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Articles 1 - 30 of 50
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Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann M. Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito
Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann M. Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito
Ole J Mengshoel
Darwin: A Ground Truth Agnostic Captcha Generator Using Evolutionary Algorithm, Eric Y. Chen, Lin-Shung Huang, Ole J. Mengshoel, Jason D. Lohn
Darwin: A Ground Truth Agnostic Captcha Generator Using Evolutionary Algorithm, Eric Y. Chen, Lin-Shung Huang, Ole J. Mengshoel, Jason D. Lohn
Ole J Mengshoel
Feedback Control For Multi-Modal Optimization Using Genetic Algorithms, Jun Shi, Ole J. Mengshoel, Dipan K. Pal
Feedback Control For Multi-Modal Optimization Using Genetic Algorithms, Jun Shi, Ole J. Mengshoel, Dipan K. Pal
Ole J Mengshoel
Adaptive Generalized Crowding For Genetic Algorithms, Ole J. Mengshoel, Severinio Galan, Antonio De Dios
Adaptive Generalized Crowding For Genetic Algorithms, Ole J. Mengshoel, Severinio Galan, Antonio De Dios
Ole J Mengshoel
Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito
Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito
Ole J Mengshoel
Will We Connect Again? Machine Learning For Link Prediction In Mobile Social Networks, Ole J. Mengshoel, Raj Desai, Andrew Chen, Brian Tran
Will We Connect Again? Machine Learning For Link Prediction In Mobile Social Networks, Ole J. Mengshoel, Raj Desai, Andrew Chen, Brian Tran
Ole J Mengshoel
Optimizing Parallel Belief Propagation In Junction Trees Using Regression, Lu Zheng, Ole J. Mengshoel
Optimizing Parallel Belief Propagation In Junction Trees Using Regression, Lu Zheng, Ole J. Mengshoel
Ole J Mengshoel
Exploring Multiple Dimensions Of Parallelism In Junction Tree Message Passing, Lu Zheng, Ole J. Mengshoel
Exploring Multiple Dimensions Of Parallelism In Junction Tree Message Passing, Lu Zheng, Ole J. Mengshoel
Ole J Mengshoel
Latent Topic Analysis For Predicting Group Purchasing Behavior On The Social Web, Feng-Tso Sun, Martin Griss, Ole J. Mengshoel, Yi-Ting Yeh
Latent Topic Analysis For Predicting Group Purchasing Behavior On The Social Web, Feng-Tso Sun, Martin Griss, Ole J. Mengshoel, Yi-Ting Yeh
Ole J Mengshoel
Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara
Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara
Ole J Mengshoel
Software Health Management With Bayesian Networks, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, Adnan Darwiche
Software Health Management With Bayesian Networks, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, Adnan Darwiche
Ole J Mengshoel
Multi-Focus And Multi-Window Techniques For Interactive Network Exploration, Priya K. Sundararajan, Ole J. Mengshoel, Ted Selker
Multi-Focus And Multi-Window Techniques For Interactive Network Exploration, Priya K. Sundararajan, Ole J. Mengshoel, Ted Selker
Ole J Mengshoel
Multi-Focus And Multi-Level Techniques For Visualization And Analysis Of Networks With Thematic Data, Michele Cossalter, Ole J. Mengshoel, Ted Selker
Multi-Focus And Multi-Level Techniques For Visualization And Analysis Of Networks With Thematic Data, Michele Cossalter, Ole J. Mengshoel, Ted Selker
Ole J Mengshoel
A Novel Mating Approach For Genetic Algorithms, Severino Galan, Ole J. Mengshoel, Rafael Pinter
A Novel Mating Approach For Genetic Algorithms, Severino Galan, Ole J. Mengshoel, Rafael Pinter
Ole J Mengshoel
Scaling Bayesian Network Parameter Learning With Expectation Maximization Using Mapreduce, Erik B. Reed, Ole J. Mengshoel
Scaling Bayesian Network Parameter Learning With Expectation Maximization Using Mapreduce, Erik B. Reed, Ole J. Mengshoel
Ole J Mengshoel
Mapreduce For Bayesian Network Parameter Learning Using The Em Algorithm, Aniruddha Basak, Irina Brinster, Ole J. Mengshoel
Mapreduce For Bayesian Network Parameter Learning Using The Em Algorithm, Aniruddha Basak, Irina Brinster, Ole J. Mengshoel
Ole J Mengshoel
Software And System Health Management For Autonomous Robotics Missions, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel
Software And System Health Management For Autonomous Robotics Missions, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel
Ole J Mengshoel
Advanced autonomous robotics space missions rely heavily on the flawless interaction of complex hardware, multiple sensors, and a mission-critical software system. This software system consists of an operating system, device drivers, controllers, and executives; recently highly complex AI-based autonomy software have also been introduced. Prior to launch, this software has to undergo rigorous verification and validation (V&V). Nevertheless, dormant software bugs, failing sensors, unexpected hardware-software interactions, and unanticipated environmental conditions—likely on a space exploration mission—can cause major software faults that can endanger the entire mission.
