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Additive Manufacturing in Biomedical Engineering
Published in Atul Babbar, Ankit Sharma, Vivek Jain, Dheeraj Gupta, Additive Manufacturing Processes in Biomedical Engineering, 2023
Vidyapati Kumar, Chander Prakash, Atul Babbar, Shubham Choudhary, Ankit Sharma, Amrinder Singh Uppal
The applications mentioned in the preceding section make use of a variety of AM techniques. For the hard-to-find application areas for particular processes, a search was conducted first using ISO/ASTM terminology with a mix of AM medical application keywords in a specific class and then using trade names or other widely used names for the processes, such as the manufacturer name. The goal was to locate at least a few instances for each category, as well as to figure out which regions lacked certain applications and procedures, and why. Scopus, Web of Science and Google Scholar were the databases utilized for the search. There has been earlier research on PBF of metallic implants [105–106], AM of medical equipment [93], biomaterials in medical AM [107], and medical phantoms and regenerated tissue and organ applications using AM [108], to name a few. Previous research has either failed to classify AM processes or has only looked at a single one. Various optimization [109–113] and selection strategies [114] may also be utilized to ensure optimum biomaterial selection and manufacture for application as implants, scaffolds and prosthetics devices. Some studies simply looked at the materials that were used, while others only looked at the applications themselves, with no mention of the AM procedures or materials. The search emphasis was then moved to additional processes and applications when at least three specific application classes and processes were discovered. Table 8.3 shows some specific search terms.
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Published in Mohammad Gharesifard, Community-Based Monitoring Initiatives of Water and Environment: Evaluation of the Establishment Dynamics and Results, 2021
The reviewed literature was identified using three main methods; i) the author’s knowledge about existing theoretical and empirical research in the field, ii) searching scientific databases (e.g. Web of Science, ScienceDirect, Scopus and Google Scholar), and iii) backward and forward snowballing (Van Wee & Banister, 2016). The literature review was started with a number of publications that were known to the researcher and which identified or mentioned influential factors on establishment, functioning or results of CBMs. Next, scientific databases were searched for additional relevant literature. The first step for defining the scope of the literature search was to identify different terminologies that are used to refer to CBM. As stated by Newman et al. (2011) the terminologies that refer to various citizen-based approaches in the field of Citizen Science still ‘remains confusing’ and there are a number of overlapping terms, which refer to the concept of CBM. Previous research (including Conrad & Hilchey, 2011; Kullenberg & Kasperowski, 2016; Newman et al., 2011; Whitelaw et al., 2003) has already identified and referred to these overlapping terminologies. For example, in a meta-analysis of Citizen Science literature Kullenberg and Kasperowski (2016) identified overlapping concepts such as ‘community-based monitoring’, ‘volunteer monitoring’ and ‘participatory monitoring’. In another study, Newman et al. (2011) found an overlap between the terms ‘community-based monitoring’, ‘citizen-based monitoring’, ‘collaborative monitoring’ and ‘volunteer monitoring’. In addition, as discussed in the Introduction Chapter, there is a close link between CBM and the concept of citizen observatories. This resulted in selecting the following set of terms for our literature search:
Domain-Specific Journal Recommendation Using a Feed Forward Neural Network
Published in Himansu Das, Jitendra Kumar Rout, Suresh Chandra Moharana, Nilanjan Dey, Applied Intelligent Decision Making in Machine Learning, 2020
For the notion that motivated this work, we use Google Scholar, Semantic Scholar, Scopus, Web of Science, and Microsoft Academic data to provide customizable recommendations for individuals. The aim is to support the research community by recommending the most suitable article from a curated list of publications for their domain of interest. For this drive, we developed a method to assess the publication attainment from a set of researchers who are involved in the identical research domain. The method comprises a scraper to acquire the required data. Figure 5.1 provides an overview of the tool.
Best Practices for Stakeholder Engagement for Government R&D Organizations
Published in Engineering Management Journal, 2023
Carrie Beam, Eric Specking, Gregory S. Parnell, Ed Pohl, Maria N. Goerger, J. Paige Buchanan, George E. Gallarno
When we started with Google, the search engine would often bring up Advertisements – We disregarded.Organic search results – We focused on the first two pages of search results, because they are often the most relevant. Google’s search algorithm is proprietary, but in general, it will rank results more highly if the result contains many matches to the keywords of the search, and also if the result is highly regarded by the rest of the Internet, as measured by how many other well-regarded pages link to this result. We found the first two pages of a Google search generally contained excellent information, and the match quality often fell off on the third page.Google Scholar search results - Google Scholar is a searchable academic database which includes bibliographic citations, patents, and the ability to filter by date range. We focused on relatively recent (last 10 years) search results, including citations but not patents, and preferred articles which had been cited by many other scholarly articles as an indication they were well-regarded.
Systematic literature review of repair shops: focus on sustainability
Published in International Journal of Production Research, 2022
Rony Arsène Djeunang Mezafack, Maria Di Mascolo, Zineb Simeu-Abazi
This step is crucial for the research, as selecting relevant keywords is the foundation of the literature review. First of all, the subject under study has two main keywords: ‘repair shop’ and ‘centralized maintenance workshops’. The aim here is to find the most frequently used and representative keywords related to these two keywords in the literature. For this purpose, it is necessary to choose a database that allows the extraction of keywords from a high number of papers. Google Scholar, for example, does not yet allow this. The Scopus database, on the other hand, offers this possibility. Scopus was therefore chosen as a suitable database to find relevant keywords for the literature review. As detailed in Figure 2, a first search of papers in Scopus with the two main keywords in their full-text yields about 14000 other keywords. To reduce this number and thus allow a more accurate choice of relevant keywords, we use the method of (Dibbern et al. 2004), which proposes to reduce the search to the 25 best-ranked journals in the studied field (Industrial and Manufacturing Engineering). The ranking used is that of (‘SJR: Scientific Journal Rankings.’ 2020). It reduces the number of keywords to 125.
Recent progress in adsorptive removal of per- and poly-fluoroalkyl substances (PFAS) from water/wastewater
Published in Critical Reviews in Environmental Science and Technology, 2022
The databases of Web of Knowledge, Google Scholar, and PubMed were employed for this review. Web of Knowledge (or Web of Science) is known as an online subscription, providing an inclusive content of research publications. PubMed is a free online search tool owned and developed by the National Center for Biotechnology Information (NCBI), and provides the information of scientific articles all over the world. Google Scholar, meanwhile, is a freely accessible online search engine, which involves academic journals, books, proceedings, technical reports, etc. The publications used in this study were collected with 66 different search terms, which were used individually or in combination. The literature review started with studies published between 2014 and September 2019 with approximately 130 documents, including journal papers, proceedings, books, and technical reports. After first screening of the titles and abstracts, 70 papers were selected and cross-checked to ensure the validity before being included in this review.