Spurious Elements Research Articles

Insights Into Vestibulo-Ocular Reflex Artifacts: A Narrative Review of the Video Head Impulse Test (vHIT).

Video head impulse test (vHIT) artifacts are defined as spurious elements or disturbances in the recorded data that deviate from the true vestibulo-ocular reflexresponse. These artifacts can arise from various sources, encompassing technological limitations, patient-specific factors, or environmental influences, introducing inaccuracies in vHIT outcomes. The absence of standardized criteria for artifact identification leads to methodological heterogeneity. This narrative review aims to comprehensively examine the challenges posed by artifacts in the vHIT. By surveying existing literature, the review seeks to elucidate the multifaceted nature of artifacts arising from technological, patient-related, evaluator-related, and environmental factors.

On the feasibility of Vis–NIR spectroscopy and machine learning for real time SARS-CoV-2 detection

The pandemic caused by Covid-19 is still present around the world. Despite advances in combating the disease, such as vaccine development, identifying infected individuals is still essential to optimize the control of human-to-human transmission of the virus. The main technique for detecting the virus is the RT-PCR method, which, despite its high relative cost, has a high accuracy in detecting the coronavirus. Given this, a method capable of performing the identification quickly, accurately, and inexpensively is necessary. Thus, this work aimed to analyze the feasibility of a new technique for identifying SARS-CoV-2 through the use of optical spectroscopy in the visible and near-infrared range (Vis–NIR) combined with machine learning algorithms. Spectral signals were obtained from nasopharyngeal swab samples previously analyzed using the RT-PCR method. The specimens were provided by the Molecular Diagnosis Laboratory of Covid-19 at Univasf. A total of 314 samples were analyzed, comprising 42 testing positive and 272 testing negative for Covid-19. Digital signal processing techniques, such as Savitzky–Golay filters and statistical methods were used to eliminate spurious elements from the original data and extract relevant features. Supervised machine learning algorithms such as SVM, Random Forest, and Naive Bayes classifiers were used to perform automatic sample identification. To evaluate the performance of the models, a 5-fold cross-validation technique was applied. With the proposed methodology, it was possible to achieve an accuracy of 75%, a sensitivity of 80%, and a specificity of 70%, in addition to an area under the ROC curve of 0.81, in the identification of nasopharyngeal swab samples from previously diagnosed individuals. From these results, it was possible to conclude that Vis–NIR spectroscopy is a promising, fast and relatively low cost technique to identify the SARS-CoV-2.

Intensity correlation scan (IC-scan) technique to characterize the optical nonlinearities of scattering media

Light scattering, whether caused by desired or spurious elements, is considered one of the main phenomena that present great challenges for the nonlinear (NL) optical characterization of turbid media. The most relevant disturbing factor is the random deformation suffered by the spatial intensity distribution of the laser beam due to multiple scattering. In this work, we report the intensity correlation scan (IC-scan) technique as a new tool to characterize the NL optical response of scattering media, by taking advantage of light scattering to generate speckle patterns sensitive to wavefront changes induced by the self-focusing and self-defocusing effects. Peak-to-valley transmittance curves, with a higher signal-to-noise ratio, are obtained by analyzing the spatial intensity correlation functions of the different speckle patterns, even in very turbid media where conventional NL spectroscopy techniques fail. To demonstrate the potential of the IC-scan technique, the NL characterization of colloids that contain a high concentration of silica nanospheres as scatterers, as well as gold nanorods, which act as NL particles and light scatterers, was performed. The results show that the IC-scan technique is more accurate, precise and robust to measure NL refractive indices in turbid media, overcoming limitations imposed by well-established Z-scan and D4σ techniques.

Release of Nanoparticles in the Environment and Catalytic Converters Ageing.

A Three-Way Catalyst (TWC) contains a cordierite ceramic monolith coated with a layer of Al2O3, CexZr1−xO2 and platinoids mixture. Under standard operation, the platinoid concentration decreases, exposing the remaining washcoat structure. After that particle release stage, the sintering process follows where the crystalline CexZr1−xO2 solution is broken and begins to separate into ZrO2 and CeO2 phases. ZrO2 is released to the environment as micro and nanoparticles, while a small amount of CeO2 generates a new AlxCe1−xO2 composite. The main effect of Ce capture is the growth in the size of the polycrystal structure from 86.13 ± 16.58 nm to 225.35 ± 69.51 nm. Moreover, a transformation of cordierite to mullite was identified by XRD analysis. Raman spectra showed that the oxygen vacancies (Vö) concentration decreased as CexZr1−xO2 phases separation occurred. The SEM-EDS revealed the incorporation of new spurious elements and microfractures favouring the detachment of the TWC support structure. The release of ultrafine particles is a consequence of catalytic devices overusing. The emission of refractory micro to nanocrystals to the atmosphere may represent an emerging public health issue underlining the importance of implementing strict worldwide regulations on regular TWCs replacement.

