This paper presents visualizations of a paradigmatic and syntagmatic dynamic multi-layered representation of musical pieces. We implemented a software called Multiscale Oracle Representations For Organized Sounds (MOR...
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ISBN:
(纸本)9798350382549
This paper presents visualizations of a paradigmatic and syntagmatic dynamic multi-layered representation of musical pieces. We implemented a software called Multiscale Oracle Representations For Organized Sounds (MORFOS) that automatically builds formal diagrams from musical data, according to a cognitive simulation of the memory behavior while listening. A coherent visualization is a valuable aid for music analysis to represent simultaneously the different levels of the musical structure. Three visualizations are presented: the first one is the superposition of two-dimensional formal diagrams for all levels of structure. The second and the third ones superimpose in three dimensions the diagrams and emphasize in different ways the links between the structural levels. In such visualizations, the musical form, organization, and structure can be visualized as three projections on planes sharing the same time axis. Because of their coherence with cognitive procedures, all these visualizations are particularly useful to understand complex musical phenomena better.
cognitive Skills (CS) are essential for job interviews and government policymaking. We have no existing work that can predict CS during interviews and policymaking. The current work proposes CS measurement method that...
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cognitive Skills (CS) are essential for job interviews and government policymaking. We have no existing work that can predict CS during interviews and policymaking. The current work proposes CS measurement method that simulates the nonlinear relationship between CS and Basic Human Factor (BHF) (aging, infection, emotions, awareness, personality, education, and experience). Firstly, the method obtains conditional probabilities of CS with respect to BHF using training data set. Secondly, particular domains and ranges are define for BHF. Based on the conditional probabilities of CS, the technique divide training data set into three partitions that result in three model equations for CS measurement method. Moreover, the propose method divides into three algorithms. The first algorithm estimates values for BHF. The second algorithm verifies the estimated values of BHF while the third algorithm predicts CS values by using the estimated values of BHF. During the experiment, the propose method test on test data set. We achieve the prediction accuracy of the method through Mean Forecast Error (MFE), Mean Absolute Deviation (MAD) and Tracking Signal (TS) measures. The results show that the accuracy of the method is 91%. Finally, we discuss these results as well as the comparison of the current method with competitive methods.
Today, a large number of cost-saving and energy-efficient applications are enabled by wireless sensor and actuator networks (WSANs). Usually, these solutions have serious connectivity problems in scenarios where other...
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Today, a large number of cost-saving and energy-efficient applications are enabled by wireless sensor and actuator networks (WSANs). Usually, these solutions have serious connectivity problems in scenarios where other wireless technologies are co-located sharing the frequency spectrum (e.g., industrial shop-floors). To cope with this issue, the concept of multi-radio (MR) has been introduced, which promotes the simultaneous use of multiple radio communication interfaces, leveraging their different characteristics, to improve the overall system performance and reliability. The proposed approach based on cognitive algorithm considers two wireless technologies operating at the 2.4-GHz frequency band, namely Wi-Fi and 6LoWPAN, and provides a concrete implementation of the system using a real test-bed industry scenario. The solution provides a reliable communication infrastructure for manufacturing processes, firstly combining the properties of several physical layer standards and secondly providing the ability to recover from temporary network failures by switching from a communication channel to another one.
Today, a large number of cost saving and energy efficient applications are enabled by Wireless Sensor and Actuator Networks (WSANs). Usually, these solutions have serious connectivity problems in scenarios where other...
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ISBN:
(纸本)9783319565385;9783319565378
Today, a large number of cost saving and energy efficient applications are enabled by Wireless Sensor and Actuator Networks (WSANs). Usually, these solutions have serious connectivity problems in scenarios where other wireless technologies are co-located sharing the frequency spectrum (e.g. industrial shop-floors). To cope with this issue, the concept of Multi-Radio (MR) has been introduced, which promotes the simultaneous use of multiple radio communication interfaces, leveraging their different characteristics, to improve the overall system performance and reliability. The proposed approach based on cognitive algorithm, considers two wireless technologies operating at the 2.4GHz frequency band, namely Wi-Fi and 6LoWPAN, and provides a concrete implementation of the system using a real test-bed industry scenario. The solution provides a reliable communication infrastructure for manufacturing processes, firstly combining the properties of several physical layer standards and secondly, providing the ability to recover from temporary network failures by switching from a communication channel to another one.
作者：
Valipour, MehrdadWang, YingxuUniv Calgary
Int Inst Cognit Informat & Cognit Comp ICIC Lab Computat Intelligence Cognit Syst Denotat Mat Dept Elect & Comp EngnSchulich Sch Engn 2500 Univ Dr NW Calgary AB T2N 1N4 Canada Univ Calgary
Hotchkiss Brain Inst 2500 Univ Dr NW Calgary AB T2N 1N4 Canada
Semantic comprehension is a fundamental challenge to machine learning. A methodology for building quantitative semantic hierarchies of formal concepts is formally described by cognitive machine learning. The algorithm...
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ISBN:
(纸本)9781538607718
Semantic comprehension is a fundamental challenge to machine learning. A methodology for building quantitative semantic hierarchies of formal concepts is formally described by cognitive machine learning. The algorithm of concept semantic hierarchy learning (CSH_Learning) is developed based on a set of semantic analysis and synthesis rules according to concept algebra. The algorithm and rules are applied in quantitative determination of levels of arbitrary concepts for the semantic hierarchy of a machines' cognitive knowledge bases. Experiments on 600+ formal concepts indicate the effectiveness of the algorithm for a wide range of applications including cognitive language processing, semantic analyses, cognitive machine learning, cognitive computation and computational linguistics.
Some aspects of cognitive processes are investigated in terms of a special theoretical extension of algorithm Theory called Formal Technology (FT). FT has many signs of the ''Metaphysics'' introduced b...
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Some aspects of cognitive processes are investigated in terms of a special theoretical extension of algorithm Theory called Formal Technology (FT). FT has many signs of the ''Metaphysics'' introduced by Mario Bunge and it correlates to Aleksander Bogdanov's 'Tektology''. Ef differs from the latter by constructivity and exactness. Besides, many results in FT correlate with reality. In that sense FT may be considered as a mathematical development of Tektology.
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