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BSD Sockets: A Quick And Dirty Primer - Temple University

https://cis.temple.edu/~giorgio/old/cis307s96/readings/docs/sockets.html

Introduction As you delve into the mysteries of UNIX, you find more and more things that are difficult to understand immediately. One of these things, at least for most people, is the BSD socket concept. This is a short tutorial that explains what they are, how they work, and gives sample code showing how to use them. The Analogy (or: What is a socket, anyway?) The socket is the BSD method for ...

Temple Rome Counselor Fly-In

https://rome.temple.edu/alumni-partners/partners/temple-rome-counselor-fly

Temple University's Rome Campus is excited to host its fifth annual high school counselor fly-in from Wednesday, June 17 through Friday, June 19, 2026. This three-day experience will give you an inside look of Temple University, our global campuses in Rome, Philadelphia, Tokyo and Kyoto, and the programs and opportunities available to students. Tentative Agenda

Ruikai Ji - Fox School of Business

https://www.fox.temple.edu/directory/ruikai-ji

Ruikai Ji joined the PhD program in accounting at the Fox School of Business in 2021. He received a master’s degree in accounting from University of California, San Diego, and a bachelor’s degree in management from Central University of Finance and Economics in China. His current research interests include capital markets, disclosure, and the healthcare industry.

Transcription - Qualitative Data Analysis and QDA Tools - Research ...

https://guides.temple.edu/qda/transcription

Information for Temple students, researchers, and instructors interested in conducting qualitative data analysis

Chat-GPT syllabus statement guidance

https://teaching.temple.edu/sites/teaching/files/resource/pdf/Chat-GPT%20syllabus%20statement%20guidance.pdf

Sample Syllabus Statements for the Use of AI Tools in Your Course The following guidance is provided to assist you in developing coherent policies on the use of generative AI tools in your course. Please adjust the guidance to fit your particular context. Remember also to note in specific assignment descriptions where AI use is allowed or disallowed.

Publications – Temple Robotics and Artificial Intelligence Laboratory

https://sites.temple.edu/trail/publications/

Pre-Prints/Under Review Alkesh Kumar Srivastava, Jared Levin, and Philip Dames. “Energy Efficient Multi Robot Package Delivery under Capacity-Constraints via Voronoi-Constrained Networks.” [arXiv] Alkesh Kumar Srivastava, Jared Levin, Alexander Derrico, and Philip Dames. “DELIVER: A System for LLM-Guided Coordinated Multi-Robot Pickup and Delivery using Voronoi-Based Relay Planning ...

Master's Programs | Graduate School | Temple University Graduate School

https://grad.temple.edu/academics/masters-programs

Those looking to expand upon their undergraduate degree and get ahead in their career can choose from master’s degree and certificate programs at Temple’s regional campuses. Students in some programs can choose to study away at Temple’s Rome and Tokyo campuses. Temple master’s degree programs span the arts and humanities, education, business, social sciences, STEM fields (science ...

Zhanteng Xie, Pujie Xin, and Philip Dames - Sites

https://sites.temple.edu/trail/files/2021/11/XieXinDamesIROS2021.pdf

Zhanteng Xie, Pujie Xin, and Philip Dames Abstract—This paper proposes a novel neural network-based control policy to enable a mobile robot to navigate safety through environments filled with both static obstacles, such as tables and chairs, and dense crowds of pedestrians. The network architecture uses early fusion to combine a short history of lidar data with kinematic data about nearby ...

Temple Esports - The website for Temple Esports, the collegiate esports ...

https://sites.temple.edu/tuesports/

The website for Temple Esports, the collegiate esports group under Temple University located in Philadelphia, PA.

Optimizing Data-Driven Federated Learning in UAV Networks

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 ...