1,735 resources related to Cognitive Informatics
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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.
2020 IEEE 18th International Conference on Industrial Informatics (INDIN)
INDIN focuses on recent developments, deployments, technology trends, and research results in Industrial Informatics-related fields from both industry and academia
The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.
IECON is focusing on industrial and manufacturing theory and applications of electronics, controls, communications, instrumentation and computational intelligence.
HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.
Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)
Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...
The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications.
Theory and applications of industrial electronics and control instrumentation science and engineering, including microprocessor control systems, high-power controls, process control, programmable controllers, numerical and program control systems, flow meters, and identification systems.
IEEE Transactions on Industrial Informatics focuses on knowledge-based factory automation as a means to enhance industrial fabrication and manufacturing processes. This embraces a collection of techniques that use information analysis, manipulation, and distribution to achieve higher efficiency, effectiveness, reliability, and/or security within the industrial environment. The scope of the Transaction includes reporting, defining, providing a forum for discourse, and informing ...
2006 5th IEEE International Conference on Cognitive Informatics, 2006
This keynote lecture presents a set of the latest advances in cognitive informatics (CI) that leads to the design and implementation of future generation computers known as the cognitive computers that are capable of thinking and feeling. The theory and philosophy behind the next generation computers and computing technologies are CI. The theoretical framework of CI may be classified as ...
2009 8th IEEE International Conference on Cognitive Informatics, 2009
Cognitive computing (CC) is an emerging paradigm of intelligent computing methodologies and systems that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain [1, 3, 4, 5, 6, 12, 13, 15, 16, 18, 20, 22, 23]. CC is emerged and developed based on the transdisciplinary research in cognitive informatics and abstract intelligence. Cognitive informatics (CI) ...
9th IEEE International Conference on Cognitive Informatics (ICCI'10), 2010
It is recognized that the key theoretical and technical problems toward the next generation internet are not only a speed issue, but also a more fundamental issue of the increasingly demands for the sharing of computational intelligent capabilities. According to cognitive informatics, the cognitive information that humans acquire, process, retain, and share can be classified into four profound forms known ...
2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing, 2012
Summary form only given. A fundamental challenge for almost all scientific disciplines is to explain how natural intelligence is generated by physiological organs and what the logical model of the brain is beyond its neural architectures. According to cognitive informatics and abstract intelligence, the exploration of the brain is a complicated recursive problem where contemporary denotational mathematics is needed to ...
2014 IEEE 13th International Conference on Cognitive Informatics and Cognitive Computing, 2014
The hierarchy of human knowledge is categorized at the levels of data, information, knowledge, and intelligence. For instance, given an AND-gate with 1,000-input pins, it may be described very much differently at various levels of perceptions in the knowledge hierarchy. At the data level on the bottom, it represents a 2<sup>1,000</sup> state space, known as `big data' in recent terms, ...
