Dense Sampling Grid Research Articles

Sampling the user controls in neural modeling of audio devices

This work studies neural modeling of nonlinear parametric audio circuits, focusing on how the diversity of settings of the target device user controls seen during training affects network generalization. To study the problem, a large corpus of training datasets is synthetically generated using SPICE simulations of two distinct devices, an analog equalizer and an analog distortion pedal. A proven recurrent neural network architecture is trained using each dataset. The difference in the datasets is in the sampling resolution of the device user controls and in their overall size. Based on objective and subjective evaluation of the trained models, a sampling resolution of five for the device parameters is found to be sufficient to capture the behavior of the target systems for the types of devices considered during the study. This result is desirable, since a dense sampling grid can be impractical to realize in the general case when no automated way of setting the device parameters is available, while collecting large amounts of data using a sparse grid only incurs small additional costs. Thus, the result provides guidance for efficient collection of training data for neural modeling of other similar audio devices.

Defining management zones for a papaya culture considering soil chemical attributes by fuzzy c-means

In precision agriculture, one of the major problems is the need for a dense sampling grid. A solution to this problem has been the generation of management zones and the correlation between them. This work aims at defining management zones for a papaya culture using the fuzzy C-means grouping method, based on the following soil attributes: phosphorus, calcium, magnesium and potassium; and base saturation. The work was conducted in an approximately 1.2 ha area planted with a commercial culture of Carica papaya L. cultivated in typical Argisol found on the coastal terraces, in the municipality of São Mateus, ES, Brazil. The management zones were defined by the proposed method, based on the following analyses: soil chemical parameters P, Ca, Mg, and base saturation (V), analyzed together; soil chemical parameters P, Ca, Mg, and V, analyzed separately; and, the following combinations of soil chemical attributes Ca-Mg, Ca-V, Ca-Mg-V, P-Ca, P-Mg, P-V, P-Ca-Mg, P-Ca-V, Mg-V, and P-Ca-Mg-V. The generated management zones facilitated an understanding of the spatial variability of the attributes in the study area and the observed similarities between management zones generated from different attributes. In addition, the data were influenced especially by the P and V% attributes. Keywords: Carica papaya L, geostatistics, grouping analysis, precision agriculture.

Investigating phoneme-dependencies of spherical voice directivity patterns II: Various groups of phonemes

The substantial variation between articulated phonemes is a fundamental feature of human voice production. However, while the spectral and temporal aspects of the phonemes have been extensively studied, few have investigated the spatial aspects and analyzed phoneme-dependent differences in voice directivity. This paper extends our previous research focusing on the directivity patterns of selected vowels and fricatives [Pörschmann and Arend, J. Acoust. Soc. Am. 149(6), 4553-4564 (2021)] and examines different groups of phonemes, such as plosives, nasals, voiced alveolars, and additional fricatives. For this purpose, full-spherical voice directivity measurements were performed for 13 persons while they articulated the respective phonemes. The sound radiation was recorded simultaneously using a surrounding spherical microphone array with 32 microphones and then spatially upsampled to a dense sampling grid. Based on these upsampled datasets, the spherical voice directivity was studied, and phoneme-dependent variations were analyzed. The results show significant differences between the groups of phonemes. However, within three groups (plosives, nasals, and voiced alveolars), the differences are small, and the variations in the directivity index were statistically insignificant.

