Multichannel band-controlled deconvolution based on a data-driven structural regularization

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. R401-R411 ◽  
Author(s):  
Xin Du ◽  
Guofa Li ◽  
Mo Zhang ◽  
Hao Li ◽  
Wuyang Yang ◽  
...  
Keyword(s):  
Seismic Data ◽  
Data Driven ◽  
Inversion Result ◽  
Spatial Continuity ◽  
Structure Characteristics ◽  
The Core ◽  
Alternating Direction ◽  
Full Band ◽  
Weak Reflection ◽  
The Cost

Sparse deconvolution methods frequently invert for subsurface reflection impulses and adopt a trace-by-trace processing pattern. However, following this approach causes unreliability of the estimated reflectivity due to the nonuniqueness of the inverse problem, the poor spatial continuity of structures in the reconstructed reflectivity section, and the suppression on the reflection signals with small amplitudes. We have developed a structurally constrained multichannel band-controlled deconvolution (SC-MBCD) algorithm to alleviate these three issues. The algorithm inverts for a high-resolution seismogram rather than the full-band reflectivity series, thereby reducing the multiple solutions in the inversion and enhancing the reliability of processing results. We also exploited a structural constraint term to guarantee the spatial continuity of the structures, and we enhanced the relatively weak signals. The reflection structure characteristics, defined and extracted from the observed stacked seismic data, are the core of the structural regularization item. We solved the cost function of the SC-MBCD by the alternating direction method of multipliers algorithm. Synthetic model and field data examples demonstrate the rationality of SC-MBCD and confirmed that the algorithm can provide a better inversion result than the conventional sparse spike inversion in terms of retrieving weak reflection events and guaranteeing stratal continuities.

scholarly journals Data-driven estimation of the sensitivity of target-oriented time-lapse seismic imaging to source geometry

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. R47-R58 ◽  
Author(s):  
Andrey H. Shabelansky ◽  
Alison Malcolm ◽  
Michael Fehler
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Time Lapse ◽  
Data Driven ◽  
Target Region ◽  
Data Driven Approach ◽  
Cost Of Time ◽  
The Cost ◽  
Time Lapse Imaging ◽  
Source Geometry

The goal of time-lapse imaging is to identify and characterize regions in which the earth’s material properties have changed between surveys. This requires an effective deployment of sources and receivers to monitor the region where changes are anticipated. Because each source adds to the acquisition cost, we should ensure that only those sources that best image the target are collected and used to form an image of the target region. This study presents a data-driven approach that estimates the sensitivity of target-oriented imaging to source geometry. The approach is based on the propagation of the recorded baseline seismic data backward in time through the entire medium and coupling it with the estimated perturbation in the subsurface. We test this approach using synthetic surface seismic and time-lapse VSP field-data from the SACROC field. These tests show that the use of the baseline seismic data enhances the robustness of the sensitivity estimate to errors, and can be used to select data that best image a target zone, thus increasing the signal-to-noise ratio of the image of the target region and reducing the cost of time-lapse acquisition, processing, and imaging.

Seismic data restoration via data-driven tight frame

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. V65-V74 ◽  
Author(s):  
Jingwei Liang ◽  
Jianwei Ma ◽  
Xiaoqun Zhang
Keyword(s):  
Seismic Data ◽  
Convex Sets ◽  
Main Idea ◽  
Tight Frame ◽  
Data Driven ◽  
Uzawa Algorithm ◽  
Sparse Regularization ◽  
Alternating Direction ◽  
Sparse Signal Representation ◽  
Data Restoration

Restoration/interpolation of missing traces plays a crucial role in the seismic data processing pipeline. Efficient restoration methods have been proposed based on sparse signal representation in a transform domain such as Fourier, wavelet, curvelet, and shearlet transforms. Most existing methods are based on transforms with a fixed basis. We considered an adaptive sparse transform for restoration of data with complex structures. In particular, we evaluated a data-driven tight-frame-based sparse regularization method for seismic data restoration. The main idea of the data-driven tight frame (TF) is to adaptively learn a set of framelet filters from the currently interpolated data, under which the data can be more sparsely represented; hence, the sparsity-promoting [Formula: see text]-norm (SPL1) minimization methods can produce better restoration results by using the learned filters. A split inexact Uzawa algorithm, which can be viewed as a generalization of the alternating direction of multiplier method (ADMM), was applied to solve the presented SPL1 model. Numerical tests were performed on synthetic and real seismic data for restoration of randomly missing traces over a regular data grid. Our experiments showed that our proposed method obtains the state-of-the-art restoration results in comparison with the traditional Fourier-based projection onto convex sets, the tight-frame-based method, and the recent shearlet regularization ADMM method.

