Computer Engineering Commons^™

Solving Disappearance At Gastech With Visual Analytic Techniques, Saulet Yskak

All Computer Science and Engineering Research

We are living in a society, where images and charts speak louder than words. Therefore, information visualization plays a major role in solving complex problems since it provides a visual summary of data that makes it easier to identify trends and patterns.

In this master project, I propose a web – based visual analytics tool that enables to analyze complex email and time based / event series data. The visual analytics framework uses test data from IEEE VAST Challenge 2014: Mini challenge 1 that concentrated on the disappearance of employees of a fictional GAStech company, but the tool allows users …

Investigating Patterns In Convolution Neural Network Parameters Using Probabilistic Support Vector Machines, Yuqiu Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Artificial neural networks(ANNs) are recognized as high-performance models for classification problems. They have proved to be efficient tools for many of today's applications like automatic driving, image and video recognition and restoration, big-data analysis. However, high performance deep neural networks have millions of parameters, and the iterative training procedure thus involves a very high computational cost. This research attempts to study the relationships between parameters in convolutional neural networks(CNNs). I assume there exists a certain relation between adjacent convolutional layers and proposed a machine learning model(MLM) that can be trained to represent this relation. The MLM's generalization ability is evaluated …

The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Alvitta Ottley, Adam Kern

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The primary purpose of information visualization is to act as a window between a user and the data. Historically, this has been accomplished via a single-agent framework: the only decision-maker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but a necessity. Before this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This paper aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. …

Point Cloud Processing With Neural Networks, Stephanie Miller, Jiahao Li

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In this project, we explore new techniques and architectures for applying deep neural networks when the input is point cloud data. We first consider applying convolutions on regular pixel and voxel grids, using polynomials of point coordinates and Fourier transforms to get a rich feature representation for all points mapped to the same pixel or voxel. We also apply these ideas to generalize the recently proposed "interpolated convolution", by learning continuous-space kernels as a combination of polynomial and Fourier basis kernels. Experiments on the ModelNet40 dataset demonstrate that our methods have superior performance over the baselines in 3D object recognition.

Static Taint Analysis Of Binary Executables Using Architecture-Neutral Intermediate Representation, Elaine Cole

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Ghidra, National Security Agency’s powerful reverse engineering framework, was recently released open-source in April 2019 and is capable of lifting instructions from a wide variety of processor architectures into its own register transfer language called p-code. In this project, we present a new tool which leverages Ghidra’s specific architecture-neutral intermediate representation to construct a control flow graph modeling all program executions of a given binary and apply static taint analysis. This technique is capable of identifying the information flow of malicious input from untrusted sources that may interact with key sinks or parts of the system without needing access to …

Pipelined Parallelism In A Work-Stealing Scheduler, Thomas Kelly

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A pipeline is a particular type of parallel program structure, often used to represent loops with cross-iteration dependencies. Pipelines cannot be expressed with the typical parallel language constructs offered by most environments. Therefore, in order to run pipelines, it is necessary to write a parallel language and scheduler with specialized support for them. Some such schedulers are written exclusively for pipelines and unable to run any other type of program, which allows for certain optimizations that take advantage of the pipeline structure. Other schedulers implement support for pipelines on top of a general-purpose scheduling algorithm. One example of such an …

Decoupling Information And Connectivity Via Information-Centric Transport, Hila Ben Abraham

McKelvey School of Engineering Graduate Student Theses & Dissertations

The power of Information-Centric Networking architectures (ICNs) lies in their abstraction for communication --- the request for named data. This abstraction was popularized by the HyperText Transfer Protocol (HTTP) as an application-layer abstraction, and was extended by ICNs to also serve as their network-layer abstraction. In recent years, network mechanisms for ICNs, such as scalable name-based forwarding, named-data routing and in-network caching, have been widely explored and researched. However, to the best of our knowledge, the impact of this network abstraction on ICN applications has not been explored or well understood. The motivation of this dissertation is to address this …

Polarization Division Multiplexing For Optical Data Communications, Darko Ivanovich

McKelvey School of Engineering Graduate Student Theses & Dissertations

Multiple parallel channels are ubiquitous in optical communications, with spatial division multiplexing (separate physical paths) and wavelength division multiplexing (separate optical wavelengths) being the most common forms. In this research work, we investigate the viability of polarization division multiplexing, the separation of distinct parallel optical communication channels through the polarization properties of light. We investigate polarization division multiplexing based optical communication systems in five distinct parts. In the first part of the work, we define a simulation model of two or more linearly polarized optical signals (at different polarization angles) that are transmitted through a common medium (e.g., air), filtered …

