Institution
Clarkson University
Education•Potsdam, New York, United States•
About: Clarkson University is a education organization based out in Potsdam, New York, United States. It is known for research contribution in the topics: Particle & Turbulence. The organization has 4414 authors who have published 10009 publications receiving 305356 citations. The organization is also known as: Thomas S. Clarkson Memorial School of Technology & Thomas S. Clarkson Memorial College of Technology.
Papers published on a yearly basis
Papers
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79 citations
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TL;DR: The results of a simulation analysis of the use of three job shop simulation scheduling rules which focus on inducing efficiency in the shop are presented and two of these rules show significant gains in efficiency and, unexpectedly, they also showsignificant gains in effectiveness.
Abstract: The need for increased productivity in small batch manufacturing has recently brought focus to the topics and concepts of group technology. The results of a simulation analysis of the use of three job shop simulation scheduling rules which focus on inducing efficiency in the shop is presented. Two of these rules show significant gains in efficiency and, unexpectedly, they also show significant gains in effectiveness. These rules, in effect, induce the efficiency gains expected with group technology implementation.
79 citations
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25 Sep 2011
TL;DR: Three ways to enhance the current code-completion systems to work more effectively with large APIs are proposed, including two methods for sorting APIs, by type hierarchy and by use count, and a proposal to group API proposals by their functional roles which can help maintain a well-ordered, meaningful list of API proposals in the presence of dynamic reordering.
Abstract: Code Completion is one of the most popular IDE features for accessing APIs, freeing programmers from remembering specific details about an API and reducing keystrokes. We propose three ways to enhance the current code-completion systems to work more effectively with large APIs. First, we propose two methods for sorting APIs, by type hierarchy and by use count, and show that their use significantly reduces the number of API proposals a user must navigate while using Code Completion. Second, we show that context-specific filtering of inappropriate proposals can also reduce the number of proposals a user must navigate. Third, we propose to group API proposals by their functional roles, which can help maintain a well-ordered, meaningful list of API proposals in the presence of dynamic reordering. These functionalities are grouped into a research prototype, BCC (Better Code Completion). We evaluated fourteen configurations of BCC by simulating Code Completion nearly three million times on nine open-source Java projects that utilize AWT/Swing.
79 citations
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TL;DR: This study shows that the application of the neural network approach incorporating fundamental accounting variables results in forecasts that are more accurate than linear forecasting models, revealing limitations of the forecasting capacity of investors in the security market when compared to neural network models.
Abstract: In this paper, we present a comparative analysis of the forecasting accuracy of univariate and multivariate linear models that incorporate fundamental accounting variables (i.e., inventory, accounts receivable, and so on) with the forecast accuracy of neural network models. Unique to this study is the focus of our comparison on the multivariate models to examine whether the neural network models incorporating the fundamental accounting variables can generate more accurate forecasts of future earnings than the models assuming a linear combination of these same variables. We investigate four types of models: univariate-linear, multivariate-linear, univariate-neural network, and multivariate-neural network using a sample of 283 firms spanning 41 industries. This study shows that the application of the neural network approach incorporating fundamental accounting variables results in forecasts that are more accurate than linear forecasting models. The results also reveal limitations of the forecasting capacity of investors in the security market when compared to neural network models.
79 citations
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TL;DR: Lee et al. as mentioned in this paper developed algorithms to discriminate potentially toxic cyanobacterial blooms from other harmless phytoplankton blooms and to extract relative phycocyanin abundances from MODIS satellite data.
79 citations
Authors
Showing all 4454 results
Name | H-index | Papers | Citations |
---|---|---|---|
Xuan Zhang | 119 | 1530 | 65398 |
Michael R. Hoffmann | 109 | 500 | 63474 |
Philip K. Hopke | 91 | 929 | 40612 |
Sudipta Seal | 86 | 514 | 32788 |
Egon Matijević | 81 | 466 | 25015 |
Mark J. Ablowitz | 74 | 374 | 27715 |
Kim R. Dunbar | 74 | 470 | 20262 |
Maureen E. Callow | 70 | 188 | 14957 |
Igor M. Sokolov | 69 | 673 | 20256 |
James A. Callow | 68 | 186 | 14424 |
Michal Borkovec | 66 | 235 | 19638 |
Sergiy Minko | 66 | 256 | 18723 |
Corwin Hansch | 66 | 342 | 26798 |
David H. Russell | 66 | 477 | 17172 |
Nitash P. Balsara | 62 | 411 | 15083 |