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Articles 1 - 17 of 17
Full-Text Articles in Physical Sciences and Mathematics
Data Set For An Empirical Analysis Of Search Engines’ Response To Web Search Queries Associated With The Classroom Setting, Oghenemaro Anuyah, Ashlee Milton, Michael Green, Maria Soledad Pera
Data Set For An Empirical Analysis Of Search Engines’ Response To Web Search Queries Associated With The Classroom Setting, Oghenemaro Anuyah, Ashlee Milton, Michael Green, Maria Soledad Pera
Computer Science Faculty Scripts and Data
This archive contains queries that capture information in different search contexts. The first file includes those written by children between the 3rd - 6th grade levels, while performing search tasks. We collected and archived this data between the April 2017 -- December 2018, based on Boise State University's IRB approval. We also include simulated queries we extracted from children's reviews. Additional columns in this dataset are children's grade levels, the query source, and the query type (i.e., if it is a keyword, phrase, or question query). The other files are comprised of queries that are meant to lead to the …
Python Practice Assignments For Computer Science I, Hyrum Carroll, Hillary Fleenor
Python Practice Assignments For Computer Science I, Hyrum Carroll, Hillary Fleenor
Computer Science and Information Technology Ancillary Materials
This set of practice assignments for Computer Science 1 were created under a Round Twelve Mini-Grant for Ancillary Materials Creation and Revision.
The assignments use the Python coding language and the repl.it coding platform and cover the following topics:
- Modules;
- Functions;
- Selections;
- Loops;
- Strings;
- Lists;
- Files;
- Dictionaries.
Internet Of Things (Open Course), Rebecca Rutherfoord, Susan Vandeven, Guangzhi Zheng, Hossain Shahriar, Xin Tian
Internet Of Things (Open Course), Rebecca Rutherfoord, Susan Vandeven, Guangzhi Zheng, Hossain Shahriar, Xin Tian
Computer Science and Information Technology Ancillary Materials
This open course for Internet of Things was created through a Round 13 Affordable Materials Grant.
Ethical Hacking For Effective Defense (Modules, Labs, And Lectures), Hossain Shahriar
Ethical Hacking For Effective Defense (Modules, Labs, And Lectures), Hossain Shahriar
Computer Science and Information Technology Ancillary Materials
Summer 2019 Update: Through a Round Twelve ALG Mini-Grant for Ancillary Materials Creation and Revision, five new modules have been added to this collection:
- Enumeration with Sparta
- Enumeration with Inguma
- Hacking Web Servers with Dirbuster
- Hacking Web Servers with Skipfish
- Hacking Wireless and IoT with Bluehydra
The following set of materials is used in the Textbook Transformation Grants implementation of Ethical Hacking for Effective Defense:
https://oer.galileo.usg.edu/compsci-collections/8/
Topics include:
- TCP/IP Level Attacks
- Port Scanning
- DDoS
- Footprinting and Social Engineering
- Enumeration
- Programming for Security Professionals
- Operating System Vulnerabilities
- Embedded System Security
- Hacking Web Servers
- Hacking Wireless Networks
- Cryptography
- Protecting Networks with …
Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey
Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey
Open Educational Resources
User-friendly Geographic Information Systems (GIS) is the common thread of this collection of presentations, and activities with full lesson plans. The first section of the site contains an overview of cartography, the art of creating maps, and then looks at historical mapping platforms like Hypercities and Donald Rumsey Historical Mapping Project. In the next section Google Earth Desktop Pro is introduced, with lessons and activities on the basics of GE such as pins, paths, and kml files, as well as a more complex activity on "georeferencing" an historic map over Google Earth imagery. The final section deals with ARCGIS Online …
Data Visualization Assignments For Principles Of Information Technology Management (Csu), Jennifer Pitts
Data Visualization Assignments For Principles Of Information Technology Management (Csu), Jennifer Pitts
Computer Science and Information Technology Ancillary Materials
This set of ancillary materials for Principles of Information Technology Management was created under a Round Eleven Mini-Grant for Ancillary Materials Creation and Revision. The skills covered in these lessons, using the Tableau data visualization and analysis tool, include:
- Instructor information for installing Tableau
- Dashboard creation
- Worksheet creation
- Data segmentation and analysis
- Geographic data visualization
Cs04all: Cryptography Module, Hunter R. Johnson
Cs04all: Cryptography Module, Hunter R. Johnson
Open Educational Resources
Cryptography module
This archive contains a series of lessons on cryptography suitable for use in a CS0 course. The only requirement is familiarity with Python, particularly dictionaries, lists, and file IO. It is also assumed that students know how to create stand-alone Python programs and interact with them through the terminal. Most of the work is done in Jupyter notebooks.
