Structural geologic modeling as an inference problem: A Bayesian perspective

2016 ◽  
Vol 4 (3) ◽  
pp. SM1-SM16 ◽  
Author(s):  
Miguel de la Varga ◽  
J. Florian Wellmann

Structural geologic models are widely used to represent the spatial distribution of relevant geologic features. Several techniques exist to construct these models on the basis of different assumptions and different types of geologic observations. However, two problems are prevalent when constructing models: (1) observations and assumptions, and therefore also the constructed model, are subject to uncertainties and (2) additional information is often available, but it cannot be considered directly in the geologic modeling step — although it could be used to reduce model uncertainties. The first problem has been addressed in recent work. Here we develop a conceptual approach to consider the second aspect: We combine uncertain prior information with geologically motivated likelihood functions in a Bayesian inference framework. The result is that we not only reduce uncertainties in the ensemble of generated models, but we also gain the potential to learn additional features about the model parameters. We develop an implementation of this concept in a probabilistic programming framework, in which we extend the functionality of a 3D implicit potential-field interpolation method with geologic likelihood functions. With schematic examples, we show how this combination leads to suites of models with reduced uncertainties and how it provides a deeper insight into parameter correlations. Furthermore, the integration into a hierarchical Bayesian model provides an insight into potential extensions of the method, for example, the interpolation functional itself, and other types of information, such as gravity or magnetic potential-field data. These aspects constitute promising paths for future research.

Geophysics ◽  
1995 ◽  
Vol 60 (2) ◽  
pp. 399-407 ◽  
Author(s):  
Carlos A. Mendonça ◽  
João B. C. Silva

Interpolation using only the observations at discrete points is an ill‐posed problem because it admits infinite solutions. Usually, to reduce ambiguity, a priori information about the sample function is introduced. Current interpolation methods in mineral exploration introduce only the constraints of continuity and smoothness of the interpolating function. In interpolating potential‐field anomalies, the constraint that the sampled function is harmonic may be introduced by the equivalent‐layer method (ELM). We compare the performance of the ELM and the minimum curvature method (MCM) in interpolating potential‐field anomalies by applying these methods to synthetic magnetic data simulating an aeromagnetic survey. In the case the anomaly flanks and peak are undersampled, the ELM performs better than the MCM in recovering the anomaly gradients and peak. In the case of elongated linear anomalies, the ELM recovers the exact linear pattern, but the MCM introduces spurious oscillations in the linear pattern. Also, the ELM is able to reduce the data from a survey flown at different heights to a common level. In contrast, the MCM, being a 2-D interpolation method, cannot account for variations in the vertical coordinates of the observation points.


2019 ◽  
Author(s):  
Joseph John Pyne Simons ◽  
Ilya Farber

Not all transit users have the same preferences when making route decisions. Understanding the factors driving this heterogeneity enables better tailoring of policies, interventions, and messaging. However, existing methods for assessing these factors require extensive data collection. Here we present an alternative approach - an easily-administered single item measure of overall preference for speed versus comfort. Scores on the self-report item predict decisions in a choice task and account for a proportion of the differences in model parameters between people (n=298). This single item can easily be included on existing travel surveys, and provides an efficient method to both anticipate the choices of users and gain more general insight into their preferences.


2019 ◽  
Vol 25 (3) ◽  
pp. 378-396 ◽  
Author(s):  
Arian Razmi-Farooji ◽  
Hanna Kropsu-Vehkaperä ◽  
Janne Härkönen ◽  
Harri Haapasalo

Purpose The purpose of this paper is twofold: first, to understand data management challenges in e-maintenance systems from a holistically viewpoint through summarizing the earlier scattered research in the field, and second, to present a conceptual approach for addressing these challenges in practice. Design/methodology/approach The study is realized as a combination of a literature review and by the means of analyzing the practices on an industry leader in manufacturing and maintenance services. Findings This research provides a general understanding over data management challenges in e-maintenance and summarizes their associated proposed solutions. In addition, this paper lists and exemplifies different types and sources of data which can be collected in e-maintenance, across different organizational levels. Analyzing the data management practices of an e-maintenance industry leader provides a conceptual approach to address identified challenges in practice. Research limitations/implications Since this paper is based on studying the practices of a single company, it might be limited to generalize the results. Future research topics can focus on each of mentioned data management challenges and also validate the applicability of presented model in other companies and industries. Practical implications Understanding the e-maintenance-related challenges helps maintenance managers and other involved stakeholders in e-maintenance systems to better solve the challenges. Originality/value The so-far literature on e-maintenance has been studied with narrow focus to data and data management in e-maintenance appears as one of the less studied topics in the literature. This research paper contributes to e-maintenance by highlighting the deficiencies of the discussion surrounding the perspectives of data management in e-maintenance by studying all common data management challenges and listing different types of data which need to be acquired in e-maintenance systems.


