Correlation Output Research Articles

Experimental investigation on heat transfer of MgO nanofluid in tubes partially filled with metal foam

The aim of the present study is to experimentally investigate the thermal performance and the pressure drop in copper tubes partially filled with open-cell metal foams using MgO nanofluid. The tubes are produced by casting liquid metal around space holder material with the porosity of 70% and bounded by constant heat flux. MgO nanoparticles are added to the base fluid (water and ethylene glycol) to make the working fluid at the volumetric concentrations of 0.0625%, 0.25%, and 0.5%. The experiments are performed in a pipe with steady-state laminar flow. The obtained experimental results are compared with the correlation outputs, where a proper agreement between the results was observed. It is perceived that both pressure drop and Nusselt number are highly dependent on the Reynolds number. The data further shows that using nanofluid and porous media inside the tubes increases the pressure drop and convection heat transfer coefficient, significantly.

A novel correlation filter based on variational calculus

Correlation filters have been a popular technique for tackling image classification problems. The traditional criteria used to design correlation filters overlook some properties that can improve their discriminative power. Therefore, new criteria are proposed to design a novel correlation filter. Such criteria take advantage of negative samples, spatial information and the smoothness of the correlation output space. A closed form is derived from the criteria proposed using variational calculus. Moreover, it is shown that the resulting correlation filter is a bandpass filter. Experiments are conducted for face identification under illumination variation for a single training image per subject and head pose classification. The correlation filter proposed delivers favorable scores when compared to other correlation filters and state-of-the-art approaches.

Parallel Correlation Filters for Real-Time Visual Tracking.

Correlation filter-based methods have recently performed remarkably well in terms of accuracy and speed in the visual object tracking research field. However, most existing correlation filter-based methods are not robust to significant appearance changes in the target, especially when the target undergoes deformation, illumination variation, and rotation. In this paper, a novel parallel correlation filters (PCF) framework is proposed for real-time visual object tracking. Firstly, the proposed method constructs two parallel correlation filters, one for tracking the appearance changes in the target, and the other for tracking the translation of the target. Secondly, through weighted merging the response maps of these two parallel correlation filters, the proposed method accurately locates the center position of the target. Finally, in the training stage, a new reasonable distribution of the correlation output is proposed to replace the original Gaussian distribution to train more accurate correlation filters, which can prevent the model from drifting to achieve excellent tracking performance. The extensive qualitative and quantitative experiments on the common object tracking benchmarks OTB-2013 and OTB-2015 have demonstrated that the proposed PCF tracker outperforms most of the state-of-the-art trackers and achieves a high real-time tracking performance.

Active contour‐based clutter defiance scheme for correlation filters

The negative impact of clutters on correlation output still remains the problem not handled in correlation pattern recognition (CPR) paradigm. Some of the known impacts caused by the presence of clutters include pronounced side-lobe generation and reduction in height of correlation peak. The occurrence of the side-lobes results in the distortion of actual correlation output while making the class decision a difficult task. Whereas, reduction in correlation height may cause class decisions to go wrong. The authors propose a novel clutter defiance strategy based on object segmentation through active contours approach thus evading a negative effect on the correlation output. Instead of allowing clutters to participate in CPR-based classification decision they recommend blocking irrelevant details to avoid distortion in the correlation process. An appropriate tweaking in the optimal logarithmic maximum average correlation height filter design yields a performance gain up to 80% in the correlation peak to side-lobe ratio, thus making it well pronounced to classify the true class objects correctly. The improvement remains consistent throughout the range of in-plane angular distortions against synthetically cluttered challenging images.

In brief

PAGE 558 Two researchers from India have devised an oil-spill detection method using hybrid-pol data carried out through a reconstruction technique. The novel method tested on two different datasets demonstrated improved detection over competing state-of-the methods, utilising Oil Spill Index (OSI) as a new parameter. PAGE 525 The current correlation pattern recognition (CPR) paradigm does not account for the negative impact of clusters on correlation output. A team of researchers from Pakistan has proposed a clutter defiance strategy based on object segmentation through an active contour approach, with consistent improvement across a range of challenging distorted images. An annotated RGB decomposed AIRSAR image. PAGE 548 A team of researchers from China have developed a compact substrate integrated waveguide three-state diplexer which operates at three frequency bands by integrating three diplexers in three different states on a single circuit. A ‘+’ shaped slot etched onto the waveguide cavity further improves design flexibility and can be used to independently control the resonant frequencies. Added complexity cluttered test images. PAGE 540 In cloud systems, malicious users can initiate side channel attacks to steal private information through virtualisation. Researchers from India present a multi-objective load balancing framework to minimise attack likelihood by reducing the number of shared servers, with this approach drastically improving resource and power usage. TE102 mode current distribution in cavity. PAGE 508 A collaboration of researchers from France have designed and fabricated a split ring resonator antenna integrated in textiles by embroidery. The textile antenna exhibited a radiation pattern similar to that of a dipole antenna and evidenced three operating modes dependent on the individual resonance frequency of either the dipole or resonator. Chromosome encoding and mutation operation. Schematic and image views of embroidered antenna.

