Multiresolution gray-scale and rotation invariant textureclassification with local binary patterns

Presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prototype distributions. The method is based on recognizing that certain local binary patterns, termed "uniform," are fundamental properties of local image texture and their occurrence histogram is proven to be a very powerful texture feature. We derive a generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis. The proposed approach is very robust in terms of gray-scale variations since the operator is, by definition, invariant against any monotonic transformation of the gray scale. Another advantage is computational simplicity as the operator can be realized with a few operations in a small neighborhood and a lookup table. Experimental results demonstrate that good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary patterns     

WATER FLOW AND BINDER MIGRATION DURING DRYING OF COATED PAPER

The aim of this study has been to develop a mathematical model for water flow and binder migration in coated paper. The model can be used for simulation of the stages starting after the coating applicator including infrared and air drying sections. On the basis of the model the moisture, temperature and binder distribution can be determined across the paper thickness. Approximating equations concerning the paper properties are used in the model. We have measured the diffusion coefficient between the water and binder substances. Representative numerical examples are presented for separate and combined infrared and air drying processes.     

Repeatability estimates for milk coagulation traits and non-coagulation of milk in Finnish Ayrshire cows

Effects of systematic environmental factors and milk production and quality traits on milk coagulation properties (MCP), and on repeatability of those traits were estimated from 979 milk samples collected once a month over a period of 2 years from 83 Finnish Ayrshire cows. Estimation was based on a multitrait animal model and REML methodology. In addition, persistence of non-coagulation of milk in individual cows, and factors associated with it were established from a sub sample of 24 cows producing non-coagulating (NC) milk at least once. MCP were at their best during the first lactation, at the beginning and at the end of lactation, and during grazing seasons. Variation in MCP with systematic environmental factors was partly due to variation in composition and quality of milk, especially in pH and ln (somatic cell count, SCC). Coefficients of repeatability for milk coagulation time and curd firmness were 0.65 and 0.68. These estimates were of the same magnitude as those for protein content, but were higher than those for daily milk yield, fat content, pH, and SCC. Based on the repeatability estimates for the milk coagulation traits and effects of the environmental factors, cows should be sampled at least three times during a lactation to estimate reliably breeding values for the milk coagulation traits. A total of 10% of the milk samples did not coagulate in 30 min after addition of rennet. Cows that produced NC milk at least once (30% of the cows) could be classified into those that produced NC milk only a few times during a lactation and those that produced NC milk at almost every sampling. Based on logistic regression analyses, peak and mid-lactation, high milk yield, low protein and fat content and high pH increased the risk of non-coagulation of milk.     

Simulation of light propagation by local spherical interface approximation

A new local elementary interface approximation is introduced for the modeling of wave propagation through interfaces between homogeneous media. The incident wave and the surface profile are approximated locally by a spherical wave and a spherical surface, respectively. The wave field travels through the modulated structure according to the laws of geometrical optics, being refracted by the surface and propagating to the output plane locally as a geometric spherical wave. Diffraction theory is applied to propagate the field from the output plane onwards. We provide comparisons of the method with the thin-element approximation, the local plane-wave and interface approach, and rigorous diffraction theory using a sinusoidal surface-relief grating as an example. We illustrate the power of the new method by applying it to the analysis of a diffractive beam splitter.     

An efficient variable neighborhood search heuristic for very large scale vehicle routing problems

In this paper, we present an efficient variable neighborhood search heuristic for the capacitated vehicle routing problem. The objective is to design least cost routes for a fleet of identically capacitated vehicles to service geographically scattered customers with known demands. The variable neighborhood search procedure is used to guide a set of standard improvement heuristics. In addition, a strategy reminiscent of the guided local search metaheuristic is used to help escape local minima. The developed solution method is specifically aimed at solving very large scale real-life vehicle routing problems. To speed up the method and cut down memory usage, new implementation concepts are used. Computational experiments on 32 existing large scale benchmarks, as well as on 20 new very large scale problem instances, demonstrate that the proposed method is fast, competitive and able to find high-quality solutions for problem instances with up to 20,000 customers within reasonable CPU times.     

