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In this paper, the information acquisition problem of columnar moving obstacles is investigated for a quadrotor equipped with a stereo vision system flying in an indoor GPS-denied environment. A acquisition algorithm based on stereo vision is proposed to obtain the position and velocity direction. The spatial position relation between the quadrotor and the object detected is used to remove the interferences...
In this work, we present Interaction+, a tool that enhances the interactive capability of existing web-based visualizations. Different from the toolkits for authoring interactions during the visualization construction, Interaction+ takes existing visualizations as input, analyzes the visual objects, and provides users with a suite of interactions to facilitate the visual exploration, including selection,...
Multivariate time series (MTS) exist in many applications. Due to all kinds of interference factors, missing data in MTS is inevitable. Aiming at this problem, a filling method based on least squares support vector machine (LSSVM) is proposed. Firstly, for the series containing missing data, similar series are searched, and its results are viewed as the training set. Secondly, to make use of the correlation...
The increasing of mobile devices results in the recent mobile big data era. A large number of useful information can be extracted from mobile big data. Extracting the residents' activity information from mobile big data is more and more popular in recent years because of its lower cost and higher accuracy. In this paper, we propose an algorithm to mine some meaningful residents' activity information...
In social network analysis, correlation estimation is a critical part for various applications. With the prevalence of location-based services, geographic information is incorporated as a new perspective to refer the interpersonal correlation. In this paper, we propose a novel multi-scale multi-feature collaborative learning model for robust location-based correlation estimation. Geographic attributes...
Malware data are typically depicted with extremely high-dimensional features, which lays an excessive computational burden on detection methods. For the sake of effectiveness and efficiency, feature selection is an indispensable part for malware detection. In this paper, we propose an ensemble feature selection method with integration of discriminative and representative properties for malware detection...
Because of large amounts of unstructured text data generated on the Internet, text mining is believed to have high commercial value. Text mining is the process of extracting previously unknown, understandable, potential and practical patterns or knowledge from the collection of text data. This paper introduces the research status of text mining. Then several general models are described to know text...
The paper applies the application of Gaussian mixture models (GMMs) for operational pattern discrimination and novelty/fault detection for an industrial gas turbine (IGT). Variational Bayesian GMM (VBGMM) is used to automatically cluster operational data into steady-state and transient responses, where extraction of steady-state data is an important preprocessing scenario for fault detection. Important...
It has been studied that the communication among software stakeholders can be used to predict potential software defects. Yet researchers have rarely studied the relations between the software and the mailing lists of the developers. In this paper, we research on how to predict software defects by mining the mailing lists of the software developers. First, we extract both the structural and the unstructured...
In this paper, a new Attributed Scattering Center(ASC) feature extraction model is proposed. Together with normalization procedure, optimization of amplitude and the length of scattering center feature extraction, we can get a fine estimation of ASC parameter. The image reconstruction experiment demonstrates that with fewer scattering center can we get a satisfied description of SAR image. Moreover,...
The performances of light-weight and the anti-damage are a pair of conflicting optimization goals. Basing on the damage data of explosion simulation, it studies multi-objective optimization of cantilever box girder about lightweight and anti-damage. Firstly, the method of PCA is introduced to mine the damage data of simulation experiments. Secondly -- the regression function about the damage of cantilever...
Web Usage Mining is one of the important methods for web recommendations, but most of its studies are limited in using web server log, and its applications are limited in serving a particular web site. In this paper, based on mining the enterprise proxy log, we propose a novel WWW-oriented web recommendation system. Unlike other data sources, the enterprise proxy log is access history of visiting...
As the shop online and its usage develop very fast, the content, structure, and usage data, and the Web mining get more and more useful in everywhere such as e-supermarkets and e-commerce. Many theories and algorithms are reported for Web mining. This paper shows a novel idea for the commodities price extracting of shop online. The MVC design model and the Bottle Formwork are opted to build the application...
In existing mobile content service systems, the study is quite rare on automatic situation-service rule construction. Hence, a method is proposed that the semantic association rules between situations and preferences are built by quantitative frequent marked lattice. Different recommendation rules can be extracted along multi-dimensional context routes from this lattice structure. It is propitious...
Nowadays China has speeded up urbanization, urban land use occurred in areas of significant change. In order to obtain land cover information speedily and correctly, many methods from data mining are used to classify the remote sensing image. In recent years, using decision trees (DTs) to classify remotely sensed data has increased, due to the algorithm running fast and making no statistical assumptions...
The Emergency Department (ED) has been frustrated by the problems of overcrowding, long waiting times and high costs over decades. With the development of computer techniques, various kinds of information systems have appeared and make people work more effectively, the Emergency Department Information System (EDIS) has been heralded as a "must" for the modern ED. This paper tries to build...
Web sequential pattern mining is an important way to learn the access behavior of Web users. In this paper, we present an efficient method of Web sequential pattern mining in the e-learning environment. Different from traditional mining methods, we categorize the user sessions into human user sessions, crawler sessions and resource-download user sessions. Then we filter out the non-human user sessions,...
In this paper, we consider blind interference suppression in IR UWB communication system, and the means of a statistical technique called independent component analysis (ICA), taken as a solution for the coexistence of impulse-radio Ultra-wideband (IR-UWB) systems with other wireless systems was studied. Particularly for the evaluation of the system performance, tone, multiton, and partial-band interference...
High voltage switchgear products always produce a great lot of parts models and design information in digital design. And such products have the characteristics of series and complexity. Therefor, this paper takes a certain series of outdoor HV isolating switchgear as an example, and multi-attribute mapping parts library system has been researched and developed based on C/S mode for corporate design...
This paper studies information diffusion in networks. Traditional models are all history insensitive, i.e. only giving activated nodes a one-time chance to activate each of its neighboring nodes with some probability. But history dependent interactions between people are often observed in real world. This paper propose a new model called the history sensitive cascade model (HSCM) that allows activated...
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