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At the intersection of technological evolution and escalating computational demand, the role of optics is reemerging as a transformative force in the field of computing. This article examines the evolving landscape surrounding optical advantages in computing, focusing on current trends and prospects. Optical computing finds applications across various domains, such as parallel processing, high-speed signal processing, energy efficiency, quantum computing, machine learning, secure communication, and signal/image processing. This review synthesizes insights from scholarly articles, peer-reviewed journals, and academic papers to analyze the potential and challenges of leveraging optics for computational tasks. The literature review also critically examines the challenges of adopting optical computing solutions. The recommended multidimensional approach to overcoming adoption challenges involves holistically addressing integration challenges, manufacturing complexities, and infrastructure needs where collaboration will catapult optical computing into an era of computational power. Through a multidimensional exploration, this article provides a comprehensive understanding of the opportunities and challenges in harnessing optical advantages in computing, positioning optical computing as a revolutionary force with far-reaching consequences. Consequently, this review offers insight and guides researchers, industry professionals, and policymakers toward a computational future that maximizes the advantages of optical computing in specific and pivotal application areas, transcending existing boundaries. [ABSTRACT FROM AUTHOR]

We extensively survey applications of Clifford Geometric algebra in recent years (mainly 2019–2022). This includes engineering; electric engineering; optical fibers; geographic information systems; geometry; molecular geometry; protein structure; neural networks; artificial intelligence; encryption; physics; signal, image, and video processing; and software. [ABSTRACT FROM AUTHOR]

This study presents a process for the quantitative investigation of thinning defects occurring in the containment liner plate (CLP) of a nuclear power plant according to various depths with a combined thermal wave signal and image processing in a lock-in thermography (LIT) technique. For that, a plate sample with a size of 300 × 300 mm was produced considering the 6 mm thickness applied to an actual CLP. The sample was designed with nine thinning defects on the back side with defect sizes of 40 × 40 mm and varying thinning rates from 10% to 90%. LIT experiments were conducted under various modulation frequency conditions, and phase angle data was calculated and evaluated through four-point method processing. The calculated phase angle was correlated with the defect depth. Then, the phase image was binarized by the Otsu algorithm to evaluate defect detection ability and shape. Furthermore, the accuracy of defect depth assessment was evaluated through third-order polynomial curve fitting. The detectability was analyzed by comparing the number of pixels of the thinning defect in the binarized image and the theoretical calculation. Finally, it was concluded that LIT can be applied for fast thinning defect detection and accurate thinning depth evaluation. [ABSTRACT FROM AUTHOR]

This study presents a process for the quantitative investigation of thinning defects occurring in the containment liner plate (CLP) of a nuclear power plant according to various depths with a combined thermal wave signal and image processing in a lock-in thermography (LIT) technique. For that, a plate sample with a size of 300 × 300 mm was produced considering the 6 mm thickness applied to an actual CLP. The sample was designed with nine thinning defects on the back side with defect sizes of 40 × 40 mm and varying thinning rates from 10% to 90%. LIT experiments were conducted under various modulation frequency conditions, and phase angle data was calculated and evaluated through four-point method processing. The calculated phase angle was correlated with the defect depth. Then, the phase image was binarized by the Otsu algorithm to evaluate defect detection ability and shape. Furthermore, the accuracy of defect depth assessment was evaluated through third-order polynomial curve fitting. The detectability was analyzed by comparing the number of pixels of the thinning defect in the binarized image and the theoretical calculation. Finally, it was concluded that LIT can be applied for fast thinning defect detection and accurate thinning depth evaluation.

Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community‐driven conservation solutions.Here, we present NABat ML, an automated machine‐learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet‐based computing resources ('cloud environment'), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future 'unseen' data. We evaluated model performance using a comprehensive, independent, holdout dataset.NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted‐average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud‐environment computing instance, the entire model training process took <16 h.Synthesis and applications. Our convolutional neural network (CNN)‐based model, NABat ML, classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species‐level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open‐source and reproducible, enabling future implementations as software on end‐user devices and cloud‐based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big‐data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad‐scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species. [ABSTRACT FROM AUTHOR]

The new applications of Clifford's geometric algebra surveyed in this paper include kinematics and robotics, computer graphics and animation, neural networks and pattern recognition, signal and image processing, applications of versors and orthogonal transformations, spinors and matrices, applied geometric calculus, physics, geometric algebra software and implementations, applications to discrete mathematics and topology, geometry and geographic information systems, encryption, and the representation of higher order curves and surfaces. [ABSTRACT FROM AUTHOR]

The utility sector has been employing ultrasonic-based nondestructive evaluation (NDE) to determine the cross-sectional groundline integrity of wooden utility poles. While it is far less invasive than other methods, its efficacy has not been thoroughly studied. This study aims to fill this technical gap by analyzing the correlation between the propagational characteristics of the ultrasonic stress wave using a novel embedded waveguide technique and the existing destructive testing methods. The proposed embedded waveguide technique excites diffusive Rayleigh mode (AW2) propagating in the shell region of the cross-sectional plane. This discovery allows a direct examination of the shell region condition through stress wave analysis. By employing the Gabor wavelet transformation and the model-based arrival region identification, this proposed technique extracts the propagation velocity and the associated spectral response of AW2. This study uses the static break assessment per ASTM 1036 Standard Test Methods And The longitudinal compression test per ASTM D143–14 “secondary method” to quantify the cross-sectional strength of the test specimen. This work performs a comprehensive correlation analysis between the extracted AW2 features and the associated destructive test. An overall correlation ${R}^{2}$ from 0.2 to 0.5 is achieved between the AW2 features and the static break test results. An overall correlation of ${R}^{2}$ of 0.4 is achieved for 30–35 ft poles in the longitudinal compression test. [ABSTRACT FROM AUTHOR]

Unbalanced optimal mass transport (OMT) seeks to remove the conservation of mass constraint by adding a source term to the standard continuity equation in the Benamou-Brenier formulation of OMT. In this study, we show how the unbalanced case fits into the vector-valued OMT framework simply by adding an auxiliary source layer and taking the flow between the source layer and the original layer(s) as the source term. This allows for unbalanced models both in the scalar and vector-valued density settings. The results are demonstrated on a number of synthetic and real vector-valued data sets.

Empirical wavelets transform (EWT) is a fully adaptive signal-analysis approach, which is similar to the empirical mode decomposition (EMD) but has a consolidated mathematical theory, and is appealing in designing automatic algorithm for a variety of signal processing tasks. EWT first estimates the frequency components presented in the given signal, then, computes the boundaries and extracts the oscillatory components based on the computed boundaries. Because of the excellent performance of the EWT in decomposing the nonlinear and non-stationary signals, it has been successfully applied into a number of problems. The last six years have seen the development of EWT. This paper presents a general overview of the recent advancements made in research on the EWT algorithm and its state-of-the-art applications in a wide range of areas, such as machine fault diagnosis, seismic data analysis, image processing, power system monitoring, and medical disease diagnosis, which aims at providing some comprehensive references for reader concerning with EWT. We place emphasis on the applications of using such signal-analysis algorithm throughout with illustrative examples. Finally, the potential avenues for the future trends and directions associated with EWT are discussed.

