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Full-Text Articles in Computer Engineering

Scalable Subgraph Counting: The Methods Behind The Madness, Comandur Seshadhri, Srikanta Tirthapura May 2019

Scalable Subgraph Counting: The Methods Behind The Madness, Comandur Seshadhri, Srikanta Tirthapura

Electrical and Computer Engineering Conference Papers, Posters and Presentations

Subgraph counting is a fundamental problem in graph analysis that finds use in a wide array of applications. The basic problem is to count or approximate the occurrences of a small subgraph (the pattern) in a large graph (the dataset). Subgraph counting is a computationally challenging problem, and the last few years have seen a rich literature develop around scalable solutions for it. However, these results have thus far appeared as a disconnected set of ideas that are applied separately by different research groups. We observe that there are a few common algorithmic building blocks that most subgraph counting results ...


Embedding Runtime Verification Post-Deployment For Real-Time Health Management Of Safety-Critical Systems, Brian Christopher Schwinkendorf Kempa Jan 2019

Embedding Runtime Verification Post-Deployment For Real-Time Health Management Of Safety-Critical Systems, Brian Christopher Schwinkendorf Kempa

Graduate Theses and Dissertations

As cyber-physical systems increase in both complexity and criticality, formal methods have gained traction for design-time verification of safety properties.

A lightweight formal method, runtime verification (RV), embeds checks necessary for safety-critical system health management; however, these techniques have been slow to appear in practice despite repeated calls by both industry and academia to leverage them.

Additionally, the state-of-the-art in RV lacks a best practice approach when a deployed system requires increased flexibility due to a change in mission, or in response to an emergent condition not accounted for at design time.

Human-robot interaction necessitates stringent safety guarantees to protect ...


Abnormality Management In Spatial Crowdsourcing For Multi-Skilled Workers Assignment, Srinandan Kota Jan 2019

Abnormality Management In Spatial Crowdsourcing For Multi-Skilled Workers Assignment, Srinandan Kota

Creative Components

Crowdsourcing is dependent on a number of skilled workers who are needed to accomplish spatial tasks. This has been an active area of research and is gaining wide popularity now. Most of these tasks can be completed online due to convenience, but this method fails when there is a need of completing a task at actual physical locations. This has led to a new area called Spatial crowd sourcing that consists of location-specific tasks that require people who can accomplish them to physically arrive at specific locations. The tasks which require specific skillsets, completion times or other constraints are matched ...


Implementation Of Image Quality Assessment Algorithms For Descriptive Statistics And Deep Learning On Stegoappdb, Venkata Bhanu Chowdary Allada Jan 2019

Implementation Of Image Quality Assessment Algorithms For Descriptive Statistics And Deep Learning On Stegoappdb, Venkata Bhanu Chowdary Allada

Creative Components

No abstract provided.


Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr. Nov 2018

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

Statistics Preprints

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 ...


Reducing Labeling Complexity In Streaming Data Mining, Yesdaulet Izenov Jan 2018

Reducing Labeling Complexity In Streaming Data Mining, Yesdaulet Izenov

Graduate Theses and Dissertations

Supervised machine learning is an approach where an algorithm estimates a mapping

function by using labeled data i.e. utilizing data attributes and target values. One of the major

obstacles in supervised learning is the labeling step. Obtaining labeled data is an expensive

procedure since it typically requires human effort. Training a model with too little data tends

to overfit therefore in order to achieve a reasonable accuracy of prediction we need a minimum

number of labeled examples. This is also true for streaming machine learning models. Maintaining

a model without rebuilding and performing a prediction task without ever storing ...


