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Cost models are an essential part of database systems, as they are the basis of query performance optimization. Based on predictions made by cost models, the fastest query execution plan can be chosen and executed or algorithms can be tuned and optimised. In-memory databases shifts the focus from disk to main memory accesses and CPU costs, compared to disk based systems where input and output costs dominate the overall costs and other processing costs are often neglected. However, modelling memory accesses is fundamentally different and common models do not apply anymore. This work presents a detailed parameter evaluation for the plan operators scan with equality selection, scan with range selection, positional lookup and insert in in-memory column stores. Based on this evaluation, a cost model based on cache misses for estimating the runtime of the considered plan operators using different data structures is developed. Considered are uncompressed columns, bit compressed and dictionary encoded columns with sorted and unsorted dictionaries. Furthermore, tree indices on the columns and dictionaries are discussed. Finally, partitioned columns consisting of one partition with a sorted and one with an unsorted dictionary are investigated. New values are inserted in the unsorted dictionary partition and moved periodically by a merge process to the sorted partition. An efficient attribute merge algorithm is described, supporting the update performance required to run enterprise applications on read-optimised databases. Further, a memory traffic based cost model for the merge process is provided.
The development of self-adaptive software requires the engineering of an adaptation engine that controls and adapts the underlying adaptable software by means of feedback loops. The adaptation engine often describes the adaptation by using runtime models representing relevant aspects of the adaptable software and particular activities such as analysis and planning that operate on these runtime models. To systematically address the interplay between runtime models and adaptation activities in adaptation engines, runtime megamodels have been proposed for self-adaptive software. A runtime megamodel is a specific runtime model whose elements are runtime models and adaptation activities. Thus, a megamodel captures the interplay between multiple models and between models and activities as well as the activation of the activities. In this article, we go one step further and present a modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that considerably eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular for feedback loops. Megamodels are kept explicit and alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops, their runtime models, and adaptation activities explicit at a higher level of abstraction. Moreover, it enables complex solutions where multiple feedback loops interact or even operate on top of each other. Finally, it leverages the co-existence of self-adaptation and off-line adaptation for evolution.
Grammatica Grandonica
(2013)
In May 2010, Johann Ernst Hanxleden’s Grammatica Grandonica was rediscovered in Montecompatri (Lazio, Rome). Although historiographers attached much weight to the nearly oldest western grammar of Sanskrit, the precious manuscript was lost for several decades. The first aim of the present digital publication is to offer a photographical reproduction of the manuscript. This facsimile is accompanied by a double edition: a facing diplomatic edition with the Sanskrit in Malayāḷam script, followed by a transliterated established text.
Various synthetic approaches were explored towards the preparation of poly(N-substituted glycine) homo/co-polymers (a.k.a. polypeptoids). In particular, monomers that would facilitate in the preparation of bio-relevant polymers via either chain- or step-growth polymerization were targeted. A 3-step synthetic approach towards N-substituted glycine N-carboxyanhydrides (NNCA) was implemented, or developed, and optimized allowing for an efficient gram scale preparation of the aforementioned monomer (chain-growth). After exploring several solvents and various conditions, a reproducible and efficient ring-opening polymerization (ROP) of NNCAs was developed in benzonitrile (PhCN). However, achieving molecular weights greater than 7 kDa required longer reaction times (>4 weeks) and sub-sequentially allowed for undesirable competing side reactions to occur (eg. zwitterion monomer mechanisms). A bulk-polymerization strategy provided molecular weights up to 11 kDa within 24 hours but suffered from low monomer conversions (ca. 25%). Likewise, a preliminary study towards alcohol promoted ROP of NNCAs suffered from impurities and a suspected alternative activated monomer mechanism (AAMM) providing poor inclusion of the initiator and leading to multi-modal dispersed polymeric systems. The post-modification of poly(N-allyl glycine) via thiol-ene photo-addition was observed to be quantitative, with the utilization of photo-initiators, and facilitated in the first glyco-peptoid prepared under environmentally benign conditions. Furthermore, poly(N-allyl glycine) demonstrated thermo-responsive behavior and could be prepared as a semi-crystalline bio-relevant polymer from solution (ie. annealing). Initial efforts in preparing these polymers via standard poly-condensation protocols were insufficient (step-growth). However, a thermally induced side-product, diallyl diketopiperazine (DKP), afforded the opportunity to explore photo-induced thiol-ene and acyclic diene metathesis (ADMET) polymerizations. Thiol-ene polymerization readily led to low molecular weight polymers (<2.5 kDa), that were insoluble in most solvents except heated amide solvents (ie. DMF), whereas ADMET polymerization, with diallyl DKP, was unsuccessful due to a suspected 6 member complexation/deactivation state of the catalyst. This understanding prompted the preparation of elongated DKPs most notably dibutenyl DKP. SEC data supports the aforementioned understanding but requires further optimization studies in both the preparation of the DKP monomers and following ADMET polymerization. This work was supported by NMR, GC-MS, FT-IR, SEC-IR, and MALDI-Tof MS characterization. Polymer properties were measured by UV-Vis, TGA, and DSC.
