Computer Sciences Commons^™

Context-Aware Synthesis For Video Frame Interpolation, Simon Niklaus, Feng Liu

Computer Science Faculty Publications and Presentations

Video frame interpolation algorithms typically estimate optical flow or its variations and then use it to guide the synthesis of an intermediate frame between two consecutive original frames. To handle challenges like occlusion, bidirectional flow between the two input frames is often estimated and used to warp and blend the input frames. However, how to effectively blend the two warped frames still remains a challenging problem. This paper presents a context-aware synthesis approach that warps not only the input frames but also their pixel-wise contextual information and uses them to interpolate a high-quality intermediate frame. Specifically, we first use a …

Contingent Requirements For Artifical Intelligent Systems Development, Gary Langford, Herman Migliore

Engineering and Technology Management Faculty Publications and Presentations

A substantial portion of project failures are due to poorly defined requirements before enough is known about pragmatic end-item product capability, technology maturity, or development strategy. Process models either start with requirements or are weakly structured to elicit and derive actual stakeholder needs and to establish incontrovertible requirements. Existing process models are used acceptably for systems but are wholly inadequate for system and system of systems requirements that involve interactions with humans at a personal level. Problems with products and services are notable when artificial intelligent systems are put into use. Rather than establishing a technology baseline then working up …

Strategic Technology Planning In Product-Service Systems With Embedded Customer Experience Requirements, Soheil Zarrin, Tugrul Daim

Engineering and Technology Management Faculty Publications and Presentations

The undeniable impact of Artificial Intelligence and Internet of things on value proposition and offerings of firms, drive many strategic initiatives in organizations to design solutions which integrate products and services. Since designing Product-Service Systems inherently introduce high level of complexity and adding artificial intelligence requirements as one of the influential factors overcomplicate the long-term planning processes, the strategic planners seek for effective tools to enable them to manage the level of complexity as well as empowering them to communicate the outcomes with the whole organization. In order to achieve this purpose, Technology Roadmaps provides a structured and flexible means …

The Changing Moral Mirror Of Society: From Human To Artifical Intelligent Systems, Gary Langford, Teresa Langford

Engineering and Technology Management Faculty Publications and Presentations

Management of technology and its development carry along the responsibility and consequences for interactions between Human and Artificial Intelligent Systems (AIS). In spite of all good intentions, the effects and repercussions of conflicts between Human and the systems built with intent to assist Human may be proceeding along the path that will recognize a dismal mistake in judgment. Dreadful and intolerable impositions on Human behavior may arise regardless of how AIS is designed. That is not to say progress should cease, but rather to make the case that intensely determined efforts need to delve into the uses and implications of …

Domain Process Model Overcome Limitations Of Engineering Models For Developing Artificial Intelligent Systems, Gary O. Langford, John Green, Daniel P. Burns, Alexander Keller, Dean C. Schmidt

Engineering and Technology Management Faculty Publications and Presentations

The integrated set of prognostic domains (ISPD) of technology presented here provides a normative means to construct a wholly new process model for guiding Technology Management of Artificial Intelligent Systems (AIS). Seventeen domains represent all-inclusive stakeholder perspectives that encapsulate lifecycle analyses, evaluations, feasibilities, and tradeoffs with the domain contexts. Following Systems Model-Based thinking (SMBT), a postulated focal point interaction is the entry condition from which each domain is considered and thereafter traversed. Domains are interactive with each other through concurrent, iterative, recursive, and non-recursive processes. This interactive work continues until the completion milestones of each domain are satisfied. Techniques such …

Joint Stabilization And Direction Of 360° Videos, Chengzhou Tang, Oliver Wang, Feng Liu, Ping Tan

Computer Science Faculty Publications and Presentations

Three-hundred-sixty-degree (360°) video provides an immersive experience for viewers, allowing them to freely explore the world by turning their head. However, creating high-quality 360° video content can be challenging, as viewers may miss important events by looking in the wrong direction, or they may see things that ruin the immersion, such as stitching artifacts and the film crew. We take advantage of the fact that not all directions are equally likely to be observed; most viewers are more likely to see content located at “true north,” i.e., in front of them, due to ergonomic constraints. We therefore propose 360° video …

