Identification of rockfall source areas using the seed cell concept and bivariate susceptibility modelling

The objective of this research was to prepare a rockfall susceptibility map. Explorations were conducted in the Dubra?ina River basin (Croatia). The input data included a geological map, an orthophoto and a 1-m digital terrain model (DTM). After a talus inventory was prepared, the seed cell concept was applied to define the rockfall source areas. The contributing factors (predictors) of rockfalls were evaluated by the chi-squared test. The analysis confirmed the following predictors: CORINE land cover, lithology, slope, aspect, distance from a spring, distance from a road, distance from a fault, distance from a stream, and distance from the rock-soil geological boundary. A matrix pairwise comparison of the predictor ratings was used to define the most significant contributing factors. The predictors that affected the susceptibility map in the share of 86.3% were the slope (61.6%), lithology (13.4%), CORINE land cover (6.2%), and distance from the rock-soil geological boundary (5.1%). Two susceptibility maps were prepared: one using all nine contributing factors and another using the four most significant factors. The analysis showed that both maps were good, with the same areas under the receiver operating characteristic (ROC) curves. The map prepared with only four contributing factors can be considered a better map due to its more precise spatial definition of critical areas. It can be concluded that geological map, 1-m DTM and orthophoto provide enough data to prepare reliable rockfall susceptibility map. The application of the bivariate statistical zonation method called the “frequency ratio method” was proven to be successful. This research demonstrates that the application of the seed cell concept can be useful to speed up the process of rockfall source area detections in large research regions.

     

Contribution of marine and continental aerosols to the content of major ions in the precipitation of the central Mediterranean

The region of the investigated receptor is situated in the southern part of the Adriatic Sea in the Mediterranean. The measuring station is located on the seashore, which, being considered as a border area, is representative for the qualitative and quantitative estimation of the influence of marine and continental aerosols on the content of major ions in precipitation. In the sampling period, precipitation in the region of the investigated receptor was more abundant during the summer and autumn than during the winter and spring. The most frequent precipitation heights were up to 20 mm, while high precipitation came exclusively from the continental region. The results of the measurements of ions readily soluble in water were used for the differentiation of marine from continental contributions of primary and secondary aerosols to their content in the precipitation. Using PCA, it was shown that main contribution of Cl(-), Na(+) and Mg(2+) came from primary marine aerosols, while the contribution from continental sources was dominant for the content of SO(4)(2-), NO(3)(-), NH(4)(+) and Ca(2+) in the precipitation. The continental origin of Ca(2+) was from a primary source, while SO(4)(2-), NO(3)(-) and NH(4)(+) were representatives of secondary aerosols produced by reactions between acid oxides and alkaline species in the atmosphere, but SO(4)(2-) and NO(3)(-) also exist in the precipitation as free acids. The origin of the trace elements Cd, Cu, Pb and Zn in the precipitation came from anthropogenic emission sources. The results obtained in this work are based on experimental data from 609 samples collected during the period 1995-2000.     

Location of deuteron sites in the proton conducting perovskite BaZr0.50In0.50O3−y

High-resolution neutron powder diffraction data have been collected on deuterated and dried samples of the perovskite BaZr_0.5In_0.5O_2.75 at 5 K and room temperature, respectively. Inspection of Fourier nuclear density maps for the deuterated phase have allowed the deuteron position to be refined on a 12h (1/2, y, 0) crystallographic site, with y = 0.217(4) yielding a chemically reasonable OD distance of 0.92(2) Å. Evidence for anisotropy of the deuteron position is also found consistent with a 24k crystallographic site (0.56, 0.21, 0) indicative of displacements of the ion towards neighbouring oxygen ions. The presence of static oxygen disorder in both the dried and deuterated samples is apparent from the structural analyses. Raman spectra confirm short range deviations from cubic symmetry for both dried and hydrated samples.     

