dynamic distribution and routing mechanism of UAV fleets for crowds is implemented to control a specific given region. The nine popular clustering algorithms have been used and tested in the presented mechanism to gain better performance.

Findings

The nine popular clustering algorithms have been used and tested in the presented mechanism to gain better performance. An outperformed clustering performance from the aggregated model has been received when compared with a singular clustering method over five different test cases about crowds of human distributions. This study has three basic components. The first one is to divide the human crowds into clusters. The second one is to determine an optimum route of UAVs over clusters. The last one is to direct the most appropriate security personnel to the events that occurred.

Originality/value

This study has three basic components. The first one is to divide the human crowds into clusters. The second one is to determine an optimum route of UAVs over clusters. The last one is to direct the most appropriate security personnel to the events that occurred.

Details

International Journal of Intelligent Unmanned Systems, vol. 12 no. 1
Type: Research Article
ISSN: 2049-6427

Keywords

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