Toward Controllable And Robust Surface Reconstruction From Spatial Curves, Zhiyang Huang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Reconstructing surface from a set of spatial curves is a fundamental problem in computer graphics and computational geometry. It often arises in many applications across various disciplines, such as industrial prototyping, artistic design and biomedical imaging. While the problem has been widely studied for years, challenges remain for handling different type of curve inputs while satisfying various constraints. We study studied three related computational tasks in this thesis. First, we propose an algorithm for reconstructing multi-labeled material interfaces from cross-sectional curves that allows for explicit topology control. Second, we addressed the consistency restoration, a critical but overlooked problem in applying …

Real-Time Reliable Middleware For Industrial Internet-Of-Things, Chao Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation contributes to the area of adaptive real-time and fault-tolerant systems research, applied to Industrial Internet-of-Things (IIoT) systems. Heterogeneous timing and reliability requirements arising from IIoT applications have posed challenges for IIoT services to efficiently differentiate and meet such requirements. Specifically, IIoT services must both differentiate processing according to applications' timing requirements (including latency, event freshness, and relative consistency of each other) and enforce the needed levels of assurance for data delivery (even as far as ensuring zero data loss). It is nontrivial for an IIoT service to efficiently differentiate such heterogeneous IIoT timing/reliability requirements to fit each application, …

Management And Security Of Multi-Cloud Applications, Lav Gupta

McKelvey School of Engineering Graduate Student Theses & Dissertations

Single cloud management platform technology has reached maturity and is quite successful in information technology applications. Enterprises and application service providers are increasingly adopting a multi-cloud strategy to reduce the risk of cloud service provider lock-in and cloud blackouts and, at the same time, get the benefits like competitive pricing, the flexibility of resource provisioning and better points of presence. Another class of applications that are getting cloud service providers increasingly interested in is the carriers' virtualized network services. However, virtualized carrier services require high levels of availability and performance and impose stringent requirements on cloud services. They necessitate the …

A Survey On The Role Of Individual Differences On Visual Analytics Interactions: Masters Project Report, Jesse Huang, Alvitta Ottley

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There is ample evidence in the visualization commu- nity that individual differences matter. These prior works high- light various traits and cognitive abilities that can modulate the use of the visualization systems and demonstrate a measurable influence on speed, accuracy, process, and attention. Perhaps the most important implication of this body of work is that we can use individual differences as a mechanism for estimating people’s potential to effectively leverage visual interfaces or to identify those people who may struggle. As visual literacy and data fluency continue to become essential skills for our everyday lives, we must embrace the growing …

Smart Home Audio Assistant, Xipeng Wang

All Computer Science and Engineering Research

This report introduces an audio processing algorithm. It provides a way to access smart devices using audio. Although there are many audio assistants already on the market, most of them will not be able to control the smart devices. Therefore, this new system presented in this report will provide a way to analysis the customer’s questions. Then the algorithm will be able to query smart device information, modify the schedule or provide the reason for some arrangement.

Challenges In Integrating Iot In Smart Home, Leiquan Pan, Chenyang Lu

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Wireless devices have become a major part in Smart Home industry. Almost every smart home company has its own wireless solutions and cloud services. Normally, customers can only monitor and control smart devices through applications or platforms companies provided. It causes inconveniences and problems when we have lots of smart devices. In my master project, I did two projects to implement smart home IoT applications. From a single functionality IoT application to a more complicated smart home system, there are lots of challenges and problems appeared. This article will mainly focus on challenges in integrating IoT in a smart home.

Feature Extraction Form Ct Scan Of Plant Root, Chunyuan Li

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Roots are vital for plant by absorbing water and nutrients and providing anchorage from beneath the soil. These roles are closely related to the roots’ architecture, which describes the geometry of individual roots and their branching structure. We proposed a pipeline to efficiently annotate root architecture. My contribution focus on building an interactive tool to visual and annotate root architecture. Besides, we come up with heuristics to automate the annotation process.