Samu: Design And Implementation Of Frequency Selectivity-Aware Multi-User Mimo For Wlans, Yongjiu Du, Yan Shi, Ehsan Aryafar, Pengfei Cui, Joseph Camp, Mung Chiang

Computer Science Faculty Publications and Presentations

The traffic demand of wireless networks is expected to increase 1000-fold over the next decade. In anticipation of such increasing data demand for dense networks with a large number of stations, IEEE 802.11ax has introduced key technologies for capacity improvement including Orthogonal Frequency-Division Multiple Access (OFDMA), multi-user multi-input multi-output (MU-MIMO), and greater bandwidth. However, IEEE 802.11ax has yet to fully define a specific scheduling framework, on which the throughput improvement of networks significantly depends. Even within a 20 MHz of bandwidth, users experience heterogeneous channel orthogonality characteristics across sub-carriers, which prevents access points (APs) from achieving the ideal multi-user gain. …

Predicting Cost Of Care In Total Hip Replacement, Cecily Corrine Froemke, Martin Zwick

Complex Systems Faculty Publications and Presentations

Legislative reforms aimed at slowing growth of US healthcare costs are focused on achieving greater value per dollar. To increase value healthcare providers must not only provide high quality care, but deliver this care at a sustainable cost. Predicting risks that may lead to poor outcomes and higher costs enable providers to augment decision making for optimizing patient care and inform the risk stratification necessary in emerging reimbursement models. Healthcare delivery systems are looking at their high volume service lines and identifying variation in cost and outcomes in order to determine the patient factors that are driving this variation and …

Annotation-Enabled Interpretation And Analysis Of Time-Series Data, Niveditha Venugopal

Dissertations and Theses

As we continue to produce large amounts of time-series data, the need for data analysis is growing rapidly to help gain insights from this data. These insights form the foundation of data-driven decisions in various aspects of life. Data annotations are information about the data such as comments, errors and provenance, which provide context to the underlying data and aid in meaningful data analysis in domains such as scientific research, genomics and ECG analysis. Storing such annotations in the database along with the data makes them available to help with analysis of the data. In this thesis, I propose a …

Systems Evolution And Engineering Thermodynamics, Terry Bristol

Systems Science Friday Noon Seminar Series

Despite impressive contributions, the philosophical foundations of systems theory remain in flux. In the practical context, the proper understanding of the relation of the systems framework to classical mechanics and quantum theory remains unresolved.

I argue our understanding of systems theory is advanced by recognizing the crucial link to engineering and thermodynamics. Engineering thermodynamics is more general than the historically dominant ‘rational mechanical’ thermodynamics of Clausius, Boltzmann, the Entropy Cult (viz. Jaynes’s MEP) and the recent information theory.

That systems theory’s philosophical foundations are in a philosophy of engineering and an engineering worldview should be no surprise, given the modern …

Reconstructability And Dynamics Of Elementary Cellular Automata, Martin Zwick

Complex Systems Faculty Publications and Presentations

Reconstructability analysis (RA) is a method to determine whether a multivariate relation, defined set- or information-theoretically, is decomposable with or without loss into lower ordinality relations. Set-theoretic RA (SRA) is used to characterize the mappings of elementary cellular automata. The decomposition possible for each mapping w/o loss is a better predictor than the λ parameter (Walker & Ashby, Langton) of chaos, & non-decomposable mappings tend to produce chaos. SRA yields not only the simplest lossless structure but also a vector of losses for all structures, indexed by parameter τ. These losses are analogous to transmissions in information-theoretic RA (IRA). IRA …

A New Functional-Logic Compiler For Curry: Sprite, Sergio Antoy, Andy Jost

Computer Science Faculty Publications and Presentations

We introduce a new native code compiler for Curry codenamed Sprite. Sprite is based on the Fair Scheme, a compilation strategy that provides instructions for transforming declarative, non-deterministic programs of a certain class into imperative, deterministic code. We outline salient features of Sprite, discuss its implementation of Curry programs, and present benchmarking results. Sprite is the first-to-date operationally complete implementation of Curry. Preliminary results show that ensuring this property does not incur a significant penalty.

