Other Computer Sciences Commons^™

Cs04all: List Comprehensions, Hunter R. Johnson

Open Educational Resources

List Comprehensions

This is a tutorial on list comprehensions in Python, suitable for use in an Intro or CS0 course. We also briefly mention set comprehensions and dictionary comprehensions.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/list_comprehensions?viewer=share/

This OER material was produced as a result of the CS04ALL CUNY OER project

Cs04all: Natural Language Processing Project, Hunter R. Johnson

Open Educational Resources

In this archive there are two activities/assignments suitable for use in a CS0 or Intro course which uses Python.

In the first activity, students are asked to "fill in the code" in a series of short programs that compute a similarity metric (cosine similarity) for text documents. This involves string tokenization, and frequency counting using Python string methods and datatypes.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/Proj1?viewer=share/

In the second activity (taken directly from Think Python 2e) students use a pronunciation dictionary to solve a riddle involving homophones.

https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/Dicts2?viewer=share/

This OER material was produced as a result of the CS04ALL CUNY OER project

Extending Set Functors To Generalised Metric Spaces, Adriana Balan, Alexander Kurz, Jiří Velebil

Mathematics, Physics, and Computer Science Faculty Articles and Research

For a commutative quantale V, the category V-cat can be perceived as a category of generalised metric spaces and non-expanding maps. We show that any type constructor T (formalised as an endofunctor on sets) can be extended in a canonical way to a type constructor T_V on V-cat. The proof yields methods of explicitly calculating the extension in concrete examples, which cover well-known notions such as the Pompeiu-Hausdorff metric as well as new ones.

Conceptually, this allows us to to solve the same recursive domain equation X ≅ TX in different categories (such as sets and metric spaces) and …

Comparisons Of Performance Between Quantum And Classical Machine Learning, Christopher Havenstein, Damarcus Thomas, Swami Chandrasekaran

SMU Data Science Review

In this paper, we present a performance comparison of machine learning algorithms executed on traditional and quantum computers. Quantum computing has potential of achieving incredible results for certain types of problems, and we explore if it can be applied to machine learning. First, we identified quantum machine learning algorithms with reproducible code and had classical machine learning counterparts. Then, we found relevant data sets with which we tested the comparable quantum and classical machine learning algorithm's performance. We evaluated performance with algorithm execution time and accuracy. We found that quantum variational support vector machines in some cases had higher accuracy …

A Comparative Evaluation Of Recommender Systems For Hotel Reviews, Ryan Khaleghi, Kevin Cannon, Raghuram Srinivas

SMU Data Science Review

There has been increasing growth in deployment of recommender systems across Internet sites, with various models being used. These systems have been particularly valuable for review sites, as they seek to add value to the user experience to gain market share and to create new revenue streams through deals. Hotels are a prime target for this effort, as there is a large number for most destinations and a lot of differentiation between them. In this paper, we present an evaluation of two of the most popular methods for hotel review recommender systems: collaborative filtering and matrix factorization. The accuracy of …

Nbgrader: A Tool For Creating And Grading Assignments In The Jupyter Notebook, Douglas S. Blank, Project Jupyter, David Bourgin, Alexander Brown, Matthias Bussonnier, Jonathan Frederic, Brian Granger, Thomas L. Griffiths, Jessica Hamrick, Kyle Kelley, M Pacer, Logan Page, Fernando Pérez, Benjamin Ragan-Kelley, Jordan W. Suchow, Carol Willing

Computer Science Faculty Research and Scholarship

No abstract provided.

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

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

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 …

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

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

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

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

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

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

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

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

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

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

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 …