Special Evening Panel Discussion: AI, Cognitive Information Processing, and Rebooting Computing - IEEE Rebooting Computing 2017
Bringing Biological Models to Life: The Power of Agent-based Modeling and Visualization
Robotics History: Narratives and Networks Oral Histories: Raja Chatila
IEEE 125th Anniversary Media Event: Cognitive Computing
Self-Organization with Information Theoretic Learning
Jean Camp: Calculating and Communicating Online Risk - Industry Forum Panel: WF IoT 2016
Active Space-Body Perception and Body Enhancement using Dynamical Neural Systems
SDRJ: Small to Large Scale Quantum Computational Systems - Kae Nemoto at INC 2019
Robotics History: Narratives and Networks Oral Histories: Barbara Hayes Roth
Behavioral Signal Processing: Enabling human-centered behavioral informatics
TryEngineering Careers with Impact: Mataric
Neuromorphic Mixed-Signal Circuitry for Asynchronous Pulse Processing Neuromorphic Mixed-Signal Circuitry for Asynchronous Pulse Processing - Peter Petre: 2016 International Conference on Rebooting Computing
Neural Cognitive Robot: Learning, Memory and Intelligence
Cognitive RAN: Next Generation 6G Network - Parag Naik - India Mobile Congress, 2018
Computing Paradigms: The Largest Cognitive Systems Will Be Optoelectronic - Jeff Shainline - ICRC 2018
Q&A with Dr. May Wang: IEEE Big Data Podcast, Episode 9
Toward Cognitive Integration of Prosthetic Devices - IEEE WCCI 2014
IROS TV 2019 Haptic Intelligence with Dr. Katherine J Kuchenbecker
IROS TV 2019- How to Build a Robot: The Quest for Human Level AI in Robotics
This keynote lecture presents a set of the latest advances in cognitive informatics (CI) that leads to the design and implementation of future generation computers known as the cognitive computers that are capable of thinking and feeling. The theory and philosophy behind the next generation computers and computing technologies are CI. The theoretical framework of CI may be classified as an entire set of cognitive functions and processes of the brain and an enriched set of descriptive mathematics, the cognitive computers are created for cognitive and perceptible concept/knowledge processing based on contemporary mathematics such as concept algebra, real-time process algebra, and system algebra. Because the cognitive computers implement the fundamental cognitive processes of the natural intelligence such as the learning, thinking, formal inference, and perception processes, they are novel information processing systems that think and feel. The cognitive computers are centered by the parallel inference engine and perception engine that implement autonomic learning/reasoning and perception mechanisms based on descriptive mathematics
Cognitive computing (CC) is an emerging paradigm of intelligent computing methodologies and systems that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain [1, 3, 4, 5, 6, 12, 13, 15, 16, 18, 20, 22, 23]. CC is emerged and developed based on the transdisciplinary research in cognitive informatics and abstract intelligence. Cognitive informatics (CI) is a transdisciplinary enquiry of computer science, information science, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications [1, 3, 6, 12, 13, 20, 22]. The theoretical framework of cognitive informatics  covers the Information-Matter-Energy (IME) model , the Layered Reference Model of the Brain (LRMB) , the Object- Attribute-Relation (OAR) model of information representation in the brain , the cognitive informatics model of the brain , Natural Intelligence (NI) , and neuroinformatics . Recent studies on LRMB in cognitive informatics reveal an entire set of cognitive functions of the brain and their cognitive process models, which explain the functional mechanisms and cognitive processes of the natural intelligence with 43 cognitive processes at seven layers known as the sensation, memory, perception, action, meta-cognitive, meta-inference, and higher cognitive layers from the bottom up .
It is recognized that the key theoretical and technical problems toward the next generation internet are not only a speed issue, but also a more fundamental issue of the increasingly demands for the sharing of computational intelligent capabilities. According to cognitive informatics, the cognitive information that humans acquire, process, retain, and share can be classified into four profound forms known as knowledge, experience, skill, and wisdom. Among them, wisdom is the most advanced cognitive objects, which is a form of natural intelligence of humans that transfers a query or instruction into an action or behavior based on a well developed reasoning and judgment. However, the current Internet is still remains as an information network. Towards the development of next generation Internet as a wisdom network, the World Wide Wisdom (WWW+) network infrastructures and technologies are yet to be sough t on the basis of cognitive informatics and cognitive computers. In WWW+, each node is a cognitive computer (CC), which is a form of autonomous and intelligent computers that think, perceive, and learn. CC enables the simulation of machinable thought such as computational inferences, reasoning, and causality analyses by autonomous inferences and perceptions mimicking the mechanisms of the brain [3, 15]. The cognitive learning engine of a CC is an autonomous learning system that enables machines learn in natural languages and symbolic notations. The cognitive search engine of a CC is a machine- learning-based search system that results in cognitive knowledge acquisitions and manipulations. On the basis of the development of CCs, the next generation internet, WWW+, will be developed as a world-wide intelligent network for knowledge processing, autonomous learning, and machine-supported problem solving. The theoretical foundations for WWW+ and cognitive computing are cognitive informatics, with underpinning contemporary denotational mathematics, such as concept algebra, system algebra, realtime process algebra, granular algebra, and visual semantic algebra. Denotational mathematics provides a coherent set of powerful mathematical means and explicit expressive power for the design, modeling, and implementation of cognitive computers and WWW+, as that of Boolean algebra for conventional computing technologies. WWW+ extends the current information-search-based Internet to wisdom providing and intelligence services that mimic and simulate the brain in the largest scope of the cyberspace in which each node plays a role as an autonomous super neural cell. As that the conventional Internet provides a solution to the “to be” category of problems for information sharing based on searching technologies, the WWW+-based internet solves the advanced “to do” category of problems for wisdom and intelligence capability sharing based on cognitive computing technologies. WWW+ will be the largest scope of computational intelligence and the closest embodiment of the brain as interconnected constituent intelligent components. A wide range of applications of WWW+ and cognitive computers have been identified such as, inter alia, theories, methodologies, and infrastructures of collective intelligence, networks of computational intelligence, services providing networks, distributed agent networks, distributed cognitive sensor networks, and distributed remote control systems.