Epa-Rimm-V: Efficient Rootkit Detection For Virtualized Environments, Tejaswini Ajay Vibhute

Dissertations and Theses

The use of virtualized environments continues to grow for efficient utilization of the available compute resources. Hypervisors virtualize the underlying hardware resources and allow multiple Operating Systems to run simultaneously on the same infrastructure. Since the hypervisor is installed at a higher privilege level than the Operating Systems in the software stack it is vulnerable to rootkits that can modify the environment to gain control, crash the system and even steal sensitive information. Thus, runtime integrity measurement of the hypervisor is essential. The currently proposed solutions achieve the goal by relying either partially or entirely on the features of the …

A Cyber-Physical System Framework For Early Detection Of Paroxysmal Diseases, Zuxing Gu, Yu Jiang, Min Zhou, Xiaoyu Song, Lui Sha

Computer Science Faculty Publications and Presentations

Paroxysmal diseases of inpatients are globally recognized as one of the top challenges in medicine. Poor clinical outcomes are primarily caused by delayed recognition, especially due to diverse clinical diagnostic criteria with complex manifestations, irregular episodes, and already overloaded clinical activities. With the proliferation of measuring devices and increased computational capabilities, cyber-physical characterization plays an increasingly important role in many domains to provide enabling technologies. This paper presents a cyber-physical system (CPS) framework to assist physicians in making earlier diagnoses of paroxysmal sympathetic hyperactivity based on existing medical knowledge. We propose a configurable diagnostic knowledge model to characterize clinical criteria …

Introduction To Reconstructability Analysis, Martin Zwick

Complex Systems Faculty Publications and Presentations

This talk will introduce Reconstructability Analysis (RA), a data modeling methodology deriving from the 1960s work of Ross Ashby and developed in the systems community in the 1980s and afterwards. RA, based on information theory and graph theory, is a member of the family of methods known as ‘graphical models,’ which also include Bayesian networks and log-linear techniques. It is designed for exploratory modeling, although it can also be used for confirmatory hypothesis testing. RA can discover high ordinality and nonlinear interactions that are not hypothesized in advance. Its conceptual framework illuminates the relationships between wholes and parts, a subject …

Preliminary Results Of Bayesian Networks And Reconstructability Analysis Applied To The Electric Grid, Marcus Harris, Martin Zwick

Complex Systems Faculty Publications and Presentations

Reconstructability Analysis (RA) is an analytical approach developed in the systems community that combines graph theory and information theory. Graph theory provides the structure of relations (model of the data) between variables and information theory characterizes the strength and the nature of the relations. RA has three primary approaches to model data: variable based (VB) models without loops (acyclic graphs), VB models with loops (cyclic graphs) and state-based models (nearly always cyclic, individual states specifying model constraints). These models can either be directed or neutral. Directed models focus on a single response variable whereas neutral models focus on all relations …

Beyond Spatial Autocorrelation: A Novel Approach Using Reconstructability Analysis, David Percy, Martin Zwick

Complex Systems Faculty Publications and Presentations

Raster data are digital representations of spatial phenomena that are organized into rows and columns that typically have the same dimensions in each direction. They are used to represent image data at any scale. Common raster data are medical images, satellite data, and photos generated by modern smartphones.
Satellites capture reflectance data in specific bands of wavelength that correspond to red, green, blue, and often some infrared and thermal bands. These composite vectors can then be classified into actual land use categories such as forest or water using automated techniques. These classifications are verified on the ground using hand-held sensors. …

