IEEE/CAA J. Autom. Sinica
IEEE/CAA Journal of Automatica Sinica aims to publish high quality, high interest, far-reaching research achievements globally, and provide an international forum for the presentation of original ideas and recent results related to all aspects of automation.
In the past 5 years after its foundation, researchers (including globally highly cited scholars) from 164 institutions in 22 countries, such as NASA Ames Research Center, MIT, Harvard University, Yale University, Stanford University, Princeton University, and other prestigious universities, select to share their research with a large audience through JAS. The publications have been reported for many times by ACM TechNews, etc.
JAS has its latest CiteScore as 3.18, which ranks it among top 18% (40/224) in the category of "Control and Systems Engineering", and top 19% (48/251, 32/168) both in the categories of "Information System" and "Artificial Intelligence". JAS has entered the 1st quantile (Q1) in all three categories it belongs to.
The coverage of JAS includes but is not limited to:
Automatic control
Artificial intelligence and intelligent control
Systems theory and engineering
Pattern recognition and intelligent systems
Automation engineering and applications
Information processing and information systems
Network based automation
Robotics
Computer-aided technologies for automation systems
Sensing and measurement
Navigation, guidance, and control.
In the past 5 years after its foundation, researchers (including globally highly cited scholars) from 164 institutions in 22 countries, such as NASA Ames Research Center, MIT, Harvard University, Yale University, Stanford University, Princeton University, and other prestigious universities, select to share their research with a large audience through JAS. The publications have been reported for many times by ACM TechNews, etc.
JAS has its latest CiteScore as 3.18, which ranks it among top 18% (40/224) in the category of "Control and Systems Engineering", and top 19% (48/251, 32/168) both in the categories of "Information System" and "Artificial Intelligence". JAS has entered the 1st quantile (Q1) in all three categories it belongs to.
The coverage of JAS includes but is not limited to:
Automatic control
Artificial intelligence and intelligent control
Systems theory and engineering
Pattern recognition and intelligent systems
Automation engineering and applications
Information processing and information systems
Network based automation
Robotics
Computer-aided technologies for automation systems
Sensing and measurement
Navigation, guidance, and control.
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Papers by IEEE/CAA J. Autom. Sinica
This perspective prescribed a pathway to achieve Ⅱ for artistic works through Parallel Art, in which LLMs like ChatGPT can serve as linguistics-based artistic knowledge foundation models and text-based human-machine interfaces for humanin-the-loop learning. Multi-modal artistic knowledge foundation models are constructed to perform linguistic, vision, and decision-making tasks of artistic creation in the human-cyberphysical hybrid creative systems. Besides, a case study of textbased painting imagination using ChatGPT is presented.
This question has started circulating in my mind two decades ago right after my first two decades of research and development in automation, robotics, intelligent control, and artificial intelligence. By the end of the 20th century, the effort of achieving the initial goal of intelligent control for complex systems, such as intelligent robotic systems and smart human-machine interaction, as envisioned by its pioneers, such as K. S. Fu [1] and G. N. Saridis [2], had seemed run into and stopped by an invisible wall, as witnessed by the fact that the well-known flagship academic gathering in the field, the annual IEEE International Symposium on Intelligent Control (IEEE ISIC), was losing steam after a decade’s rapid rising since 1985 [3]. For those of you interested, related historical reviews and future perspectives can be found in [3]–[5].
This perspective prescribed a pathway to achieve Ⅱ for artistic works through Parallel Art, in which LLMs like ChatGPT can serve as linguistics-based artistic knowledge foundation models and text-based human-machine interfaces for humanin-the-loop learning. Multi-modal artistic knowledge foundation models are constructed to perform linguistic, vision, and decision-making tasks of artistic creation in the human-cyberphysical hybrid creative systems. Besides, a case study of textbased painting imagination using ChatGPT is presented.
This question has started circulating in my mind two decades ago right after my first two decades of research and development in automation, robotics, intelligent control, and artificial intelligence. By the end of the 20th century, the effort of achieving the initial goal of intelligent control for complex systems, such as intelligent robotic systems and smart human-machine interaction, as envisioned by its pioneers, such as K. S. Fu [1] and G. N. Saridis [2], had seemed run into and stopped by an invisible wall, as witnessed by the fact that the well-known flagship academic gathering in the field, the annual IEEE International Symposium on Intelligent Control (IEEE ISIC), was losing steam after a decade’s rapid rising since 1985 [3]. For those of you interested, related historical reviews and future perspectives can be found in [3]–[5].