Shortness of breath is a major reason that patients present to the emergency department (ED) and point-of-care ultrasound (POCUS) has been shown to aid in diagnosis, particularly through evaluation for artifacts known as B-lines. B-line identification and quantification can be a challenging skill for novice ultrasound users, and experienced users could benefit from a more objective measure of quantification. We sought to develop and test a deep learning (DL) algorithm to quantify the assessment of B-lines in lung ultrasound. We utilized ultrasound clips (${n} =400$) from an existing database of ED patients to provide training and test sets to develop and test the DL algorithm based on deep convolutional neural networks. Interpretations of the images by algorithm were compared to expert human interpretations on binary and severity (a scale of 0–4) classifications. Our model yielded a sensitivity of 93% (95% confidence interval (CI) 81%–98%) and a specificity of 96% (95% CI 84%–99%) for the presence or absence of B-lines compared to expert read, with a kappa of 0.88 (95% CI 0.79–0.97). Model to expert agreement for severity classification yielded a weighted kappa of 0.65 (95% CI 0.56–074). Overall, the DL algorithm performed well and could be integrated into an ultrasound system in order to help diagnose and track B-line severity. The algorithm is better at distinguishing the presence from the absence of B-lines but can also be successfully used to distinguish between B-line severity. Such methods could decrease variability and provide a standardized method for improved diagnosis and outcome. [ABSTRACT FROM AUTHOR]

Modified Gram–Schmidt (MGS) algorithm is one of the most-known forms of QR decomposition (QRD) algorithms. It has been used in many signal and image processing applications to solve least square problem and linear equations or to invert matrices. However, QRD is well-thought-out as a computationally expensive technique, and its sequential implementation fails to meet the requirements of many real-time applications. In this paper, we suggest a new parallel version of MGS algorithm that uses VLIW (Very Long Instruction Word) resources in an efficient way to get more performance. The presented parallel MGS is based on compact VLIW kernels that have been designed for each algorithm step taking into account architectural and algorithmic constraints. Based on instruction scheduling and software pipelining techniques, the proposed kernels exploit efficiently data, instruction and loop levels parallelism. Additionally, cache memory properties were used efficiently to enhance parallel memory access and to avoid cache misses. The robustness, accuracy and rapidity of the introduced parallel MGS implementation on VLIW enhance significantly the performance of systems under severe rea-time and low power constraints. Experimental results show great improvements over the optimized vendor QRD implementation and the state of art. [ABSTRACT FROM AUTHOR]

• Development of a high temporal resolution tool to characterize fluid distribution. • Modelling of fluid characteristics using electric and flow phenomena. • Techniques of shadowgraphy and conductometry used for processing experimental data. • Investigation of fluid features under Taylor flow regime. In the field of structured reactors applied to multiphase reactions, the apparatus performance is related to the quality of the spatial distribution of fluids at the reactor inlet. This holds particularly true for monolith-type reactors since no flow redistribution is possible downstream in between the different parallel channels. In order to characterize the gas-liquid flows and their distribution in all the channels, a resistive sensor consisting in a printed circuit board with several annular electrodes has been developed, which can be scanned with high temporal resolution, of up to 20,000 Hz. This technique allows investigating flow features, such as gas holdup, bubble velocity, and bubble frequency, which are assessed in this work by shadowgraphy for a 12-channel monolith fed by air and water. Several treatment methods are evaluated, allowing the flow characteristics to be indirectly measured for Taylor flow regime conditions, with an accuracy of ±10% for bubble frequency and of ±20% for gas holdup and bubble velocity, with respect to the shadowgraphy. Thus, the innovative sensor can be used for industrial applications in order to distinguish the performance of gas-liquid distributors to provide uniform flow in multi-channel structured reactors. [Display omitted] [ABSTRACT FROM AUTHOR]

This study aimed to identify instant intima-media thickness changes (ΔIMT) in the common carotid artery (CCA) during cardiac cycle in order to assess atherosclerosis progression. Using a computerized semi-automated method, instant IMT changes were extracted in the two walls of the left CCA (240 consecutive patients) using B-mode ultrasound images. We found that CCA ΔIMT increased from 8 ± 4% of IMTmax in the controls to 15 ± 6% of IMTmax in the severe stenosis group. According to the multiple ordinal regression analysis, ΔIMT was associated with the severity of carotid artery stenosis (odds ratio [OR], 4.95; p < 0.001), independent of sex (OR, 1.11; p = 0.04), age (OR, 1.14; p < 0.001), body mass index; OR, 1.13; p = 0.036), hypertension (OR, 2.04; p < 0.001), diabetes (OR, 1.38; p = 0.045) and hyperlipidemia (OR, 1.54; p = 0.002). We concluded that increment of CCA ΔIMT during the cardiac cycle was strongly and independently associated with severity of carotid artery stenosis or atherosclerosis progression. [ABSTRACT FROM AUTHOR]

