Roughness Statistics Research Articles

Automatic digital mood boards to connect users and designers with kansei engineering

One challenge for designers is how to express emotions to clients when helping them analyze ideas for the development of products. Mood boards, which comprise a set of images and words, are one of the most common tools for synthesizing a client's perception and instructing the designer about visual communication. The creation of these boards is time-consuming and becomes static before the end of the design process. This article investigates the possibility of building a kansei engineering system that is based on rough set probability statistics and is capable of linking kansei words obtained from clients with images that can be continuously collected online. The result is a proposal for a new kansei engineering procedure that contains five cycles and captures users' opinions in all phases of the design process. A subset of real data is used in the application of this procedure to a consumer product, which demonstrates the feasibility of this kind of application. The article presents a complete theoretical model of this system and its procedures and algorithms, which enables the creation of automatic mood boards and connects designers to users' needs.

Simple Regression Model for Estimating Reflectance Reduction due to Random Surface Roughness

Radiative properties of rough surfaces differ from those of smooth surfaces due to their tendency to scatter electromagnetic waves. Accurate evaluation of property change of rough surfaces requires theoretical background and numerical techniques for solving the scattering of electromagnetic waves, which is challenging and time-consuming. Therefore, this study proposes a simple regression model for estimating the reflectance reduction due to random surface roughness. Because reflectance reduction is significant when multiple reflections occur due to large surface roughness, a Monte Carlo ray-tracing (MCRT) method based on geometric optics approximation was used to evaluate reflectance reduction. Then, a regression analysis based on the numerical results of the MCRT method was implemented. A regression equation was derived as a function of the smooth-surface reflectance and a roughness slope parameter. For silicon and aluminum surfaces, the results of the proposed regression model agreed with those obtained using the MCRT method under 4.4 % error limit. Hopefully, the proposed model can be used to easily bridge between radiative properties of rough surfaces and statistics of surface roughness without relying on laborious numerical techniques for light scattering problems.

Bridging the lab‐field interface in fluvial morphology at patch‐scale: Using close‐range photogrammetry to assess surface replication and vegetation influence

AbstractIn fluvial research, comparisons of laboratory and field data sets are rare or outdated; therefore, future research would benefit from the integration of laboratory and field data sets. We use close‐range photogrammetry as a tool to help bridge that interface. Close‐range photogrammetry is a technique that is readily applied in both laboratory and field environments to capture submillimetre topographic data of natural and replica surfaces of gravel‐bed rivers. Digital Elevation Models (DEMs) of difference (DoDs) are presented to quantitatively assess the replicability of four surfaces, using the casting process. Replication results with accuracies of <35 mm, including observed localized areas of particle dislodgement, suggest casting is a suitable process to integrate laboratory and field data sets in fluvial morphology, allowing natural surfaces (e.g., from the field) to be analysed in a controlled laboratory environment. This enables the isolation of parameters, such as the microtopography of the surface or water submergence. Further, we highlight the importance of considerations of the wider scale morphology required to contextualize patch‐scale field research using close‐range photogrammetry. We demonstrate this with an example of the influence of vegetation on DEM quality and roughness statistics. These wider morphological features are difficult to simulate in the laboratory, albeit have a control on patch‐scale processes. The successful replication of natural surfaces using casting and the use of tools such as close‐range photogrammetry provide a bridge for future research that requires the integration of laboratory experiments, field experiments, and numerical modelling.

Evaluation of DEM size and grid spacing for fluvial patch-scale roughness parameterisation

Surface roughness is a term used in fluvial research without a unanimous definition. Clarification of the term and improved parameterisation is needed in future research. Improvements to the collection of topographic data, using photogrammetry, have provided accurate digital elevation models (DEMs) of field and laboratory gravel-bed patches of varied sediment size and surface structure. In this study, a moving-window process is used for analysing spatial variability within DEMs. Using this information, and in unison, the effect of DEM size and grid spacing are considered on an extensive range of roughness parameters, in order to provide insights for obtaining grain-roughness statistics. It is shown that DEM size influences the calculated roughness statistics, and the observation of plateaus in statistics for DEM window sizes above 16 × D50A in both directions (where D50A is the median grain size of the bed-surface material) suggests this as a minimum DEM size for grain-scale roughness analysis. Further, the DEM grid spacing should be 1 mm or below, in order to adequately capture grain roughness, as coarser resolutions failed to detect particle imbrication. Finally, variability in roughness parameters was evident due to natural spatial variation in gravel-bed microtopography, suggesting using a single roughness parameter is not appropriate to holistically describe the roughness of a gravel patch. As the importance of topographic information continues to grow in geomorphology, the results of this study will assist researchers in the collection and subsequent analysis of DEMs.

