scholarly journals A Methodological Review of Systematic Literature Reviews in Higher Education: Heterogeneity and Homogeneity

2021 ◽  
Author(s):  
Sin Wang Chong ◽  
Lin Ting Jun ◽  
Yulu Chen
Keyword(s):  
Higher Education ◽  
Future Research ◽  
Research Directions ◽  
Methodological Review ◽  
The Past ◽  
Interdisciplinary Field ◽  
Wide Range ◽  
Literature Reviews ◽  
Research Findings ◽  
Future Research Directions

The field of higher education research has bourgeoned in the past decades, addressing a wide range of topics. Being in a rapidly expanding and interdisciplinary field of research, higher education scholars have demonstrated exigency for aggregating research findings to map the research landscape, identify future research directions, and bridge the research-practice divide. In this connection, systematic literature reviews have been carried out to consolidate research findings. With a proliferation of systematic literature reviews in higher education, the aim of this meta, methodological review is to provide a state-of-the-art systematic literature review methodologies in the field of higher education. Adhering to the exploratory nature of this study, this review analyses systematic literature reviews published in 16 top-tiered international journals in higher education (n=160). Through qualitative research synthesis using thematic analysis and informed by grounded theory, a methodological framework comprising six stages and 20 steps is developed, which might help to instigate methodological dialogue between researchers when it comes to conducting systematic literature reviews. A handy checklist for conducting and evaluating systematic literature reviews in higher education is created.

scholarly journals Fatigue modeling using neural networks: a comprehensive review

2021 ◽  
Author(s):  
Jie Chen ◽  
Yongming Liu
Keyword(s):  
Life Prediction ◽  
Current Trend ◽  
Future Research ◽  
Fatigue Load ◽  
Research Directions ◽  
Comprehensive Review ◽  
The Past ◽  
Wide Range ◽  
Future Research Directions ◽  
Fatigue Modeling

Neural network (NN) models have made a significant impact on fatigue-related engineering communities and are expected to increase rapidly soon due to the recent advancements in machine learning and artificial intelligence. A comprehensive review of fatigue modeling methods using NNs is lacking and will help to recognize past achievements and suggest future research directions. Thus, this paper presents a survey of 251 publications between 1990 and July 2021. The NN modeling in fatigue is classified into five applications: fatigue life prediction, fatigue crack, fatigue damage diagnosis, fatigue strength, and fatigue load. A wide range of NN architectures are employed in the literature and are summarized in this review. An overview of important considerations and current limitations for the application of NNs in fatigue is provided. Statistical analysis for the past and the current trend is provided with representative examples. Existing gaps and future research directions are also presented based on the reviewed articles.

Research trend of joint ventures in construction: a two-decade taxonomic review

2014 ◽  
Vol 12 (2) ◽  
pp. 118-141 ◽  
Author(s):  
Yuming Hong ◽  
Daniel W.M. Chan
Keyword(s):  
Research Methods ◽  
Joint Ventures ◽  
Research Trend ◽  
Future Research ◽  
Research Directions ◽  
Content Type ◽  
Or Management ◽  
The Past ◽  
Research Findings ◽  
Future Research Directions

Purpose – This paper aims to systematically and critically explore the research trend of construction joint ventures (CJVs) in some selected leading construction journals over the past two decades between 1993 and 2012. It is also expected that some valuable insights into the extended application of JVs to facilities service management and maintenance could be generated from the research findings. Design/methodology/approach – A powerful search engine “Scopus” was selected to identify those journals that have published CJV-related articles. The papers related to CJVs, as retrieved from the selected journals, were first classified based on their relevance to CJV study and were then analyzed in terms of the annual number of CJV-related publications, research focus of CJV studies and the applied research methods and techniques. Future research directions are suggested to enrich and add value to the extant literature about CJVs. Findings – An apparent increasing trend of research on CJVs has been witnessed over the past two decades. A critical analysis of the two-decade research outputs indicated that research topics of CJVs published in the selected journals consist of several key areas: theory and model development; motives, benefits and other strategic demands of application; performance measurement or management; risk assessment or management; influential factors for practice; problematic issues and challenges in practice; and managerial practices of CJVs in the industry. This study also identified that the research methods employed in CJV studies are predominantly questionnaire survey, case study, literature review/analysis, and interview. Research techniques applied in CJV studies were classified into seven main groups, with rank-order analysis, structural equation modelling and regression analysis being the three mostly adopted analytical tools. Research limitations/implications – The critical review of CJV literature reveals several inherent limitations of the existing research and practices of CJVs, The research findings also help visualize future research directions associated with the identification of barriers to the adoption and successful operation of CJVs, investigation of the appropriateness and effectiveness of CJV contracting strategies, and exploration into possible strategies for improving the industrial applications in future. Originality/value – Joint ventures have been extensively used in the construction sector, which calls for the need of more rigorous and meaningful research to guide the appropriate and effective use of it. The findings of this taxonomic review could provide useful insights towards researchers into shaping their research foci under the umbrella of CJVs to suit the demands of both the literature base and the real construction market.

