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Full-Text Articles in Computer Engineering

Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham Sep 2019

Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham

Research Collection School Of Information Systems

Prior research reported that workers on Amazon Mechanical Turk (AMT) are underpaid, earning about $2/h. But the prior research did not investigate the difference in wage due to worker characteristics (e.g., country of residence). We present the first data-driven analysis on wage gap on AMT. Using work log data and demographic data collected via online survey, we analyse the gap in wage due to different factors. We show that there is indeed wage gap; for example, workers in the U.S. earn $3.01/h while those in India earn $1.41/h on average.


Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr. Aug 2019

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

William Q Meeker

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 ...


Provisioning On-Line Games: A Traffic Analysis Of A Busy Counter-Strike Server, Francis Chang, Wu-Chang Feng, Wu-Chi Feng, Jonathan Walpole Aug 2019

Provisioning On-Line Games: A Traffic Analysis Of A Busy Counter-Strike Server, Francis Chang, Wu-Chang Feng, Wu-Chi Feng, Jonathan Walpole

Jonathan Walpole

A poster that illustrates the client/server model employed by an multiplayer online game, focusing on bandwidth usage.


Distributed Edge Bundling For Large Graphs, Yves Tuyishime Aug 2019

Distributed Edge Bundling For Large Graphs, Yves Tuyishime

Computer Science and Engineering: Theses, Dissertations, and Student Research

Graphs or networks are widely used to depict the relationships between data entities in diverse scientific and engineering applications. A direct visualization (such as node-link diagram) of a graph with a large number of nodes and edges often incurs visual clutter. To address this issue, researchers have developed edge bundling algorithms that visually merge similar edges into curved bundles and can effectively reveal high-level edge patterns with reduced visual clutter. Although the existing edge bundling algorithms achieve appealing results, they are mostly designed for a single machine, and thereby the size of a graph they can handle is limited by ...


Exploring Eye Tracking Data On Source Code Via Dual Space Analysis, Li Zhang Aug 2019

Exploring Eye Tracking Data On Source Code Via Dual Space Analysis, Li Zhang

Computer Science and Engineering: Theses, Dissertations, and Student Research

Eye tracking is a frequently used technique to collect data capturing users' strategies and behaviors in processing information. Understanding how programmers navigate through a large number of classes and methods to find bugs is important to educators and practitioners in software engineering. However, the eye tracking data collected on realistic codebases is massive compared to traditional eye tracking data on one static page. The same content may appear in different areas on the screen with users scrolling in an Integrated Development Environment (IDE). Hierarchically structured content and fluid method position compose the two major challenges for visualization. We present a ...


Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore Jul 2019

Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore

Computer Science and Engineering: Theses, Dissertations, and Student Research

Robot software risks the hazard of dimensional inconsistencies. These inconsistencies occur when a program incorrectly manipulates values representing real-world quantities. Incorrect manipulation has real-world consequences that range in severity from benign to catastrophic. Previous approaches detect dimensional inconsistencies in programs but require extra developer effort and technical complications. The extra effort involves developers creating type annotations for every variable representing a real-world quantity that has physical units, and the technical complications include toolchain burdens like specialized compilers or type libraries.

To overcome the limitations of previous approaches, this thesis presents novel methods to detect dimensional inconsistencies without developer annotations. We ...


The Design And Implementation Of Aida: Ancient Inscription Database And Analytics System, M Parvez Rashid Jul 2019

The Design And Implementation Of Aida: Ancient Inscription Database And Analytics System, M Parvez Rashid

Computer Science and Engineering: Theses, Dissertations, and Student Research

AIDA, the Ancient Inscription Database and Analytic system can be used to translate and analyze ancient Minoan language. The AIDA system currently stores three types of ancient Minoan inscriptions: Linear A, Cretan Hieroglyph and Phaistos Disk inscriptions. In addition, AIDA provides candidate syllabic values and translations of Minoan words and inscriptions into English. The AIDA system allows the users to change these candidate phonetic assignments to the Linear A, Cretan Hieroglyph and Phaistos symbols. Hence the AIDA system provides for various scholars not only a convenient online resource to browse Minoan inscriptions but also provides an analysis tool to explore ...