Augmented reality has a wide range of applications in many areas that can extend the study of real objects into the digital world, including stomatology. Real dental objects that were previously examined using their plaster casts are often replaced by their digital models or three-dimensional (3D) prints in the cyber-physical world. This paper reviews a selection of digital methods that have been applied in dentistry, including the use of intra-oral scanning technology for data acquisition and evaluation of fundamental features of dental arches. The methodology includes the use of digital filters and morphological operations for spatial objects analysis, their registration, and evaluation of changes during the treatment of specific disorders. The results include 3D models of selected dental arch objects, which allow a comparison of their shape and position during repeated observations. The proposed methods present digital alternatives to the use of plaster casts for semiautomatic evaluation of dental arch measures. This paper describes some of the advantages of 3D digital technology replacing real world elements and plaster cast dental models in many areas of classical stomatology. [ABSTRACT FROM AUTHOR]

This manuscript is concerned with the development of digital inspection of casting defects using x-ray radiography images. An efficient approach for detection and classification time of casting defects in x-ray radiography images is proposed. The accuracy of this approach depends on suggested algorithms for background correction, image de-noising, image enhancement and image segmentation of casting defects. Three different algorithms are introduced for automatic detection of casting defects in x-ray images. These algorithms depend on features extraction power density spectrum (PDS) and high order statistics (HOS). An artificial neural network is utilized as a classifier for matching purposes of extracted features. The results show that HOS achieved the best recognition rate of 100% for casting defects in X-ray radiography images in comparison with other algorithms. Besides, a reduction of classification time for casting defects is another target in this paper. It is achieved using costly powerful digital processing hardware and advanced software. Furthermore, an algorithm is realized to reduce classification time of casting defects. This algorithm depends on textural features that extracted from x-ray images of casting defects. Hence, a feature reduction program code is implemented for reduction of extracted features. This program code is relied on average value of each extracted feature for normal and defect image. The numbers of extracted features are reduced from 22 to 2 features. Therefore, better execution time can be achieved for classification purposes of casting defects. The proposed algorithms are evaluated using Intel core TM i5-3470 CPU with 3.20 GHz and Intel core TM i7-3612QM CPU with 4.00 GHz. Consequently, these algorithms can be transferred into more powerful digital processing hardware such as FPGA and GPU for faster classification of casting defects. The obtained results confirm that proposed algorithms can be applied for a broad range of non-destructive applications using image processing techniques. [ABSTRACT FROM AUTHOR]

Ultrasound has been used to inspect composite laminates since their invention but only recently has the response from the internal plies themselves been considered of interest. This paper uses modeling techniques to make sense of the fluctuating and interfering reflections from the resin layers between plies, providing clues to the underlying inhomogeneities in the structure. It shows how the analytic signal, analyzed in terms of instantaneous amplitude, phase, and frequency, allows 3-D characterization of the microstructure. It is found that, under certain conditions, the phase becomes locked to the interfaces between plies and that the first and last plies have characteristically different instantaneous frequencies. This allows the thin resin layers between plies to be tracked through various features and anomalies found in real composite components (ply drops, tape gaps, tape overlaps, and out-of-plane wrinkles), giving crucial information about conformance to design of as-manufactured components. Other types of defects such as delaminations are also considered. Supporting evidence is provided from experimental ultrasonic data acquired from real composite specimens and compared with X-ray computed tomography images and microsections. [ABSTRACT FROM PUBLISHER]

