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A high-dimensional Simultaneous Localization and Mapping (SLAM) algorithm is presented that replaces the particles in FastSLAM with individual Gaussians. In addition, the high-dimensional vehicle state is partitioned into linear and nonlinear parts and the nonlinear part is approximated by a mixture of Gaussians of which the means and covariances are propagated and updated using sparse grid quadrature...
The accuracy and the computational complexity of a Gaussian mixture model depends upon the number of components. In a stochastic dynamical system, the number of these components must change over time to account for the change in the uncertainty over time. A new splitting technique is provided based on the minimization of Fokker Planck Kolmogorov Equation. The effect of the splitting on the other components...
This paper presents a detailed comparison of the most significant methods developed to compute lower bounds on the structured singular value. The objective is to characterize the behavior of these robustness analysis tools on the basis of a common framework constituted by a wide set of various real-world applications.
AFM based nano robotics uses the tip to perform observing and maneuvering with high resolution and accuracy. The tip position uncertainties in the task space due to the PZT nonlinearity and thermal drift is compensated by using the landmarks existing in the task region. This method can detect and control the accuracy of the relative position between AFM tip and the interest object. However, as for...
We have reported recently a high-accuracy measurement of the differential static scalar polarizability, Δα0, of the clock transition of 88Sr+. In this paper, we review the method used to make this measurement and the results obtained. Δα0 is an essential parameter for the control of the systematic shifts in ion optical frequency standards as it determines the blackbody radiation shift coefficient...
Recent research efforts in data stream management systems (DSMS) focus mainly on processing continuous queries over traditional data streams, and only a few addressed spatio-temporal continuous queries. OCEANUS presents an effort to extend TelegraphCQ DSMS with spatial support providing a platform for spatio-temporal streaming applications. Data type system that represents the formal basis for modeling...
Power Quality assessment is based on measuring and monitoring of specific parameters. Measure uncertainty level is important because parameters values are estimated based on this information and then compared with admissible limits. More, the decisions and solutions for electromagnetic pollution limitation is also based on that results. ISO/IEC 61000-4-30:2008 Standard contains uncertainty levels...
This paper proposes a novel method to estimate relative poses for a calibrated stereo camera. Three corresponding points in 3D space are theoretically required to recover unconstraint motion which has six degrees of freedom. The proposed method solves this problem with only two 3D points by exploiting a common reference direction between poses. Two points are selected in accordance with the distance...
Tracking systems that use RFID are increasingly being used for monitoring the movement of goods in supply chains. While these systems are effective, they still have to overcome significant challenges, such as missing reads, to improve their performance further. In this paper, we describe an optimised tracking algorithm to predict the locations of objects in the presence of missed reads using particle...
Swarms of autonomous underwater vehicles (AUVs) forming mobile underwater networks often operate in moving currents, which introduce severe turbulence that interferes with coordinated and stealthy navigation of fleet. Therefore, individual AUV must adjust their heading whenever needed to ensure it can reach a pre-determined destination. To achieve accurate navigation, AUVs must maintain precise knowledge...
Wild bootstrap resampling technique was proposed to improve parameter estimations of intra-voxel incoherent motion (IVIM) MRI, i.e. diffusion fraction (f), diffusion (D) and pseudo-diffusion (D∗), without increasing scan time. It was verified via simulation and clinical scan. In simulation, estimation accuracy and uncertainty obtained from asymptotic fitting with and without wild bootstrapping were...
In this paper we present a scheme to reduce the amount of user iterations required to segment an object by delineating on cross-section planes. Starting with an initial segmentation created from a small number of delineated curves, the algorithm progressively analyzes the uncertainty of segmentation with respect to the image features and suggests the “next plane” for delineation that would maximally...
We propose a active learning (AL) approach to segment Crohn's disease (CD) affected regions in abdominal magnetic resonance (MR) images. Our label query strategy is inspired from the principles of visual saliency which has similar considerations for choosing the most salient region. These similarities are encoded in a graph using classification maps and low level features. The most informative node...
Traditional approaches for semantic segmentation work in a supervised setting assuming a fixed number of semantic categories and require sufficiently large training sets. The performance of various approaches is often reported in terms of average per pixel class accuracy and global accuracy of the final labeling. When applying the learned models in the practical settings on large amounts of unlabeled...
Many advancement is made in recent days and number of techniques are proposed by different researchers for processing and extracting knowledge from big data. But to evaluate the consistency in extracted model is always questionable. In this paper we are presenting two techniques for measuring the consistency between extracted model and predicting their applicability. In this paper, Meta learning based...
As there are climatic changes, there are many risks involved in predicting these changes and make decisions on some infrastructure due to extreme weather conditions and shifting weather patterns. Existing research indicates that small increase in the climate and weather extremes which have the potential to bring large calamities to the existing infrastructures. These changes may be due to the presence...
A typical trade-off in decision making is between the cost of acquiring information and the decline in decision quality caused by insufficient information. Consumers regularly face this trade-off in purchase decisions. Online product/service reviews serve as sources of product/service related information. Meanwhile, modern technology has led to an abundance of such content, which makes it prohibitively...
Recently, various consensus-based protocols have been developed for time synchronization in wireless sensor networks. However, due to the uncertainties lying in both the hardware fabrication and network communication process, it is not clear how most of the protocols will perform in real implementations. In order to reduce such gap, this paper investigates whether and how the typical consensus-based...
The problem of classifying samples for which there is no definite label is a challenging one in which multiple annotators will provide a more certain input for a classifier. Unlike most of active learning scenarios that require identifying which images to be annotated, we explore how many annotations can potentially be used per instance (one annotation per instance is only the initial step) and propose...
In real world applications, data are often uncertain or imperfect. In most classification approaches, they are transformed into precise data. However, this uncertainty is an information in itself which should be part of the learning process. Data uncertainty can take several forms: probabilities, (fuzzy)sets of possible values, expert assessments, etc. We therefore need a flexible and generic enough...
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