0890-0604
Published by: Cambridge University Press
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 873 | 6 | 8 | 5 |
| Engineering and Technology | 1254 | 8 | 8 | 5 |
The topics of Artificial intelligence, Engineering design process, Systems engineering, Software engineering and Human–computer interaction are the focal point of discussions in Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing. The research on Artificial intelligence tackled can also make contributions to studies in the areas of Machine learning and Computer Aided Design. Engineering design process research presented in Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing encompasses a variety of subjects, including Management science, Design process and Knowledge management.
The journal focuses on Systems engineering as well as the interrelated topic of Conceptual design.
The main points discussed in the journal publications deal with Artificial intelligence, Engineering design process, Systems engineering, Conceptual design and Software engineering. While Artificial intelligence is the focus of the journal papers, it also provides insights into the studies of Computer Aided Design, Theoretical computer science, Function (engineering) and Natural language processing. The works on Engineering design process tackled in the journal publications bring together disciplines like Management science, Knowledge management, Concurrent engineering, Product design and Operations research.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing investigates studies in Artificial intelligence, Smart system, Engineering design process, Embedded system and Ontology (information science). It explores Artificial intelligence concepts, specifically Semantic network but expands to research in Sitting posture. The studies on Engineering design process discussed can also contribute to research in the domains of New product development, Human–computer interaction and Cognitive development.
While the journal focused on New product development, it was also able to explore topics like Page layout, Genetic algorithm, Reliability engineering and Optimization problem. The featured Ontology (information science) studies mainly concentrate on Reduction (mathematics) but also cover areas of interest in Cyber-physical system. While work presented in it provided substantial information on Systems engineering, it also covered topics in Metrology and Big data.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 31.82% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.33% of all publications and 73.33% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
While our focus is largely academic, we recognize the importance of understanding how the topics of study translate into the professional realm, especially for our readers considering a career in the Ai Edam field. To that end, we shed light on various careers which intertwine with the subjects covered by our journal. Take teaching, for example. The realm of Artificial Intelligence and Engineering Design is ripe with opportunities for educators. Not just at the tertiary level, but also for those enthusiastic about guiding the next generation at the primary and secondary levels. North Carolina is one such place where demand for teachers in this area of expertise is becoming increasingly prominent. If you are considering a career in this space, we recommend reading this detailed guide on how to become a teacher in North Carolina. Moreover, those with a background in topics like System Engineering, Software Engineering, Machine learning and Human-Computer Interaction will find ample opportunities in the industry. Many companies focused on product platform design or conceptual design are in continual need for skilled professionals in these sectors. Linking academia to actual career paths creates a broader understanding of how these fields of study apply in our day-to-day lives and fuels innovation in industries.
Serhad Sarica;Binyang Song;Jianxi Luo;Kristin L. Wood
(2021)Jie Pan;Jingwei Huang;Yunli Wang;Gengdong Cheng
(2021)Tomohiko Sakao;John S. Gero;Hajime Mizuyama
(2020)Megan Tomko;Wendy Newstetter;Melissa W. Alemán;Robert L. Nagel
(2020)Eduardo Castro e Costa;Joaquim A. Jorge;Aaron D. Knochel;José Pinto Duarte
(2020)Dimitrios Boursinos;Xenofon D. Koutsoukos
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