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2019

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Articles 1 - 30 of 178

Full-Text Articles in Engineering

Maximizing Multifaceted Network Influence, Yuchen Li, Ju Fan, George V. Ovchinnikov, Panagiotis Karras Nov 2019

Maximizing Multifaceted Network Influence, Yuchen Li, Ju Fan, George V. Ovchinnikov, Panagiotis Karras

Research Collection School Of Information Systems

An information dissemination campaign is often multifaceted, involving several facets or pieces of information disseminating from different sources. The question then arises, how should we assign such pieces to eligible sources so as to achieve the best viral dissemination results? Past research has studied the problem of Influence Maximization (IM), which is to select a set of k promoters that maximizes the expected reach of a message over a network. However, in this classical IM problem, each promoter spreads out the same unitary piece of information. In this paper, we propose the Optimal Influential Pieces Assignment (OIPA) problem, which is ...


Adaptive Randomized Rounding In The Big Parsimony Problem, Sangho Shim, Sunil Chopra, Eunseok Kim Oct 2019

Adaptive Randomized Rounding In The Big Parsimony Problem, Sangho Shim, Sunil Chopra, Eunseok Kim

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.


Metnet: Systems Biology Tools For Arabidopsis, Eve Syrkin Wurtele, Ling Li, Dan Berleant, Dianne Cook, Julie A. Dickerson, Jing Ding, Heike Hofmann, Michael Lawrence, Eun-Kyung Lee, Jie Li, Wieslawa Mentzen, Leslie Miller, Basil J. Nikolau, Nick Ransom, Yingjun Wang Sep 2019

Metnet: Systems Biology Tools For Arabidopsis, Eve Syrkin Wurtele, Ling Li, Dan Berleant, Dianne Cook, Julie A. Dickerson, Jing Ding, Heike Hofmann, Michael Lawrence, Eun-Kyung Lee, Jie Li, Wieslawa Mentzen, Leslie Miller, Basil J. Nikolau, Nick Ransom, Yingjun Wang

Eve Wurtele

MetNet (http://metnetdb.org) is an emerging open-source software platform for exploration of disparate experimental data types and regulatory and metabolic networks in the context of Arabidopsis systems biology. The MetNet platform features graph visualization, interactive displays, graph theoretic computations for determining biological distances, a unique multivariate display and statistical analysis tool, graph modeling using the open source statistical analysis language, R, and versatile text mining. The use of these tools is illustrated with data from the bio1 mutant of Arabidopsis.


Pipelined Parallelism In A Work-Stealing Scheduler, Thomas Kelly Sep 2019

Pipelined Parallelism In A Work-Stealing Scheduler, Thomas Kelly

All Computer Science and Engineering Research

A pipeline is a particular type of parallel program structure, often used to represent loops with cross-iteration dependencies. Pipelines cannot be expressed with the typical parallel language constructs offered by most environments. Therefore, in order to run pipelines, it is necessary to write a parallel language and scheduler with specialized support for them. Some such schedulers are written exclusively for pipelines and unable to run any other type of program, which allows for certain optimizations that take advantage of the pipeline structure. Other schedulers implement support for pipelines on top of a general-purpose scheduling algorithm. One example of such an ...


Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham Sep 2019

Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham

Research Collection School Of Information Systems

Prior research reported that workers on Amazon Mechanical Turk (AMT) are underpaid, earning about $2/h. But the prior research did not investigate the difference in wage due to worker characteristics (e.g., country of residence). We present the first data-driven analysis on wage gap on AMT. Using work log data and demographic data collected via online survey, we analyse the gap in wage due to different factors. We show that there is indeed wage gap; for example, workers in the U.S. earn $3.01/h while those in India earn $1.41/h on average.


Metnet: Systems Biology Tools For Arabidopsis, Eve Syrkin Wurtele, Ling Li, Dan Berleant, Dianne Cook, Julie A. Dickerson, Jing Ding, Heike Hofmann, Michael Lawrence, Eun-Kyung Lee, Jie Li, Wieslawa Mentzen, Leslie Miller, Basil J. Nikolau, Nick Ransom, Yingjun Wang Aug 2019

Metnet: Systems Biology Tools For Arabidopsis, Eve Syrkin Wurtele, Ling Li, Dan Berleant, Dianne Cook, Julie A. Dickerson, Jing Ding, Heike Hofmann, Michael Lawrence, Eun-Kyung Lee, Jie Li, Wieslawa Mentzen, Leslie Miller, Basil J. Nikolau, Nick Ransom, Yingjun Wang

Ling Li

MetNet (http://metnetdb.org) is an emerging open-source software platform for exploration of disparate experimental data types and regulatory and metabolic networks in the context of Arabidopsis systems biology. The MetNet platform features graph visualization, interactive displays, graph theoretic computations for determining biological distances, a unique multivariate display and statistical analysis tool, graph modeling using the open source statistical analysis language, R, and versatile text mining. The use of these tools is illustrated with data from the bio1 mutant of Arabidopsis.