ObjectiveThe objective of this study was to evaluate the diagnostic efficacy of Pixon-based reconstruction method on planar somatostatin receptor scintigraphy (SRS).MethodsAll patients with neuroendocrine tumors (NETs) disease who were referred for SRS to our department during 1-year period from January to December 2015 were consecutively included. Three nuclear physicians independently reviewed all the data sets of images which included conventional images (CI; 15 min/view) and processed images (PI) obtained by reconstructing the first 450 s extracted data using Oncoflash® software package. Image analysis using a 3-point rating scale for abnormal uptake of 111 Indium-DTPA-Phe-octreotide in any lesion or organ was interpreted as positive, uncertain, or negative for the evidence of NET disease. A maximum grade uptake of the radiotracer in the lesion was assessed by the Krenning scale method. The results of image interpretation by the two methods were considered significantly discordant when the difference in organ involvement assessment was negative vs. positive or in lesion uptake was ≥2 grades. Agreement between the results of two methods and by different scan observers was evaluated using Cohen κ coefficients.ResultsThere was no significant (p = 0.403) correlation between data acquisition protocol and quality image. The rates of significant discrepancies for exam interpretation and organs involvement assessment were 2.8 and 2.6%, respectively. Mean κ values revealed a good agreement for concordance between CI and PI interpretation without difference of agreement for inter/intra-observer analysis.ConclusionOur results suggest the feasibility to use a Pixon-based reconstruction method for SRS planar images allowing a twofold reduction of acquisition time and without significant alteration of image quality or on image interpretation.

One of the fastest growing and efficient methods for solving the unconstrained minimization problem is the conjugate gradient method (CG). Recently, considerable efforts have been made to extend the CG method for solving monotone nonlinear equations. In this research article, we present a modification of the Fletcher−Reeves (FR) conjugate gradient projection method for constrained monotone nonlinear equations. The method possesses sufficient descent property and its global convergence was proved using some appropriate assumptions. Two sets of numerical experiments were carried out to show the good performance of the proposed method compared with some existing ones. The first experiment was for solving monotone constrained nonlinear equations using some benchmark test problem while the second experiment was applying the method in signal and image recovery problems arising from compressive sensing.

Augmented reality has a wide range of applications in many areas that can extend the study of real objects into the digital world, including stomatology. Real dental objects that were previously examined using their plaster casts are often replaced by their digital models or three-dimensional (3D) prints in the cyber-physical world. This paper reviews a selection of digital methods that have been applied in dentistry, including the use of intra-oral scanning technology for data acquisition and evaluation of fundamental features of dental arches. The methodology includes the use of digital filters and morphological operations for spatial objects analysis, their registration, and evaluation of changes during the treatment of specific disorders. The results include 3D models of selected dental arch objects, which allow a comparison of their shape and position during repeated observations. The proposed methods present digital alternatives to the use of plaster casts for semiautomatic evaluation of dental arch measures. This paper describes some of the advantages of 3D digital technology replacing real world elements and plaster cast dental models in many areas of classical stomatology.

Progress in computational fluid dynamics and the availability of new composite materials are driving major advances in the design of aerospace engine components which now have highly complex geometries optimized to maximize system performance. However, shape complexity poses significant challenges to traditional nondestructive evaluation methods whose sensitivity and selectivity rapidly decrease as surface curvature increases. In addition, new aerospace materials typically exhibit an intricate microstructure that further complicates the inspection. In this context, an attractive solution is offered by combining ultrasonic phased array (PA) technology with immersion testing. Here, the water column formed between the complex surface of the component and the flat face of a linear or matrix array probe ensures ideal acoustic coupling between the array and the component as the probe is continuously scanned to form a volumetric rendering of the part. While the immersion configuration is desirable for practical testing, the interpretation of the measured ultrasonic signals for image formation is complicated by reflection and refraction effects that occur at the water-component interface. To account for refraction, the geometry of the interface must first be reconstructed from the reflected signals and subsequently used to compute suitable delay laws to focus inside the component. These calculations are based on ray theory and can be computationally intensive. Moreover, strong reflections from the interface can lead to a thick dead zone beneath the surface of the component which limits sensitivity to shallow subsurface defects. This paper presents a general approach that combines advanced computing for rapid ray tracing in anisotropic media with a 256-channel parallel array architecture. The full-volume inspection of complex-shape components is enabled through the combination of both reflected and transmitted signals through the part using a pair of arrays held in a yoke configuration. Experimental results are provided for specimens of increasing complexity relevant to aerospace applications such as fan blades. It is shown that PA technology can provide a robust solution to detect a variety of defects including porosity and waviness in composite parts. [ABSTRACT FROM AUTHOR]

