Computer Sciences Commons^™

Exploratory Reconstructability Analysis Of Accident Tbi Data, Martin Zwick, Nancy Ann Carney, Rosemary Nettleton

Complex Systems Faculty Publications and Presentations

This paper describes the use of reconstructability analysis to perform a secondary study of traumatic brain injury data from automobile accidents. Neutral searches were done and their results displayed with a hypergraph. Directed searches, using both variable-based and state-based models, were applied to predict performance on two cognitive tests and one neurological test. Very simple state-based models gave large uncertainty reductions for all three DVs and sizeable improvements in percent correct for the two cognitive test DVs which were equally sampled. Conditional probability distributions for these models are easily visualized with simple decision trees. Confounding variables and counter-intuitive findings are …

Ideas And Graphs: The Tetrad Of Activity, Martin Zwick

Complex Systems Faculty Publications and Presentations

A graph can specify the skeletal structure of an idea, onto which meaning can be added by interpreting the structure. This paper considers several directed and undirected graphs consisting of four nodes, and suggests different meanings that can be associated with these different structures. Drawing on John G. Bennett’s “systematics,” specifically on the Tetrad that systematics offers as a model of “activity,” the analysis formalizes and augments the systematics account and shows that the Tetrad is a versatile model of problem-solving, regulation and control, and other processes. Discussion is extended to include hypergraphs, in which links can relate more than …

A Parallel Mesh Generator In 3d/4d, Kirill Voronin

Portland Institute for Computational Science Publications

In the report a parallel mesh generator in 3d/4d is presented. The mesh generator was developed as a part of the research project on space-time discretizations for partial differential equations in the least-squares setting. The generator is capable of constructing meshes for space-time cylinders built on an arbitrary 3d space mesh in parallel. The parallel implementation was created in the form of an extension of the finite element software MFEM. The code is publicly available in the Github repository

Introduction To Data Science: Executive Summary, Liming Wang

TREC Project Briefs

This education project created the curriculum for a new course: Introduction to Data Science for Planners, Engineers, and Scientists. The course helps students and professionals tackle the challenges of processing high volumes of data.

Designing In-Headset Authoring Tools For Virtual Reality Video, Cuong Nguyen

Dissertations and Theses

Virtual Reality (VR) video is emerging as a new art form. Viewing VR video requires wearing the VR headset to fully experience the immersive surrounding of the content. However, the novel viewing experience of VR video creates new challenges and requirements for conventional video authoring tools, which were designed mainly for working with normal video on a desktop display. Designing effective authoring tools for VR video requires intuitive video interfaces specific to VR.

This dissertation develops new workflows and systems that enable filmmakers to create and improve VR video while fully immersed in a VR headset. We introduce a series …

On The Temporal Effects Of Mobile Blockers In Urban Millimeter-Wave Cellular Scenarios, Margarita Gapeyenko, Mikhail Gerasimenko, Andrey Samuylov, Dmitri Moltchanov, Sarabjot Singh, Mustafa Riza Akdeniz, Ehsan Aryafar, Nageen Himayat, Sergey Andreev, Yevgeni Koucheryavy

Computer Science Faculty Publications and Presentations

Millimeter-wave (mmWave) propagation is known to be severely affected by the blockage of the line-of-sight (LoS) path. In contrast to microwave systems, at shorter mmWave wavelengths such blockage can be caused by human bodies, where their mobility within environment makes wireless channel alternate between the blocked and non-blocked LoS states. Following the recent 3GPP requirements on modeling the dynamic blockage as well as the temporal consistency of the channel at mmWave frequencies, in this paper a new model for predicting the state of a user in the presence of mobile blockers for representative 3GPP scenarios is developed: urban micro cell …

Ideas And Graphs, Martin Zwick

Complex Systems Faculty Publications and Presentations

A graph can specify the skeletal structure of an idea, onto which meaning can be added by interpreting the structure.

This paper considers graphs (but not hypergraphs) consisting of four nodes, and suggests meanings that can be associated with several different directed and undirected graphs.

Drawing on Bennett's "systematics," specifically on the Tetrad that systematics offers as a model of 'activity,' the analysis here shows that the Tetrad is versatile model of problem-solving, regulation and control, and other processes.

Slides are available below.

