Matrix Array Research Articles

Content‐based image retrieval using Gaussian–Hermite moments and firefly and grey wolf optimization

Rapid growth in the transfer of multimedia information over the Internet requires algorithms to retrieve a queried image from large image database repositories. The proposed content-based image retrieval (CBIR) uses Gaussian–Hermite moments as the low-level features. Later these features are compressed with principal component analysis. The compressed feature set is multiplied with the weight matrix array, which has the same size as the feature vector. Hybrid firefly and grey wolf optimization (FAGWO) is used to prevent the premature convergence of optimization in the firefly algorithm. The retrieval of images in CBIR is carried out in an OpenCV python environment with K-nearest neighbours and random forest algorithm classifiers. The fitness function for FAGWO is the accuracy of the classifier. The FAGWO algorithm derives the optimum weights from a randomly generated initial population. When these optimized weights are applied, the proposed algorithm shows better precision/recall and efficiency than other techniques such as exact legendre moments, Region-based image retrieval, K-means clustering ​and Color descriptor wavelet-based texture descriptor retrieval technique. In terms of optimization, hybrid FAGWO outperformed various optimization techniques (when used alone) like Particle Swarm Optmization, Genetic Algorithm, Grey-Wolf Optimization and FireFly algorithm.

A Dual-Mode 2D Matrix Array for Ultrasound Image-Guided Noninvasive Therapy.

Focused ultrasound (FUS) lacks reliable real-time image guidance, which hinders the development of non-invasive ultrasound treatment in many important clinical applications. A dual-mode ultrasound array, capable of both imaging and therapy offers a new and reliable strategy for image-guided ultrasound therapy applications. The strategy has the advantages of real-time use, low cost, portability and inherent registration between imaging and therapeutic coordinate systems. In this work, a dual-mode two-dimensional (2D) matrix array with 1 MHz center frequency and 256 elements for ultrasound image-guided non-invasive therapy is reported. The array can provide three-dimensional (3D) volumetric ultrasound imaging and 3D focus control. Ultrasound imaging and therapeutic applications for the brain of small animals demonstrated the multi-functional capability of the dual-mode 2D matrix array. A method of rat brain positioning based on ultrasound imaging was proposed and verified. Transcranial ultrasound image-guided blood-brain barrier (BBB) opening of multiple-targets was achieved in vivo, using the proposed dual-mode 2D array. The obtained results indicate that the dual-mode 2D matrix array is a promising method for practical use in ultrasound image-guided non-invasive therapy applications.

Connecting Networks for Two-Dimensional Butler Matrices Generating a Triangular Lattice of Beams

Connecting networks for two-dimensional beamforming matrices are discussed. They provide a suitable interconnection between the output ports of a Butler matrix and antenna array ports, transforming a square (and more generally, rectangular) lattice of beams into a triangular lattice of beams. This change in lattice improves the crossover between beams, reducing gain roll-off over the field of view for a given multiple fixed beam coverage. A general description of the concept is provided and numerical results are reported, which confirm a reduction in crossover level between 1 and 1.5 dB. The proposed solution is further validated through the design and test of a 4 × 4 open-ended waveguide array in K-band. The connecting network has a length of 70 mm, compared to 226 mm for the 2D Butler matrix, with a design frequency of 19.55 GHz. Good agreement is found between simulated and measured data. The desired triangular lattice of beams is confirmed with the measured multiple beams. This solution is of interest for multiple-beam millimeter-wave communication systems, considered for next generation of terrestrial and non-terrestrial networks.

A 1.5-D Array for Acoustic Radiation Force (ARF)-Induced Peak Displacement-Based Tissue Anisotropy Assessment With a Row-Column Excitation Method.

