Toxicological experiments in animals are carried out to determine the type and severity of any potential toxic effect associated with a new lead compound. The collected data are then used to extrapolate the effects on humans and determine initial dose regimens for clinical trials. The underlying assumption is that the severity of the toxic effects in animals is correlated with that in humans. H...

evaluating the forest stands structure in different development stages is one of the ways for better understanding the forest dynamics and its response to natural disturbances. this study was carried out in the compartment 319, kheiroud forest in order to quantify the structure properties of mixed beech stands in the stem exclusion phase. for this purpose, three one-hectare sample plots were se...

We consider the problem of feature-based face recognition in the setting where only a single example of each face is available for training. The mixture-distance technique we introduce achieves a recognition rate of 95% on a database of 685 people in which each face is represented by 30 measured distances. This is currently the best recorded recognition rate for a feature-based system applied t...

This paper demonstrates gait recognition using only the trajectories of lower body joint angles projected into the walking plane. For this work, we begin with the position of 3D markers as projected into the sagittal or walking plane. We show a simple method for estimating the planar offsets between the markers and the underlying skeleton and joints; given these offsets we compute the joint ang...

To avoid the undesired effects of distance concentration in high-dimensional spaces, previous work has already advocated the use of fractional p norms instead of the ubiquitous Euclidean norm. Closely related to concentration is the emergence of hub and anti-hub objects. Hub objects have a small distance to an exceptionally large number of data points while anti-hubs lie far from all other data...

Similarity between images in image retrieval is measured by computing distances between feature vectors. This paper presents a probabilistic approach and describes two likelihood-based similarity measures for image retrieval. Popular distance measures like the Euclidean distance implicitly assign more weighting to features with large ranges than those with small ranges. First, we discuss the ef...

We introduce a new approach for predicting the secondary structure of proteins using profiles and the Fuzzy K-Nearest Neighbor algorithm. K-Nearest Neighbor methods give relatively better performance than Neural Networks or Hidden Markov models when the query protein has few homologs in the sequence database to build sequence profile. Although the traditional K-Nearest Neighbor algorithms are a...

This paper presents a new algorithm to answer k -nearest neighbor queries called the Fractal k -Nearest Neighbor (k NNF ()). This algorithm takes advantage of the fractal dimension of the dataset under scan to estimate a suitable radius to shrinks a query that retrieves the k -nearest neighbors of a query object. k -NN() algorithms starts searching for elements at any distance from the query ce...