| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1032 | 5 | 5 | 3 |
The concepts of Artificial intelligence, Computer vision, Computer network, Pattern recognition and Data mining are tackled in the journal. Artificial intelligence research featured in it incorporates concerns from various other topics such as Machine learning and Natural language processing.
The journal papers generally zeroe in on subjects such as Artificial intelligence, Pattern recognition, Computer network, Computer vision and Data mining. While the primary focus in the journal papers is Artificial intelligence, they also dissect topics surrounding Machine learning and Fuzzy logic as a whole. Object-class detection and Edge detection are some topics wherein Pattern recognition research discussed in the journal papers has an impact.
International Journal of Computer Theory and Engineering primarily focuses on research topics in Artificial intelligence, Text mining, Computer security, Cooperative planning and Q-learning. Most of the works presented in International Journal of Computer Theory and Engineering deals with Artificial intelligence but it intersects with the subject of Computer vision.
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 International Journal of Computer Theory and 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 International Journal of Computer Theory and 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, 100.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, nan% were posted by at least one author from the top 10 institutions publishing in the journal. Another nan% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included nan% of all publications and nan% 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.
For those interested in the practical application of the themes discussed in this journal, there are several possible career paths, particularly in education. For instance, one could choose to become a lecturer in artificial intelligence, data mining, or other emerging fields in computer science. Alternatively, one might opt to apply these research topics more directly to the classroom. An interesting career path somewhat related to the journal's content is teaching math at the middle school level. While this would not use the concepts in the same depth, foundational elements of computer science have their roots in mathematics. Therefore, establishing strong foundational mathematical knowledge, particularly in young learners, is a crucial facet of tech education. In West Virginia, there are specific requirements and steps to be taken to teach at this level. You can find more information about the process, and even follow a guide, on how to become a middle school math teacher in this part of the country. Click here to learn how to be a middle school math teacher in West Virginia. By following this pathway, you could inspire the next generation of computer engineers and data scientists.
Madah-Ul Mustafa;Zhu Liang Yu
(2021)For students considering Computer Science in the USA, online degrees offer flexibility and accessibility. Accredited self paced online colleges provide an excellent option for learners balancing work and study, allowing them to progress at their own speed without compromising quality education.
Cost is often a major concern when selecting a program. Many prospective students seek the least expensive online masters to gain advanced skills without the burden of substantial debt. These affordable programs make graduate education more attainable, especially in competitive fields like Computer Science.
If you’re starting out or exploring entry points, finding the easiest associate degree to get online can be a strategic step. These programs help build foundational knowledge quickly while still being recognized by employers. It’s a practical approach for gaining relevant qualifications efficiently.
Choosing from the best online colleges ensures that the institution meets rigorous standards, offering nationally recognized credentials. Institutions with strong national accreditation have proven records of student success and comprehensive academic support, which are vital for building a career in technology fields.