Many biological tissues, including muscle or kidney, are mechanically anisotropic, and the degree of anisotropy (DoA) in mechanical properties is diagnostically relevant. DoA can be assessed either using the ratio of shear wave velocities (SWVs) or acoustic radio forced impulse (ARFI)-induced peak displacements (PD) measured longitudinal over transverse orientations. Whether using SWV or PD as a basis, DoA expressed as the ratio of values requires 90° transducer rotation when a linear array is employed. This large rotation angle is prone to misalignment errors. One solution is the use of a fully sampled matrix array for electronic rotation of point spread function (PSF). However, the challenges of matrix array are its high fabrication cost and complicated fabrication procedures. The cheaper and simpler alternative of matrix array is the use of a row-column array. A 3×64 elements 1.5-D array with a row-column excitation mode is proposed to assess DoA in mechanical properties using the PD ratio. Different numbers of elements in elevational and lateral directions were selected to have orthogonal ARFI excitation beams without rotating the transducer. A custom-designed flex circuit was used to fabricate the array with a simpler electrode connection than a fully sampled matrix array. The performance of the array was evaluated in Field II simulation and experiment. The output pressure was 0.57-MPa output under a 40- [Formula: see text] excitation with a -6-dB point spread dimension of 14×4 mm2 in orthogonal directions. The PD was measured to be [Formula: see text] in an isotropic elastic phantom with Young's modulus of 5.4 kPa. These results suggest that the array is capable of assessing DoA using PD ratio without physical rotation of the transducer. The array has the potential to reduce the misalignment errors for DoA assessment.

A Novel Pseudonym Assignment and Encryption Scheme for Preserving the Privacy of Military Vehicles

In this digital era, security has become one of the important topics of concern, and things become more critical for military vehicles where safety plays a vital role. In this paper, we have discussed a pseudonym-based approach that preserves the real identity of military vehicles. This paper also focuses on military vehicles’ location privacy by deploying a novel pseudonym assignment and encryption schemes. The proposed security scheme is based on a hybrid approach of matrix array symmetric key and the intelligent water drop scheme. After implementing the proposed security scheme, each military vehicle will obtain its pseudonym for hiding their original identities. The proposed algorithm effectively manages pseudonym generation and change requests for the local region and inter-region environment. The proposed security scheme not only provides secure communication and preservation of location privacy of military vehicles but also ensures their security against various attacks. Finally, the time efficiency of proposed algorithms is obtained for both local and inter-region requests. Comparative analysis shows that the proposed scheme is more efficient than other existing techniques.

GPU-Based Simulation of Echocardiography Volumes Using Quantitative Fiber-Angle-to-Backscatter Measurements.

The intensity of backscattered ultrasound signal from heart muscle is known to be related to the angle between cardiac fibers and the insonification direction. In this work, a GPU-based method of simulating three-dimensional (3D) echocardiographic images from an empirically derived angle-to-backscatter relationship is developed and validated. Images of a rotating fiber phantom are simulated, and it is validated that the angle-to-backscatter relationship is accurately reflected by the simulated envelope data. In a second experiment, echocardiography images are simulated from a diffusion tensor magnetic resonance imaging (DT-MRI) volume of a canine heart to demonstrate that the method produces view-dependent speckle. 3D volumes of a parametrically generated ideal left ventricle phantom are also simulated and processed into fiber orientation maps using the underlying quantitative parameters. Images are simulated based on the characteristics of a 35-by-32 two-dimensional (2D) matrix array probe and a clinical one-dimensional (1D) phased array probe. The processed fiber volumes exhibit good agreement with the virtual phantom's ground truth, having an average acute angle error (AAE) of less than 10 degrees for both probes. The simulation method is fast and opens a new approach for ultrasound fiber imaging.