Optimal Resource Scheduling For Energy-Efficient Next Generation Wireless Networks, Taewoon Kim Jan 2018

Optimal Resource Scheduling For Energy-Efficient Next Generation Wireless Networks, Taewoon Kim

Graduate Theses and Dissertations

Cellular networks can provide highly available and reliable communication links to the Internet of Things (IoT) applications, letting the connected Things paradigm gain much more momentum than ever. Also, the rich information collected from the Things with sensing capabilities can guide the network operator to an unforeseen direction, allowing the underlying cellular networks to be further optimized. In this regard, the cellular networks and IoT are conceived as the key components of the beyond-4G and future 5G networks. Therefore, in this dissertation, we study each of the two components in depth, focusing on how to optimize the networking resources for ...


Variance-Optimal Offline And Streaming Stratified Random Sampling, Trong Duc Nguyen, Ming-Hung Shih, Divesh Srivastava, Srikanta Tirthapura, Bojian Xu Jan 2018

Variance-Optimal Offline And Streaming Stratified Random Sampling, Trong Duc Nguyen, Ming-Hung Shih, Divesh Srivastava, Srikanta Tirthapura, Bojian Xu

Electrical and Computer Engineering Publications

Stratified random sampling (SRS) is a fundamental sampling technique that provides accurate estimates for aggregate queries using a small size sample, and has been used widely for approximate query processing. A key question in SRS is how to partition a target sample size among different strata. While Neyman's allocation provides a solution that minimizes the variance of an estimate using this sample, it works under the assumption that each stratum is abundant, i.e. has a large number of data points to choose from. This assumption may not hold in general: one or more strata may be bounded, and ...


A Software Architecture For Cloud-Based Text Annotation: The Aflex Tag Tool Architecture (Atta), Mahmood Ramezani Jan 2018

A Software Architecture For Cloud-Based Text Annotation: The Aflex Tag Tool Architecture (Atta), Mahmood Ramezani

Graduate Theses and Dissertations

Text annotation is a valuable method of adding metadata to an existing text or document. However, there is no standard text annotation tool across disciplines, in part because of the variety of disciplinary needs. This document presents the AFLEX Tag Tool Architecture (ATTA), a modular software system to allow the development of text annotation tools across disciplines that vary in user interface according the needs of the disciplinary users, but share a common technical back end, ATTA.

This research describes the development of ATTA, along with the development of four different ATTA-based software tools related to text annotation that meet ...


Exploring Granger Causality In Dynamical Systems Modeling And Performance Monitoring, Homagni Saha Jan 2018

Exploring Granger Causality In Dynamical Systems Modeling And Performance Monitoring, Homagni Saha

Graduate Theses and Dissertations

Data-driven approaches are becoming increasingly crucial for modeling and performance

monitoring of complex dynamical systems. Such necessity stems from complex interactions

among sub-systems and high dimensionality that render majority of rst-principle based

methods insucient. This work explores the capability of a recently proposed probabilistic

graphical modeling technique called spatiotemporal pattern network (STPN) in capturing

Granger causality among observations in a dynamical system. In this context, we introduce

the notion of Granger-STPN (G-STPN) inspired by the notion of Granger causality. We

compare the metrics used in the two frameworks for increasing memory in a dynamical

system, and show that the metric ...


Host Managed Storage Solutions For Big Data, Pratik Mishra Jan 2018

Host Managed Storage Solutions For Big Data, Pratik Mishra

Graduate Theses and Dissertations

The performance gap between Compute and Storage is fairly considerable. With multi-core computing capabilities, CPUs have scaled with the proliferation of Big Data, but storage still remains the bottleneck. The physical media characteristics are mostly blamed for storage being slow, but this is partially true. The full potential of storage devices cannot be harnessed till all layers of I/O hierarchy function efficiently. Despite advanced optimizations applied across various layers along the odyssey of data access, the I/O stack still remains volatile. The problems associated due to the inefficiencies in data management get amplified in multi-tasking Big Data shared ...