Climatic variations and human activity now and increasingly in the future cause land cover changes and introduce perturbations in the terrestrial carbon reservoirs in vegetation, soil and detritus. Optical remote sensing and in particular Imaging Spectroscopy has shown the potential to quantify land surface parameters over large areas, which is accomplished by taking advantage of the characteristic interactions of incident radiation and the physico-chemical properties of a material. The objective of this thesis is to quantify key soil parameters, including soil organic carbon, using field and Imaging Spectroscopy. Organic carbon, iron oxides and clay content are selected to be analyzed to provide indicators for ecosystem function in relation to land degradation, and additionally to facilitate a quantification of carbon inventories in semiarid soils. The semiarid Albany Thicket Biome in the Eastern Cape Province of South Africa is chosen as study site. It provides a regional example for a semiarid ecosystem that currently undergoes land changes due to unadapted management practices and furthermore has to face climate change induced land changes in the future. The thesis is divided in three methodical steps. Based on reflectance spectra measured in the field and chemically determined constituents of the upper topsoil, physically based models are developed to quantify soil organic carbon, iron oxides and clay content. Taking account of the benefits limitations of existing methods, the approach is based on the direct application of known diagnostic spectral features and their combination with multivariate statistical approaches. It benefits from the collinearity of several diagnostic features and a number of their properties to reduce signal disturbances by influences of other spectral features. In a following step, the acquired hyperspectral image data are prepared for an analysis of soil constituents. The data show a large spatial heterogeneity that is caused by the patchiness of the natural vegetation in the study area that is inherent to most semiarid landscapes. Spectral mixture analysis is performed and used to deconvolve non-homogenous pixels into their constituent components. For soil dominated pixels, the subpixel information is used to remove the spectral influence of vegetation and to approximate the pure spectral signature coming from the soil. This step is an integral part when working in natural non-agricultural areas where pure bare soil pixels are rare. It is identified as the largest benefit within the multi-stage methodology, providing the basis for a successful and unbiased prediction of soil constituents from hyperspectral imagery. With the proposed approach it is possible (1) to significantly increase the spatial extent of derived information of soil constituents to areas with about 40 % vegetation coverage and (2) to reduce the influence of materials such as vegetation on the quantification of soil constituents to a minimum. Subsequently, soil parameter quantities are predicted by the application of the feature-based soil prediction models to the maps of locally approximated soil signatures. Thematic maps showing the spatial distribution of the three considered soil parameters in October 2009 are produced for the Albany Thicket Biome of South Africa. The maps are evaluated for their potential to detect erosion affected areas as effects of land changes and to identify degradation hot spots in regard to support local restoration efforts. A regional validation, carried out using available ground truth sites, suggests remaining factors disturbing the correlation of spectral characteristics and chemical soil constituents. The approach is developed for semiarid areas in general and not adapted to specific conditions in the study area. All processing steps of the developed methodology are implemented in software modules, where crucial steps of the workflow are fully automated. The transferability of the methodology is shown for simulated data of the future EnMAP hyperspectral satellite. Soil parameters are successfully predicted from these data despite intense spectral mixing within the lower spatial resolution EnMAP pixels. This study shows an innovative approach to use Imaging Spectroscopy for mapping of key soil constituents, including soil organic carbon, for large areas in a non-agricultural ecosystem and under consideration of a partially vegetation coverage. It can contribute to a better assessment of soil constituents that describe ecosystem processes relevant to detect and monitor land changes. The maps further provide an assessment of the current carbon inventory in soils, valuable for carbon balances and carbon mitigation products.