Flash Scanning Volumetric Optoacoustic Tomography for High Resolution Whole‐Body Tracking of Nanoagent Kinetics and Biodistribution

AbstractTracking of biodynamics across entire living organisms is essential for understanding complex biology and disease progression. The presently available small‐animal functional and molecular imaging modalities remain constrained by factors including long image acquisition times, low spatial resolution, limited penetration or poor contrast. Here flash scanning volumetric optoacoustic tomography (fSVOT), a new approach for high‐speed imaging of fast kinetics and biodistribution of optical contrast agents in whole mice that simultaneously provides reference images of vascular and organ anatomy with unrivaled fidelity and contrast, is presented. The imaging protocol employs continuous overfly scanning of a spherical matrix array transducer, accomplishing a 200 µm resolution 3D scan of the whole mouse body within 45 s without relying on signal averaging. This corresponds to an imaging speed gain of more than an order of magnitude compared with existing state‐of‐the‐art implementations of comparable resolution performance. Volumetric tracking and quantification of gold nanoagent and near infrared (NIR)‐II dye kinetics and their differential uptake in various organs are demonstrated. fSVOT thus offers unprecedented capabilities for multiscale imaging of pharmacokinetics and biodistribution with high contrast, resolution, and speed.

Three-Dimensional Multi-Frequency Shear Wave Absolute Vibro-Elastography (3D S-WAVE) With a Matrix Array Transducer: Implementation and Preliminary In Vivo Study of the Liver.

Magnetic resonance elastography (MRE) is commonly regarded as the imaging-based gold-standard for liver fibrosis staging, comparable to biopsy. While ultrasound-based elastography methods for liver fibrosis staging have been developed, they are confined to a 1D or a 2D region of interest and to a limited depth. 3D Shear Wave Absolute Vibro-Elastography (S-WAVE) is a steady-state, external excitation, volumetric elastography technique that is similar to MRE, but has the additional advantage of multi-frequency excitation. We present a novel ultrasound matrix array implementation of S-WAVE that takes advantage of 3D imaging. We use a matrix array transducer to sample axial multi-frequency steady-state tissue motion over a volume, using a Color Power Angiography sequence. Tissue motion with the frequency components {40,50,60} and {45,55,65} Hz are acquired over a (90° lateral) × (40° elevational) × (16 cm depth) sector with an acquisition time of 12 seconds. We compute the elasticity map in 3D using local spatial frequency estimation. We characterize this new approach in tissue phantoms against measurements obtained with transient elastography and MRE. Six healthy volunteers and eight patients with chronic liver disease were imaged. Their MRE and S-WAVE volumes were aligned using T1 to B-mode registration for direct comparison in common regions of interest. S-WAVE and MRE results are correlated with R2 = 0.92, while MRE and TE results are correlated with R2 = 0.71. Our findings show that S-WAVE with matrix array has the potential to deliver a similar assessment of liver fibrosis as MRE in a more accessible, inexpensive way, to a broader set of patients.

Run-off election-based decision method for the training and inference process in an artificial neural network

Generally, the decision rule for classifying unstructured data in an artificial neural network system depends on the sequence results of an activation function determined by vector–matrix multiplication between the input bias signal and the analog synaptic weight quantity of each node in a matrix array. Although a sequence-based decision rule can efficiently extract a common feature in a large data set in a short time, it can occasionally fail to classify similar species because it does not intrinsically consider other quantitative configurations of the activation function that affect the synaptic weight update. In this work, we implemented a simple run-off election-based decision rule via an additional filter evaluation to mitigate the confusion from proximity of output activation functions, enabling the improved training and inference performance of artificial neural network system. Using the filter evaluation selected via the difference among common features of classified images, the recognition accuracy achieved for three types of shoe image data sets reached ~ 82.03%, outperforming the maximum accuracy of ~ 79.23% obtained via the sequence-based decision rule in a fully connected single layer network. This training algorithm with an independent filter can precisely supply the output class in the decision step of the fully connected network.