Christiansen uniformity revisited: Re-thinking uniformity assessment in rainfall simulator studies

Rainfall simulators have been used extensively for a variety of research applications. The uniformity and spatial distribution of simulated rainfall is an important metric to consider when conducting rainfall simulator experiments. Over the past 80 years, several methods of assessing rainfall distribution and uniformity over the plot surface below a rainfall simulator have been developed. However, the Christiansen Uniformity Coefficient (CU; Christiansen, 1942) is most frequently used. Here, we provide a critique of this established methodology and metric for quantifying rainfall distribution characteristics. Uniformity coefficients express the distribution of rainfall across the plot surface as a single percentage value. Therefore, if all collection beakers receive equal volumes of water during an experimental run, the rainfall simulator or irrigation system would be applying water with 100% uniformity. There are shortcomings with using a single percentage value to represent rainfall simulator rainfall distribution, especially over a larger plot surface, and CU is highly dependent on the sampling methodology employed. This paper assesses rainfall uniformity by conducting a series of controlled uniformity experiments and resampling different grid layouts of collection containers. Results demonstrate that the coarseness of the sampling methodology affects rainfall uniformity coefficient values. CU values of 45 – 51% were recorded under a dense (17 × 17) sampling grid layout, compared to CU values of 81% using a coarser (8 × 8) sampling methodology, despite being subjected to comparable rainfall events. This paper explores the sensitivity of CU to the resolution and spatial layout of the sampling methodology used and assesses whether the CU captures repeatability and localised variability of uniformity between experimental runs. A complementary statistical approach expressing variations in relation to their standard deviation from the mean is presented. Understanding how experimental setup (i.e. number, density, spatial configuration of collection containers) affects CU is critical when interpreting results from different rainfall simulator studies and an understanding of the factors which influence CU is critical to benchmark the results of uniformity testing across different rainfall simulator setups.

Investigating phoneme-dependencies of spherical voice directivity patterns.

Dynamic directivity is a specific characteristic of the human voice, showing time-dependent variations while speaking or singing. To study and model the human voice's articulation-dependencies and provide datasets that can be applied in virtual acoustic environments, full-spherical voice directivity measurements were carried out for 13 persons while articulating eight phonemes. Since it is nearly impossible for subjects to repeat exactly the same articulation numerous times, the sound radiation was captured simultaneously using a surrounding spherical microphone array with 32 microphones and then subsequently spatially upsampled to a dense sampling grid. Based on these dense directivity patterns, the spherical voice directivity was studied for different phonemes, and phoneme-dependent variations were analyzed. The differences between the phonemes can, to some extent, be explained by articulation-dependent properties, e.g., the mouth opening size. The directivity index, averaged across all subjects, varied by a maximum of 3 dB between any of the vowels or fricatives, and statistical analysis showed that these phoneme-dependent differences are significant.

Image Resolution Enhancement of Highly Compressively Sensed CT/PET Signals

One of the most challenging aspects of medical modalities such as Computed Tomography (CT) as well hybrid techniques such as CT/PET (Computed Tomography/Positron emission tomography) and PET/MRI is finding a balance between examination time, radiation dose, and image quality. The need for a dense sampling grid is associated with two major factors: image resolution enhancement, which leads to a strengthening of human perception, and image features interpretation. All these aspects make an unsupervised image processing much easier. The presented algorithm employs super-resolution-reconstruction with high accuracy motion fields’ estimation at its core for Computed Tomography/Positron Emission Tomography (CT/PET) images enhancement. The suggested method starts with processing compressively sensed input signals. This paper shows that it is possible to achieve higher image resolution while keeping the same radiation dose. The purpose of this paper is to propose a highly effective CT/PET image reconstruction strategy, allowing for simultaneous resolution enhancing and scanning time minimisation. The algorithm aims to overcome two major obstacles—image resolution limitation and algorithm reconstruction time efficiency-by combining a highly-sparse Ridgelet analysis based sampling pattern as well as PET signal sensing with super-resolution (SR) image enhancement. Due to the diverse nature of Computed Tomography, the applied Ridgelet analysis arguing its usability turned out to be efficient in reducing acquisition times in regard to maintaining satisfying scan quality. This paper presents a super-resolution image enhancement algorithm designed for handling highly sensitively compressed hybrid CT/PET scanners raw data. The presented technique allows for improving image resolution while reducing motion artefacts and keeping scanning times at pretty low levels.

