1683-3198
Published by: Zarqa University
http://ccis2k.org/iajit/?option=com_content&task=view&id=794&Itemid=348
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 729 | 13 | 13 | 7 |
The main points discussed in the journal deals with Artificial intelligence, Pattern recognition, Computer vision, Computer network and Data mining. Artificial neural network is part of Artificial intelligence studies tackled in it. The International Arab Journal of Information Technology emphasizes research on Computer vision, which includes concerns such as Segmentation.
Discussions in it are anchored in the subject of Computer network and the similar topic of Distributed computing.
The journal publications primarily focus on research topics in Artificial intelligence, Pattern recognition, Computer vision, Natural language processing and Artificial neural network. The Artificial intelligence study tackled in the most cited papers is a key component of adjacent topics in the area of Speech recognition. The journal articles with studies in Pattern recognition featured incorporate elements of Feature (machine learning) and Robustness (computer science).
The topics of Artificial intelligence, Pattern recognition, Computer network, Natural language processing and Machine learning are the focal point of discussions in the journal. Artificial intelligence and Computer vision are closely related fields of research discussed in it. Topics like Protocol (object-oriented programming) and Wireless sensor network are tackled as part of the discussions on Computer network.
The works on Natural language processing deal in particular with Sentiment analysis.
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 The International Arab Journal of Information 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 The International Arab Journal of Information 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, 97.80% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 50.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 50.00% of all publications and 0.00% 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.
Advancements in the field of computer science such as Artificial Intelligence, Computer Vision, Natural Language Processing, etc., have widened the path for career opportunities for scholars researching these subjects. Additionally, with the rise in demand for these advanced concepts across various industries, they hold immense potential for job prospects in both academia and industry settings. For instance, roles such as data analysts, AI specialists, machine learning engineers, software developers, and consultants are mostly sought-after. Academia also has ample opportunities for those interested in continual research and knowledge transfer. Individuals having a good research processor and publish history can opt for teaching roles, in subjects like computer vision, artificial intelligence and others in various universities.
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In conclusion, for those poised at the cusp of their careers, research work in computer science fields lays out a multitude of career opportunities to consider. Rest assured, whatever you choose, the journey promises to be marked with constant learning, innovation, and progress in this age of digital evolution.
Riaz Ahmad;Saeeda Naz;Muhammad Afzal;Sheikh Rashid
(2020)Kamal Bashir;Tianrui Li;Mahama Yahaya
(2020)Lei Shi;Junping Du;Feifei Kou
(2020)Muhammad Babar;Akmal Khattak;Fahim Arif;Muhammad Tariq
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