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2019

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Articles 121 - 150 of 160

Full-Text Articles in Other Computer Sciences

The Ethics Of An Unlicensed Medical Practitioner, Charles C. Escott Jan 2019

The Ethics Of An Unlicensed Medical Practitioner, Charles C. Escott

Writing Across the Curriculum

For option A of this assignment, the prompt is that Harry, a manufacturer of medical equipment and an avid reader of medical textbooks, has developed a program that will allow its users to self-diagnose and self-treat their ailments, without a doctor’s help. Harry wants to sell his program to “ordinary folk” as a replacement for consulting licensed medical practitioners. An important point here is that Harry is not licensed to practice medicine and has only read books on the subject. The posed question is whether or not his program should be published (from an ethical standpoint—not necessarily a profit-driven one). …


Programming Safety Tips: Why You Should Use Immutable Objects Or How To Create Programs With Bugs That Can Never Be Found Or Fixed., Charles W. Kann Jan 2019

Programming Safety Tips: Why You Should Use Immutable Objects Or How To Create Programs With Bugs That Can Never Be Found Or Fixed., Charles W. Kann

Programming Tips and Tricks

Program safety deals with how to make programs as error free as possible. The hardest errors in a program for a programmer to find are often errors in using memory. There are two reasons for this. The first is that errors in accessing memory almost never show problems in the proximate area of the program where the error is made. The error has no apparent impact when it is made, but often causes catastrophic results to occur much later in the program, in areas of the program unrelated to memory error that caused it.

The second reason memory errors are …


Image-Based Malware Classification: A Space Filling Curve Approach, Stephen O Shaughnessy Jan 2019

Image-Based Malware Classification: A Space Filling Curve Approach, Stephen O Shaughnessy

Conference Papers

Anti-virus (AV) software is effective at distinguishing between benign and malicious programs yet lack the ability to effectively classify malware into their respective family classes. AV vendors receive considerably large volumes of malicious programs daily and so classification is crucial to quickly identify variants of existing malware that would otherwise have to be manually examined. This paper proposes a novel method of visualizing and classifying malware using Space-Filling Curves (SFC's) in order to improve the limitations of AV tools. The classification models produced were evaluated on previously unseen samples and showed promising results, with precision, recall and accuracy scores of …


Optimization Of Simulations In Opensimpplle, Robin Lockwood Jan 2019

Optimization Of Simulations In Opensimpplle, Robin Lockwood

Graduate Student Theses, Dissertations, & Professional Papers

Computer software has become an integral tool in exploring scientific concepts and computational models. Models, such as OpenSIMPPLLE, use a complex set of rules developed by experts to predict the impact of fires, disease, and wildlife on large scale landscapes.

OpenSIMPPLLE’s simulations are time-consuming when projecting far into the future. OpenSIMPPLLE needs to execute more efficiently to allow for faster completion of simulations. The increase in speed will also enable users to run simulations with more timesteps in shorter periods. There are plenty of ways to accomplish this.

The work described here identifies three different methods for increasing efficiency. The …


Exploring Age-Related Metamemory Differences Using Modified Brier Scores And Hierarchical Clustering, Chelsea Parlett-Pelleriti, Grace C. Lin, Masha R. Jones, Erik Linstead, Susanne M. Jaeggi Jan 2019

Exploring Age-Related Metamemory Differences Using Modified Brier Scores And Hierarchical Clustering, Chelsea Parlett-Pelleriti, Grace C. Lin, Masha R. Jones, Erik Linstead, Susanne M. Jaeggi

Engineering Faculty Articles and Research

Older adults (OAs) typically experience memory failures as they age. However, with some exceptions, studies of OAs’ ability to assess their own memory functions—Metamemory (MM)— find little evidence that this function is susceptible to age-related decline. Our study examines OAs’ and young adults’ (YAs) MM performance and strategy use. Groups of YAs (N = 138) and OAs (N = 79) performed a MM task that required participants to place bets on how likely they were to remember words in a list. Our analytical approach includes hierarchical clustering, and we introduce a new measure of MM—the modified Brier—in order to adjust …


