The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportati...

In this work we propose a novel unsupervised classification technique based on the estimation of nonlinear nonparametric mixed-effects models. The proposed method is an iterative algorithm that alternates a nonparametric EM step and a nonlinear Maximum Likelihood step. We apply this new procedure to perform an unsupervised clustering of longitudinal data in two different case studies.

Clustering plays an important role in data mining, as it is used by many applications as a preprocessing step for data analysis. Traditional clustering focuses on grouping similar objects, while two-way co-clustering can group dyadic data (objects as well as their attributes) simultaneously. In this research, we apply two-way co-clustering to the analysis of online advertising where both ads an...

It presents some definitions of projected cluster and projected cluster group on hybrid attributes after having given some definitions on ordered attributes and sorted attributes to solve clustering analysis problem of infinite hybrid attributes data streams in finite space. In order to improve the clustering quality of hybrid attributes data streams, it presents a two-step projected clustering...

coriolis mass flow meters are one of the most accurate tools to measure the mass flow in the industry. however, two-phase mode (gas-liquid) may cause severe operating difficulties as well as decreasing certitude in measurement. this paper presents a method based on fuzzy systems to correct the error and improve the reliability of these sensors in the presence of two-phase model fluid. definite ...

This paper applies a new clustering approach for identifying and segmenting motion in image sequences. We estimate a matrix whose entries represent similarity probabilities between local motion estimates. We adopt a two step iterative algorithm which consists of a variant of the expectationmaximization algorithm for segmenting regions with similar motion. The proposed algorithm updates cluster ...

Uncovering common themes from a large number of unorganized search queries is a primary step to mine insights about aggregated user interests. Common topic modeling techniques for document modeling often face sparsity problems with search query data as these are much shorter than documents. We present two novel techniques that can discover semantically meaningful topics in search queries: i) wo...

We apply the dressing method to a string solution given by a static string wrapped around the equator of a three-sphere and find that the result is the single spike solution recently discussed in the literature. Further application of the method allows the construction of solutions with multiple spikes. In particular we construct the solution describing the scattering of two single spikes and c...

  Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. In this paper we propose a novel app...