2,678 research outputs found

    A scalable system for microcalcification cluster automated detection in a distributed mammographic database

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    A computer-aided detection (CADe) system for microcalcification cluster identification in mammograms has been developed in the framework of the EU-founded MammoGrid project. The CADe software is mainly based on wavelet transforms and artificial neural networks. It is able to identify microcalcifications in different datasets of mammograms (i.e. acquired with different machines and settings, digitized with different pitch and bit depth or direct digital ones). The CADe can be remotely run from GRID-connected acquisition and annotation stations, supporting clinicians from geographically distant locations in the interpretation of mammographic data. We report and discuss the system performances on different datasets of mammograms and the status of the GRID-enabled CADe analysis.Comment: 6 pages, 4 figures; Proceedings of the IEEE NNS and MIC Conference, October 23-29, 2005, Puerto Ric

    Motion of an impurity in a two-leg ladder

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    We study the motion of an impurity in a two-leg ladder interacting with two fermionic baths along each leg, a simple model bridging cold atom quantum simulators with an idealized description of the basic transport processes in a layered heterostructure. Using the linked-cluster expansion, we obtain exact analytical results for the single-particle Green's function and find that the long-time behavior is dominated by an intrinsic orthogonality catastrophe associated to the motion of the impurity in each one-dimensional chain. We explore both the case of two identical legs as well as the case where the legs are characterized by different interaction strengths: In the latter case, we observe a subleading correction which can be relevant for intermediate-time transport at an interface between different materials. In all the cases, we do not find significant differences between the intra- and interleg Green's functions in the long-time limit

    RISK ASSESSMENT OF MALICIOUS ATTACKS AGAINST POWER SYSTEMS

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    The new scenarios of malicious attack prompt for their deeper consideration and mainly when critical systems are at stake. In this framework, infrastructural systems, including power systems, represent a possible target due to the huge impact they can have on society. Malicious attacks are different in their nature from other more traditional cause of threats to power system, since they embed a strategic interaction between the attacker and the defender (characteristics that cannot be found in natural events or systemic failures). This difference has not been systematically analyzed by the existent literature. In this respect, new approaches and tools are needed. This paper presents a mixed-strategy game-theory model able to capture the strategic interactions between malicious agents that may be willing to attack power systems and the system operators, with its related bodies, that are in charge of defending them. At the game equilibrium, the different strategies of the two players, in terms of attacking/protecting the critical elements of the systems, can be obtained. The information about the attack probability to various elements can be used to assess the risk associated with each of them, and the efficiency of defense resource allocation is evidenced in terms of the corresponding risk. Reference defense plans related to the online defense action and the defense action with a time delay can be obtained according to their respective various time constraints. Moreover, risk sensitivity to the defense/attack-resource variation is also analyzed. The model is applied to a standard IEEE RTS-96 test system for illustrative purpose and, on the basis of that system, some peculiar aspects of the malicious attacks are pointed ou

    Revised analysis of Ca

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