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This paper introduces a hand tracking system in unconstrained environment. The system consists of two main stages which are initialization and tracking. In initialization, hand region is first detected by combining motion and skin color pixels. A region of interest (ROI) is then created around the detected hand region. In tracking stage, skin and motion pixels are scanned around top, left and right...
Context-aware computing is one of the attractive research topics in pervasive computing. Context-aware systems can react to users' preferences according to context including location, time and other environment conditions. Context is generated by context interpreters or aggregated by context aggregators from the signals of sensors. A traditional context interpreter is usually built as an executable...
Thanks to the drastic proliferation of Internet, e-learning has been recognized as an effective media for various kinds of learners. However, the tremendous course materials in the Internet may make learners be confused in choosing their suitable course materials. In this paper, we propose an approach to construct an adaptive curriculum portfolio recommendation system. It offers tailored course materials...
This paper proposes an improved Hierarchical Multi-label Classification (HMC) method for solving the gene function prediction. The HMC task is transferred into a series of binary SVM classification tasks. By introducing the hierarchy constraint into learning procedures, two measures with incorporating prior information are implemented to improve the HMC performance. Firstly, for imbalanced functional...
The paper deals with using so called singularity exponent in a classifier that is based on ordered distances of patterns to a given (classified) pattern. The approximation of probability distribution mapping function of the distribution of points from the viewpoint of distances from a given point in a form of a suitable power (exponent) of a distance is presented together with a way how to state it...
In this paper, a T-S fuzzy modeling and tracking control method is proposed for wheeled mobile robots by using T-S fuzzy linearization approach. The proposed method has advantages in that the linear control theories can be used for the tracking control of wheeled mobile robots after linearization of them. The local linear models are converted into controllable canonical forms respectively and then...
The active magnetic bearing (AMB) presents a solution for all the technical problems of the classical bearing since it ensures the total levitation of a body in space eliminating any mechanical contact between the rotor and the stator. The goal of our work is to show the control efficiency of a magnetic sustention, characterized by its nonlinear model, using neural networks (NN). In this paper a study...
According to some biological observations, generating output variability is one of the characteristics expected from a memory model. In this paper a BAM inspired chaotic model is used to mimic this functionality of the brain. Chaos gives the potential to create deterministic variability and control its degree of uncertainty. Using some time series generated by the trained network, largest lyapunov...
In classifier combining, predictions of several classifiers are aggregated into a single prediction in order to improve the classification quality. Among others, fuzzy integrals are commonly used as aggregation operators. Usually, Sugeno lambda-measure is used as the fuzzy measure of the integral. However, interaction between the classifiers in the team (diversity), an important property in classifier...
Autonomous steering control is the principal task in the development of an intelligent transportation system. This research paper proposes a novel approach for vision based intelligent control of unmanned vehicles. The paper addresses the problems of accurate and efficient intelligent vehicle control by incorporating a well known evolutionary algorithm cAnt-Miner. The uniqueness of the proposed algorithm...
Most existing research in the area of emotions recognition has focused on short segments or utterances of speech. In this paper we propose a machine learning system for classifying the overall sentiment of long conversations as being Positive or Negative. Our system has three main phases, first it divides a call into short segments, second it applies machine learning to recognize the emotion for each...
In this paper an off-grid hybrid energy system consisting of a reverse osmosis desalination plant for brackish water powered by renewable energy sources, and a diesel generator as back-up will be described. The whole system serves as a prototype for testing new automatic control methods to increase the plant reliability, which is crucial in remote arid areas. The necessary steps for the design of...
Support Vector Machines (SVMs) ensembles have been widely used to improve classification accuracy in complicated pattern recognition tasks. In this work we propose to apply an ensemble of SVMs coupled with feature-subset selection methods to aleviate the curse of dimensionality associated with expression-based classification of DNA microarray data. We compare the single SVM classifier to SVM ensembles...
In this paper, we describe an alternative method of the recognition of human irises with the usage of Non-Negative Matrix Factorization. The proposed method has been implemented on graphic processor unit (GPU) which makes the method usable in the real world due to short computation time.
The constant growth of the Internet has made recommender systems very useful to guide users coping with a large amount of data. In this paper, we present a domain independent collaborative and semantic-based recommender system which uses distinct and complementary modules. The approach targets users with various interests and is based on: (i) a collaborative module using association rules in order...
The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models can describe the scene accurately, but they come with a high computational requirements, too. Low complex models promote segmentation speed, with the drawback of a less exhaustive description. In this paper we propose an...
Modeling distributed system and modeling intelligent system means that we create a model of a system with corresponding behavior. Multiagent systems are complex systems implementing a platform which is responsible for agent management including inter-agent communication, an agent specification, its behavior, etc. There are many agent platforms that are primarily intended for different applications...
In some machine learning applications using soft labels is more useful and informative than crisp labels. Soft labels indicate the degree of membership of the training data to the given classes. Often only a small number of labeled data is available while unlabeled data is abundant. Therefore, it is important to make use of unlabeled data. In this paper we propose an approach for Fuzzy-Input Fuzzy-Output...
This paper addresses the problem of moving obstacle detection for autonomous mobile robots in unknown urban environments through the fusion of (vehicle-mounted) forward looking laser and vision sensors. In this approach we reparameterize the 2D gaussian distribution of the laser free-configuration eigenspaces by vision saliency gaussian kernel function. The approach uses bi-sensor paradigm to achieve...
Support Vector Machine (SVM) is one of the most popular tools for solving general classification and regression problems because of its high predicting accuracy. However, the training phase of nonlinear kernel based SVM algorithm is a computationally expensive task, especially for large datasets. In this paper, we propose an intelligent system to solve large classification problems based on parallel...
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