Rank-Based Local Self-Similarity Descriptor for Optical-to-SAR Image Matching

Automatic optical-to-synthetic aperture radar (SAR) image matching is still a challenging task due to the existence of severe nonlinear radiometric differences between the images and the presence of strong speckles in the SAR images. To address this problem, we propose a novel feature descriptor called rank-based local self-similarity (RLSS) for optical-to-SAR image template matching. The RLSS descriptor is an improved version of the local self-similarity (LSS) descriptor, inspired by Spearman's rank correlation coefficient in statistics. It can describe the local shape properties of an image in a discriminable manner. To further improve the discriminability, a dense RLSS (DRLSS) descriptor is formed with a dense scheme by integrating the RLSS descriptors for multiple local regions into a dense sampling grid. Experimental results conducted based on the optical and SAR image pairs demonstrated that the proposed descriptor was robust to nonlinear radiometric differences and it outperformed two state-of-the-art descriptors [dense LSS (DLSS) and histogram of orientated phase congruency (HOPC)].

Directional Equalization of Sparse Head-Related Transfer Function Sets for Spatial Upsampling

Acquiring decent full-spherical sets of head-related transfer functions HRTFs based on a small number of measurements is highly desirable. For spatial upsampling, HRTF interpolation in the spatially continuous spherical harmonics SH domain is a common approach. However, the number of measured HRTFs limits the assessable SH order, resulting in order-limited HRTFs when transformed to the SH domain. Thus, the SH representation of sparse HRTF sets shows restricted spatial resolution and suffers from order-limitation errors. We present a method that reduces these errors by a directional equalization prior to the SH transform. This is done by a spectral division of each HRTF with a corresponding directional rigid sphere transfer function. The processing removes direction-dependent temporal and spectral components and, therefore, significantly reduces the spatial complexity of the HRTF set, allowing for an enhanced interpolation of HRTFs at reduced SH orders. Spatial upsampling is achieved by an inverse SH transform on an arbitrary dense sampling grid. A subsequent de-equalization by a spectral multiplication with the rigid sphere transfer function recovers the energy in higher spatial orders that was not inherent in the sparse HRTF set. For evaluation, HRTFs were calculated for various limited orders from sparse datasets and compared to a reference. The results show that the proposed method clearly outperforms common SH interpolation of HRTF spectra regarding the overall spectral and temporal structure as well as modeled localization performance.

Precision production environments for sugarcane fields

ABSTRACT: Sugarcane (saccharum spp.) in Brazil is managed on the basis of “production environments”. These “production environments” are used for many purposes, such as variety allocation, application of fertilizers and definition of the planting and harvesting periods. A quality classification is essential to ensure high economic returns. However, the classification is carried out by few and, most of the time, non-representative soil samples, showing unreal local conditions of soil spatial variability and resulting in classifications that are imprecise. One of the important tools in the precision agriculture technological package is the apparent electrical conductivity (ECa) sensors that can quickly map soil spatial variability with high-resolution and at low-cost. The aim of the present work was to show that soil ECa maps are able to assist classification of the “production environments” in sugarcane fields and rapidly and accurately reflect the yield potential. Two sugarcane fields (35 and 100 ha) were mapped with an electromagnetic induction sensor to measure soil ECa and were sampled by a dense sampling grid. The results showed that the ECa technique was able to reflect mainly the spatial variability of the clay content, evidencing regions with different yield potentials, guiding soil sampling to soil classification that is both more secure and more accurate. Furthermore, ECa allowed for more precise classification, where new “production environments”, different from those previously defined by the traditional sampling methods, were revealed. Thus, sugarcane growers will be able to allocate suitable varieties and fertilize their agricultural fields in a coherent way with higher quality, guaranteeing greater sustainability and economic return on their production.

