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Full-Text Articles in Engineering

What Broke Where For Distributed And Parallel Applications — A Whodunit Story, Subrata Mitra Dec 2016

What Broke Where For Distributed And Parallel Applications — A Whodunit Story, Subrata Mitra

Open Access Dissertations

Detection, diagnosis and mitigation of performance problems in today's large-scale distributed and parallel systems is a difficult task. These large distributed and parallel systems are composed of various complex software and hardware components. When the system experiences some performance or correctness problem, developers struggle to understand the root cause of the problem and fix in a timely manner. In my thesis, I address these three components of the performance problems in computer systems. First, we focus on diagnosing performance problems in large-scale parallel applications running on supercomputers. We developed techniques to localize the performance problem for root-cause analysis. Parallel applications, …


Students' Explanations In Complex Learning Of Disciplinary Programming, Camilo Vieira Dec 2016

Students' Explanations In Complex Learning Of Disciplinary Programming, Camilo Vieira

Open Access Dissertations

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, …


Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam Aug 2016

Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam

Open Access Dissertations

Humans exhibit a significant ability to answer a wide range of questions about previously unencountered planning domains, and leverage this ability to construct “general-purpose'' solution plans for the domain.

The long term vision of this research is to automate this ability, constructing a system that utilizes reasoning to automatically verify claims about a planning domain. The system would use this ability to automatically construct and verify a generalized plan to solve any planning problem in the domain. The goal of this thesis is to start with baseline results from the interactive verification of claims about planning domains and develop the …


Data Driven Low-Bandwidth Intelligent Control Of A Jet Engine Combustor, Nathan L. Toner Aug 2016

Data Driven Low-Bandwidth Intelligent Control Of A Jet Engine Combustor, Nathan L. Toner

Open Access Dissertations

This thesis introduces a low-bandwidth control architecture for navigating the input space of an un-modeled combustor system between desired operating conditions while avoiding regions of instability and blow-out. An experimental procedure is discussed for identifying regions of instability and gathering sufficient data to build a data-driven model of the system's operating modes. Regions of instability and blow-out are identified experimentally and a data-driven operating point classifier is designed. This classifier acts as a map of the operating space of the combustor, indicating regions in which the flame is in a "good" or "bad" operating mode. A data-driven predictor is also …


Learning From Minimally Labeled Data With Accelerated Convolutional Neural Networks, Aysegul Dundar Apr 2016

Learning From Minimally Labeled Data With Accelerated Convolutional Neural Networks, Aysegul Dundar

Open Access Dissertations

The main objective of an Artificial Vision Algorithm is to design a mapping function that takes an image as an input and correctly classifies it into one of the user-determined categories. There are several important properties to be satisfied by the mapping function for visual understanding. First, the function should produce good representations of the visual world, which will be able to recognize images independently of pose, scale and illumination. Furthermore, the designed artificial vision system has to learn these representations by itself. Recent studies on Convolutional Neural Networks (ConvNets) produced promising advancements in visual understanding. These networks attain significant …


Optimal Monitoring And Mitigation Of Systemic Risk In Lending Networks, Zhang Li Apr 2016

Optimal Monitoring And Mitigation Of Systemic Risk In Lending Networks, Zhang Li

Open Access Dissertations

This thesis proposes optimal policies to manage systemic risk in financial networks. Given a one-period borrower-lender network in which all debts are due at the same time and have the same seniority, we address the problem of allocating a fixed amount of cash among the nodes to minimize the weighted sum of unpaid liabilities. Assuming all the loan amounts and cash flows are fixed and that there are no bankruptcy costs, we show that this problem is equivalent to a linear program. We develop a duality-based distributed algorithm to solve it which is useful for applications where it is desirable …


Energy Efficiency In Data Collection Wireless Sensor Networks, Miquel Andres Navarro Patino Apr 2016

Energy Efficiency In Data Collection Wireless Sensor Networks, Miquel Andres Navarro Patino

