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Institution

National Cheng Kung University

EducationTainan City, Taiwan
About: National Cheng Kung University is a education organization based out in Tainan City, Taiwan. It is known for research contribution in the topics: Population & Thin film. The organization has 49723 authors who have published 69799 publications receiving 1437420 citations. The organization is also known as: NCKU.


Papers
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Journal ArticleDOI
TL;DR: The global impact on public health of elevated arsenic (As) in water supplies is highlighted by an increasing number of countries worldwide reporting high As concentrations in drinking water as discussed by the authors, which is known in 14 out of 20 countries: Argentina, Bolivia, Brazil, Chile, Colombia, Cuba, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Peru and Uruguay.

443 citations

Proceedings ArticleDOI
25 Jul 2010
TL;DR: The experimental results show that UP-Growth not only reduces the number of candidates effectively but also outperforms other algorithms substantially in terms of execution time, especially when the database contains lots of long transactions.
Abstract: Mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. Although a number of relevant approaches have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets. Such a large number of candidate itemsets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility itemsets. In this paper, we propose an efficient algorithm, namely UP-Growth (Utility Pattern Growth), for mining high utility itemsets with a set of techniques for pruning candidate itemsets. The information of high utility itemsets is maintained in a special data structure named UP-Tree (Utility Pattern Tree) such that the candidate itemsets can be generated efficiently with only two scans of the database. The performance of UP-Growth was evaluated in comparison with the state-of-the-art algorithms on different types of datasets. The experimental results show that UP-Growth not only reduces the number of candidates effectively but also outperforms other algorithms substantially in terms of execution time, especially when the database contains lots of long transactions.

442 citations

Journal ArticleDOI
TL;DR: This paper builds a relational network DEA model, taking into account the interrelationship of the processes within the system, to measure the efficiency of the system and those of the process at the same time, and decomposes the system efficiency into the sum of the inefficiency slacks of its component processes connected in parallel.

442 citations

Journal ArticleDOI
TL;DR: In this article, degradation models and data are used to make inferences and predictions about a failure-time distribution, and the connection between degradation reliability models and failure time reliability models is explained.
Abstract: High reliability systems generally require individual system components having extremely high reliability over long periods of time. Short product development times require reliability tests to be conducted with severe time constraints. Frequently few or no failures occur during such tests, even with acceleration. Thus, it is difficult to assess reliability with traditional life tests that record only failure times. For some components, degradation measures can be taken over time. A relationship between component failure and amount of degradation makes it possible to use degradation models and data to make inferences and predictions about a failure-time distribution. This article describes degradation reliability models that correspond to physical-failure mechanisms. We explain the connection between degradation reliability models and failure-time reliability models. Acceleration is modeled by having an acceleration model that describes the effect that temperature (or another accelerating variable) has on...

442 citations

Journal ArticleDOI
TL;DR: In this paper, the authors performed a prospective, international, observational study of 844 hospitalized patients with blood cultures positive for Streptococcus pneumoniae and evaluated the impact of concordant antibiotic therapy (i.e., receipt of a single antibiotic with in vitro activity against S. pneumoniae) versus discordant therapy (inactive in vitro) on mortality at 14 days.
Abstract: We performed a prospective, international, observational study of 844 hospitalized patients with blood cultures positive for Streptococcus pneumoniae. Fifteen percent of isolates had in vitro intermediate susceptibility to penicillin (minimum inhibitory concentration [MIC], 0.12-1 microg/mL), and 9.6% of isolates were resistant (MIC, >or=2 microg/mL). Age, severity of illness, and underlying disease with immunosuppression were significantly associated with mortality; penicillin resistance was not a risk factor for mortality. The impact of concordant antibiotic therapy (i.e., receipt of a single antibiotic with in vitro activity against S. pneumoniae) versus discordant therapy (inactive in vitro) on mortality was assessed at 14 days. Discordant therapy with penicillins, cefotaxime, and ceftriaxone (but not cefuroxime) did not result in a higher mortality rate. Similarly, time required for defervescence and frequency of suppurative complications were not associated with concordance of beta-lactam antibiotic therapy. beta-Lactam antibiotics should still be useful for treatment of pneumococcal infections that do not involve cerebrospinal fluid, regardless of in vitro susceptibility, as determined by current NCCLS breakpoints.

441 citations


Authors

Showing all 49872 results

NameH-indexPapersCitations
Yi Chen2174342293080
Yang Yang1642704144071
R. E. Hughes1541312110970
Mercouri G. Kanatzidis1521854113022
Thomas J. Smith1401775113919
Hui Li1352982105903
Gerald M. Reaven13379980351
Chi-Huey Wong129122066349
Joseph P. Vacanti11944150739
Kai Nan An10995351638
Ding-Shinn Chen10477446068
James D. Neaton10133164719
David C. Christiani100105255399
Jo Shu Chang9963937487
Yu Shyr9854239527
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202373
2022315
20213,425
20203,154
20192,895
20182,764