| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 72 | 293 | 386 | 50 |
| Electronics and Electrical Engineering | 191 | 38 | 47 | 19 |
The scientific interests tackled in the journal are Computational intelligence, Artificial intelligence, Pattern recognition, Computer network and Algorithm. While the journal focused on Computational intelligence, it was also able to explore topics like Data mining, Artificial neural network, Cluster analysis, Fuzzy logic and Cloud computing. Most of the Cloud computing studies addressed also intersect with Distributed computing.
It facilitates discussions on Artificial intelligence that incorporate concepts from other fields like Machine learning and Computer vision. The Pattern recognition study featured in the journal draws parallels with the field of Feature (computer vision). The journal focused on Computer network research but expanded to cover Throughput.
Journal of Ambient Intelligence and Humanized Computing holds forums on Wireless sensor network that merges themes from other disciplines such as Energy consumption and Real-time computing.
The most cited papers mostly deal with topics like Computational intelligence, Artificial intelligence, Computer security, Cloud computing and Pattern recognition. While Computational intelligence is the focus of the most cited articles, it also provides insights into the studies of Decision tree, Data mining, Mathematical optimization, Fuzzy logic and Algorithm. The journal publications explore research in Machine learning and overlapping concepts in Context (language use) to expand the discourse in Artificial intelligence.
The main research concerns discussed in Journal of Ambient Intelligence and Humanized Computing are Computational intelligence, Artificial intelligence, Pattern recognition, Computer network and Cloud computing. It addresses concerns in Computational intelligence which are intertwined with other disciplines, such as Data mining, Artificial neural network, Cluster analysis, Fuzzy logic and Algorithm. The journal links adjacent topics like Artificial intelligence with Machine learning.
The study on Pattern recognition presented in Journal of Ambient Intelligence and Humanized Computing intersects with subjects under the field of Feature (computer vision). Journal of Ambient Intelligence and Humanized Computing tackles issues in Computer network, particularly in the topics of Network packet, Node (networking), Wireless sensor network, Routing protocol and Routing (electronic design automation). The studies in Cloud computing featured incorporate elements of Scheduling (computing), Distributed computing and Encryption.
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 Journal of Ambient Intelligence and Humanized Computing (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 Journal of Ambient Intelligence and Humanized Computing (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, 10.05% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 17.99% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.40% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 10.34% of all publications and 66.27% 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.
This expanding field offers a wide range of career opportunities due to the variety and depth of the topics covered. Careers in artificial intelligence, pattern recognition, computer networks, and cloud computing can range from academia to high-tech companies, research institutions, and more. For instance, expertise in these subjects can pave the way to becoming a professor, research scientist, data analyst, or AI specialist among other roles. However, in order to pursue such careers, it's vital to understand the specific educational and professional requirements. As an example, consider the path of becoming an elementary school teacher focusing on introducing these complex topics at a young age. The path and prerequisites for this position would largely vary in different states and countries. If you reside in Oklahoma and are interested in guiding young minds in these fascinating areas of study, you can find detailed information about the specific requirements to become an elementary school teacher in the state by visiting elementary school teacher requirements Oklahoma. This information will provide an overview of the qualifications, certifications, and experienc e needed, offering a concrete first step towards this fulfilling career path.
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