Emotional Choices

2018 ◽  
Author(s):  
Robin Markwica
Keyword(s):  
Decision Making ◽  
Choice Behavior ◽  
Choice Theory ◽  
Cuban Missile Crisis ◽  
Coercive Diplomacy ◽  
The Core ◽  
Present Book ◽  
Action Model ◽  
The Cost ◽  
Dynamic Interplay

In coercive diplomacy, states threaten military action to persuade opponents to change their behavior. The goal is to achieve a target’s compliance without incurring the cost in blood and treasure of military intervention. Coercers typically employ this strategy toward weaker actors, but targets often refuse to submit and the parties enter into war. To explain these puzzling failures of coercive diplomacy, existing accounts generally refer to coercers’ perceived lack of resolve or targets’ social norms and identities. What these approaches either neglect or do not examine systematically is the role that emotions play in these encounters. The present book contends that target leaders’ affective experience can shape their decision-making in significant ways. Drawing on research in psychology and sociology, the study introduces an additional, emotion-based action model besides the traditional logics of consequences and appropriateness. This logic of affect, or emotional choice theory, posits that target leaders’ choice behavior is influenced by the dynamic interplay between their norms, identities, and five key emotions, namely fear, anger, hope, pride, and humiliation. The core of the action model consists of a series of propositions that specify the emotional conditions under which target leaders are likely to accept or reject a coercer’s demands. The book applies the logic of affect to Nikita Khrushchev’s decision-making during the Cuban missile crisis in 1962 and Saddam Hussein’s choice behavior in the Gulf conflict in 1990–91, offering a novel explanation for why coercive diplomacy succeeded in one case but not in the other.

scholarly journals The core academic and scientific disciplines underlying data-driven smart sustainable urbanism: an interdisciplinary and transdisciplinary framework

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
The Body ◽  
Data Driven ◽  
New Era ◽  
The Core ◽  
Sustainable Urbanism ◽  
Scientific Disciplines ◽  
Specific Direction ◽  
Research Problems ◽  
Urban Planning And Development ◽  
Application Potential

AbstractA new era is presently unfolding wherein both smart urbanism and sustainable urbanism processes and practices are becoming highly responsive to a form of data-driven urbanism under what has to be identified as data-driven smart sustainable urbanism. This flourishing field of research is profoundly interdisciplinary and transdisciplinary in nature. It operates out of the understanding that advances in knowledge necessitate pursuing multifaceted questions that can only be resolved from the vantage point of interdisciplinarity and transdisciplinarity. This implies that the research problems within the field of data-driven smart sustainable urbanism are inherently too complex and dynamic to be addressed by single disciplines. As this field is not a specific direction of research, it does not have a unitary disciplinary framework in terms of a uniform set of the academic and scientific disciplines from which the underlying theories can be drawn. These theories constitute a unified foundation for the practice of data-driven smart sustainable urbanism. Therefore, it is of significant importance to develop an interdisciplinary and transdisciplinary framework. With that in regard, this paper identifies, describes, discusses, evaluates, and thematically organizes the core academic and scientific disciplines underlying the field of data-driven smart sustainable urbanism. This work provides an important lens through which to understand the set of established and emerging disciplines that have high integration, fusion, and application potential for informing the processes and practices of data-driven smart sustainable urbanism. As such, it provides fertile insights into the core foundational principles of data-driven smart sustainable urbanism as an applied domain in terms of its scientific, technological, and computational strands. The novelty of the proposed framework lies in its original contribution to the body of foundational knowledge of an emerging field of urban planning and development.

