Almost constant-time 3D nearest-neighbor lookup using implicit octrees

A recurring problem in 3D applications is nearest-neighbor lookups in 3D point clouds. In this work, a novel method for exact and approximate 3D nearest-neighbor lookups is proposed that allows lookup times that are, contrary to previous approaches, nearly independent of the distribution of data and query points, allowing to use the method in real-time scenarios. The lookup times of the proposed method outperform prior art sometimes by several orders of magnitude. This speedup is bought at the price of increased costs for creating the indexing structure, which, however, can typically be done in an offline phase. Additionally, an approximate variant of the method is proposed that significantly reduces the time required for data structure creation and further improves lookup times, outperforming all other methods and yielding almost constant lookup times. The method is based on a recursive spatial subdivision using an octree that uses the underlying Voronoi tessellation as splitting criteria, thus avoiding potentially expensive backtracking. The resulting octree is represented implicitly using a hash table, which allows finding the leaf node a query point belongs to with a runtime that is logarithmic in the tree depth. The method is also trivially extendable to 2D nearest neighbor lookups.     

Application of feedforward neural network in the study of dissociated gas flow along the porous wall

This paper concerns the use of feedforward neural networks (FNN) for predicting the nondimensional velocity of the gas that flows along a porous wall. The numerical solution of partial differential equations that govern the fluid flow is applied for training and testing the FNN. The equations were solved using finite differences method by writing a FORTRAN code. The Levenberg–Marquardt algorithm is used to train the neural network. The optimal FNN architecture was determined. The FNN predicted values are in accordance with the values obtained by the finite difference method (FDM). The performance of the neural network model was assessed through the correlation coefficient (r), mean absolute error (MAE) and mean square error (MSE). The respective values of r, MAE and MSE for the testing data are 0.9999, 0.0025 and 1.9998 · 10^?5.     

GPS telemetry of energetic-technical and technological parameters at open pit mines

Application of GPS in mining and geology has proved to be of ever increasing importance since recently. GPS is used for positioning both researching and exploitation drill holes, mining facilities, equipment, machines, when monitoring slopes and falls, mining facilities dimensioning, navigation of machines, roads tracing, etc. The paper presents a pilot system for surveillance and monitoring of energetic and technological parameters at open pit mines, developed at the “Jazovnik” open pit mine for experimental purposes. __________ Translated from Fiziko-Tekhnicheskie Problemy Razrabotki Poleznykh Iskopaemykh, No. 4, pp. 90–94, July–August, 2008.     

Longitudinal air permeability of pinewood with beetle transmitted blue-stain

The mountain pine beetle epidemic is destroying an extensive volume of the lodgepole pine forests being one of the most commercially harvested trees in British Columbia. The purpose of this study was to test the permeability of wood of four different classes regarding the time of the beetle attack. The experiments used the ‘‘falling water’’ unsteady-steady method of measuring superficial air permeability. The results showed that the specific permeability is not significantly different between the infested classes tested. The same conclusion could be reached for comparisons of uninfected and infested wood.     

Parking assistance using dense motion-stereo

The ability of generating and interpreting a three-dimensional representation of the environment in real-time is one of the key technologies for autonomous vehicles. While active sensors like ultrasounds have been commercially used, their cost and precision is not favorable. On the other hand, integrating passive sensors, like video cameras, in modern vehicles is quite appealing especially because of their low cost. However, image processing requires reliable real-time algorithms to retrieve depth from visual information. In addition, the limited processing power in automobiles and other mobile platforms makes this problem even more challenging. In this paper we introduce a parking assistance system which relies on dense motion-stereo to compute depth maps of the observed environment in real-time. The flexibility and robustness of our method is showcased with different applications: automatic parking slot detection, a collision warning for the pivoting ranges of the doors and an image-based rendering technique to visualize the environment around the host vehicle. We evaluate the accuracy and reliability of our system and provide quantitative and qualitative results. A comparison to ultrasound and feature-based motion-stereo solutions shows that our approach is more reliable.     