Comparative analysis on precise distribution-patterns of microsatellites in HIV-1 with differential statistical method

Microsatellite is a short tandem-repeated sequence found in most of the genomes. The former microsatellite analysis usually identified their positions and applied relatively rough statistics, herein, the genomic differential statistical method was raised to show precise distribution-patterns of microsatellites along the whole analyzed sequences in different extents, which processed differential on the genome and calculated the microsatellites per differential-unit. The genomic sequences of 75 Human Immunodeficiency Virus Type 1 (HIV-1) isolates, which came from three subtypes, were selected as the representatives to firstly practice the new method. The results showed that the regionally different distributions of the microsatellites in HIV-1 genome, and totally, relatively fewer microsatellites occurred in the middle of these analyzed genomic sequences. In detail, More mononucleotide microsatellites appeared in the forepart of HIV-1 genomes (5′ side), while dinucleotide microsatellites tended to be rich in the latter-half of genomes (3′ side), and most of trinucleotide microsatellites accumulated in the rear of the genomes (3′ side). Tetranucleotide to hexanucleotide microsatellites were closely absent. And there were different microsatellite distributions in 3 subtypes in some regions. The regionally different distributions of microsatellites in HIV-1 genome suggested that microsatellite distributions might have faced with powerful pressures and regional selections, which might be related with the evolution of HIV-1 genomes. The differential statistical method could help to precisely clarify microsatellite distribution-patterns to associate with series of selection and genomic evolution.

Bistatic Radar Equation for Signals of Opportunity Revisited

The bistatic radar equation currently used for simulating surface-reflected waveforms or delay-Doppler maps (DDMs), produced by signals of opportunity from global navigation satellites system (GNSS) or communication satellites, was previously derived under some limiting assumptions. One of them was the use of the Kirchhoff approximation in a geometric optics limit that assumes strong diffuse (noncoherent) scattering typical for very rough surfaces. This equation would produce an incorrect result for the case of weak diffuse scattering, or in the presence of coherent reflection. In this paper, it is shown that the assumption of strong diffuse scattering is not necessary in deriving such an equation. The derivation of a generalized bistatic radar equation is now based only on the assumption of roughness statistics being spatially homogeneous, and thus this equation is applicable for a much wider range of surface conditions and scattering geometries. This approach allows to correctly describe the transition from partially coherent scattering to completely noncoherent, strong diffuse scattering. It is demonstrated for the case of the GNSS-R DDMs simulated for a wide range of surface winds, and their transitional behavior is discussed.

Fractal dimension used for evaluation of oxidation behaviour of Fe-Al-Cr-Zr-C alloys

The article describes the possibility of using a methodology for the quantification of oxidised surfaces. The methodology is based on determining the parameters on a dividing line between alloy and air which has been generated from images of a cross-section sample. The parameters are obtained from the methodology using fractal geometry, surface roughness characterisation and statistic tools. The methodology is presented on oxidised iron aluminides (Fe-29.7Al-3.8Cr-0.3Zr-0.2C and Fe-26.4Al-2.8Cr-0.2Zr-0.6C) at high temperatures (900–1200 °C). The results show that methodology can be used for easy quantification of alloy oxidation attacks and for easy comparison of alloy oxidation resistance.