Predicting Public Opinion On Drug Legalization: Social Media Analysis And Consumption Trends, Farahnaz Golrooy Motlagh, Saeedeh Shekarpour, Amit Sheth, Krishnaprasad Thirunarayan, Michael L. Raymer Jan 2019

Predicting Public Opinion On Drug Legalization: Social Media Analysis And Consumption Trends, Farahnaz Golrooy Motlagh, Saeedeh Shekarpour, Amit Sheth, Krishnaprasad Thirunarayan, Michael L. Raymer

Computer Science Faculty Publications

In this paper, we focus on the collection and analysis of relevant Twitter data on a state-by-state basis for (i) measuring public opinion on marijuana legalization by mining sentiment in Twitter data and (ii) determining the usage trends for six distinct types of marijuana. We overcome the challenges posed by the informal and ungrammatical nature of tweets to analyze a corpus of 306,835 relevant tweets collected over the four-month period, preceding the November 2015 Ohio Marijuana Legalization ballot and the four months after the election for all states in the US. Our analysis revealed two key insights: (i) the people …


Reachability Analysis For Neural Feedback Systems Using Regressive Polynomial Rule Inference, Souradeep Dutta, Xin Chen, Sriram Sankaranarayanan Jan 2019

Reachability Analysis For Neural Feedback Systems Using Regressive Polynomial Rule Inference, Souradeep Dutta, Xin Chen, Sriram Sankaranarayanan

Computer Science Faculty Publications

We present an approach to construct reachable set overapproxi- mations for continuous-time dynamical systems controlled using neural network feedback systems. Feedforward deep neural net- works are now widely used as a means for learning control laws through techniques such as reinforcement learning and data-driven predictive control. However, the learning algorithms for these net- works do not guarantee correctness properties on the resulting closed-loop systems. Our approach seeks to construct overapproxi- mate reachable sets by integrating a Taylor model-based flowpipe construction scheme for continuous differential equations with an approach that replaces the neural network feedback law for a small subset of …


Agent-Based Iot Coordination For Smart Cities Considering Security And Privacy, Iván García-Magariño, Geraldine Gray, Rajarajan Muttukrishnan, Waqar Asif Jan 2019

Agent-Based Iot Coordination For Smart Cities Considering Security And Privacy, Iván García-Magariño, Geraldine Gray, Rajarajan Muttukrishnan, Waqar Asif

Conference papers

The interest in Internet of Things (IoT) is increasing steeply, and the use of their smart objects and their composite services may become widespread in the next few years increasing the number of smart cities. This technology can benefit from scalable solutions that integrate composite services of multiple-purpose smart objects for the upcoming large-scale use of integrated services in IoT. This work proposes an agent-based approach for supporting large-scale use of IoT for providing complex integrated services. Its novelty relies in the use of distributed blackboards for implicit communications, decentralizing the storage and management of the blackboard information in the …


Python Loops, Natalia Novak Jan 2019

Python Loops, Natalia Novak

Open Educational Resources

The following topics are covered:

  • While Loops
  • For Loops
  • Nested loops
  • Break and continue
  • Loops else
  • enumerate()

Applications: Turtle library with loops and decision procedures.

Prior knowledge of variables, assignments, expressions, input-output, lists, and conditionals is recommended.

For CS0 students. Part of the CUNY CS04All project.


