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The problem of identifying the 3D pose of a known object from a given 2D image has important applications in Computer Vision. Our proposed method of registering a 3D model of a known object on a given 2D photo of the object has numerous advantages over existing methods. It does not require prior training, knowledge of the camera parameters, explicit point correspondences or matching features between...
In this paper, we use an FPGA platform and a high level synthesis tool, called Impulse C, to speedup a statistical Line Of Reaction (LOR) estimation for a high-resolution Positron Emission Tomography (PET) scanner. The estimation algorithm provides a significant improvement over conventional methods, but the execution time is too long to be practical for clinic applications. Impulse C allows us to...
Accurate cardinality estimates are essential for a successful query optimization. This is not only true for relational DBMSs but also for RDF stores. An RDF database consists of a set of triples and, hence, can be seen as a relational database with a single table with three attributes. This makes RDF rather special in that queries typically contain many self joins. We show that relational DBMSs are...
A distributed event processing system consists of one or more nodes (machines), and can execute a directed acyclic graph (DAG) of operators called a dataflow (or query), over long-running high-event-rate data sources. An important component of such a system is cost estimation, which predicts or estimates the “goodness” of a given input, i.e., operator graph and/or assignment of individual operators...
The process of determining the worst-case execution time (WCET) is challenged in the presence of caches due to their unpredictable effect on the speed of memory references. In particular, when cache conflicts between program lines are common, thrashing occurs and this inadvertently increases the WCET, sometimes significantly so. One way to minimise the cache impact on the WCET, therefore, is to judiciously...
The k-core of a graph is the largest subgraph in which every vertex is connected to at least k other vertices within the subgraph. Core decomposition finds the k-core of the graph for every possible k. Past studies have shown important applications of core decomposition such as in the study of the properties of large networks (e.g., sustainability, connectivity, centrality, etc.), for solving NP-hard...
This article analyses the calculation problems concerning mean square error of side length, mean square error of starting point and triangle figure condition which will affect comprehensively error of intersection point, especially linear intersection minor angle triangle's intersection angle between 150° ~ 180° intersection point's error optimization and the optimum solution of point transfer coordinate...
In this work we address the problem of state estimation in dynamical systems using recent developments in compressive sensing and sparse approximation. We formulate the traditional Kalman filter as a one-step update optimization procedure which leads us to a more unified framework, useful for incorporating sparsity constraints. We introduce three combinations of two sparsity conditions (sparsity in...
The compensator design is closely related to the transient response achieved by the closed loop converter. So, the representation of the aforementioned transient response while designing the compensator is a powerful optimization tool. However, in order to represent the transient response, the small signal model of the power stage must be completely characterized. When the power stage is not determined...
Brain image segmentation is one of the most important applications in medicine and also is one of the most challenging topics in the field of medical image processing. In general, most automatic segmentation methods consist of an energy function, a shape model, and an optimization strategy. Each plays an important role in the design of an accurate segmentation algorithm. Here we introduce a modified...
This paper deals with the detection and estimation of fault parameter in nonlinear systems. Our main contribution in this work consists in the synthesis of a flat moving horizon estimator for a supervision industrial process. The effectiveness of the proposed method is shown through the supervise of a series DC motor. The obtained results are very satisfactory in terms of detection rapidity and precision...
In cyclic (or alternating) method, the full parameter vector is divided into two or more subvectors and the process proceeds by sequentially optimizing each of the subvectors while holding the remaining parameters at their most recent values. One example of the advantage of the scheme is the preservation of large investments in software while allowing for an extension of capability to include new...
Multi-resource sharings among virtual machines (VM)are very important in data center, but also bring contentions for cache, disk and network in host server. Recent studies focus primarily on locally optimizing resource sharings in a single server, or global optimization of mitigating cache and memory contentions. But it remains an open question how to efficiently find optimal co-schedules for cache,...
Tracking algorithms are traditionally based on either a variational approach or a Bayesian one. In the variational case, a cost function is established between two consecutive frames and minimized by standard optimization algorithms. In the Bayesian case, a stochastic motion model is used to maintain temporal consistency. Among the Bayesian methods we focus on the particle filter, which is especially...
Symmetry and inverse consistency are two important features for deformable image registration in medical imaging analysis. This work presents a novel registration method computing symmetric and inverse-consistent image alignment efficiently while preserving high accuracy and consistency of the mapping. This is achieved by optimizing a symmetric energy functional estimating forward and backward transformations...
Recent work has shown that resonate-and-fire model is both computationally efficient and suitable for large network simulations. In this paper, we examine the estimation problem of a resonate-and-fire model with random threshold. The model parameters are divided into two sets. The first set is associated with subthreshold behavior and can be optimized by a nonlinear least squares algorithm. The other...
In this paper we deal with modeling serum proteolysis process from tandem mass spectrometry data. The parameters of peptide degradation process inferred from LC-MS/MS data correspond directly to the activity of specific enzymes present in the serum samples of patients and healthy donors. Our approach integrate the existing knowledge about peptidases' activity stored in MEROPS database with the efficient...
This paper focuses on the optimization of the 2D geometry of sensor arrays for 2D direction-of-arrival (DOA) estimation. Such arrays can be used for radar imaging purposes. Due to the optimization, the number of array channels can be kept quite small, which reduces hardware costs, while highly accurate DOA estimation accuracy can be achieved. Therefore, we derive a very simple expression of the 2D...
As an important type of reliability optimization problems, the component assignment problem (CAP) is to find the optimal arrangement of n available components to n positions of a system such that the resulting system reliability is maximized. The CAP is a combinatorial problem in nature and needs effective solution methods. The importance measures of components, e.g., the Birnbaum importance (BI),...
The criteria of finding the optimal structure of the model as interval difference operator is carried out. It is shown that the formulated task of structure identification is a multicriteria optimization task with the discrete target functions and nonlinear constraints specified by interval system of nonlinear algebraic equations (ISNAE).
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