| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Electronics and Electrical Engineering | 30 | 774 | 1820 | 61 |
| Engineering and Technology | 71 | 391 | 957 | 51 |
The primary areas of discussion in IEEE Sensors Journal are Optoelectronics, Artificial intelligence, Electronic engineering, Optics and Acoustics. The work on Optoelectronics tackled in IEEE Sensors Journal brings together disciplines like Electrode and Sensitivity (control systems). In addition to Artificial intelligence research, IEEE Sensors Journal aims to explore topics under Machine learning, Computer vision and Pattern recognition.
While it focused on Electronic engineering, it was also able to explore topics like Wireless sensor network and Electrical engineering. Studies on Wireless sensor network discussed in the journal link to the field of Energy consumption. IEEE Sensors Journal emphasizes research on Electrical engineering, which includes concerns such as CMOS.
The journal facilitated presentations on Optics research, particularly Optical fiber, Fiber optic sensor, Fiber Bragg grating, Interferometry and Refractive index. IEEE Sensors Journal focused on Optical fiber research but expanded to cover Fiber.
The published articles investigate areas of study like Electronic engineering, Wireless sensor network, Optoelectronics, Artificial intelligence and Electrical engineering. The published articles explore topics in Electronic engineering which can be helpful for research in disciplines like Acoustics and Signal. While Optoelectronics is the focus of the journal articles, it also provides insights into the studies of Optics and Analytical chemistry.
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 Sensors 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 IEEE Sensors 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, 15.76% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 12.91% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.69% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 14.23% of all publications and 66.17% 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.
Yuchen Jiang;Shen Yin;Jingwei Dong;Okyay Kaynak
(2021)Zhongyang Han;Jun Zhao;Henry Leung;King Fai Ma
(2021)Cynthia M. Furse;Moussa Kafal;Reza Razzaghi;Yong-June Shin
(2021)Haobo Li;Aman Shrestha;Hadi Heidari;Julien Le Kernec
(2020)Jun Zhu;Nan Chen;Changqing Shen
(2020)Anusha Vangala;Ashok Kumar Das;Neeraj Kumar;Mamoun Alazab
(2021)Unknown
(2022)Hossein Darvishi;Domenico Ciuonzo;Eivind Roson Eide;Pierluigi Salvo Rossi
(2021)Manju Rana;Vikas Mittal
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