The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag Jan 2019

The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag

Faculty Articles

Now that the dust has settled on the Authors Guild cases, this Article takes stock of the legal context for TDM research in the United States. This reappraisal begins in Part I with an assessment of exactly what the Authors Guild cases did and did not establish with respect to the fair use status of text mining. Those cases held unambiguously that reproducing copyrighted works as one step in the process of knowledge discovery through text data mining was transformative, and thus ultimately a fair use of those works. Part I explains why those rulings followed inexorably from copyright's most …


The Application Of Cloud Resources To Terrain Data Visualization, Gregory J. Larrick Jan 2019

The Application Of Cloud Resources To Terrain Data Visualization, Gregory J. Larrick

EWU Masters Thesis Collection

In this thesis, the recent trends in cloud computing, via virtual machine hosted servers, are applied to the field of big data visualization. In particular, we investigate the visualization of terrain data acquired from several major open data sets with a graphics library for browser based rendering. Similar terrain data visualization solutions have not fully taken advantage of remote computational resources. In this thesis, we show that, by using a collection of Amazon EC-2 machines for fetching and decoding of terrain data, in conjunction with modern graphics libraries, three dimensional terrain information may be viewed and interacted with by many …


Relaxed Mental State Detection Using The Emotiv Epoc And Adaptive Threshold Algorithms, Olin L. Anderson Jan 2019

Relaxed Mental State Detection Using The Emotiv Epoc And Adaptive Threshold Algorithms, Olin L. Anderson

EWU Masters Thesis Collection

The electroencephalogram (EEG) has proven to be useful in a wide variety of applications, including: diagnosis of mental disorders, psychological research, neurofeedback, and brain-computer interfacing. Most such applications of the EEG benefit from an ability to automatically detect when the subject is in a relaxed state. Recently, inexpensive and relatively easy to use EEG systems, with multiple electrodes, have become available at prices comparable to cellular phones or game machines. This project’s purpose is to investigate the feasibility of real-time classification of a subject's relaxation state using one such consumer-grade EEG system, the Emotiv Epoc. The subject's state is classified …


Virtual Hearings And Blockchain Technology Solutions In Criminal Law, Chantell Bergquist Jan 2019

Virtual Hearings And Blockchain Technology Solutions In Criminal Law, Chantell Bergquist

Political Science Theses and Capstones

Technology has evolved and raided our personal and professional lives. Although the courts are not immune to the advancement and integration of technology, the courts are not keeping up with relevant technological advancements. Historically, courts have been hesitant to embrace new technologies despite the Federal Rules of Civil Procedure and the American Bar Association Model Rules of Professional Conduct. Rule 1 of the Federal Rules of Civil Procedure creates the right to a “just, speedy, and inexpensive determination of every action and proceeding.” Likewise, the American Bar Association Model Rules of Professional Conduct have determined attorneys must “keep abreast of …


The Structural Information Filtered Features Potential For Machine Learning Calculations Of Energies And Forces Of Atomic Systems., Jorge Arturo Hernandez Zeledon Jan 2019

The Structural Information Filtered Features Potential For Machine Learning Calculations Of Energies And Forces Of Atomic Systems., Jorge Arturo Hernandez Zeledon

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the last ten years, machine learning potentials have been successfully applied to the study of crystals, and molecules. However, more complex materials like clusters, macro-molecules, and glasses are out reach of current methods. The input of any machine learning system is a tensor of features (the most universal type are rank 1 tensors or vectors of features), the quality of any machine learning system is directly related to how well the feature space describes the original physical system. So far, the feature engineering process for machine learning potentials can not describe complex material. The current methods are highly inefficient …


Optimaztion Of Fantasy Basketball Lineups Via Machine Learning, James Earl Jan 2019

Optimaztion Of Fantasy Basketball Lineups Via Machine Learning, James Earl

Senior Honors Theses

Machine learning is providing a way to glean never before known insights from the data that gets recorded every day. This paper examines the application of machine learning to the novel field of Daily Fantasy Basketball. The particularities of the fantasy basketball ruleset and playstyle are discussed, and then the results of a data science case study are reviewed. The data set consists of player performance statistics as well as Fantasy Points, implied team total, DvP, and player status. The end goal is to evaluate how accurately the computer can predict a player’s fantasy performance based off a chosen feature …


