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Chameleon: A Customizable Language For Teaching Programming Languages, Saverio Perugini, Jack L. Watkin 2018 University of Dayton

Chameleon: A Customizable Language For Teaching Programming Languages, Saverio Perugini, Jack L. Watkin

Computer Science Faculty Publications

ChAmElEoN is a programming language for teaching students the concepts and implementation of computer languages. We describe its syntax and semantics, the educational aspects involved in the implementation of a variety of interpreters for it, its malleability, and student feedback to inspire its use for teaching languages.


An Application Of The Actor Model Of Concurrency In Python: A Euclidean Rhythm Music Sequencer, Daniel P. Prince, Saverio Perugini 2018 University of Dayton

An Application Of The Actor Model Of Concurrency In Python: A Euclidean Rhythm Music Sequencer, Daniel P. Prince, Saverio Perugini

Computer Science Faculty Publications

We present a real-time sequencer, implementing the Euclidean rhythm algorithm, for creative generation of drum sequences by musicians or producers. We use the Actor model of concurrency to simplify the communication required for interactivity and musical timing, and generator comprehensions and higher-order functions to simplify the implementation of the Euclidean rhythm algorithm. The resulting application sends Musical Instrument Digital Interface (MIDI) data interactively to another application for sound generation.


Developing A Contemporary Operating Systems Course, Saverio Perugini, David J. Wright 2018 University of Dayton

Developing A Contemporary Operating Systems Course, Saverio Perugini, David J. Wright

Computer Science Faculty Publications

The objective of this tutorial presentation is to foster innovation in the teaching of operating systems (os) at the undergraduate level as part of a three-year NSF-funded IUSE (Improving Undergraduate STEM Education) project titled “Engaged Student Learning: Reconceptualizing and Evaluating a Core Computer Science Course for Active Learning and STEM Student Success” (2017–2020).


The Chapman Bone Algorithm: A Diagnostic Alternative For The Evaluation Of Osteoporosis, Elise Levesque, Anton Ketterer, Wajiha Memon, Cameron James, Noah Barrett, Cyril Rakovski, Frank Frisch 2018 Chapman University

The Chapman Bone Algorithm: A Diagnostic Alternative For The Evaluation Of Osteoporosis, Elise Levesque, Anton Ketterer, Wajiha Memon, Cameron James, Noah Barrett, Cyril Rakovski, Frank Frisch

Mathematics, Physics, and Computer Science Faculty Articles and Research

Osteoporosis is the most common metabolic bone disease and goes largely undiagnosed throughout the world, due to the inaccessibility of DXA machines. Multivariate analyses of serum bone turnover markers were evaluated in 226 Orange County, California, residents with the intent to determine if serum osteocalcin and serum pyridinoline cross-links could be used to detect the onset of osteoporosis as effectively as a DXA scan. Descriptive analyses of the demographic and lab characteristics of the participants were performed through frequency, means and standard deviation estimations. We implemented logistic regression modeling to find the best classification algorithm for osteoporosis. All calculations and ...


Programming For The Web: From Soup To Nuts: Implementing A Complete Gis Web Page Using Html5, Css, Javascript, Node.Js, Mongodb, And Open Layers., Charles W. Kann III 2018 None

Programming For The Web: From Soup To Nuts: Implementing A Complete Gis Web Page Using Html5, Css, Javascript, Node.Js, Mongodb, And Open Layers., Charles W. Kann Iii

Gettysburg College Open Educational Resources

This book is designed to be used as a class text but should be easily accessible to programmers interested in Web Programming. It should even be accessible to an advanced hobbyist.

The original goal behind this text was to help students doing research with me in Web based mapping applications, generally using Open Layers. The idea was to provide persistent storage using REST and simple http request from JavaScript to store the data on a server.

When teaching this class, I became painfully aware of just how little students know about Web Programming. They did not know how to format ...


Rationality And Efficient Verifiable Computation, Matteo Campanelli 2018 The Graduate Center, City University of New York

Rationality And Efficient Verifiable Computation, Matteo Campanelli

All Dissertations, Theses, and Capstone Projects

In this thesis, we study protocols for delegating computation in a model where one of the parties is rational. In our model, a delegator outsources the computation of a function f on input x to a worker, who receives a (possibly monetary) reward. Our goal is to design very efficient delegation schemes where a worker is economically incentivized to provide the correct result f(x). In this work we strive for not relying on cryptographic assumptions, in particular our results do not require the existence of one-way functions.

We provide several results within the framework of rational proofs introduced by ...