scholarly journals Machine learning applied to simulations of collisions between rotating, differentiated planets

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Miles L. Timpe ◽  
Maria Han Veiga ◽  
Mischa Knabenhans ◽  
Joachim Stadel ◽  
Stefano Marelli
Keyword(s):  
Machine Learning ◽  
Planet Formation ◽  
Critical Role ◽  
Ensemble Methods ◽  
Terrestrial Planet ◽  
Data Driven ◽  
Analytic Methods ◽  
Accurate Treatment ◽  
Post Impact ◽  
The Cost

AbstractIn the late stages of terrestrial planet formation, pairwise collisions between planetary-sized bodies act as the fundamental agent of planet growth. These collisions can lead to either growth or disruption of the bodies involved and are largely responsible for shaping the final characteristics of the planets. Despite their critical role in planet formation, an accurate treatment of collisions has yet to be realized. While semi-analytic methods have been proposed, they remain limited to a narrow set of post-impact properties and have only achieved relatively low accuracies. However, the rise of machine learning and access to increased computing power have enabled novel data-driven approaches. In this work, we show that data-driven emulation techniques are capable of classifying and predicting the outcome of collisions with high accuracy and are generalizable to any quantifiable post-impact quantity. In particular, we focus on the dataset requirements, training pipeline, and classification and regression performance for four distinct data-driven techniques from machine learning (ensemble methods and neural networks) and uncertainty quantification (Gaussian processes and polynomial chaos expansion). We compare these methods to existing analytic and semi-analytic methods. Such data-driven emulators are poised to replace the methods currently used in N-body simulations, while avoiding the cost of direct simulation. This work is based on a new set of 14,856 SPH simulations of pairwise collisions between rotating, differentiated bodies at all possible mutual orientations.

Contour clustering: A field-data-driven approach for documenting and analysing prototypical f0 contours

2021 ◽  
pp. 1-30
Author(s):  
Constantijn Kaland
Keyword(s):  
Cluster Analysis ◽  
User Interfaces ◽  
Data Driven ◽  
Language Documentation ◽  
Cluster Number ◽  
Automatic Data ◽  
Speaker Variability ◽  
The Core ◽  
Data Driven Approach ◽  
Confirmatory Analysis

ABSTRACT This paper reports an automatic data-driven analysis for describing prototypical intonation patterns, particularly suitable for initial stages of prosodic research and language description. The approach has several advantages over traditional ways to investigate intonation, such as the applicability to spontaneous speech, language- and domain-independency, and the potential of revealing meaningful functions of intonation. These features make the approach particularly useful for language documentation, where the description of prosody is often lacking. The core of this approach is a cluster analysis on a time-series of f0 measurements and consists of two scripts (Praat and R, available from https://constantijnkaland.github.io/contourclustering/). Graphical user interfaces can be used to perform the analyses on collected data ranging from spontaneous to highly controlled speech. There is limited need for manual annotation prior to analysis and speaker variability can be accounted for. After cluster analysis, Praat textgrids can be generated with the cluster number annotated for each individual contour. Although further confirmatory analysis is still required, the outcomes provide useful and unbiased directions for any investigation of prototypical f0 contours based on their acoustic form.

STUDY ON THE PROCESS OF RAPESEED HULLING BY THE IMPACT

2019 ◽  
Author(s):  
А.О. РЕНЗЯЕВ ◽  
О.П. РЕНЗЯЕВ ◽  
С.Н. КРАВЧЕНКО ◽  
Р.В. КРЮК
Keyword(s):  
Rotational Speed ◽  
Calculated Data ◽  
Quality Characteristics ◽  
Complete Separation ◽  
Edible Oil ◽  
Siberian Region ◽  
The Core ◽  
The Cost ◽  
The Impact

