Visual tracking using convolutional features with sparse coding

Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial...     

The rare caribbean spongeLeucosolenia canariensis: Phospholipid fatty acids and sterols

The phospholipid fatty acid composition of the Calcarean spongeLeucosolenia canariensis was studied, and no Δ^5,9 fatty acids were detected. These results are in contrast to the phospholipids from sponges belonging to the class Demospongiae where Δ5,9 fatty acids are predominant. Odd branched-chain fatty acids between 17 and 19 carbons accounted for 26% of the total fatty acids ofL. canariensis, while straight-chain fatty acids between 16 and 22 carbons accounted for 61% of the total fatty acid composition. The sterol composition ofL. canariensis is also reported, and only Δ^5,7,22 sterols were observed.     

Speech enhancement with an adaptive Wiener filter

This paper proposes an adaptive Wiener filtering method for speech enhancement. This method depends on the adaptation of the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance. It is implemented in the time domain rather than in the frequency domain to accommodate for the time-varying nature of the speech signals. The proposed method is compared to the traditional frequency-domain Wiener filtering, spectral subtraction and wavelet denoising methods using different speech quality metrics. The simulation results reveal the superiority of the proposed Wiener filtering method in the case of Additive White Gaussian Noise (AWGN) as well as colored noise.     

An efficient singular value decomposition algorithm for digital audio watermarking

The singular value decomposition (SVD) mathematical technique is utilized, in this paper, for audio watermarking in time and transform domains. Firstly, the audio signal in time or an appropriate transform domain is transformed to a 2-D format. The SVD algorithm is applied on this 2-D matrix, and an image watermark is added to the matrix of singular values (SVs) with a small weight, to guarantee the possible extraction of the watermark without introducing harmful distortions to the audio signal. The transformation of the audio signal between the 1-D and 2-D formats is performed in the well-known lexicographic ordering method used in image processing. A comparison study is presented in the paper between the time and transform domains as possible hosting media for watermark embedding. Experimental results are in favor of watermark embedding in the time domain if the distortion level in the audio signal is to be kept as low as possible with a high detection probability. The proposed algorithm is utilized also for embedding chaotic encrypted watermarks to increase the level of security. Experimental results show that watermarks embedded with the proposed algorithm can survive several attacks. A segment-by-segment implementation of the proposed SVD audio watermarking algorithm is also presented to enhance the detectability of the watermark in the presence of severe attacks.     

Applying Dynamic Training‐Subset Selection Methods Using Genetic Programming for Forecasting Implied Volatility

Volatility is a key variable in option pricing, trading, and hedging strategies. The purpose of this article is to improve the accuracy of forecasting implied volatility using an extension of genetic programming (GP) by means of dynamic training‐subset selection methods. These methods manipulate the training data in order to improve the out‐of‐sample patterns fitting. When applied with the static subset selection method using a single training data sample, GP could generate forecasting models, which are not adapted to some out‐of‐sample fitness cases. In order to improve the predictive accuracy of generated GP patterns, dynamic subset selection methods are introduced to the GP algorithm allowing a regular change of the training sample during evolution. Four dynamic training‐subset selection methods are proposed based on random, sequential, or adaptive subset selection. The latest approach uses an adaptive subset weight measuring the sample difficulty according to the fitness cases' errors. Using real data from S&P500 index options, these techniques are compared with the static subset selection method. Based on mean squared error total and percentage of non‐fitted observations, results show that the dynamic approach improves the forecasting performance of the generated GP models, especially those obtained from the adaptive‐random training‐subset selection method applied to the whole set of training samples.     

Hybrid‐impulsive second‐order sliding mode control: Lyapunov approach

Dynamic system of relative degree two controlled by discontinuous‐hybrid‐impulsive feedback in the presence of bounded perturbations is considered. The state feedback impulsive‐twisting control exhibits a uniform exact finite time convergence to the second‐order sliding mode with zero convergence time. The output feedback discontinuous control augmented by a simplified hybrid‐impulsive functions provides uniform exact convergence with zero convergence time of the system's states to a real second‐order sliding mode in the presence of bounded perturbations. Only ‘snap’ knowledge of the output derivative, that is, the knowledge of the output derivative in isolated time instants, is required. The output feedback hybrid‐impulsive control with practically implemented impulsive actions asymptotically drives the system's states to the origin. The Lyapunov analysis of the considered hybrid‐impulsive‐discontinuous system proves the system's stability. The efficacy of the proposed control technique is illustrated via computer simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

Asymptotic stability and estimating the region of attraction for the swing equations

We state and prove a theorem that asserts the asymptotic stability and provides an estimate of the region of attraction of an equilibrium point of the swing equations. A version of this theorem was originally introduced by Willems; however, his justifications are sketchy and, in our opinion, require additional analysis. All the Liapunov method analyses utilized in the transient stability problem of power systems have been based on the assumed validity of this theorem. The shortcomings of the other proposed proofs in the literature is that they rely on available Liapunov theorems for which an assumption can not be verified. In contrast, the techniques used in the proof here avoid the restriction of the available Liapunov theorems; moreover, they can be extended to apply to a broader class of systems.     

A videogrammetric as-built data collection method for digital fabrication of sheet metal roof panels

A roofing contractor typically needs to acquire as-built dimensions of a roof structure several times over the course of its build because a structure is never built to the exact drawing dimensions. In the construction phase and in order to digitally fabricate sheet metal roof panels, the contractor has to measure end-to-end dimensions of boundaries of every roof plane with a certain level of accuracy (i.e., errors less than ±2 cm). This is necessary to be able to cut sheet metal coil such that different pieces perfectly fit together. Obtaining these measurements using the exiting roof surveying methods could be costly in terms of equipment, labor, and/or worker exposure to safety hazards. This paper presents a video-based surveying framework as an alternative method which is simple to use, automated, less expensive, and safe. When using this framework, the contractor collects video streams with a calibrated stereo camera set. The captured data is processed to automatically generate a 3D wire-diagram of the target roof. Measurements from the wire-diagram are saved in a digital file (XML format) which could be loaded into an on-site sheet metal folding and cutting machine. Experimental analyses demonstrate applicability of the proposed framework.