Results 271 to 280 of about 22,112,797 (304)

Protein Sequence Analysis by Proximities

2016
Sequence data are widely used to get a deeper insight into biological systems. From a data analysis perspective they are given as a set of sequences of symbols with varying length. In general they are compared using nonmetric score functions. In this form the data are nonstandard, because they do not provide an immediate metric vector space and their ...
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Sampling and Proximate Analysis

1987
Considerable information about a food sample can be gained through a general analysis of its main components—moisture, crude fat, crude protein, ash, and crude fiber. The determination of the percentages of these components is termed a proximate analysis.
Leonard W. Aurand, A. Edwin Woods, Marion R. Wells   +2 more
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Proximal Analysis and the Minimal Time Function

SIAM Journal on Control and Optimization, 1998
Continuing and refining previous work [e.g., \textit{F. H. Clarke, Yu. S. Ladyaev} and \textit{P. R. Wolenski}, J. Math. Anal. Appl. 196, No. 2, 722-735 (1995; Zbl 0865.49015); \textit{F. J. Clarke, R. J. Stern} and \textit{P. R. Wolenski}, J. Convex Anal. 2, No.
Wolenski, Peter R., Zhuang, Yu
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Proximal Decision Analysis with Imperfect Information

Management Science, 1976
In proximal decision analysis the value of a decision depends on a vector of state variables s and a vector of decision variables d in a quadratic fashion. Suppose some data, represented by a vector x, can be obtained. This paper describes a technique for using the data and develops an expression for the value of the information conveyed by the data ...
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Exploratory analysis of point proximity in subspaces

Object recognition supported by user interaction for service robots, 2003
We consider clustering as computation of a structure of proximity relationships within a data set in a feature space or its subspaces. We propose a data structure to represent such relationships, and show that, despite unavoidable arbitrariness in the clustering algorithms, constructive uses of their results can be made by studying correlations between
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Proximity and Network Analysis

2018
Proximity analysis is an important function in GIS as it covers a wide range of topics that help in answering many spatial questions, such as 1. How close is the observation well to a treatment plant? 2. Do any wells fall within 500 m of a fault system? 3. What are the distances between the wells and the treatment plant?
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Proximate Composition Analysis

2015
The proximate composition of foods includes moisture, ash, lipid, protein and carbohydrate contents. These food components may be of interest in the food industry for product development, quality control (QC) or regulatory purposes. Analyses used may be rapid methods for QC or more accurate but time-consuming official methods.
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Proximate Composition Analysis.

Progress in drug research. Fortschritte der Arzneimittelforschung. Progres des recherches pharmaceutiques, 2016
The proximate composition of foods includes moisture, ash, lipid, protein and carbohydrate contents. These food components may be of interest in the food industry for product development, quality control (QC) or regulatory purposes. Analyses used may be rapid methods for QC or more accurate but time-consuming official methods.
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Genome-Wide Proximal Promoter Analysis and Interpretation

2009
High-throughput gene expression technologies based on DNA microarrays allow the examination of biological systems. However, the interpretation of the complex molecular descriptions generated by these approaches is still challenging. The development of new methodologies to identify common regulatory mechanisms involved in the control of the expression ...
Corrales, F.J. (Fernando José), Guruceaga, E. (Elizabeth), Segura, V. (Víctor), Rubio, A. (Ángel)   +3 more
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Analysis of Skew-Symmetry in Proximity Data

2011
Skew-symmetric data matrices can be represented in graphical displays in different ways. Some simple procedures that can be easily performed by standard software will be proposed and applied in this communication. Other methods based on spatial models that need ad hoc computational programs will be also reviewed emphasizing advantages and disadvantages
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