Improvement Of Decision On Coding Unit Split Mode And Intra-Picture Prediction By Machine Learning, Wenchan Jiang 2018 Kennesaw State University

Improvement Of Decision On Coding Unit Split Mode And Intra-Picture Prediction By Machine Learning, Wenchan Jiang

Master of Science in Computer Science Theses

High efficiency Video Coding (HEVC) has been deemed as the newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The reference software (i.e., HM) have included the implementations of the guidelines in appliance with the new standard. The software includes both encoder and decoder functionality.

Machine learning (ML) works with data and processes it to discover patterns that can be later used to analyze new trends. ML can play a key role in a wide range of critical applications, such as data mining, natural language processing, image recognition, and ...


Assessing Apache Spark Streaming With Scientific Data, Janak Dahal 2018 University of New Orleans

Assessing Apache Spark Streaming With Scientific Data, Janak Dahal

University of New Orleans Theses and Dissertations

Processing real-world data requires the ability to analyze data in real-time. Data processing engines like Hadoop come short when results are needed on the fly. Apache Spark's streaming library is increasingly becoming a popular choice as it can stream and analyze a significant amount of data. To showcase and assess the ability of Spark various metrics were designed and operated using data collected from the USGODAE data catalog. The latency of streaming in Apache Spark was measured and analyzed against many nodes in the cluster. Scalability was monitored by adding and removing nodes in the middle of a streaming ...


Building Test Anonymity Networks In A Cybersecurity Lab Environment, John Schriner 2018 CUNY Queensborough Community College

Building Test Anonymity Networks In A Cybersecurity Lab Environment, John Schriner

Student Theses

This paper explores current methods for creating test anonymity networks in a laboratory environment for the purpose of improving these networks while protecting user privacy. We first consider how each of these networks is research-driven and interested in helping researchers to conduct their research ethically. We then look to the software currently available for researchers to set up in their labs. Lastly we explore ways in which digital forensics and cybersecurity students could get involved with these projects and look at several class exercises that help students to understand particular attacks on these networks and ways they can help to ...


Data Scientist’S Analysis Toolbox: Comparison Of Python, R, And Sas Performance, Jim Brittain, Mariana Cendon, Jennifer Nizzi, John Pleis 2018 Southern Methodist University

Data Scientist’S Analysis Toolbox: Comparison Of Python, R, And Sas Performance, Jim Brittain, Mariana Cendon, Jennifer Nizzi, John Pleis

SMU Data Science Review

A quantitative analysis will be performed on experiments utilizing three different tools used for Data Science. The analysis will include replication of analysis along with comparisons of code length, output, and results. Qualitative data will supplement the quantitative findings. The conclusion will provide data support guidance on the correct tool to use for common situations in the field of Data Science.


Cryptovisor: A Cryptocurrency Advisor Tool, matthew baldree, paul widhalm, brandon hill, matteo ortisi 2018 Southern Methodist University

Cryptovisor: A Cryptocurrency Advisor Tool, Matthew Baldree, Paul Widhalm, Brandon Hill, Matteo Ortisi

SMU Data Science Review

In this paper, we present a tool that provides trading recommendations for cryptocurrency using a stochastic gradient boost classifier trained from a model labeled by technical indicators. The cryptocurrency market is volatile due to its infancy and limited size making it difficult for investors to know when to enter, exit, or stay in the market. Therefore, a tool is needed to provide investment recommendations for investors. We developed such a tool to support one cryptocurrency, Bitcoin, based on its historical price and volume data to recommend a trading decision for today or past days. This tool is 95.50% accurate ...


Case Study: Using Crime Data And Open Source Data To Design A Police Patrol Area, Brent Allen 2018 Southern Methodist University

Case Study: Using Crime Data And Open Source Data To Design A Police Patrol Area, Brent Allen

SMU Data Science Review

This case study examines how to use existing crime data augmented with open source data to design a patrol area. We used the a demand signal of "calls for service" vice reports which summarize calls for service. Additionally, we augmented our existing data with traffic data from Google Maps. Traffic delays did not correspond to traffic incidents reported in the area examined. These data were plotted geographically to aid in the determination of the new patrol area. The new patrol area was created around natural geographic boundaries, the density of calls for service and police operational experience.


Social Engineering In Non-Linear Warfare, Bill Gardner 2018 Marshall University

Social Engineering In Non-Linear Warfare, Bill Gardner

Journal of Applied Digital Evidence

This paper explores the use of hacking, leaking, and trolling by Russia to influence the 2016 United States Presidential Elections. These tactics have been called “the weapons of the geek” by some researchers. By using proxy hackers and Russian malware to break into the email of the Democratic National Committee and then giving that email to Wikileaks to publish on the Internet, the Russian government attempted to swing the election in the favor of their preferred candidate.

The source of the malware used in the DNC hack was determined to be of Russian in nature and has been used on ...


