-alyzing each procedure in its calling context. Top-down analyses have several applications in verification and software model check-ing. However, traditionally, bottom-up analyses have been easier to scale and parallelize than top-down analyses. In this paper, we propose a generic framework, BOLT, which

Integration of goal-driven, top-down attention and image-driven, bottom-up attention is crucial for visual search. Yet, previous research has mostly focused on models that are purely top-down or bottom-up. Here, we propose a new model that combines both. The bottom-up component computes the visual

and intensities) at mul-tiple spatial scales in a manner described in [6]. Next, the top-down component uses learnt statistical knowledge of the local features of the target and distracting clutter, to optimize the relative weights of the bottom-up maps such that the overall salience of the target is maximized

that this number is fundamental to physics. Probabilities similar to the field of information theory developed by Claude Shannon [16] and others were used as tools to develop an information based approach to energy. Considering the probability of one neutron as 1/exp(180) a “top-down ” model lead to information

to system developers via the components interface specifications. Software components provide a means for large-scale reuse of

, mini-split models, low-scale supersymmetry breaking scenario and some string theory inspired low-energy spectra. 1

critical resolution of 1–10 nm and the hybrid top-down and bottom-up technolo-gies to achieve massively parallel integration of heterogeneous nanoscale components into higher-order structures and devices. Furthermore, SINAM will develop system engineering strategies to scale-up the nano

Distributed assembly tasks, in which large numbers of agents collaborate to produce composite objects out of component parts, require careful algorithm design to ensure behavior that scales well with the numbers of agents and parts. Yet al-gorithm evaluation, through which design is guided, is com

Abstract. The paper presents an experience report in course design for a versatile group of computer science students where their needs were surfaced and met by the combination of strict top-down exposure to course material and the flipped classroom model of lecturing. Motivation Computer science

, are not well-suited for set-valued data. In this paper we propose a top-down, partition-based approach to anonymizing set-valued data that scales linearly with the input size and scores well on an information-loss data quality metric. We further note that our technique can be applied to anonymize the infamous