The Silencing Power Of Algorithms: How The Facebook News Feed Algorithm Manipulates Users' Perceptions Of Opinion Climates, Callie Jessica Morgan

University Honors Theses

This extended literature review investigates how the architecture and features of the Facebook Newsfeed algorithm, EdgeRank, can inhibit and facilitate the expression of political opinions. This paper will investigate how Elisabeth Noelle-Neumann's theory on public opinion, Spiral of Silence, can be used to assess the Facebook news feed as a political opinion source that actively shapes users' perceptions of minority and majority opinion climates. The feedback loops created by the algorithm's criteria influences users' decisions to self-censor or express their political opinions with interpersonal connections and unfamiliar connections on the site.

Bounding Box Improvement With Reinforcement Learning, Andrew Lewis Cleland

Dissertations and Theses

In this thesis, I explore a reinforcement learning technique for improving bounding box localizations of objects in images. The model takes as input a bounding box already known to overlap an object and aims to improve the fit of the box through a series of transformations that shift the location of the box by translation, or change its size or aspect ratio. Over the course of these actions, the model adapts to new information extracted from the image. This active localization approach contrasts with existing bounding-box regression methods, which extract information from the image only once. I implement, train, and …

An Exploration Of Linear Classifiers For Unsupervised Spiking Neural Networks With Event-Driven Data, Wesley Chavez

Dissertations and Theses

Object recognition in video has seen giant strides in accuracy improvements in the last few years, a testament to the computational capacity of deep convolutional neural networks. However, this computational capacity of software-based neural networks coincides with high power consumption compared to that of some spiking neural networks (SNNs), up to 300,000 times more energy per synaptic event in IBM's TrueNorth chip, for example. SNNs are also well-suited to exploit the precise timing of event-driven image sensors, which transmit asynchronous "events" only when the luminance of a pixel changes above or below a threshold value. The combination of event-based imagers …

Sensing Building Structure Using Uwb Radios For Disaster Recovery, Jeong Eun Lee

Dissertations and Theses

This thesis studies the problem of estimating the interior structure of a collapsed building using embedded Ultra-Wideband (UWB) radios as sensors. The two major sensing problems needed to build the mapping system are determining wall type and wall orientation. We develop sensing algorithms that determine (1) load-bearing wall composition, thickness, and location and (2) wall position within the indoor cavity. We use extensive experimentation and measurement to develop those algorithms.

In order to identify wall types and locations, our research approach uses Received Signal Strength (RSS) measurement between pairs of UWB radios. We create an extensive database of UWB signal …

Assessment Of Observed Increases In Extreme Warm Exceedances In Locations With Short Warm Side Tails, Jacob S. Hunter, Paul C. Loikith, J. David Neelin

Student Research Symposium

Regions of shorter-than-Gaussian temperature distribution tails have been shown to occur in spatially coherent patterns in the current climate using reanalysis. Under such conditions, future changes in extremes due to global warming may manifest in more complex ways than if the underlying distribution were closer to Gaussian. For instance, under a uniform warm shift, the simplest prototype for future warming, a location with a short warm side tail would experience a greater increase in exceedances than if the distribution were Gaussian. This carries meaningful societal and environmental implications including but not limited to negative impacts on human and ecosystem health, …

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

Student Research Symposium

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 …

Technological Evolution In Software Engineering, Cody Miller

Engineering and Technology Management Student Projects

In all software development processes, the software must evolve in response to its environment or user needs to maintain satisfactory performance. If software doesn’t support change, it gradually becomes useless. With many organizations today, being software-centric organizations, this has huge implications for their business: evolve your software, or risk your software becoming gradually useless, and therefore, your entire business.

Technology Evolution is a highly relevant subject, Intel’s business model for the last 50 years, has been that of Moore’s Law, a hardware centric Technology Evolution model. As a Software Engineer at Intel, our business group faces a similar issue, we …

Opportunity Identification For New Product Planning: Ontological Semantic Patent Classification, Farshad Madani

Dissertations and Theses

Intelligence tools have been developed and applied widely in many different areas in engineering, business and management. Many commercialized tools for business intelligence are available in the market. However, no practically useful tools for technology intelligence are available at this time, and very little academic research in technology intelligence methods has been conducted to date.

