Home About us Contact
|
Home About us Contact | ||
|
|
||
Sequential Algorithm (sequential + algorithm)
Selected AbstractsA Massively Parallel Time-Dependent Least-Time-Path Algorithm for Intelligent Transportation Systems ApplicationsCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 5 2001Athanasios Ziliaskopoulos This article is concerned with the problem of computing in parallel time-dependent least-time paths that can be used in real-time intelligent transportation systems applications. A message-passing scheme is presented, and its correctness is proved. The algorithm's computational complexity is shown to be O(|T|2|V|2), an improvement by |V| over the best-known sequential algorithm. The algorithm is implemented, coded, and computationally tested on actual and random networks with promising results. The algorithm is implemented on a CRAY-T3D supercomputer using a Parallel Virtual Machine environment that allows portability to lower-end multiprocessor machines. [source] SAFE biopsy: A validated method for large-scale staging of liver fibrosis in chronic hepatitis C,HEPATOLOGY, Issue 6 2009Giada Sebastiani The staging of liver fibrosis is pivotal for defining the prognosis and indications for therapy in hepatitis C. Although liver biopsy remains the gold standard, several noninvasive methods are under evaluation for clinical use. The aim of this study was to validate the recently described sequential algorithm for fibrosis evaluation (SAFE) biopsy, which detects significant fibrosis (,F2 by METAVIR) and cirrhosis (F4) by combining the AST-to-platelet ratio index and Fibrotest-Fibrosure, thereby limiting liver biopsy to cases not adequately classifiable by noninvasive markers. Hepatitis C virus (HCV) patients (2035) were enrolled in nine locations in Europe and the United States. The diagnostic accuracy of SAFE biopsy versus histology, which is the gold standard, was investigated. The reduction in the need for liver biopsies achieved with SAFE biopsy was also assessed. SAFE biopsy identified significant fibrosis with 90.1% accuracy (area under the receiver operating characteristic curve = 0.89; 95% confidence interval, 0.87-0.90) and reduced by 46.5% the number of liver biopsies needed. SAFE biopsy had 92.5% accuracy (area under the receiver operating characteristic curve = 0.92; 95% confidence interval, 0.89-0.94) for the detection of cirrhosis, obviating 81.5% of liver biopsies. A third algorithm identified significant fibrosis and cirrhosis simultaneously with high accuracy and a 36% reduction in the need for liver biopsy. The patient's age and body mass index influenced the performance of SAFE biopsy, which was improved with adjusted Fibrotest-Fibrosure cutoffs. Two hundred two cases (9.9%) had discordant results for significant fibrosis with SAFE biopsy versus histology, whereas 153 cases (7.5%) were discordant for cirrhosis detection; 71 of the former cases and 56 of the latter cases had a Fibroscan measurement within 2 months of histological evaluation. Fibroscan confirmed SAFE biopsy findings in 83.1% and 75%, respectively. Conclusion: SAFE biopsy is a rational and validated method for staging liver fibrosis in hepatitis C with a marked reduction in the need for liver biopsy. It is an attractive tool for large-scale screening of HCV carriers. (HEPATOLOGY 2009.) [source] Rain-gauge network evaluation and augmentation using geostatisticsHYDROLOGICAL PROCESSES, Issue 14 2008Ke-Sheng Cheng Abstract Rain-gauge networks are often used to provide estimates of area average rainfall or point rainfalls at ungauged locations. The level of accuracy a network can achieve depends on the total number and locations of gauges in the network. A geostatistical approach for evaluation and augmentation of an existing rain-gauge network is proposed in this study. Through variogram analysis, hourly rainfalls are shown to have higher spatial variability than annual rainfalls, with hourly Mei-Yu rainfalls having the highest spatial variability. A criterion using ordinary kriging variance is proposed to assess the accuracy of rainfall estimation using the acceptance probability defined as the probability that estimation error falls within a desired range. Based on the criterion, the percentage of the total area with acceptable accuracy Ap under certain network configuration can be calculated. A sequential algorithm is also proposed to prioritize rain-gauges of the existing network, identify the base network, and relocate non-base gauges. Percentage of the total area with acceptable accuracy is mostly contributed by the base network. In contrast, non-base gauges provide little contribution to Ap and are subject to removal or relocation. Using a case study in northern Taiwan, the proposed approach demonstrates that the identified base network which comprises of approximately two-thirds of the total rain-gauges can achieve almost the same level of performance (expressed in terms of percentage of the total area with acceptable accuracy) as the complete network for hourly Mei-Yu rainfall estimation. The