Adaboost‑Based Security Level Classifcation Of Mobile Intelligent Terminals, Feng Wang, Houbing Song, Dingde Jiang, Hong Wen Jul 2019

Adaboost‑Based Security Level Classifcation Of Mobile Intelligent Terminals, Feng Wang, Houbing Song, Dingde Jiang, Hong Wen

Publications

With the rapid development of Internet of Things, massive mobile intelligent terminals are ready to access edge servers for real-time data calculation and interaction. However, the risk of private data leakage follows simultaneously. As the administrator of all intelligent terminals in a region, the edge server needs to clarify the ability of the managed intelligent terminals to defend against malicious attacks. Therefore, the security level classification for mobile intelligent terminals before accessing the network is indispensable. In this paper, we firstly propose a safety assessment method to detect the weakness of mobile intelligent terminals. Secondly, we match the evaluation results ...


Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg Jul 2019

Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

This paper points students towards ideas they can use towards developing a convenient library for robot navigation, with examples based on Botball primitives, and points educators towards mathematics and programming exercises they can suggest to students, especially advanced high school students.


Features Of Designing The Architecture Of Intelligent Transport Systems, Jaffar Daeibal, Vyacheslav Lapshin, Dmitry Elkin, Sergey A. Kucherov Jul 2019

Features Of Designing The Architecture Of Intelligent Transport Systems, Jaffar Daeibal, Vyacheslav Lapshin, Dmitry Elkin, Sergey A. Kucherov

Karbala International Journal of Modern Science

In the global experience, intelligent transport systems (ITS) are recognized as a general transport ideology for integrating the achievements of telematics in all types of transport activities to solve economic and social problems: reducing accidents, improving the efficiency of public transport and cargo transportation, ensuring overall transport security, and improving environmental performance. Considering the design features of the intelligent transport system (ITS), there is a need to develop requirements for the functional and physical architecture as the main part of the ITS development. The creation of functional and physical architecture touches upon issues such as: the scheme of interaction between ...


Developing 5gl Concepts From User Interactions, David Stuckless Meyer Jul 2019

Developing 5gl Concepts From User Interactions, David Stuckless Meyer

Masters Theses

In the fulfilling of the contracts generated in Test Driven Development, a developer could be said to act as a constraint solver, similar to those used by a 5th Generation Language(5GL). This thesis presents the hypothesis that 5GL linguistic mechanics, such as facts, rules and goals, will be emergent in the communications of developer pairs performing Test Driven Development, validating that 5GL syntax is congruent with the ways that practitioners communicate. Along the way, nomenclatures and linguistic patterns may be observed that could inform the design of future 5GL languages.


Scheduling And Prefetching In Hadoop With Block Access Pattern Awareness And Global Memory Sharing With Load Balancing Scheme, Sai Suman Jun 2019

Scheduling And Prefetching In Hadoop With Block Access Pattern Awareness And Global Memory Sharing With Load Balancing Scheme, Sai Suman

Computer Science and Engineering: Theses, Dissertations, and Student Research

Although several scheduling and prefetching algorithms have been proposed to improve data locality in Hadoop, there has not been much research to increase cluster performance by targeting the issue of data locality while considering the 1) cluster memory, 2) data access patterns and 3) real-time scheduling issues together.

Firstly, considering the data access patterns is crucial because the computation might access some portion of the data in the cluster only once while the rest could be accessed multiple times. Blindly retaining data in memory might eventually lead to inefficient memory utilization.

Secondly, several studies found that the cluster memory goes ...


Grammar-Based Procedurally Generated Village Creation Tool, Kevin Matthew Graves Jun 2019

Grammar-Based Procedurally Generated Village Creation Tool, Kevin Matthew Graves

Computer Engineering

This project is a 3D village generator tool for Unity. It consists of three components: a building, mountain, and river generator. All of these generators use grammar-based procedural generation in order to create a unique and logical village and landscape each time the program is run.


Forecasting Building Energy Consumption With Deep Learning: A Sequence To Sequence Approach, Ljubisa Sehovac, Cornelius Nesen, Katarina Grolinger Jun 2019

Forecasting Building Energy Consumption With Deep Learning: A Sequence To Sequence Approach, Ljubisa Sehovac, Cornelius Nesen, Katarina Grolinger

Electrical and Computer Engineering Publications

Energy Consumption has been continuously increasing due to the rapid expansion of high-density cities, and growth in the industrial and commercial sectors. To reduce the negative impact on the environment and improve sustainability, it is crucial to efficiently manage energy consumption. Internet of Things (IoT) devices, including widely used smart meters, have created possibilities for energy monitoring as well as for sensor based energy forecasting. Machine learning algorithms commonly used for energy forecasting such as feedforward neural networks are not well-suited for interpreting the time dimensionality of a signal. Consequently, this paper uses Recurrent Neural Networks (RNN) to capture time ...


Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch Jun 2019

Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch

Computer Engineering

With the increasing development of autonomous vehicles, being able to detect driveable paths in arbitrary environments has become a prevalent problem in multiple industries. This project explores a technique which utilizes a discretized output map that is used to color an image based on the confidence that each block is a driveable path. This was done using a generalized convolutional neural network that was trained on a set of 3000 images taken from the perspective of a robot along with matching masks marking which portion of the image was a driveable path. The techniques used allowed for a labeling accuracy ...


Identifying Hourly Traffic Patterns With Python Deep Learning, Christopher L. Leavitt Jun 2019

Identifying Hourly Traffic Patterns With Python Deep Learning, Christopher L. Leavitt

Computer Engineering

This project was designed to explore and analyze the potential abilities and usefulness of applying machine learning models to data collected by parking sensors at a major metro shopping mall. By examining patterns in rates at which customer enter and exit parking garages on the campus of the Bellevue Collection shopping mall in Bellevue, Washington, a recurrent neural network will use data points from the previous hours will be trained to forecast future trends.


Reach - A Community Service Application, Samuel Noel Magana Jun 2019

Reach - A Community Service Application, Samuel Noel Magana

Computer Engineering

Communities are familiar threads that unite people through several shared attributes and interests. These commonalities are the core elements that link and bond us together. Many of us are part of multiple communities, moving in and out of them depending on our needs. These common threads allow us to support and advocate for each other when facing a common threat or difficult situation. Healthy and vibrant communities are fundamental to the operation of our society. These interactions within our communities define the way we as individuals interact with each other, and society at large. Being part of a community helps ...


Exploring The Behavior Repertoire Of A Wireless Vibrationally Actuated Tensegrity Robot, Zongliang Ji Jun 2019

Exploring The Behavior Repertoire Of A Wireless Vibrationally Actuated Tensegrity Robot, Zongliang Ji

Honors Theses

Soft robotics is an emerging field of research due to its potential to explore and operate in unstructured, rugged, and dynamic environments. However, the properties that make soft robots compelling also make them difficult to robustly control. Here at Union, we developed the world’s first wireless soft tensegrity robot. The goal of my thesis is to explore effective and efficient methods to explore the diverse behavior our tensegrity robot. We will achieve that by applying state-of-art machine learning technique and a novelty search algorithm.


A Data Driven Approach To Identify Journalistic 5ws From Text Documents, Venkata Krishna Mohan Sunkara Jun 2019

A Data Driven Approach To Identify Journalistic 5ws From Text Documents, Venkata Krishna Mohan Sunkara

Computer Science and Engineering: Theses, Dissertations, and Student Research

Textual understanding is the process of automatically extracting accurate high-quality information from text. The amount of textual data available from different sources such as news, blogs and social media is growing exponentially. These data encode significant latent information which if extracted accurately can be valuable in a variety of applications such as medical report analyses, news understanding and societal studies. Natural language processing techniques are often employed to develop customized algorithms to extract such latent information from text.

Journalistic 5Ws refer to the basic information in news articles that describes an event and include where, when, who, what and why ...


On The Responsibility For Uses Of Downstream Software, Marty J. Wolf, Keith W. Miller, Frances S. Grodzinsky May 2019

On The Responsibility For Uses Of Downstream Software, Marty J. Wolf, Keith W. Miller, Frances S. Grodzinsky

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

In this paper we explore an issue that is different from whether developers are responsible for the direct impact of the software they write. We examine, instead, in what ways, and to what degree, developers are responsible for the way their software is used “downstream.” We review some key scholarship analyzing responsibility in computing ethics, including some recent work by Floridi. We use an adaptation of a mechanism developed by Floridi to argue that there are features of software that can be used as guides to better distinguish situations where a software developer might share in responsibility for the software ...


Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey May 2019

Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey

Open Educational Resources

User-friendly Geographic Information Systems (GIS) is the common thread of this collection of presentations, and activities with full lesson plans. The first section of the site contains an overview of cartography, the art of creating maps, and then looks at historical mapping platforms like Hypercities and Donald Rumsey Historical Mapping Project. In the next section Google Earth Desktop Pro is introduced, with lessons and activities on the basics of GE such as pins, paths, and kml files, as well as a more complex activity on "georeferencing" an historic map over Google Earth imagery. The final section deals with ARCGIS Online ...