Computational Geometry Teaching Tool, Yujie Zhou, Tao Ju

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When students are taking Computational Geometry course which covers many geometry algorithms, most of them are difficult to follow because these algorithms are very abstract even if authors draw pictures to illustrate. In order to help students to get a better understanding of these algorithms, we decide to design Computational Geometry Teaching Tool. This tool is a web application that covers 8 geometry algorithms : Graham Scan, Quick Hull, Line Segment Intersection, Dual, Line Arrangement, Voronoi Diagram, Incremental Delaunay Triangulation and Kd Tree. First, this tool is developed by using JavaScript so that users don't need to install any software …

Nanopower Analog Frontends For Cyber-Physical Systems, Kenji Aono

McKelvey School of Engineering Graduate Student Theses & Dissertations

In a world that is increasingly dominated by advances made in digital systems, this work will explore the exploiting of naturally occurring physical phenomena to pave the way towards a self-powered sensor for Cyber-Physical Systems (CPS). In general, a sensor frontend can be broken up into a handful of basic stages: transduction, filtering, energy conversion, measurement, and interfacing. One analog artifact that was investigated for filtering was the physical phenomenon of hysteresis induced in current-mode biquads driven near or at their saturation limit. Known as jump resonance, this analog construct facilitates a higher quality factor to be brought about without …

Decoupling Information And Connectivity Via Information-Centric Transport, Hila Ben Abraham, Jyoti Parwatikar, John Dehart, Adam Drescher, Patrick Crowley

Computer Science and Engineering Faculty Research

The power of Information-Centric Networking (ICN) architectures lies in their abstraction for communication --- the request for named data. This abstraction promises that applications can choose to operate only in the information plane, agnostic to the mechanisms implemented in the connectivity plane. However, despite this powerful promise, the information and connectivity planes are presently coupled in today's incarnations of leading ICNs by a core architectural component, the forwarding strategy. Presently, this component is not sustainable: it implements both the information and connectivity mechanisms without specifying who should choose a forwarding strategy --- an application developer or the network operator. In …

Self-Powered Time-Keeping And Time-Of-Occurrence Sensing, Liang Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Self-powered and passive Internet-of-Things (IoT) devices (e.g. RFID tags, financial assets, wireless sensors and surface-mount devices) have been widely deployed in our everyday and industrial applications. While diverse functionalities have been implemented in passive systems, the lack of a reference clock limits the design space of such devices used for applications such as time-stamping sensing, recording and dynamic authentication. Self-powered time-keeping in passive systems has been challenging because they do not have access to continuous power sources. While energy transducers can harvest power from ambient environment, the intermittent power cannot support continuous operation for reference clocks. The thesis of this …

Security Services Using Blockchains: A State Of The Art Survey, Maeda Zolanvari, Aiman Erbad, Raj Jain, Mohammed Samaka

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This article surveys blockchain-based approaches for several security services. These services include authentication, confidentiality, privacy and access control list (ACL), data and resource provenance, and integrity assurance. All these services are critical for the current distributed applications, especially due to the large amount of data being processed over the networks and the use of cloud computing. Authentication ensures that the user is who he/she claims to be. Confidentiality guarantees that data cannot be read by unauthorized users. Privacy provides the users the ability to control who can access their data. Provenance allows an efficient tracking of the data and resources …

Development Of Scalable Simulator For Spiking Neural Network, Jae Sang Ha

McKelvey School of Engineering Graduate Student Theses & Dissertations

A neural network simulator for Spiking Neural Network (SNN) is a useful research tool to model brain functions with a computer. With this tool, different parameters can be explored easily compared to using a real brain. For several decades, researchers have developed many software packages and simulators to accelerate research in computational neuroscience. However, despite their advantages, different neural simulators possess different limitations, such as flexibility of choosing different neuron models and scalability of simulators for large numbers of neurons. This paper demonstrates an efficient and scalable spiking neural simulator that is based on growth transform neurons and runs on …

Bio-Inspired Multi-Spectral And Polarization Imaging Sensors For Image-Guided Surgery, Nimrod Missael Garcia

McKelvey School of Engineering Graduate Student Theses & Dissertations

Image-guided surgery (IGS) can enhance cancer treatment by decreasing, and ideally eliminating, positive tumor margins and iatrogenic damage to healthy tissue. Current state-of-the-art near-infrared fluorescence imaging systems are bulky, costly, lack sensitivity under surgical illumination, and lack co-registration accuracy between multimodal images. As a result, an overwhelming majority of physicians still rely on their unaided eyes and palpation as the primary sensing modalities to distinguish cancerous from healthy tissue. In my thesis, I have addressed these challenges in IGC by mimicking the visual systems of several animals to construct low power, compact and highly sensitive multi-spectral and color-polarization sensors. I …

Efficiently And Transparently Maintaining High Simd Occupancy In The Presence Of Wavefront Irregularity, Stephen V. Cole