Shared-Memory Parallel Maximal Clique Enumeration, Apurba Das, Seyed-Vahid Sanei-Mehri, Srikanta Tirthapura Jan 2018

Shared-Memory Parallel Maximal Clique Enumeration, Apurba Das, Seyed-Vahid Sanei-Mehri, Srikanta Tirthapura

Electrical and Computer Engineering Publications

We present shared-memory parallel methods for Maximal Clique Enumeration (MCE) from a graph. MCE is a fundamental and well-studied graph analytics task, and is a widely used primitive for identifying dense structures in a graph. Due to its computationally intensive nature, parallel methods are imperative for dealing with large graphs. However, surprisingly, there do not yet exist scalable and parallel methods for MCE on a shared-memory parallel machine. In this work, we present efficient shared-memory parallel algorithms for MCE, with the following properties: (1) the parallel algorithms are provably work-efficient relative to a state-of-the-art sequential algorithm (2) the algorithms have ...


Efficient Similarity Computations On Parallel Machines Using Data Shaping, Parijat Shukla Jan 2017

Efficient Similarity Computations On Parallel Machines Using Data Shaping, Parijat Shukla

Graduate Theses and Dissertations

Similarity computation is a fundamental operation in all forms of data. Big Data is, typically, characterized by attributes such as volume, velocity, variety, veracity, etc. In general, Big Data variety appears as structured, semi-structured or unstructured forms. The volume of Big Data in general, and semi-structured data in particular, is increasing at a phenomenal rate. Big Data phenomenon is posing new set of challenges to similarity computation problems occurring in semi-structured data.

Technology and processor architecture trends suggest very strongly that future processors shall have ten's of thousands of cores (hardware threads). Another crucial trend is that ratio between ...


Evaluation Of A Soc For Real-Time 3d Slam, Benjamin Williams Jan 2017

Evaluation Of A Soc For Real-Time 3d Slam, Benjamin Williams

Graduate Theses and Dissertations

SLAM, or Simultaneous Localization and Mapping, is the combined problem of constructing a map of an agent’s environment while localizing, or tracking that same agent’s pose in tandem. It is among the most challenging and fundamental tasks in computer vision, with applications ranging from augmented reality to robotic navigation. With the increasing capability and ubiquity of mobile computers such as cell phones, portable 3D SLAM systems are becoming feasible for widespread use. The Microsoft Hololens, Google Project Tango, and other 3D aware devices are modern day examples of the potential of SLAM and the challenges it has yet ...


Leveraging Bluetooth As A Second Factor In Two-Factor Authentication, Cimone Le Wright-Hamor Jan 2017

Leveraging Bluetooth As A Second Factor In Two-Factor Authentication, Cimone Le Wright-Hamor

Graduate Theses and Dissertations

Passwords have been the dominant single-factor authentication method for decades but are no longer sufficient to validate a user's identity. The simplistic nature of passwords perpetuate their existence and makes them an easy attack vector. However, Two-Factor Authentication (2FA) augments passwords and adds a layer of security. Although 2FA has the potential to increase security, traditional second factors require user interaction at every login attempt, which may contribute to slow adaptation. Traditional second factors drastically alter the user authentication experience and typically require the user to navigate away from the login screen. Therefore, we present a new second-factor method ...


Computational Modeling Of Impact And Deformation, Feifei Wang Jan 2017

Computational Modeling Of Impact And Deformation, Feifei Wang

Graduate Theses and Dissertations

This thesis tackles several problems arising in robotics and mechanics: analysis and computation of two- and muti-body impacts, planning a contact velocity for robotic batting, impact of an elastic rod onto a fixed foundation, robotic pickup of soft three-dimensional objects, and recovery of their gravity-free shapes.

Impact is an event that lasts a very short period of time but generates a very large interaction force. Assuming Stronge’s energy-based restitution, a formal impulse-based analysis is presented for the collision of two rigid bodies at single contact point under Coulomb friction in three dimensions (3D). Based on this analysis, we describe ...


