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Clustering high dimensional datasets is challenging due to the curse of dimensionality. One approach to address this challenge is to search for subspace clusters, i.e., clusters present in subsets of attributes. Recently the cartification algorithm was proposed to find such subspace clusters. The distinguishing feature of this algorithm is that it operates on a neighborhood database, in which for...
It is becoming increasingly common for organizations to collect very large amounts of data over time, and to need to detect unusual or anomalous time series. For example, Yahoo has banks of mail servers that are monitored over time. Many measurements on server performance are collected every hour for each of thousands of servers. We wish to identify servers that are behaving unusually. We compute...
With the rapid expansion of data scale, big datamining and analysis has attracted increasing attention. Outlierdetection as an important task of data mining is widely usedin many applications. However, conventional outlier detectionmethods have difficulty handling large-scale datasets. In addition, most of them typically can only identify global outliersand are over sensitive to parameters variation...
The human visual system proves smart in extracting both global and local features. Can we design a similar way for unsupervised feature learning? In this paper, we propose anovel pooling method within an unsupervised feature learningframework, named Rich and Robust Feature Pooling (R2FP), to better explore rich and robust representation from sparsefeature maps of the input data. Both local and global...
Nowadays mobile phone data are an actual proxy for studying the users' social life and urban dynamics. In this paper we present the Sociometer, and analytical framework aimed at classifying mobile phone users into behavioral categories by means of their call habits. The analytical process starts from spatio-temporal profiles, learns the different behaviors, and returns annotated profiles. After the...
We show a directed and robust analogue of a boolean isoperimetric type theorem of Talagrand. As an application, we give a monotonicity testing algorithm that makes, up to polylog factors, (square root of n)/ε2 non-adaptive queries to a function f:0, 1n -> 0, 1, always accepts a monotone function and rejects a function that is ε-far from being monotone with constant...
Here is applied The Immersion and Invariance method (I&I) in order to design a novel observer to solve the chaotic synchronization for the master-slave configuration, where the master belongs to a class of feedback linearized systems. This paper shows a robust observer which asymptotically calculates the underlying dynamics of the master system. We performed convincing numerical simulations.
Engineering students majoring in instrumentation and control require training modules to realize practices in industrial processes and automatic control. Usually these modules are expensive and most are designed to control a single variable. In the present work we design and built a low-cost training module, which makes possible to realize labs practices in the industrial process control area, with...
An efficient foreground detection algorithm is presented in this work to be robust against consecutively illuminance changes and noise, and adaptive with dynamic speeds of motion in the background. The scene background is firstly modeled by a novel algorithm, namely Neighbor-based Intensity Correction, which identifies and modifies motion pixels extracted from the difference of the background and...
Optical Flow is the pixels apparent movement pattern of two consecutives images. There are differents methods to estimate the optical flow: variational methods and exaustive methods. Exhaustive methods take a neighborhood around a point in the first image of the sequence and search for the most similar in the second image. This procedure is known as correspondency estimation. This work evaluate the...
Robust control design for operation of quantum systems has been considered as a demanding and challenging task in the development of quantum technologies. In this paper, we apply the sampling-based learning control (SLC) approach to design a control law for manipulating two-level quantum systems with uncertainties. The gradient-based learning and optimization algorithm is adopted to find the optimal...
In this paper we implemented a system of fisheye vision (a 360° × 180° visual field) for georeferenced tracking of feature points associated with moving objects in urban scenes. To develop this system: 1. We calibrate the intrinsic parameters of a fisheye camera based on the stereographic model. 2. We propose a geometric model of image formation and adjust the position and orientation parameters using...
Several problems in engineering and applied sciences require the parameters optimal determination. An example of such problems is the fitting of a Cole-Cole theoretical curve to experimental measurements of the relative permittivity in a biological media. Fitting such curves requires a high level of accuracy to determine the values of its parameters (the so-called Cole-Cole parameters). In this work,...
In this paper the control problem of a nonlinear chemical reactor using a free offset state feedback controller using linear matrix inequalities (LMI) is presented. The performance of the control system is verified throughout the operating range by numerical simulations. A performance comparison between the control system with a controller adjusted based on a nominal model and other with a robust...
This paper presents a comparative analysis of two nonlinear state estimators applied to the production process of tequila. The estimates consist of an extended Kalman filter (EKF) and a sliding mode observer (SMO), which are assessed to changes in process inputs and model parametric changes. The estimates are used to estimate the microbial growth and production of alcohol from the measurement of glucose...
Clustering by fast search and find of density peaks (CFSFDP) is proposed to cluster the data by finding of density peaks. CFSFDP is based on two assumptions that: a cluster center is a high dense data-point as compared to its surrounding neighbors and it lies at a large distance from other cluster centers. Based on these assumptions, CFSFDP supports a heuristic approach, known as decision graph to...
Aming at the problem that the match algorithms of feature points under complex background have low reliability and weak robustness, a match the feature points algorithm is based on Speed Up Robust Features, namely determine the main direction by calculating the gradient information around feature points using Haar wavelet, generate 64-dimensional descriptors by Gaussian weighted in the sub-region,...
Infants are curious learners who drive their own cognitive development by imposing structure on their learning environments as they explore. Understanding the mechanisms underlying this curiosity is therefore critical to our understanding of development. However, very few studies have examined the role of curiosity in infants' learning, and in particular, their categorization; what structure infants...
In this paper, a distributed, set-theoretic based subspace tracking scheme is presented. In particular, each one of the agents in the network has access to a subset of data, which are not allowed to be shared among them. Moreover, the data vectors lie on a low-rank linear subspace, which is unknown and it might also be time-varying. The agents aim at estimating and tracking the unknown subspace using...
Email is one of the most popular Internet ap- plications which enables individuals and organisations alike to communicate and work effectively. However, email has also been used by criminals as a means to commit cybercrimes such as phishing, spamming, cyberbullying and cyberstalking. Cyberstalking is a relatively new surfacing cybercrime, which recently has been recognised as a serious social and...
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