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We report results of the switching properties of Stoner-like magnetic particles subject to short magnetic field pulses, obtained by numerical investigations. We discuss the switching properties as a function of the external field pulse strength and direction, the pulse length and the pulse shape. For field pulses long compared to the ferromagnetic resonance precession time the switching behavior is governed by the magnetic damping term, whereas in the limit of short field pulses the switching properties are dominated by the details of the precession of the magnetic moment. In the latter case, by choosing the right field pulse parameters, the magnetic damping term is of minor importance and ultrafast switching can be achieved. Switching can be obtained in an enlarged angular range of the direction of the applied field compared to the case of long pulses.
A multiscale method is introduced using spherical (vector) wavelets for the computation of the earth's magnetic field within source regions of ionospheric and magnetospheric currents. The considerations are essentially based on two geomathematical keystones, namely (i) the Mie representation of solenoidal vector fields in terms of toroidal and poloidal parts and (ii) the Helmholtz decomposition of spherical (tangential) vector fields. Vector wavelets are shown to provide adequate tools for multiscale geomagnetic modelling in form of a multiresolution analysis, thereby completely circumventing the numerical obstacles caused by vector spherical harmonics. The applicability and efficiency of the multiresolution technique is tested with real satellite data.
We show how to prove ground confluence of term rewrite relations that areinduced by reductive systems of clausal rewrite rules. According to a well-knowncritical pair criterion it suffices for such systems to prove ground joinability ofa suitable set of 'critical clauses'. We outline how the latter can be done in asystematic fashion, using mathematical induction as a key concept of reasoning.
We present a new software architecture in which all concepts necessary to achieve fault tolerance can be added to an appli- cation automatically without any source code changes. As a case study, we consider the problem of providing a reliable service despite node failures by executing a group of replicat- ed servers. Replica creation and management as well as fail- ure detection and recovery are performed automatically by a separate fault tolerance layer (ft-layer) which is inserted be- tween the server application and the operating system kernel. The layer is invisible for the application since it provides the same functional interface as the operating system kernel, thus making the fault tolerance property of the service completely transparent for the application. A major advantage of our ar- chitecture is that the layer encapsulates both fault tolerance mechanisms and policies. This allows for maximum flexibility in the choice of appropriate methods for fault tolerance with- out any changes in the application code.
We describe a technique to make application programs fault tolerant. This techADnique is based on the concept of checkpointing from an active program to one ormore passive backup copies which serve as an abstraction of stable memory. Ifthe primary copy fails, one of the backup copies takes over and resumes processADing service requests. After each failure a new backup copy is created in order torestore the replication degree of the service. All mechanisms necessary to achieveand maintain fault tolerance can be added automatically to the code of a nonADfaulttolerant server, thus making fault tolerance completely transparent for the applicaADtion programmer.
This paper presents a completely systematic design procedure for asynchronous controllers.The initial step is the construction of a signal transition graph (STG, an interpreted Petri net) ofthe dialog between data path and controller: a formal representation without reference to timeor internal states. To implement concurrently operating control structures, and also to reducedesign effort and circuit cost, this STG can be decomposed into overlapping subnets. A univer-sal initial solution is then obtained by algorithmically constructing a primitive flow table fromeach component net. This step links the procedure to classical asynchronous design, in particu-lar to its proven optimization methods, without restricting the set of solutions. In contrast toother approaches, there is no need to extend the original STG intuitively.
Coordinating distributed processes, especially engineering and software design processes, has been a research topic for some time now. Several approaches have been published that aim at coordinating large projects in general, and large software development processes in specific. However, most of these approaches focus on the technical part of the design process and omit management activities like planning and scheduling the project, or monitoring it during execution. In this paper, we focus on coordinating the management activities that accompany the technical software design process. We state the requirements for a Software Engineering Environm ent (SEE) accommodating management, and we describe a possible architecture for such an SEE.
This paper describes the architecture and concept of operation of a Framework for Adaptive Process Modeling and Execution (FAME). The research addresses the absence of robust methods for supporting the software process management life cycle. FAME employs a novel, model-based approach in providing automated support for different activities in the software development life cycle including project definition, process design, process analysis, process enactment, process execution status monitoring, and execution status-triggered process redesign. FAME applications extend beyond the software development domain to areas such as agile manufacturing, project management, logistics planning, and business process reengineering.
In this paper we present an extensional higher-order resolution calculus that iscomplete relative to Henkin model semantics. The treatment of the extensionality princi-ples - necessary for the completeness result - by specialized (goal-directed) inference rulesis of practical applicability, as an implentation of the calculus in the Leo-System shows.Furthermore, we prove the long-standing conjecture, that it is sufficient to restrict the orderof primitive substitutions to the order of input formulae.
Abstract: Random matrix theory (RMT) is a powerful statistical tool to model spectral fluctuations. In addition, RMT provides efficient means to separate different scales in spectra. Recently RMT has found application in quantum chromodynamics (QCD). In mesoscopic physics, the Thouless energy sets the universal scale for which RMT applies. We try to identify the equivalent of a Thouless energy in complete spectra of the QCD Dirac operator with staggered fermions and SU_(2) lattice gauge fields. Comparing lattice data with RMT predictions we find deviations which allow us to give an estimate for this scale.
