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When clustering the tuples in the target table which is in a relational database, the prior task is to exactly and effectively calculate the relational distance between tuples. A lot of methods are used today, such as the relational distance measuring based on RIBL2. However, all these methods fail to consider the differences of similarity between the objects in both non-target table and target table,...
The detection of illegal roadside parking is becoming more and more interesting in the field of intelligent transportation systems, since it may cause traffic congestion or accidents. In this paper we propose a method able to analyze videos acquired by traditional surveillance cameras and to automatically detect the vehicles stopped in a forbidden area. Two main contributions have been introduced:...
Trajectory segmentation, i.e., breaking the trajectory into sub-trajectories, is a fundamental task needed for many applications dealing with moving objects. Several methods for trajectory segmentation, e.g., based on minimum description length (MDL), have been proposed. In this paper, we develop a novel technique for trajectory segmentation which created a series of oblique envelopes to partition...
In recent years, the wide usage of GPS-enabled devices has generated vast volumes of spatio temporal streams of location data, which raising management challenges, such as efficient storage and querying. Therefore, compression techniques are inevitable also in the field of moving object databases. In this paper, we propose a line simplification technique to compress moving object trajectories, which...
Moving characteristics of ocean eddy have become one of the research foci, based on more advanced detection and tracking method. This study applied trajectory data mining to the analysis of eddies trajectories in the South China Sea (SCS), and experimented with two methods. One of them identified moving patterns of eddies by trajectory clustering and obtained representative paths. The other one discovered...
Existing surveying methods are either labor intensive or highly costly and have a long updating cycle, which hinders the timely update of maps. In view of these problems, this paper proposes a framework of extracting digital map information from raw geospatial big data. The framework consists of four steps: data preprocessing, mathematical modeling, information extraction and map post-processing....
In this paper, we consider the problem of model reduction of large scale systems, such as those obtained through the discretization of PDEs. We propose a randomized proper orthogonal decomposition (RPOD) technique to obtain the reduced order models by randomly choosing a subset of the inputs/outputs of the system to construct a suitable small sized Hankel matrix from the full Hankel matrix. It is...
The world-wide size of social networks, such as Facebook and Twitter, is making possible to analyse the realtime behaviour of large groups of people, such those attending popular events. This paper presents work and results on the analysis of geotagged tweets carried out to understand the behaviour of people attending the 2014 FIFA World Cup. We monitored the Twitter users attending the World Cup...
Frequent item set mining(FIM) is an important research topic because it is widely applied in real world to find the frequent item sets and to mine human behavior patterns. FIM process is both memory and compute-intensive. As data grows exponentially every day, the problems of efficiency and scalability become more severe. In this paper, we propose a new distributed FIM algorithm, called Sequence-Growth,...
Lots of researches have been increasingly focusing on time series analysis of remote sensing datasets, deriving phenology time and trajectory parameters by carve fitting and detecting changes due to natural or artificial factors. For these applications extraction of various characteristic parameters is an indispensable and fundamental procedure. However, there is a lack of an integrated method currently...
Travelling by taxi is more convenient and effective. With an overcrowding population and a much terrible traffic, the traditional way of hailing a taxi encounters many challenges like where to pick-up/drop-off passengers reasonably and where to find potential passengers quickly. More cities have established taxi stands to advocate and to guide passengers to hail a taxi. However, most of them have...
The surveillance of illegal fishing activities is a critical issue for the management of marine resources. Here, we address the monitoring of fishing activities from space, namely from VMS data (Vessel Monitoring System). We propose and evaluate a novel method for the recognition of the fishing vessel gear type from VMS trajectories as a mean of detecting abnormal uses of undeclared fishing gear....
Maritime Situational Awareness (MSA) is the capability of understanding events, circumstances and activities within and impacting the maritime environment. Nowadays, the vessel positioning sensors provide a vast amount of data that could enhance the maritime knowledge if analysed and modelled. Vessel positioning data is dynamic and continuous on time and space, requiring spatio-temporal data mining...
Crossroads of international issues, maritime domain is facing growing human activities (fishing, transportation, boating…) involving a large spectrum of ships from small sailing boats to super tankers. This increase of maritime mobilities has favored the appearance and generalization of position report systems for keeping track of ships movements. Amongst these systems, cooperative position reports...
This paper discusses machine learning and data mining approaches to analyzing maritime vessel traffic based on the Automated Information System (AIS). We review recent efforts to apply machine learning techniques to AIS data and put them in the context of the challenges posed by the need for both algorithmic performance generalization and interpretability of the results in real-world maritime Situational...
Cellular motility is a fundamental biological process. Progress in the fields of gene silencing and high-throughput (HT) microscopy provide us with the tools to study its molecular basis and potential perturbators. The primary contribution of this paper is to present MotIW, a generic workflow for single cell motility study in HT time-lapse screening data. We successfully apply it to a simulated screen,...
Recently, robots have been increasing demand for elderly care problem, dangerous work involved in life, disappearing skilled work and so on. To use robots like human, human motion information is needed to obtain. The motion information is also needed to analyze in order to use effectively information. In this paper, motion information is extracted by motion-copying system. Motion-copying system is...
Location-based services allow users to perform geo-spatial recording actions, which facilitates the mining of the moving activities of human beings. This paper proposes a system, Trip Router, to recommend time-sensitive trip routes consisting of a sequence of locations with associated time stamps based on knowledge extracted from large-scale location check-in data. We first propose a statistical route...
Theory of "embodied cognition" suggests that a variety of mental activities are reflected in states of the body, such as postures, arm movements and facial expressions. The present study investigates the extent to which profiles of computer users -- their gender, feelings, and emotional experience -- can be assessed from movements of computer cursors. In one experiment, participants (N =...
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