World's Best Scientists 2026 revealed!
Journal of Artificial Intelligence and Systems
H-index 7

Journal of Artificial Intelligence and Systems

2642-2859

Published by: The Institute of Electronics and Computer

https://iecscience.org/journals/AIS

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 741 9 12 7

Additional Metrics

Number of Best Scientists*: 11
Documents by Best Scientists*: 13
Top 100 Ranked Scientists*: 0
SCIMAGO H-index:
SCIMAGO SJR:
Impact Factor: N/A

Overview

Top Research Topics at Ai & Society?

The main points discussed in the journal deals with Performing arts, Artificial intelligence, Knowledge management, Epistemology and Context (language use). In addition to Performing arts research, the journal aims to explore topics under Social science, Social psychology, Cognitive science and Engineering ethics. It concentrated on Artificial intelligence research, specifically Robot and Robotics.

The study on Knowledge management presented in the journal intersects with subjects under the field of Process (engineering).

  • Performing arts (32.05%)
  • Artificial intelligence (15.84%)
  • Knowledge management (12.97%)

What are the most cited papers published in the journal?

  • A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations (370 citations)
  • Social media analytics: a survey of techniques, tools and platforms (280 citations)
  • Thinking with external representations (279 citations)

Research areas of the most cited articles at Ai & Society:

The most cited articles focus on Performing arts, Artificial intelligence, Knowledge management, Social psychology and Robot. Aside from discussions in Performing arts, the published papers also deal with the subject of Social science which intersects with Epistemology disciplines. While work presented in the most cited publications provide substantial information on Knowledge management, it also covers topics in Context (language use), Information technology and Process (engineering).

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

  • Law
  • Artificial intelligence
  • World War II

The previous edition focused in particular on these issues:

The discussions in the journal mainly cover the fields of Performing arts, Artificial intelligence, Epistemology, Robot and Context (language use). Issues in Performing arts were discussed, taking into consideration concepts from other disciplines like Work (electrical), Perspective (graphical), Cognitive science and Engineering ethics. In it, Machine learning and Health care are investigated in conjunction with one another to address concerns in Artificial intelligence research.

Specifically, studies on Argument are prevalent in the Epistemology works discussed. The research topics discussed in it include Robot as well as Social robot.

The most cited articles from the last journal are:

  • Excavating AI: the politics of images in machine learning training sets (37 citations)
  • The Chinese approach to artificial intelligence: an analysis of policy, ethics, and regulation (22 citations)
  • Artificial intelligence in cyber physical systems. (19 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.

The top authors publishing in Ai & Society (based on the number of publications) are:

  • Richard Ennals (53 papers) absent at the last edition,
  • Karamjit S. Gill (42 papers) published 2 papers at the last edition, 3 less than at the previous edition,
  • Toyoaki Nishida (24 papers) absent at the last edition,
  • Renate Fruchter (16 papers) absent at the last edition,
  • David Smith (14 papers) published 1 paper at the last 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.

Only papers with recognized affiliations are considered

The top affiliations publishing in Ai & Society (based on the number of publications) are:

  • University of Brighton (47 papers) published 2 papers at the last edition, 5 less than at the previous edition,
  • Kingston University (33 papers) absent at the last edition,
  • Kyoto University (32 papers) absent at the last edition,
  • Kingston Business School (27 papers) absent at the last edition,
  • Stanford University (23 papers) absent at the last 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, 20.69% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 6.28% were posted by at least one author from the top 10 institutions publishing in the journal. Another 7.73% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.94% of all publications and 70.05% 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 after Publishing in AI & Society

After publishing in the AI & Society journal, many researchers embark on a journey to apply the theoretical knowledge they've gained. One such career path often chosen is that of a Preschool Teacher Assistant. This role allows individuals to fuse their technical knowledge with their passion for education, molding future generations. Particularly in regions such as Arkansas, this function is in high demand. Becoming a preschool teacher assistant in Arkansas requires specific qualifications and skills. To effectively convey scientific concepts, a comprehensive understanding of subjects like Artificial Intelligence and Knowledge Management, common topics in AI & Society, can be advantageous. Moreover, a strong foundation in Cognitive Science or Social Science can contribute significantly to one's competence. Remember, just like publishing a research paper, securing a position as a preschool teacher assistant takes preparation and knowledge of the specific requirements. Detailed information and a stepwise guide on how to meet the teacher assistant certificate requirements in Arkansas can be found on our website. This readily accessible resource can be a stepping-stone to navigate your way towards this rewarding profession. Our platform provides valuable insights into career progression, ensuring a seamless transition from research to rewarding vocational practice.

Top Publications

  • Emotion Recognition and Detection Methods: A Comprehensive Survey

    Anvita Saxena;Ashish Khanna

    (2020)
    186 Citations
  • Detection of Skin Diseases from Dermoscopy Image Using the combination of Convolutional Neural Network and One-versus-All

    Kemal Polat;Kaan Onur Koc

    (2020)
    83 Citations
  • Binary particle swarm optimization (BPSO) based channel selection in the EEG signals and its application to speller systems

    Murat Arican;Kemal Polat

    (2020)
    37 Citations
  • Artificial neural network and Bayesian network models for credit risk prediction

    (2020)
    31 Citations
  • An Improved Fuzzy Inventory Model Under Two Warehouses

    A K Malik;Harish Garg

    (2021)
    10 Citations
  • Feature Extraction aligned Email Classification based on Imperative Sentence Selection through Deep Learning

    Nashit Ali;Anum Fatima;Hureeza Shahzadi

    (2021)
    9 Citations
  • Automated Multimodal image fusion for brain tumor detection

    Harpreet Kaur;Deepika Koundal

    (2021)
    7 Citations
  • Classifying Alzheimer's disease based on a convolutional neural network with MRI images

    (2023)
    6 Citations
  • Short time prediction of cloud server round-trip time using a hybrid neuro-fuzzy network

    Robertas Damaševičius;Tatjana Sidekerskienė

    (2020)
    4 Citations
  • Set of Approaches Based on Position Specific Scoring Matrix and Amino Acid Sequence for Primary Category Enzyme Classification

    L. Nanni;S. Brahnam

    (2020)
    3 Citations

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Best Scientists Contributing to This Journal