Fluents are logical descriptions of situations that persist, and composite fluents are statistically significant temporal relationships (nearly identical with those in Allen’s temporal calculus) between fluents. This paper presents an algorithm for learning composite fluents incrementally. The algorithm is tested with a large dataset of mobile robot episodes. The algorithm is given no knowledge...

By extracting local spatial-temporal features from videos, many recently proposed approaches for action recognition achieve promising performance. The Bag-of-Words (BoW) model is commonly used in the approaches to obtain the video level representations. However, BoW model roughly assigns each feature vector to its closest visual word, therefore inevitably causing nontrivial quantization errors ...

88 Abstract— One of the most challenging areas in data mining is Association rule mining. Several algorithms have been developed to solve this problem. These algorithms work efficiently with static datasets. But if new records are added time to time to the datasets means if the datasets are incremental in nature, scenario of association rules may changed. Some of the new itemsets may become fre...

The increasing quantity and quality of functional genomic information motivate the assessment and integration of these data with association data, including data originating from genome-wide association studies (GWAS). We used previously described GWAS signals ("hits") to train a regularized logistic model in order to predict SNP causality on the basis of a large multivariate functional dataset...

Most researches on human activity recognition do not take into account the temporal localization of actions. In this paper, a new method is designed to model both actions and their temporal domains. This method is based on a new Hough method which outperforms previous published ones on honeybee dataset thanks to a deeper optimization of the Hough variables. Experiments are performed to select s...

Ecological data can be difficult to collect, and as a result, some important temporal ecological datasets contain irregularly sampled data. Since many temporal modelling techniques require regularly spaced data, one common approach is to linearly interpolate the data, and build a model from the interpolated data. However this process introduces an unquantified risk that the data is overfitted t...

Law enforcement agencies, as well as researchers rely on temporal analysis methods in many crime analyses, e.g., spatio-temporal analyses. A number of temporal analysis methods are being used, but a structured comparison in different configurations is yet to be done. This study aims to fill this research gap by comparing the accuracy of five existing, and one novel, temporal analysis methods in...

in order to present a quantitative indicator for the onset of instability, in this paper, the critical points of a stratified gravitational flow on a slope are found and analyzed. these points are obtained by means of the solution of the two-dimensional navier-stokes equations via the standard arakawa-c finite-difference method. results show that in the marginal richardson numbers, the critical...

In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic varia...