Direct modulation of the gut microbiota as a therapeutic approach for Alzheimer’s disease

2021 ◽  
Vol 20 ◽  
Author(s):  
Yi Wang ◽  
Gary A. Dykes
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gut Microbiota ◽  
Future Research ◽  
Research Directions ◽  
Progressive Decline ◽  
Direct Modulation ◽  
Wide Range ◽  
Research Findings ◽  
Future Research Directions

: Alzheimer’s disease is a neurodegenerative disease characterized by a progressive decline in memory and cognitive functions. It is a multifactorial disease involving a wide range of pathological factors that are not fully understood. As supported by a growing amount of evidence in recent years, the gut microbiota plays an important role in the pathogenesis of Alzheimer’s disease through the brain-gut-microbiota axis. This suggests that direct modulation of the gut microbiota can be a potential therapeutic target for Alzheimer’s disease. This review summarizes recent research findings on the modulation of the gut microbiota by probiotic therapies and faecal microbiota transplantation for controlling the pathologies of Alzheimer’s disease. Current limitations and future research directions of this field are also discussed.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

scholarly journals A matrix-less method to approximate the spectrum and the spectral function of Toeplitz matrices with real eigenvalues

2021 ◽  
Author(s):  
Sven-Erik Ekström ◽  
Paris Vassalos
Keyword(s):  
Distribution Function ◽  
Asymptotic Distribution ◽  
Numerical Experiments ◽  
Toeplitz Matrices ◽  
Future Research ◽  
Research Directions ◽  
Numerical Examples ◽  
Working Hypothesis ◽  
Wide Range ◽  
Future Research Directions

AbstractIt is known that the generating function f of a sequence of Toeplitz matrices {Tn(f)}n may not describe the asymptotic distribution of the eigenvalues of Tn(f) if f is not real. In this paper, we assume as a working hypothesis that, if the eigenvalues of Tn(f) are real for all n, then they admit an asymptotic expansion of the same type as considered in previous works, where the first function, called the eigenvalue symbol $\mathfrak {f}$ f , appearing in this expansion is real and describes the asymptotic distribution of the eigenvalues of Tn(f). This eigenvalue symbol $\mathfrak {f}$ f is in general not known in closed form. After validating this working hypothesis through a number of numerical experiments, we propose a matrix-less algorithm in order to approximate the eigenvalue distribution function $\mathfrak {f}$ f . The proposed algorithm, which opposed to previous versions, does not need any information about neither f nor $\mathfrak {f}$ f is tested on a wide range of numerical examples; in some cases, we are even able to find the analytical expression of $\mathfrak {f}$ f . Future research directions are outlined at the end of the paper.

scholarly journals CubeSat Communications: Recent Advances and Future Challenges

2020 ◽  
Author(s):  
Nasir Saeed ◽  
Ahmed Elzanaty ◽  
Heba Almorad ◽  
Hayssam Dahrouj ◽  
Tareq Y. Al-Naffouri ◽  
...  
Keyword(s):  
Channel Modeling ◽  
Future Research ◽  
New Paradigm ◽  
Earth Remote Sensing ◽  
Research Directions ◽  
Space Industry ◽  
Recent Advances ◽  
Wide Range ◽  
Future Challenges ◽  
Future Research Directions