Prospects of wind energy sector development in Serbia with relevant regulatory framework overview

The growth of the renewable energy sector in the world in the first decade of the twenty-first century was rapid. Wind energy sector was one of the fastest growing renewable energy technologies. In this paper, authors have tried to review the current state of wind power utilization in Serbia as one of the most penetrating RES technologies in the world. The brief overview of electric power sector in Serbia was given in order to describe the environment for emerging wind energy sector development. Sufficient wind energy resources were identified in several regions of the country. Current energy policy in Serbia was reviewed in terms of the regulations that have to be followed in order to meet the requirements for RES power plants, i.e. wind power plant construction. In subsequent section short reviews of wind energy projects which are in their initial phases are provided. The wind energy sector in Serbia is emerging despite the difficulties faced by the investors, regulatory bodies and other shareholders, in the course of the past several years. There is an urgent need of a broader transfer of specific knowledge and technologies related to wind farms and wind turbines in order to speed up the current wind energy sector development.     

Multivariate statistical analysis of Raman images of a pharmaceutical tablet

This paper describes the application of principal component analysis (PCA) and independent component analysis (ICA) to identify the reference spectra of a pharmaceutical tablet's constituent compounds from Raman spectroscopic data. The analysis shows, first with a simulated data set and then with data collected from a pharmaceutical tablet, that both PCA and ICA are able to identify most of the features present in the reference spectra of the constituent compounds. However, the results suggest that the ICA method may be more appropriate when attempting to identify unknown reference spectra from a sample. The resulting PCA and ICA models are subsequently used to estimate the relative concentrations of the constituent compounds and to produce spatial distribution images of the analyzed tablet. These images provide a visual representation of the spatial distribution of the constituent compounds throughout the tablet. Images associated with the ICA scores are found to be more informative and not as affected by measurement noise as the PCA based score images. The paper concludes with a discussion of the future work that needs to be undertaken for ICA to gain wider acceptance in the applied spectroscopy community.     

Internal multiple-scattering hole-enhanced Raman spectroscopy: improved backscattering Fourier transform Raman sampling in pharmaceutical tablets utilizing cylindrical-conical holes

The benefits of Raman signal enhancement and improved measurement precision are demonstrated using 180° backscattering Fourier transform Raman (FT-Raman) spectroscopy from drilled cylindrical-conical holes within pharmaceutical tablet cores. Multiple scattering of the incident laser light within the holes results in an increased Raman signal due to the larger Raman sampling volume. This is important for overcoming typical sub-sampling issues encountered when employing FT-Raman backscattering of heterogeneous pharmaceutical tablets. Hole depth and diameter were found to be important experimental parameters and were optimized to yield the greatest signal enhancement. The FT-Raman spectra collected using backscattering from cylindrical-conical holes is compared to typical 180° backscattering from flat surfaces using tablet cores of Excedrin? and Vivarin?. Raman chemical images are used to establish a representative sampling area. We observe a three- to five-fold increase in the Raman intensity and a two-fold improvement in the measurement precision when sampling from cylindrical-conical holes rather than classic backscattering from flat tablet cores. Self-absorption effects on analyte band ratios are negligible in the fingerprint region but are more significant at the higher near-infrared (NIR) absorbances found in the C-H/O-H/-N-H stretching region. The sampling technique will facilitate developing quantitative FT-Raman methods for application to pharmaceutical tablets using the fingerprint spectral region.     

Sensitivity of the Red River Basin Flood Protection System to Climate Variability and Change

An original modeling framework for assessment of climate variation and change impacts on the performance of complex flood protection system has been implemented in the evaluation of the impact of climate variability and change on the reliability, vulnerability and resiliency of the Red River Basin flood protection system (Manitoba, Canada). The modeling framework allows for an evaluation of different climate change scenarios generated by the global climate models. Temperature and precipitation are used as the main factors affecting flood flow generation. System dynamics modeling approach proved to be of great value in the development of system performance assessment model. The most important impact of climate variability and change on hydrologic processes is reflected in the change of flood patterns: flood starting time, peak value and timing. The results show increase in the annual precipitation and the annual streamflow volume in the Red River basin under the future climate change scenarios. Most of the floods generated using three different climate models had an earlier starting time and peak time. The assessment of the performance of Red River flood protection system is based on the flood flows, the capacity of flood control structures and failure flow levels at different locations in the basin. In the Assiniboine River Basin, higher reliabilities at downstream locations are obtained indicating that Shellmouth reservoir plays an important role in reducing downstream flooding. However, a different trend was identified in the Red River Basin. The study results show that flood protection capacity of the Red River infrastructure is sufficient under low reliability criteria but may not be sufficient under high reliability criteria.