Robust long‐term correlation tracking with multiple models

To address the challenge of repetitive target appearance variation and frequent occlusion, existing visual tracking methods either handle corrupted samples or correct the appearance model. In this study, the authors propose a novel framework that successfully combines these two strategies. In their method, the base tracker is an improved discriminative correlation filter-based tracker, in which an independent classifier is employed to alleviate the problem of corrupted samples; the best model is selected for improvement from a group of models, which they call a ‘model colony’. The model colony is composed of models updated via different processes. The correlation output and the peak-to-sidelobe ratio are used to evaluate each model in the model colony. In addition, they propose a novel criterion called the maximum-to-others ratio for superior model selection. Experiments on 80 challenging sequences show that their tracker outperforms state-of-the-art trackers. In addition, experimental results demonstrate that their formulation significantly improves the performance of their base tracker.

EVALUATION NOISE IMMUNITY OF THE BINARY DIGITAL MODEM WITH SIGNALS TYPE NOISE USING THE CHARACTERISTIC FUNCTION METHOD

The issue of improving modems with noise signals implies increasing the accuracy of theoretical estimation of noise immunity of the proposed methods of demodulation of information components of signals. Important is the task of assessing the immunity of digital modems, enabling engineers to ascertain the prospect of system development at the design stage. The article investigates the noise immunity of a binary digital modem with phase manipulation of the noise signal and the autocorrelation algorithm of its reception, which uses as noise carrier Gaussian signals. The paper presents a technique for calculating the bit error rate (BER) in a demodulator, which is characterized by the fact that the functional for estimating the received information bit contains components with different laws of probability distribution. The presented methodology is based on a mathematical apparatus of characte­ristic functions, which allows determining the potential noise immunity of a digital modem, providing a reduction of the discrepancies between theoretical and experimental data for determining the BER. Summing up the whole research it is worth noting the following research results: 1 noise immunity analysis of digital binary modem of noise signals was performed using mathematical apparatus of characteristic functions at autocorrelation method of operation of Gaussian type noise signal demodulator in the presence of Gaussian additive interference; 2 an analytical expression was found to calculate the characteristic density function of the random variable distribution at the output of a binary digital correlator; 3 the ratio was obtained to determine the potential noise immunity of the demodulator. The results of the study showed that the application of this technique eli­minates significant differences between the results of the theoretical evaluation of the noise immunity of the demodulator and the results of its simulation.

Design of Enhanced Rotation Locked Loop for Roll Angle Estimation of Rotating Vehicle in a Weak GPS Signal Environment.

In order to estimate the roll angle of a rotating vehicle, an enhanced rotation locked loop (RLL) algorithm is proposed in this paper. The RLL algorithm estimates the roll angle by using the property that the power of the GPS signal measured at the receiver of a rotating vehicle changes periodically. However, in case the received GPS power is decreased, the performance of the conventional RLL algorithm degrades, or it cannot estimate the roll angle anymore, therefore, for operating the RLL algorithm in a weak signal environment, this paper designs a method to increase the signal-to-noise ratio (SNR) by overlapping multiple GPS signals’ correlator outputs and a method to compensate the decreased response of a rotation discriminator at low-signal strength. Through computer simulations, the performance of the proposed algorithm is verified and it is shown that the roll angle can be estimated stably even at a weak signal environment down to 29 dB–Hz of C/N0.

Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data

In this paper, the experimental data on the thermal conductivity of EG based hybrid nanofluid containing zinc oxide and titanium oxide have been used. At the first, three two-variable correlations have been proposed using curve-fitting on experimental data. After that, the best transfer function for training the artificial neural network has been selected. The input variables of neural network were temperature and solid volume fraction, while the output variable was the thermal conductivity enhancement of the nanofluid. Moreover, the correlation outputs, ANN results and experimental data have been compared. The results showed that there is a good agreement between experimental data and neural network results so that the resulting model of the neural network is able to predict the thermal conductivity enhancement of the nanofluid. The findings also indicated that the accuracy of the neural network is much greater than the curve fitting method to predict thermal conductivity enhancement of ZnO-TiO2/EG hybrid nanofluid.