Creating, Modeling, And Visualizing Metabolic Networks, Julie A. Dickerson, Daniel Berleant, Pan Du, Jing Ding, Carol M. Foster, Ling Li, Eve Syrkin Wurtele Aug 2019

Creating, Modeling, And Visualizing Metabolic Networks, Julie A. Dickerson, Daniel Berleant, Pan Du, Jing Ding, Carol M. Foster, Ling Li, Eve Syrkin Wurtele

Ling Li

Metabolic networks combine metabolism and regulation. These complex networks are difficult to understand and create due to the diverse types of information that need to be represented. This chapter describes a suite of interlinked tools for developing, displaying, and modeling metabolic networks. The metabolic network interactions database, MetNetDB, contains information on regulatory and metabolic interactions derived from a combination of web databases and input from biologists in their area of expertise. PathBinderA mines the biological “literaturome” by searching for new interactions or supporting evidence for existing interactions in metabolic networks. Sentences from abstracts are ranked in terms of the likelihood ...


Machine Learning In Support Of Electric Distribution Asset Failure Prediction, Robert D. Flamenbaum, Thomas Pompo, Christopher Havenstein, Jade Thiemsuwan Aug 2019

Machine Learning In Support Of Electric Distribution Asset Failure Prediction, Robert D. Flamenbaum, Thomas Pompo, Christopher Havenstein, Jade Thiemsuwan

SMU Data Science Review

In this paper, we present novel approaches to predicting as- set failure in the electric distribution system. Failures in overhead power lines and their associated equipment in particular, pose significant finan- cial and environmental threats to electric utilities. Electric device failure furthermore poses a burden on customers and can pose serious risk to life and livelihood. Working with asset data acquired from an electric utility in Southern California, and incorporating environmental and geospatial data from around the region, we applied a Random Forest methodology to predict which overhead distribution lines are most vulnerable to fail- ure. Our results provide evidence ...


Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr. Aug 2019

Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr.

William Q Meeker

Warranty return data from repairable systems, such as vehicles, usually result in recurrent event data. The non-homogeneous Poisson process (NHPP) model is used widely to describe such data. Seasonality in the repair frequencies and other variabilities, however, complicate the modeling of recurrent event data. Not much work has been done to address the seasonality, and this paper provides a general approach for the application of NHPP models with dynamic covariates to predict seasonal warranty returns. A hierarchical clustering method is used to stratify the population into groups that are more homogeneous than the than the overall population. The stratification facilitates ...


Provisioning On-Line Games: A Traffic Analysis Of A Busy Counter-Strike Server, Francis Chang, Wu-Chang Feng, Wu-Chi Feng, Jonathan Walpole Aug 2019

Provisioning On-Line Games: A Traffic Analysis Of A Busy Counter-Strike Server, Francis Chang, Wu-Chang Feng, Wu-Chi Feng, Jonathan Walpole

Jonathan Walpole

A poster that illustrates the client/server model employed by an multiplayer online game, focusing on bandwidth usage.


Distributed Edge Bundling For Large Graphs, Yves Tuyishime Aug 2019

Distributed Edge Bundling For Large Graphs, Yves Tuyishime

Computer Science and Engineering: Theses, Dissertations, and Student Research

Graphs or networks are widely used to depict the relationships between data entities in diverse scientific and engineering applications. A direct visualization (such as node-link diagram) of a graph with a large number of nodes and edges often incurs visual clutter. To address this issue, researchers have developed edge bundling algorithms that visually merge similar edges into curved bundles and can effectively reveal high-level edge patterns with reduced visual clutter. Although the existing edge bundling algorithms achieve appealing results, they are mostly designed for a single machine, and thereby the size of a graph they can handle is limited by ...


Exploring Eye Tracking Data On Source Code Via Dual Space Analysis, Li Zhang Aug 2019

Exploring Eye Tracking Data On Source Code Via Dual Space Analysis, Li Zhang

Computer Science and Engineering: Theses, Dissertations, and Student Research

Eye tracking is a frequently used technique to collect data capturing users' strategies and behaviors in processing information. Understanding how programmers navigate through a large number of classes and methods to find bugs is important to educators and practitioners in software engineering. However, the eye tracking data collected on realistic codebases is massive compared to traditional eye tracking data on one static page. The same content may appear in different areas on the screen with users scrolling in an Integrated Development Environment (IDE). Hierarchically structured content and fluid method position compose the two major challenges for visualization. We present a ...


Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang Aug 2019

Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang

Research Collection School Of Information Systems

Items adopted by a user over time are indicative ofthe underlying preferences. We are concerned withlearning such preferences from observed sequencesof adoptions for recommendation. As multipleitems are commonly adopted concurrently, e.g., abasket of grocery items or a sitting of media consumption, we deal with a sequence of baskets asinput, and seek to recommend the next basket. Intuitively, a basket tends to contain groups of relateditems that support particular needs. Instead of recommending items independently for the next basket, we hypothesize that incorporating informationon pairwise correlations among items would help toarrive at more coherent basket recommendations.Towards this objective, we ...


Using Reservoir Computing To Build A Robust Interface With Dna Circuits In Determining Genetic Similarities Between Pathogens, Christopher Neighbor, Christof Teuscher Jul 2019

Using Reservoir Computing To Build A Robust Interface With Dna Circuits In Determining Genetic Similarities Between Pathogens, Christopher Neighbor, Christof Teuscher

Christof Teuscher

As computational power increases, the field of neural networks has advanced exponentially. In particular recurrent neural networks (RNNs) are being utilized to simulate dynamic systems and to learn to predict time series data. Reservoir computing is an architecture which has the potential to increase training speed while reducing computational costs. Reservoir computing consists of a RNN with a fixed connections “reservoir” while only the output layer is trained. The purpose of this research is to explore the effective use of reservoir computing networks with the eventual application towards use in a DNA based molecular computing reservoir for use in pathogen ...


Exploring And Expanding The One-Pixel Attack, Umairullah Khan, Walt Woods, Christof Teuscher Jul 2019

Exploring And Expanding The One-Pixel Attack, Umairullah Khan, Walt Woods, Christof Teuscher

Christof Teuscher

In machine learning research, adversarial examples are normal inputs to a classifier that have been specifically perturbed to cause the model to misclassify the input. These perturbations rarely affect the human readability of an input, even though the model’s output is drastically different. Recent work has demonstrated that image-classifying deep neural networks (DNNs) can be reliably fooled with the modification of a single pixel in the input image, without knowledge of a DNN’s internal parameters. This “one-pixel attack” utilizes an iterative evolutionary optimizer known as differential evolution (DE) to find the most effective pixel to perturb, via the ...


Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore Jul 2019

Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore

Computer Science and Engineering: Theses, Dissertations, and Student Research

Robot software risks the hazard of dimensional inconsistencies. These inconsistencies occur when a program incorrectly manipulates values representing real-world quantities. Incorrect manipulation has real-world consequences that range in severity from benign to catastrophic. Previous approaches detect dimensional inconsistencies in programs but require extra developer effort and technical complications. The extra effort involves developers creating type annotations for every variable representing a real-world quantity that has physical units, and the technical complications include toolchain burdens like specialized compilers or type libraries.

To overcome the limitations of previous approaches, this thesis presents novel methods to detect dimensional inconsistencies without developer annotations. We ...


The Design And Implementation Of Aida: Ancient Inscription Database And Analytics System, M Parvez Rashid Jul 2019

The Design And Implementation Of Aida: Ancient Inscription Database And Analytics System, M Parvez Rashid

Computer Science and Engineering: Theses, Dissertations, and Student Research

AIDA, the Ancient Inscription Database and Analytic system can be used to translate and analyze ancient Minoan language. The AIDA system currently stores three types of ancient Minoan inscriptions: Linear A, Cretan Hieroglyph and Phaistos Disk inscriptions. In addition, AIDA provides candidate syllabic values and translations of Minoan words and inscriptions into English. The AIDA system allows the users to change these candidate phonetic assignments to the Linear A, Cretan Hieroglyph and Phaistos symbols. Hence the AIDA system provides for various scholars not only a convenient online resource to browse Minoan inscriptions but also provides an analysis tool to explore ...


Design Of Personnel Big Data Management System Based On Blockchain, Houbing Song, Jian Chen, Zhihan Lv Jul 2019

Design Of Personnel Big Data Management System Based On Blockchain, Houbing Song, Jian Chen, Zhihan Lv

Publications

With the continuous development of information technology, enterprises, universities and governments are constantly stepping up the construction of electronic personnel information management system. The information of hundreds of thousands or even millions of people’s information are collected and stored into the system. So much information provides the cornerstone for the development of big data, if such data is tampered with or leaked, it will cause irreparable serious damage. However, in recent years, electronic archives have exposed a series of problems such as information leakage, information tampering, and information loss, which has made the reform of personnel information management more ...