Simpal: A Compositional Reasoning Framework For Imperative Programs, Lucas G. Wagner Jan 2017

Simpal: A Compositional Reasoning Framework For Imperative Programs, Lucas G. Wagner

Graduate Theses and Dissertations

The Static IMPerative AnaLyzer (SIMPAL) is a tool for performing compositional reasoning over software programs that utilize preexisting software components. SIMPAL features a specification language, called Limp, for modeling programs that utilize preexisting components. Limp is an extension of the Lustre synchronous data flow language. Limp extends Lustre by introducing control flow elements, global variables, and syntax specifying preconditions, postconditions, and global variable interactions of preexisting components.

SIMPAL translates Limp programs to an equivalent Lustre representation which can be passed to the JKind model checking tool to perform assume-guarantee reasoning, reachability, and viability analyses. The feedback from these analyses can ...


Specification: The Biggest Bottleneck In Formal Methods And Autonomy, Kristin Yvonne Rozier Nov 2016

Specification: The Biggest Bottleneck In Formal Methods And Autonomy, Kristin Yvonne Rozier

Aerospace Engineering Conference Papers, Presentations and Posters

Advancement of AI-enhanced control in autonomous systems stands on the shoulders of formal methods, which make possible the rigorous safety analysis autonomous systems require. An aircraft cannot operate autonomously unless it has design-time reasoning to ensure correct operation of the autopilot and runtime reasoning to ensure system health management, or the ability to detect and respond to off-nominal situations. Formal methods are highly dependent on the specifications over which they reason; there is no escaping the “garbage in, garbage out” reality. Specification is difficult, unglamorous, and arguably the biggest bottleneck facing verification and validation of aerospace, and other, autonomous systems ...


Massive Model Visualization: A Practical Solution, Jeremy S. Bennett Jan 2016

Massive Model Visualization: A Practical Solution, Jeremy S. Bennett

Graduate Theses and Dissertations

The ever-increasingly complex designs emanating from various companies are leading to a data explosion that is far outstripping the growth in computing processing power. The traditional large model visualization approaches used for rendering these data sets are quickly becoming insufficient, thus leading to a greater adoption of the new massive model visualization approaches designed to handle these arbitrarily sized data sets. Most new approaches utilize GPU occlusion queries that limit the data needed for loading and rendering to only those which can potentially contribute to the final image. By doing so, these approaches introduce disocclusion artifacts that often reduce the ...


Advanced Terahertz Data Processing For Nde Applications, C.P. Thomas Chiou, John R. Nagel, Jared L. Taylor, Donald Palmer Jr, Nathan R. Smith Jan 2016

Advanced Terahertz Data Processing For Nde Applications, C.P. Thomas Chiou, John R. Nagel, Jared L. Taylor, Donald Palmer Jr, Nathan R. Smith

Review of Progress in Quantitative Nondestructive Evaluation

Recently terahertz technology (THz) has emerged as a very powerful NDE tool for inspecting and characterizing dielectric materials. Due to its exceptional longitudinal and lateral resolutions, time-domain pulsed THz scan is particularly effective for inspecting thin layered dielectric media. This pulsed scanning produces multi-dimensional data for which advanced processing techniques are needed to extract and analyze the ample information within. In this presentation we conduct a comparable study of several renowned data processing techniques to determine their applicability and performance in processing THz data. These data processing techniques include an outlier detection algorithm based on minimum covariance determinant estimator, the ...


Two Opposite Sides Synchronous Tracking X-Ray Based Robotic Welding Inspection System, Kai Zheng, Jie Li, Chun Lei Tu, Xing Song Wang Jan 2016

Two Opposite Sides Synchronous Tracking X-Ray Based Robotic Welding Inspection System, Kai Zheng, Jie Li, Chun Lei Tu, Xing Song Wang

Review of Progress in Quantitative Nondestructive Evaluation

For inspecting welding seams of large-scale equipment such as storage tanks and spherical tanks, it usually cost much manpower and material, while automated testing robot can achieve fast and accurate detection. Because X-ray Flat Panel Detector is dependent on specialized automated equipment, it can greatly enhance X-ray inspection technology in large storage tanks that applying the Mecanum Omnidirectional Mobile Robot into automated weld detection. In this paper, an X-ray Flat Panel Detector based wall-climbing robotic system is developed for intelligent detecting of welding seams. The robot system consists of two Mecanum vehicles equipped with either a Flat Panel Detector or ...