Patent databases are the most important data source for technology intelligence tools, but patents inherently contain unstructured data. Consequently, extracting text data from patent databases, converting that data to meaningful information and generating useful knowledge from this information become complex tasks. These tasks are currently …

When Good Components Go Bad: Formally Secure Compilation Despite Dynamic Compromise, Guglielmo Fachini, CăTăLin Hriţcu, Marco Stronati, Arthur Azevedo De Amorim, Carmine Abate, Roberto Blanco, Théo Laurent, Benjamin C. Pierce, Andrew Tolmach

Computer Science Faculty Publications and Presentations

We propose a new formal criterion for secure compilation, giving strong end-to-end security guarantees for software components written in unsafe, low-level languages with C-style undefined behavior. Our criterion is the first to model dynamic compromise in a system of mutually distrustful components running with least privilege. Each component is protected from all the others—in particular, from components that have encountered undefined behavior and become compromised. Each component receives secure compilation guarantees up to the point when it becomes compromised, after which an attacker can take complete control over the component and use any of its privileges to attack the remaining …

Statistical Analysis Of Network Change, Teresa D. Schmidt, Martin Zwick

Complex Systems Faculty Publications and Presentations

Networks are rarely subjected to hypothesis tests for difference, but when they are inferred from datasets of independent observations statistical testing is feasible. To demonstrate, a healthcare provider network is tested for significant change after an intervention using Medicaid claims data. First, the network is inferred for each time period with (1) partial least squares (PLS) regression and (2) reconstructability analysis (RA). Second, network distance (i.e., change between time periods) is measured as the mean absolute difference in (1) coefficient matrices for PLS and (2) calculated probability distributions for RA. Third, the network distance is compared against a reference distribution …

Sosiel: A Cognitive, Multi-Agent, And Knowledge-Based Platform For Modeling Boundedly-Rational Decision-Making, Garry Sotnik

Dissertations and Theses

Decision-related activities, such as bottom-up and top-down policy development, analysis, and planning, stand to benefit from the development and application of computer-based models that are capable of representing spatiotemporal social human behavior in local contexts. This is especially the case with our efforts to understand and search for ways to mitigate the context-specific effects of climate change, in which case such models need to include interacting social and ecological components. The development and application of such models has been significantly hindered by the challenges in designing artificial agents whose behavior is grounded in both empirical evidence and theory and in …

Data Warehousing Class Project Report, Gaya Haciane, Chuan Chieh Lu, Rassaniya Lerdphayakkarat, Rudraxi Mitra

Engineering and Technology Management Student Projects

Data mining is widely described or defined as the discipline of: “making sense of the data”. In today’s day and age, the rise of ubiquity of information calls for more advanced and developed techniques to mine the data and come up with insights. Data mining finds applications in many different fields and industries: Whether it is in Embryology, Crops, Elections, or Business Marketing...etc. It is not a wild assumption to consider that every organization in the world has some data mining capabilities or its main activity necessitates it and they have some third party organization doing that for them. One …

Bootcmatch: A Software Package For Bootstrap Amg Based On Graphweighted Matching, Pasqua D'Ambra, Salvatore Filipone, Panayot S. Vassilevski

Mathematics and Statistics Faculty Publications and Presentations

This article has two main objectives: one is to describe some extensions of an adaptive Algebraic Multigrid (AMG) method of the form previously proposed by the first and third authors, and a second one is to present a new software framework, named BootCMatch, which implements all the components needed to build and apply the described adaptive AMG both as a stand-alone solver and as a preconditioner in a Krylov method. The adaptive AMG presented is meant to handle general symmetric and positive definite (SPD) sparse linear systems, without assuming any a priori information of the problem and its origin; the …