High-Contrast and -Resolution 3-D Ultrasonography with a Clinical Linear Transducer Array Scanned in a Rotate-Translate Geometry

We proposed a novel solution for volumetric ultrasound imaging using single-side access 3-D synthetic aperture scanning of a clinical linear array. This solution is based on an advanced scanning geometry and a software-based ultrasound platform. The rotate-translate scanning scheme increases the elevation angular aperture by pivoting the array (−45° to 45°) around its array axis (axis along the row of its elements) and then scans the imaged object for each pivoted angle by translating the array perpendicularly to the rotation axis. A theoretical basis is presented so that the angular and translational scan sampling periods can be best adjusted for any linear transducer array. We experimentally implemented scanning with a 5-MHz array. In vitro characterization was performed with phantoms designed to test resolution and contrast. Spatial resolution assessed based on the full-width half-maximum of images from isolated microspheres was increased by a factor of 3 along the translational direction from a simple translation scan of the array. Moreover, the resolution was uniform over a cross-sectional area of 4.5 cm2. Angular sampling periods were optimized and tapered to decrease the scan duration while maintaining image contrast (contrast at the center of a 5-mm cyst on the order of −26 dB for 4° angular period and a scan duration of 10 s for a 9-cm3 volume). We demonstrated that superior 3-D ultrasound imaging can be obtained with a clinical array using our scanning strategy. This technique offers a promising and flexible alternative to development of costly matrix arrays toward the development of sensitive volumetric ultrasonography.

Improving Autoencoder Training with novel Goal Functions based on Multivariable Control Concepts

Abstract Autoencoders are becoming more representative in all fields of knowledge, due to their ability to classify, compress, and identify data patterns. This study objective was to propose entirely new objective functions using multivariable process control concepts as the gain matrix and Relative Gain Array to improve the quality of prediction and classification of an autoencoder. The advantages of the proposed approach are illustrated through a pulp-and-paper industry. The new function results show an improvement in the detection, leading to savings of up to 22 to 38 thousand dollars per month compared to a model using only MSE.

Enhancement of Noisy Reverberant Speech Using Polynomial Matrix Eigenvalue Decomposition

Speech enhancement is important for applications such as telecommunications, hearing aids, automatic speech recognition and voice-controlled systems. Enhancement algorithms aim to reduce interfering noise and reverberation while minimizing any speech distortion. In this work for speech enhancement, we propose to use polynomial matrices to model the spatial, spectral and temporal correlations between the speech signals received by a microphone array and polynomial matrix eigenvalue decomposition (PEVD) to decorrelate in space, time and frequency simultaneously. We then propose a blind and unsupervised PEVD-based speech enhancement algorithm. Simulations and informal listening examples involving diverse reverberant and noisy environments have shown that our method can jointly suppress noise and reverberation, thereby achieving speech enhancement without introducing processing artefacts into the enhanced signal.

Self-Navigated 3D Acoustic Tweezers in Complex Media Based on Time Reversal.

Acoustic tweezers have great application prospects because they allow noncontact and noninvasive manipulation of microparticles in a wide range of media. However, the nontransparency and heterogeneity of media in practical applications complicate particle trapping and manipulation. In this study, we designed a 1.04 MHz 256-element 2D matrix array for 3D acoustic tweezers to guide and monitor the entire process using real-time 3D ultrasonic images, thereby enabling acoustic manipulation in nontransparent media. Furthermore, we successfully performed dynamic 3D manipulations on multiple microparticles using multifoci and vortex traps. We achieved 3D particle manipulation in heterogeneous media (through resin baffle and ex vivo macaque and human skulls) by introducing a method based on the time reversal principle to correct the phase and amplitude distortions of the acoustic waves. Our results suggest cutting-edge applications of acoustic tweezers such as acoustical drug delivery, controlled micromachine transfer, and precise treatment.

Process parameters optimization in machining of duplex 2205 stainless steel alloy using AWJM technique

The AWJM process is highly used for the machining of very difficult to cut tough materials. In this study a novel attempt was made to find the influence of various process parameters of AWJM process over the machining of duplex 2205 stainless steel alloy. The process parameters considered in this study are transverse speed, abrasive flow rate and stand- off distance. The work is mainly concentrated to obtain reduced angle of kerf taper and minimum surface roughness. The taguchi L9 orthogonal array matrix was used to optimize the responses recorded after the machining. ANOVA table is used to verify the influence of each parameter on the machining of duplex 2205 alloy. The results showed that the stand –off distance is the major influencing parameter which is followed by transverse speed and abrasive flow rate.

