Frequent pattern mining is an important research field and can be applied to different labeled data structures ranging from itemsets to graphs. There are scenarios where a label can be assigned to a taxonomy and gener...
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Frequent pattern mining is an important research field and can be applied to different labeled data structures ranging from itemsets to graphs. There are scenarios where a label can be assigned to a taxonomy and generalized patterns can be mined by replacing labels by their ancestors. In this work, we propose a novel approach to generalized frequent subgraph mining. In contrast to existing work, our approach considers new requirements from use cases beyond molecular databases. In particular, we support directed multigraphs as well as multiple taxonomies to deal with the different semantic meaning of vertices. Since results of generalized frequent subgraph mining can be very large, we use a fast analytical method of p-value estimation to rank results by significance. We propose two extensions of the popular gSpan algorithm that mine frequent subgraphs across all taxonomy levels. We compare both algorithms in an experimental evaluation based on a database of business process executions represented by graphs.
This paper proposes a fuzzy cluster-scaled principal component analysis (fuzzy cluster-scaled PCA) for mixed data, which consists of both numerical and categorical data with respect to quantitative and qualitative var...
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We present a procedure to decode spatiotemporal spiking patterns in delay coincidence detection networks with stable limit cycles. We apply this to control a simulated e-puck robot to solve the t-maze memory task. Thi...
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ISBN:
(纸本)9781450319645
We present a procedure to decode spatiotemporal spiking patterns in delay coincidence detection networks with stable limit cycles. We apply this to control a simulated e-puck robot to solve the t-maze memory task. This work shows that dynamic memory modules formed by coincidence detection neurones with transmission delays can be effectively coupled to produce adaptive behaviours.
The problem of assessing robust H/sub 2/ performance (as a first step towards robust H/sub 2/ synthesis) has been open for the last two decades. Moreover, while convex characterizations of the worst H/sub 2/ performan...
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The problem of assessing robust H/sub 2/ performance (as a first step towards robust H/sub 2/ synthesis) has been open for the last two decades. Moreover, while convex characterizations of the worst H/sub 2/ performance are available for SISO plants, a counterexample has pointed out that these characterizations are potentially conservative for MIMO plants, with a gap size that increases with the number of inputs. We consider the problem of assessing worst-case H/sub 2/ performance for MIMO systems and we give an LMI based sufficient condition for robust performance under LTI (not necessarily causal) model uncertainty, having game complexity as H/sub /spl infin// conditions for the same problem. Moreover, we show that this condition is indeed necessary and sufficient for MIMO plants under (arbitrarily slow) linear time varying uncertainty and for MISO and SIMO systems under a class of LTI uncertainty.
For the analytic on-line recognition of handwriting, the range of pattern recognition problems can be described by the severity of letter segmentation required. More difficult problems require an interaction of letter...
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The article analyzes the statistical data of environmental pollution resulting from the activity of extracting natural resources n Russia in the period of 2009-2018. The present study of the dynamics in statistical da...
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The article analyzes the statistical data of environmental pollution resulting from the activity of extracting natural resources n Russia in the period of 2009-2018. The present study of the dynamics in statistical data is resulting in conclusions concerning the effectiveness of measures implemented for the protection of atmospheric air, water sources and soil. Statistics for the period under study showed the decrease in the effectiveness of measures practiced in the industry to protect atmospheric air and to utilize (neutralize) production and consumption wastes. The same period revealed that the quality of wastewater treatment in the industry under study improved. The results of the present analysis can be used for developing the strategy for the planned management of measures to protect the environment during natural resources extraction.
The influence of the wavefront duration on impulse breakdown voltages is reported for three nonuniform gaps: a 100-mm point-plane gap and a 100-mm cylindrical rod-plane gap, both in air, and a 35-mm point-plane gap in...
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The influence of the wavefront duration on impulse breakdown voltages is reported for three nonuniform gaps: a 100-mm point-plane gap and a 100-mm cylindrical rod-plane gap, both in air, and a 35-mm point-plane gap in SF//6. For comparison purposes, the impulse-breakdown-voltage-wavefront relationship was also measured for a 10-kV indoor post insulator. The wavefronts were 0. 6, 1. 2, 18, 34, 80, and 190 mu s while the wave tail duration was about 1800 mu s in all cases. Experiments showed that while the wavefront had an insignificant effect on positive breakdown voltages, it drastically influenced the negative breakdown voltages. Negative breakdown voltages under long-wavefront impulses may be as high as 1. 6 times those under steep-fronted impulses. The highest impulse ratio measured was 2. In contrast to the air gaps, the wavefront had a very pronounced effect on positive breakdown voltages for the SF//6 gap. The impulse ratio under positive polarity varied from 0. 62 to 1. 35 within the wavefront range studied.
We present a novel swimmer motion analysis approach for detecting possible drowning incidents in a swimming pool. The drowning incidents are detected by examining the sequence of motion and shape features extracted fr...
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ISBN:
(纸本)0780374487
We present a novel swimmer motion analysis approach for detecting possible drowning incidents in a swimming pool. The drowning incidents are detected by examining the sequence of motion and shape features extracted from swimmers in the pools. Incorporated with the knowledge of professional practice in water crisis recognition, two event-inference modules have been developed: one evaluates the condition of a swimmer using a set of reasoning rules and another relies on hidden Markov models (HMMs) to recognize drowning behavioral signs. Both modules have been applied to a number of video clips of simulated drowning incidents and promising results have been obtained.
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