Nondestructive evaluation methods rely on prior knowledge of the expected interaction of ultrasonic waves with defects to inform detection and characterization decisions. Wavefield imaging, which refers to the measurement of signals originating from a spatially fixed source on a 2-D rectilinear grid, can be applied to visualize the effect of a subsurface scatterer on surface-measured wave motion. Here, obliquely incident shear waves are directed at the far surface of a plate containing a through-hole using the well-known angle-beam ultrasonic inspection method. A laser vibrometer and laboratory scanner are used to record the resulting out-of-plane motion on the plate surface in the vicinity of the through-hole both before and after a far-surface corner notch is introduced and subsequently enlarged. Waves scattered from the notch are isolated from the incident and hole-scattered waves via baseline subtraction of wavefields. The scattered wavefields are then filtered in the frequency–wavenumber domain to separate Rayleigh, shear, and longitudinal contributions to the scattered wavefield. The filtered wavefields are interpolated in space to obtain 2-D radial wavefield slices originating at the base of the notch. Each radial slice is analyzed to quantify scattering as a function of observation direction, resulting in Rayleigh, shear, and longitudinal scattering profiles for each notch size. The results are compared for four different notch sizes and two transducer orientations. [ABSTRACT FROM AUTHOR]

In cardiology, optical coherence tomography (OCT) has been established as a reference for in vivo intravascular image. OCT provides high-resolution and enables us to visualize accurately vessel intimal layers and stents. The drawback is the time necessary to manually select stent struts and lumen boundary. We developed and evaluated an automatic stent strut detection method to apply to intravascular OCT images. The proposed approach innovates the strut shadow detection, which can be considered as an independent processing step that helps discriminating struts by using a profile map. The paper will be presented as a complete process, explaining the necessary steps in order of appearance. [ABSTRACT FROM AUTHOR]

Passive ultrasonic tomography is described. Results of developing, modeling, and testing some key techniques in passive ultrasonic tomography are provided. The techniques include an algorithm for determining arrival times of noisy acoustic signals with sloping leading edge; a method for determining the source coordinates and onset times of acoustic signals and estimating the accuracy of those; and regularizing procedures for tomographic reconstruction of nonuniform distributions of propagation speed of acoustic signals. The results of modeling the effect of measurement noises on the accuracy of source location and the mutual influence of the source location accuracy and the soughtfor nonuniform distribution of propagation speed of acoustic signals are described. Results of experimental testing of the developed techniques are also provided. [ABSTRACT FROM AUTHOR]

So far quaternion Fourier transforms have been mainly defined over $${\mathbb{R}^2}$$ as signal domain space. But it seems natural to define a quaternion Fourier transform for quaternion valued signals over quaternion domains. This quaternion domain Fourier transform (QDFT) transforms quaternion valued signals (for example electromagnetic scalar-vector potentials, color data, space-time data, etc.) defined over a quaternion domain (space-time or other 4D domains) from a quaternion position space to a quaternion frequency space. The QDFT uses the full potential provided by hypercomplex algebra in higher dimensions and may moreover be useful for solving quaternion partial differential equations or functional equations, and in crystallographic texture analysis. We define the QDFT and analyze its main properties, including quaternion dilation, modulation and shift properties, Plancherel and Parseval identities, covariance under orthogonal transformations, transformations of coordinate polynomials and differential operator polynomials, transformations of derivative and Dirac derivative operators, as well as signal width related to band width uncertainty relationships. [ABSTRACT FROM AUTHOR]

A traditional way for describing objects, based on the well-known Euclidean geometry, is not capable to describe different natural objects and phenomena such as clouds, relief shapes, trends in economy, etc. On the contrary fractal geometry and its extension multifractals are new "tools" which can be used for describing, modeling, analyzing and processing different complex shapes and signals. This paper considers fractal geometry and multifractals and their application in signal analyzing and processing particularly in medical signal analysis.

