Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- 'space and time'; data science; 'schools of thought'; metaphysics; ontology (1)
- 3D scaled models (1)
- ACH (Air exchanges per hour) (1)
- ArcGIS Pro (1)
- COVID-19 Pandemic (1)
-
- COVID-19 pandemic (1)
- Computational Fluid Dynamics (1)
- Covid-19 (1)
- Cyberharassment (1)
- Dark web (1)
- Deep learning (1)
- Digital Tools (1)
- Education (1)
- Educational technology (1)
- Financial sentiment (1)
- Food/Energy/Water Nexus (1)
- Game-based learning (1)
- Games (1)
- Gamification (1)
- Geosciences (1)
- Google Earth Pro (1)
- Indoor air Quality (1)
- Life Cycle Assessment (1)
- Long short term memory (1)
- Loughran-McDonald Dictionary (1)
- Machine learning (1)
- Outbreaks (1)
- Pedagogy (1)
- Remote learning (1)
- Revenge pornography (1)
- File Type
Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
African Land Mammal Ages, John Van Couvering, Eric Delson
African Land Mammal Ages, John Van Couvering, Eric Delson
Publications and Research
We define 17 African land mammal ages, or AFLMAs, covering the Cenozoic record of the Afro-arabian continent, the planet’s second largest land mass. While fossiliferous deposits are absent on the eroded plateau of the continent’s interior, almost 800 fossil genera from over 350 locations have now been identified in coastal deposits, karst caves, and in the Neogene rift valleys. Given a well-developed geochronologic framework, together with continuing revision to the fossil record—both stimulated by the story of human evolution in Africa—and also to compensate for the variation in fossil ecosystems across such great distances, the AFLMAs are biochronological units defined …
Applying The Food-Energy-Water Nexus Approach To Urban Agriculture: From Few To Fewp (Food-Energy- Water-People), Silvio Caputo, Victoria Schoen, Kathrin Spect, Baptiste Grard, Chris Blythe, Nevin Cohen, Runrid Fox-Kämper, Jason Hawes, Joshua Newell, Lidia Poniży
Applying The Food-Energy-Water Nexus Approach To Urban Agriculture: From Few To Fewp (Food-Energy- Water-People), Silvio Caputo, Victoria Schoen, Kathrin Spect, Baptiste Grard, Chris Blythe, Nevin Cohen, Runrid Fox-Kämper, Jason Hawes, Joshua Newell, Lidia Poniży
Publications and Research
Many studies examine the correlation between the use of resources such as water, energy and land, and the production of food. These nexus studies focus predominantly on large scale systems, often considering the social dimensions only in terms of access to resources and participation in the decision- making process, rather than individual attitudes and behaviours with respect to resource use. Such a concept of the nexus is relevant to urban agriculture (UA), but it requires customisation to the particular characteristics of growing food in cities, which is practiced mainly at a small scale and produces not only food but also …
Understanding Of Aerosol Transmission Of Covid 19 In Indoor Environments, Adama Barro, Cathal O'Toole, Jacob S. Lopez, Matthew Quinones, Sherene Moore
Understanding Of Aerosol Transmission Of Covid 19 In Indoor Environments, Adama Barro, Cathal O'Toole, Jacob S. Lopez, Matthew Quinones, Sherene Moore
Publications and Research
Our reason for discussing severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) or 2019 novel corona virus (Covid-19), is to understand its aerosol transmission characteristics in indoor spaces and to mitigate further spread of this disease by designing a new HVAC system. The problem that we are tackling is the spread of covid-19 droplets through aerosol transmission by looking at potential engineering solutions to the existing HVAC systems. The purpose is to eradicate the spread of the COVID-19 by testing indoor spaces in an effort to understand the effectiveness of ventilation controls. We believe that scientists and engineers have not …
Integrating Digital Tools In Remote Learning To Enhance The Delivery Methods Of Technical Content In Undergraduate Geosciences, Ruslana Baker, Malek Shami, Nazrul I. Khandaker, Stanley Schleifer
Integrating Digital Tools In Remote Learning To Enhance The Delivery Methods Of Technical Content In Undergraduate Geosciences, Ruslana Baker, Malek Shami, Nazrul I. Khandaker, Stanley Schleifer
Publications and Research
The global transition to remote learning due to the COVID-19 pandemic was an extremely difficult task for both students and faculty in geological sciences. Technical courses, such as Structural Geology, Mineralogy, Petrology, and Invertebrate Paleontology, that require in-person lectures and laboratory sessions involving various rocks and mineral samples, fossils, maps, and models, were a major concern at the start. The challenge of delivering the technical content via Microsoft Teams, Skype, Webex, Blackboard Collaborate Ultra, Zoom, and other internet based platforms was not only a burden for the faculty to carry, as students were struggling to conceptualize outcrop-and-type-section-based information and link …
