Showing papers by "Karlsruhe Institute of Technology published in 2000"

Potential for biomolecular imaging with femtosecond X-ray pulses

Abstract: Sample damage by X-rays and other radiation limits the resolution of structural studies on non-repetitive and non-reproducible structures such as individual biomolecules or cells(1). Cooling can slow sample deterioration, but cannot eliminate damage-induc

Review of Particle Physics

Abstract: This biennial Review summarizes much of particle physics. Using data from previous editions., plus 2778 new measurements from 645 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We also summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors., probability, and statistics. Among the 108 reviews are many that are new or heavily revised including those on CKM quark-mixing matrix, V-ud & V-us, V-cb & V-ub, top quark, muon anomalous magnetic moment, extra dimensions, particle detectors, cosmic background radiation, dark matter, cosmological parameters, and big bang cosmology.

Temperature-dependent self-diffusion coefficients of water and six selected molecular liquids for calibration in accurate 1H NMR PFG measurements

Abstract: Pulsed magnetic field gradient (PFG) NMR is today a routine method for the determination of self-diffusion coefficients, D. However, a remaining goal is the improvement of the precision of the method. The best procedure for the determination of accurate diffusion coefficients by PFG NMR is a calibration with a sample of precisely known D-value. In continuation of our previous work on calibration at 25°C (M. Holz and H. Weingartner, J. Magn. Reson., 1991, 92, 115) we present reference data as a function of temperature. Since H2O plays an outstanding role as liquid and as primary standard, we carefully measured self-diffusion coefficients of water by 1H PFG NMR in the temperature range from + 5 to + 55°C and added literature data obtained from tracer methods in the range between 0 and + 100°C. This comparatively large collection of data could then be fitted to a Speedy–Angell power law, showing the excellent congruence of the results of two completely different methods and proofing the certainty of the absolute values for water. In this manner reliable primary standard values with error limits of <1% were obtained, allowing us to adapt the temperature of the standard water to the sample temperature of interest. We further give 1H PFG NMR self-diffusion reference data in the range from + 5 to + 55°C for six easily accessible solvents, which we propose as secondary calibration standards, namely cyclohexane, dioxane, dodecane, DMSO, tetradecane and pentanol, covering a large range of absolute D-values and allowing us to match in addition the absolute D-values of calibration sample and sample under investigation. Furthermore, the gained accurate self-diffusion data are suited for an elaborate check of theoretical approaches in the physics of molecular liquids.

Conditional Cooperation and Voluntary Contributions to Public Goods

Abstract: We compare a partners condition where the same small group of subjects plays a repeated publi c good game to a strangers condition where subjects play this game in changing group formations. Subjects in the partners conditi on contribute from t he first period on significantly more to the publi c good than subjects in the strangers conditi on. In the strangers conditi on, contributions show a continual decay, whil e in the partners conditi on, contributions fluctuate on a high level until t hey decrease in the final periods. We interpret subjects’ behavior in terms of conditional cooperation which is characterized by both future-oriented and reactive behavior.

Ant colony optimization for resource-constrained project scheduling

Abstract: An ant colony optimization approach (ACO) for the resource-constrained project scheduling problem (RCPSP) is presented. Combinations of two pheromone evaluation methods are used by the ants to find new solutions. We tested our ACO algorithm on a set of large benchmark problems from the PSPLIB. Compared to several other heuristics for the RCPSP including genetic algorithms, simulated annealing, tabu search, and different sampling methods our algorithm performed best on the average. For some test instances the algorithm was able to find new best solutions.

Implicit human computer interaction through context

Abstract: In this paper the term “implicit human-computer interaction” is defined. It is discussed how the availability of processing power and advanced sensing technology can enable a shift in HCI from explicit interaction, such as direct manipulation GUIs, towards a more implicit interaction based on situational context. In the paper, an algorithm is given based on a number of questions to identify applications that can facilitate implicit interaction. An XML-based language to describe implicit HCI is proposed. The language uses contextual variables that can be grouped using different types of semantics as well as actions that are called by triggers. The term of perception is discussed and four basic approaches are identified that are useful when building context-aware applications. Two examples, a wearable context awareness component and a sensor-board, show how sensor-based perception can be implemented. It is also discussed how situational context can be exploited to improve input and output of mobile devices.

Onset of antiferromagnetism in heavy-fermion metals

Abstract: There are two main theoretical descriptions of antiferromagnets. The first arises from atomic physics, which predicts that atoms with unpaired electrons develop magnetic moments. In a solid, the coupling between moments on nearby ions then yields antiferromagnetic order at low temperatures1. The second description, based on the physics of electron fluids or ‘Fermi liquids’, states that Coulomb interactions can drive the fluid to adopt a more stable configuration by developing a spin density wave2,3. It is at present unknown which view is appropriate at a ‘quantum critical point’, where the antiferromagnetic transition temperature vanishes4,5,6,7. Here we report neutron scattering and bulk magnetometry measurements of the metal CeCu6-xAux, which allow us to discriminate between the two models. We find evidence for an atomically local contribution to the magnetic correlations which develops at the critical gold concentration (xc = 0.1 ), corresponding to a magnetic ordering temperature of zero. This contribution implies that a Fermi-liquid-destroying spin-localizing transition, unanticipated from the spin density wave description, coincides with the antiferromagnetic quantum critical point.