Исследованы прочностные и физико-механические свойства оболочки рапса с точки зрения ее разрушения и удаления. Установлено, что наиболее рациональным является двухстадийный способ обрушивания: 1-я стадия – на вальцовых мельницах, 2-я – на центробежной обрушивающей машине. Определены параметры центробежной обрушивающей машины для обеспечения минимальной необходимой линейной скорости 10,81 м/с: угол наклона отбойной пластины (90 ± 2)°, частота вращения барабана (2400 ± 150) об/мин. Установлено, что правильно подобранные условия и угол, под которым происходит удар, позволяют значительно снизить количество не до конца обрушенного семени и содержание расколотого ядра. При этом при свободном ударе об отбойную пластину под углом, отличным от 88–91°, или подаче недостаточно равномерного потока семян значительно увеличивается содержание необрушенных семян. На разрушение 1 кг семян необходимо затратить 58,45 Дж. Таким образом, по расчетным данным, для семян рапса диаметром 1,5 мм частота вращения барабана должна находиться в диапазоне от 2221 до 2565 об/мин при ударе семени под углом 90°. Диаметр семян рапса, выращиваемого в Сибирском регионе, составляет от 0,8 до 1,8 мм. Установлено, что подсушивание семян рапса в течение 30–40 с при температуре 100°С позволяет увеличить эффективность разрушения оболочки до полного ее отделения от ядра рапса. Представленные результаты позволяют повысить качество очистки семян рапса от оболочки и улучшить качественные характеристики получаемого масла, облегчить последующие технологические процессы получения пищевого масла, снизить затраты на рафинацию и дезодорацию на 2%. The strength and physico-mechanical properties of the shell of rapeseed in terms of its destruction and removal are investigated. It is established that the most rational is a two-stage method of seed hulling: the 1st stage – on roller mills, the 2nd – on a centrifugal hulling machine. The parameters of the centrifugal hulling machine to provide the minimum required linear speed of 10,81 m/s are defined: the angle of inclination of the turnback plate (90 ± 2)°, the rotational speed of drum (2400 ± 150) RPM. It is established that the correctly selected conditions and the angle at which the impact occurs, can significantly reduce the amount is not completely hulling seed and the substance of the split nucleus. At the same time, with a free impact on the turnback plate at an angle different from 88–91°, or the supply of an insufficiently uniform flow of seeds, the content is not completely hulling seed increases significantly. On hulling of 1 kg of seeds it is necessary to spend 58,45 J. Thus, according to the calculated data, for rape seeds with a diameter of 1,5 mm, the rotational speed of drum should be in the range from 2221 to 2565 RPM when the seed is struck at an angle of 90°. The diameter of rapeseed grown in the Siberian region ranges from 0,8 to 1,8 mm. It was found that drying of rapeseed for 30–40 s at a temperature of 100°C, can increase the efficiency of destruction of the shell to its complete separation from the core of rapeseed. The presented results make it possible to improve the quality of cleaning of rape seeds from the shell and improve the quality characteristics of the obtained oil, facilitate the subsequent technological processes of obtaining edible oil, reduce the cost of refining and deodorization by 2%.

An Episode in the History of PreCrime

2018 ◽  
Vol 48 (5) ◽  
pp. 637-647
Author(s):  
Rebecca Lemov
Keyword(s):  
Mathematical Models ◽  
Crime Prevention ◽  
Scientific Study ◽  
Behavioral Data ◽  
Data Driven ◽  
Special Issue ◽  
Predictive Policing ◽  
The Core ◽  
Current Spread ◽  
History Of

This article traces the rise of “predictive” attitudes to crime prevention. After a brief summary of the current spread of predictive policing based on person-centered and place-centered mathematical models, an episode in the scientific study of future crime is examined. At UCLA between 1969 and 1973, a well-funded “violence center” occasioned great hopes that the quotient of human “dangerousness”—potential violence against other humans—could be quantified and thereby controlled. At the core of the center, under the direction of interrogation expert and psychiatrist Louis Jolyon West, was a project to gather unprecedented amounts of behavioral data and centrally store it to identify emergent crime. Protesters correctly seized on the violence center as a potential site of racially targeted experimentation in psychosurgery and an example of iatrogenic science. Yet the eventual spectacular failure of the center belies an ultimate success: its data-driven vision itself predicted the Philip K. Dick–style PreCrime policing now emerging. The UCLA violence center thus offers an alternative genealogy to predictive policing. This essay is part of a special issue entitled Histories of Data and the Database edited by Soraya de Chadarevian and Theodore M. Porter.

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