scholarly journals An analysis of the relationship between conditional entropy and failed error propagation in software testing

2014 ◽  
Author(s):  
Kelly Androutsopoulos ◽  
David Clark ◽  
Haitao Dan ◽  
Robert M. Hierons ◽  
Mark Harman
Keyword(s):  
Software Testing ◽  
Error Propagation ◽  
Conditional Entropy ◽  
The Relationship

scholarly journals BASELINE ERROR ANALYSIS AND EXPERIMENTAL VALIDATION FOR HEIGHT MEASUREMENT OF FORMATION INSAR SATELLITE

2018 ◽  
Vol XLII-3 ◽  
pp. 371-376
Author(s):  
X. Gao ◽  
T. Li ◽  
X. Zhang ◽  
X. Geng
Keyword(s):  
Stochastic Model ◽  
Error Propagation ◽  
Experimental Validation ◽  
Simulation Analysis ◽  
Srtm Dem ◽  
Height Measurement ◽  
Spatial Distribution Characteristics ◽  
Propagation Rule ◽  
The Relationship ◽  
Baseline Error

In this paper, we proposed the stochastic model of InSAR height measurement by considering the interferometric geometry of InSAR height measurement. The model directly described the relationship between baseline error and height measurement error. Then the simulation analysis in combination with TanDEM-X parameters was implemented to quantitatively evaluate the influence of baseline error to height measurement. Furthermore, the whole emulation validation of InSAR stochastic model was performed on the basis of SRTM DEM and TanDEM-X parameters. The spatial distribution characteristics and error propagation rule of InSAR height measurement were fully evaluated.

scholarly journals Assessment of Precipitation Error Propagation in Discharge Simulations over the Contiguous United States

2021 ◽  
Author(s):  
Nergui Nanding ◽  
Huan Wu ◽  
Jing Tao ◽  
Viviana Maggioni ◽  
Hylke E. Beck ◽  
...  
Keyword(s):  
United States ◽  
Error Propagation ◽  
Hydrological Model ◽  
River Basins ◽  
Distributed Hydrological Model ◽  
Highly Nonlinear ◽  
Relative Errors ◽  
The Relationship ◽  
Continental Climate ◽  
Peak Discharges

AbstractThis study characterizes precipitation error propagation through a distributed hydrological model based on the river basins across the Contiguous United States (CONUS), to better understand the relationship between errors in precipitation inputs and simulated discharge (i.e., P-Q error relationship). The NLDAS-2 precipitation and its simulated discharge are used as the reference to compare with TMPA-3B42 V7, TMPA-3B42RT V7, StageIV, CPC-U, MERRA-2, and MSWEP-2.2 for 1,548 well gauged river basins. The relative errors in multiple conventional precipitation products and their corresponding discharges are analysed for the period of 2002-2013. The results reveal positive linear P-Q error relationships at annual and monthly timescales, and the stronger linearity for larger temporal accumulations. Precipitation errors can be doubled in simulated annual accumulated discharge. Moreover, precipitation errors are strongly dampened in basins characterized by temperate and continental climate regimes, particularly for peak discharges, showing highly nonlinear relationships. Radar-based precipitation product consistently shows dampening effects on error propagation through discharge simulations at different accumulation timescales compared to the other precipitation products. Although basin size and topography also influence the P-Q error relationship and propagation of precipitation errors, their roles depend largely on precipitation products, seasons and climate regimes.

scholarly journals Research on Entity Label Value Assignment Method in Knowledge Graph

2021 ◽  
Vol 14 (2) ◽  
pp. 63
Author(s):  
Linqing Yang ◽  
Bo Liu ◽  
Youpei Huang ◽  
Xiaozhuo Li
Keyword(s):  
Conditional Entropy ◽  
Knowledge Graph ◽  
Specific Knowledge ◽  
Relationship Type ◽  
Value Assignment ◽  
External Resources ◽  
Domain Specific ◽  
Assignment Method ◽  
Domain Specific Knowledge ◽  
The Relationship

The lack of entity label values is one of the problems faced by the application of Knowledge Graph. The method of automatically assigning entity label values still has shortcomings, such as costing more resources during training, leading to inaccurate label value assignment because of lacking entity semantics. In this paper, oriented to domain-specific Knowledge Graph, based on the situation that the initial entity label values of all triples are completely unknown, an Entity Label Value Assignment Method (ELVAM) based on external resources and entropy is proposed. ELVAM first constructs a Relationship Triples Cluster according to the relationship type, and randomly extracts the triples data from each cluster to form a Relationship Triples Subset; then collects the extended semantic text of the entities in the subset from the external resources to obtain nouns. Information Entropy and Conditional Entropy of the nouns are calculated through Ontology Category Hierarchy Graph, so as to obtain the entity label value with moderate granularity. Finally, the Label Triples Pattern of each Relationship Triples Cluster is summarized, and the corresponding entity is assigned the label value according to the pattern. The experimental results verify the effectiveness of ELVAM in assigning entity label values in Knowledge Graph.