Estimation of tree crown volume from airborne lidar data using computational geometry

Although simple geometrical shapes are commonly used to describe tree crowns, computational geometry enables calculation of the individual crown properties directly from airborne lidar point clouds. Our objective was to calculate crown volumes (CVs) using this technique and validate the results by comparing them with field-measured values and modelled ellipsoidal crowns. The CVs of standing trees were obtained by measuring the crown radii at different heights, integrating the obtained crown profiles as solids of revolution, and finally averaging the volumes obtained from the four separate profiles. With the lidar data, the CVs were extracted using 3D alpha shape and 3D convex hull techniques. Crown base heights (CBHs) were also estimated from the lidar data and used to exclude echoes from the understory, which was also done using field-based CBHs to exclude this error source. The results show that the field-measured CVs had a high correlation with lidar-based estimates (best R ² = 0.83), but the lidar-based estimates were generally smaller than the field values. The best correspondence (root mean square difference (RMSD) = 45.0%, average difference = –24.7%) was obtained using the convex hull of the point data and field-measured CBH. The CBHs were consistently overestimated (RMSD = 37.3%; average difference = –20.0%), especially in spruces with long crowns. Thus using lidar-based CBH also increased the inaccuracy of the CV estimates. While the underestimation of CV is mainly explained by the inadequate number of echoes from the lower regions of the crowns, the CVs obtained from the lidar were better than those obtained with ellipsoids fitted by using general models for crown dimensions. The utility of the estimated CVs in the prediction of stem diameter is also demonstrated.     

High-level parameterizable area estimation modeling for ASIC designs

Architectural design space exploration and early area budgeting for ASIC and IP block development require accurate high level gate count estimation methods without requiring the hardware being fully specified. The proposed method uses hierarchical and parameterizable models requiring minimal amount of information about the implementation technology to meet this goal. The modeling process flow is to: (1) create a block diagram of the design, (2) create a model for each block, and (3) sum up estimates of all sub-blocks by supplying the correct parameters to each sub-model. We discuss the model creation for a few parameterized library blocks as well as three communication blocks and a processor core from real IC projects ranging from 22 to 250 kgates. The average relative estimation error of the proposed method for the library blocks is 3.2% and for the real world examples 4.0%. The best application of this method is early in the design phase when different implementation architectures are compared.     

The energy release rate and the J-integral in nonlocal micropolar field theory

The recent theory of nonlocal micropolar continuum is used to derive explicit expressions for both the energy release rate and J-integral. It was shown that this J-integral has a physical meaning of the energy release rate and, for homogeneous body with the straight crack, is path independent. It was also shown that the influence of nonlocality is contained in J-integral which allows one to discuss several special cases.     

Direct synthesis of carbon nanofibers on the surface of copper powder

A novel approach to synthesize carbon nanofibers (CNFs) directly on the surface of metal μm-sized particles to evenly disperse the carbon nanomaterials in a composite material was proposed. As a metal matrix, 5–10 μm copper particles were utilized. As a carbon source, C₂H₂, CH₄ and CO were examined. The best conditions were found to be in C₂H₂ (30 cm³/min) and H₂ (260 cm³/min) atmosphere at the temperature of 750 °C. The composites based on copper and CNFs prepared by vacuum hot pressing showed the increase in hardness from 35 to 60 kg/mm² almost retaining pure copper electrical properties.     

A Simulation Model for Malt Enzyme Activities in Kilning

The drying and survival of enzyme activities during the kilning of malt were modelled. A set of experiments at the micro‐malting scale was carried out for model identification and validation. The dynamic models predict the effects of the kilning programme, i.e. the temperature profile on grain moisture, activities of β‐glucanase, α‐amylase and limit‐dextrinase, and diastatic power during kilning. The process behaviour was analysed by simulations. The predictions match the malting experience well. The models increase the general understanding of enzyme inactivation and can be used in planning the kilning programme.