scholarly journals Model-based approach to improve class 1 AVO attributes

2021 ◽  
pp. 100076
Author(s):  
Ashok Yadav ◽  
Soumya Nayak ◽  
Samit Mondal ◽  
Rima Chatterjee
Keyword(s):  
Class 1 ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 176-182
Author(s):  
Reskiani Reskiani ◽  
Supriadi Supriadi

The topic of buffer has connections between concepts and some prerequisite materials that students should understand to be able to facilitate this material. The lack of mastery on the material will lower the learning outcomes. This study aimed to improve students’ learning outcomes on buffer through the implementation of advance organizer learning model based on numbered heads together (NHT). This study was one group pretest-posttest design. The sample of this study was students of 11th grade Science at SMAN 2 Balaesang consisting of class XI Science 1 as the experiment class 1 with 33 students and class XI Science 2 as the experiment class 2 with 32 students. The effectiveness of the implementation of advance organizer learning model NHT-based can be seen from the average N-gain value of the experimental classes. The average N-gain value of experimental class 1 was 0.69 included in the medium category. While the average N-gain value of experimental class 2 was 0.71 included in the high category. Data analysis showed that the average value of students learning scores was greater than 65, where for the experimental class 1 was 76.36 and the experimental class 2 was 76.71. The advance organizer learning model NHT-based improved learning outcomes of students in 11th grade Science on buffer at SMAN 2 Balaesang.


Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. C59-C69 ◽  
Author(s):  
E. Causse ◽  
M. Riede ◽  
A. J. van Wijngaarden ◽  
A. Buland ◽  
J. F. Dutzer ◽  
...  

Linear equations used to approximate reflection coefficient-versus-angle curves are usually valid only for small seismic parameter changes across reflectors, and they are rather inaccurate close to the critical angle. These inaccuracies affect the quality of AVO analysis and cause systematic errors when estimating relative seismic-parameter variations at reflectors, especially for density. We present an optimal model-based approach to build more accurate linear AVO approximations. Their basis functions are calculated by applying singular value decomposition to realistic modeled AVO curves. By extending the validity range of linear approximations to larger angles, this approach helps when using information contained at near-critical offsets. It alsooffers several advantages in other situations. The basis functions of the new approximations are orthogonal. Their coefficients represent new AVO attributes that can be used either to classify AVO responses directly, or to obtain more accurate estimates of usual AVO attributes (intercept, gradient, and possibly a third coefficient). This leads to a better estimation of seismic-parameter contrasts at reflecting interfaces. These coefficients are naturally sorted in decreasing order of importance. Therefore, the proper number of terms in the proposed equations can be chosen easily to offer an optimal compromise between noise and the information carried by each coefficient. Synthetic tests confirm the robustness of the method. This flexible and robust approach will be particularly well adapted for three-parameter AVO analysis.


Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. C71-C79 ◽  
Author(s):  
E. Causse ◽  
M. Riede ◽  
A. J. van Wijngaarden ◽  
A. Buland ◽  
J. F. Dutzer ◽  
...  

AVO analysis can be conducted by estimating amplitude variation with offset (AVO) attributes from seismic prestack data and by characterizing the measured amplitude responses by the position of their projection in the attribute space. The most common AVO attributes are the intercept (zero-offset reflectivity) and AVO gradient. We have constructed an optimized, model-based linear AVO equation that is more accurate than usual AVO approximations. The parameters of this equation represent new AVO attributes that are more directly related to the information contained in seismic reflection amplitudes. We use these new AVO attributes to classify reflector responses from field data. Five seismic facies are defined that are characterized by differentdistributions of seismic parameters. Nine reflector classes are formed by associating appropriate pairs of facies. The expected locations of the different reflector classes in the space of optimized attributes are found by modeling and are used to derive a classification scheme. This scheme is applied to sections of optimized attributes calculated from the prestack data, leading to a vertical section showing the distribution of most probable facies in an area containing a sand reservoir. We compare the new approach to classification with intercept and gradient. The new method is more robust and less sensitive to the number of attributes (two or three) used for classification. It offers an optimal, flexible, and robust way of extracting the information contained in reflection amplitudes by simple linear AVO equations.


2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.


2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.


2019 ◽  
Vol 24 (5) ◽  
pp. 14-15
Author(s):  
Jay Blaisdell ◽  
James B. Talmage

Abstract Ratings for “non-specific chronic, or chronic reoccurring, back pain” are based on the diagnosis-based impairment method whereby an impairment class, usually representing a range of impairment values within a cell of a grid, is selected by diagnosis and “specific criteria” (key factors). Within the impairment class, the default impairment value then can be modified using non-key factors or “grade modifiers” such as functional history, physical examination, and clinical studies using the net adjustment formula. The diagnosis of “nonspecific chronic, or chronic reoccurring, back pain” can be rated in class 0 and 1; the former has a default value of 0%, and the latter has a default value of 2% before any modifications. The key concept here is that the physician believes that the patient is experiencing pain, yet there are no related objective findings, most notably radiculopathy as distinguished from “nonverifiable radicular complaints.” If the individual is found not to have radiculopathy and the medical record shows that the patient has never had clinically verifiable radiculopathy, then the diagnosis of “intervertebral disk herniation and/or AOMSI [alteration of motion segment integrity] cannot be used.” If the patient is asymptomatic at maximum medical improvement, then impairment Class 0 should be chosen, not Class 1; a final whole person impairment rating of 1% indicates incorrect use of the methodology.


Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery

Author(s):  
Jonathan Jacky ◽  
Margus Veanes ◽  
Colin Campbell ◽  
Wolfram Schulte
Keyword(s):  

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