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Full-Text Articles in Computer Engineering

Where We Are With Enterprise Architecture, Leila Halawi, Richard Mccarthy, James Farah Dec 2019

Where We Are With Enterprise Architecture, Leila Halawi, Richard Mccarthy, James Farah

Publications

Enterprise architecture has been continuously developing since the mid-1980s. Although there is now 35 years of research and use, there is still a lack consistent definitions and standards. This is apparent in the proliferation of so many different enterprise architecture frameworks. Despite the significant body of research, there is a need for standardization of terminology based upon a meta-analysis of the literature. Enterprise architecture programs require commitment throughout an organization to be effective and must be perceived to add value. This research offers an initial basis for researchers who need to expand and continue this research topic with an actual ...


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.


Bayesian Optimization For Refining Object Proposals, Anthony D. Rhodes, Jordan Witte, Melanie Mitchell, Bruno Jedynak Aug 2019

Bayesian Optimization For Refining Object Proposals, Anthony D. Rhodes, Jordan Witte, Melanie Mitchell, Bruno Jedynak

Melanie Mitchell

We develop a general-purpose algorithm using a Bayesian optimization framework for the efficient refinement of object proposals. While recent research has achieved substantial progress for object localization and related objectives in computer vision, current state-of-the-art object localization procedures are nevertheless encumbered by inefficiency and inaccuracy. We present a novel, computationally efficient method for refining inaccurate bounding-box proposals for a target object using Bayesian optimization. Offline, image features from a convolutional neural network are used to train a model to predict an object proposal’s offset distance from a target object. Online, this model is used in a Bayesian active search ...


Fast On-Line Kernel Density Estimation For Active Object Localization, Anthony D. Rhodes, Max H. Quinn, Melanie Mitchell Aug 2019

Fast On-Line Kernel Density Estimation For Active Object Localization, Anthony D. Rhodes, Max H. Quinn, Melanie Mitchell

Melanie Mitchell

A major goal of computer vision is to enable computers to interpret visual situations—abstract concepts (e.g., “a person walking a dog,” “a crowd waiting for a bus,” “a picnic”) whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. In this paper, we propose a novel method for prior learning and active object localization for this kind of knowledge-driven search in static images. In our system, prior situation knowledge is captured by a set of flexible, kernel-based density estimations— a situation model—that represent the expected spatial structure of the ...


Machine Learning To Predict The Likelihood Of A Personal Computer To Be Infected With Malware, Maryam Shahini, Ramin Farhanian, Marcus Ellis Aug 2019

Machine Learning To Predict The Likelihood Of A Personal Computer To Be Infected With Malware, Maryam Shahini, Ramin Farhanian, Marcus Ellis

SMU Data Science Review

In this paper, we present a new model to predict the prob- ability that a personal computer will become infected with malware. The dataset is selected from a Kaggle competition supported by Mi- crosoft. The data includes computer configuration, owner information, installed software, and configuration information. In our research, sev- eral classification models are utilized to assign a probability of a machine being infected with malware. The LightGBM classifier is the optimum machine learning model by performing faster with higher efficiency and lower memory usage in this research. The LightGBM algorithm obtained a cross-validation ROC-AUC score of 74%. Leading factors ...


Aws Ec2 Instance Spot Price Forecasting Using Lstm Networks, Jeffrey Lancon, Yejur Kunwar, David Stroud, Monnie Mcgee, Robert Slater Aug 2019

Aws Ec2 Instance Spot Price Forecasting Using Lstm Networks, Jeffrey Lancon, Yejur Kunwar, David Stroud, Monnie Mcgee, Robert Slater

SMU Data Science Review

Cloud computing is a network of remote computing resources hosted on the Internet that allow users to utilize cloud resources on demand. As such, it represents a paradigm shift in the way businesses and industries think about digital infrastructure. With the shift from IT resources being a capital expenditure to a managed service, companies must rethink how they approach utilizing and optimizing these resources in order to maximize productivity and minimize costs. With proper resource management, cloud resources can be instrumental in reducing computing expenses.

Cloud resources are perishable commodities; therefore, cloud service providers have developed strategies to maximize utilization ...


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 ...


Addressing Multiple Bit/Symbol Errors In Dram Subsystem, Ravikiran Yeleswarapu, Arun K. Somani Aug 2019

Addressing Multiple Bit/Symbol Errors In Dram Subsystem, Ravikiran Yeleswarapu, Arun K. Somani

Arun Somani

As DRAM technology continues to evolve towards smaller feature sizes and increased densities, faults in DRAM subsystem are becoming more severe. Current servers mostly use CHIPKILL based schemes to tolerate up-to one/two symbol errors per DRAM beat. Multi-symbol errors arising due to faults in multiple data buses and chips may not be detected by these schemes. In this paper, we introduce Single Symbol Correction Multiple Symbol Detection (SSCMSD) - a novel error handling scheme to correct single-symbol errors and detect multi-symbol errors. Our scheme makes use of a hash in combination with Error Correcting Code (ECC) to avoid silent data ...


