IEEE Transactions on Cognitive and Developmental Systems

Top Research Topics at IEEE Transactions on Cognitive and Developmental Systems?

The main points discussed in the journal deals with Artificial intelligence, Robot, Pattern recognition, Human–computer interaction and Feature extraction. Some problems in Artificial intelligence that were presented in it overlapped with concepts under Machine learning and Computer vision. The work tackled in the journal goes beyond the discipline of Robot as it also encompasses Task analysis.

The research on Pattern recognition tackled can also make contributions to studies in the areas of Representation (mathematics), Autoencoder, Feature (computer vision) and Electroencephalography. Brain–computer interface is a major topic of Electroencephalography research presented in IEEE Transactions on Cognitive and Developmental Systems. Issues in Human–computer interaction were discussed, taking into consideration concepts from other disciplines like Perception, Human–robot interaction and Social robot.

The study on Feature extraction presented in the journal intersects with subjects under the field of Feature learning. ICub is a focus of the presented Humanoid robot works and it dives deep in iCub. Visualization research discussed connects with the study of Cognition.

• Artificial intelligence (57.74%)
• Robot (30.75%)
• Pattern recognition (18.45%)

What are the most cited papers published in the journal?

• Deep Reinforcement Learning With Visual Attention for Vehicle Classification (98 citations)
• Domain Adaptation Techniques for EEG-Based Emotion Recognition: A Comparative Study on Two Public Datasets (93 citations)
• Affordances in Psychology, Neuroscience, and Robotics: A Survey (90 citations)

Research areas of the most cited articles at IEEE Transactions on Cognitive and Developmental Systems:

The journal articles focus largely on the fields of Artificial intelligence, Robot, Feature extraction, Computer vision and Pattern recognition. Most of the Artificial intelligence studies addressed in the journal papers also intersect with Machine learning. The Robot study tackled in the published articles is a key component of adjacent topics in the area of Human–computer interaction.

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

• Artificial intelligence
• Machine learning
• Cognition

The previous edition focused in particular on these issues:

IEEE Transactions on Cognitive and Developmental Systems facilitates discussions on Artificial intelligence, Robot, Pattern recognition, Human–computer interaction and Feature extraction. It holds forums on Artificial intelligence that merges themes from other disciplines such as Machine learning and Electroencephalography. The research on Robot featured in the journal combines topics in other fields like Task analysis and Trajectory.

The overlapping concepts between Encoding (memory) and Spiking neural network are the key highlights of Pattern recognition study. While Human–computer interaction is the focus of it, it also provided insights into the studies of Perception and Reinforcement learning. Feature extraction research presented in IEEE Transactions on Cognitive and Developmental Systems encompasses a variety of subjects, including Visualization, Feature (machine learning) and Feature learning.

The most cited articles from the last journal are:

• A Rapid Spiking Neural Network Approach With an Application on Hand Gesture Recognition (15 citations)
• CLIC: Curriculum Learning and Imitation for Object Control in Nonrewarding Environments (14 citations)
• A Regression Method With Subnetwork Neurons for Vigilance Estimation Using EOG and EEG (13 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 IEEE Transactions on Cognitive and Developmental Systems (based on the number of publications) are:

• Zhijun Li (11 papers) published 3 papers at the last edition, 2 more than at the previous edition,
• Yukie Nagai (9 papers) published 2 papers at the last edition the same number as at the previous edition,
• Emre Ugur (7 papers) published 3 papers at the last edition,
• Huajin Tang (6 papers) published 2 papers at the last edition,
• Chin-Teng Lin (6 papers) published 1 paper at the last edition, 3 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 IEEE Transactions on Cognitive and Developmental Systems (based on the number of publications) are:

• Chinese Academy of Sciences (25 papers) published 10 papers at the last edition, 2 more than at the previous edition,
• South China University of Technology (18 papers) published 6 papers at the last edition, 2 more than at the previous edition,
• Istituto Italiano di Tecnologia (13 papers) published 2 papers at the last edition, 1 more than at the previous edition,
• Zhejiang University (13 papers) published 7 papers at the last edition, 4 more than at the previous edition,
• Sichuan University (12 papers) published 3 papers at the last edition, 1 more 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, 26.79% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 33.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 11.38% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.33% of all publications and 34.96% 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 Applied Cognitive Science and Developmental Systems

Given the top-notch research topics and breakthroughs mentioned in this review, it's evident that a specialized field like Cognitive and Developmental Systems offers promising career opportunities as researchers, educators, or engineers. A career in this domain would primarily involve contributing to advancements in artificial intelligence, robotics, and features extraction, among other areas.

For instance, considering the rise in discussions about the conjunction of Artificial Intelligence (AI) with Machine Learning (ML), there is a growing demand for professionals with expertise in these domains. Pursuing a career in this realm can also open doors for teaching opportunities, such as becoming an English teacher with a specialized focus in technology. This would involve teaching students about implementing AI and ML in applications, helping shape future leaders in the tech industry.

If you're interested in embarking on a teaching career in a tech-oriented setting, you may want to understand more about the prerequisites and requirements. To guide you further on this, you can check out this comprehensive guide on how to become an English teacher in South Carolina.

Remember, the world of Cognitive and Developmental Systems is ever-evolving and continually growing, offering exciting potential for a fulfilling career in research, academia, or technical application.