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"Engineering Research Methodology."
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Research methods for engineers
\"Learn how to plan for success with this hands-on guide to conducting high-quality engineering research. Plan and implement your next project for maximum impact: step-by-step instructions cover every stage in engineering research, from the identification of an appropriate research topic through to the successful presentation of results. Improve your research outcomes: discover essential tools and methods for producing high-quality, rigorous research, including statistical analysis, survey design, and optimisation techniques. Research with purpose and direction: clear explanations, real-world examples, and over 50 customisable end-of-chapter exercises, all written with the practical and ethical considerations of engineering in mind. A unique engineering perspective: written especially for engineers, and relevant across all engineering disciplines, this is the ideal book for graduate students, undergraduates, and new academics looking to launch their research careers\"-- Provided by publisher.
Book
Methods in research and development of biomedical devices
This book presents a road map for applying the stages in conceptualization, evaluation, and testing of biomedical devices in a systematic order of approach, leading to solutions for medical problems within a well-deserved safety limit. The issues discussed will pave the way for understanding the preliminary concepts used in modern biomedical device engineering, which include medical imaging, computational fluid dynamics, finite element analysis, particle image velocimetry, and rapid prototyping. This book would undoubtedly be of use to biomedical engineers, medical doctors, radiologists, and any other professionals related to the research and development of devices for health care.
eBook
Data analysis and statistics for geography, environmental science, and engineering
This practical, classroom-tested textbook helps readers learn quantitative methodology, including how to implement advanced analysis methods using an open-source software platform. Based on the author's many years of teaching undergraduate and graduate students in several countries, the book brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applied to a variety of geographical and environmental models. Theory is accompanied by practical hands-on computer exercises, progressing from easy to difficult. The text also presents a review of mathematical methods, making the book self-contained.
eBook
Research methods in engineering design: a synthesis of recent studies using a systematic literature review
The relation between scientific research and engineering design is fraught with controversy. While the number of academic PhD programs on design grows, because the discipline is in its infancy, there is no consolidated method for systematically approaching the generation of knowledge in this domain. This paper reviews recently published papers from four top-ranked journals in engineering design to analyse the research methods that are frequently used. The research questions consider the aim and contributions of the papers, as well as which experimental design and which sources of data are being used. Frequency tables show the high variety of approaches and aims of the papers, combining both qualitative and quantitative empirical approaches and analytical methods. Most of the papers focus on methodological concerns or on delving into a particular aspect of the design process. Data collection methods are also diverse without a clear relation between the type of method and the objective or strategy of the research. This paper aims to act as a valuable resource for academics, providing definitions related to research methods and referencing examples, and for researchers, shedding light on some of the trends and challenges for current research in the domain of engineering design.
Journal Article
Sampling in software engineering research: a critical review and guidelines
Representative sampling appears rare in empirical software engineering research. Not all studies need representative samples, but a general lack of representative sampling undermines a scientific field. This article therefore reports a critical review of the state of sampling in recent, high-quality software engineering research. The key findings are: (1) random sampling is rare; (2) sophisticated sampling strategies are very rare; (3) sampling, representativeness and randomness often appear misunderstood. These findings suggest that software engineering research has a generalizability crisis. To address these problems, this paper synthesizes existing knowledge of sampling into a succinct primer and proposes extensive guidelines for improving the conduct, presentation and evaluation of sampling in software engineering research. It is further recommended that while researchers should strive for more representative samples, disparaging non-probability sampling is generally capricious and particularly misguided for predominately qualitative research.
Journal Article
Computer Vision Techniques in Construction: A Critical Review
Computer vision has been gaining interest in a wide range of research areas in recent years, from medical to industrial robotics. The architecture, engineering and construction and facility management sector ranks as one of the most intensive fields where vision-based systems/methods are used to facilitate decision making processes during the construction phase. Construction sites make efficient monitoring extremely tedious and difficult due to clutter and disorder. Extensive research has been carried out to investigate the potential to utilise computer vision for assisting on-site managerial tasks. This paper reviews studies on computer vision in the past decade, with a focus on state-of-the-art methods in a typical vision-based scheme, and discusses challenges associated with their application. This research aims to guide practitioners to successfully find suitable approaches for a particular project.
Journal Article
A New Paradigm for Systematic Literature Reviews in Supply Chain Management
While systematic literature reviews (SLRs) have contributed substantially to developing knowledge in fields such as medicine, they have made limited contributions to developing knowledge in the supply chain management domain. This is due to the ontological and epistemological idiosyncrasies of research in supply chain management, which need to be accounted for when retrieving, selecting, and synthesizing studies in an SLR. Therefore, we propose a new paradigm for SLRs in the supply chain domain that is based on both best practice and the unique attributes of doing supply chain management research. This approach involves exploring existing studies with attention to theoretical boundaries, units of analysis, sources of data, study contexts, and definitions and the operationalization of constructs, as well as research methods, with the goal of refining or revising existing theory. This new paradigm will push supply chain management research to the frontier of current methodological standards and build a foundation for improving the contribution of future SLRs in the supply chain and adjacent management disciplines.
Journal Article
Systematic Literature Reviews in Engineering Education and Other Developing Interdisciplinary Fields
Background In fields such as medicine, psychology, and education, systematic reviews of the literature critically appraise and summarize research to inform policy and practice. We argue that now is an appropriate time in the development of the field of engineering education to both support systematic reviews and benefit from them. More reviews of prior work conducted more systematically would help advance the field by lowering the barrier for both researchers and practitioners to access the literature, enabling more objective critique of past efforts, identifying gaps, and proposing new directions for research. Purpose The purpose of this article is to introduce the methodology of systematic reviews to the field of engineering education and to adapt existing resources on systematic reviews to engineering education and other developing interdisciplinary fields. Scope/Method This article is primarily a narrative review of the literature on conducting systematic reviews. Methods are adapted to engineering education and similar developing interdisciplinary fields. To offer concrete, pertinent examples, we also conducted a systematic review of systematic review articles published on engineering education topics since 1990. Fourteen exemplars are presented in this article and used to illustrate systematic review procedures. Conclusions Systematic reviews can benefit the field of engineering education by synthesizing prior work, by better informing practice, and by identifying important new directions for research. Engineering education researchers should consider including systematic reviews in their repertoire of methodologies.
Journal Article
Sex and gender analysis improves science and engineering
The goal of sex and gender analysis is to promote rigorous, reproducible and responsible science. Incorporating sex and gender analysis into experimental design has enabled advancements across many disciplines, such as improved treatment of heart disease and insights into the societal impact of algorithmic bias. Here we discuss the potential for sex and gender analysis to foster scientific discovery, improve experimental efficiency and enable social equality. We provide a roadmap for sex and gender analysis across scientific disciplines and call on researchers, funding agencies, peer-reviewed journals and universities to coordinate efforts to implement robust methods of sex and gender analysis.
The authors discuss the potential for sex and gender analysis to foster scientific discovery, improve experimental efficiency and enable social equality.
Journal Article
From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices
The debate about the ethical implications of Artificial Intelligence dates from the 1960s (Samuel in Science, 132(3429):741–742, 1960.
https://doi.org/10.1126/science.132.3429.741
; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by (Deep) Neural Networks and Machine Learning (ML) techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the ‘what’ of AI ethics (beneficence, non-maleficence, autonomy, justice and explicability)—rather than on practices, the ‘how.’ Awareness of the potential issues is increasing at a fast rate, but the AI community’s ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs.
Journal Article