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.


Knn Optimization For Multi-Dimensional Data, Arialdis Japa Aug 2019

Knn Optimization For Multi-Dimensional Data, Arialdis Japa

Master of Science in Computer Science Theses

The K-Nearest Neighbors (KNN) algorithm is a simple but powerful technique used in the field of data analytics. It uses a distance metric to identify existing samples in a dataset which are similar to a new sample. The new sample can then be classified via a class majority voting of its most similar samples, i.e. nearest neighbors. The KNN algorithm can be applied in many fields, such as recommender systems where it can be used to group related products or predict user preferences. In most cases, the performance of the KNN algorithm tends to suffer as the size of ...


Centralizing Energy Consumption Data In State Energy Data Centers, Zach Sibley Aug 2019

Centralizing Energy Consumption Data In State Energy Data Centers, Zach Sibley

Minnesota Journal of Law, Science & Technology

No abstract provided.


Bleeding Out: The Case For Strengthening Healthcare Client Portal Data Privacy Regulations, Matthew D. Mccord Aug 2019

Bleeding Out: The Case For Strengthening Healthcare Client Portal Data Privacy Regulations, Matthew D. Mccord

Minnesota Journal of Law, Science & Technology

No abstract provided.


Subsurface Mimo: A Beamforming Design In Internet Of Underground Things For Digital Agriculture Applications, Abdul Salam Aug 2019

Subsurface Mimo: A Beamforming Design In Internet Of Underground Things For Digital Agriculture Applications, Abdul Salam

Faculty Publications

In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required for the degree of ...


The Use Of Agricultural Robots In Weed Management And Control, Brian L. Steward, Jingyao Gai, Lie Tang Aug 2019

The Use Of Agricultural Robots In Weed Management And Control, Brian L. Steward, Jingyao Gai, Lie Tang

Brian L. Steward

Weed management and control are essential for the production of high-yielding and high-quality crops, and advances in weed control technology have had a huge impact on agricultural productivity. Any effective weed control technology needs to be both robust and adaptable. Robust weed control technology will successfully control weeds in spite of variability in the field conditions. Adaptable weed control technology has the capacity to change its strategy in the context of evolving weed populations, genetics, and climatic conditions. This chapter focuses on key work in the development of robotic weeders, including weed perception systems and weed control mechanisms. Following an ...


Asap: A Source Code Authorship Program, Matthew F. Tennyson Phd Aug 2019

Asap: A Source Code Authorship Program, Matthew F. Tennyson Phd

Faculty & Staff Research and Creative Activity

Source code authorship attribution is the task of determining who wrote a computer program, based on its source code, usually when the author is either unknown or under dispute. Areas where this can be applied include software forensics, cases of software copyright infringement, and detecting plagiarism. Numerous methods of source code authorship attribution have been proposed and studied. However, there are no known easily accessible and user-friendly programs that perform this task. Instead, researchers typically develop software in an ad hoc manner for use in their studies, and the software is rarely made publicly available. In this paper, we present ...


Predicting Critical Warps In Near-Threshold Gpgpu Applications Using A Dynamic Choke Point Analysis, Sourav Sanyal Aug 2019

Predicting Critical Warps In Near-Threshold Gpgpu Applications Using A Dynamic Choke Point Analysis, Sourav Sanyal

All Graduate Theses and Dissertations

General purpose graphics processing units (GP-GPU), owing to their enormous thread-level parallelism, can significantly improve the power consumption at the near-threshold (NTC) operating region, while offering close to a super-threshold performance. However, process variation (PV) can drastically reduce the GPU performance at NTC. In this work, choke points—a unique device-level characteristic of PV at NTC—that can exacerbate the warp criticality problem in GPUs have been explored. It is shown that the modern warp schedulers cannot tackle the choke point induced critical warps in an NTC GPU. Additionally, Choke Point Aware Warp Speculator, a circuit-architectural solution is proposed to ...


Cooperative Learning For The Consensus Of Multi-Agent Systems, Qishuai Liu Aug 2019

Cooperative Learning For The Consensus Of Multi-Agent Systems, Qishuai Liu

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

Due to a lot of attention for the multi-agent system in recent years, the consensus algorithm gained immense popularity for building fault-tolerant systems in system and control theory. Generally, the consensus algorithm drives the swarm of agents to work as a coherent group that can reach an agreement regarding a certain quantity of interest, which depends on the state of all agents themselves. The most common consensus algorithm is the average consensus, the final consensus value of which is equal to the average of the initial values. If we want the agents to find the best area of the particular ...


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 ...