McKelvey School of Engineering Graduate Student Theses & Dissertations

Demand is increasing for high throughput processing of irregular streaming applications; examples of such applications from scientific and engineering domains include biological sequence alignment, network packet filtering, automated face detection, and big graph algorithms. With wide SIMD, lightweight threads, and low-cost thread-context switching, wide-SIMD architectures such as GPUs allow considerable flexibility in the way application work is assigned to threads. However, irregular applications are challenging to map efficiently onto wide SIMD because data-dependent filtering or replication of items creates an unpredictable data wavefront of items ready for further processing. Straightforward implementations of irregular applications on a wide-SIMD architecture are prone …

Easier Parallel Programming With Provably-Efficient Runtime Schedulers, Robert Utterback

McKelvey School of Engineering Graduate Student Theses & Dissertations

Over the past decade processor manufacturers have pivoted from increasing uniprocessor performance to multicore architectures. However, utilizing this computational power has proved challenging for software developers. Many concurrency platforms and languages have emerged to address parallel programming challenges, yet writing correct and performant parallel code retains a reputation of being one of the hardest tasks a programmer can undertake.

This dissertation will study how runtime scheduling systems can be used to make parallel programming easier. We address the difficulty in writing parallel data structures, automatically finding shared memory bugs, and reproducing non-deterministic synchronization bugs. Each of the systems presented depends …

Parallel Real-Time Scheduling For Latency-Critical Applications, Jing Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

In order to provide safety guarantees or quality of service guarantees, many of today's systems consist of latency-critical applications, e.g. applications with timing constraints. The problem of scheduling multiple latency-critical jobs on a multiprocessor or multicore machine has been extensively studied for sequential (non-parallizable) jobs and different system models and different objectives have been considered. However, the computational requirement of a single job is still limited by the capacity of a single core. To provide increasingly complex functionalities of applications and to complete their higher computational demands within the same or even more stringent timing constraints, we must exploit the …

Decoupling Information And Connectivity In Information-Centric Networking, Hila Ben Abraham, Jyoti Parwatikar, John Dehart, Adam Drescher, Patrick Crowley

All Computer Science and Engineering Research

This paper introduces and demonstrates the concept of Information-Centric Transport as a mechanism for cleanly decoupling the information plane from the connectivity plane in Information-Centric Networking (ICN) architectures, such as NDN and CICN. These are coupled in today's incarnations of NDN and CICN through the use of forwarding strategy, which is the architectural component for deciding how to forward packets in the presence of either multiple next-hop options or dynamic feedback. As presently designed, forwarding strategy is not sustainable: application developers can only confidently specify strategy if they understand connectivity details, while network node operators can only confidently assign strategies …

Underwater Celestial Navigation Using The Polarization Of Light Fields, Samuel Bear Powell

McKelvey School of Engineering Graduate Student Theses & Dissertations

Global-scale underwater navigation presents challenges that modern technology has not solved. Current technologies drift and accumulate errors over time (inertial measurement), are accurate but short-distance (acoustic), or do not sufficiently penetrate the air-water interface (radio and GPS). To address these issues, I have developed a new mode of underwater navigation based on the passive observation of patterns in the polarization of in-water light. These patterns can be used to infer the sun__s relative position, which enables the use of celestial navigation in the underwater environment. I have developed an underwater polarization video camera based on a bio-inspired polarization image sensor …

Multipath And Rate Stability, Junjie Liu, Roch A. Guérin

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Originally Published In Proc. IEEE Globecom Conference - CQRM: Communication QoS, Reliability & Modeling Symposium

Learning In The Real World: Constraints On Cost, Space, And Privacy, Matt J. Kusner

McKelvey School of Engineering Graduate Student Theses & Dissertations

The sheer demand for machine learning in fields as varied as: healthcare, web-search ranking, factory automation, collision prediction, spam filtering, and many others, frequently outpaces the intended use-case of machine learning models. In fact, a growing number of companies hire machine learning researchers to rectify this very problem: to tailor and/or design new state-of-the-art models to the setting at hand.

However, we can generalize a large set of the machine learning problems encountered in practical settings into three categories: cost, space, and privacy. The first category (cost) considers problems that need to balance the accuracy of a machine learning model …

Mercator (Mapping Enumerator For Cuda) User's Manual, Stephen V. Cole, Jeremy Buhler

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Welcome to the MERCATOR user's manual! MERCATOR is a CUDA/C++ system designed to assist you in writing efficient CUDA applications by automatically generating significant portions of the GPU-side application code. We hope you find it helpful; please feel free to contact the authors with any questions or feedback.