Web Technologies (Ggc), Shuting Xu, Shuhua Lai 2018 Georgia Gwinnett College

Web Technologies (Ggc), Shuting Xu, Shuhua Lai

Computer Science and Information Technology Grants Collections

This Grants Collection for Web Technologies was created under a Round Nine ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

  • Linked Syllabus
  • Initial Proposal
  • Final Report


Mining Temporal Activity Patterns On Social Media, Nikan Chavoshi 2018 University of New Mexico

Mining Temporal Activity Patterns On Social Media, Nikan Chavoshi

Computer Science ETDs

Social media provide communication networks for their users to easily create and share content. Automated accounts, called bots, abuse these platforms by engaging in suspicious and/or illegal activities. Bots push spam content and participate in sponsored activities to expand their audience. The prevalence of bot accounts in social media can harm the usability of these platforms, and decrease the level of trustworthiness in them. The main goal of this dissertation is to show that temporal analysis facilitates detecting bots in social media. I introduce new bot detection techniques which exploit temporal information. Since automated accounts are controlled by computer ...


Investigating On Through Glass Via Based Rf Passives For 3-D Integration, Libo Qian, Jifei Sang, Yinshui Xia, Jian Wang, Peiyi Zhao 2018 Ningbo University

Investigating On Through Glass Via Based Rf Passives For 3-D Integration, Libo Qian, Jifei Sang, Yinshui Xia, Jian Wang, Peiyi Zhao

Mathematics, Physics, and Computer Science Faculty Articles and Research

Due to low dielectric loss and low cost, glass is developed as a promising material for advanced interposers in 2.5-D and 3-D integration. In this paper, through glass vias (TGVs) are used to implement inductors for minimal footprint and large quality factor. Based on the proposed physical structure, the impact of various process and design parameters on the electrical characteristics of TGV inductors is investigated with 3-D electromagnetic simulator HFSS. It is observed that TGV inductors have identical inductance and larger quality factor in comparison with their through silicon via counterparts. Using TGV inductors and parallel plate capacitors, a ...


Data Mining Ancient Script Image Data Using Convolutional Neural Networks, Shruti Daggumati, Peter Revesz 2018 University of Nebraska-Lincoln

Data Mining Ancient Script Image Data Using Convolutional Neural Networks, Shruti Daggumati, Peter Revesz

CSE Conference and Workshop Papers

The recent surge in ancient scripts has resulted in huge image libraries of ancient texts. Data mining of the collected images enables the study of the evolution of these ancient scripts. In particular, the origin of the Indus Valley script is highly debated. We use convolutional neural networks to test which Phoenician alphabet letters and Brahmi symbols are closest to the Indus Valley script symbols. Surprisingly, our analysis shows that overall the Phoenician alphabet is much closer than the Brahmi script to the Indus Valley script symbols.


Finding Spanning Trees In Strongly Connected Graphs With Per-Vertex Degree Constraints, Samuel Benjamin Chase 2018 California Polytechnic State University

Finding Spanning Trees In Strongly Connected Graphs With Per-Vertex Degree Constraints, Samuel Benjamin Chase

Computer Science

No abstract provided.


Accuracy Evaluation Of The Canadian Openstreetmap Road Networks, Hongyu Zhang, Jacek Malczewski 2018 The University of Western Ontario

Accuracy Evaluation Of The Canadian Openstreetmap Road Networks, Hongyu Zhang, Jacek Malczewski

International Journal of Geospatial and Environmental Research

Volunteered geographic information (VGI) has been applied in many fields such as participatory planning, humanitarian relief and crisis management. One of the reasons for popularity of VGI is its cost-effectiveness. However, the coverage and accuracy of VGI cannot be guaranteed. The issue of geospatial data quality in the OpenStreetMap (OSM) project has become a trending research topic because of the large size of the dataset and the multiple channels of data access. This paper focuses on a national study of the Canadian OSM road network data for the assessment of completeness, positional accuracy, attribute accuracy, semantic accuracy and lineage. The ...


Acceleration Of Jaccard’S Index Algorithm For Training To Tag Damage On Post-Earthquake Images, Kyle John Mulligan 2018 California Polytechnic State University – San Luis Obispo

Acceleration Of Jaccard’S Index Algorithm For Training To Tag Damage On Post-Earthquake Images, Kyle John Mulligan

Master's Theses and Project Reports

There are currently different efforts to use Supervised Neural Networks (NN) to automatically label damages on images of above ground infrastructure (buildings made of concrete) taken after an earthquake. The goal of the supervised NN is to classify raw input data according to the patterns learned from an input training set. This input training data set is usually supplied by experts in the field, and in the case of this project, structural engineers carefully and mostly manually label these images for different types of damage. The level of expertise of the professionals labeling the training set varies widely, and some ...


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