The European Values Education (EVE) project is a large-scale, cross-national, and longitudinal survey research programme on basic human values. The main topic of its second stage was family values in Europe. Student teachers of several universities in Europe worked together in multicultural exchange groups. Their results are presented in this issue.
This thesis rests on two large Active Galactic Nuclei (AGNs) surveys. The first survey deals with galaxies that host low-level AGNs (LLAGN) and aims at identifying such galaxies by quantifying their variability. While numerous studies have shown that AGNs can be variable at all wavelengths, the nature of the variability is still not well understood. Studying the properties of LLAGNs may help to understand better galaxy evolution, and how AGNs transit between active and inactive states. In this thesis, we develop a method to extract variability properties of AGNs. Using multi-epoch deep photometric observations, we subtract the contribution of the host galaxy at each epoch to extract variability and estimate AGN accretion rates. This pipeline will be a powerful tool in connection with future deep surveys such as PANSTARS. The second study in this thesis describes a survey of X-ray selected AGN hosts at redshifts z>1.5 and compares them to quiescent galaxies. This survey aims at studying environments, sizes and morphologies of star-forming high-redshift AGN hosts in the COSMOS Survey at the epoch of peak AGN activity. Between redshifts 1.5<z<3.8, the COSMOS HST/ACS imaging probes the UV regime, where separating the AGN flux from its host galaxy is very challenging. Nevertheless, we successfully derived the structural properties of 249 AGN hosts using two-dimensional surface-brightness profile fitting with the GALFIT package. This is the largest sample of AGN hosts at redshift z>1.5 to date. We analyzed the evolution of structural parameters of AGN and non-AGN host galaxies with redshift, and compared their disturbance rates to identify the more probable AGN triggering mechanism in the 43.5<log_10 L_X<45 luminosity range. We also conducted mock AGN and quiescent galaxies observations to determine errors and corrections for the derived parameters. We find that the size-absolute magnitude relations of AGN hosts and non-AGN galaxies are very similar, with estimated mean sizes in both samples decreasing by ~50% between redshifts z=1.5 and z=3.5. Morphological classification of both active and quiescent galaxies shows that the majority of the AGN host galaxies are disc-dominated, with disturbance rates that are significantly lower than among the non-AGN galaxies. Such a finding suggests that Major Mergers are probably not responsible for triggering AGN accretion in most of these galaxies. Other secular mechanisms should therefore be responsible.
Cellulose is the most abundant biopolymer on earth. In this work it has been used, in various forms ranging from wood to fully processed laboratory grade microcrystalline cellulose, to synthesise a variety of metal and metal carbide nanoparticles and to establish structuring and patterning methodologies that produce highly functional nano-hybrids. To achieve this, the mechanisms governing the catalytic processes that bring about graphitised carbons in the presence of iron have been investigated. It was found that, when infusing cellulose with an aqueous iron salt solution and heating this mixture under inert atmosphere to 640 °C and above, a liquid eutectic mixture of iron and carbon with an atom ratio of approximately 1:1 forms. The eutectic droplets were monitored with in-situ TEM at the reaction temperature where they could be seen dissolving amorphous carbon and leaving behind a trail of graphitised carbon sheets and subsequently iron carbide nanoparticles. These transformations turned ordinary cellulose into a conductive and porous matrix that is well suited for catalytic applications. Despite these significant changes on the nanometre scale the shape of the matrix as a whole was retained with remarkable precision. This was exemplified by folding a sheet of cellulose paper into origami cranes and converting them via the temperature treatment in to magnetic facsimiles of those cranes. The study showed that the catalytic mechanisms derived from controlled systems and described in the literature can be transferred to synthetic concepts beyond the lab without loss of generality. Once the processes determining the transformation of cellulose into functional materials were understood, the concept could be extended to other metals and metal-combinations. Firstly, the procedure was utilised to produce different ternary iron carbides in the form of MxFeyC (M = W, Mn). None of those ternary carbides have thus far been produced in a nanoparticle form. The next part of this work encompassed combinations of iron with cobalt, nickel, palladium and copper. All of those metals were also probed alone in combination with cellulose. This produced elemental metal and metal alloy particles of low polydispersity and high stability. Both features are something that is typically not associated with high temperature