Off-Grid Direction-of-Arrival Estimation Based on Steering Vector Approximation

In this paper, a novel off-grid direction-of-arrival (DOA) estimation algorithm is proposed based on steering vector approximation. The conventional multiple signal classification (MUSIC) technique estimates the DOA with a uniformly discretized grid by assuming that the true DOAs lie on the grids. In practice, this assumption is rarely satisfied. In order to improve the estimation accuracy, a dense sampling grid is required for the MUSIC technique. Besides the higher computational complexity, it is still not guaranteed that the dense sampling grids will cover the true DOAs. In order to address the off-grid problem with a lower computational complexity, we use the Taylor series expansion to approximate the steering vectors. We first construct a two-dimensional spectrum searching method to simultaneously estimate the nearest on-grid DOA and the corresponding off-grid error. To further improve the estimation accuracy, we then solve an optimization problem to obtain the accurate DOA estimation, which is formulated by the fact that the signal and noise subspaces are orthogonal to each other. Simulation results demonstrate the effectiveness of the proposed off-grid DOA estimation algorithm.

Distribution of macrozoobenthic taxa - potential indicators of vulnerable marine ecosystems in the western part of Bering Sea. 1. Anadyr Bay area

Following recent tendencies in fisheries policy to ensure both sustainability of ecosystems and conservation of economically sustainable fisheries, protection of vulnerable resources with low direct economic value comes to the focus of fisheries management on ecosystem principles. One of the problems of modern fishing is a negative impact of bottom trawling because of destruction of benthic organisms vulnerable to mechanical impacts. This by-effect of fishing could affect negatively on functioning of bottom biocenoses, reproduction of exploited species, and decrease generally productivity of vulnerable marine ecosystems (VME). Potential VME indicators are determined for the area of the Anadyr Bay in the Bering Sea on the base of results of 4 benthic surveys using bottom sampler (1985, 2005) and bottom trawl (2008, 2012), as the most common species in some macrozoobenthic groups of epifauna. They are Gersemia rubiformis for soft corals, Myxilla incrustans , Halichondria panicea , Semisuberites cribrosa for sponges, Halocynthia aurantium , Boltenia ovifera for sea squirts, Cystisella saccata , Flustra foliacea for bryozoans, Chirona evermanni for barnacles, and Gorgonocephalus eucnemis for brittle stars. Their distribution is mapped. According to their life history and feeding habits, these species-indicators are divided onto two groups: immobile sestonophages (alcyonarians, sponges, ascidians, bryozoans, cirripedians) and mobile filtrators (brittle stars). The first group prevails on hard and mixed grounds mainly along southwestern and northeastern coasts of the Anadyr Bay at the depths of 80-90 m (sponges and bryozoans - to 250 m in the Navarin Canyon) with relatively warm water, active hydrodynamics and high biological productivity. The second group represented by G. eucnemis dominates on soft sediments in the central part of the Anadyr Bay with the depths of 50-270 m occupied by the cold water pool. Quantitative distribution of brittle star, on the one hand, and barnacles with sea squirts, on the other hand, is alternative to each other. On the contrary, barnacles, sponges and sea squirts have similar distribution of the biomass, being complementary species. Distribution patterns of all species-indicators are stable for many decades. However, biomass of some these species has changed in the southern Anadyr Bay between the similar surveys conducted in the 2008 and 2012: the mean biomass of barnacle Ch. evermanni and sea squirt H. aurantium had decreased in 6.5 and 3.7 times, respectively, whereas the mean biomass of sponges, brittle star G. eucnemis and sea squirt B. ovifera did not change. Bottom trawl fishery is not active in the northwestern Bering Sea, moreover, the habitats of immobile sestonophages with hard grounds are avoided by bottom trawlers being dangerous for fishing gears, so the observed decreasing of two species abundance is presumably caused by natural reasons or is a random error of the mosaic-distributed stocks assessment with insufficiently dense sampling grid.

