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Articles 931 - 960 of 1793

Full-Text Articles in Computer Sciences

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 …


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 …


Agent-Based Modeling And Simulation Approaches In Stem Education Research, Shanna R. Simpson-Singleton, Xiangdong Che Jan 2019

Agent-Based Modeling And Simulation Approaches In Stem Education Research, Shanna R. Simpson-Singleton, Xiangdong Che

Journal of International Technology and Information Management

The development of best practices that deliver quality STEM education to all students, while minimizing achievement gaps, have been solicited by several national agencies. ABMS is a feasible approach to provide insight into global behavior based upon the interactions amongst agents and environments. In this review, we systematically surveyed several modeling and simulation approaches and discussed their applications to the evaluation of relevant theories in STEM education. It was found that ABMS is optimal to simulate STEM education hypotheses, as ABMS will sensibly present emergent theories and causation in STEM education phenomena if the model is properly validated and calibrated.


Snap Scholar: The User Experience Of Engaging With Academic Research Through A Tappable Stories Medium, Ieva Burk Jan 2019

Snap Scholar: The User Experience Of Engaging With Academic Research Through A Tappable Stories Medium, Ieva Burk

CMC Senior Theses

With the shift to learn and consume information through our mobile devices, most academic research is still only presented in long-form text. The Stanford Scholar Initiative has explored the segment of content creation and consumption of academic research through video. However, there has been another popular shift in presenting information from various social media platforms and media outlets in the past few years. Snapchat and Instagram have introduced the concept of tappable “Stories” that have gained popularity in the realm of content consumption.

To accelerate the growth of the creation of these research talks, I propose an alternative to video: …


Ifocus: A Framework For Non-Intrusive Assessment Of Student Attention Level In Classrooms, Narayanan Veliyath Jan 2019

Ifocus: A Framework For Non-Intrusive Assessment Of Student Attention Level In Classrooms, Narayanan Veliyath

College of Graduate Studies: Theses & Dissertations

The process of learning is not merely determined by what the instructor teaches, but also by how the student receives that information. An attentive student will naturally be more open to obtaining knowledge than a bored or frustrated student. In recent years, tools such as skin temperature measurements and body posture calculations have been developed for the purpose of determining a student's affect, or emotional state of mind. However, measuring eye-gaze data is particularly noteworthy in that it can collect measurements non-intrusively, while also being relatively simple to set up and use. This paper details how data obtained from such …


Browsing Via Sonification, Taylor C. Cutlip Jan 2019

Browsing Via Sonification, Taylor C. Cutlip

Graduate Theses, Dissertations, and Problem Reports (ETD)

Based on unexpected results in her previous research, Dr. Frances Van Scoy became inspired to develop a tool that allows the user to navigate spaces using auditory instead of visual cues to detect objects or anomalies in a given space in an effort to overcome the encountered obstacles. This problem report details the work of one of her grad students in exploring different open source software for developing the tool as well as research into gestures and other considerations when furthering this research into the third dimension at a future date.


Detecting And Mapping Real-Time Influenza-Like Illness Using Twitter Stream Data, Elisha D. Brunette Jan 2019

Detecting And Mapping Real-Time Influenza-Like Illness Using Twitter Stream Data, Elisha D. Brunette

EWU Masters Thesis Collection

Influenza has been identified by the World Health Organization as a global issue that could be more effectively served through an accelerated and widely-accessible public health surveillance tracking process. The ability to map and predict influenza outbreaks in a real-time heat map would be invaluable to health care systems to prepare for influenza outbreaks. In this study, the Twitter stream data is filtered to identify potential influenza-like illness (ILI) cases. Then the tracking of real-time influenza cases is further explored and analyzed through various machine-learning models. Among seven learning models developed to identify ILI tweets, the ELMo deep neural network …


We Have Always Been Virtual: Gilles Deleuze And The Computer-Generated Image, Hugh Mccabe Jan 2019

We Have Always Been Virtual: Gilles Deleuze And The Computer-Generated Image, Hugh Mccabe

Conference papers

The use of computer-generated imagery is becoming increasingly ubiquitous across many fields including media, advertising, architecture and art. This represents a fundamental shift within visual culture, as imagery can now be produced routinely by means of rendering algorithms based on spatial representations. We propose that the account of the image provided by Gilles Deleuze in his books on cinema provides a rich philosophical framework for understanding such contemporary imaging practices. By providing a Deleuzian reading of James Kajiya's 1986 rendering equation we argue that there is a tacit ontology of the image underwriting both Deleuze’s work on cinema and current …


Estimating Waterbird Abundance On Catfish Aquaculture Ponds Using An Unmanned Aerial System, Paul C. Burr, Sathishkumar Samiappan, Lee A. Hathcock, Robert J. Moorhead, Brian S. Dorr Jan 2019

Estimating Waterbird Abundance On Catfish Aquaculture Ponds Using An Unmanned Aerial System, Paul C. Burr, Sathishkumar Samiappan, Lee A. Hathcock, Robert J. Moorhead, Brian S. Dorr

Human–Wildlife Interactions

In this study, we examined the use of an unmanned aerial system (UAS) to monitor fish-eating birds on catfish (Ictalurus spp.) aquaculture facilities in Mississippi, USA. We tested 2 automated computer algorithms to identify bird species using mosaicked imagery taken from a UAS platform. One algorithm identified birds based on color alone (color segmentation), and the other algorithm used shape recognition (template matching), and the results of each algorithm were compared directly to manual counts of the same imagery. We captured digital imagery of great egrets (Ardea alba), great blue herons (A. herodias), …