Published by: Springer
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Electronics and Electrical Engineering | 404 | 10 | 21 | 7 |
| Mechanical and Aerospace Engineering | 410 | 6 | 12 | 4 |
ROBOMECH Journal mainly deals with areas of study such as Mechatronics, Robot, Artificial intelligence, Computational intelligence and Simulation. The discussions emphasized the topic of Mechatronics in an attempt to further explore the field of Control engineering. It addresses concerns in the field of Robot by exploring it in line with topics in Human–computer interaction which intersect with Task (project management) subjects.
The Artificial intelligence works featured in the journal incorporate elements from Computer vision and Pattern recognition. It explores research in Computational intelligence and the adjacent study of Robustness (computer science). Topics in Simulation were tackled in line with various other fields like Gait (human), Motion (physics), Mechanism (engineering) and Climbing.
In it, researchers investigate the Mechanism (engineering) study as part of research in the field of Mechanical engineering. The journal centers on topics in Mobile robot, with a focus on Robot control. Control theory and Vibration are closely related fields of research discussed in the journal.
The published articles generally zeroe in on subjects such as Simulation, Robot, Mechatronics, Artificial intelligence and Computer vision. The studies on Robot discussed at the journal publications can also contribute to research in the domains of Biomimetics, Mechanism (engineering) and Pneumatic actuator, Actuator. The published papers tackle studies in Computational intelligence and the interrelated subject of Control engineering, Risk analysis (engineering), Automotive industry and Risk assessment to gain insights into Mechatronics.
The scientific interests tackled in ROBOMECH Journal are Robot, Mechatronics, Computational intelligence, Artificial intelligence and Computer vision. Impedance control, Mobile robot and Service robot are all disciplines of Robot that connect with topics in Map matching and Quasi-Zenith Satellite System. The studies in Mechatronics featured incorporate elements of Robotic systems, Simulation, Robotic arm and Human–computer interaction.
The journal focuses on Computational intelligence but the discussions also offer insight into other areas such as Motion planning and Control theory. The tackled Artificial intelligence research is interrelated with Pattern recognition which concerns subjects like Robustness (computer science), Sensor fusion, Bayesian probability and Probabilistic logic. ROBOMECH Journal facilitates discussions in Object (computer science) as part of the larger field of Computer vision, however, it also tackles fields such as Interface (computing), Window (computing) and Drone.
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 ROBOMECH Journal (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 ROBOMECH Journal (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, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 59.09% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.09% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.73% of all publications and 9.09% 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.
Ren Komatsu;Hiromitsu Fujii;Yusuke Tamura;Atsushi Yamashita
(2020)Sarin Kittisares;Hiroyuki Nabae;Gen Endo;Koichi Suzumori
(2020)Yunhao Feng;Tohru Ide;Hiroyuki Nabae;Gen Endo
(2021)Hiroaki Ito;Makoto Kaneko
(2020)Mengze Li;Tadayoshi Aoyama;Yasuhisa Hasegawa
(2020)Toshiaki Nishio;Yuichiro Yoshikawa;Takamasa Iio;Mariko Chiba
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