Management And Security Of Multi-Cloud Applications, Lav Gupta May 2019

Management And Security Of Multi-Cloud Applications, Lav Gupta

Engineering and Applied Science 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 ...


Self-Driving Cars: Evaluation Of Deep Learning Techniques For Object Detection In Different Driving Conditions, Ramesh Simhambhatla, Kevin Okiah, Shravan Kuchkula, Robert Slater May 2019

Self-Driving Cars: Evaluation Of Deep Learning Techniques For Object Detection In Different Driving Conditions, Ramesh Simhambhatla, Kevin Okiah, Shravan Kuchkula, Robert Slater

SMU Data Science Review

Deep Learning has revolutionized Computer Vision, and it is the core technology behind capabilities of a self-driving car. Convolutional Neural Networks (CNNs) are at the heart of this deep learning revolution for improving the task of object detection. A number of successful object detection systems have been proposed in recent years that are based on CNNs. In this paper, an empirical evaluation of three recent meta-architectures: SSD (Single Shot multi-box Detector), R-CNN (Region-based CNN) and R-FCN (Region-based Fully Convolutional Networks) was conducted to measure how fast and accurate they are in identifying objects on the road, such as vehicles, pedestrians ...


Depressiongnn: Depression Prediction Using Graph Neural Network On Smartphone And Wearable Sensors, Param Bidja May 2019

Depressiongnn: Depression Prediction Using Graph Neural Network On Smartphone And Wearable Sensors, Param Bidja

Honors Scholar Theses

Depression prediction is a complicated classification problem because depression diagnosis involves many different social, physical, and mental signals. Traditional classification algorithms can only reach an accuracy of no more than 70% given the complexities of depression. However, a novel approach using Graph Neural Networks (GNN) can be used to reach over 80% accuracy, if a graph can represent the depression data set to capture differentiating features. Building such a graph requires 1) the definition of node features, which must be highly correlated with depression, and 2) the definition for edge metrics, which must also be highly correlated with depression. In ...


Smart Home Audio Assistant, Xipeng Wang May 2019

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.


Hardware Ip Classification Through Weighted Characteristics, Brendan Mcgeehan May 2019

Hardware Ip Classification Through Weighted Characteristics, Brendan Mcgeehan

Theses and Dissertations

Today’s business model for hardware designs frequently incorporates third-party Intellectual Property (IP) due to the many benefits it can bring to a company. For instance, outsourcing certain components of an overall design can reduce time-to-market by allowing each party to specialize and perfect a specific part of the overall design. However, allowing third-party involvement also increases the possibility of malicious attacks, such as hardware Trojan insertion. Trojan insertion is a particularly dangerous security threat because testing the functionality of an IP can often leave the Trojan undetected. Therefore, this thesis work provides an improvement on a Trojan detection method ...


A Survey On The Role Of Individual Differences On Visual Analytics Interactions: Masters Project Report, Jesse Huang, Alvitta Ottley May 2019

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

All Computer Science and Engineering Research

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 ...


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 ...


Paper Prototyping Comfortable Vr Play For Diverse Sensory Needs, Louanne E. Boyd, Kendra Day, Ben Wasserman, Kaitlyn Abdo, Gillian Hayes, Erik J. Linstead May 2019

Paper Prototyping Comfortable Vr Play For Diverse Sensory Needs, Louanne E. Boyd, Kendra Day, Ben Wasserman, Kaitlyn Abdo, Gillian Hayes, Erik J. Linstead

Engineering Faculty Articles and Research

We co-designed paper prototype dashboards for virtual environments for three children with diverse sensory needs. Our goal was to determine individual interaction styles in order to enable comfortable and inclusive play. As a first step towards an inclusive virtual world, we began with designing for three sensory-diverse children who have labels of neurotypical, ADHD, and autism respectively. We focused on their leisure interests and their individual sensory profiles. We present the results of co-design with family members and paper prototyping sessions conducted by family members with the children. The results contribute preliminary empirical findings for accommodating different levels of engagement ...


Applications Of Fog Computing In Video Streaming, Kyle Smith May 2019

Applications Of Fog Computing In Video Streaming, Kyle Smith

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this paper is to show the viability of fog computing in the area of video streaming in vehicles. With the rise of autonomous vehicles, there needs to be a viable entertainment option for users. The cloud fails to address these options due to latency problems experienced during high internet traffic. To improve video streaming speeds, fog computing seems to be the best option. Fog computing brings the cloud closer to the user through the use of intermediary devices known as fog nodes. It does not attempt to replace the cloud but improve the cloud by allowing faster ...