• Design a fast-parallel low-level kernel of the Complex Matrix Multiplication algorithm based on modulo-scheduling, software pipelining and loop unrolling techniques. • Suggest a novel approach of implementing the Complex Matrix Multiplication algorithm based on the fast-parallel kernel and the miss-pipelining technique. • Introduce an ultra-optimized parallel implementation approach based on the fast-parallel kernel and the internal direct memory access data transfer technique. • Accelerate the beamforming and Doppler Filter Bank algorithms to meet tight real-time constraints of radar applications. The Complex Matrix Multiplication (CMM) algorithm is known to require a high computing performance and presenting exceptional challenges in real-life applications. Recent advances in Very Long Instruction Word (VLIW) based Digital Signal Processors (DSP) demonstrated high computing capabilities with a very low power consumption. In this work, we propose three ultra-fast, parallel and efficient VLIW implementation approaches of the CMM algorithm which could be used to meet tighter real-time constraints of several signal and image processing applications like radars. A novel parallel kernel, task mapping strategy and low-level optimization techniques are suggested, to fit a set of modern VLIW architectures. Additionally, an original memory access management technique was adopted to accelerate the algorithm by avoiding cache misses and bank conflicts. The experimental results showed the effectiveness of the proposed approaches where a peak performance of 15.89 GFLOPS was achieved on one C66x DSP core with a core utilization of 99% and a speedup of about 1.61, 3 and 10 compared to the state-of-the-art, the most optimized vendor and the conventional approaches, respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

This article discusses the latest development in computational mapping for the identification and localization of critical sources in patients with atrial fibrillation (AF). It focuses on the contribution of electrogram-derived anatomical maps, obtained by applying innovative signal and image processing methodologies, to the investigation of the mechanisms underlying the arrhythmia and to the planning of new target ablation strategies. Reviewed are the experimental studies which allowed to infer the peculiar rate and regularity features of critical sources, the signal processing methods for the quantification of these parameters from atrial electrograms, and the clinical studies mapping rate and organization in AF patients. Finally, we present a novel methodological framework, based on the construction of the logic operation map, designed to merge in a single map the most relevant electrophysiological and anatomical features of the AF process, which may guide the selective identification of critical sources. [ABSTRACT FROM PUBLISHER]

In this paper the application of bounded series theory due to Carathéodory and Toeplitz is explored to study Brune positive real rational function (PRF). The main goal is to find the necessary and sufficient conditions for PRF coefficients. The introduced algorithms and assertions present an appropriate mathematical model derived from the developed analytical functions. The suggested solution is based on the results of Carathéodory, Toeplitz, Schur and their achievements at the beginning of the twentieth century. Toeplitz matrix lowest eigenvalues are constructed by the coefficients of the bounded power series representing Carathéodory function to establish a new simple and general algorithm for testing the nonnegativeness of real rational functions. The achieved results have shown engineering interests in two different areas of research: the electrical and mechanical circuit theory from one side and the image analysis and processing from the other side. The involvement in these methods has recently drawn the attention of researchers due to the increasing demand for simple methods of electrical and mechanical network synthesis. The author has proved the reasonability of Carathéodory–Toeplitz theory and modified it for using in other new areas of research. The most important achievements that describe relevant applications in such fields as digital filter design, speech signal and object image processing are discussed in the paper. Examples are introduced to illustrate these applications with emphasis on biometrics. [ABSTRACT FROM AUTHOR]

