Profitability of different grouping criteria was simulated in a dairy farm with 153 lactating cows that were divided into three groups of high (79), medium (40) and low (34) cows based on the milk records. Animals were reassigned to the new groups based on the following criteria using a decision support tool and the same three groups scenario: fat corrected milk 4%, days in milk (DIM), dairy me...

Edge detection is a fundamental stage in order to facilitate the analysis or the interpretation of an image. However classical edge detectors usually yield gaps in the contour image. To restore incomplete contours, criteria based on perceptual grouping have been proposed. Almost all existing closing algorithms based only on these criteria fail at discontinuity points junction. In this perspecti...

We present a scalable and flexible grouping service based on concast and best-effort single-source multicast. The service assigns participating end systems to specific groups based on application-supplied criteria. Example uses of such a service include peer-to-peer applications that want to group machines that are “near” each other, and reliable multicast services that need to assign receivers...

A new contour extraction method is described in this paper. It is based on organization of the image data using perceptual grouping rules. and is therefore largely domain independent. The first step is to form an intermediate line segment representation of the contours by grouping edge points in paraBe and at different re~so~ution.s, The main feature of the hne .segn~ent extra~ti[~n process is ...

In a curve-tracing task, subjects have to judge whether items are located on a single, continuous curve. Spatially separate segments of such a curve are related to each other through grouping criteria, like collinearity and connectedness. These grouping cues need to be exploited during curve tracing, but it is still an open issue how grouping of contour segments is achieved by the visual system...

We present a graph partitioning method to integrate prior knowledge in data grouping. We consider priors represented by three types of constraints: unitary constraints on labelling of groups, partial a priori grouping information, external in uence on binary constraints. They are modelled as biases in the grouping process. We incorporate these biases into graph partitioning criteria. Computatio...

Objective. The study is conducted in order to identify the most valuable metrics for mobile application analytics and evaluate its effectiveness; consideration of state development trends market Russian Federation; determining priority areas evaluating effectiveness applications. Method . To achieve this goal, methods analyzing promising scientific sources field are used, area Federation consid...

In this paper, we argue that clustering WordNet senses into more coarse-grained groupings results in higher inter-annotator agreement and increased system performance. Clustering of verb senses involves examining syntactic and semantic features of verbs and arguments on a caseby-case basis rather than applying a strict methodology. Determining appropriate criteria for clustering is based primar...

In this paper we combine two approaches for road extraction. The first approach makes use of multiple scales to detect roads segments and employs local grouping criteria and also context information to extract the road network. This approach is suitable for aerial imagery with a resolution of 0.2–0.5 m. The second approach was designed to extract roads from satellite imagery and can be applied ...

Dynamic group formation and discovery is an important component of several emerging end system applications and network services including peer-to-peer and overlay systems, network storage/caching systems, and reliable multicast/distribution services. In our previous work, we proposed a programmable, scalable grouping service based on multicast and concast. In this paper, we present a generaliz...