Abstract: Recently, the contributions of chiral logarithms predicted by quenched chiral perturbation theory have been extracted from lattice calculations of hadron masses. We argue that a detailed comparison of random matrix theory and lattice calculations allows for a precise determination of such corrections. We estimate the relative size of the m log(m), m, and m^2 corrections to the chiral condensate for quenched SU(2).
Beyond the Thouless energy
(1999)
Abstract: The distribution and the correlations of the small eigenvalues of the Dirac operator are described by random matrix theory (RMT) up to the Thouless energy E_= 1 / sqrt (V), where V is the physical volume. For somewhat larger energies, the same quantities can be described by chiral perturbation theory (chPT). For most quantities there is an intermediate energy regime, roughly 1/V < E < 1/sqrt (V), where the results of RMT and chPT agree with each other. We test these predictions by constructing the connected and disconnected scalar susceptibilities from Dirac spectra obtained in quenched SU(2) and SU(3) simulations with staggered fermions for a variety of lattice sizes and coupling constants. In deriving the predictions of chPT, it is important totake into account only those symmetries which are exactly realized on the lattice.
Abstract: Recently, the chiral logarithms predicted by quenched chiral perturbation theory have been extracted from lattice calculations of hadron masses. We argue that the deviations of lattice results from random matrix theory starting around the so-called Thouless energy can be understood in terms of chiral perturbation theory as well. Comparison of lattice data with chiral perturbation theory formulae allows us to compute the pion decay constant. We present results from a calculation for quenched SU(2) with Kogut-Susskind fermions at ß = 2.0 and 2.2.
We present results from a study of the coherence properties of a system involving three discrete states coupled to each other by two-photon processes via a common continuum. This tripod linkage is an extension of the standard laser-induced continuum structure (LICS) which involves two discrete states and two lasers. We show that in the tripod scheme, there exist two population trapping conditions; in some cases these conditions are easier to satisfy than the single trapping condition in two-state LICS. Depending on the pulse timing, various effects can be observed. We derive some basic properties of the tripod scheme, such as the solution for coincident pulses, the behaviour of the system in the adiabatic limit for delayed pulses, the conditions for no ionization and for maximal ionization, and the optimal conditions for population transfer between the discrete states via the continuum. In the case when one of the discrete states is strongly coupled to the continuum, the population dynamics reduces to a standard two-state LICS problem (involving the other two states) with modified parameters; this provides the opportunity to customize the parameters of a given two-state LICS system.
Abstract: We propose a simple method for measuring the populations and the relative phase in a coherent superposition of two atomic states. The method is based on coupling the two states to a third common (excited) state by means of two laser pulses, and measuring the total fluorescence from the third state for several choices of the excitation pulses.
Collecting Experience on the Systematic Development of CBR Applications using the INRECA Methodology
(1999)
This paper presents an overview of the INRECA methodology for building and maintaining CBR applications. This methodology supports the collection and reuse of experience on the systematic development of CBR applications. It is based on the experience factory and the software process modeling approach from software engineering. CBR development experience is documented using software process models and stored in different levels of generality in a three-layered experience base. Up to now, experience from 9 industrial projects enacted by all INRECA II partners has been collected.
Complex problem solving can be substantially improved by the reuse of experience from previously solved problems. This requires that case libraries of successful problem solutions are transformed into problem solving knowledge with high utility, i.e. knowledge which causes high savings in search time, high application probability and low matching costs in a respective performance component. Planning can be improved by explanation-based learning (EBL) of abstract plans from detailed, successfully solved planning problems. Abstract plans, expressed in well-established terms of the domain, serve as useful problem decompositions which can drastically reduce the planning complexity. Abstractions which are valid for a class of planning cases rather than for a single case, ensure a successful application in a larger spectrum of new situations. The hierarchical organization of the learned shared abstractions causes low matching costs. The presented S-PABS procedure is an EBL-procedure in which abstraction, learning from multiple examples and hierarchical clustering are combined to automatically construct a hierarchy of shared abstract plans by analyzing concrete planning cases. A specific planning procedure has been designed to solve new planning problems guided by the knowledge learned by S-PABS. By allowing a feedback from this planning procedure to the learning component, the integrated system shows an increase in performance through past problem solving.
Although skeletal plan refinement is used in several planning systems, a procedure for the automatic acquisition of such high-level plans has not yet been developed. The proposed explanation- based knowledge acquisition procedure constructs a skeletal plan automatically from a sophisticated concrete planning case. The classification of that case into a well-described class of problems serves as an instrument for adjusting the applicability of the acquired skeletal plans to that class. The four phases of the proposed procedure are constituted as follows: In the first phase, the execution of the source plan is simulated, and explanations for the effects of the occurred operators are constructed. In the second phase, the generalization of these explanations is performed with respect to a criterion of operationality which specifies the vocabulary for defining abstract operators for the skeletal plan. The third phase, a dependency analysis of the resulting operator effects, unveils the interactions of the concrete plan which are substantial for the specified class. In the forth phase, the concept descriptions for the abstract operators of the skeletal plan are formed by collecting and normalizing the important constraints for each operation that were indicated by the dependencies. With this procedure sophisticated planning solutions from human experts can be generalized into skeletal plans and consequently be reused by a planning system in novel situations.
Abstraction is one of the most promising approaches to improve the performance of problem solvers. Abstraction by dropping sentences of a domain description - as used in most hierarchical planners - is known to be very representation dependent. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract.