Can the EU become a global player?

The birth of the European Economic Community and the EURATOM represented the materialization of a new and brave idea about the role which the economical integration could play in insuring the peace, stability and prosperity of the people in member states. Nobody can make today abstraction of the presence and the role of the EU: an area of great economic, geographic, demographic and political power. Europe should also act as an important player in finding solutions to major problems such as: terrorism, climacteric changes due to global warming, ensuring energy supplies, diminishing social and economical disparities between and inside states.European Union, international problems, political power, global power

Le Rappel des Rameaux

Sound Wrappings II - “Le Rappel des Rameaux” (2009) е втората творба от цикъла Sound Wrappings, композиран като почит и рефлексия към изкуството на двамата автори на пространствени художествени инсталации Кристо (Христо Явашев) и Жан Клод (“Wrapped Walk Ways”, “Wrapped Reichstag”, “The Gates”). В тази двучастна сюрреалистична барокова творба прототипът е прочутата клавирна пиеса „Le rappel des oiseaux” на Жан-Филип Рамо, взета от сборника Piиces de Clavecin – Paris, 1724. В случая, многоезичното заглавие Sound wrappings II – Le rappel des Rameaux e пределно умишлено, още повече, че „опаковането” на името на Рамо и поставянето му в множествено число доведе до коренно и то смислово изменение – Rameaux, това са върбовите, палмовите клонки на Цветница и оттам на използването на френски Le dimanche des Rameaux – Връбница. Написах първоначално втората част на творбата, а по време на конструирането на програмата за концерта на Марио Ангелов и първата. Впрочем, в нея в два отделни момента вплетох и цели дялове на оригинала. Отначало докрай и в двете части прототипът е спазван буквално като конструкция, структури и звукови планове. Минималистичните изменения са винаги в посока на подсилване на интензивност, а не заради натрапчивост, което води до търсенето на едно почти сюрреалистично осъзнаване на интерваликата и консонанса, до преосмислянето на клъстери като барокови гроздове от звуци”. (Г. Арнаудов) Sound Wrappings II - “Le Rappel des Rameaux” (2009) is the second part of the huge Sound Wrappings cycle, composed as a tribute to and reflection on the art of environmental artists Christo and Jeanne-Claude (“Wrapped Walk Ways”, “Wrapped Reichstag”, “The Gates”). Here, in this two-part Surrealistic Baroque set (a double entendre “wrapping” of J. Ph. Rameau's masterpiece “Le Rappel des Oiseuax”), the high concentration of instrumental expression corresponds with sumptuous virtuoso rhythmical arabesques. (G. Arnaoudov

Distributed query-aware quantization for high-dimensional similarity searches

The concept of similarity is used as the basis for many data exploration and data mining tasks. Nearest Neighbor (NN) queries identify the most similar items, or in terms of distance the closest points to a query point. Similarity is traditionally characterized using a distance function between multi-dimensional feature vectors. However, when the data is high-dimensional, traditional distance functions fail to significantly distinguish between the closest and furthest points, as few dissimilar dimensions dominate the distance function. Localized similarity functions, i.e. functions that only consider dimensions close to the query, quantize each dimension independently and only compute similarity for the dimensions where the query and the points fall into the same bin. These quantizations are query-agnostic. There is potential to improve accuracy when a query-dependent quantization is used. In this paper we propose a Query dependent Equi-Depth (QED) on-the-fly quantization method to improve high-dimensional similarity searches. The quantization is done for each dimension at query time and localized scores are generated for the closest p fraction of the points while a constant penalty is applied for the rest of the points. QED not only improves the quality of the distance metric, but also improves query time performance by filtering out non relevant data. We propose a distributed indexing and query algorithm to efficiently compute QED. Our experimental results show improvements in classification accuracy as well as query performance up to one order of magnitude faster than Manhattan-based sequential scan NN queries over datasets with hundreds of dimensions

Faster Multidimensional Data Queries on Infrastructure Monitoring Systems

The analytics in online performance monitoring systems have often been limited due to the query performance of large scale multidimensional data. In this paper, we introduce a faster query approach using the bit-sliced index (BSI). Our study covers multidimensional grouping and preference top-k queries with the BSI, algorithms design, time complexity evaluation, and the query time comparison on a real-time production performance monitoring system. Our research work extended the BSI algorithms to cover attributes filtering and multidimensional grouping. We evaluated the query time with the single attribute, multiple attributes, feature filtering, and multidimensional grouping. To compare with the existing prior arts, we made a benchmarking comparison with the bitmap indexing, sequential scan, and collection streaming grouping. In the result of our experiments with large scale production data, the proposed BSI approach outperforms the existing prior arts: 3 times faster than the bitmap indexing approach on single attribute top-k queries, 10 times faster than the collection stream approach on the multidimensional grouping. While comparing with the baseline sequential scan approach, our proposed algorithm BSI approach outperforms the sequential scan approach with a factor of 10 on multiple attributes queries and a factor of 100 on single attribute queries. In the previous research, we had evaluated the BSI time complexity and space complexity on simulation data with various distributions, this research work further studied, evaluated, and concluded the BSI approach query performance with real production data

Hybrid query optimization for hard-to-compress bit-vectors

Bit-vectors are widely used for indexing and summarizing data due to their efficient processing in modern computers. Sparse bit-vectors can be further compressed to reduce their space requirement. Special compression schemes based on run-length encoders have been designed to avoid explicit decompression and minimize the decoding overhead during query execution. Moreover, highly compressed bit-vectors can exhibit a faster query time than the non-compressed ones. However, for hard-to-compress bit-vectors, compression does not speed up queries and can add considerable overhead. In these cases, bit-vectors are often stored verbatim (non-compressed). On the other hand, queries are answered by executing a cascade of bit-wise operations involving indexed bit-vectors and intermediate results. Often, even when the original bit-vectors are hard to compress, the intermediate results become sparse. It could be feasible to improve query performance by compressing these bit-vectors as the query is executed. In this scenario, it would be necessary to operate verbatim and compressed bit-vectors together. In this paper, we propose a hybrid framework where compressed and verbatim bitmaps can coexist and design algorithms to execute queries under this hybrid model. Our query optimizer is able to decide at run time when to compress or decompress a bit-vector. Our heuristics show that the applications using higher-density bitmaps can benefit from using this hybrid model, improving both their query time and memory utilization

Performance evaluation of word-aligned compression methods for bitmap indices

Bitmap indices are a widely used scheme for large read-only repositories in data warehouses and scientific databases. This binary representation allows the use of bit-wise operations for fast query processing and is typically compressed using run-length encoding techniques. Most bitmap compression techniques are aligned using a fixed encoding length (32 or 64 bits) to avoid explicit decompression during query time. They have been proposed to extend or enhance word-aligned hybrid (WAH) compression. This paper presents a comparative study of four bitmap compression techniques: WAH, PLWAH, CONCISE, and EWAH. Experiments are targeted to identify the conditions under which each method should be applied and quantify the overhead incurred during query processing. Performance in terms of compression ratio and query time is evaluated over synthetic-generated bitmap indices, and results are validated over bitmap indices generated from real data sets. Different query optimizations are explored, query time estimation formulas are defined, and the conditions under which one method should be preferred over another are formalized

Analytical and numerical study concerning the behaviour of single-sided bonded patch repairs

Adhesive bonded joints are used in the assembling of structural parts, especially of those which are made from dissimilar materials. Lightweight fibre reinforced polymer composites and other adhesive bonded components represent a major proportion of a modern aircraft. Bonded patch repair technology has been widely used to repair cracked thin-walled structures to extend their service life, because a correctly executed repair significantly enhances the structural performance.In practice, the single-sided bonded patch repair is the most used because a good solution like the double-sided repair may not be an option if the access to the structure is only available from one side.This paper presents a relatively simple and effective design procedure for the single strapped bonded joints. Also, the influence of various geometrical parameters of the joint is evaluated. The analytical development is validated based on nonlinear finite element analyses