Subspace tracking with adaptive threshold rank estimation

In frequency and direction of arrival (DOA) tracking problems, singular value decomposition (SVD) can be used to track the signal subspace. Typically, for a problem sizen, only a few, sayr dominant eigencomponents need to be tracked, wherern. In this paper we show how to modify the Jacobi-type SVD to track only ther-dimensional signal subspace by forcing the (n-r)-dimensional noise subspace to be spherical. Therby, the computational complexity is brought down fromO(n²) toO(nr) per update. In addition to tracking the subspace itself, we demonstrate how to exploit the structure of the Jacobi-type SVD to estimate the signal subspace dimension via a simple adptive threshold comparison technique. Most available computationally efficient subspace tracking algorithms rely on off-line estimation of the signal subspace dimension, which acts as a bottleneck in real-time parallel implementations. The noise averaged Jacobi-type SVD updating algorithm presented in this paper is capable of simultaneously tracking the signal subspace and its dimension, while preserving both the low computational cost ofO(nr) and the parallel structure of the method, as demonstrated in a systolic implementation. Furthermore, the algorithm tracks all signal singular values. Their squares are estimates of the powers in the orthogonal modes of the signal. Thus, applications of the algorithm are not limited to only DOA and frequency tracking where information about the powers of signal components is not exploited.     

The number of spanning trees of a graph with given matching number

The number of spanning trees of a graph G is the total number of distinct spanning subgraphs of G that are trees. In this paper, we present sharp upper bounds for the number of spanning trees of a graph with given matching number.     

Annotating patient clinical records with syntactic chunks and named entities: the Harvey Corpus

The free text notes typed by physicians during patient consultations contain valuable information for the study of disease and treatment. These notes are difficult to process by existing natural language analysis tools since they are highly telegraphic (omitting many words), and contain many spelling mistakes, inconsistencies in punctuation, and non-standard word order. To support information extraction and classification tasks over such text, we describe a de-identified corpus of free text notes, a shallow syntactic and named entity annotation scheme for this kind of text, and an approach to training domain specialists with no linguistic background to annotate the text. Finally, we present a statistical chunking system for such clinical text with a stable learning rate and good accuracy, indicating that the manual annotation is consistent and that the annotation scheme is tractable for machine learning.     

A novel neural network based approach to latent overlapped fingerprints separation

Multimedia Tools and Applications - Overlapped fingerprints are often found in latent fingerprints lifted from crime scenes and in live-scan fingerprint images when the surface of fingerprint...     

Dynamic Virtual Resource Allocation in Virtualized multi-RAT Cellular Networks

The legacy wireless systems are designed to exploit static configuration and deployment, and cannot handle the discrepancies of the spatio-temporal traffic demand. Cloud RAN (C-RAN) is a novel flexible radio technology that utilizes the virtualization concepts and can efficiently address the static deployment of conventional wireless systems. The C-RAN also leverages high radio network flexibility by introducing the network function virtualization approach to wireless networks. This paper presents a novel C-RAN platform that virtualizes and operates with full GSM and LTE systems. The presented platform is solely based on open-source and off the shelf solutions, providing easy implementation, low cost and high scalability. The paper also introduces a novel dynamic resource allocation algorithm that facilitates the C-RAN’s optimal performance in dynamic scenarios. The proposed algorithm is analyzed and validated on the presented C-RAN platform. The results of the performance analysis clearly show the advantages of the proposed dynamic resource allocation algorithm. Moreover, they prove the applicability of the C-RAN platform for variety of different scenarios.     

Predicting piezometric water level in dams via artificial neural networks

The safety control of dams is based on measurements of parameters of interest such as seepage flows, seepage water clarity, piezometric levels, water levels, pressures, deformations or movements, temperature variations, loading conditions, etc. Interpretation of these large sets of available data is very important for dam health monitoring and it is based on mathematical models. Modelling seepage through geological formations located near the dam site or dam bodies is a challenging task in dam engineering. The objective of this study is to develop a feedforward neural network (FNN) model to predict the piezometric water level in dams. An improved resilient propagation algorithm has been used to train the FNN. The measured data have been compared with the results of FNN models and multiple linear regression (MLR) models that have been widely used in analysis of the structural dam behaviour. The FNN and MLR models have been developed and tested using experimental data collected during 9 years. The results of this study show that FNN models can be a powerful and important tool which can be used to assess dams.