Evidence-Enabled Verification For The Linux Kernel, Ahmed Yousef Tamrawi Jan 2016

Evidence-Enabled Verification For The Linux Kernel, Ahmed Yousef Tamrawi

Graduate Theses and Dissertations

Formal verification of large software has been an elusive target, riddled with problems of low accuracy and high computational complexity. With growing dependence on software in embedded and cyber-physical systems where vulnerabilities and malware can lead to disasters, an efficient and accurate verification has become a crucial need. The verification should be rigorous, computationally efficient, and automated enough to keep the human effort within reasonable limits, but it does not have to be completely automated. The automation should actually enable and simplify human cross-checking which is especially important when the stakes are high. Unfortunately, formal verification methods work mostly as ...


Testing Non-Termination In Multi-Threaded Programs, Priyanka Thyagarajan Jan 2016

Testing Non-Termination In Multi-Threaded Programs, Priyanka Thyagarajan

Graduate Theses and Dissertations

We study the problem of detecting non - termination in multi - threaded programs due to unwanted race conditions. We claim that the cause of non-termination can be attributed to the presence of at least two loops in two different threads, where the valuations of the loop controlling parameters are inter-dependent, i.e., value of one parameter in one thread depends on the execution sequence in the other thread and vice versa. In this thesis, we propose a testing based technique to analyze finite execution sequences and infer the likelihood of non-termination scenarios. Our technique is a light weight, flexible testing based ...


Device Fingerprinting Identification And Authentication: A Two-Fold Use In Multi-Factor Access Control Schemes, Paul Eugene Manning Jan 2016

Device Fingerprinting Identification And Authentication: A Two-Fold Use In Multi-Factor Access Control Schemes, Paul Eugene Manning

Graduate Theses and Dissertations

Network security has always had an issue with secure authentication and identification. In the current mixed device network of today, the number of nodes on a network has expanded but these nodes are often unmanaged from a network security perspective. The solution proposed requires a paradigm shift, a recognition of what has already happened, identity is for sale across the internet. That identity is the users’ network ID, their behavior, and even their behavior in using the networks. Secondly a majority of the devices on the Internet have been fingerprinted. Use of device fingerprinting can help secure a network if ...


Green Cooperative Spectrum Sensing And Scheduling In Heterogeneous Cognitive Radio Networks, Abdulkadir Celik Jan 2016

Green Cooperative Spectrum Sensing And Scheduling In Heterogeneous Cognitive Radio Networks, Abdulkadir Celik

Graduate Theses and Dissertations

The motivation behind the cognitive radio networks (CRNs) is rooted in scarcity of the radio spectrum and inefficiency of its management to meet the ever increasing high quality of service demands. Furthermore, information and communication technologies have limited and/or expensive energy resources and contribute significantly to the global carbon footprint. To alleviate these issues, energy efficient and energy harvesting (EEH) CRNs can harvest the required energy from ambient renewable sources while collecting the necessary bandwidth by discovering free spectrum for a minimized energy cost. Therefore, EEH-CRNs have potential to achieve green communications by enabling spectrum and energy self-sustaining networks ...


