| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mechanical and Aerospace Engineering | 29 | 151 | 409 | 42 |
| Electronics and Electrical Engineering | 46 | 260 | 592 | 50 |
| Engineering and Technology | 148 | 118 | 255 | 37 |
The journal primarily tackles Control theory, Actuator, Control engineering, Robot and Control theory. The journal explores research in Control theory and the adjacent study of Motion control. Mechanical engineering and Mechanism (engineering) are some topics wherein Actuator research discussed in IEEE-ASME Transactions on Mechatronics have an impact.
Mechatronics, Robust control and Adaptive control are all topics related to Control engineering research discussed. While Robot is the focus of it, it also provided insights into the studies of Kinematics and Simulation. Haptic technology is the primary subject of Simulation works presented in it.
The Control theory study featured in IEEE-ASME Transactions on Mechatronics draws parallels with the field of Trajectory. It is focused mainly on Artificial intelligence, particularly Robotics.
The journal publications cover a variety of subjects, including Control theory, Control engineering, Actuator, Motion control and Robot. While the published articles focused on Control engineering, they were also able to explore topics like Kinematics, Robot kinematics and Trajectory. The published papers focus on Robot but sometimes tackle the closely related topic of Simulation which is concerned with Teleoperation.
IEEE-ASME Transactions on Mechatronics tackles a plethora of topics, such as Control theory, Robot, Control theory, Actuator and Artificial intelligence. The Control theory research presented places emphasis on topics like Torque, Trajectory, Nonlinear system, Robustness (computer science) and Control system. It focuses on Robot research which is adjacent to topics in Simulation.
The concepts on Control theory presented in IEEE-ASME Transactions on Mechatronics can also apply to other research fields, including Kinematics, Lyapunov function and Position (vector). The studies on Artificial intelligence discussed can also contribute to research in the domains of Computer vision and Pattern recognition.
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 IEEE-ASME Transactions on Mechatronics (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 IEEE-ASME Transactions on Mechatronics (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, 14.91% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.09% were posted by at least one author from the top 10 institutions publishing in the journal. Another 15.42% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.76% of all publications and 46.73% 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.
Zong Guangdeng;Dong Yang;James Lam;Xiaoqi Song
(2021)Wei He;Tingting Wang;Xiuyu He;Lung-Jieh Yang
(2020)Zheng Chen;Fanghao Huang;Weichao Sun;Jason Gu
(2020)Haidong Shao;Min Xia;Jiafu Wan;Clarence De Silva
(2021)Zhongwei Deng;Xiaosong Hu;Xianke Lin;Le Xu
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