Commutation Code Index DCSK Modulation Technique for High-Data-Rate Communication Systems

In this brief, a novel non-coherent modulation system called commutation code index differential chaos shift keying (CCI-DCSK) is presented. In the proposed scheme, the benefits of index modulation (IM) are exploited so that the system energy and spectral efficiencies are improved. We are putting forward a CCI-DCSK scheme in which the reference sequence along with its corresponding data bearing orthogonal version are sent within the same time slot to enhance spectral efficiency. Specifically, at the transmitter p additional bits are mapped into the index of the repetition commutation, which is performed on the reference signal for the sake of forming its orthogonal version. Furthermore, the modulated bit is spread by the corresponding commutated replica of the reference signal. The reference and orthogonal data bearing signals are then summed within the same time slot prior to transmission. At the receiver, the received signal is first correlated with all possible combinations of the commutated replicas in order to find the index of the correlator output with the maximum magnitude. Subsequently, the maximizing index is then used to estimate the mapped bits, while the output of the corresponding correlator is used to despread the modulated bit via a zero-threshold comparator. To complete the study, analytical expressions for the bit error rate are derived for both additive white Gaussian noise and multipath Rayleigh fading channels. Finally, performance results of the proposed CCI-DCSK scheme is compared with the state-of-the-art IM-based non-coherent chaotic modulations and is found to be superior and competitive.

Coupled-Region Visual Tracking Formulation Based on a Discriminative Correlation Filter Bank

The visual tracking algorithm based on discriminative correlation filter (DCF) has shown excellent performance in recent years, especially as the higher tracking speed meets the real-time requirement of object tracking. However, when the target is partially occluded, the traditional single discriminative correlation filter will not be able to effectively learn information reliability, resulting in tracker drift and even failure. To address this issue, this paper proposes a novel tracking-by-detection framework, which uses multiple discriminative correlation filters called discriminative correlation filter bank (DCFB), corresponding to different target sub-regions and global region patches to combine and optimize the final correlation output in the frequency domain. In tracking, the sub-region patches are zero-padded to the same size as the global target region, which can effectively avoid noise aliasing during correlation operation, thereby improving the robustness of the discriminative correlation filter. Considering that the sub-region target motion model is constrained by the global target region, adding the global region appearance model to our framework will completely preserve the intrinsic structure of the target, thus effectively utilizing the discriminative information of the visible sub-region to mitigate tracker drift when partial occlusion occurs. In addition, an adaptive scale estimation scheme is incorporated into our algorithm to make the tracker more robust against potential challenging attributes. The experimental results from the OTB-2015 and VOT-2015 datasets demonstrate that our method performs favorably compared with several state-of-the-art trackers.

A novel applicable experimental study on the thermal behavior of SWCNTs(60%)-MgO(40%)/EG hybrid nanofluid by focusing on the thermal conductivity

The aim of this study is to investigate the thermal conductivity of a hybrid nanofluid containing SWCNT-MgO particles dispersed in ethylene glycol as a base fluid. Experiments have executed on nanofluid with concentration of 0.015, 0.025, 0.05, 0.1, 0.2, 0.35, 0.45, and 0.55at temperatures between 25 and 50 °C. The results showed that the percentage of thermal conductivity increase with the volume fraction variation at higher temperatures is much more than at lower temperatures. It was reported that the thermal conductivity at the solid volume fraction of 0.55and temperature of 50 °C increases >35%. Moreover, the results revealed that using MgO nanoparticle can decrease the cost of producing the nanofluid. Since there is no model for evaluation of the thermal conductivity of hybrid nanofluid, a new correlation based on the experiments has been proposed. R-squared of the correlation outputs is 0.993428, which shows a good agreement of the proposed correlation with the experimental data and a high accuracy of the experimental correlation.