A novel forest state assessment methodology to support conservation and forest management planning

A new forest state assessment methodology to complement existing conservation and forestry data has been developed. The aim is to provide tools for strategic planning including spatial distribution of conservation priorities. The method is point-based using a dense systematic sampling grid and provides more detailed information than vegetation maps or forest subcompartment descriptions, but requires less effort than forest inventories. Indicators include canopy composition and structure, deadwood, herbs, microhabitats, disturbances, shrubs and regeneration. The results can inform managers about the structural and compositional diversity of forest stands in the form of thematic maps and can provide the basis for analysis of habitat suitability for forest-dwelling organisms. A smartphone application has been developed to enable electronic data collection. PostGIS and Python scripts were used in the data flow. In this paper, we outline the development of the assessment protocol, and present the sampling design and the variables recorded. The main advantages of the survey methodology are also shown by case-studies based on data collected during the first field season in 2014. The protocol has been designed for low mountain forests in Hungary, but it can be modified to fit other forest types.

Covariance vector sparsity-aware DOA estimation for monostatic MIMO radar with unknown mutual coupling

In this paper, a covariance vector sparsity-aware DOA estimation method is proposed for monostatic multiple-input multiple-output (MIMO) radar with unknown mutual coupling. The new method firstly utilizes the banded symmetric Toeplitz structure of the mutual coupling matrix (MCM) in both of the transmit and receive arrays to eliminate the unknown mutual coupling. Then a sparse representation framework of the array covariance vector is formulated for obtaining the coarse DOA estimation. Finally, a refined maximum likelihood estimation procedure is introduced to estimate the DOA based on the recovered result. Compared with conventional algorithms, the proposed method provides higher angular resolution and better angle estimation performance. Furthermore, the computational complexity of the proposed method is reasonable, because it only involves single measurement vector (SMV) problem and does not require a dense discretized sampling grid for the recovered procedure. Simulation results are used to verify the effectiveness and advantages of the proposed method.

Coarse-grained ancient coin classification using image-based reverse side motif recognition

In this paper, we propose a novel approach for the image-based classification of ancient coins by recognizing motifs minted on their reverse sides. Reverse motif recognition is achieved with dense sampling-based bag-of-visual-words model. As the bag-of-visual-words model lacks spatial information of visual words, we evaluate three types of tiling schemes to incorporate such information. Due to the specific geometric structures of the objects in the reverse motifs, spatial information is also important for a better motif recognition rate. Furthermore, a coin can be imaged under various rotations. We also investigate the type of spatial scheme more robust to such rotations. Other parameters such as the size of visual vocabulary, resolution of the dense sampling grid, number of features collected per image to construct the visual vocabulary and the number of tilings in each tiling scheme are also investigated.

Consistent assessment of trace metal contamination in surface sediments and suspended particulate matter: A case study from the Jade Bay in NW Germany

Recently, within the framework of European directives, the importance of marine monitoring programs has increased. In this study, a dense sampling grid was applied for a detailed assessment of the metal contents of surface sediments and suspended particulate matter from the Jade Bay, one of the tidal basins in the southern North Sea. The local lithogenic background was defined and compared with average shale, a common reference material. Based on the calculated non-lithogenic fraction and a cluster analysis, the metals are distributed in two groups: (i) elements of mainly natural origin (Co, Cr, and a major portion of Cd) and (ii) elements associated with anthropogenic activity (As, Cd, Cu, Ni, Pb, Sn, and Zn). However, even the metals of the second group are enriched by at most a factor of two relative to the local background, suggesting minimal anthropogenic impact. Spatial distribution maps show that the harbor area of Wilhelmshaven may be a particularly important source of metal.