The Internet Never Forgets: Image-Based Sexual Abuse And The Workplace, John Schriner, Melody Lee Rood
The Internet Never Forgets: Image-Based Sexual Abuse And The Workplace, John Schriner, Melody Lee Rood
Publications and Research
Image-based sexual abuse (IBSA), commonly known as revenge pornography, is a type of cyberharassment that often results in detrimental effects to an individual's career and livelihood. Although there exists valuable research concerning cyberharassment in the workplace generally, there is little written about specifically IBSA and the workplace. This chapter examines current academic research on IBSA, the issues with defining this type of abuse, victim blaming, workplace policy, and challenges to victim-survivors' redress. The authors explore monetary motivation for websites that host revenge pornography and unpack how the dark web presents new challenges to seeking justice. Additionally, this chapter presents recommendations …
Decision Tree For Predicting The Party Of Legislators, Afsana Mimi
Decision Tree For Predicting The Party Of Legislators, Afsana Mimi
Publications and Research
The motivation of the project is to identify the legislators who voted frequently against their party in terms of their roll call votes using Office of Clerk U.S. House of Representatives Data Sets collected in 2018 and 2019. We construct a model to predict the parties of legislators based on their votes. The method we used is Decision Tree from Data Mining. Python was used to collect raw data from internet, SAS was used to clean data, and all other calculations and graphical presentations are performed using the R software.
Philosophical Perspectives, Jochen Albrecht
Philosophical Perspectives, Jochen Albrecht
Publications and Research
This entry follows in the footsteps of Anselin’s famous 1989 NCGIA working paper entitled “What is special about spatial?” (a report that is very timely again in an age when non-spatial data scientists are ignorant of the special characteristics of spatial data), where he outlines three unrelated but fundamental characteristics of spatial data. In a similar vein, I am going to discuss some philosophical perspectives that are internally unrelated to each other and could warrant individual entries in this Body of Knowledge. The first one is the notions of space and time and how they have evolved in …
Does Applying Deep Learning In Financial Sentiment Analysis Lead To Better Classification Performance?, Tao Wang, Changhe Yuan, Cuiyuan Wang
Does Applying Deep Learning In Financial Sentiment Analysis Lead To Better Classification Performance?, Tao Wang, Changhe Yuan, Cuiyuan Wang
Publications and Research
Using a unique data set from Seeking Alpha, we compare the deep learning approach with traditional machine learning approaches in classifying financial text. We apply the long short-term memory (LSTM) as the deep learning method and Naive Bayes, SVM, Logistic Regression, XGBoost as the traditional machine learning approaches. The results suggest that the LSTM model outperforms the conventional machine learning methods on all metrics. Based on the tSNE graph, the success of the LSTM model is partially explained as the high-accuracy LSTM model distinguishes between positive and negative important sentiment words while those words are chosen based on SHAP values …
Proceedings Of The Cuny Games Conference 6.0, Robert O. Duncan, Joseph Bisz, Christina Boyle, Kathleen Offenholley, Maura A. Smale, Carolyn Stallard, Deborah Sturm
Proceedings Of The Cuny Games Conference 6.0, Robert O. Duncan, Joseph Bisz, Christina Boyle, Kathleen Offenholley, Maura A. Smale, Carolyn Stallard, Deborah Sturm
Publications and Research
The CUNY Games Network is an organization dedicated to encouraging research, scholarship and teaching in the developing field of games-based learning. We connect educators from every campus and discipline at CUNY and beyond who are interested in digital and non-digital games, simulations, and other forms of interactive teaching and inquiry-based learning. These proceedings summarize the CUNY Games Conference 6.0, where scholars shared research findings at a three-day event to promote and discuss game-based pedagogy in higher education. Presenters could share findings in oral presentations, posters, demos, or play testing sessions. The conference also included workshops on how to modify existing …