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Underwater imaging is a crucial technology necessary for many ocean-related applications such as underwater navigation, surveying, mining and many others. Unfortunately, the optical attenuation produced by oceanic waters imposes severe limitations to traditional imaging devices. Thus, new technologies are needed to probe the underwater environment in a more efficient manner. Quantum imaging represents...
The paper considers an issues of protecting data from unauthorized access by users' authentication through keystroke dynamics. It proposes to use keyboard pressure parameters in combination with time characteristics of keystrokes to identify a user. The authors designed a keyboard with special sensors that allow recording complementary parameters. The paper presents an estimation of the information...
Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we introduce a distributed compressive sensing approach, which utilizes spatial correlation among sensor nodes to group them into coalitions. The coalition formation method is represented by a block diagonal measurement matrix...
Ballistocardiogram (BCG) has been revisited in the last years as an unobtrusive method to detect heart beats. New electromechanical film (EMFi) sensors are now able to detect minimal oscillations in its surface, allowing to detect the mechanical action of the heart as it beats. This has allowed to develop unobtrusive systems for heart rate monitoring to be used as Point-of-Care devices, and to deploy...
Accurate estimation of the vehicle sideslip angle is fundamental in vehicle dynamics control and stability. In this paper two different methods for vehicle sideslip estimation, based on Principal Component Analysis (PCA) and Neural Networks (NN), are presented comparing the procedure responses with full-scale vehicle acquired test data. The estimation algorithms use driver's steering angle, lateral...
In this paper, we address the use of multi-layered sliding windows to detect the presence of a wireless network for cognitive radio applications. Although synchronization signals of the Long Term Evolution (LTE) has been used as the reference system, the proposed scheme is generic in principle. Our proposed scheme doesn't require any a priori knowledge of the exact synchronization sequences, so it...
A cluster formation algorithm is proposed to save the wastage of energy in cooperative spectrum sensing (CSS), in which small number of groups called clusters are made using fuzzy c-means (FCM). Based on spatial correlation, only limited number of SUs are selected from each cluster, whose sensing information is forwarded to their cluster head (CHs). The primary goal of cognitive radio network is spectrum...
Benefiting from compressed sensing theory, sub-Nyquist spectrum sensing (SNSS) has been considered as a promising way to deal with the implementation limitations of conventional wideband spectrum sensing in cognitive radio (CR) networks. However, in most existing SNSS methods, the prior knowledge of the monitored frequency bands is needed to determine the termination condition of the iteration process...
Cognitive radio (CR) is an intelligent system for designing modern wireless communication systems. Spectrum sensing is one of the most important issues in CR. This paper presents a semi blind spectrum sensing method which exploits the combination of comb filter and autocorrelator. The proposed method improves the detection performance of blind spectrum sensing in severe noise environments where an...
Considering a small-scale fading environment in a dense random wireless network, we investigate the impact of the carrier-sensing threshold on the link performance under the premise of a fixed carrier-sensing range. At first, we assume a close transmitter-receiver distance and model the network nodes as a homogeneous Poisson point process (PPP). Then we present a simple analysis model of the conditional...
The use of the Electrohysterogram (EHG) for imaging the sources of the uterine electrical activity is a new and powerful diagnosis technique. However, its performance is limited as the uterus often demonstrates several simultaneously active regions and as EHGs present low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a...
Overhead distribution lines are usually subject to voltage transients during thunderstorms. Lightning flashes, whether direct or indirect, are one of the main causes of power quality disturbances on the electric grid. In this paper, a methodology to establish a correlation between the incidence point of a lightning flash, the stroke current amplitude and polarity and its effects on the electric distribution...
The article presents an analysis of correlation-based clustering procedure in cooperative spectrum sensing. The motivation is to assess if it is more beneficial in terms of energy efficiency to group nodes according to the received signal-to-noise ratio (SNR) on the link between Primary User and node or according to the distance between nodes. To this end, a merged clustering measure is introduced...
Presented paper deals with a model of the electromagnetic sources localization in near-field sources region and verification of selected algorithms for correct modelling estimations. The localization is performed from cross-correlation matrix of planar sensors network signals and further cross-correlation matrix decomposition — Multiple Signal Classification (MUSIC). The whole mathematical model from...
High data quality and low sensing cost are two primary goals in large-scale mobile crowdsensing applications. The oversampling and the undersampling are common problems which always result in a high cost or low data quality that can not satisfy the system requirement. To address this problem, taking into account low-rank latent structure, we propose a compressive and adaptive data sampling scheme...
A monocular vision detection system was designed for multipoint pulse signals detection. The system consists of three parts. The first is pulse image acquisition device, which is used to collect dynamic pulse images. The second is multipoint pulse signals extraction algorithm that is using suitable digital image processing methods to process the collected pulse image sequence, and adopting monocular...
Today's high-performance computing (HPC) systems are heavily instrumented, generating logs containing information about abnormal events, such as critical conditions, faults, errors and failures, system resource utilization, and about the resource usage of user applications. These logs, once fully analyzed and correlated, can produce detailed information about the system health, root causes of failures,...
Improving the accuracy of satellite-derived precipitation estimates is very important to extend the extent and depth of their application. Existing calibration methods calibrated satellite-derived precipitation estimates based on a strong relationship between gauge measurements and estimated precipitation. However, such a relationship is always disturbed by variation of land surface characteristics,...
Clustering of multimodal data according to their information content is considered in this paper. Statistical correlations present in data that contain similar information are exploited to perform the clustering task. Specifically, multiset canonical correlation analysis is equipped with norm-one regularization mechanisms to identify clusters within different types of data that share the same information...
Compressed Sensing is for sparse and compressible signals, the data is compressed while the signal is sampled. This paper proposes the new deterministic measurement matrices that are studied: according to the compressible signal characteristics, we will use the unit matrix added with random orthogonal matrix and complementary sequences as the measurement matrix, and then using orthogonal matching...
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