Open Access Dissertations

This dissertation studies the problem of energy efficiency in resource constrained and heterogeneous wireless sensor networks (WSNs) for data collection applications in real-world scenarios. The problem is addressed from three different perspectives: network routing, node energy profiles, and network management. First, the energy efficiency in a WSN is formulated as a load balancing problem, where the routing layer can diagnose and exploit the WSN topology redundancy to reduce the data traffic processed in critical nodes, independent of their hardware platform, improving their energy consumption and extending the network lifetime. We propose a new routing strategy that extends traditional cost-based routing …


Learning In Vision And Robotics, Daniel P. Barrett Apr 2016

Learning In Vision And Robotics, Daniel P. Barrett

Open Access Dissertations

I present my work on learning from video and robotic input. This is an important problem, with numerous potential applications. The use of machine learning makes it possible to obtain models which can handle noise and variation without explicitly programming them. It also raises the possibility of robots which can interact more seamlessly with humans rather than only exhibiting hard-coded behaviors. I will present my work in two areas: video action recognition, and robot navigation. First, I present a video action recognition method which represents actions in video by sequences of retinotopic appearance and motion detectors, learns such models automatically …


Grounding Robot Motion In Natural Language And Visual Perception, Scott Alan Bronikowski Apr 2016

Grounding Robot Motion In Natural Language And Visual Perception, Scott Alan Bronikowski

Open Access Dissertations

The current state of the art in military and first responder ground robots involves heavy physical and cognitive burdens on the human operator while taking little to no advantage of the potential autonomy of robotic technology. The robots currently in use are rugged remote-controlled vehicles. Their interaction modalities, usually utilizing a game controller connected to a computer, require a dedicated operator who has limited capacity for other tasks.

I present research which aims to ease these burdens by incorporating multiple modes of robotic sensing into a system which allows humans to interact with robots through a natural-language interface. I conduct …


On The 3d Point Cloud For Human-Pose Estimation, Kai-Chi Chan Apr 2016

On The 3d Point Cloud For Human-Pose Estimation, Kai-Chi Chan

Open Access Dissertations

This thesis aims at investigating methodologies for estimating a human pose from a 3D point cloud that is captured by a static depth sensor. Human-pose estimation (HPE) is important for a range of applications, such as human-robot interaction, healthcare, surveillance, and so forth. Yet, HPE is challenging because of the uncertainty in sensor measurements and the complexity of human poses. In this research, we focus on addressing challenges related to two crucial components in the estimation process, namely, human-pose feature extraction and human-pose modeling.

In feature extraction, the main challenge involves reducing feature ambiguity. We propose a 3D-point-cloud feature called …


Generalized Techniques For Using System Execution Traces To Support Software Performance Analysis, Thelge Manjula Peiris Dec 2015

Generalized Techniques For Using System Execution Traces To Support Software Performance Analysis, Thelge Manjula Peiris

Open Access Dissertations

This dissertation proposes generalized techniques to support software performance analysis using system execution traces in the absence of software development artifacts such as source code. The proposed techniques do not require modifications to the source code, or to the software binaries, for the purpose of software analysis (non-intrusive). The proposed techniques are also not tightly coupled to the architecture specific details of the system being analyzed. This dissertation extends the current techniques of using system execution traces to evaluate software performance properties, such as response times, service times. The dissertation also proposes a novel technique to auto-construct a dataflow model …


Response Of Plasma Facing Components In Tokamaks Due To Intense Energy Deposition Using Particle-In-Cell(Pic) Methods, Filippo Genco Oct 2013

Response Of Plasma Facing Components In Tokamaks Due To Intense Energy Deposition Using Particle-In-Cell(Pic) Methods, Filippo Genco

Open Access Dissertations

Damage to plasma-facing components (PFC) due to various plasma instabilities is still a major concern for the successful development of fusion energy and represents a significant research obstacle in the community. It is of great importance to fully understand the behavior and lifetime expectancy of PFC under both low energy cycles during normal events and highly energetic events as disruptions, Edge-Localized Modes (ELM), Vertical Displacement Events (VDE), and Run-away electron (RE). The consequences of these high energetic dumps with energy fluxes ranging from 10 MJ/m2 up to 200 MJ/m2 applied in very short periods (0.1 to 5 ms) can be …


