نتایج جستجو برای: cross cutting

تعداد نتایج: 527225  

Journal: :Journal of food science 2010
Xiangwu Nou Yaguang Luo

Currently, most fresh-cut processing facilities in the United States use chlorinated water or other sanitizer solutions for microbial reduction after lettuce is cut. Freshly cut lettuce releases significant amounts of organic matter that negatively impacts the effectiveness of chlorine or other sanitizers for microbial reduction. The objective of this study is to evaluate whether a sanitizer wa...

Journal: :Slovenske divadlo /The Slovak Theatre 2020

Journal: :Information & Software Technology 2017
Birgitta Lindström A. Jefferson Offutt Daniel Sundmark Sten F. Andler Paul Pettersson

Context: Testing for properties such as robustness or security is complicated because their concerns are often repeated in many locations and muddled with the normal code. Such “cross-cutting concerns” include things like interrupt events, exception handling, and security protocols. Aspect-oriented (AO) modeling allows developers to model the cross-cutting behavior independently of the normal b...

2013
Marco Molinaro Sanjeeb Dash Santanu Dey François Margot R. Ravi

Cutting planes for a mixed-integer program are linear inequalities which are satisfied by all feasible solutions of the latter. These are fundamental objects in mixed-integer programming that are critical for solving large-scale problems in practice. One of the main challenge in employing them is that there are limitless possibilities for generating cutting planes; the selection of the stronges...

2002
K. Tanaka

Supporting material prepared for consideration by the Intergovernmental Panel on Climate Change. This supporting material has not been subject to formal IPCC review process. Preface The Intergovernmental Panel on Climate Change (IPCC) completed its Second Assessment Report in 1995. The IPCC has three Working Groups that focus on different aspects of climate change, viz. natural science, impacts...

1987
J S Marron

Partitioned cross-validation is proposed as a method for overcoming the large amounts of across sample variability to which ordinary cross-validation is subject. The price for cutting down on the sample noise is that a type of bias is introduced. A theory is presented for optimal trade-off of this variance and bias. Comparison with other bandwidth selection methods is given.

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