The material found in the notebooks is a combination of reading material, exercises, activities and assignments. Below are descriptions of each lesson or assignment and links to notebooks on Cocalc. The same files are available for batch download in this …
Cs04all: Command Line Python, Hunter R. Johnson
Cs04all: Command Line Python, Hunter R. Johnson
Open Educational Resources
Command Line Tutorial
Students are presented with information relating to stand alone Python programs, stdin, stdout, and command line arguments. This is a lab exercise. After completion students should be able to create executable Python programs which can accept input from stdin or command line arguments.
Please begin with the READ_ME file.
https://cocalc.com/share/bde99afd-76c8-493d-9608-db9019bcd346/171/stdin?viewer=share/
This OER material was produced as a result of the CS04ALL CUNY OER project
Cs04all: Machine Learning Module, Hunter R. Johnson
Cs04all: Machine Learning Module, Hunter R. Johnson
Open Educational Resources
These are materials that may be used in a CS0 course as a light introduction to machine learning.
The materials are mostly Jupyter notebooks which contain a combination of labwork and lecture notes. There are notebooks on Classification, An Introduction to Numpy, and An Introduction to Pandas.
There are also two assessments that could be assigned to students. One is an essay assignment in which students are asked to read and respond to an article on machine bias. The other is a lab-like exercise in which students use pandas and numpy to extract useful information about subway ridership in NYC. …
Cs04all: Natural Language Processing Project, Hunter R. Johnson
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
Cs04all: List Comprehensions, Hunter R. Johnson
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
Python String, Natalia Novak
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.
Integrated Database System With Spatial Information For Disaster Risk Management, Ever Enrique Castillo Osorio, Bashir Hayat, Babar Shah, Francis Chow, Ki Il Kim
Integrated Database System With Spatial Information For Disaster Risk Management, Ever Enrique Castillo Osorio, Bashir Hayat, Babar Shah, Francis Chow, Ki Il Kim
All Works
© 2019 AECE. Despite availability of various image sources for specific areas, a new disaster management system is likely to be implemented by using only one of them. Thus, its applicability and extensibility are severely limited. In addition, real-time update for the disaster area is one of the crucial functions for search and rescue activities. To meet the aforementioned requirements, in this paper, we propose a new spatial data infrastructure by defining the methodological scheme for the raster information. The proposed system has four respective layers to reduce the management cost as well as provide a flexible architecture. In each …
Contextual Word Embeddings - Trained On English Wikipedia Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Contextual Word Embeddings - Trained On English Wikipedia Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. These have been trained on real language sentences collected from the English Wikipedia. As such, they contain contextual (thematic) knowledge about words (rather than taxonomic).
Taxonomic Word Embeddings - Trained On English Wordnet Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Taxonomic Word Embeddings - Trained On English Wordnet Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. They have been trained on pseudo-sentences generated artificially from a random walk over the English WordNet taxonomy, and thus reflect taxonomic knowledge about words (rather than contextual).
English Wikipedia Corpus Chunks, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
English Wikipedia Corpus Chunks, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of language corpora. These are text files that contain samples of text collected from English Wikipedia.
Python List, Natalia Novak
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.