<pre><pre>Given the increasing number of space-related applications, research in the emerging space industry is becoming more and more attractive. One compelling area of current space research is the design of miniaturized satellites, known as CubeSats, which are enticing because of their numerous applications and low design-and-deployment cost. </pre><pre>The new paradigm of connected space through CubeSats makes possible a wide range of applications, such as Earth remote sensing, space exploration, and rural connectivity.</pre><pre>CubeSats further provide a complementary connectivity solution to the pervasive Internet of Things (IoT) networks, leading to a globally connected cyber-physical system.</pre><pre>This paper presents a holistic overview of various aspects of CubeSat missions and provides a thorough review of the topic from both academic and industrial perspectives.</pre><pre>We further present recent advances in the area of CubeSat communications, with an emphasis on constellation-and-coverage issues, channel modeling, modulation and coding, and networking.</pre><pre>Finally, we identify several future research directions for CubeSat communications, including Internet of space things, low-power long-range networks, and machine learning for CubeSat resource allocation.</pre></pre>

scholarly journals A Systematic Survey on Deep Generative Models for Graph Generation

2020 ◽  
Author(s):  
Xiaojie Guo ◽  
Liang Zhao
Keyword(s):  
Generative Models ◽  
Future Research ◽  
Specific Domain ◽  
Research Directions ◽  
Wide Range ◽  
Data Representations ◽  
Future Research Directions ◽  
Definition Of ◽  
Rich History ◽  
Graph Generation

Graphs are important data representations for describing objects and their relationships, which appear in a wide diversity of real-world scenarios. As one of a critical problem in this area, graph generation considers learning the distributions of given graphs and generating more novel graphs. Owing to its wide range of applications, generative models for graphs have a rich history, which, however, are traditionally hand-crafted and only capable of modeling a few statistical properties of graphs. Recent advances in deep generative models for graph generation is an important step towards improving the fidelity of generated graphs and paves the way for new kinds of applications. This article provides an extensive overview of the literature in the field of deep generative models for graph generation. Firstly, the formal definition of deep generative models for the graph generation as well as preliminary knowledge is provided. Secondly, two taxonomies of deep generative models for unconditional, and conditional graph generation respectively are proposed; the existing works of each are compared and analyzed. After that, an overview of the evaluation metrics in this specific domain is provided. Finally, the applications that deep graph generation enables are summarized and five promising future research directions are highlighted.

Retail Customer Engagement

2019 ◽  
pp. 1-26
Author(s):  
Andrea Moretta Tartaglione ◽  
Giuseppe Granata
Keyword(s):  
Literature Review ◽  
Bibliometric Analysis ◽  
Scientific Community ◽  
State Of The Art ◽  
Customer Engagement ◽  
Future Research ◽  
Research Directions ◽  
Study Results ◽  
Research Findings ◽  
Future Research Directions

Customer engagement is one of the most debated topics in marketing literature. The great interest of the scientific community resulted in a large amount of research on this topic making it difficult for scholars to understand how to really contribute to advance the research. Based on these considerations, this chapter aims to provide an overview of the research findings and trends of previous studies to guide the researcher to the most influential works, results, and issues that need more insights. In particular, this chapter offers a literature review on customer engagement and retail customer engagement using bibliometric analysis and scientific mapping study. Results show the most productive authors, most cited publications, most frequent words, and clusters of related words. The analysis provides a description of the state of the art of retail customer engagement and suggests future research directions.

The Same but Different

2019 ◽  
pp. 1-32
Author(s):  
Maria Northcote
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Online Courses ◽  
Future Research ◽  
Technological Innovations ◽  
Research Directions ◽  
Learning Programs ◽  
History Of ◽  
Future Research Directions ◽  
Practical Recommendations

The field of online learning, like many other technological innovations, has not burgeoned without controversy. Despite the debates about the role and value of online learning, it has continued to grow in many sectors, especially in higher education. Alongside the growth of online learning, discussions about its benefits and limitations have also flourished, and many studies have investigated the quality and integrity of online courses. This chapter offers an investigation of some of the history of online learning, concluding with a collection of practical recommendations and suggestions for future research directions to guide institutions embarking on online learning programs.

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