percentage of area with acceptable accuracy can be raised from 56% to 88% using an augmented network. A threshold value for the percentage of area with acceptable accuracy is also recommended to help determine the number of non-base gauges which need to be relocated. Copyright © 2007 John Wiley & Sons, Ltd. [source] Parallel Algorithms for Dynamic Shortest Path ProblemsINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 3 2002Ismail Chabini The development of intelligent transportation systems (ITS) and the resulting need for the solution of a variety of dynamic traffic network models and management problems require faster-than-real-time computation of shortest path problems in dynamic networks. Recently, a sequential algorithm was developed to compute shortest paths in discrete time dynamic networks from all nodes and all departure times to one destination node. The algorithm is known as algorithm DOT and has an optimal worst-case running-time complexity. This implies that no algorithm with a better worst-case computational complexity can be discovered. Consequently, in order to derive algorithms to solve all-to-one shortest path problems in dynamic networks, one would need to explore avenues other than the design of sequential solution algorithms only. The use of commercially-available high-performance computing platforms to develop parallel implementations of sequential algorithms is an example of such avenue. This paper reports on the design, implementation, and computational testing of parallel dynamic shortest path algorithms. We develop two shared-memory and two message-passing dynamic shortest path algorithm implementations, which are derived from algorithm DOT using the following parallelization strategies: decomposition by destination and decomposition by transportation network topology. The algorithms are coded using two types of parallel computing environments: a message-passing environment based on the parallel virtual machine (PVM) library and a multi-threading environment based on the SUN Microsystems Multi-Threads (MT) library. We also develop a time-based parallel version of algorithm DOT for the case of minimum time paths in FIFO networks, and a theoretical parallelization of algorithm DOT on an ,ideal' theoretical parallel machine. Performances of the implementations are analyzed and evaluated using large transportation networks, and two types of parallel computing platforms: a distributed network of Unix workstations and a SUN shared-memory machine containing eight processors. Satisfactory speed-ups in the running time of sequential algorithms are achieved, in particular for shared-memory machines. Numerical results indicate that shared-memory computers constitute the most appropriate type of parallel computing platforms for the computation of dynamic shortest paths for real-time ITS applications. [source] The combination of a blood test and Fibroscan improves the non-invasive diagnosis of liver fibrosisLIVER INTERNATIONAL, Issue 10 2009Jérôme Boursier Abstract Background and aims: Blood tests and liver stiffness evaluation (LSE) by ultrasonographic elastometry are accurate tools for diagnosing liver fibrosis. We evaluated whether their synchronous combination in new scores could improve the diagnostic accuracy and reduce liver biopsy requirement in algorithm. Methods: Three hundred and ninety patients with chronic liver disease of miscellaneous causes were included. Five blood fibrosis tests were evaluated: APRI, FIB-4, Hepascore, Fibrotest and FibroMeter. The reference was fibrosis Metavir staging. Results: Diagnosis of significant fibrosis (Metavir F,2). The most accurate synchronous combination was FibroMeter+LSE, which provided a significantly higher area under the receiver operating characteristic curve (0.892) than LSE alone (0.867, P=0.011) or Fibrometer (0.834, P<10,3). An algorithm using the FibroMeter+LSE combination and then a liver biopsy in indeterminate cases had 91.9% diagnostic accuracy and required significantly fewer biopsies (20.2%) than previously published Bordeaux algorithm (28.6%, P=0.02) or sequential algorithm for fibrosis evaluation (SAFE) (55.7%, P<10,3). The Angers algorithm performance was not significantly different between viral hepatitis and other causes. Diagnosis of cirrhosis. The most accurate synchronous combination was LSE+FibroMeter, which provided ,90% predictive values for cirrhosis in 90.6% of patients vs 87.4% for LSE (P=0.02) and 57.9% for FibroMeter (P<10,3). An algorithm including the LSE+FibroMeter combination, and then a liver biopsy in indeterminate cases, had a significantly higher diagnostic accuracy than the SAFE algorithm (91.0 vs 79.8%, P<10,3), and required significantly fewer biopsies than the Bordeaux algorithm (9.3 vs 25.3%, P<10,3). Conclusion: The synchronous combination of a blood test plus LSE improves the accuracy of the non-invasive diagnosis of liver fibrosis and, consequently, markedly decreases the biopsy requirement in the diagnostic algorithm, notably to <10% in cirrhosis diagnosis. [source] | |||||||||||||