Research within a larger, multi-faceted risk assessment project for the Intelligence Community (IC) combines Natural Language Processing (NLP) and Machine Learning techniques to detect potentially malicious shifts in the semantic content of information either accessed or produced by insiders within an organization. Our hypothesis is that the use of fewer, more discriminative linguistic features...

We discuss the design of jet-driven, radiativeblast-wave experiments for a 10 kJ class pulsed laser facility. The astrophysical motivation is the fact that jets from Young Stellar Objects are typically radiative and that the resulting radiative bow shocks produce complex structure that is difficult to predict. To drive a radiative bow shock, the jet velocity must exceed the threshold for strong...

Recently, Bag of Visual Words (BoW) model has shown its success in image classification and retrieval. The key idea behind the BoW model is to quantize the continuous highdimensional space of image features (e.g. SIFT [1]) to a manageable visual codebook. The quality of the visual codebook has an important impact on BoW-based methods. Different from the existing techniques, such as Kernel codeb...

[1] The present empirical models describing a location and shape of the magnetopause and bow shock are based on a statistical evaluation of magnetopause and bow shock crossings. The crossings are usually identified by a visual inspection of the plots or by automatic methods which are less reliable. We present a new method of determination of the most probable boundary locations. The method is b...

Most text retrieval systems are essentially based on bagof-words (BOW) text representations. Despite popularity of BOW, it ignores the internal semantic meanings of words since each word is treated as an atomic unit. Recently, distributed word and text representations become increasingly popular in NLP literatures. They embed syntactic and semantic information of words and texts into low-dimens...

The method based on Bag-of-visual-Words (BoW) deriving from local keypoints has recently appeared promising for video annotation. Spatial partition scheme has critical impact to the performance of BoW method. In this paper, we propose a new adaptive annular spatial partition scheme. The proposed scheme firstly determines the centroid of partition according to the distribution of keypoints. And ...

This paper describes the approach proposed by ARTEMIS-UBIMEDIA team at TRECVID 2012, Instance Search (INS) task [1]. The method is based on the Bag-of-Words representation obtained from uniform sampling of the frames of the videos. We propose a query expansion technique that employs the textual description of the queries to identify new instances of the query objects on Flickr in order to enric...

Representing videos by densely extracted local space-time features has recently become a popular approach for analysing actions. In this paper, we tackle the problem of categorising human actions by devising Bag of Words (BoW) models based on covariance matrices of spatio-temporal features, with the features formed from histograms of optical flow. Since covariance matrices form a special type o...

a r t i c l e i n f o a b s t r a c t The method based on Bag-of-visual-Words (BoW) deriving from local keypoints has recently appeared promising for video annotation. Visual word weighting scheme has critical impact to the performance of BoW method. In this paper, we propose a new visual word weighting scheme which is referred as emerging patterns weighting (EP-weighting). The EP-weighting sch...