Abstract: Ultrasound and Duplex ultrasonography in particular are routinely used to diagnose cardiovascular disease (CVD), which is the leading cause of morbidity and mortality worldwide. However, these techniques may not be able to characterize vascular tissue compositional changes due to CVD. This work describes an ultrasound-based hybrid imaging technique that can be used for vascular tissue characterization and the diagnosis of atherosclerosis. Ultrasound radiofrequency (RF) data were acquired and processed in time, frequency, and wavelet domains to extract six parameters including time integrated backscatter (TIB ), time variance (Tvar ), time entropy (TE ), frequency integrated backscatter (FIB ), wavelet root mean square value (Wrms ), and wavelet integrated backscatter (WIB ). Each parameter was used to reconstruct an image co-registered to morphological B-scan. The combined set of hybrid images were used to characterize vascular tissue in vitro and in vivo using three mouse models including control (C57BL/6), and atherosclerotic apolipoprotein E-knockout (APOE-KO) and APOE/A1 adenosine receptor double knockout (DKO) mice. The technique was tested using high-frequency ultrasound including single-element (center frequency=55MHz) and commercial array (center frequency=40MHz) systems providing superior spatial resolutions of 24μm and 40μm, respectively. Atherosclerotic vascular lesions in the APOE-KO mouse exhibited the highest values (contrast) of −10.11±1.92dB, −12.13±2.13dB, −7.54±1.45dB, −5.10±1.06dB, −5.25±0.94dB, and −10.23±2.12dB in TIB , Tvar , TE , FIB , Wrms , WIB hybrid images (n =10, p <0.05), respectively. Control segments of normal vascular tissue showed the lowest values of −20.20±2.71dB, −22.54±4.54dB, −14.94±2.05dB, −9.64±1.34dB, −10.20±1.27dB, and −19.36±3.24dB in same hybrid images (n =6, p <0.05). Results from both histology and optical images showed good agreement with ultrasound findings within a maximum error of 3.6% in lesion estimation. This study demonstrated the feasibility of a high-resolution hybrid imaging technique to diagnose atherosclerosis and characterize plaque components in mouse. In the future, it can be easily implemented on commercial ultrasound systems and eventually translated into clinics as a screening tool for atherosclerosis and the assessment of vulnerable plaques. [Copyright &y& Elsevier]

This paper analyzes the block structure of the matrix of the N-point discrete Fourier transform (DFT) in the real space R. Each block of this matrix corresponds to the Givens transformation, or elementary rotation describing the multiplications by twiddle coefficients. Such rotations around the circle can be substituted by other kinds of rotations, for instance rotations around ellipses, while reserving the block-wise representation of the matrix and main properties of the DFT. To show that, we present two classes of the elliptic discrete Fourier transforms (EDFT), that are defined by different types of the Nth roots of the identity matrix 2×2, whose groups of motion move points around different ellipses. These two classes (the N-block EDFT of types I and II) are parameterized and exist for any order N. Properties and examples of application of the proposed elliptic EDFTs in signal and image processing are given. [ABSTRACT FROM AUTHOR]

Recording of maternal uterine pressure (UP) and fetal heart rate (FHR) during labor and delivery is a procedure referred to as cardiotocography. We modeled this signal pair as an input-output system using a system identification approach to estimate their dynamic relation in terms of an impulse response function. We also modeled FHR baseline with a linear fit and FHR variability unrelated to UP using the power spectral density, computed from an auto-regressive model. Using a perinatal database of normal and pathological cases, we trained suport-vector-machine classifiers with feature sets from these models. We used the classification in a detection process. We obtained the best results with a detector that combined the decisions of classifiers using both feature sets. It detected half of the pathological cases, with very few false positives (7.5%), 1 h and 40 min before delivery. This would leave sufficient time for an appropriate clinical response. These results clearly demonstrate the utility of our method for the early detection of cases needing clinical intervention. [ABSTRACT FROM AUTHOR]