Comparing the Use of Terrestrial LiDAR Scanners and Pin Profilers for Deriving Agricultural Roughness Statistics

ABSTRACTAdequate descriptions of soil surface roughness are vital for the accurate retrieval of soil moisture maps from remote sensing products. Terrestrial laser scanners (TLSs) have the potential to offer a more comprehensive method of measuring surface roughness than traditional techniques, but are underused in this application. This research examines the use of TLSs for measuring the surface roughness of bare agricultural fields in Elora, Ontario. Through the development and application of an innovative plug-in called Roughness from Point Cloud Profiles (RPCP), this research compares TLS surface roughness characterizations to those derived from a pin profiler. In most cases, the root mean square height (RMSH) measurements obtained from the pin profiler are within 1.5 cm of those obtained from Light Detection and Ranging (LiDAR). Nearly 90% of the l measurements obtained from the TLS were >5 cm larger than those from the pin profiler. Discrepancies between pin profiler and TLS roughness characterizations can be partially explained by LiDAR shadowing in some cases, but are likely caused by other factors such as de-trending techniques, profile length, and profile orientation. The results of this research illustrate roughness variations across fields and between roughness profile orientations according to tillage structures.

Optimization of measurement and analysis parameters of burnishing surfaces

Studies related to the optimization of roughness measurements for surface topography obtained by milling and subsequent burnishing of hardened aluminum alloys, are presented. The measurements were made using the TOPO 01 contact profilometer. The best measurement parameters were selected. Additional measurements were also made with selected configuration, geometric surface analysis, and profile roughness statistics.

Seabed Structure Inferences From TREX13 Reflection Measurements

Seabed reflection measurements can be used to infer highly detailed properties of marine sediments. The information content is largely contained in the interference pattern in frequency-angle arising from wave constructive and destructive interference in a plane layer. Wide-angle reflection measurements at a ridge crest and a swale site off the coast of Panama City, FL, USA, instead show interference patterns that are highly perturbed. Interface roughness was hypothesized to be the cause of the perturbations. This hypothesis is examined using numerical simulations. Measured data and simulations at the swale site show broadband peaks and troughs due to focusing/defocusing effects from boundary curvature which perturbs the interference pattern. While the hypothesis roughness is likely correct at the swale site, the roughness statistics are not known sufficiently to validate the hypothesis. At the crest site including roughness did not lead to strong similarities with the data. Interference pattern perturbations at both sites eliminated the possibility of estimating sediment parameters from inversion of broadband wide-angle data. Instead, sediment properties were estimated by inspection and forward modeling. The estimates reasonably agree with geoacoustic properties estimated from normal incidence measurements in the swale and indicate similar sound speeds and densities on two ridges ∼6 km apart.

Engineering the crack path by controlling the microstructure

We explore the possibility of engineering the crack path by controlling a material's microstructure in order to increase its crack growth resistance. Attention is confined to a specific type of microstructure that is encountered in a variety of structural metals and alloys - second phase particles distributed in a ductile matrix. The type of controlled microstructure modeled is characterized by various sinusoidal distributions of particles with fixed mean particle spacing. Three dimensional, finite deformation small scale yielding calculations of mode I crack growth are carried out for such controlled microstructures using an elastic-viscoplastic constitutive relation for a progressively cavitating solid. The results show that appropriately engineered sinusoidal distributions of particles can give fracture toughness values 2 to 3 times greater than a random distribution of particles with the same mean particle spacing. Tearing modulus values can be increased by a factor of 1.5 to 2. The greatest crack growth resistance generally occurs when the amplitude and the wavelength of the sinusoidal distribution are increased together. When the amplitude and the wavelength of the sinusoidal distribution do not increase together the crack can jump from one crest (or trough) to the next crest (or trough) which tends to reduce the crack growth resistance. Fracture surface roughness statistics are also calculated. In contrast to the essentially universal value for random distributions of particles, the value of the computed Hurst exponent is found to depend on the amplitude and the wavelength of the sinusoidal profile. A correlation is found between the computed fracture toughness values and values of characteristic length scales of the fracture surface roughness.