An Optical Disdrometer for Measuring Size and Velocity of Hydrometeors

Abstract: The characteristics of a prototype optical disdrometer are presented. Particles are detectable in the diameter range from 0.3 to 30 mm having velocities of up to 20 m s−1. Advantages of the new system are (i) it is easy to handle, robust, and low cost, allowing a cluster of instruments to investigate the spatial and temporal fine-scale structure of precipitation; (ii) it provides reliable detection of the range of small drops; and (iii) it allows the possibility of snow measurements. Results of rain measurements are compared with data from a Joss–Waldvogel disdrometer and a Hellmann rain gauge. Furthermore, some snow measurements are presented and compared with results of a research spectrometer. The overall agreement is good. The repeatability of particle size estimation was checked in the diameter range between 1.4 and 8.0 mm and yielded a standard deviation of less than 5%. For drop velocities the standard deviation varies between 25% (0.3-mm drops) and 10% (5-mm drops). The optical disdromete...

OIL in a Nutshell

Abstract: Currently computers are changing from single isolated devices into entry points into a worldwide network of information exchange and business transactions. Support in data, information, and knowledge exchange is becoming the key issue in current computer technology. Ontologies will play a major role in supporting information exchange processes in various areas. A prerequisite for such a role is the development of a joint standard for specifying and exchanging ontologies. The purpose of the paper is precisely concerned with this necessity. We will present OIL, which is a proposal for such a standard. It is based on existing proposals such as OKBC, XOL and RDF schema, enriching them with necessary features for expressing ontologies. The paper sketches the main ideas of OIL.

Tunable two-dimensional photonic crystals using liquid crystal infiltration

Abstract: The photonic band gap of a two-dimensional photonic crystal is continuously tuned using the temperature dependent refractive index of a liquid crystal. Liquid crystal $E7$ was infiltrated into the air pores of a macroporous silicon photonic crystal with a triangular lattice pitch of 1.58 $\ensuremath{\mu}$m and a band gap wavelength range of 3.3--5.7 \ensuremath{\mu}m. After infiltration, the band gap for the H polarized field shifted dramatically to 4.4--6.0 \ensuremath{\mu}m while that of the E-polarized field collapsed. As the sample was heated to the nematic-isotropic phase transition temperature of the liquid crystal $(59\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}),$ the short-wavelength band edge of the H gap shifted by as much as 70 nm while the long-wavelength edge was constant within experimental error. Band structure calculations incorporating the temperature dependence of the liquid crystal birefringence can account for our results and also point to an escaped-radial alignment of the liquid crystal in the nematic phase.

Discovering conceptual relations from text

Abstract: Non-taxonomic relations between concepts appear as a major building block in common ontology definitions. In fact, their definition consumes much of the time needed for engineering an ontology. We here describe a new approach to discover non-taxonomic conceptual relations from text building on shallow text processing techniques. We use a generalized association rule algorithm that does not only detect relations between concepts, but also determines the appropriate level of abstraction at which to define relations. This is crucial for an appropriate ontology definition in order that it be succinct and conceptually adequate and, hence, easy to understand, maintain, and extend. We also perform an empirical evaluation of our approach with regard to a manually engineered ontology. For this purpose, we present a new paradigm suited to evaluate the degree to which relations that are learned match relations in a manually engineered ontology.

An empirical comparison of seven programming languages

Abstract: Often heated, debates regarding different programming languages' effectiveness remain inconclusive because of scarce data and a lack of direct comparisons. The author addresses that challenge, comparatively analyzing 80 implementations of the phone-code program in seven different languages (C, C++, Java, Perl, Python, Rexx and Tcl). Further, for each language, the author analyzes several separate implementations by different programmers. The comparison investigates several aspects of each language, including program length, programming effort, runtime efficiency, memory consumption, and reliability. The author uses comparisons to present insight into program language performance.

A Multi-population Approach to Dynamic Optimization Problems

Abstract: Time-dependent optimization problems pose a new challenge to evolutionary algorithms, since they not only require a search for the optimum, but also a continuous tracking of the optimum over time. In this paper, we will will use concepts from the ”forking GA” (a multi-population evolutionary algorithm proposed to find multiple peaks in a multi-modal landscape) to enhance search in a dynamic landscape. The algorithm uses a number of smaller populations to track the most promising peaks over time, while a larger parent population is continuously searching for new peaks. We will show that this approach is indeed suitable for dynamic optimization problems by testing it on the recently proposed Moving Peaks Benchmark.

Mining frequent patterns with counting inference

Abstract: In this paper, we propose the algorithm PASCAL which introduces a novel optimization of the well-known algorithm Apriori. This optimization is based on a new strategy called pattern counting inference that relies on the concept of key patterns. We show that the support of frequent non-key patterns can be inferred from frequent key patterns without accessing the database. Experiments comparing PASCAL to the three algorithms Apriori, Close and Max-Miner, show that PASCAL is among the most efficient algorithms for mining frequent patterns.