Improved Scoring Models For Semantic Image Retrieval Using Scene Graphs, Erik Timothy Conser

Dissertations and Theses

Image retrieval via a structured query is explored in Johnson, et al. [7]. The query is structured as a scene graph and a graphical model is generated from the scene graph's object, attribute, and relationship structure. Inference is performed on the graphical model with candidate images and the energy results are used to rank the best matches. In [7], scene graph objects that are not in the set of recognized objects are not represented in the graphical model. This work proposes and tests two approaches for modeling the unrecognized objects in order to leverage the attribute and relationship models to …

Refining Bounding-Box Regression For Object Localization, Naomi Lynn Dickerson

Dissertations and Theses

For the last several years, convolutional neural network (CNN) based object detection systems have used a regression technique to predict improved object bounding boxes based on an initial proposal using low-level image features extracted from the CNN. In spite of its prevalence, there is little critical analysis of bounding-box regression or in-depth performance evaluation. This thesis surveys an array of techniques and parameter settings in order to further optimize bounding-box regression and provide guidance for its implementation. I refute a claim regarding training procedure, and demonstrate the effectiveness of using principal component analysis to handle unwieldy numbers of features produced …

Spatial-Semantic Image Search By Visual Feature Synthesis, Mai Long, Hailin Jin, Chen Fang, Feng Liu

Computer Science Faculty Publications and Presentations

The performance of image retrieval has been improved tremendously in recent years through the use of deep feature representations. Most existing methods, however, aim to retrieve images that are visually similar or semantically relevant to the query, irrespective of spatial configuration. In this paper, we develop a spatial-semantic image search technology that enables users to search for images with both semantic and spatial constraints by manipulating concept text-boxes on a 2D query canvas. We train a convolutional neural network to synthesize appropriate visual features that captures the spatial-semantic constraints from the user canvas query. We directly optimize the retrieval performance …

Fully Generic Programming Over Closed Universes Of Inductive-Recursive Types, Larry Diehl

Dissertations and Theses

Dependently typed programming languages allow the type system to express arbitrary propositions of intuitionistic logic, thanks to the Curry-Howard isomorphism. Taking full advantage of this type system requires defining more types than usual, in order to encode logical correctness criteria into the definitions of datatypes. While an abundance of specialized types helps ensure correctness, it comes at the cost of needing to redefine common functions for each specialized type. This dissertation makes an effort to attack the problem of code reuse in dependently typed languages. Our solution is to write generic functions, which can be applied to any datatype.

Such …

Communicating At Terahertz Frequencies, Farnoosh Moshirfatemi

Dissertations and Theses

The number of users who get access to wireless links is increasing each day and many new applications require very high data rates. The increasing demand for higher data rates has led to the development of new techniques to increase spectrum efficiency to achieve this goal. However, the limited bandwidth of the frequency bands that are currently used for wireless communication bounds the maximum data rate possible.

In the past few years, researchers have developed new devices that work as Terahertz (THz) transmitters and receivers. The development of these devices and the large available bandwidth of the THz band is …

Bayesian Optimization For Refining Object Proposals, With An Application To Pedestrian Detection, Anthony D. Rhodes

Student Research Symposium

We devise an algorithm using a Bayesian optimization framework in conjunction with contextual visual data for the efficient localization of objects in still images. Recent research has demonstrated substantial progress in object localization and related tasks for computer vision. However, many current state-of-the-art object localization procedures still suffer from inaccuracy and inefficiency, in addition to failing to successfully leverage contextual data. We address these issues with the current research.

Our method encompasses an active search procedure that uses contextual data to generate initial bounding-box proposals for a target object. We train a convolutional neural network to approximate an offset distance …

Performance Analysis Of Droughthpc, Yasodhadevi Nachimuthu

Student Research Symposium

We present our performance analysis of DroughtHPC, a software application being developed by an interdisciplinary effort lead by Dr.Moradkhani in the Civil Engineering department, Dr. Daescu in the Math Department, and Dr. Karavanic in the Computer Science Department.

The DroughtHPC application is used to predict drought conditions for a target geographical area. The data used in the prediction are soil conditions, vegetation layers, canopy cover, snow accumulation information from satellites, and meteorological data. DroughtHPC is written in Python and uses two hydrologic models, PRMS [1] and VIC [2], to simulate soil moisture levels. A larger geographical area such as the …

Certifying Loop Pipelining Transformations In Behavioral Synthesis, Disha Puri

Dissertations and Theses

Due to the rapidly increasing complexity in hardware designs and competitive time to market trends in the industry, there is an inherent need to move designs to a higher level of abstraction. Behavioral Synthesis is the process of automatically compiling such Electronic System Level (ESL) designs written in high-level languages such as C, C++ or SystemC into Register-Transfer Level (RTL) implementation in hardware description languages such as Verilog or VHDL. However, the adoption of this flow is dependent on designers' faith in the correctness of behavioral synthesis tools.

