Journal of King Saud University - Computer and Information Sciences

Top Research Topics at Journal of King Saud University - Computer and Information Sciences?

Journal of King Saud University - Computer and Information Sciences mainly tackles studies in Artificial intelligence, Pattern recognition, Algorithm, Data mining and Computer network. Topics in Artificial intelligence were tackled in line with various other fields like Machine learning, Computer vision and Natural language processing. Image (mathematics) is a major topic of Computer vision research presented in Journal of King Saud University - Computer and Information Sciences.

It focuses on different Pattern recognition studies like Convolutional neural network, Classifier (UML), Segmentation, Feature extraction and Feature selection. Wireless sensor network and Network packet studies are all carried out as a component of the study in Computer network presented. Journal of King Saud University - Computer and Information Sciences connects the study in Deep learning with the closely related area of Artificial neural network.

• Artificial intelligence (37.32%)
• Pattern recognition (14.90%)
• Algorithm (12.17%)

What are the most cited papers published in the journal?

• A survey on Internet of Things architectures (562 citations)
• Big Data technologies: A survey (306 citations)
• Intrusion detection model using fusion of chi-square feature selection and multi class SVM (158 citations)

Research areas of the most cited articles at Journal of King Saud University - Computer and Information Sciences:

The journal articles are organized to reinforce research efforts on Artificial intelligence, Algorithm, Computer network, Data mining and Pattern recognition. The journal articles focus on Artificial intelligence but the discussions also offer insight into other areas such as Machine learning, Arabic, Computer vision and Natural language processing. While Pattern recognition is the focus of the published articles, it also provides insights into the studies of Genetic algorithm, Random forest and Space (punctuation).

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Operating system
• The Internet

The previous edition focused in particular on these issues:

The topics of Artificial intelligence, Pattern recognition, Algorithm, Deep learning and Natural language processing are the focal point of discussions in the journal. The studies in Artificial intelligence featured incorporate elements of Machine learning and Computer vision. The Pattern recognition study featured in it draws parallels with the field of Feature (computer vision).

The Deep learning study featured in Journal of King Saud University - Computer and Information Sciences draws connections with the study of Artificial neural network. It explores topics in Natural language processing which can be helpful for research in disciplines like Set (abstract data type), Word (computer architecture) and Arabic.

The most cited articles from the last journal are:

• Fruits and vegetables quality evaluation using computer vision: A review (96 citations)
• A Survey on Human Face Expression Recognition Techniques (47 citations)
• A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications (39 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Journal of King Saud University - Computer and Information Sciences (based on the number of publications) are:

• Ajith Abraham (6 papers) absent at the last edition,
• W. R. Sam Emmanuel (6 papers) published 5 papers at the last edition,
• Adnan Gutub (6 papers) published 3 papers at the last edition the same number as at the previous edition,
• K. S. Kuppusamy (6 papers) absent at the last edition,
• Mohammad Shorif Uddin (6 papers) published 2 papers at the last edition, 2 less than at the previous edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Journal of King Saud University - Computer and Information Sciences (based on the number of publications) are:

• Veer Surendra Sai University of Technology (20 papers) published 1 paper at the last edition, 5 less than at the previous edition,
• Pondicherry University (19 papers) published 5 papers at the last edition,
• Jaypee Institute of Information Technology (18 papers) published 5 papers at the last edition, 4 more than at the previous edition,
• VIT University (17 papers) published 3 papers at the last edition, 1 more than at the previous edition,
• Siksha O Anusandhan University (15 papers) published 3 papers at the last edition, 1 less than at the previous edition.

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.

Publication chance based on affiliation

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, 14.95% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 14.45% were posted by at least one author from the top 10 institutions publishing in the journal. Another 7.42% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 23.44% of all publications and 54.69% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in Computer and Information Sciences

For those interested in contributing to the sectors of computer and information sciences, establishing a career in this field generally requires formal academic credentials. When choosing a credentialing program, such as those offered in Arizona, it's essential to consider factors like cost, program reputation, curriculum, and outcomes. Considering financial aspect, one must be aware of the cost-effective ways to earn a teaching credential. If you are based in Arizona, or considering relocation, becoming familiar with the best teaching credential programs in Arizona can be a significant career move. An ideal program will provide you with a solid foundation in subjects like artificial intelligence, pattern recognition, algorithms, data mining and computer network, all of which are prominent topics in the Journal of King Saud University - Computer and Information Sciences. By aligning your academic pursuits with the latest trends and high-impact topics in the field, you will be better prepared for a successful career. A formal credential can serve as a testament to your skills and knowledge, making you more appealing to prospective employers in academia, research institutions, and corporate entities within the tech sector. They can also set you on a path towards contributing valuable research and insights in esteemed journals, such as the Journal of King Saud University - Computer and Information Sciences.