DAFNE: A dataset of fresco fragments for digital anastlylosis

• A large publicly available dataset of simulated fresco fragments. • High variety of subjects and conditions. • Different painters and historical periods. • Missing and spurious elements have been considered. Restoring artworks seriously damaged or completely destroyed is a challenging task. In particular, the reconstruction of frescoes has to deal with problems such as very small fragments, irregular shapes and missing pieces. Several attempts have been done to develop new techniques for helping restorers in the matching process, starting from traditional image processing methods to the more recent deep learning approaches. However, as often happens in the Cultural Heritage field, the availability of labeled data to test new strategies is limited, and publicly available datasets contain only few samples. For this reason, in this paper we introduce DAFNE, a large dataset that includes hundreds of thousands of images of fresco fragments artificially generated to guarantee a high variability in terms of shapes and dimensions. Fragments have been obtained starting from 62 images of famous frescoes of various artists and historical periods, in order to consider different artistic styles, subjects and colors.

SAFFO: A SIFT based approach for digital anastylosis for fresco recOnstruction

Abstract Anastylosis is an archaeological technique which focuses on the reconstruction of collapsed building and destroyed artworks, starting from the original pieces. Many digital approaches have been developed in the last decade, mainly based on 2D and 3D analysis of the structure of the fragments. These techniques aim at supporting the priceless work of the involved operators, mainly in the decision processes and in the resolution of positioning ambiguities. Techniques acting with this scope lie in the field of the digital anastylosis. In this paper we present SAFFO, a digital approach to 2D reconstruction of frescoes, based on the extraction of SIFT features from a painting. The approach appears to be very robust to false positives, resulting optimal in scenarios involving fragment sets containing spurious elements. The experiments have been performed on the DAFNE (Digital Anastylosis for Fresco challeNgE) dataset, which gathers more than 30 2D artworks and provides several tessellation for each. For its robustness against spurious fragments, SAFFO won the third place in the rank list of DAFNE Challenge 2019.

Improved Small-Signal Model of Single-Electron Transistor

An improved version of the Small-Signal model of a single-electron transistor for high frequency is proposed in this paper. The modification is done by incorporating the parasitic elements for the high-frequency operation of single-electron transistor. The high-frequency operation introduces several spurious elements due to the physical structure and the testing instrument connection to the device under test. The impact of these elements on the matching network is significant but yet unpredictable. The formulation of the Small-Signal model considering the extrinsic and intrinsic elements is elaborated in this literature. The scattering parameters play an important role in the determination of the properties of a transistor working at high frequency. This study is carried out for determining the scattering parameters for single-electron transistor and their relationship with the other intrinsic as well as extrinsic parameters.

Practical dynamic de Bruijn graphs.

The de Bruijn graph is fundamental to the analysis of next generation sequencing data and so, as datasets of DNA reads grow rapidly, it becomes more important to represent de Bruijn graphs compactly while still supporting fast assembly. Previous implementations of compact de Bruijn graphs have not supported node or edge deletion, however, which is important for pruning spurious elements from the graph. Belazzougui et al. (2016b) recently proposed a compact and fully dynamic representation, which supports exact membership queries and insertions and deletions of both nodes and edges. In this paper, we give a practical implementation of their data structure, supporting exact membership queries and fully dynamic edge operations, as well as limited support for dynamic node operations. We demonstrate experimentally that its performance is comparable to that of state-of-the-art implementations based on Bloom filters. Our source-code is publicly available at https://github.com/csirac/dynamicDBG under an open-source license.

A Technique to Suppress Harmonic Outputs in Coaxial Cavity Filters at the Excitation Port

A technique to improve the spurious performance of coaxial cavity filters is investigated. It involves incorporating elements/posts resonant at spurious frequencies within the coaxial input/output cavites. To perform suppression and control of harmonic outputs, the spurious elements are coupled directly to the excitation posts and prevent the excitation of harmonics at the fundamental elements. The spurious elements are physically significantly smaller than the fundamental elements that perform the basic filtering function (fundamental frequency); thus they impose only minimized degradation to the ohmic loss of the devices and miniscule additional design effort. Design guidelines of the proposed filters are given. Obtained results demonstrate significant improvement in the spurious performance, and experimental results verify the concept.