Speeding up DNA sequence alignment by optical correlator

In electronic computers, extensive amount of computations required for searching biological sequences in big databases leads to vast amount of energy consumption for electrical processing and cooling. On the other hand, optical processing is much faster than electrical counterpart, due to its parallel processing capability, at a fraction of energy consumption level and cost. In this regard, this paper proposes a correlation-based optical algorithm using metamaterial, taking advantages of optical parallel processing, to efficiently locate the edits as a means of DNA sequence comparison. Specifically, the proposed algorithm partitions the read DNA sequence into multiple overlapping intervals, referred to as windows, and then, extracts the peaks resulted from their cross-correlation with the reference sequence in parallel. Finally, to locate the edits, a simple algorithm utilizing number and location of the peaks is introduced to analyze the correlation outputs obtained from window-based DNA sequence comparison. As a novel implementation approach, we adopt multiple metamaterial-based optical correlators to optically implement the proposed parallel architecture, named as Window-based Optical Correlator (WOC). This wave-based computing architecture fully controls wave transmission and phase using dielectric and plasmonic materials. Design limitations and challenges of the proposed architecture are also discussed in details. The simulation results, comparing WOC with the well-known BLAST algorithm, demonstrate superior speed-up up to 60%, as well as, high accuracy even at the presence of large number of edits. Also, WOC method considerably reduces power consumption as a result of implementing metamaterial-based optical computing structure.

Modeling and prediction of rheological behavior of Al[formula omitted]O[formula omitted]-MWCNT/5W50 hybrid nano-lubricant by artificial neural network using experimental data

In this paper, the artificial neural network model and new correlation based on experimental data are proposed to predict Rheological behavior of Al2O3-MWCNT/5W50. The ANN model has three inputs including temperature, volume fraction and share rate. Predictions of suggested models were evaluated by using statistical and graphical validations approaches. The results revealed that the maximum values of margin of deviation are 0.07% and 7.3% for ANN and correlation outputs, respectively. The findings showed that an artificial neural network can predict the relative viscosity of the nanofluid more accurately than empirical correlation.

A Frequency-Domain SPICE Approach to High-Resolution Time Delay Estimation

We propose a frequency-domain sparse iterative covariance-based estimation (FD-SPICE) approach for the high-resolution time delay estimation of spread spectrum signals. The conventional correlation method fails to resolve the signals in the case where they are spaced within a Rayleigh resolution limit and further processing should be applied to the correlation outputs in order to improve performance. SPICE is one of the most prominent candidates for further processing since it has various advantages over subspace-based approaches. SPICE is implemented normally in the time domain like other sparse signal reconstruction-based approaches. However, the time-domain SPICE (TD-SPICE) approach suffers from a severe performance degradation in coherent signal cases, as in direction-of-arrival estimation. We develop an FD-SPICE approach which makes use of the Fourier transform bins of the correlation output samples to form a sample covariance matrix. Numerical examples demonstrate the superiority of FD-SPICE over TD-SPICE, especially in coherent signal cases.

Novel Anti-spoofing Methods Based on Discrete Wavelet Transform in the Acquisition and Tracking Stages of Civil GPS Receiver

The growing dependence of critical civil infrastructure on Global Positioning System (GPS) makes GPS interference not only a safety threat, but also a matter of national security. Spoofing could pose a major threat for GPS navigation systems, so the GPS users have to gain an in-depth understanding of GPS spoofing. Therefore, spoofing countermeasure is a significant subject of research these days. In this paper, we utilize wavelets transform (WT) as a tool that effectively hinders the adverse activities of these groups, and then introduce two novel methods to mitigate spoofing in the acquisition and tracking processes. In the first suggested algorithm, using WT in the acquisition process, we control satellite constellation to mitigate spoofing errors. After generating the in-phase and quadrature correlator output signals, called I and Q respectively, we apply the wavelet db3 to the Q samples to remove their noise components. In the second method, WT is used in a tracking loop. In this way, we apply sym4 to the Q arm, which results in spoofing reduction. We apply our new algorithms to both simulated and measurement data sets, to shed light on its performance. Results show that both methods successfully mitigate the spoofing effect on the tested data sets.

Permutation Index DCSK Modulation Technique for Secure Multiuser High-Data-Rate Communication Systems

A new noncoherent scheme called Permutation Index Differential Chaos Shift Keying (PI-DCSK) modulation is proposed in this paper. This original design aims to enhance data security, energy and spectral efficiencies, compared to its rivals. In the proposed PI-DCSK scheme, each data frame is divided into two time slots in which the reference chaotic signal is sent in the first time slot and a permuted replica of the reference signal multiplied by the modulating bit is sent in the second time slot. In particular, the bit stream is divided at the transmitter into blocks of $n+1$ bits, where $n$ mapped bits are used to select one of the predefined reference sequence permutations, while a single modulated bit is spread by the permuted reference signal just mentioned. At the receiver side, the reference signal is recovered first, then all permuted versions of it are correlated with the data-bearing signal. The index of the correlator output with maximum magnitude will estimate the mapped bits, while the output content of the corresponding correlator is compared to a zero threshold to recover the modulated bit. Moreover, a new multiple access method based on the proposed scheme is described and analysed. Analytical expressions for the error performance in single-user and multiuser environments are derived for additive white Gaussian noiseand multipath Rayleigh fading channels, respectively. Furthermore, the performance of the proposed PI-DCSK system is analysed and compared with other noncoherent chaotic modulation schemes and is found to be promising.

