Institute for Parallel Processing

The cement production is accompanied by generation of fine dust, known as cement kiln dust (CKD), formed during the high-temperature processing of raw materials in the rotary kilns. This study focusses on characterizing CKD from Bulgarian cement plants and explore its physical and chemical properties. The study includes analysing CKD samples from three local cement plants using techniques such as laser dif fraction, XRD, XRF, FT-IR, and SEM. Variations have been observed in their physical, chemical, and mineralogical properties likely due to differences in raw materials, kiln conditions and the use of alternative fuels. This research provides valuable local data that can guide sustainable CKD management and utilization strategies, contributing to reduced waste and environmental impact in cement production.

People with autism spectrum disorder (ASD) experience reading comprehension difficulties, often misinterpreting complex texts, metaphors, and idioms. We have developed and tested a new assistive technology tool for adaptive, personalized text simplification, called Open Book. This tool is an open-sourced, online platform that uses Natural Language Processing with the specific aim of assisting reading and aiding understanding of written text for people with ASD. The accessibility and effectiveness of Open Book was tested by examining the differences in text comprehension scores between the original texts and texts that were simplified by Open Book tool, randomly allocated to study participants. Two hundred forty-three participants (153 adults and 90 adolescents) with high-functioning ASD were recruited in the UK, Spain, and Bulgaria. Regarding the primary outcome, results showed that both adults and adolescents with ASD gave more correct answers for the simplified (M = 11.2, SD = 4.1) than original texts (M = 10, SD = 4.1; p < 0.001). This finding was consistent across age groups and countries. Regarding the secondary outcome, when participants were asked to blindly rate how easy was to understand each text, simplified texts were rated as easier (M = 7.6, SD = 2.4) to understand than the original texts (M = 8.7, SD = 2.6; p < 0.001). The Open Book software seems to have the potential to be a useful tool in assisting reading among people with ASD. Our findings support our primary hypothesis that texts simplified through Open Book were easier to comprehend compared to original texts.

The theoretical equivalence of the Wigner and ballistic Boltzmann equations for up to quadratic electric potentials provides the convenient opportunity to evaluate stochastic algorithms for the solution of the former equation with the analytic solutions of the latter equation - Liouville trajectories corresponding to acceleration due to a constant electric field. The direct application of this idea is impeded by the fact that the analytic transformation of the first equation into the second involves generalized functions. In particular, the Wigner potential acts as a derivative of the delta function which gives rise to a Newtonian accelerating force. The second problem is related to the discrete nature of the Wigner momentum space. These peculiarities incorporate unphysical effects in the approximate Wigner solution, which tends to the Boltzmann counterpart in a limiting case only.

Abstract The Wigner equation provides an interesting mathematical limit, which recovers the constant field, ballistic Boltzmann equation. The peculiarities of a recently proposed Monte Carlo approach for solving the transient Wigner problem, based on generation and annihilation of particles are summarized. The annihilation process can be implemented at consecutive time steps to improve the Monte Carlo resolution. We analyze theoretically and numerically this process applied to the simulation of important quantum phenomena, such as time-dependent tunneling of a wave packet through potential barriers.KeywordsMonte Carlo ResolutionWigner EquationTime-dependent TunnelingRenormalization TechniqueInitial Wave VectorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

One of the important claims that permeate the current view of information management is that ontological demarcation of data and semantic information processing are going to allow us to infuse intelligence into information systems. Separately, it is claimed that software agents, combined with ontologies will be the foundation ofWeb 4.0. In our work we are developing an agent-team-based resource management and brokering infrastructure for computational grids. The proposed meta-level middleware is to utilize both software agents and ontologies. In this context, the aim of this chapter is twofold. First, we present an overview of found efforts to develop ontologies to be used in grid and agent-grid computing. Second, we analyze which one of them, if any, should be the base ontology for the system under development.

Numerical homogenization is used for upscaling of the linear elasticity tensor of strongly heterogeneous microstructures The implemented 3D algorithm is described in terms of six auxiliary elastic problems for the reference volume element (RVE) Rotated trilinear Rannacher- Turek finite elements are used for discretization of the involved subproblems A parallel PCG method is implemented for efficient solution of the arising large-scale systems with sparse, symmetric, and positive semidefinite matrices The implemented preconditioner is based on modified incomplete Cholesky factorization MIC(0). The numerical homogenization scheme is derived on the assumption of periodic microstructure This implies periodic boundary conditions (PBCs) on the RVE From algorithmic point of view, an important part of this study concerns the incorporation of PBCs in the parallel MIC(0) solver. Numerical upscaling results are shown The test problem represents a trabecular bone tissue, taking into account the elastic response of the solid phase The voxel microstructure of the bone is extracted from a high resolution computer tomography image The presented results evidently demonstrate that the bone tissues could be substantially anisotropic. The computations are performed on IBM Blue Gene/P machine at the Bulgarian Supercomputing Center.

Sobol sequence is the most widely used low discrepancy sequence for numerical solving of multiple integrals and other quasi-Monte Carlo computations Owen first proposed scrambling of this sequence through permutation in a manner that maintained its low discrepancy Scrambling is necessary not only for error analysis but for parallel implementations Good scrambling is especially important for GRID applications However, scrambling is often difficult to implement and time consuming In this paper we propose fast generation of Sobol sequence with Owen scrambling, tuned to specific hardware Numerical and timing results, demonstrating the advantages of our approach are presented and discussed.

UNI–DEM is an Eulerian model for studying long range transport of air pollutants. The computational domain of the model covers Europe and some neighbour parts of Atlantic ocean, Asia and Africa. The model mainly is developed in the National Environmental Research Institute of Denmark, located at Roskilde. If UNI–DEM model is to be applied on a large space domain by using fine grids, then its discretization leads to a huge computational problem. If the space domain is discretized by using a (480 x 480) grid and the number of chemical species studied by the model is 35, then several systems of ordinary differential equations containing 8 064 000 equations have to be treated at every time-step (the number of time-steps being typically several thousand). If a three-dimensional version of the same air pollution model is to be used, then the figure above must be multiplied by the number of layers. This implies that such a model as UNI–DEM must be run only on high-performance computer architectures, like IBM Blue Gene/P. The implementatation of such complex large–scale model on each new computer is a non trivial task. Analysis of the runs of UNI–DEM performed until now on IBM Blue Gene/P computer is presented and some preliminary results on performance, speed ups and efficiency are discussed.

Abstract Domain knowledge is essential resource in Information Extraction (IE) from free text since it supports the decisions about structuring the extracted text objects into domain statements. Thus manually-created conceptual structures enable the semantic representation of textual information. This paper discusses the role of domain knowledge in information extraction of structured data from patient-related texts. The article shows that domain knowledge is encoded not only in the conceptual structures, which provide the ontological framework for the IE task, but also in the IE templates that are designed to capture domain semantics. A prototype system and IE examples of domain knowledge usage are considered together with results of the current prototype evaluation.KeywordsThyroid GlandDomain KnowledgeNatural Language ProcessingInformation ExtractionEntity RecognitionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.