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- Bennaceur, A., et al.
(författare)
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Mechanisms for leveraging models at runtime in self-adaptive software
- 2014
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Ingår i: Lecture Notes in Computer Science: Dagstuhl Seminar 11481 on Models@run.time; ; 27 November 2011 through 2 December 2011. - Cham : Springer. - 9783319089140
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Konferensbidrag (refereegranskat)abstract
- Modern software systems are often required to adapt their behavior at runtime in order to maintain or enhance their utility in dynamic environments. Models at runtime research aims to provide suitable abstractions, techniques, and tools to manage the complexity of adapting software systems at runtime. In this chapter, we discuss challenges associated with developing mechanisms that leverage models at runtime to support runtime software adaptation. Specifically, we discuss challenges associated with developing effective mechanisms for supervising running systems, reasoning about and planning adaptations, maintaining consistency among multiple runtime models, and maintaining fidelity of runtime models with respect to the running system and its environment. We discuss related problems and state-of-the-art mechanisms, and identify open research challenges.
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| 2. |
- Aksit Ciris, P., et al.
(författare)
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Accelerated Segmented Diffusion-Weighted Prostate Imaging for Higher Resolution, Higher Geometric Fidelity, and Multi-b Perfusion Estimation
- 2019
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Ingår i: Investigative Radiology. - 0020-9996. ; 54:4, s. 238-246
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Tidskriftsartikel (refereegranskat)abstract
- Purpose The aim of this study was to improve the geometric fidelity and spatial resolution of multi-b diffusion-weighted magnetic resonance imaging of the prostate. Materials and Methods An accelerated segmented diffusion imaging sequence was developed and evaluated in 25 patients undergoing multiparametric magnetic resonance imaging examinations of the prostate. A reduced field of view was acquired using an endorectal coil. The number of sampled diffusion weightings, or b-factors, was increased to allow estimation of tissue perfusion based on the intravoxel incoherent motion (IVIM) model. Apparent diffusion coefficients measured with the proposed segmented method were compared with those obtained with conventional single-shot echo-planar imaging (EPI). Results Compared with single-shot EPI, the segmented method resulted in faster acquisition with 2-fold improvement in spatial resolution and a greater than 3-fold improvement in geometric fidelity. Apparent diffusion coefficient values measured with the novel sequence demonstrated excellent agreement with those obtained from the conventional scan (R 2 = 0.91 for b max = 500 s/mm 2 and R 2 = 0.89 for b max = 1400 s/mm 2 ). The IVIM perfusion fraction was 4.0% ± 2.7% for normal peripheral zone, 6.6% ± 3.6% for normal transition zone, and 4.4% ± 2.9% for suspected tumor lesions. Conclusions The proposed accelerated segmented prostate diffusion imaging sequence achieved improvements in both spatial resolution and geometric fidelity, along with concurrent quantification of IVIM perfusion. © 2019 Wolters Kluwer Health, Inc. All rights reserved.
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| 3. |
- Stoyenko, AD, et al.
(författare)
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Load balanced mapping of distributed objects to minimize network communication
- 1996
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Ingår i: Journal of Parallel and Distributed Computing. - SAN DIEGO : ACADEMIC PRESS INC JNL-COMP SUBSCRIPTIONS. - 0743-7315 .- 1096-0848. ; , s. 117-136
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Tidskriftsartikel (refereegranskat)abstract
- This paper introduces a new load balancing and communication minimizing heuristic used in the In verse Remote Procedure Call (IRPC) system. While the paper briefly describes the IRPC system, the focus is on the new IRPC assignment heuristic. The IRPC compiler maps a distributed program to a graph that represents program objects and their dependencies (due to invocations and parameter passing) as nodes and edges, respectively. In the graph, the system preserves conditional and iterative flows, records network transmission and execution costs, and marks nodes that have to reside at specific network sites. The graph is then partitioned by the heuristic to derive a (sub)optimal node assignment to network sites minimizing load balancing and network data transport. The resulting program partition is then reflected in the physical object distribution, and remote and local object communication is transparently implemented. The compiler and run-time system use efficient implementation techniques such as type prediction, inlining, splitting and subprogram passing. The last of these allows remote code to be copied to local data, as an alternative to copying data to the remote site, whenever this will reduce network data transport. The IRPC graph partitioning heuristic operates in time O(E(log d + l + log M)), where M is the number of network sites, E is the number of communication edges, and d is the maximum degree of a node; l is a parameter of the algorithm, and can vary between 1 and N, where N is the number of communicating objects. This complexity is more nearly independent of M, and considerably better in terms of E and N, than that of previously known related algorithms, such as A*, which employs backtracking and is potentially exponential, or the max-flow/min-cut class of network flow algorithms or heuristics which tend to be at least of Omega(MN(2)E), and it can be made (by choosing l appropriately) as efficient as even such fast heuristics as heaviest-edge-first, minimal communication, and Kernighan-Lin. In an extensive quantitative evaluation, the heuristic has been demonstrated to perform very well, giving on the average 75% traffic cost reductions for over 95% of the programs when compared to random partitioning, and outperforming in cost reduction and actual execution time the three aforementioned fast heuristics, even with a large l. Thus, to the best of our knowledge, this is the first report of a well-performing assignment heuristic that is both essentially linear in the number of communication edges, and better than existing, established heuristics of no better complexity. (C) 1996 Academic Press, Inc.
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