Development of a technique for the reconstruction and validation of gene network models based on gene expression profiles

We have developed a technique for the reconstruction and validation of models of gene networks based on the gene expression profiles derived in the course of DNA microchip experiments or by the method of RNA molecules sequencing. A structural block diagram is presented of a stepwise process for determining optimal parameters of the algorithm for reconstruction of a gene network that meet the optimum network topology. We proposed a comprehensive estimation criterion of a gene network topology based on the Harrington desirability function that contains network topological parameters as constituent components. The maximum value of this criterion corresponds to the optimal topology of a gene network. A technique for the validation of models of gene networks is based on a ROC analysis whose implementation implies a comparative analysis of the character of relations between relevant genes in the network on the basis of the totality of genes and gene networks based on the obtained biclusters. Qualitative reconstruction of a gene network makes it possible to explore the nature of interaction between genes that determine the process of functioning of a biological organism at different stages of development of complex genetic diseases for the purpose of early diagnosis and correction of a given process. It was established that the gene network reconstructed based on the correlation output algorithm is more efficient in comparison with the gene network based on the algorithm ARACNE. The weighted average of relative validation criterion for the derived models based on the correlation output algorithm is significantly greater than the corresponding value when applying the algorithm of ARACNE. This fact indicates a higher degree of compliance with the character of relations between respective genes in the network based on the totality of genes and in the networks based on gene expression profiles in the obtained biclusters. Qualitative reconstruction of a gene network makes it possible to explore the character of development of a biological organism at the gene level, which creates preconditions for early diagnosis and adjustment of the development of different types of genetic diseases.

Robust face recognition via non‐linear correlation filter bank

The author proposes a robust face recognition algorithm called non-linear correlation filter bank (NCFB). NCFB combines the benefits of a sigmoid function such as non-linearities of image pixels and correlation filters (CFs) to achieve better recognition performance. The sigmoid function is used in the spatial domain to extend the uniform dynamic range for enhancing the image contrast. Greyscale images are divided into non-overlapping regions. CFs are designed based on the unconstrained minimum average correlation energy corresponding to each sub-region of images to optimise the overall correlation outputs. NCFB not only takes the differences among face sub-regions into account but also effectively exploits the discriminative information in face sub-regions. The author shows that the proposed method is robust against illumination, pose, and facial expression variations. Experimental results obtained on labelled faces in the wild, Yale B, AR, and FERET face databases demonstrate that the recognition rate in the proposed method is improved compared with other CFs.

Performance Analysis of PN Code Acquisition with MIMO Scheme for an UWB TH/CDMA System

This paper presents performance and its simulation results of pseudonoise (PN) code acquisition scheme with MIMO scheme for an ultra‐wideband time‐hopping/code‐division‐multiple‐access (UWB TH/CDMA) system. The transmission channel is modelled as a frequency selective lognormal fading channel. In almost practical PN code acquisition system, the existence of more than two synchronous cells in the uncertainty region of the search process is possible due to multipath effect. Therefore, based on deriving the detection probability, false alarm rate, miss detection probability, and mean acquisition time, the acquisition performance is analyzed under the hypothesis of multiple synchronous states (cells) in the uncertainty region of the PN code. And the code acquisition performance is evaluated when the correlator outputs are noncoherently combined by using equal gain combining (EGC) scheme. In this procedure, the closed form for the conditional probability of decision variable is derived using the Gauss‐Hermite quadrature formula. The performance comparison of the scheme mentioned above shows that the code acquisition performance with the diversity combining technique, especially when increasing the number of antenna, is more robust than that using no diversity. And code acquisition performance comparison also shows that if the detection threshold is set inappropriately, the performance might be degraded, even if an antenna diversity method is applied. It is also shown that Tx diversity can improve the acquisition performance but not as much as Rx diversity does. And Rx diversity can be applied to the acquisition system for additional diversity gain if the complexity of the receiver can be accepted.