Knowledge extraction from trained neural network scour model at culvert outlets

Artificial neural networks (ANNs), due to their outstanding capabilities for modeling complex processes, have been successfully applied to a variety of problems in hydraulics. However, one of the major criticisms of ANNs is that they are just black-box models, since a satisfactory explanation of their behavior has not been offered. They, in particular, do not explain easily how the inputs are related to the output and also whether the selected inputs have any significant relationship with an output. In this paper, a perturbation analysis for determining the order of influence of the elements in the input vector on the output vector is discussed. The analyses of the results suggest that each variable in the input vector (d 50/d 0, F 0, H/d 0, σg, and W 0/d 0) influences the depth of scour in different ways. However, the magnitude of the influence cannot be clearly quantified by this approach. Further it adds that the selection of input vector based on linear measures between the variables of interest, which is commonly employed, may still include certain spurious elements that only increase the model complexity.

Knowledge Extraction from Trained Neural Network Scour Models

This study extends the earlier contribution of Azamathulla et al. in 2005. Artificial neural networks (ANNs), due to their excellent capabilities for modeling complex processes, have been successfully applied to a variety of problems in hydraulics. However, one of the major criticisms of ANNs is that they are just black-box models, since a satisfactory explanation of their behavior has not been offered. They, in particular, do not explain easily how the inputs are related to the output, and also whether the selected inputs have any significant relationship with an output. In this paper, a perturbation analysis for determining the order of influence of the elements in the input vector on the output vector is discussed. The approach is illustrated though networks recommended in Azamathulla et al. 2005 for prediction of scour using neural networks. The analyses of the results suggest that each variable in the input vector (discharge intensity, head, tail water depth, bed material, lip angle and radius of the bucket) influences the depth of scour in different ways. However, the magnitude of the influence cannot be clearly quantified by this approach. Further it adds that the selection of input vector based on linear measures between the variables of interest, which is commonly employed, may still include certain spurious elements that only increase the complexity of the model.

Differential calibration of seismometers for measurement of rotation and strain

A method of correcting the seismometers’ responses discrepancy for differential measurements of strains and rotations in the seismic far field is proposed. The method concerns differential calibration of the whole seismometers’ array by electric current. A model of corrective filtering of the obtained differential signals in the Z domain is given. Two methods of the filter parameters’ estimation are introduced; they are based on the seismometers response to the calibration. A practical test of the methods — an analysis of a recorded seismic event — is added. Significant reduction of differences between simultaneous seismic recordings was obtained, which is interpreted as cleaning of differential signal from spurious elements.

Quality control of industrial processes by combining a hyperspectral sensor and Fisher's linear discriminant analysis

Abstract A non-intrusive and non-contact system for the real time detection of spurious elements in raw material processing chains for industrial environments is presented. Observation line spectrographs, obtained from the visible–near infrared (Vis–NIR) reflectance of the material under study, are obtained using a dual spatial-spectral technique. Therefore, a huge amount of information is involved in the process and an efficient classification algorithm would be a great asset. In this paper, the validity of Fisher's linear discriminant for this application is investigated. The technique has been successfully tested on the tobacco industry. However, the technique is not limited to tobacco leaves, but other materials can additionally be discriminated or classified.

Improved Vertical Covariance Estimates for Ensemble-Filter Assimilation of Near-Surface Observations

AbstractStrategies to improve covariance estimates for ensemble-based assimilation of near-surface observations in atmospheric models are explored. It is known that localization of covariance estimates can improve conditioning of covariance matrices in the assimilation process by removing spurious elements and increasing the rank of the matrix. Vertical covariance localization is the focus of this work, and two basic approaches are compared: 1) a recently proposed hierarchical filter approach based on sampling theory and 2) a more commonly used fifth-order piecewise rational function. The hierarchical filter allows for dynamic estimates of localization functions and does not place any restrictions on their form. The rational function is optimized for every analysis time of day and for every possible observation and state variable combination. The methods are tested with a column model containing PBL and land surface parameterization schemes that are available in current mesoscale modeling systems. The results are expected to provide context for assimilation of near-surface observations in mesoscale models, which will benefit short-range mesoscale NWP applications. Results show that both the hierarchical and rational function approaches effectively improve covariance estimates from small ensembles. The hierarchical approach provides localization functions that are irregular and more closely related to PBL structure. Analysis of eigenvalue spectra show that both approaches improve the rank of the covariance matrices, but the amount of improvement is not always directly related to the assimilation performance. Results also show that specifying different localization functions for different observation and state variable combinations is more important than including time dependence.