Multicomponent column optimization of ternary adsorption based removal of phenolic compounds using modified activated carbon

The removal of phenol (P), 4-chlorophenol (CP), 4-nitrophenol (NP), catechol (C), resorcinol (R) and hydroquinone (HQ) from P-CP-NP and C-R-HQ ternary systems, via multicomponent column adsorption on modified activated carbon (MAC), was evaluated in this study to determine the characteristic parameters of the column for ternary systems. A Taguchi L9 orthogonal array matrix was applied to investigate the effect of process parameters such as flow rate (Q), bed height (Z) and column diameter (D) on the breakthrough point of the process. The BET surface area of MAC was found to be 1245 m2/g. Higher flow rate, and lower bed height and diameter resulted in faster breakthrough. Statistical analysis of the data revealed that column diameter was the most significant factor (p < 0.05) for simultaneous adsorbate removal from ternary systems. Elution of phenol, 4-chlorophenol and 4-nitrophenol or elution of catechol, resorcinol and hydroquinone from their respective ternary mixtures showed that the thermal desorption may be a better option over that of solvent desorption. MAC worked well for at least seven adsorption-desorption cycles, with the continuous decrease in adsorption efficiency after each them desorption/regeneration. Owing to its heating value, spent-MAC can be used as co-fuel in the boiler-furnace.

Developing a Photoacoustic Whole-Breast Imaging System Based on the Synthetic Matrix Array

In this study, we reported a photoacoustic (PA) imaging system for whole-breast imaging. Similar to the traditional X-ray mammography, this system slightly compressed the breast by a water tank. The PA signal is acquired via scanning a long unfocused ultrasonic linear array probe over the breast top surface, and the expanded high-energy laser pulses illuminate the breast bottom through a transparent supporting plate. Scanning the unfocused transducer probe is equivalent to a synthetic two-dimensional (2D) matrix array, which significantly increased the field of view (FOV) via a much easier way and at a much lower cost. Our phantom results demonstrated that this system has a great potential for clinical implementation.

Implementation of an AFDX Interface with Zynq SoC Board in FPGA

This work is based on the Hardware development of the Transmission part for the communication inside the satellite. Our goal is move as much as possible of the software part into the Field-programmable gate array (FPGA) matrix due to the single event upsets (SEU). This project is part of the collaborative project called “Mission: NET@SPACE”. It was chosen by the European Commission under the Seventh Framework Program for Research (FP7) to develop an Avionics Full Duplex Switched Ethernet (AFDX) demonstrator based in FPGA. It has to be able to receive and transmit frames and enhance the robustness. The scheduling of the protocol should also be moved into the hardware, by still keeping a small footprint of the whole design. In this paper, we introduce the theory and used technologies, the project flow and development, including the decisions and milestones, to arrive at the end to the further possibilities and conclusions.

Relating starter cultures to volatile profile and potential markers in green Spanish-style table olives by compositional data analysis