scholarly journals ERROR ANALYSIS AND VALIDATION FOR INSAR HEIGHT MEASUREMENT INDUCED BY SLANT RANGE

2018 ◽  
Vol XLII-3 ◽  
pp. 2321-2326
Author(s):  
X. Zhang ◽  
T. Li ◽  
W. Fan ◽  
X. Geng
Keyword(s):  
Error Propagation ◽  
Propagation Model ◽  
Large Area ◽  
Height Measurement ◽  
Slant Range ◽  
Simulation Validation ◽  
Spatial Distribution Characteristics ◽  
Propagation Rule ◽  
Range Error ◽  
The Relationship

InSAR technique is an important method for large area DEM extraction. Several factors have significant influence on the accuracy of height measurement. In this research, the effect of slant range measurement for InSAR height measurement was analysis and discussed. Based on the theory of InSAR height measurement, the error propagation model was derived assuming no coupling among different factors, which directly characterise the relationship between slant range error and height measurement error. Then the theoretical-based analysis in combination with TanDEM-X parameters was implemented to quantitatively evaluate the influence of slant range error to height measurement. In addition, the simulation validation of InSAR error model induced by slant range was performed on the basis of SRTM DEM and TanDEM-X parameters. The spatial distribution characteristics and error propagation rule of InSAR height measurement were further discussed and evaluated.

Generalized Two-Point Method Using Inverse Filtering for Surface Profile Measurement – Theoretical Analysis and Experimental Results for Error Propagation –

2014 ◽  
Vol 8 (1) ◽  
pp. 43-48 ◽  
Author(s):  
Eiki Okuyama ◽  
◽  
Hiromi Ishikawa
Keyword(s):  
Theoretical Analysis ◽  
Error Propagation ◽  
Surface Profile ◽  
Sampling Interval ◽  
Experimental Results ◽  
Profile Measurement ◽  
Inverse Filtering ◽  
Multiple Sensors ◽  
The Difference ◽  
The Relationship

Error separation techniques of the surface profile from parasitic motions have been developed for the straightness profile measurement of a mechanical workpiece. These are known as software datums, which separate the surface profile from the parasitic motions by using multiple sensors and/or multiple orientations. The authors proposed a generalized twopoint method that used the difference with either integration or inverse filtering. This method can take any sampling interval. In this article, the relationship between the ratio of the sensor distance to the sampling interval and the error propagation at the lowest spatial frequency is clarified. Furthermore, experimental results are described to support the theoretical analysis of the error propagation.

scholarly journals Biodiversity, functional redundancy and system stability: subtle connections

2018 ◽  
Vol 15 (147) ◽  
pp. 20180367 ◽  
Author(s):  
Robert E. Ulanowicz
Keyword(s):  
Conditional Entropy ◽  
Functional Redundancy ◽  
System Stability ◽  
Biomass Distribution ◽  
Information Theoretic ◽  
Trophic Networks ◽  
System Components ◽  
Hill Numbers ◽  
Ensemble Systems ◽  
The Relationship

The relationship between biodiversity and functional redundancy has remained ambiguous for over a half-century, likely due to an inability to distinguish between positivist and apophatic (that which is missing) properties of ecosystems. Apophases are best addressed by mathematics that is predicated upon absence, such as information theory. More than 40 years ago, the conditional entropy of a flow network was proposed as a formulaic way to quantify trophic functional redundancy, an advance that has remained relatively unappreciated. When applied to a collection of 25 fully quantified trophic networks, this authoritative index correlates only poorly and transitively with conventional Hill numbers used to represent biodiversity. Despite such a weak connection, the underlying biomass distribution remains useful in conjunction with the qualitative diets of system components for providing a quick and satisfactory emulation of a system's functional redundancy. Furthermore, an information-theoretic cognate of the Wigner Semicircle Rule can be formulated using network conditional entropy to provide clues to the relative stability of any ecosystem under study. The necessity for a balance between positivist and apophatic attributes pertains to the functioning of a host of other living ensemble systems.

A Model of Error Propagation in Conjunctive Decisions and its Application to Database Quality Management

2012 ◽  
Vol 23 (1) ◽  
pp. 103-126 ◽  
Author(s):  
Irit Askira Gelman
Keyword(s):  
Error Propagation ◽  
Information Quality ◽  
Decision Rules ◽  
Cost Benefit ◽  
Residential Real Estate ◽  
Selection Decisions ◽  
Proposed Model ◽  
Quality Assessments ◽  
The Relationship ◽  
System Designs

This study centers on the accuracy dimension of information quality and models the relationship between input accuracy and output accuracy in a popular class of applications. These applications consist of dichotomous decisions that are implemented through conjunction of selected criteria. In particular, the model provides the tools for quantifying the effect of errors in each decision input on the accuracy of a decision. Application of the model is illustrated through the example of a residential real estate database, where users’ preferences are captured by conjunctive decision rules. This example demonstrates how the new model can be utilized for quantifying the aggregate damage that errors in different database attributes inflict on property selection decisions. Finally, this paper reports on an initial empirical validation of the proposed model through a series of Monte Carlo simulations. Numerical estimates of the model that have been developed through this inquiry can be useful for data and information quality assessments or policy-making purposes. Mainly, they can be integrated into cost-benefit analyses that assess alternative data accuracy enhancements or process and system designs.

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