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There are various leak test methods used to verify the integrity of seals for underwater hardware; these methods have a wide range of sensitivity and cost. Helium leak testing with the use of a high vacuum mass spectrometer leak detector provides the greatest sensitivity; however, in more complex sealing systems, the utility of the results is entirely dependent upon the test configuration and method...
Fall-related injuries of elderly people have become a major public-health burden resulting in direct physical, physiological and financial costs to the surfer and indirect societal costs. Automated fall detectors play a central role in reducing these damages and in supporting safety and independency of the seniors. Typically, automated fall detection devices can send real time notifications to the...
Action recognition is still a challenging problem. In order to catch effective compact representation of the action sequences, the discriminative dictionaries could be learned by sparse coding. But sparse coding is needed in both the training and testing phases of the classifier framework. And it is also time consuming for the adoption of 1-norm sparsity constraint on the representation coefficients...
This paper introduces an intelligent integrated nondestructive testing system based on active the infrared thermal wave detection. The excitation heat source of the thermal wave includes ultrasonic excitation and electromagnetic excitation and exploiting the powerful resources of computer system and LabVIEW software to develop the virtual instrument. The integrated nondestructive testing system based...
We present a model and a hypothesis testing based framework for determining genuinely good service providers from the ratings given to them by customers, allowing ratings to be imperfect representations of the service provided. The problem is complicated because the nature of the customer that rates the service provider affects the reliability of the rating, but this nature is not known a priori and...
Car Recognition is a part of Intelligent Transportation System. This research proposes the manufacture of ITS-based system to identify car model from Its frontal image using Binary Robust Invariant Scalable method. The BRISK method is used to detect image keypoint, and it uses Hamming Distance for keypoint matching. As for matching error, this research depends on RANSAC. BRISK method excellence lies...
This research proposes a reliable machine learning based computational solution for human detection. The proposed model is specifically applicable for illumination-variant natural scenes in big data video frames. In order to solve the illumination variation problem, a new feature set is formed by extracting features using histogram of gradients (HoG) and linear phase quantization (LPQ) techniques,...
Convolutional neural network (CNN) based face detectors are inefficient in handling faces of diverse scales. They rely on either fitting a large single model to faces across a large scale range or multi-scale testing. Both are computationally expensive. We propose Scale-aware Face Detection (SAFD) to handle scale explicitly using CNN, and achieve better performance with less computation cost. Prior...
In this work we consider the problem of developing algorithms that automatically identify small-scale solar photovoltaic arrays in high resolution aerial imagery. Such algorithms potentially offer a faster and cheaper solution to collecting small-scale photovoltaic (PV) information, such as their location, capacity, and the energy they produce. Here we build on previous algorithmic work by employing...
An interesting target detection framework with transferred deep convolutional neural network (CNN) is proposed. For CNN, many labeled samples are needed to train the multi-layer network. However, for target detection tasks, only few target spectral signatures are available, or they are unknown in anomaly detection. In this work, we employ a reference data and further generate pixel-pairs to enlarge...
In this work, we consider the problem of detecting target objects in remote sensing imagery; such as detecting rooftops, trees, or cars in color/hyperspectral imagery. Many detection algorithms for this problem work by assigning a decision statistic (or “confidence”) to all, or a subset, of spatial locations in the data. A threshold is then applied to the statistics to identify detections. The detection...
This paper mainly concerns about the binary hypothesis testing problems with unknown parameters in null hypothesis and alternative hypothesis, where the prior for unknown parameters is not completely known, but is assumed to belong to an ∊-contamination class. We develop a method that decides between null hypothesis and alternative hypothesis reliably. Furthermore, when it decides in favor of null...
Detection with multiple distributions is considered. Rather than formulating the problem with multiple hypotheses, we formulate the problem in a binary hypothesis testing framework by a multiple model approach. Three classes of the Multi-Model Detection (MMD) problems are considered: simplex, compound, and mixture. Three concepts of optimality are given for these three problems, including Uniformly...
In this paper, we investigate active brain regions for motor execution and motor imagination tasks after training with a rehabilitation robot. Functional near-infrared spectroscopy (fNIRS) is used to measure the hemodynamic responses in the motor cortices of five subjects. An assistive robot (IMT 2.0, connected to the right hand) is used during the training session to make the subject to reach a target...
This article describes the radar (RL) method for extraction information about the defects of the rail track by registering their own natural oscillation frequency (NOF) rail span between two sleepers.
A distributed binary hypothesis testing problem, in which multiple observers transmit their observations to a detector over noisy channels, is studied. Together with its own observations, the goal of the detector is to decide between two hypotheses for the joint distribution of the data. Single-letter upper and lower bounds on the optimal type 2 error exponent (T2-EE), when the type 1 error probability...
The Radiated emission measurement is one of the tests required in EMC testing. CISPR 25 standard specifies the frequency range and the antennas used for this purpose. In this paper, differences that appear when using different measurement antennas and different semi-anechoic chambers in radiated emissions testing on the same DUT are investigated. Results show sometimes significant differences that...
In this study, the motion blur caused by the variable speed egomotion of camera is deblurred using multiple image frames and the obtained results are compared based on the detection performance of corner features. A linear, uniform motion blur data set is collected which is suitable for testing the multi-image deblurring method. The proposed method is tested on the dataset together with two baseline...
Vector Quantization (VQ) design for distributed binary decision in the presence of an eavesdropper (Eve) is investigated. An encoder/quantizer (Alice) observes i.i.d. samples and communicates them via a public noiseless rate-limited channel to the detector (Bob) who has also access to a correlated analog source. Bob can take advantage of both informations to perform a binary decision on the joint...
Numerous technical papers have been published discussing the topic of SubSynchronous Resonance (SSR) and more recently about new protection devices capable of detecting and protecting against the detrimental effects of SSR. The advent of such protection devices has created the new challenge of testing and commissioning such devices. Commissioning subharmonic protection devices require following a...
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