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The following topics are dealt with: natural intelligence; abstract intelligence; neural informatics; cognitive computing; and computational intelligence.
Regarding the workings of the human mind, memory and pattern recognition seem to be intertwined. You generally do not have one without the other. Taking inspiration from life experience, a new form of computer memory has been devised. Certain conjectures about human memory are keys to the central idea. The design of a practical and useful “cognitive” memory system is contemplated, a memory system...
Summary form only given. Information granules and their computing, which give rise to the framework of Granular Computing, deliver interesting opportunities to endow processing with an important facet of human-centricity. This facet directly implies that the underlying processing supports non-numeric data inherently associated with the variable perception of humans and generates results being seamlessly...
In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. But by recent information processing techniques, these kinds of features cannot be detected by computers robustly so that in computer vision it's still difficult...
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...
Summary form only given. Deoxyribonucleic acid (DNA) has become one of the most examined molecules on the planet. Scientist around the world have been trying to unravel its secrets for many purposes. For example, genetic information is currently used to raise better plants and animals, create enhanced pharmaceuticals for humans, and for gene therapy in medicine. Science as a whole has benefited from...
Cognitive Computing (CC) is an emerging paradigm of intelligent computing theories and technologies based on cognitive informatics that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. The development of Cognitive Computers (cC) is centric in cognitive computing methodologies. A cC is an intelligent computer for knowledge processing...
The contemporary wonder of sciences and engineering has recently refocused on the beginning point of them: how the brain processes internal and external information autonomously and cognitively rather than imperatively as those of conventional computers. Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science...
This paper presents a study of the properties of optimization algorithms for use in cognitive machines through five key measures: (i) speed of convergence, (ii) degree of exploration of the parameter space, (iii) storage and system size, (iv) adaptability, and (v) multi-scale capabilities. Based on these factors, a novel study of the trajectories of a particle in the particle swarm optimization algorithm...
Causal inference is one of the central capabilities of the natural intelligence that plays a crucial role in thought, perception, reasoning, and problem solving. This paper presents a set of cognitive models for causation analyses and causal inferences. The taxonomy and mathematical models of causations are created. The framework and properties of causal inferences are elaborated. Methodologies for...
This paper introduces a Partially Connected Neural Evolutionary (Parcone) model and its application to object and gesture recognition as part of the "China Brain Project", which aims to build China's first artificial brain, consisting of 10,000s of evolved interconnected neural net modules, each with its own little task, similar to Minsky's agents.
Emotion recognition is very important for applications of human-computer intelligent interaction. It is always performed on facial or audio information with such method as ANN, fuzzy set, SVM, HMM, etc. Ensemble learning is a hot topic in machine learning and ensemble method is proved an effective pattern recognition method. In this paper, a novel ensemble learning method which is based on selective...
Prion protein (PrP) is probably the only known infectious protein that possesses chameleon-like features, as reflected not only in its conformation but also in its function. Cellular PrP (PrPC), rich in α-helical structures, is believed to be functionally involved in neurotransmitter metabolism, immune cell activation, cell adhesion, signal transduction, copper metabolism, antioxidant activity, and...
Emotion might selectively affect spatial and verbal cognitive activities and the selective interaction patter could be modulated by cognitive load. To test the hypotheses, we used event-related potentials (ERPs) technique to investigate the interaction pattern of emotion and working memory (WM) by typical WM n-back tasks with low and high cognitive loads. In the 0-back task, late ERP components for...
Free text written in natural languages is lack of definite structures, and semantic analysis of such text is critically important to many Natural Language Processing applications. In this paper, based on dependency parsing, we present a semantic analytic technique to automatically assign clinical ICD-9-CM codes to complex medical patient records written in English. Our semantics analysis method includes...
Prioritizing software requirements includes negotiation among people involved in the process as well as an acceptance of the prioritization criteria. The analysis includes negotiation as an important issue, which becomes extremely difficult, as clients often do not know exactly what they need. To overcome this situation, aiming at improving stakeholder's negotiation, we propose reducing the gap of...
We address the problem of high-precision attitude synchronization in a leader-follower spacecraft formation architecture using robust integral of the sign of the error (RISE) based Neural Network (NN) technique. Based on the relative attitude dynamic model of the spacecraft formation, RISE is introduced to approximate the dynamics of the follower as well as various external disturbances. It is shown...
The increasing demand for air travel is stressing the current Air Traffic Control (ATC). This is likely to cause both safety and performance degradation in the near future. In order to solve this problem, increasing the automation level of ATC is an important development direction. So flight behavior recognizing is becoming a key technique for ATC, for it is the basis of other function of ATC, such...
In this paper, we present a general approach for helping designers to develop new human centered industrial products using intelligent techniques. First, we characterize and evaluate consumer perception on industrial products, which is composed of two levels: basic perception independent of the socio-cultural context of these products, and complex socio-cultural concepts integrated into these products...
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