| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Engineering and Technology | 178 | 157 | 190 | 33 |
| Materials Science | 205 | 209 | 195 | 37 |
The scientific interests tackled in the journal are Structural engineering, Composite material, Artificial intelligence, Mechanical engineering and Mechanics. The main emphasis of the journal is the research on Structural engineering, emphasizing the topic of Finite element method. It features Artificial intelligence research that overlaps with concepts in Computer vision.
The journal papers focus on Nanotechnology, Artificial intelligence, Waste management, Big data and Manufacturing engineering. Tissue engineering and 3D printing are some topics wherein Nanotechnology research discussed in the published articles has an impact. The majority of Artificial intelligence studies presented in the most cited papers zero in on Deep learning.
The primary areas of discussion in Engineering are Artificial intelligence, Coronavirus disease 2019 (COVID-19), Pandemic, Chemical engineering and Internal medicine. It explores research in Artificial intelligence and the adjacent study of Machine learning. The Coronavirus disease 2019 (COVID-19) study tackling the subject of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the focus of the journal.
Most of the works presented in it deals with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) but it intersects with the subject of 2019-20 coronavirus outbreak.
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 Engineering (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 Engineering (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, 40.79% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 37.80% were posted by at least one author from the top 10 institutions publishing in the journal. Another 10.53% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.70% of all publications and 33.97% 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.
Danae Gonzalez Ortiz;Celine Pochat-Bohatier;Julien Cambedouzou;Mikhael Bechelany
(2020)Xi Lu;Shaojun Zhang;Jia Xing;Yunjie Wang
(2020)Aiguo Wang;Yi Zheng;Zuhua Zhang;Kaiwei Liu
(2020)Maarten R. Dobbelaere;Pieter P. Plehiers;Ruben Van de Vijver;Christian V. Stevens
(2021)Wei Liu;Congmin Liu;Parikshit Gogoi;Yulin Deng
(2020)Yue Hou;Qiuhan Li;Qiuhan Li;Chen Zhang;Chen Zhang;Guoyang Lu
(2021)Unknown
(2022)Khalid Elbaz;Shui Long Shen;Annan Zhou;Zhen Yu Yin
(2021)Unknown
(2021)Li Sun;Fengqi You
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