Novel Readout Electronics for Thickness Shear-Mode Liquid Sensors Compensating for Spurious Conductivity and Capacitances

In this paper, a readout circuit for a thickness shear-mode (TSM) resonator is presented which can be used for sensing applications in liquids such as viscosity sensing. The system features compensation of both spurious capacitances and conductances in parallel to the resonator. This allows measurements even in conductive liquids without the need for an elaborate sealing of the sensor. The influence of the spurious elements is determined by means of two orthogonal synchronous detectors and eliminated by active compensation using voltage-controlled amplifiers (VCAs). Furthermore, the circuit is robust against possible phase errors. The basic concept is discussed in detail, and a readout circuit is developed. A prototype is presented, and sample results are given, demonstrating the feasibility of the approach

New raw material discrimination system based on a spatial optical spectroscopy technique

A non-intrusive and non-contact system for real-time detection of spurious elements in raw material processing chains for industrial environments is presented. Observation line spectrographs, based on the visible–near infrared (Vis–NIR) reflectance of the material under study, are obtained using a dual spatial-spectroscopic imaging technique. To attain a representative spectral fingerprint, the large amount of data is compressed using a principal component analysis (PCA) fast algorithm prior to the classification made by a neural network.The technique has been successfully tested on the tobacco industry. However, the technique is not limited to tobacco leaves, but other materials can be discriminated or classified instead.

Class-E microwave oscillator

The class-E oscillator with the directed coupler in the feedback is studied. The similar design allows to retune the oscillator with preservation of high efficiency due to a constancy of a directed coupler coupling coefficient in band of readjustable frequencies and absence of the additional selective resonator in the feedback. Influence of spurious elements of the transistor on generation conditions in class-E is considered. The experimental breadboard of a class-E oscillator with output power 500 mW and efficiency 65% on frequency 800 MHz is investigated.

Symmetry Maps of Free-Form Curve Segments via Wave Propagation

This paper presents an approach for computing the symmetries (skeletons) of an edge map consisting of a collection of curve segments. This approach is a combination of analytic computations in the style of computational geometry and discrete propagations on a grid in the style of the numerical solutions of PDE's. Specifically, waves from each of the initial curve segments are initialized and propagated as a discrete wavefront along discrete directions. In addition, to avoid error built up due to the discrete nature of propagation, shockwaves are detected and explicitly propagated along a secondary dynamic grid. The propagation of shockwaves, integrated with the propagation of the wavefront along discrete directions, leads to an exact simulation of propagation by the Eikonal equation. The resulting symmetries are simply the collection of shockwaves formed in this process which can be manipulated locally, exactly, and efficiently under local changes in an edge map (gap completion, removal of spurious elements, etc). The ability to express grouping operations in the language of symmetry maps makes it an appropriate intermediate representation between low-level edge maps and high level object hypotheses.

X-Ray Microanalysis in the Variable Pressure (Environmental) Scanning Electron Microscope.

Electron-excited x-ray microanalysis performed in the variable pressure and environmental scanning electron microscopes is subject to additional artifacts beyond those encountered in the conventional scanning electron microscope. Gas scattering leads to direct contributions to the spectrum from the environmental gas, as well as remote generation of x rays by electrons scattered out of the focussed beam. The analyst can exert some degree of control over these artifacts, but depending on the exact situation, spurious elements can appear at the trace (< 0.01 mass fraction), minor (0.01 mass fraction to 0.1 mass fraction), or even major (> 0.1 mass fraction) levels. Dispersed particle samples give the least compromised results, while fine scale microstructures are the most severely compromised. Procedures to optimize the situation based upon specimen preparation as well as spectral processing are described.

Optimization of the transfer function of an acoustooptic cell with an apodized piezoelectric transducer

It is shown that an apodized piezoelectric transducer can significantly reduce the side lobe level of the acoustooptic cell transfer function. Series and symmetric connections of the transducer sections and measures to suppress the effect of spurious elements arising in the electric circuit are proposed. In particular, the effect of spurious capacitances and inductances on the frequency response of the transducer is studied. It is shown that they violate the optimal condition for the suppression of the transfer function side lobes, especially at high frequencies. It is shown by calculations that the effect of spurious elements can be eliminated by the insertion of additional capacitors at 80 and 150 MHz.