Summary form only given. A fundamental challenge for almost all scientific disciplines is to explain how natural intelligence is generated by physiological organs and what the logical model of the brain is beyond its neural architectures. According to cognitive informatics and abstract intelligence, the exploration of the brain is a complicated recursive problem where contemporary denotational mathematics is needed to efficiently deal with it. Cognitive psychology and medical science are used to explain that the brain works in a certain way based on empirical observations of corresponding activities in usually overlapped brain areas. However, the lack of precise models and rigorous causality in brain studies has dissatisfied the formal expectations of researchers in computational science and mathematics, because a computer, the logical counterpart of the brain, might not be explained in such a vigor and empirical approach without the support of a formal model and a rigorous means. In order to formally explain the architectures and functions of the brain, as well as their intricate relations and interactions, systematic models of the brain are sought for revealing the principles and mechanisms of the brain at the neural, physiological, cognitive, and logical (abstract) levels. Cognitive and brain informatics investigate into the brain via not only inductive syntheses through these four cognitive levels from the bottom up in order to form theories based on empirical observations, but also deductive analyses from the top down in order to explain various functional and behavioral instances according to the abstract intelligence theory. This keynote lecture presents systematic models of the brain from the facets of cognitive informatics, abstract intelligence, brain Informatics, neuroinformatics and cognitive psychology. A logical model of the brain is introduced that maps the cognitive functions of the brain onto its neural and physiological architectures. This work leads to a coherent abstract intelligence theory based on both denotational mathematical models and cognitive psychology observations, which rigorously explains the underpinning principles and mechanisms of the brain. On the basis of the abstract intelligence theories and the logical models of the brain, a comprehensive set of cognitive behaviors as identified in the Layered Reference Model of the Brain (LRMB) such as perception, inference and learning can be rigorously explained and simulated.The logical model of the brain and the abstract intelligence theory of the natural intelligence will enable the development of cognitive computers that perceive, think and learn. The functional and theoretical difference between cognitive computers and classic computers are that the latter are data processors based on Boolean algebra and its logical counterparts; while the former are knowledge processors based on contemporary denotational mathematics. A wide range of applications of the cognitive computers have been developing in ICIC and my laboratory such as , inter alia, cognitive robots, cognitive learning engines, cognitive Internet, cognitive agents, cognitive search engines, cognitive translators, cognitive control systems, and cognitive automobiles.