Loop pipelining is a critical transformation employed in behavioral synthesis process, and …

Power-Aware Datacenter Networking And Optimization, Qing Yi

Dissertations and Theses

Present-day datacenter networks (DCNs) are designed to achieve full bisection bandwidth in order to provide high network throughput and server agility. However, the average utilization of typical DCN infrastructure is below 10% for significant time intervals. As a result, energy is wasted during these periods. In this thesis we analyze traffic behavior of datacenter networks using traces as well as simulated models. Based on the insight developed, we present techniques to reduce energy waste by making energy use scale linearly with load. The solutions developed are analyzed via simulations, formal analysis, and prototyping. The impact of our work is significant …

Grace's Inheritance, James Noble, Andrew P. Black, Kim B. Bruce, Michael Homer, Timothy Jones

Computer Science Faculty Publications and Presentations

This article is an apologia for the design of inheritance in the Grace educational programming language: it explains how the design of Grace’s inheritance draws from inheritance mechanisms in predecessor languages, and defends that design as the best of the available alternatives. For simplicity, Grace objects are generated from object constructors, like those of Emerald, Lua, and Javascript; for familiarity, the language also provides classes and inheritance, like Simula, Smalltalk and Java. The design question we address is whether or not object constructors can provide an inheritance semantics similar to classes.

Mining Data On Traumatic Brain Injury With Reconstructability Analysis, Martin Zwick, Nancy Carney, Rosemary Nettleton

Complex Systems Faculty Publications and Presentations

This paper reports the analysis of data on traumatic brain injury using a probabilistic graphical modeling technique known as reconstructability analysis (RA). The analysis shows the flexibility, power, and comprehensibility of RA modeling, which is well-suited for mining biomedical data. One finding of the analysis is that education is a confounding variable for the Digit Symbol Test in discriminating the severity of concussion; another - and anomalous - finding is that previous head injury predicts improved performance on the Reaction Time test. This analysis was exploratory, so its findings require follow-on confirmatory tests of their generalizability.

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly

Dissertations and Theses

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat.

An implantable cardiac …

Image Stitching: Handling Parallax, Stereopsis, And Video, Fan Zhang

Dissertations and Theses

Panorama stitching increases the field of view in an image by assembling multiple views together. Traditional stitching techniques are proven to be effective only when dealing with parallax-free monocular images. Many challenges that remain unsolved in the stitching research area include how to stitch monocular images with large parallax, how to stitch stereoscopic images to maintain their stereoscopic consistency and original disparity distribution, and how to create panoramic videos with temporally coherent content. To provide more powerful stitching techniques with more universality, we first develop a parallax-tolerant image stitching technique. With the help of it, we then effectively extend the …

Fast And Adaptive Indexing Of Multi-Dimensional Observational Data, Sheng Wang, David Maier, Beng Chin Ooi

Computer Science Faculty Publications and Presentations

Sensing devices generate tremendous amounts of data each day, which include large quantities of multi-dimensional measurements. These data are expected to be immediately available for real-time analytics as they are streamed into storage. Such scenarios pose challenges to state-of-the-art indexing methods, as they must not only support efficient queries but also frequent updates. We propose here a novel indexing method that ingests multi-dimensional observational data in real time. This method primarily guarantees extremely high throughput for data ingestion, while it can be continuously refined in the background to improve query efficiency. Instead of representing collections of points using Minimal Bounding …

Generating Technology Development Paths To The Desired Future Through System Dynamics Modeling And Simulation, Hongyi Chen, Jiang Yu, Wayne Wakeland

Complex Systems Faculty Publications and Presentations

Technology foresight is usually conducted by government or industry associations and can serve to provide companies with information on critical technologies that a country or industry intends to develop in the next ten to twenty years. For individual companies to benefit from foresight results and transform them into specific technology development plans, the relationships between the desired technologies and the dynamic business environment need to be understood. In this article, an innovation diffusion model implemented via system dynamics simulation is used to operationalize the link between foresight and planning. It helps company decision makers visualize the diffusion process of the …

Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi

Dissertations and Theses

The overall objective of this thesis is to build an integrated, inexpensive, human-sized humanoid robot from scratch that looks and behaves like a human. More specifically, my goal is to build an android robot called Marie Curie robot that can act like a human actor in the Portland Cyber Theater in the play Quantum Debate with a known script of every robot behavior. In order to achieve this goal, the humanoid robot need to has degrees of freedom (DOF) similar to human DOFs. Each part of the Curie robot was built to achieve the goal of building a complete humanoid …

Active Object Localization In Visual Situations, Max H. Quinn, Anthony Rhodes, Melanie Mitchell

Computer Science Faculty Publications and Presentations

—We describe a method for performing active localization of objects in instances of visual situations. A visual situation is an abstract concept—e.g., “a boxing match”, “a birthday party”, “walking the dog”, “waiting for a bus”—whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. Our system combines given and learned knowledge of the structure of a particular situation, and adapts that knowledge to a new situation instance as it actively searches for objects. More specifically, the system learns a set of probability distributions describing spatial and other relationships among relevant objects. The …

Investigations Of An "Objectness" Measure For Object Localization, Lewis Richard James Coates

Dissertations and Theses

Object localization is the task of locating objects in an image, typically by finding bounding boxes that isolate those objects. Identifying objects in images that have not had regions of interest labeled by humans often requires object localization to be performed first. The sliding window method is a common naïve approach, wherein the image is covered with bounding boxes of different sizes that form windows in the image. An object classifier is then run on each of these windows to determine if each given window contains a given object. However, because object classification algorithms tend to be computationally expensive, it …

Collecting Image Cropping Dataset: A Hybrid System Of Machine And Human Intelligence, Uyen T. Mai, Feng Liu

Student Research Symposium

Image cropping is a common tool that exists in almost any image editor, yet automatic cropping is still a difficult problem in Computer Vision. Since images nowadays can be easily collected through the web, machine learning is a promising approach to solve this problem. However, an image cropping dataset is not yet available and gathering such a large-scale dataset is a non-trivial task. Although a crowdsourcing website such as Mechanical Turk seems to be a solution to this task, image cropping is a sophisticated task that is vulnerable to unreliable annotation; furthermore, collecting a large-scale high-quality dataset through crowdsourcing is …

Identifying Relationships Between Scientific Datasets, Abdussalam Alawini

Dissertations and Theses

Scientific datasets associated with a research project can proliferate over time as a result of activities such as sharing datasets among collaborators, extending existing datasets with new measurements, and extracting subsets of data for analysis. As such datasets begin to accumulate, it becomes increasingly difficult for a scientist to keep track of their derivation history, which complicates data sharing, provenance tracking, and scientific reproducibility. Understanding what relationships exist between datasets can help scientists recall their original derivation history. For instance, if dataset A is contained in dataset B, then the connection between A and B could be that A was …

Incorporating Priors For Medical Image Segmentation Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung

Computer Science Faculty Publications and Presentations

Medical image segmentation is typically performed manually by a physician to delineate gross tumor volumes for treatment planning and diagnosis. Manual segmentation is performed by medical experts using prior knowledge of organ shapes and locations but is prone to reader subjectivity and inconsistency. Automating the process is challenging due to poor tissue contrast and ill-defined organ/tissue boundaries in medical images. This paper presents a genetic algorithm for combining representations of learned information such as known shapes, regional properties and relative position of objects into a single framework to perform automated three-dimensional segmentation. The algorithm has been tested for prostate segmentation …

3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall

Maseeh Summer Undergraduate Research Experience

Physical size limitations in miniaturizing two-dimensional (2D) transistors are becoming more difficult to overcome. In order to continue increasing the processing power of electronic circuits, new design paradigms are needed. Three-dimensional (3D) architectures provide a solution to this issue and are currently being implemented via wafer stacking. However, more significant gains in terms of packing and speed can be achieved by CMOS components with truly integrated 3D cellular architectures. One of these is the Cell Matrix, a self-configurable defect- and fault-tolerant architecture, which is ideally suited for ultra large-scale integration. For this project, we worked to expand the Cell Matrix …

Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood

Maseeh Summer Undergraduate Research Experience

The goal of this work is to explore applications of reservoir computing in biomolecular computation. Reservoir computing is a unique model for representing a mapping from one instance in time to a specific output. A neural network of randomly connected neurons is linked with a single output neuron or multiple output neurons. The output neurons are capable of mapping inputs to desired outputs using adaptable algorithms. This framework is investigated by using the Python programming language and object oriented design and programming. Neurons are created in programs by bundling information like input data and attributes of the network, which utilize …