This work relates native lactic acid bacteria (LAB) (Lactobacillus pentosus LPG1, L. pentosus Lp13, and Lactobacillus plantarum Lpl15) and yeast (Wickerhamomyces anomalus Y12) starters to the volatile components (VOCs) produced in green Spanish-style table olives. For this aim, the VOC profile was considered as compositional data (CoDa). The CoDa analysis generated new information on the relationship among inocula and VOCs through the tetrahedral plot, CoDa-biplot, variation array matrix, and CoDa dendrogram. The ilr (which includes pivot) coordinates (Euclidean space) from VOCs produced more reliable starters’ clustering than the original data. The potential VOC markers, identified by a test based on the pairwise comparison of the logratio variation arrays from the whole data set and the individual groups, were (starters in the parenthesis): 2-phenylethyl acetate (LPG1, Y12, Y12 + LAB), methanol (Lpl15), cis-2-penten-1-ol (LPG1, Y12, Y12 + LAB), 2-methyl-3-hexanol (LPG1, Y12), U (non-identified) C (m/z 83-112-97) (Y12) and UF (m/z 95-154-110) (LPG1, Y12 + LAB). Besides, some VOCs were partial/totally inhibited by specific starters: 2-methyl-1-propanol (Lp13, Y12 + LAB), 2-phenyl ethanol (Lp13), furfuryl methyl ether (Y12 + LAB), purpurocatechol (Y12, Y12 + LAB), 4-ethyl guaiacol (Lp13, Lpl15), 4-ethyl phenol (Lpl15), 5-tert-butylpyrogallol (Lp13, Lpl15), and UE (m/z 111–198) (Lp13). A better understanding of the relationship between starters and their VOC may facilitate modelling the flavour and quality of Spanish-style green table olive fermentations.

Analysis of three-dimensional echo decorrelation and integrated backscatter imaging during ex vivo radiofrequency ablation

Radiofrequency ablation experiments were performed in ex vivo bovine liver (N = 14) using a clinical ablation system (RITA 1500X generator and StarBurst probe, Angiodynamics). Three-dimensional (3-D) ultrasound images were acquired as complex beamformed echo volumes from a Siemens Acuson SC2000 scanner with a 4Z1c matrix array. Echo decorrelation images, depicting echo changes between sequential volumes (interframe time 18 ms), and integrated backscatter (IBS) images, depicting local changes in echogenicity relative to baseline, were computed in 3-D at 11 s intervals throughout each treatment. To assess potential for real-time prediction of tissue ablation, cumulative 3-D echo decorrelation and integrated backscatter images were compared to reconstructed ablation zones, segmented from optically scanned tissue sections. Both echo decorrelation and IBS provided good prediction of local ablation using receiver operator characteristic (ROC) curve analysis (area under curve 0.91 for echo decorrelation normalized to global echo energy; &amp;gt;0.85 for all parameters), with accuracy depending weakly on correlation window size. While ablation regions were predicted fairly well (Dice coefficients &amp;gt;0.6), ablation zone volume was not consistently predicted by thresholded parameter maps. Both echo decorrelation and IBS showed weak but statistically significant correlation with simultaneous, co-located tissue temperatures measured by four thermocouples on the RF probe.

Real-time control of radiofrequency ablation by three-dimensional echo decorrelation imaging

Feasibility for real-time control of radiofrequency ablation (RFA) by three-dimensional (3-D) echo decorrelation imaging, with potential application to liver cancer treatment, is investigated. Ex vivo bovine liver is treated using a clinical RFA system (RITA 1500X generator with StarBurst probe, Angiodynamics). During ablation, pairs of echo volumes from a Siemens SC2000 scanner with a 4Z1c matrix array probe (inter-frame time 18 ms) are recorded as in-phase and quadrature (IQ) data. 3-D echo decorrelation maps are computed from these volume pairs every 11 s. Cumulative echo decorrelation, defined as the temporal maximum decorrelation for each voxel, is spatially averaged within a spherical region of interest (ROI) centered at the RF needle tip. Once the spatially averaged cumulative decorrelation within the spherical ROI exceeds a predefined threshold, ablation is halted by communication with the RF generator via a pneumatic switch connected to a microcontroller circuit. The control threshold and ROI were determined by empirically evaluating predictive performance of decorrelation in preliminary uncontrolled ablation trials. Controlled and uncontrolled ablation are compared based on correspondence of sectioned tissue histology to targeted ablation zones, receiver operating characteristic curve analysis of local ablation prediction by echo decorrelation, treatment duration, and ablation rate.