0045-7906
Published by: Elsevier
https://www.journals.elsevier.com/computers-and-electrical-engineering
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 73 | 279 | 402 | 49 |
| Electronics and Electrical Engineering | 119 | 91 | 131 | 27 |
| Engineering and Technology | 553 | 49 | 57 | 15 |
Computers & Electrical Engineering is organized to address concerns in the fields of Artificial intelligence, Computer network, Algorithm, Control theory and Pattern recognition. Computers & Electrical Engineering addresses concerns in Artificial intelligence which are intertwined with other disciplines, such as Machine learning and Computer vision. Many of the studies tackled connect Computer network with a similar field of study like Distributed computing.
Control theory and Control engineering are closely related fields of research discussed in the journal.
The journal articles mainly tackle studies in Artificial intelligence, Computer network, Computer vision, Computer security and Pattern recognition. The most cited papers dive deep in exploring the relationship between the study of Artificial intelligence and Machine learning. The journal publications explore research in Computer network alongside concepts in Distributed computing and other areas of study in Cloud computing.
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 Computers & Electrical 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 Computers & Electrical 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, 15.65% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.14% were posted by at least one author from the top 10 institutions publishing in the journal. Another 2.58% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.98% of all publications and 68.30% 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.
If you find interest in expanding from the field of Computers and Electrical Engineering to a completely different career path such as History, then considering teaching might be a worthwhile path. A career in teaching, specifically one that includes sharing historical knowledge, can be deeply satisfying for those who are passionate about specific areas of history. In order to become a history teacher, one must follow a certain course of education and training. Generally, this involves obtaining a bachelor's degree in History or a related field, completion of a teacher preparation program, and obtaining the necessary certification or licensure. You can find out more detailed information about the steps needed to become a history teacher in Pennsylvania through this resource. This resource is especially beneficial for understanding the specific requirements and opportunities in the state of Pennsylvania, as the requirements for teachers can vary by state. Remember, it's perfectly fine to shift careers or explore different fields. You never know, your skills in research and analysis from electrical engineering and computer studies might provide you with unique perspectives on historical events. Plus, the ability to handle advanced technology is an asset in today's classrooms. Life-long learning is a journey, not a destination.
Wazir Zada Khan;Muhammad Habib Ur Rehman;Hussein Mohammed Zangoti;Muhammad Khalil Afzal
(2020)Unknown
(2022)Unknown
(2022)Unknown
(2022)Rajesh Gupta;Sudeep Tanwar;Neeraj Kumar;Sudhanshu Tyagi
(2020)Muhammad Attique Khan;Yu-Dong Zhang;Yu-Dong Zhang;Muhammad Sharif;Tallha Akram
(2021)Shaoan Xie;Zibin Zheng;Weili Chen;Jiajing Wu
(2020)For students interested in studying Computer Science in the USA, exploring online courses can offer flexible learning options. Many institutions now provide accessible online classes that accommodate various schedules, making it easier for learners to balance studies with other commitments.
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