syntheses and enables to connect the good size control with a scalable process. Each of the probed reactions resulted in phase pure, single crystalline, stable materials. After showing that cellulose is a good stabilising and separating agent for all the investigated types of nanoparticles, the focus of the work at hand is shifted towards probing the limits of the structuring and pattering capabilities of cellulose. Moreover possible post-processing techniques to further broaden the applicability of the materials are evaluated. This showed that, by choosing an appropriate paper, products ranging from stiff, self-sustaining monoliths to ultra-thin and very flexible cloths can be obtained after high temperature treatment. Furthermore cellulose has been demonstrated to be a very good substrate for many structuring and patterning techniques from origami folding to ink-jet printing. The thereby resulting products have been employed as electrodes, which was exemplified by electrodepositing copper onto them. Via ink-jet printing they have additionally been patterned and the resulting electrodes have also been post functionalised by electro-deposition of copper onto the graphitised (printed) parts of the samples. Lastly in a preliminary test the possibility of printing several metals simultaneously and thereby producing finely tuneable gradients from one metal to another have successfully been made. Starting from these concepts future experiments were outlined. The last chapter of this thesis concerned itself with alternative synthesis methods of the iron-carbon composite, thereby testing the robustness of the devolved reactions. By performing the synthesis with partly dissolved scrap metal and pieces of raw, dry wood, some progress for further use of the general synthesis technique were made. For example by using wood instead of processed cellulose all the established shaping techniques available for wooden objects, such as CNC milling or 3D prototyping, become accessible for the synthesis path. Also by using wood its intrinsic well defined porosity and the fact that large monoliths are obtained help expanding the prospect of using the composite. It was also demonstrated in this chapter that the resulting material can be applied for the environmentally important issue of waste water cleansing. Additionally to being made from renewable resources and by a cheap and easy one-pot synthesis, the material is recyclable, since the pollutants can be recovered by washing with ethanol. Most importantly this chapter covered experiments where the reaction was performed in a crude, home-built glass vessel, fuelled – with the help of a Fresnel lens – only by direct concentrated sunlight irradiation. This concept carries the thus far presented synthetic procedures from being common laboratory syntheses to a real world application. Based on cellulose, transition metals and simple equipment, this work enabled the easy one-pot synthesis of nano-ceramic and metal nanoparticle composites otherwise not readily accessible. Furthermore were structuring and patterning techniques and synthesis routes involving only renewable resources and environmentally benign procedures established here. Thereby it has laid the foundation for a multitude of applications and pointed towards several future projects reaching from fundamental research, to application focussed research and even and industry relevant engineering project was envisioned.
We are interested in modeling the Darwinian evolution of a population described by two levels of biological parameters: individuals characterized by an heritable phenotypic trait submitted to mutation and natural selection and cells in these individuals influencing their ability to consume resources and to reproduce. Our models are rooted in the microscopic description of a random (discrete) population of individuals characterized by one or several adaptive traits and cells characterized by their type. The population is modeled as a stochastic point process whose generator captures the probabilistic dynamics over continuous time of birth, mutation and death for individuals and birth and death for cells. The interaction between individuals (resp. between cells) is described by a competition between individual traits (resp. between cell types). We are looking for tractable large population approximations. By combining various scalings on population size, birth and death rates and mutation step, the single microscopic model is shown to lead to contrasting nonlinear macroscopic limits of different nature: deterministic approximations, in the form of ordinary, integro- or partial differential equations, or probabilistic ones, like stochastic partial differential equations or superprocesses.
In this article we analyse the structure of Markov processes and reciprocal processes to underline their time symmetrical properties, and to compare them. Our originality consists in adopting a unifying approach of reciprocal processes, independently of special frameworks in which the theory was developped till now (diffusions, or pure jump processes). This leads to some new results, too.