Enhancing Informative Frame Filtering By Water And Bubble Detection In Colonoscopy Videos, Ashok Dahal, Junghwan Oh, Wallapak Tavanapong, Johnny S. Wong, Piet C. De Groen Jul 2015

Enhancing Informative Frame Filtering By Water And Bubble Detection In Colonoscopy Videos, Ashok Dahal, Junghwan Oh, Wallapak Tavanapong, Johnny S. Wong, Piet C. De Groen

Computer Science Conference Presentations, Posters and Proceedings

Colonoscopy has contributed to a marked decline in the number of colorectal cancer related deaths. However, recent data suggest that there is a significant (4-12%) miss-rate for the detection of even large polyps and cancers. To address this, we have been investigating an ‘automated feedback system’ which informs the endoscopist of possible sub-optimal inspection during colonoscopy. A fundamental step of this system is to distinguish non-informative frames from informative ones. Existing methods for this cannot classify water/bubble frames as non-informative even though they do not carry any useful visual information of the colon mucosa. In this paper, we propose ...


Cable Footprint History: Spatio-Temporal Technique For Instrument Detection In Gastrointestinal Endoscopic Procedures, Chuanhai Zhang, Wallapak Tavanapong, Johnny S. Wong, Piet C. De Groen, Junghwan Oh Jul 2015

Cable Footprint History: Spatio-Temporal Technique For Instrument Detection In Gastrointestinal Endoscopic Procedures, Chuanhai Zhang, Wallapak Tavanapong, Johnny S. Wong, Piet C. De Groen, Junghwan Oh

Computer Science Conference Presentations, Posters and Proceedings

We propose a new fast spatio-temporal technique that detects an operation scene---a video segment corresponding to a single purpose diagnosis action or a single purpose therapeutic action. The technique utilizes (1) color contrast of the cable region and the background, (2) the new area-based coordinate system to compute spatial features, and (3) the history of locations of detected cables of the instrument in a video to discard false regions. The proposed technique and software are useful for (1) automatic documentation of diagnostic or therapeutic operations at the end of the procedure, (2) a second review for causes of complications due ...


An Initial Matching And Mapping For Dense 3d Object Tracking In Augmented Reality Applications, Timothy Daniel Garrett Jan 2015

An Initial Matching And Mapping For Dense 3d Object Tracking In Augmented Reality Applications, Timothy Daniel Garrett

Graduate Theses and Dissertations

Augmented Reality (AR) applications rely on efficient and robust methods of tracking. One type of tracking uses dense 3D point data representations of the object to track. As opposed to sparse, dense tracking approaches are highly accurate and precise by considering all of the available data from a camera. A major challenge to dense tracking is that it requires a rough initial matching and mapping to begin. A matching means that from a known object, we can determine the object exists in the scene, and a mapping means that we can identify the position and orientation of an object with ...


Engaging Developers In Open Source Software Projects: Harnessing Social And Technical Data Mining To Improve Software Development, Patrick Eric Carlson Jan 2015

Engaging Developers In Open Source Software Projects: Harnessing Social And Technical Data Mining To Improve Software Development, Patrick Eric Carlson

Graduate Theses and Dissertations

As software development has evolved, an increasing amount of collaboration and management is done online. Open source software, in particular, has benefited greatly from communication and collaboration on the Internet. As software projects increase in size, the codebase complexity and required communication between developers increases. The barriers of entry for development participation are not only technical in nature but involve understanding the changing dynamics of the community.

Social Technical Congruence (STC) attempts to understand and model the synergies between technical development and communication. Motivated by this theory, three algorithms were developed that leverage data from version control history and email ...


Robot Dexterity: From Deformable Grasping To Impulsive Manipulation, Huan Lin Jan 2015

Robot Dexterity: From Deformable Grasping To Impulsive Manipulation, Huan Lin

Graduate Theses and Dissertations

Nowadays, it is fairly common for robots to manipulate different objects and perform sophisticated tasks. They lift up massive hard and soft objects, plan the motion with specific speed, and repeat complex tasks with high precision. However, without carefully control, even the most sophisticated robots would not be able to achieve a simple task.

Robot grasping of deformable objects is an under-researched area. The difficulty comes from both mechanics and computation. First, deformation caused by grasping motions changes the global geometry of the object. Second, different from rigid body grasping whose torques are invariant, the torques exerted by the grasping ...