Towards Smooth Particle Methods Without Smoothing

In this article we present a new class of particle methods which aim at being accurate in the uniform norm with a minimal amount of smoothing. The crux of our approach is to compute local polynomial expansions of the characteristic flow to transport the particle shapes with improved accuracy. In the first order case the method consists of representing the transported density with linearly-transformed particles, the second order version transports quadratically-transformed particles, and so on. For practical purposes we provide discrete versions of the resulting LTP and QTP schemes that only involve pointwise evaluations of the forward characteristic flow, and we propose local indicators for the associated transport error. On a theoretical level we extend these particle schemes up to arbitrary polynomial orders and show by a rigorous analysis that for smooth flows the resulting methods converge in \(L^\infty \) without requiring remappings, extended overlapping or vanishing moments for the particles. Numerical tests using different passive transport problems demonstrate the accuracy of the proposed methods compared to basic particle schemes, and they establish their robustness with respect to the remapping period. In particular, it is shown that QTP particles can be transported without remappings on very long periods of time, without hampering the accuracy of the numerical solutions. Finally, a dynamic criterion is proposed to automatically select the time steps where the particles should be remapped. The strategy is a by-product of our error analysis, and it is validated by numerical experiments.     

Activity-dependent development of axonal and dendritic delays, or, why synaptic transmission should be unreliable

Systematic temporal relations between single neuronal activities or population activities are ubiquitous in the brain. No experimental evidence, however, exists for a direct modification of neuronal delays during Hebbian-type stimulation protocols. We show that in fact an explicit delay adaptation is not needed if one assumes that the synaptic strengths are modified according to the recently observed temporally asymmetric learning rule with the downregulating branch dominating the upregulating branch. During development, slow, unbiased fluctuations in the transmission time, together with temporally correlated network activity, may control neural growth and implicitly induce drifts in the axonal delays and dendritic latencies. These delays and latencies become optimally tuned in the sense that the synaptic response tends to peak in the soma of the postsynaptic cell if this is most likely to fire. The nature of the selection process requires unreliable synapses in order to give successful synapses an evolutionary advantage over the others. The width of the learning function also determines the preferred dendritic delay and the preferred width of the postsynaptic response. Hence, it may implicitly determine whether a synaptic connection provides a precisely timed or a broadly tuned "contextual" signal.     

共话工业以太网风云变幻--访西门子自动化与驱动集团工业通信全球地区总经理贺日安及

2004年10月19日至20日,中国工业以太网发展论坛暨全国第一届工业以太网技术发展与应用研讨会(IEHF2004)在京召开.借此机会,本刊记者采访了西门子自动化与驱动集团工业通信全球地区总经理贺日安和德国菲尼克斯电气集团自动化总裁Martin Muller,畅谈工业以太网的过去、现在与未来.     

A configurable type hierarchy index for OODB

With respect to the specific requirements of advanced OODB applications, index data structures for type hierarchies in OODBMS have to provide efficient support for multiattribute queries and have to allow index optimization for a particular query profile. We describe the multikey type index and an efficient implementation of this indexing scheme. It meets both requirements: in addition to its multiattribute query capabilities it is designed as a mediator between two standard design alternatives, key-grouping and type-grouping. A prerequisite for the multikey type index is a linearization algorithm which maps type hierarchies to linearly ordered attribute domains in such a way that each subhierarchy is represented by an interval of this domain. The algorithm extends previous results with respect to multiple inheritance. The subsequent evaluation of our proposal focuses on storage space overhead as well as on the number of disk I/O operations needed for query execution. The analytical results for the multikey type index are compared to previously published figures for well-known single-key search structures. The comparison clearly shows the superiority of the multikey type index for a large class of query profiles. Edited by E. Bertino. Received October 7, 1996 / Accepted March 28, 1997     

Towards User‐Centered Active Learning Algorithms

The labeling of data sets is a time‐consuming task, which is, however, an important prerequisite for machine learning and visual analytics. Visual‐interactive labeling (VIAL) provides users an active role in the process of labeling, with the goal to combine the potentials of humans and machines to make labeling more efficient. Recent experiments showed that users apply different strategies when selecting instances for labeling with visual‐interactive interfaces. In this paper, we contribute a systematic quantitative analysis of such user strategies. We identify computational building blocks of user strategies, formalize them, and investigate their potentials for different machine learning tasks in systematic experiments. The core insights of our experiments are as follows. First, we identified that particular user strategies can be used to considerably mitigate the bootstrap (cold start) problem in early labeling phases. Second, we observed that they have the potential to outperform existing active learning strategies in later phases. Third, we analyzed the identified core building blocks, which can serve as the basis for novel selection strategies. Overall, we observed that data‐based user strategies (clusters, dense areas) work considerably well in early phases, while model‐based user strategies (e.g., class separation) perform better during later phases. The insights gained from this work can be applied to develop novel active learning approaches as well as to better guide users in visual interactive labeling.     

