Feature modeling has enjoyed success as a widely used variability modeling method in companies utilizing product lines. A number of different feature modeling methods have been proposed with expanded notational concepts and ability to model various dependencies among features. Despite popular usage and relatively simple concepts, different feature modeling methods tend not to explicate their pu...

Since various behavioral movement patterns are likely to be valid within different, unique ranges of spatial and temporal scales (e.g., instantaneous, diurnal, or seasonal) with the corresponding spatial extents, a cross-scale approach is needed for accurate classification of behaviors expressed in movement. Here, we introduce a methodology for the characterization and classification of behavio...

This paper gives an overview of automatic speaker recognition technology, with an emphasis on text-independent recognition. Speaker recognition has been studied actively for several decades. We give an overview of both the classical and the state-of-the-art methods. We start with the fundamentals of automatic speaker recognition, concerning feature extraction and speaker modeling. We elaborate ...

Robustness for BCI is usually obtained at the classifier level Non-stationarity is inherent to brain signals We propose to leverage this at the feature extraction level

When a location is cued, targets appearing at that location are detected more quickly. When a target feature is cued, targets bearing that feature are detected more quickly. These attentional cueing effects are only superficially similar. More detailed analyses find distinct temporal and accuracy profiles for the two different types of cues. This pattern parallels work with probability manipula...

Although early research suggested that attention to nonspatial features (i.e., red) was confined to stimuli appearing at an attended spatial location, more recent research has emphasized the global nature of feature-based attention. For example, a distractor sharing a target feature may capture attention even if it occurs at a task-irrelevant location. Such findings have been used to argue that...

The detection of camouflaged objects is important for industrial inspection, medical diagnoses, and military applications. Conventional supervised learning methods for hyperspectral images can be a feasible solution. Such approaches, however, require a priori information of a camouflaged object and background. This letter proposes a fully autonomous feature selection and camouflaged object dete...

Feature evolutionary relationship discovery based on tree structure pattern mining and spatial co-location in cliques aims to combine algorithm find data relationships of features these cliques. This allows for a deeper analysis possible causal between features, predicting the occurrence other certain or summarizing general laws. For clique, appearance one feature may lead another feature, whic...

Spatial data quality (SDQ) is conventionally presented in the form of a report. The data quality statements in the report refer to the entire data set. In reality the quality of data varies spatially due to data collection methods, data capturing techniques, and analysis. Thus, the quality of spatial data for one area may not be applicable to spatial data describing other regions. The present s...

The development of rural tourism in the greater Xi’an area is full swing, which an important indicator for implementation revitalization. However, there are certain realistic challenges such as lack culture, destruction cultural context, and loss “rurality” tourist areas. It vital significance to explore, integrate revive culture by advancing landscape based on concept human geography. specific...