Compressive sensing using the modified entropy functional

Cataloged from PDF version of article.In most compressive sensing problems, 1 norm is used during the signal reconstruction process. In this article, a modified version of the entropy functional is proposed to approximate the 1 norm. The proposed modified version of the entropy functional is continuous, differentiable and convex. Therefore, it is possible to construct globally convergent iterative algorithms using Bregman’s row-action method for compressive sensing applications. Simulation examples with both 1D signals and images are presented. © 2013 Elsevier Inc. All rights reserved

Projections Onto Convex Sets (POCS) Based Optimization by Lifting

Two new optimization techniques based on projections onto convex space (POCS) framework for solving convex and some non-convex optimization problems are presented. The dimension of the minimization problem is lifted by one and sets corresponding to the cost function are defined. If the cost function is a convex function in R^N the corresponding set is a convex set in R^(N+1). The iterative optimization approach starts with an arbitrary initial estimate in R^(N+1) and an orthogonal projection is performed onto one of the sets in a sequential manner at each step of the optimization problem. The method provides globally optimal solutions in total-variation, filtered variation, l1, and entropic cost functions. It is also experimentally observed that cost functions based on lp, p<1 can be handled by using the supporting hyperplane concept

Probabilistic Assessment of Liquefaction Over Large Areas

Since the 1964 Niigata, Japan, earthquake, damages attributed to earthquake induced liquefaction phenomena have cost society hundreds of millions U.S. dollars. Most procedures developed so far predict the potential for earthquake induced liquefaction at the “point” or over the small area, where the soil strength is evaluated. This paper describes a technique to estimate the probability of earthquake induced liquefaction over arbitrary large areas. The proposed technique may be of special interest to both large corporation and insurance company risk management departments, which are looking at estimating earthquake damages over a large area. The area of interest is meshed forming a grid of individual cells, for which the probability of liquefaction is estimated. The probability of liquefaction for a given percentage of the total area is then computed as a system reliability problem

Entropy-Functional-Based Online Adaptive Decision Fusion Framework with Application to Wildfire Detection in Video

Cataloged from PDF version of article.In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented

Lossless image compression by LMS adaptive filter banks

Cataloged from PDF version of article.A lossless image compression algorithm based on adaptive subband decomposition is proposed. The subband decomposition is achieved by a two-channel LMS adaptive filter bank. The resulting coefficients are lossy coded first, and then the residual error between the lossy and error-free coefficients is compressed. The locations and the magnitudes of the nonzero coefficients are encoded separately by an hierarchical enumerative coding method. The locations of the nonzero coefficients in children bands are predicted from those in the parent band. The proposed compression algorithm, on the average, provides higher compression ratios than the state-of-the-art methods. (C) 2001 Elsevier Science B.V. All rights reserved

Test beam studies of the TRD prototype filled with different gas mixtures based on Xe, Kr, and Ar

Towards the end of LHC Run1, gas leaks were observed in some parts of the Transition Radiation Tracker (TRT) of ATLAS. Due to these leaks, primary Xenon based gas mixture was replaced with Argon based mixture in various parts. Test-beam studies with a dedicated Transition Radiation Detector (TRD) prototype were carried out in 2015 in order to understand transition radiation performance with mixtures based on Argon and Krypton. We present and discuss the results of these test-beam studies with different active gas compositions.Comment: 5 pages,12 figures, The 2nd International Conference on Particle Physics and Astrophysics (ICPPA-2016); Acknowledgments section correcte

Wavelet based flickering flame detector using differential PIR sensors

Cataloged from PDF version of article.A Pyro-electric Infrared (PIR) sensor based flame detection system is proposed using a Markovian decision algorithm. A differential PIR sensor is only sensitive to sudden temperature variations within its viewing range and it produces a time-varying signal. The wavelet transform of the PIR sensor signal is used for feature extraction from sensor signal and wavelet parameters are fed to a set of Markov models corresponding to the flame flicker process of an uncontrolled fire, ordinary activity of human beings and other objects. The final decision is reached based on the model yielding the highest probability among others. Comparative results show that the system can be used for fire detection in large rooms. (C) 2012 Elsevier Ltd. All rights reserved

Some results of test beam studies of Transition Radiation Detector prototypes at CERN

Operating conditions and challenging demands of present and future accelerator experiments result in new requirements on detector systems. There are many ongoing activities aimed to develop new technologies and to improve the properties of detectors based on existing technologies. Our work is dedicated to development of Transition Radiation Detectors (TRD) suitable for different applications. In this paper results obtained in beam tests at SPS accelerator at CERN with the TRD prototype based on straw technology are presented. TRD performance was studied as a function of thickness of the transition radiation radiator and working gas mixture pressure

Video fire detection - Review

Cataloged from PDF version of article.This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor “volumes” and do not have transport delay that the traditional “point” sensors suffer from. It is possible to cover an area of 100 km2 using a single pan-tiltzoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation. © 2013 Elsevier Inc. All rights reserve