Enrollment And Assessment Of A First-Year College Class Social Network For A Controlled Trial Of The Indirect Effect Of A Brief Motivational Intervention, Nancy P. Barnett, Melissa A. Clark, Shannon R. Kenney, Graham Diguiseppi, Matthew K. Meisel, Sara Balestrieri, Miles Q. Ott, John Light Jan 2019

Enrollment And Assessment Of A First-Year College Class Social Network For A Controlled Trial Of The Indirect Effect Of A Brief Motivational Intervention, Nancy P. Barnett, Melissa A. Clark, Shannon R. Kenney, Graham Diguiseppi, Matthew K. Meisel, Sara Balestrieri, Miles Q. Ott, John Light

Statistical and Data Sciences: Faculty Publications

Heavy drinking and its consequences among college students represent a serious public health problem, and peer social networks are a robust predictor of drinking-related risk behaviors. In a recent trial, we administered a Brief Motivational Intervention (BMI) to a small number of first-year college students to assess the indirect effects of the intervention on peers not receiving the intervention. Objectives: To present the research design, describe the methods used to successfully enroll a high proportion of a first-year college class network, and document participant characteristics. Methods: Prior to study enrollment, we consulted with a student advisory group and campus stakeholders …


Building Recommendation Systems, Orion Davis Jan 2019

Building Recommendation Systems, Orion Davis

Williams Honors College, Honors Research Projects

Recommendation systems are pieces of software that suggest new items to a user. There are many moving parts to these systems including data, the actual recommendation model, processing data and finally displaying data. This project explores the role each part plays in the overall system and how to develop a recommendation system for beer from scratch. This project highlights the algorithm behind the recommendations and a user facing Android application.


Absorption Calculator: A Cross-Platform Application For Portable Data Analysis, Annmarie Kolbl Jan 2019

Absorption Calculator: A Cross-Platform Application For Portable Data Analysis, Annmarie Kolbl

Williams Honors College, Honors Research Projects

Traditional spectrometers are expensive and non-portable, making them inaccessible to the public. This application will be used in conjunction with spectrometer hardware developed by Erie Open Systems. The hardware itself is 3D printed and, in addition to being portable, enables data to be collected easily. The purpose of this project is to create a cross-platform application capable of reading the output from the spectrometer hardware, calculating the absorbance levels of the sample against the control, and recording the data in tables stored on the cloud. The end result will be an application that runs on iOS and Android, and is …


Queue: A Mobile Application For Collaborative Music Playlists, Vlad Mirea Jan 2019

Queue: A Mobile Application For Collaborative Music Playlists, Vlad Mirea

Williams Honors College, Honors Research Projects

This paper focuses on the design and development of the mobile application “Queue”. Queue is an app for creating music playlists that anyone can add songs to while a host controls playback. The app connects to music streaming services such as Spotify to allow users access to their favorite songs while providing functionality not found in those services.


Hand Widget Project: Creating A Controllable Interface For Use With Motion Capture Gloves, Owen Seidler Jan 2019

Hand Widget Project: Creating A Controllable Interface For Use With Motion Capture Gloves, Owen Seidler

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.


Python If Statements, Natalia Novak Jan 2019

Python If Statements, Natalia Novak

Open Educational Resources

Python If-else branches, equality and relational operators, and some additional topics: Boolean operators and expressions, membership and identity operators.

Prior knowledge of variables, assignments, and expressions is recommended.

For CS0 students. Part of the CUNY CS04All project.


Mobile Application: Peril, Michael Prough Jan 2019

Mobile Application: Peril, Michael Prough

Williams Honors College, Honors Research Projects

In today’s world, phones and computers are widely used for various purposes, whether it would be using social media or using it for work. As they have become more popular, these devices have improved and continue to evolve, and as such, they have a wider range of uses. One such popular use of these devices is for entertainment, which includes watching content online or playing video games. With the rise of entertainment applications, I decided that I should learn how to make these applications. I ultimately decided on creating a video game for android systems which incorporated features from platformer …


Python List, Natalia Novak Jan 2019

Python List, Natalia Novak

Open Educational Resources

A brief introduction to Python list.