Topological Equivalence between a 3D Object and the Reconstruction of Its Digital Image

Digitization is not as easy as it looks. If one digitizes a 3D object even with a dense sampling grid, the reconstructed digital object may have topological distortions and, in general, there exists no upper bound for the Hausdorff distance. This explains why so far no algorithm has been known which guarantees topology preservation. However, as we will show, it is possible to repair the obtained digital image in a locally bounded way so that it is homeomorphic and close to the 3D object. The resulting digital object is always well-composed, which has nice implications for a lot of image analysis problems. Moreover, we will show that the surface of the original object is homeomorphic to the result of the marching cubes algorithm. This is really surprising since it means that the well-known topological problems of the marching cubes reconstruction simply do not occur for digital images of r-regular objects. Based on the trilinear interpolation, we also construct a smooth isosurface from the digital image that has the same topology as the original surface. Finally, we give a surprisingly simple topology preserving reconstruction method by using overlapping balls instead of cubical voxels. This is the first approach of digitizing 3D objects which guarantees topology preservation and gives an upper bound for the geometric distortion. Since the output can be chosen as a pure voxel presentation, a union of balls, a reconstruction by trilinear interpolation, a smooth isosurface, or the piecewise linear marching cubes surface, the results are directly applicable to a huge class of image analysis algorithms. Moreover, we show how one can efficiently estimate the volume and the surface area of 3D objects by looking at their digitizations. Measuring volume and surface area of digital objects are important problems in 3D image analysis. Good estimators should be multigrid convergent, i.e., the error goes to zero with increasing sampling density. We will show that every presented reconstruction method can be used for volume estimation and we will give a solution for the much more difficult problem of multigrid-convergent surface area estimation. Our solution is based on simple counting of voxels and we are the first to be able to give absolute bounds for the surface area.

Mapping Lichen Diversity as a First Step for Air Quality Assessment

The evaluation of air quality is an important topic. It is well known that lichens have a set of characteristics that make them well suited for biomonitoring purposes. Sampling lichen diversity is not as expensive as chemical analysis, allowing a dense sampling grid and reducing the costs. Lichen diversity can be used to identify more disturbed areas, resulting from pollution, land use or ecological variables. In recent years, in order to enable extended use of lichens and to reduce ambiguities, i.e., variations due to unwanted environmental variables, efforts have been made to develop a feasible protocol for lichen sampling for biomonitoring purposes. This work aims at providing the information needed a priori for an air quality assessment study, in the form of a map showing areas where lichen diversity and abundance is lower. This study was done by sampling foliose and fruticulose lichen diversity and frequency, in a region in southwest Portugal (Sines) with large industrial facilities. A long-term study has been underway in the same area since the 1970s using lichens as bioindicators to evaluate air quality. In this work, we used a standard protocol to determine a lichen diversity value (LDV), to be used as an indicator of environmental quality. In order to reduce uncertainty concerning the type of disturbance affecting lichens, sampling sites were restricted using well-defined criteria. Whenever possible, sampling site variables were quantified. This method allowed us to reduce the many sources of variability affecting lichen diversity.

Turbulent flow structure at concordant and discordant open-channel confluences

Models of flow at river-channel confluences that consist of two concordant confluent channels with avalanche faces dipping into a scour zone are limited because this morphology may be the exception rather than the rule in nature. In this paper the mean and turbulent flow structure in the streamwise and vertical directions at both concordant and discordant laboratory confluences were examined in order to determine the effect of bed discordance on the flow field, and to assess its influence on sediment transport. Instantaneous velocities were measured with a laser Doppler anemometer using a dense spatial sampling grid. The spatial distribution of normal stress varies with bed geometry as bed discordance generates a distortion of the mixing layer between the confluent streams. Turbulent shear stress is larger in the discordant bed case and its peak is associated with the position of the mixing layer whereas for concordant beds the zone of mixing is characterised by a decrease in the Reynolds shear stress. Quadrant analysis also revealed differential dominating quadrants between the two bed geometries which will influence sediment transport routing and, consequently, the resulting bed morphology. These results highlight the need for significant modifications to current models of confluence flow dynamics in order to account for the bed configuration.