Adaboost‑Based Security Level Classifcation Of Mobile Intelligent Terminals, Feng Wang, Houbing Song, Dingde Jiang, Hong Wen Jul 2019

Adaboost‑Based Security Level Classifcation Of Mobile Intelligent Terminals, Feng Wang, Houbing Song, Dingde Jiang, Hong Wen

Publications

With the rapid development of Internet of Things, massive mobile intelligent terminals are ready to access edge servers for real-time data calculation and interaction. However, the risk of private data leakage follows simultaneously. As the administrator of all intelligent terminals in a region, the edge server needs to clarify the ability of the managed intelligent terminals to defend against malicious attacks. Therefore, the security level classification for mobile intelligent terminals before accessing the network is indispensable. In this paper, we firstly propose a safety assessment method to detect the weakness of mobile intelligent terminals. Secondly, we match the evaluation results ...


Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg Jul 2019

Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

This paper points students towards ideas they can use towards developing a convenient library for robot navigation, with examples based on Botball primitives, and points educators towards mathematics and programming exercises they can suggest to students, especially advanced high school students.


Identification Of The Impacts Of Code Changes On The Security Of Software, Moataz Abdelkhalek, Ameerah-Muhsina Jamil, Lotfi Ben Othmane Jul 2019

Identification Of The Impacts Of Code Changes On The Security Of Software, Moataz Abdelkhalek, Ameerah-Muhsina Jamil, Lotfi Ben Othmane

Electrical and Computer Engineering Conference Papers, Posters and Presentations

Companies develop their software in versions and iterations. Ensuring the security of each additional version using code review is costly and time consuming. This paper investigates automated tracing of the impacts of code changes on the security of a given software. To this end, we use call graphs to model the software code, and security assurance cases to model the security requirements of the software. Then we relate assurance case elements to code through the entry point methods of the software, creating a map of monitored security functions. This mapping allows to evaluate the security requirements that are affected by ...


Features Of Designing The Architecture Of Intelligent Transport Systems, Jaffar Daeibal, Vyacheslav Lapshin, Dmitry Elkin, Sergey A. Kucherov Jul 2019

Features Of Designing The Architecture Of Intelligent Transport Systems, Jaffar Daeibal, Vyacheslav Lapshin, Dmitry Elkin, Sergey A. Kucherov

Karbala International Journal of Modern Science

In the global experience, intelligent transport systems (ITS) are recognized as a general transport ideology for integrating the achievements of telematics in all types of transport activities to solve economic and social problems: reducing accidents, improving the efficiency of public transport and cargo transportation, ensuring overall transport security, and improving environmental performance. Considering the design features of the intelligent transport system (ITS), there is a need to develop requirements for the functional and physical architecture as the main part of the ITS development. The creation of functional and physical architecture touches upon issues such as: the scheme of interaction between ...


Developing 5gl Concepts From User Interactions, David Stuckless Meyer Jul 2019

Developing 5gl Concepts From User Interactions, David Stuckless Meyer

Masters Theses

In the fulfilling of the contracts generated in Test Driven Development, a developer could be said to act as a constraint solver, similar to those used by a 5th Generation Language(5GL). This thesis presents the hypothesis that 5GL linguistic mechanics, such as facts, rules and goals, will be emergent in the communications of developer pairs performing Test Driven Development, validating that 5GL syntax is congruent with the ways that practitioners communicate. Along the way, nomenclatures and linguistic patterns may be observed that could inform the design of future 5GL languages.


Seven Hci Grand Challenges, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Jessie Y. C. Chen, Jianming Dong, Vincent G. Duffy, Xiaowen Fang, Cali Fidopiastis, Gino Fragomeni, Limin Paul Fu, Yinni Guo, Don Harris, Andri Ioannou, Kyeong-Ah (Kate) Jeong, Shin'ichi Konomi, Heidi Kromker, Masaaki Kurosu, James R. Lewis, Aaron Marcus, Gabriele Meiselwitz, Abbas Moallem, Hirohiko Mori, Fiona Fui-Hoon Nah, Stavroula Ntoa, Pei-Luen Patrick Rau, Dylan Schmorrow, Keng Siau, Norbert Streitz, Wentao Wang, Sakae Yamamoto, Panayiotis Zaphiris, Jia Zhou Jun 2019