Our Integrated Software Health Management (ISWHM) system continuously monitors the hardware sensors and the software …
Reactive Bayesian Network Computation Using Feedback Control: An Empirical Study, Ole J. Mengshoel, Abe Ishihara, Erik Reed
Reactive Bayesian Network Computation Using Feedback Control: An Empirical Study, Ole J. Mengshoel, Abe Ishihara, Erik Reed
Ole J Mengshoel
The Impact Of Social Affinity On Phone Calling Patterns: Categorizing Social Ties From Call Data Records, Sara Motahari, Ole J. Mengshoel, Phyllis Reuther, Sandeep Appala, Luca Zoia, Jay Shah
The Impact Of Social Affinity On Phone Calling Patterns: Categorizing Social Ties From Call Data Records, Sara Motahari, Ole J. Mengshoel, Phyllis Reuther, Sandeep Appala, Luca Zoia, Jay Shah
Ole J Mengshoel
Accelerating Bayesian Network Parameter Learning Using Hadoop And Mapreduce, Aniruddha Basak, Irina Brinster, Xianheng Ma, Ole J. Mengshoel
Accelerating Bayesian Network Parameter Learning Using Hadoop And Mapreduce, Aniruddha Basak, Irina Brinster, Xianheng Ma, Ole J. Mengshoel
Ole J Mengshoel
Adaptive Control Of Bayesian Network Computation, Erik Reed, Abe Ishihara, Ole J. Mengshoel
Adaptive Control Of Bayesian Network Computation, Erik Reed, Abe Ishihara, Ole J. Mengshoel
Ole J Mengshoel
Age-Layered Expectation Maximization For Parameter Learning In Bayesian Networks, Avneesh Saluja, Priya Sundararajan, Ole J. Mengshoel
Age-Layered Expectation Maximization For Parameter Learning In Bayesian Networks, Avneesh Saluja, Priya Sundararajan, Ole J. Mengshoel
Ole J Mengshoel
A Tutorial On Bayesian Networks For System Health Management, Arthur Choi, Lu Zheng, Adnan Darwiche, Ole J. Mengshoel
A Tutorial On Bayesian Networks For System Health Management, Arthur Choi, Lu Zheng, Adnan Darwiche, Ole J. Mengshoel
Ole J Mengshoel
Bayesian networks have established themselves as an indispensable tool in artificial intelligence, and are being used effectively by researchers and practitioners more broadly in science and engineering. The domain of system health management, including diagnosis, is no exception. In fact, diagnostic applications have driven much of the developments in Bayesian networks over the past few decades. In this chapter, we provide a gentle and accessible introduction to modeling and reasoning with Bayesian networks, with the domain of system health management in mind.
Bayesian Software Health Management For Aircraft Guidance, Navigation, And Control, Johann M. Schumann, Timmy Mbaya, Ole J. Mengshoel
Bayesian Software Health Management For Aircraft Guidance, Navigation, And Control, Johann M. Schumann, Timmy Mbaya, Ole J. Mengshoel
Ole J Mengshoel
Modern aircraft — both piloted fly-by-wire commercial aircraft as well as UAVs — more and more depend on highly complex safety critical software systems with many sensors and computer-controlled actuators. Despite careful design and V&V of the software, severe incidents have happened due to malfunctioning software.