Mispronunciation Detection For Language Learning And Speech Recognition Adaptation, Zhenhao Ge Oct 2013

Mispronunciation Detection For Language Learning And Speech Recognition Adaptation, Zhenhao Ge

Open Access Dissertations

The areas of "mispronunciation detection" (or "accent detection" more specifically) within the speech recognition community are receiving increased attention now. Two application areas, namely language learning and speech recognition adaptation, are largely driving this research interest and are the focal points of this work.

There are a number of Computer Aided Language Learning (CALL) systems with Computer Aided Pronunciation Training (CAPT) techniques that have been developed. In this thesis, a new HMM-based text-dependent mispronunciation system is introduced using text Adaptive Frequency Cepstral Coefficients (AFCCs). It is shown that this system outperforms the conventional HMM method based on Mel Frequency Cepstral …


Scholarly Collaboration In Engineering Education: From Big-Data Scientometrics To User-Centered Software Design, Hanjun Xian Oct 2013

Scholarly Collaboration In Engineering Education: From Big-Data Scientometrics To User-Centered Software Design, Hanjun Xian

Open Access Dissertations

Engineering education research has grown into a flourishing community with an-ever increasing number of publications and scholars. However, recent studies show that a significant amount of engineering education knowledge retains a clear disciplinary orientation. If the gaps in scholarly collaboration continue to be prevalent within the entire community, it will become increasingly difficult to sustain community memory. This will eventually inhibit the propagation of innovations and slow the movement of research findings into practice.

This dissertation studies scholarly collaboration in the engineering education research community. It provides a clear characterization of collaboration problems and proposes potential solutions. The dissertation is …


Predictive Duty Cycling Of Radios And Cameras Using Augmented Sensing In Wireless Camera Networks, Joonhwa Shin Oct 2013

Predictive Duty Cycling Of Radios And Cameras Using Augmented Sensing In Wireless Camera Networks, Joonhwa Shin

Open Access Dissertations

Energy efficiency dominates practically every aspect of the design of wireless camera networks (WCNs), and duty cycling of radios and cameras is an important tool for achieving high energy efficiencies. However, duty cycling in WCNs is made complex by the camera nodes having to anticipate the arrival of the objects in their field-of-view. What adds to this complexity is the fact that radio duty cycling and camera duty cycling are tightly coupled notions in WCNs.

Abstract In this dissertation, we present a predictive framework to provide camera nodes with an ability to anticipate the arrival of an object in the …


Simulating Land Use Land Cover Change Using Data Mining And Machine Learning Algorithms, Amin Tayyebi Jan 2013

Simulating Land Use Land Cover Change Using Data Mining And Machine Learning Algorithms, Amin Tayyebi

Open Access Dissertations

The objectives of this dissertation are to: (1) review the breadth and depth of land use land cover (LUCC) issues that are being addressed by the land change science community by discussing how an existing model, Purdue's Land Transformation Model (LTM), has been used to better understand these very important issues; (2) summarize the current state-of-the-art in LUCC modeling in an attempt to provide a context for the advances in LUCC modeling presented here; (3) use a variety of statistical, data mining and machine learning algorithms to model single LUCC transitions in diverse regions of the world (e.g. United States …


Information Measures For Statistical Orbit Determination, Alinda Kenyana Mashiku Jan 2013

Information Measures For Statistical Orbit Determination, Alinda Kenyana Mashiku

Open Access Dissertations

The current Situational Space Awareness (SSA) is faced with a huge task of tracking the increasing number of space objects. The tracking of space objects requires frequent and accurate monitoring for orbit maintenance and collision avoidance using methods for statistical orbit determination. Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty given by the probability density function (PDF). As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full PDF of the random orbit state. Through representing the full PDF …