Energy and discrepancy of rotationally invariant determinantal point processes in high dimensional spheres

We study expected Riesz s-energies and linear statistics of some determinantal processes on the sphere Sd. In particular, we compute the expected Riesz and logarithmic energies of the determinantal processes given by the reproducing kernel of the space of spherical harmonics. This kernel defines the so called harmonic ensemble on Sd. With these computations we improve previous estimates for the discrete minimal energy of configurations of points in the sphere. We prove a comparison result for Riesz 2-energies of points defined through determinantal point processes associated with isotropic kernels. As a corollary we get that the Riesz 2-energy of the harmonic ensemble is optimal among ensembles defined by isotropic kernels with the same trace. Finally, we study the variance of smooth and rough linear statistics for the harmonic ensemble and compare the results with the variance for the spherical ensemble (in S2).

SU-F-R-03: Classification of Glioblastoma Multiforme Molecular Subtypes Using Three-Dimensional Multi-Modal MR Imaging Features

Purpose: Positive patient outcomes with the use of aggressive concurrent chemoradiotherapy have been shown for classical and mesenchymal glioblastoma multiformae (GBM) subtypes, while not having the same positive effect for patients with neural and proneural subtypes. Quantitative MR Imaging features from multimodal MRI have been recently explored for GBM subtype classification with some promising results. We have integrated 3D textural and moment invariant features to investigate if these will strengthen the association between glioblastoma MR image features and genomic markers. Methods: 147 subjects with a complete set of T1, T1C (post-contrast T1), T2, and FLAIR imaging modalities without significant imaging artifacts acquired prior to surgery and with a known genomic subtype (Classical: 30, Mesenchymal:47, Neural:25, and Proneural:45) were chosen from TCIA database for GBM. The subject data were preprocessed and tumor and edema were contoured for the entire volume. Features were extracted from the segmented multi-modal data. These 3D features include volume, surface area, surface roughness, moment invariants, intensity statistics, and texture features. Feature selection and classification was performed using random forest. Features were extracted from the four modalities and difference fields of T1C-T1 and FLAIR-T2. Results: Random forest out-of-bag classification error of 23.91% was achieved in the classification of mesenchymal group from the proneural group using the top twenty-eight selected features. These imaging features were primarily texture features on T1C but also include a moment invariant of T1, and ROI roughness statistics of the tumor and of the edema ROIs. These features show that tumor heterogeneity, gross shape, as well the tumor and edema border smoothness distinguish the molecular subtypes. Conclusion: Using heterogeneous MRI data from the TCIA GBM database we have shown a 76% correct classification rate for GBM genomic subtypes with the same treatment protocol. Imaging features may lead to preoperative classification for improved treatment planning.

Roughness-Induced Vehicle Energy Dissipation: Statistical Analysis and Scaling

AbstractThe energy dissipated in a vehicle suspension system due to road roughness affects rolling resistance and the resulting fuel consumption and greenhouse gas emission. The key parameters driving this dissipation mechanism are identified via dimensional analysis. A mechanistic model is proposed that relates vehicle dynamic properties and road roughness statistics to vehicle dissipated energy and thus fuel consumption. A scaling relationship between the dissipated energy and the most commonly used road roughness index, the International Roughness Index (IRI), is also established. It is shown that the dissipated energy scales with IRI squared and scaling of dissipation with vehicle speed V depends on road waviness number w in the form of Vw−2. The effect of marginal probability distribution of the road roughness profile on dissipated energy is examined. It is shown that although the marginal distribution of the road profile does not affect the identified scaling relationships, the multiplicative factor...

Analysis of mirror soft-x-ray-EUV scattering using generalized continuous growth model of multiscale reliefs.

Combined computer simulations of the growth of multilayer mirrors and their exact differential reflection coefficients in the soft-x-ray-EUV range have been conducted. The proposed model describes the variation of the surface roughness of the multilayer Al/Zr mirror boundary profiles taking into account a random noise source. Theoretically calculated Al/Zr boundary profiles allow one to know real rough boundary statistics including rms roughnesses and correlation lengths and, to obtain rigorously EUV specular and diffuse reflection coefficients. The proposed integrated approach opens up a way to performing exact theoretical studies similar in accuracy to results obtained by quantitative microscopy investigations of nanoreliefs and synchrotron radiation measurements.

Effect of the porosity on the fracture surface roughness of sintered materials: from anisotropic to isotropic self-affine scaling.