In this paper, we discuss the use of Bayesian networks to monitor the health of the on-board software and sensor system, and to perform advanced on-board diagnostic reasoning. We focus on the development of reliable and robust health models for combined software and sensor systems, with application to guidance, navigation, and control (GN&C). Our …
Integrating Probabilistic Reasoning And Statistical Quality Control Techniques For Fault Diagnosis In Hybrid Domains, Brian Ricks, Craig Harrison, Ole J. Mengshoel
Integrating Probabilistic Reasoning And Statistical Quality Control Techniques For Fault Diagnosis In Hybrid Domains, Brian Ricks, Craig Harrison, Ole J. Mengshoel
Ole J Mengshoel
Visualizing And Understanding Large-Scale Bayesian Networks, Michele Cossalter, Ole J. Mengshoel, Ted Selker
Visualizing And Understanding Large-Scale Bayesian Networks, Michele Cossalter, Ole J. Mengshoel, Ted Selker
Ole J Mengshoel
Bayesian networks are a theoretically well-founded approach to represent large multi-variate probability distributions, and have proven useful in a broad range of applications. While several software tools for visualizing and editing Bayesian networks exist, they have important weaknesses when it comes to enabling users to clearly understand and compare conditional probability tables in the context of network topology, especially in large-scale networks. This paper describes a system for improving the ability for computers to work with people to develop intelligent systems through the construction of high-performing Bayesian networks. We describe NetEx, a tool developed as a Cytoscape plugin, which allows …
Software Health Management With Bayesian Networks, Ole J. Mengshoel, Johann M. Schumann
Software Health Management With Bayesian Networks, Ole J. Mengshoel, Johann M. Schumann
Ole J Mengshoel
No abstract provided.
Integrated Software And Sensor Health Management For Small Spacecraft, Johann Schumann, Ole J. Mengshoel, Timmy Mbaya
Integrated Software And Sensor Health Management For Small Spacecraft, Johann Schumann, Ole J. Mengshoel, Timmy Mbaya
Ole J Mengshoel
Despite their size, small spacecraft have highly complex architectures with many sensors and computer-controlled actuators. At the same time, size, weight, and budget constraints often dictate that small spacecraft are designed as single-string systems, which means that there are no or few redundant systems. Thus, all components, including software, must operate as reliably. Faults, if present, must be detected as early as possible to enable (usually limited) forms of mitigation. Telemetry bandwidth for such spacecraft is usually very limited. Therefore, fault detection and diagnosis must be performed on-board. Further restrictions include low computational power and small memory.
In this paper, …
Belief Propagation By Message Passing In Junction Trees: Computing Each Message Faster Using Gpu Parallelization, Lu Zheng, Ole J. Mengshoel, Jike Chong
Belief Propagation By Message Passing In Junction Trees: Computing Each Message Faster Using Gpu Parallelization, Lu Zheng, Ole J. Mengshoel, Jike Chong
Ole J Mengshoel
Compiling Bayesian networks (BNs) to junction trees and performing belief propagation over them is among the most prominent approaches to computing posteriors in BNs. However, belief propagation over junction tree is known to be computationally intensive in the general case. Its complexity may increase dramatically with the connectivity and state space cardinality of Bayesian network nodes. In this paper, we address this computational challenge using GPU parallelization. We develop data structures and algorithms that extend existing junction tree techniques, and specifically develop a novel approach to computing each belief propagation message in parallel. We implement our approach on an NVIDIA …
Verification And Validation Of System Health Management Models Using Parametric Testing, Erik Reed, Johann Schumann, Ole J. Mengshoel
Verification And Validation Of System Health Management Models Using Parametric Testing, Erik Reed, Johann Schumann, Ole J. Mengshoel
Ole J Mengshoel
System Health Management (SHM) systems have found their way into many safety-critical aerospace and industrial applications. A SHM system processes readings from sensors throughout the system and uses a Health Management (HM) model to detect and identify potential faults (diagnosis) and to predict possible failures in the near future (prognosis). It is essential that a SHM system, which monitors a safety-critical component, must be at least as reliable and safe as the component itself—false alarms or missed adverse events can potentially result in catastrophic failures. The SHM system including the HM model, a piece of software, must therefore undergo rigorous …