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In prior work, the Distributed Gradient Projection (DGP) algorithm was proposed to allow loads or load aggregators to provide contingency service to the grid using local frequency measurements. The DGP algorithm was shown to perform well in linear simulations. The goal of this work is to evaluate the performance of the DGP algorithm in more realistic scenarios and its robustness to issues of practical...
Reliability management is of great importance for the secure and sufficient operation of power systems, thus the n — KG — KL contingency constrained unit commitment (CCUC) problem is determined for investigation in this paper. In order to reveal the capability of different methods on the solution of CCUC, both explicit and implicit decomposition frameworks have been investigated, as well as their...
Background modeling from surveillance video plays a key role in event detection and human action recognition. Its goal is finding moving objects in video that are independent of the background scene. Among many background modeling algorithms, robust principle component analysis is a recently popular technique, which characterizes the moving objects via L1 norm. However, L1 norm often leads to inaccurate...
Paper is focused on problem of robust feature detector stability and efficiency in case when intensity distribution is uneven over image. Results of feature detector simulation and equations for estimation rate of false alarms and probability of correct detection are presented in paper.
Subspace clustering is one of the active research problem associated with high-dimensional data. Here some of the standard techniques are reviewed to investigate existing methodologies. Although, there have been various forms of research techniques evolved recently, they do not completely mitigate the problems pertaining to noise sustainability and optimization of clustering accuracy. Hence, a novel...
An accurate and robust lane recognition is a key aspect for autonomous cars of the near future. This paper presents the design and implementation of a robust autonomous driving algorithm using the proven Viola-Jones object detection method for lane recognition. The Viola-Jones method is used to detect traffic cones that are located besides the road as it can be done in emergency situations. The positions...
A robust structure of an emergency service system is usually designed so that the deployment of given number of service centers complies with specified scenarios by minimizing the maximal value of objective functions corresponding with the particular scenarios. If the problem is modelled by means of mathematical programming and solved by a general IP solver, than the min-max link-up constraints represent...
The paper considers the problem of ship autopilot design based on Bech's model of the vessel. Since the ship model is highly nonlinear and the state vector is not completely measurable, the control system synthesis is performed by means of output feedback linearization method combined with a state observer. Due to considerable parameter variations and other substantial uncertainties a robust-adaptive...
Automatic malware categorization plays an important role in combating the current large volume of malware and aiding the corresponding forensics. Generally, there are lot of sample information could be extracted with the static tools and dynamic sandbox for malware analysis. Combine these obtained features effectively for further analysis would provides us a better understanding. On the other hand,...
Control algorithms are essential in multirotor aerial platforms and remain a trending research topic. This paper presents the development process of different cascade controllers for multirotor UAVs. Two main usage areas of this method are described — the control of position and attitude. Based on the literature and experience from previous research, structures of mentioned algorithms are proposed...
In this paper, a robust algorithm for gait cycle segmentation is proposed based on a peak detection approach. The proposed algorithm is less influenced by noise and outliers and is capable of segmenting gait cycles from different types of gait signals recorded using different sensor systems. The presented algorithm has enhanced ability to segment gait cycles by eliminating the false peaks and interpolating...
A novel sensorless speed control algorithm based on sliding mode observer (SMO) for permanent magnet synchronous motors (PMSM) is proposed. By utilizing a phase locked loop algorithm (PLL) based on synchronous reference frame and an embedded low pass filter, the drawback of SMO called “chattering phenomenon” is effectively attenuated, with no phase delay caused by the filter. The active back electromotive...
An image watermarking algorithm based on grey relational analysis and singular value decomposition in wavelet domain is proposed. Firstly, the host image is processed with one-level of discrete wavelet transform. The low frequency coefficients LL1 can be obtained from mentioned operation, and LL1 is divided into non-overlapping blocks whose size is same as watermarking. Secondly, through the gained...
In order to reduce the false matching rate and matching time, an improved algorithm based on RANSAC-SIFT was proposed. The feature points were extracted by SIFT algorithm firstly. Then most of the mismatching points were eliminated according to the constraints that matching distances tend to be consistent. Finally the remaining points were regarded as pre matching points for achieve fine matching...
Data Encryption Standard (DES) was initially considered a strong symmetric encryption algorithm, resistant to all known cryptographic attacks at that time [1]. But the short key used to encrypt data is a weakness of the algorithm. Increasing the data structure size and the key length are two recommended measures that ensure the strength of the encryption algorithm. The running-time is a constraint...
A heuristic neural network (HNN) algorithm is proposed for pattern recognition. To achieve faster convergence and to promote the recognition accuracy, the proposed neural network is trained by adjusting the weighting values between layers, bias values of neurons and the learning rate according to the classification error. The whole architecture includes the image capturing by CCD camera, image pre-processing,...
K-means algorithm is a classical algorithm and has been widely used in many applications. However, the traditional K-means algorithm is easily influenced by outliers and it usually obtains an unstable clustering result and poor clustering accuracy. In this paper, aiming at K-means algorithm resistant to outliers, we proposed a Capped Robust K-means Algorithm (CRK-means) by adding a capped norm and...
We introduce a novel approach to jointly estimate consistent depth and normal maps from 4D light fields, with two main contributions. First, we build a cost volume from focal stack symmetry. However, in contrast to previous approaches, we introduce partial focal stacks in order to be able to robustly deal with occlusions. This idea already yields significanly better disparity maps. Second, even recent...
We present an algorithm for registration between a large-scale point cloud and a close-proximity scanned point cloud, providing a localization solution that is fully independent of prior information about the initial positions of the two point cloud coordinate systems. The algorithm, denoted LORAX, selects super-points–local subsets of points–and describes the geometric structure...
Principal Component Analysis (PCA) is a fundamental method for estimating a linear subspace approximation to high-dimensional data. Many algorithms exist in literature to achieve a statistically robust version of PCA called RPCA. In this paper, we present a geometric framework for computing the principal linear subspaces in both situations that amounts to computing the intrinsic average on the space...
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