Institution
Clemson University
Education•Clemson, South Carolina, United States•
About: Clemson University is a education organization based out in Clemson, South Carolina, United States. It is known for research contribution in the topics: Population & Control theory. The organization has 20556 authors who have published 42518 publications receiving 1170779 citations. The organization is also known as: Clemson Agricultural College of South Carolina.
Topics: Population, Control theory, Poison control, Optical fiber, Fiber
Papers published on a yearly basis
Papers
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TL;DR: The authors pointed out that making acquisitions, although a popular strategy, may not always lead to positive firm performance, and offered several explanations for this relationship, including that acquisitions may not necessarily lead to better performance.
Abstract: Making acquisitions, although a popular strategy, may not always lead to positive firm performance. Researchers have offered several explanations for this relationship. One is that acquisitions lea...
565 citations
TL;DR: In this article, the degradation and durability of polymers are reviewed in the presence of nanoparticles/nanocomposites under different environmental conditions, and the nanoparticulates have been incorporated into polymer as " nano-additives" for both purposes: degradation and stabilization.
565 citations
TL;DR: The authors provided the first systematic empirical analysis of the economic determinants of the formation of free trade agreements and of the likelihood of FTAs between pairs of countries using a qualitative choice model.
564 citations
TL;DR: It is shown that the common trend TPR and Sawa’s Bayes criteria procedures seem optimal for most climate time series, whereas the SNH procedure and its nonparametric variant are probably best for mostClimate time series.
Abstract: This review article enumerates, categorizes, and compares many of the methods that have been proposed to detect undocumented changepoints in climate data series. The methods examined include the standard normal homogeneity (SNH) test, Wilcoxon’s nonparametric test, two-phase regression (TPR) procedures, inhomogeneity tests, information criteria procedures, and various variants thereof. All of these methods have been proposed in the climate literature to detect undocumented changepoints, but heretofore there has been little formal comparison of the techniques on either real or simulated climate series. This study seeks to unify the topic, showing clearly the fundamental differences among the assumptions made by each procedure and providing guidelines for which procedures work best in different situations. It is shown that the common trend TPR and Sawa’s Bayes criteria procedures seem optimal for most climate time series, whereas the SNH procedure and its nonparametric variant are probably best whe...
562 citations
TL;DR: It is concluded that the PPCEM provides an efficient and effective means to design a scalable product platform and corresponding product family, promoting increased commonality within the product family with minimal performance tradeoff.
Abstract: In this paper we focus on scale-based product families derived from scalable product platforms that can be exploited from both a functional and a manufacturing standpoint to increase the potential benefits of having a common platform. While many companies have been successful with scalable product platforms, few, if any, have instituted a systematic approach to design (i) the product platform and (ii) the corresponding family of products which are scaled around the product platform. Accordingly, in this paper we address the following question: How can a scalable product platform and its resulting product family be efficiently and effectively modeled, analyzed, and designed?
562 citations
Authors
Showing all 20718 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Yury Gogotsi | 171 | 956 | 144520 |
| Philip S. Yu | 148 | 1914 | 107374 |
| Aaron Dominguez | 147 | 1968 | 113224 |
| Danny Miller | 133 | 512 | 71238 |
| Marco Ajello | 131 | 535 | 58714 |
| David C. Montefiori | 129 | 920 | 70049 |
| Frank L. Lewis | 114 | 1045 | 60497 |
| Jianqing Fan | 104 | 488 | 58039 |
| Wei Chen | 103 | 1438 | 44994 |
| Ken A. Dill | 99 | 401 | 41289 |
| Gerald Schubert | 98 | 614 | 34505 |
| Rod A. Wing | 98 | 333 | 47696 |
| Feng Chen | 95 | 2138 | 53881 |
| Jimin George | 94 | 331 | 62684 |
| François Diederich | 93 | 843 | 46906 |