Reciprocal processes, whose concept can be traced back to E. Schrödinger, form a class of stochastic processes constructed as mixture of bridges, that satisfy a time Markov field property. We discuss here a new unifying approach to characterize several types of reciprocal processes via duality formulae on path spaces: The case of reciprocal processes with continuous paths associated to Brownian diffusions and the case of pure jump reciprocal processes associated to counting processes are treated. This presentation is based on joint works with M. Thieullen, R. Murr and C. Léonard.
The challenge is providing teachers with the resources they need to strengthen their instructions and better prepare students for the jobs of the 21st Century. Technology can help meet the challenge. Teachers’ Tryscience is a noncommercial offer, developed by the New York Hall of Science, TeachEngineering, the National Board for Professional Teaching Standards and IBM Citizenship to provide teachers with such resources. The workshop provides deeper insight into this tool and discussion of how to support teaching of informatics in schools.
.NET Gadgeteer Workshop
(2013)
Problem solving is one of the central activities performed by computer scientists as well as by computer science learners. Whereas the teaching of algorithms and programming languages is usually well structured within a curriculum, the development of learners’ problem-solving skills is largely implicit and less structured. Students at all levels often face difficulties in problem analysis and solution construction. The basic assumption of the workshop is that without some formal instruction on effective strategies, even the most inventive learner may resort to unproductive trial-and-error problemsolving processes. Hence, it is important to teach problem-solving strategies and to guide teachers on how to teach their pupils this cognitive tool. Computer science educators should be aware of the difficulties and acquire appropriate pedagogical tools to help their learners gain and experience problem-solving skills.
A method is presented of acquiring the principles of three sorting algorithms through developing interactive applications in Excel.
We present a concept of better integration of practical teaching in student teacher education in Computer Science. As an introduction to the workshop different possible scenarios are discussed on the basis of examples. Afterwards workshop participants will have the opportunity to discuss the application of the aconcepts in other settings.
In this paper we report on our experiments in teaching computer science concepts with a mix of tangible and abstract object manipulations. The goal we set ourselves was to let pupils discover the challenges one has to meet to automatically manipulate formatted text. We worked with a group of 25 secondary school pupils (9-10th grade), and they were actually able to “invent” the concept of mark-up language. From this experiment we distilled a set of activities which will be replicated in other classes (6th grade) under the guidance of maths teachers.
Informatics as a school subject has been virtually absent from bilingual education programs in German secondary schools. Most bilingual programs in German secondary education started out by focusing on subjects from the field of social sciences. Teachers and bilingual curriculum experts alike have been regarding those as the most suitable subjects for bilingual instruction – largely due to the intercultural perspective that a bilingual approach provides. And though one cannot deny the gain that ensues from an intercultural perspective on subjects such as history or geography, this benefit is certainly not limited to social science subjects. In consequence, bilingual curriculum designers have already begun to include other subjects such as physics or chemistry in bilingual school programs. It only seems a small step to extend this to informatics. This paper will start out by addressing potential benefits of adding informatics to the range of subjects taught as part of English-language bilingual programs in German secondary education. In a second step it will sketch out a methodological (= didactical) model for teaching informatics to German learners through English. It will then provide two items of hands-on and tested teaching material in accordance with this model. The discussion will conclude with a brief outlook on the chances and prerequisites of firmly establishing informatics as part of bilingual school curricula in Germany.
We shall examine the Pedagogical Content Knowledge (PCK) of Computer Science (CS) teachers concerning students’ Computational Thinking (CT) problem solving skills within the context of a CS course in Dutch secondary education and thus obtain an operational definition of CT and ascertain appropriate teaching methodology. Next we shall develop an instrument to assess students’ CT and design a curriculum intervention geared toward teaching and improving students’ CT problem solving skills and competences. As a result, this research will yield an operational definition of CT, knowledge about CT PCK, a CT assessment instrument and teaching materials and accompanying teacher instructions. It shall contribute to CS teacher education, development of CT education and to education in other (STEM) subjects where CT plays a supporting role, both nationally and internationally.