https://scholarshare.temple.edu/bitstreams/2c72d2bb-ad1a-4928-ba73-60804dc3285a/download
This chapter examines how L2 listening ability has been modeled and operation-alized in the research literature, and provides a critical overview of the dominant models. It also describes how researchers have used both taxonomies of listening skills as well as data-driven approaches to creating models of listening ability. The chapter then provides a critical discussion of how the constructs ...
https://cis.temple.edu/~yanwang/publications.html
Yucheng Xie, Xiaonan Guo, Yan Wang, Jerry Cheng, and Yingying Chen. "Universal targeted adversarial attacks against mmwave-based human activity recognition." In Network Security Empowered by Artificial Intelligence, pp. 177-211. Cham: Springer Nature Switzerland, 2024. New!
https://education.temple.edu/sites/education/files/uploads/grad/DissertationHandbook%20Feb%201%20Revision.pdf
There are a number of books and articles which have been published that might be of help in completing the dissertation. Several of these are listed in the reference section. I have also created a short document that contains some words of advice about writing issues in proposals and dissertations. This is contained in Appendix A.I should mention that quite a bit of this document was taken ...
https://sites.temple.edu/ticlj/files/2025/09/17_36TempIntlCompLJ532021-2022.pdf
Orford's International Law and the Politics of History works from a cluster of prominent and influential comments on approaches to history and/of international law, to a general diagnosis of the interdisciplinary encounter.1 Some of the publications animating the book, particularly those by Ian Hunter, both critique contemporary scholarship and characterize scholarly orientations over ...
https://www.fox.temple.edu/faculty-research/institutes-centers/center-ethics-diversity-workplace-culture
Our Mission The Center for Ethics, Diversity and Workplace Culture (CEDWC) is a hub for research, dialogue and innovation within Temple University’s Fox School of Business and the School of Sport Tourism and Hospitality Management (STHM). Through a three-pronged approach that prioritizes education, research and industry engagement, CEDWC brings together leaders in industry, government and ...
https://hope.temple.edu/sites/hope/files/media/document/SOH_Implementation.pdf
INTRODUCTION An estimated 1 in 2 college students experiences food insecurity while pursuing postsecondary credentials. Food insecurity is associated with compromised academic performance and lower rates of degree attainment. Many organizations around the country are seeking ways to address this problem. For ten years, a nonprofit organization called Swipe Out Hunger has been on a mission ...
https://cis.temple.edu/tagit/presentations/Hopfield%20Networks%20is%20all%20you%20need.pdf
Classical Binary Hopfield Networks More complicated, patterns like (binary) images can be learned.
https://law.temple.edu/wp-content/uploads/Cognitive-Bias-and-Its-Impact-on-Expert-Witnesses-and-the-Court.pdf
Expert evidence provides a much needed contribution to the courts in administering justice. Understanding the way humans think and how the brain processes information offers insights to circumstances in which even expert evidence may be influenced by contextual information and cognitive bias. Cognitive science can identify such potential weaknesses and suggest practical ways to mitigate them.
https://cis-linux1.temple.edu/~jiewu/research/publications/Publication_files/ICPADS2024.pdf
Abstract—Federated Learning (FL) is an emerging privacy-preserving distributed machine learning paradigm that enables numerous clients to collaboratively train a global model without transmitting private datasets to the FL server. Unlike most existing research, this paper introduces a Data-Driven FL system in Unmanned Aerial Vehicle (UAV) networks, named DDFL, which features an innovative ...
https://cis.temple.edu/tagit/presentations/Neural-Symbolic%20Computing%20An%20Effective%20Methodology%20for%20Principled%20Integration%20of%20Machine%20Learning%20and%20Reasoning.pdf
25) Is it possible to combine the 2 approaches to AI? This has been a field of study for years – but interest has peaked recently in response to the growing need for explainable AI, as unexplainable deep learning tools enter popular use. This approach of combining Symbolic AI with artificial neural nets is called Neural-Symbolic Computing.