An overview of recommender systems in the healthy food domain

Recently, food recommender systems have received increasing attention due to their relevance for healthy living. Most existing studies on the food domain focus on recommendations that suggest proper food items for individual users on the basis of considering their preferences or health problems. These systems also provide functionalities to keep track of nutritional consumption as well as to persuade users to change their eating behavior in positive ways. Also, group recommendation functionalities are very useful in the food domain, especially when a group of users wants to have a dinner together at home or have a birthday party in a restaurant. Such scenarios create many challenges for food recommender systems since the preferences of all group members have to be taken into account in an adequate fashion. In this paper, we present an overview of recommendation techniques for individuals and groups in the healthy food domain. In addition, we analyze the existing state-of-the-art in food recommender systems and discuss research challenges related to the development of future food recommendation technologies.     

Guaranteed and Fully Robust a posteriori Error Estimates for Conforming Discretizations of Diffusion Problems with Discontinuous Coefficients

We study in this paper a posteriori error estimates for H ¹-conforming numerical approximations of diffusion problems with a diffusion coefficient piecewise constant on the mesh cells but arbitrarily discontinuous across the interfaces between the cells. Our estimates give a global upper bound on the error measured either as the energy norm of the difference between the exact and approximate solutions, or as a dual norm of the residual. They are guaranteed, meaning that they feature no undetermined constants. (Local) lower bounds for the error are also derived. Herein, only generic constants independent of the diffusion coefficient appear, whence our estimates are fully robust with respect to the jumps in the diffusion coefficient. In particular, no condition on the diffusion coefficient like its monotonous increasing along paths around mesh vertices is imposed, whence the present results also include the cases with singular solutions. For the energy error setting, the key requirement turns out to be that the diffusion coefficient is piecewise constant on dual cells associated with the vertices of an original simplicial mesh and that harmonic averaging is used in the scheme. This is the usual case, e.g., for the cell-centered finite volume method, included in our analysis as well as the vertex-centered finite volume, finite difference, and continuous piecewise affine finite element ones. For the dual norm setting, no such a requirement is necessary. Our estimates are based on H(div)-conforming flux reconstruction obtained thanks to the local conservativity of all the studied methods on the dual grids, which we recall in the paper; mutual relations between the different methods are also recalled. Numerical experiments are presented in confirmation of the guaranteed upper bound, full robustness, and excellent efficiency of the derived estimators.     

Two faces of anonymity: Paradoxical effects of cues to identity in CMC

This paper presents two experimental studies investigating the effects of presenting cues that provide information about the interactors – called cues to identity – in computer mediated communications (CMCs). Study 1 shows that even though cues to identity affected interpersonal evaluations, in making them more positive, the presence of these cues were associated with less certainty and less medium satisfaction for users with experience in online communication. Study 2 shows that when performing an online communication task, participants felt more certain, were more satisfied with the medium, and thought they had performed better in the absence of cues to identity. Thus, this study supports the widespread assumption that rich interactions (i.e., interactions that allow the transmission of cues to identity such as face-to-face) are superior in that they make the interaction more personal, but that these outcomes are not mirrored by the evaluation of the interaction. It is suggested that the presence of cues to identity positively affects interpersonal perceptions, but at the same time decreases perceptions of solidarity or entitativity.     

Everything but the kitchen sink [review of Integrated System-Level Modeling of Network-on-Chip Enabled Multi-Processor Platforms by Kogel, T. et al.; 2006]

This is a review of Integrated System-Level Modeling of Network-on-Chip Enabled Multi-processor Platforms (by Tim Kogel, Rainer Leupers, and Heinrich Meyr).This book offers an education in the wide range of areas involved in embedded-systems design, as well as a brief exploration of solutions on the horizon. It should resonate with students, researchers, and practical designers interested in the state of electronic systems-level (ESL) design in 2007.     

Preventing injection attacks with syntax embeddings

Software written in one language often needs to construct sentences in another language, such as SQL queries, XML output, or shell command invocations. This is almost always done using unhygienic string manipulation, the concatenation of constants and client-supplied strings. A client can then supply specially crafted input that causes the constructed sentence to be interpreted in an unintended way, leading to an injection attack. We describe a more natural style of programming that yields code that is impervious to injections by construction. Our approach embeds the grammars of the guest languages (e.g. SQL) into that of the host language (e.g. Java) and automatically generates code that maps the embedded language to constructs in the host language that reconstruct the embedded sentences, adding escaping functions where appropriate. This approach is generic, meaning that it can be applied with relative ease to any combination of context-free host and guest languages.