The continuing relevance of Germany's engine for CEE andthe EU

The article looks first into the nature of the relations between Germany and the CEE countries a decade since the accession of the CEE countries to the EU. The relations are characterized as normalised and intensive with diverse levels of closeness and co-operation reflecting of the conceptual and ideological compatibility/differences. Next, the article focuses on the German attitude to the euro zone crisis. Germany has become a hegemon in the rescue effort aimed at stabilisation and economic invigoration of the euro zone. However, German hegemony has developed by default, not by design: her leading position is linked with considerable political and financial costs. Germany moved central stage and took the position of a reluctant hegemon. However, German role is contested internationally (it has not the support of the French government in key areas) as well as internally (particularly by the Federal Constitutional Court and the Bundesbank).The article argues that the new situation makes the German-CEE relations increasingly relevant for both sides. The German leadership of the EU increasing split along the north-south divide requires backing by the Northern group countries to which the CEE in general belongs. Given a number of reasons the CEE countries implement three distinctive strategies of co-operation with Germany in European politics. Also military co-operation, which remained rather limited so far, may receive new impulses, given the financial austerity. © 2013 The Regents of the University of California.

An improved memory management scheme for large scale graph computing engine GraphChi

GraphChi is the first reported disk-based graph engine that can handle billion-scale graphs on a single PC efficiently. GraphChi is able to execute several advanced data mining, graph mining and machine learning algorithms on very large graphs. With the novel technique of parallel sliding windows (PSW) to load subgraph from disk to memory for vertices and edges updating, it can achieve data processing performance close to and even better than those of mainstream distributed graph engines. GraphChi mentioned that its memory is not effectively utilized with large dataset, which leads to suboptimal computation performances. In this paper we are motivated by the concepts of 'pin ' from TurboGraph and 'ghost' from GraphLab to propose a new memory utilization mode for GraphChi, which is called Part-in-memory mode, to improve the GraphChi algorithm performance. The main idea is to pin a fixed part of data inside the memory during the whole computing process. Part-in-memory mode is successfully implemented with only about 40 additional lines of code to the original GraphChi engine. Extensive experiments are performed with large real datasets (including Twitter graph with 1.4 billion edges). The preliminary results show that Part-in-memory mode memory management approach effectively reduces the GraphChi running time by up to 60% in PageRank algorithm. Interestingly it is found that a larger portion of data pinned in memory does not always lead to better performance in the case that the whole dataset cannot be fitted in memory. There exists an optimal portion of data which should be kept in the memory to achieve the best computational performance.

Low-temperature organic Rankine cycle engine with isothermal expansion for use in desalination

Groundwater salinity is a widespread problem that contributes to the freshwater deficit of humanity. Consequently, where conventional energy supply is also lacking, organic Rankine cycle (ORC) engines are being considered as a feasible option to harness readily available low-grade heat (<180°C) to drive the desalination of the saline water via reverse osmosis (RO). However, this application is still not very well developed, and has significantly high specific energy consumption (SEC). Hence, this study explores the isothermal expansion of the ORC working fluid to achieve improved efficiency for driving a batch-RO desalination process, "DesaLink". Here, the working fluid is directly vaporized in the expansion cylinder which is heated externally by heat transfer fluid, thus obviating the need for a separate external boiler and high-pressure piping. Experimental investigations with R245fa have shown cycle efficiency of 8.8%. And it is predicted that the engine could drive DesaLink to produce 256 L of freshwater per 8 h per day, from 4000 ppm saline water, with a thermal and mechanical SEC of 2.5 and 0.36 kWh/m3, respectively, representing a significant improvement on previously reported or predicted SEC values. © 2014 © 2014 Balaban Desalination Publications. All rights reserved.

A high-efficiency solar rankine engine with isothermal expansion

Though the principle of the solar Rankine cycle is well known, with several examples reported in the literature, there is yet a scarcity of engines that could be efficiently applied in small-scale (<100 KW) applications. Hence, this paper presents a variant of the engine that uses an isothermal expansion to achieve a theoretical efficiency close to the Carnot limit. Generation of steam inside the power cylinder obviates the need for an external boiler. The device is suitable for slow-moving applications and is of particular interest for driving a batch-desalination process. Preliminary experiments have shown cycle efficiency of 16%, and a high work ratio of 0.997. ©The Author 2013. Published by Oxford University Press. All rights reserved.

Proposal and design of airy-based rocket pulses for invariant propagation in lossy dispersive media

A novel kind of Airy-based pulse with an invariant propagation in lossy dispersive media is proposed. The basic principle is based on an optical energy trade-off between different parts of the pulse caused by the chromatic dispersion, which is used to compensate the attenuation losses of the propagation medium. Although the ideal concept of the proposed pulses implies infinite pulse energy, the numerical simulations show that practical finite energy pulses can be designed to obtain a partially invariant propagation over a finite distance of propagation.

A Digital Library of Folklore Songs and Keyword-Based Search Engine

ACM Computing Classification System (1998): H3.3, H.5.5, J5.

Regrouping metric-space search index for search engine size adaptation

This work contributes to the development of search engines that self-adapt their size in response to fluctuations in workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computational resources to or from the engine. In this paper, we focus on the problem of regrouping the metric-space search index when the number of virtual machines used to run the search engine is modified to reflect changes in workload. We propose an algorithm for incrementally adjusting the index to fit the varying number of virtual machines. We tested its performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud, while calibrating the results to compensate for the performance fluctuations of the platform. Our experiments show that, when compared with computing the index from scratch, the incremental algorithm speeds up the index computation 2–10 times while maintaining a similar search performance.

Automated Assessment Through Integration of Heterogeneous Systems with a Workflow Engine

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

Combustion and emission characteristics of a typical biodiesel engine operated on waste cooking oil derived biodiesel

Waste cooking oils can be converted into fuels to provide economical and environmental benefits. One option is to use such fuels in stationary engines for electricity generation, co-generation or tri-generation application. In this study, biodiesel derived from waste cooking oil was tested in an indirect injection type 3-cylinder Lister Petter biodiesel engine. We compared the combustion and emission characteristics with that of fossil diesel operation. The physical and chemical properties of pure biodiesel (B100) and its blends (20% and 60% vol.) were measured and compared with those of diesel. With pure biodiesel fuel, full engine power was achieved and the cylinder gas pressure diagram showed stable operation. At full load, peak cylinder pressure of B100 operation was almost similar to diesel and peak burn rate of combustion was about 13% higher than diesel. For biodiesel operation, occurrences of peak burn rates were delayed compared to diesel. Fuel line injection pressure was increased by 8.5-14.5% at all loads. In comparison to diesel, the start of combustion was delayed and 90% combustion occurred earlier. At full load, the total combustion duration of B100 operation was almost 16% lower than diesel. Biodiesel exhaust gas emissions contained 3% higher CO2 and 4% lower NOx, as compared to diesel. CO emissions were similar at low load condition, but were decreased by 15 times at full load. Oxygen emission decreased by around 1.5%. Exhaust gas temperatures were almost similar for both biodiesel and diesel operation. At full engine load, the brake specific fuel consumption (on a volume basis) and brake thermal efficiency were respectively about 2.5% and 5% higher compared to diesel. Full engine power was achieved with both blends, and little difference in engine performance and emission results were observed between 20% and 60% blends. The study concludes that biodiesel derived from waste cooking oil gave better efficiency and lower NOx emissions than standard diesel. Copyright © 2012 SAE International.

Self-adapting parallel metric-space search engine for variable query loads

This research focuses on automatically adapting a search engine size in response to fluctuations in query workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computer resources to or from the engine. Our solution is to contribute an adaptive search engine that will repeatedly re-evaluate its load and, when appropriate, switch over to a dierent number of active processors. We focus on three aspects and break them out into three sub-problems as follows: Continually determining the Number of Processors (CNP), New Grouping Problem (NGP) and Regrouping Order Problem (ROP). CNP means that (in the light of the changes in the query workload in the search engine) there is a problem of determining the ideal number of processors p active at any given time to use in the search engine and we call this problem CNP. NGP happens when changes in the number of processors are determined and it must also be determined which groups of search data will be distributed across the processors. ROP is how to redistribute this data onto processors while keeping the engine responsive and while also minimising the switchover time and the incurred network load. We propose solutions for these sub-problems. For NGP we propose an algorithm for incrementally adjusting the index to t the varying number of virtual machines. For ROP we present an ecient method for redistributing data among processors while keeping the search engine responsive. Regarding the solution for CNP, we propose an algorithm determining the new size of the search engine by re-evaluating its load. We tested the solution performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud. Our experiments show that when we compare our NGP solution with computing the index from scratch, the incremental algorithm speeds up the index computation 2{10 times while maintaining a similar search performance. The chosen redistribution method is 25% to 50% faster than other methods and reduces the network load around by 30%. For CNP we present a deterministic algorithm that shows a good ability to determine a new size of search engine. When combined, these algorithms give an adapting algorithm that is able to adjust the search engine size with a variable workload.

A domain-specific search engine for the construction sector

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Effects of engine cooling water temperature on performance and emission characteristics of a CI engine operated with biofuel blend

The temperature of the coolant is known to have significant influence on engine performance and emissions. Whereas existing literature describes the effects of coolant temperature in engines using fossil derived fuels, very few studies have investigated these effects when biofuel is used. In this study, Jatropha oil was blended separately with ethanol and butanol. It was found that the 80% jatropha oil + 20% butanol blend was the most suitable alternative, as its properties were closest to that of fossil diesel. The coolant temperature was varied between 50°C and 95°C. The combustion process enhanced for both diesel and biofuel blend, when the coolant temperature was increased. The carbon dioxide emissions for both diesel and biofuel blend were observed to increase with temperature. The carbon monoxide, oxygen and lambda values were observed to decrease with temperature. When the engine was operated using diesel, nitrogen oxides emissions correlated in an opposite manner to smoke opacity; however, nitrogen oxides emissions and smoke opacity correlated in an identical manner for biofuel blend. Brake specific fuel consumption was observed to decrease as the temperature was increased and was higher on average when the biofuel was used. The study concludes that both biofuel blend and fossil diesel produced identical correlations between coolant temperature and engine performance. The trends of nitrogen oxides and smoke emissions with cooling temperatures were not identical to fossil diesel when biofuel blend was used in the engine.

A domain-specific search engine for the construction sector

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.