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This article describes the design and process of a 3D Mini Camera Lens to be utilised in multi-purpose 3D stereo reconstruction on computers, mobile devices and robots. It can also be useful for various tasks including demonstration, knowledge-sharing, online programming, database sharing, results comparison in the stereo vision research community, and recreation used by non-specialists. In contrast...
As a new type of flexible drive, pneumatic artificial muscle (PAM) has been widely concerned in various fields, but the research on the dynamic characteristics is difficult because of its strong nonlinearity and hysteresis. In this paper, the effects of system hardware configuration and control algorithm on the dynamic displacement characteristics of the double parallel Mckibben artificial muscles...
This paper presents a connectivity control algorithm of a multi-agent system. The connectivity of the multi-agent system can be represented by the second smallest eigenvalue λ2 of the Laplacian matrix LG and it is also referred to as algebraic connectivity. Unlike many of the existing connectivity control algorithms which adapt convex optimization technique to maximize algebraic connectivity, we first...
This paper deals with the results on the reconstruction accuracy of the irregularly sampled discrete-time signal (DTS) with unknown sampling locations. Reconstruction is performed by means of special reconstruction algorithms based on the sampling locations estimation. Comparison is done for results of estimation of the algorithms accuracy and accuracy of signal reconstruction by means of interpolation...
This article suggests an algorithm of impulse noise filtration, based on the community detection in graphs. The image is representing as non-oriented weighted graph. Each pixel of an image is corresponding to a vertex of the graph. Community detection algorithm is running on the given graph. Assumed that communities that contain only one pixel are corresponding to noised pixels of an image. Suggested...
Building secure networks is one of the most important tasks of information security. The paper describes the main technologies of dynamic networks and technologies for secure communication in them. Also this paper reviews and compares the system developed by the authors for the secure exchange of data in dynamic networks using encryption with data technology.
Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple change points. This general purpose change point detection procedure 'cp3o' applies a pruning routine within a dynamic program to greatly reduce the search space and computational costs. Existing goodness-of-fit change point...
CANDECOMP/PARAFAC Decomposition (CPD) is one of the most popular tensor decomposition methods that has been extensively studied and widely applied. In recent years, sparse tensors that contain a huge portion of zeros but a limited number of non-zeros have attracted increasing interest. Existing techniques are not directly applicable to sparse tensors, since they mainly target dense ones and usually...
In machine learning, data augmentation is the process of creating synthetic examples in order to augment a dataset used to learn a model. One motivation for data augmentation is to reduce the variance of a classifier, thereby reducing error. In this paper, we propose new data augmentation techniques specifically designed for time series classification, where the space in which they are embedded is...
In competitive energy markets, the growing adoption of renewable energy sources such as wind energy and photovoltaics causes power grid fluctuations due to the intermittency and variability in their power output. To balance the demand and generation by renewable sources conventional thermal power plants must operate with greater flexibility in the way they increase or decrease output. Furthermore,...
Biological molecules (e.g. DNAs, RNs, proteins, etc.) do not function in isolation themselves but in a sophisticated manner of various interactions between them to carry out every biological processes in living cells. Data about these interactions are exponentially increased thanks to advanced technologies. Analyzing biological interaction networks is essential to get insights into how biological...
Most state-of-the-art graph kernels only take local graph properties into account, i.e., the kernel is computed with regard to properties of the neighborhood of vertices or other small substructures. On the other hand, kernels that do take global graph properties into account may not scale well to large graph databases. Here we propose to start exploring the spacebetween local and global graph kernels,...
Consider a microgrid with a hybrid collection of distributed energy resources (DERs) that include fossil, renewables and energy storage battery systems. Given the dynamic variability of the DERs in terms of power production, this paper presents an optimization approach for the optimal power dispatch in such a hybrid microgrid by taking into account amplitude and rate constraints on each DER. The constrained...
The paper presents an approach for tracking a variable number of objects by using a multi-layer particle filter combined with an extended Expectation Maximization (EM) clustering. The approach works on basis of binary foreground images coming from previous background subtraction. The multi-layer particle filter is an improvement of a conventional particle filter approach. It uses an introduced adaptive...
In robotics, non-linear least squares estimation is a common technique for simultaneous localization and mapping. One of the remaining challenges are measurement outliers leading to inconsistency or even divergence within the optimization process. Recently, several approaches for robust state estimation dealing with outliers inside the optimization back-end were presented, but all of them include...
Algorithm research of task scheduling is one of the key techniques in grid computing. This paper firstly describes an DAG task scheduling model used in grid computing environment, then discusses generational scheduling (GS) and communication inclusion generational scheduling (CIGS) algorithms. Finally, an improved CIGS algorithm is proposed to use in grid computing environment, and it has been proved...
Vehicular fog computing extends the fog computing paradigm to conventional vehicular networks. This allows us to support more ubiquitous vehicles, achieve better communication efficiency, and address limitations in conventional vehicular networks in terms of latency, location awareness, and real-time response (typically required in smart traffic control, driving safety applications, entertainment...
This paper formulates and studies the problem of distributed filtering based on randomized gossip strategy in order to estimate the state of a dynamic system via all sensors in a network. First we introduce the randomized gossip algorithm by which the fastest averaging strategy can be obtained for a network with an arbitrary topology. Then we combine the randomized gossip algorithm with the information...
Adapted from biological sequence alignment, trace alignment is a process mining technique used to visualize and analyze workflow data. Any analysis done with this method, however, is affected by the alignment quality. The best existing trace alignment techniques use progressive guide-trees to heuristically approximate the optimal alignment in O(N2L2) time. These algorithms are heavily dependent on...
We revisit the K Nearest Neighbors (KNN) problem in large binary datasets which is of major importance in several applied areas. The goal is to find the K nearest items in a dataset to a query point where both the query and the items lie in the Hamming cube. The problem is addressed in its online setting, that is, data items are inserted sequentially into the dataset. To accommodate efficient similarity...
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