No loops, no decision structures.

For CS0 students. Part of the CUNY CS04All project.


Python String, Natalia Novak Jan 2019

Python String, Natalia Novak

Open Educational Resources

An introduction to Python strings and string formatting.

Proposed lecture slides are supplied with in-class activity, homework assignment, and assessment.

No loops, no decision structures.

For CS0 students.

Part of the CUNY CS04All project.


Python Working With Files, Natalia Novak Jan 2019

Python Working With Files, Natalia Novak

Open Educational Resources

This is an introduction to work with files in Python.

Prior knowledge of variables, assignments, expressions, input-output, lists, conditionals, and loops is recommended.

For CS0 students. Part of the CUNY CS04All project.


Python Functions, Natalia Novak Jan 2019

Python Functions, Natalia Novak

Open Educational Resources

An introduction to functions in Python.

Prior knowledge of variables, assignments, expressions, input-output, lists, conditionals, and loops is recommended.

For CS0 students. Part of the CUNY CS04All project.


Python Dictionary, Natalia Novak Jan 2019

Python Dictionary, Natalia Novak

Open Educational Resources

This is an introduction Python dictionary, using Python 3.

Prior knowledge of input/output in Python, and Python list is recommended.

For CS0 students. Part of the CUNY CS04All project.


Designing Pre-Test Questions As Phone Notifications: Studying The Effects Of A Mobile Learning Intervention, Ingrid Yvonne Herras, Don Romielito N. Abanes, Nico B. Del Rosario, Jonathan D.L Casano Jan 2019

Designing Pre-Test Questions As Phone Notifications: Studying The Effects Of A Mobile Learning Intervention, Ingrid Yvonne Herras, Don Romielito N. Abanes, Nico B. Del Rosario, Jonathan D.L Casano

Department of Information Systems & Computer Science Faculty Publications

Mobile devices are increasingly becoming more pervasive and emerging as part of our daily life, particularly with university students. From these devices developed in tandem with face-to-face class interaction it has opened new possibilities for ubiquitous learning. We present out work on designing a smart-phone Mobile Learning application that streamlines pre-test questions into a “set it then forget it” input system where students can answer quiz items as slide-down notifications within the day prior to a scheduled lecture. Teachers using the application are afforded a web application to create pre-tests in advance and review class scores. The study was conducted …


Indirect Relatedness, Evaluation, And Visualization For Literature Based Discovery, Sam Henry Jan 2019

Indirect Relatedness, Evaluation, And Visualization For Literature Based Discovery, Sam Henry

Theses and Dissertations

The exponential growth of scientific literature is creating an increased need for systems to process and assimilate knowledge contained within text. Literature Based Discovery (LBD) is a well established field that seeks to synthesize new knowledge from existing literature, but it has remained primarily in the theoretical realm rather than in real-world application. This lack of real-world adoption is due in part to the difficulty of LBD, but also due to several solvable problems present in LBD today. Of these problems, the ones in most critical need of improvement are: (1) the over-generation of knowledge by LBD systems, (2) a …


A Critical Review Of Current Approaches And Practices In Computing Ethics Education, Sophia Farquhar Jan 2019

A Critical Review Of Current Approaches And Practices In Computing Ethics Education, Sophia Farquhar

Dissertations, Master's Theses and Master's Reports

Recent scandals caused by the results of negligent, malicious, or shortsighted software development practices highlight the need for software developers to consider the ethical implications of their work. Computing ethics has historically been a marginalized area within computing disciplines, so educators in these disciplines do not have a common background for teaching the topic. Computing ethics education, although often a required part of coursework, can vary widely in the method of implementation from university to university.

In this report I summarize the insights I gained from interviewing four educators from three different institutions on their pedagogical approaches to computing ethics. …