| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1053 | 10 | 13 | 2 |
International Journal of Information and Communication Technology primarily focuses on research topics in Artificial intelligence, Computer network, Algorithm, Pattern recognition and Distributed computing. While Artificial intelligence is the focus of the journal, it also provided insights into the studies of Machine learning and Computer vision. Wireless sensor network, Node (networking), Network packet, Wireless Routing Protocol and Quality of service are all aspects of Computer network discussed in the journal.
It explores issues in Wireless sensor network which can be linked to other research areas like Energy consumption, Key distribution in wireless sensor networks, Real-time computing and Efficient energy use. The main emphasis of it is the subject of Wireless Routing Protocol, focusing on Zone Routing Protocol. The work tackled in International Journal of Information and Communication Technology goes beyond the discipline of Distributed computing as it also encompasses Cloud computing.
The published articles focus on Computer network, Artificial intelligence, Pattern recognition, Network packet and Computer security. While Computer network is the focus of the published papers, it also provides insights into the studies of Transmission (telecommunications), Task (computing) and Reputation. While the journal publications focused on Artificial intelligence, they were also able to explore topics like Speech recognition and Correlation coefficient.
International Journal of Information and Communication Technology generally zeroes in on subjects such as Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Image (mathematics). Topics in Artificial intelligence were tackled in line with various other fields like Machine learning, Set (abstract data type) and Sequence. The research on Computer vision discussed in it draws on the closely related field of Process (computing).
While Pattern recognition is the key highlight in it, it also covered some subjects on Feature (computer vision) and Word error rate. Research in E-commerce and the interrelating topic of Cluster analysis were among the subjects of interest in the Algorithm studies discussed in the journal. Some problems in Image (mathematics) that were presented in the journal overlapped with concepts under Feature extraction, Noise reduction and Fuzzy logic.
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 Information and Communication Technology (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 Information and Communication Technology (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, 71.95% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 21.74% were posted by at least one author from the top 10 institutions publishing in the journal. Another 4.35% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.39% of all publications and 56.52% 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.
One key aspect might enrich the substance of this article: the practical applications of these research topics in the teaching field, particularly in Computer Science education. These research areas are not only essential in advancing technology, but they can also be harnessed in improving the pedagogical approach in related fields. Artificial Intelligence (AI), for example, can be integrated into intelligent tutoring systems, enabling personalized learning experiences for students, thereby making education more engaging and effective. As expressed in the 'Career Prospects in Teaching with AI', upgrading one's skills in this field is a valuable investment. Likewise, understanding Computer Networks can equip educators with the knowledge necessary to utilize and troubleshoot network systems used in online learning platforms. It would be worth considering to innovate teaching strategies inspired by these research interests. For those interested in gaining teaching credentials in these areas, you may want to consult various teaching credential programs in Michigan. Such preparation programs can provide robust training on effectively teaching these crucial Computer Science concepts, contributing to the progressive adaptation of education in our technological era.
Christos Douligeris;Sarandis Mitropoulos;Vassilis Toulas
(2021)R.S. Ramya;Ganesh Singh;Santosh Nimbhorkar Sejal;K.R. Venugopal
(2020)For those considering studying Computer Science in the USA, exploring related online degrees can expand career options and fit diverse schedules. Many professionals seek accelerated programs, such as 1 year phd programs online, offering a fast track into advanced research and leadership roles.
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