To unravel how the microstructure affects the fracture surface roughness in heterogeneous brittle solids like rocks or ceramics, we characterized the roughness statistics of postmortem fracture surfaces in homemade materials of adjustable microstructure length scale and porosity, obtained by sintering monodisperse polystyrene beads. Beyond the characteristic size of disorder, the roughness profiles are found to exhibit self-affine scaling features evolving with porosity. Starting from a null value and increasing the porosity, we quantitatively modify the self-affine scaling properties from anisotropic (at low porosity) to isotropic (for porosity >10%).

1506 不規則粗面の線測定に基づく粗度統計量評価と流体摩擦抵抗の予測

1506 不規則粗面の線測定に基づく粗度統計量評価と流体摩擦抵抗の予測

The fission yeast cytokinetic contractile ring regulates septum shape and closure.

During cytokinesis, fission yeast and other fungi and bacteria grow a septum that divides the cell in two. In fission yeast closure of the circular septum hole by the β-glucan synthases (Bgs) and other glucan synthases in the plasma membrane is tightly coupled to constriction of an actomyosin contractile ring attached to the membrane. It is unknown how septum growth is coordinated over scales of several microns to maintain septum circularity. Here, we documented the shapes of ingrowing septum edges by measuring the roughness of the edges, a measure of the deviation from circularity. The roughness was small, with spatial correlations indicative of spatially coordinated growth. We hypothesized that Bgs-mediated septum growth is mechanosensitive and coupled to contractile ring tension. A mathematical model showed that ring tension then generates almost circular septum edges by adjusting growth rates in a curvature-dependent fashion. The model reproduced experimental roughness statistics and showed that septum synthesis sets the mean closure rate. Our results suggest that the fission yeast cytokinetic ring tension does not set the constriction rate but regulates septum closure by suppressing roughness produced by inherently stochastic molecular growth processes.

First-year sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 1: In situ observations

Abstract. Understanding the evolution of melt ponds on Arctic sea ice is important for climate model parameterisations, weather forecast models and process studies involving mass, energy and biogeochemical exchanges across the ocean–sea ice–atmosphere interface. A field campaign was conducted in a region of level first-year sea ice (FYI) in the central Canadian Arctic Archipelago (CAA), during the summer of 2012, to examine the potential for estimating melt pond fraction (fp) from satellite synthetic aperture radar (SAR). In this study, 5.5 GHz (C-band) dual co- (HH + VV – horizontal transmit and horizontal receive + vertical transmit and vertical receive) and cross-polarisation (HV + HH – horizontal transmit and vertical receive + horizontal transmit and horizontal receive) radar scatterometer measurements of melt-pond-covered FYI are combined with ice and pond properties to analyse the effects of in situ physical and morphological changes on backscatter parameters. Surface roughness statistics of ice and ponds are characterised and compared to the validity domains of the Bragg and integral equation model (IEM) scattering models. Experimental and model results are used to outline the potential and limitations of the co-polarisation ratio (VV / HH) for retrieving melt pond information, including fp, at large incidence angles (≥35°). Despite high variability in cross-polarisation ratio (HV / HH) magnitudes, increases at small incidence angles (<30°) are attributed to the formation of ice lids on ponds. Implications of the results for pond information retrievals from satellite C-, L- and P-band SARs are discussed.

Optically recording velocity interferometer system configurations and impact of target surface reflectance properties [invited

The utility of the optically recording velocity interferometer system (ORVIS) diagnostic to be configured to meet specific experimental needs in terms of line- and surface-imaging modes enabling direct control of the spatial, temporal, and velocity sensitivities is presented along with two case studies of gas gun testing with highly heterogeneous materials. These experiments have successfully coupled two and three ORVIS interferometers onto a single experiment. Light collection from the target reflector is of critical importance to successful test execution. By utilizing the established field of electromagnetic wave scattering from rough surfaces, the reflectance characteristics of several ORVIS reflectors are qualitatively and quantitatively analyzed in terms of the surface roughness statistics, power spectral density, and bidirectional reflectance distribution function. Insights into the impact of the surfaces on ORVIS image records are quantified. Through method development for quantitatively characterizing reflector surfaces, future experimentation can begin with an ability to tailor a reflector to a given test material and experimental arrangement.