2021 ◽  
Vol 54 (7) ◽  
pp. 1-39
Author(s):  
Ankur Lohachab ◽  
Saurabh Garg ◽  
Byeong Kang ◽  
Muhammad Bilal Amin ◽  
Junmin Lee ◽  
...  

Unprecedented attention towards blockchain technology is serving as a game-changer in fostering the development of blockchain-enabled distinctive frameworks. However, fragmentation unleashed by its underlying concepts hinders different stakeholders from effectively utilizing blockchain-supported services, resulting in the obstruction of its wide-scale adoption. To explore synergies among the isolated frameworks requires comprehensively studying inter-blockchain communication approaches. These approaches broadly come under the umbrella of Blockchain Interoperability (BI) notion, as it can facilitate a novel paradigm of an integrated blockchain ecosystem that connects state-of-the-art disparate blockchains. Currently, there is a lack of studies that comprehensively review BI, which works as a stumbling block in its development. Therefore, this article aims to articulate potential of BI by reviewing it from diverse perspectives. Beginning with a glance of blockchain architecture fundamentals, this article discusses its associated platforms, taxonomy, and consensus mechanisms. Subsequently, it argues about BI’s requirement by exemplifying its potential opportunities and application areas. Concerning BI, an architecture seems to be a missing link. Hence, this article introduces a layered architecture for the effective development of protocols and methods for interoperable blockchains. Furthermore, this article proposes an in-depth BI research taxonomy and provides an insight into the state-of-the-art projects. Finally, it determines possible open challenges and future research in the domain.


2021 ◽  
Vol 54 (3) ◽  
pp. 1-28
Author(s):  
Jun Huang ◽  
Debiao He ◽  
Mohammad S. Obaidat ◽  
Pandi Vijayakumar ◽  
Min Luo ◽  
...  

Voting is a formal expression of opinion or choice, either positive or negative, made by an individual or a group of individuals. However, conventional voting systems tend to be centralized, which are known to suffer from security and efficiency limitations. Hence, there has been a trend of moving to decentralized voting systems, such as those based on blockchain. The latter is a decentralized digital ledger in a peer-to-peer network, where a copy of the append-only ledger of digitally signed and encrypted transactions is maintained by each participant. Therefore, in this article, we perform a comprehensive review of blockchain-based voting systems and classify them based on a number of features (e.g., the types of blockchain used, the consensus approaches used, and the scale of participants). By systematically analyzing and comparing the different blockchain-based voting systems, we also identify a number of limitations and research opportunities. Hopefully, this survey will provide an in-depth insight into the potential utility of blockchain in voting systems and device future research agenda.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Luan Thanh Pham ◽  
Ozkan Kafadar ◽  
Erdinc Oksum ◽  
Ahmed M. Eldosouky

1991 ◽  
Vol 15 (2) ◽  
pp. 123-138
Author(s):  
Joachim Biskup ◽  
Bernhard Convent

In this paper the relationship between dependency theory and first-order logic is explored in order to show how relational chase procedures (i.e., algorithms to decide inference problems for dependencies) can be interpreted as clever implementations of well known refutation procedures of first-order logic with resolution and paramodulation. On the one hand this alternative interpretation provides a deeper insight into the theoretical foundations of chase procedures, whereas on the other hand it makes available an already well established theory with a great amount of known results and techniques to be used for further investigations of the inference problem for dependencies. Our presentation is a detailed and careful elaboration of an idea formerly outlined by Grant and Jacobs which up to now seems to be disregarded by the database community although it definitely deserves more attention.


2021 ◽  
pp. 108926802199516
Author(s):  
Rikki H. Sargent ◽  
Leonard S. Newman

Pluralistic ignorance occurs when group members mistakenly believe others’ cognitions and/or behaviors are systematically different from their own. More than 20 years have passed since the last review of pluralistic ignorance from a psychological framework, with more than 60 empirical articles assessing pluralistic ignorance published since then. Previous reviews took an almost entirely conceptual approach with minimal review of methodology, making existing reviews outdated and limited in the extent to which they can provide guidelines for researchers. The goal of this review is to evaluate and integrate the literature on pluralistic ignorance, clarify important conceptual issues, identify inconsistencies in the literature, and provide guidance for future research. We provide a comprehensive definition for the phenomenon, with a focus on its status as a group-level phenomenon. We highlight three areas of variation in particular in the current scoping review: variation in topics assessed, variation in measurement, and (especially) variation in methods for assessing the implications of individual-level misperceptions that, in aggregate, lead to pluralistic ignorance. By filling these gaps in the literature, we ultimately hope to motivate further analysis of the phenomenon.


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