Seven Hci Grand Challenges, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Jessie Y. C. Chen, Jianming Dong, Vincent G. Duffy, Xiaowen Fang, Cali Fidopiastis, Gino Fragomeni, Limin Paul Fu, Yinni Guo, Don Harris, Andri Ioannou, Kyeong-Ah (Kate) Jeong, Shin'ichi Konomi, Heidi Kromker, Masaaki Kurosu, James R. Lewis, Aaron Marcus, Gabriele Meiselwitz, Abbas Moallem, Hirohiko Mori, Fiona Fui-Hoon Nah, Stavroula Ntoa, Pei-Luen Patrick Rau, Dylan Schmorrow, Keng Siau, Norbert Streitz, Wentao Wang, Sakae Yamamoto, Panayiotis Zaphiris, Jia Zhou

Abbas Moallem

This article aims to investigate the Grand Challenges which arise in the current and emerging landscape of rapid technological evolution towards more intelligent interactive technologies, coupled with increased and widened societal needs, as well as individual and collective expectations that HCI, as a discipline, is called upon to address. A perspective oriented to humane and social values is adopted, formulating the challenges in terms of the impact of emerging intelligent interactive technologies on human life both at the individual and societal levels. Seven Grand Challenges are identified and presented in this article: Human-Technology Symbiosis; Human-Environment Interactions; Ethics, Privacy and Security ...


A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne Jun 2019

A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne

REU Final Reports

As wildfires surge in frequency and impact in the Pacific Northwest, in tandem with increasingly traffic-choked roads, personal exposure to harmful airborne pollutants is a rising concern. Particularly at risk are school-age children, especially those living in disadvantaged communities near major motorways and industrial centers. Many of these children must walk to school, and the choice of route can effect exposure. Route-planning applications and frameworks utilizing computational shortest paths methods have been proposed which consider personal exposure with reasonable success, but few have focused on pollution exposure, and all have been limited in scalability or geographic scope. This paper addresses ...


Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde Jun 2019

Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde

Baskar Ganapathysubramanian

Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, training samples obey invariances that are \textit{a priori} known; for example, in complex physics simulations, the training data obey universal laws encoded as well-defined mathematical equations. In this paper, we propose a new generative modeling approach, InvNet, that can efficiently model data spaces with known invariances. We devise an adversarial training algorithm to encode them into data distribution. We validate our framework in three experimental settings: generating images with fixed motifs; solving nonlinear partial differential equations (PDEs); and ...


Scheduling And Prefetching In Hadoop With Block Access Pattern Awareness And Global Memory Sharing With Load Balancing Scheme, Sai Suman Jun 2019

Scheduling And Prefetching In Hadoop With Block Access Pattern Awareness And Global Memory Sharing With Load Balancing Scheme, Sai Suman

Computer Science and Engineering: Theses, Dissertations, and Student Research

Although several scheduling and prefetching algorithms have been proposed to improve data locality in Hadoop, there has not been much research to increase cluster performance by targeting the issue of data locality while considering the 1) cluster memory, 2) data access patterns and 3) real-time scheduling issues together.

Firstly, considering the data access patterns is crucial because the computation might access some portion of the data in the cluster only once while the rest could be accessed multiple times. Blindly retaining data in memory might eventually lead to inefficient memory utilization.

Secondly, several studies found that the cluster memory goes ...


Parallel Streaming Random Sampling, Kanat Tangwongsan, Srikanta Tirthapura Jun 2019

Parallel Streaming Random Sampling, Kanat Tangwongsan, Srikanta Tirthapura

Electrical and Computer Engineering Publications

This paper investigates parallel random sampling from a potentially-unending data stream whose elements are revealed in a series of element sequences (minibatches). While sampling from a stream was extensively studied sequentially, not much has been explored in the parallel context, with prior parallel random-sampling algorithms focusing on the static batch model. We present parallel algorithms for minibatch-stream sampling in two settings: (1) sliding window, which draws samples from a prespecified number of most-recently observed elements, and (2) infinite window, which draws samples from all the elements received. Our algorithms are computationally and memory efficient: their work matches the fastest sequential ...


Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde Jun 2019

Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde

Mechanical Engineering Publications

Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, training samples obey invariances that are \textit{a priori} known; for example, in complex physics simulations, the training data obey universal laws encoded as well-defined mathematical equations. In this paper, we propose a new generative modeling approach, InvNet, that can efficiently model data spaces with known invariances. We devise an adversarial training algorithm to encode them into data distribution. We validate our framework in three experimental settings: generating images with fixed motifs; solving nonlinear partial differential equations (PDEs); and ...


Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga Jun 2019

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different ...