A novel dynamic time delay neural network is proposed for ultrasonic motors identification and control in this paper. By introducing time delay neurons, the neural network identifier and controller of ultrasonic motor...
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Continuous queries for moving objects are becoming more and more important due to the increasing number of application domains that deal with moving entities. The asynchronous updating algorithm for continuous queries...
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Continuous queries for moving objects are becoming more and more important due to the increasing number of application domains that deal with moving entities. The asynchronous updating algorithm for continuous queries of moving objects is superior to synchronous updating algorithms in communication cost. By improving Haibo Hu's rectangle safe region strategy we proposed a new continuous queries algorithm. Circle safe region and dynamic interval are adopted in our algorithm. Theory proof and experiment results show that our algorithm substantially outperforms the traditional periodic monitoring and the rectangle safe region algorithms in terms of monitoring accuracy, communication cost and CPU time. Furthermore, the mobile terminals need not have any computation ability in our algorithm.
Moving objects databases are becoming more and more popular due to the increasing number of application domains that deal with moving entities. Continuous queries are important in moving objects databases. We summariz...
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ISBN:
(纸本)1424404754
Moving objects databases are becoming more and more popular due to the increasing number of application domains that deal with moving entities. Continuous queries are important in moving objects databases. We summarize three types of continuous queries, but only two of them have been studied before. We proposed new algorithms to process the other two types of queries. Experiment results all show that our algorithms is excellent in monitoring accuracy, communication cost and CPU load balance.
An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antib...
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An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antibody's fitness and setting the dynamic threshold value. Numerical experiments show that compared with the genetic algorithm and the originally real-valued coding artificial immune algorithm, the improved algorithm possesses high speed of convergence and good performance for preventing premature convergence.
Object-Oriented software design improving technology is an effective means to increase system flexibility for adapting to future requirement variation and expansion. In this paper, a software design improving approach...
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Object-Oriented software design improving technology is an effective means to increase system flexibility for adapting to future requirement variation and expansion. In this paper, a software design improving approach, based on micro-architecture anti-pattern and case based reasoning, is presented to improve software quality and maintainability. In this approach, problematic, inflexible structures and corresponding refactoring alternatives at micro-architecture level are formally defined and described as cases. Their organization and index mechanism in the case base are studied. Following the 4R procedures of CBR, similarity measurement methods on class diagrams, sequence diagrams, OO quality metric factors, and semantic constraints are discussed. Based on the measurement results, some algorithms on identifying anti-patterns instances in a given original design and replacing them by designs with high quality are presented. Furthermore, a supporting system CBDIT is developed to aid this approach.
Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve...
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Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under this framework, we use two prevalent evolutionary algorithms: genetic algorithm (GA) and particle swarm optimization (PSO) to find unknown sites in a collection of relatively long intergenic sequences that are suspected of being bound by the same factor. This paper represents binding sites motif to position weight matrix (PWM) and introduces how to code PWM to genome for GA and how to code it to particle for PSO. We apply these two algorithms to 5 different yeast saccharomyces cerevisiae transcription factor binding sites and CRP binding sites. The results on saccharomyces cerevisiae show that it can find the correct binding sites motifs, and the result on CRP shows that these two algorithms can achieve more accuracy than MEME and Gibbs sampler
Identification of Transcription Factor Binding Sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a nove...
Identification of Transcription Factor Binding Sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a novel approach to identify transcription factor binding sites. This approach combines greedy method and genetic algorithm (CGGA) to search conserved segment in the given sequence set. A new greedy method which can efficiently search a local optimal result is proposed. In order to solve the high complexity of this algorithm, we also give an effective improvement for this method. Then, we describe how to combine genetic algorithm with this greedy method to find the more optimal results. Greedy method is combined to the fitness function of the genetic algorithm. We apply this approach on two different TFBS sets and the results show that it can find correct result both effective and efficient, and for CRP binding sites, it get a more accurate result than Gibbs Sampler, AlignACE and MDGA.
Coordination is essential for five reasons: preventing anarchy or chaos;efficiency;meeting global constraints;distributed information, expertise or resources;and dependencies between the agents' actions. Coordinat...
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Coordination is essential for five reasons: preventing anarchy or chaos;efficiency;meeting global constraints;distributed information, expertise or resources;and dependencies between the agents' actions. Coordination is also an important method for cooperation. Due to this significance,coordination have been paid great attention in recent years, from coordination models, mechanisms, methods, etc. to resource management. In this paper, we will survey these advances and give our view of future research direction.
Classification and regression are most interesting problems in the fields of pattern recognition. The regression problem can be changed into binary classification problem and least squares support vector machine can b...
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We propose a new visualization method WDM to classify documents by adding in the position-factors of words such as the title-factor and the first-sentence-factor based on a SOM neural network. We also discuss the sele...
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ISBN:
(纸本)1424406048
We propose a new visualization method WDM to classify documents by adding in the position-factors of words such as the title-factor and the first-sentence-factor based on a SOM neural network. We also discuss the selection of the function which is used to calculate the belong-to-probability in neurons' reflecting process. The experimental results indicate that WDM makes the boundaries of different documents greatly more clear, and thus it can produce more accurate and intuitive classification compared to the visualization methods which do not have position-factors considered
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