A Path Loss Model For Through The Soil Wireless Communications In Digital Agriculture, Abdul Salam Jul 2019

A Path Loss Model For Through The Soil Wireless Communications In Digital Agriculture, Abdul Salam

Faculty Publications

In this paper, a path loss model is developed to predict the impact of soil type, soil moisture, operation frequency, distance, and burial depth of sensors for through-the-soil wireless communications channel. The soil specific model is developed based on empirical measurements in a testbed and field settings. The model can be used in different soils for a frequency range of 100MHz to 1GHz. The standard deviation between measured and predicted path loss is from 4-6dB in the silt loam, sandy, and silty clay loam soil types. The model leads to development of sensor-guided irrigation system in the field of digital ...


Underground Soil Sensing Using Subsurface Radio Wave Propagation, Abdul Salam, Akhlaque Ahmad Jul 2019

Underground Soil Sensing Using Subsurface Radio Wave Propagation, Abdul Salam, Akhlaque Ahmad

Faculty Publications

Continuous sensing of soil moisture is essential for smart agriculture variable rate irrigation (VRI), real-time agricultural decision making, and water conservation. Therefore, development of simple techniques to measure the in-situ properties of soil is of vital importance. Moreover, permittivity estimation has applications in electromagnetic (EM) wave propagation analysis in the soil medium, depth analysis, subsurface imaging, and UG localization. Different methods for soil permittivity and moisture estimation are time-domain reflectometry (TDR), ground-penetrating radar (GPR) measurements, and remote sensing. One major bottleneck in the current laboratory-based permittivity estimation techniques is off-line measurement of the collected soil samples. At that, the remote ...


A Comparison Of Path Loss Variations In Soil Using Planar And Dipole Antennas, Abdul Salam Jul 2019

A Comparison Of Path Loss Variations In Soil Using Planar And Dipole Antennas, Abdul Salam

Faculty Publications

In this paper, an empirical investigation of propagation path loss variations with frequency in sandy and silty clay loam soils has been done using planar and dipole antennas. The path loss experiments are conducted using vector network analyzer (VNA) in sandy soil testbed, and greenhouse outdoor silty clay loam testbed for different operation frequencies and communication distances. The results show that the planar antenna can be used for subsurface communications in a wide range of operation frequencies. The comparison paves the way for development of sensor-guided irrigation system in the field of digital agriculture.


Transportation Safety Performance Of Us Bus Transit Agencies And Population Density: A Cross-Sectional Analysis (2008-2014), Ilker Karaca, Peter T. Savolainen Jul 2019

Transportation Safety Performance Of Us Bus Transit Agencies And Population Density: A Cross-Sectional Analysis (2008-2014), Ilker Karaca, Peter T. Savolainen

Ilker Karaca

The paper examines the transportation safety performance of transit agencies providing public bus service in the US by using data from the National Transit Database (NTD)

Uses NTD data for a seven-year period from 2008 to 2014 • 3,853 observations for 651 public transportation agencies in 50 states

Seven types of bus transit fatalities and injuries (including passengers, operators, pedestrians, bicyclists)

Main explanatory variable: urban density obtained from the US Census figures

Other explanatory variables: total agency revenue miles, unlinked passenger trips, agency fleet size, and urban population


Mindset For Software Architecture Students, Lotfi Ben Othmane, Monica H. Lamm Jul 2019

Mindset For Software Architecture Students, Lotfi Ben Othmane, Monica H. Lamm

Electrical and Computer Engineering Conference Papers, Posters and Presentations

Software architecture students need to believe that they can change their abilities in order to become proficient with software architecture design. Addressing students’ beliefs about their capabilities introduces the realm of mindset. This paper reports about a survey that we conducted in a large university to study a set of factors associated with the students’ mindset. The study found that the students’ mindsets weakly correlates with their cognitive levels and are associated with their expectations from the course. In addition, it found that the students who prefer practicing software architecture have more open mindset than the ones who prefer quizzes ...


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.


A Systematic Review Of Studies On Educational Robotics, Saira Anwar, Nicholas Alexander Bascou, Muhsin Menekse, Asefeh Kardgar Jul 2019

A Systematic Review Of Studies On Educational Robotics, Saira Anwar, Nicholas Alexander Bascou, Muhsin Menekse, Asefeh Kardgar

Journal of Pre-College Engineering Education Research (J-PEER)

There has been a steady increase in the number of studies investigating educational robotics and its impact on academic and social skills of young learners. Educational robots are used both in and out of school environments to enhance K–12 students’ interest, engagement, and academic achievement in various fields of STEM education. Some prior studies show evidence for the general benefits of educational robotics as being effective in providing impactful learning experiences. However, there appears to be a need to determine the specific benefits which have been achieved through robotics implementation in K–12 formal and informal learning settings. In ...


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 ...