The hierarchy of human knowledge is categorized at the levels of data, information, knowledge, and intelligence. For instance, given an AND-gate with 1,000-input pins, it may be described very much differently at various levels of perceptions in the knowledge hierarchy. At the data level on the bottom, it represents a 2<sup>1,000</sup> state space, known as `big data' in recent terms, which appears to be a big issue in engineering. However, at the information level, it just represents 1,000 bit information that is equivalent to the numbers of inputs. Further, at the knowledge level, it expresses only two rules that if all inputs are one, the output is one; and if any input is zero, the output is zero. Ultimately, at the intelligence level, it is simply an instance of the logical model of an AND-gate with arbitrary inputs. This problem reveals that human intelligence and wisdom are an extremely efficient and a fast convergent induction mechanism for knowledge and wisdom elicitation and abstraction where data are merely factual materials and arbitrary instances in the almost infinite state space of the real world. Although data and information processing have been relatively well studied, the nature, theories, and suitable mathematics underpinning knowledge and intelligence are yet to be systematically studied in cognitive informatics and cognitive computing. This will leads to a new era of human intelligence revolution following the industrial, computational, and information revolutions. This is also in accordance with the driving force of the hierarchical human needs from low-level material requirements to high-level ones such as knowledge, wisdom, and intelligence. The trend to the emerging intelligent revolution is to meet the ultimate human needs. The basic approach to intelligent revolution is to invent and embody cognitive computers, cognitive robots, and cognitive systems that extend human memory capacity, learning ability, wisdom, and creativity. Via intelligence revolution, an interconnected cognitive intelligent Internet will enable ordinary people to access highly intelligent systems created based on the latest development of human knowledge and wisdom. Highly professional systems may help people to solve typical everyday problems. Towards these objectives, the latest advances in abstract intelligence and intelligence science investigated in cognitive informatics and cognitive computing are well positioned at the center of intelligence revolution. A wide range of applications of cognitive computers have been developing in ICIC [http://www.ucalgary.ca/icic/] such as, inter alia, cognitive computers, cognitive robots, cognitive learning engines, cognitive Internet, cognitive agents, cognitive search engines, cognitive translators, cognitive control systems, cognitive communications systems, and cognitive automobiles.
From a scientific perspective explaining how the brain thinks is a big goal. Cognitive informatics studies intelligent behavior from a computational point of view in terms of updated research efforts and processes of brain science and neuroscience. Cognitive informatics is the interdisciplinary study of cognition. Cognition includes mental states and processes, such as thinking, reasoning, remembering, language understanding and generation, visual and auditory perception, learning, consciousness, emotions, etc. In this paper we will point out basic research topics of learning, memory, thought, language, and neural computing which are active fields related to cognitive informatics.
Cognitive informatics is a growing discipline that incorporates elements from cognitive science and information science in the development of information systems. The approaches used in cognitive informatics largely inform the design of Electronic Medical Record (EMR) systems. EMR systems have been extensively used by physicians for diagnosis and healthcare data management, ever since 1990s. Though most of the EMR systems are GUI-based, they are not designed to incorporate the elements of cognitive informatics in operation. This research aims to propose a DICOM-compliant approach to enhance cognitive informatics in EMR using sequence logo.
This paper summarizes a few recent developments in cognitive informatics, with special emphasis on signal processing for autonomic computing and its metrics.
Although the term "granular computing (GrC)" was first explicitly used by researchers in computational intelligence, its fundamental ideas and principles have long appeared in many branches of sciences. Granular computing, in our view, attempts to extract the commonalities from existing fields to establish a set of generally applicable principles, to synthesize their results into an integrated whole, and to connect fragmentary studies in a unified framework
A fuzzy inference is an extended form of formal inferences that enables symbolic and rigorous evaluation of the degree of a confidential level for a given causality on the basis of fuzzy expressions constructed with fuzzy sets and fuzzy logic operations. Fuzzy inferences are powerful denotational mathematical means for rigorously dealing with degrees of matters, uncertainties, and vague semantics of linguistic variables, as well as for precisely reasoning the semantics of fuzzy causalities. This paper presents a denotational mathematical framework of a set of mathematical structures of fuzzy inferences encompassing deductive, inductive, abductive, and analogical inferences. Each of the fuzzy inference processes is formally modeled and illustrated with real-world examples and cases of applications. The formalization of fuzzy inferences and methodologies enables machines to mimic complex human reasoning mechanisms in cognitive informatics, soft computing, and computational intelligence.
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