https://cis.temple.edu/~tug29203/18spring-3329/reading/hw4a.pdf
c. Suppose that different VC numbers are permitted in each link along a VC’s path. During connection setup, after an end-to-end path is determined, describe how the links can choose their VC numbers and configure their for-warding tables in a decentralized manner, without reliance on a central node. P3. A bare-bones forwarding table in a VC network has four columns. What is the meaning of ...
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring13/Modern_intro_probability_statistics_Dekking05.pdf
The two experiments are totally coupled: one has outcome ai if and the other has outcome ai. 2.6 Now there are 10 outcomes in B (for example (0,1,0,1,0)), each probability (1 p)3p2. Hence P(B) = 10(1 p)3p2. − − 2.7 This happens if and only if the experiment fails on Monday,. . . , and is a success on Sunday. This has probability p(1 p)6 to ...
https://teaching.temple.edu/sites/teaching/files/resource/pdf/Getting_Students_to_do_Readings.pdf
Lack of “pay off” Often students don’t do reading assignments because they can achieve their goals without doing them. The course goal for the average undergraduate is “getting through,” and students are adept at identifying exactly what’s necessary to get through (with their target grade). This is especially true for undergraduates for whom the daily goal is simply survival, and ...
https://www2.law.temple.edu/lppp/the-u-s-supreme-court-can-protect-the-lgbtq-community-but-will-it/
Ellie Holzman, JD Anticipated May 2023, Law & Public Policy Scholar There are currently over 385 anti-LGBTQ bills that have been introduced at the state level across the country. Ninety of these bills would prevent transgender youth from accessing age-appropriate gender affirming care, two of which have already become law. These proposed laws also target drag performances, bathroom access, and ...
https://www.fox.temple.edu/sites/fox/files/Frontiers-Machines-versus-Humans-The-Impact-of-Artificial-Intelligence-Chatbot-Disclosure-on-Customer-Purchases.pdf
Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases Xueming Luo,aSiliang Tong,aZheng Fang,bZhe Quc
https://cis.temple.edu/~jiewu/research/publications/Publication_files/DiVE.pdf
Abstract—Ensuring stable and high-quality real-time video an-alytics for computationally constrained mobile agents is essential. However, limited computing resources and network bandwidth present significant challenges in meeting the objective of low response time and high inference accuracy. In this paper, we present DiVE, an edge-assisted video analytics system that utilizes motion vectors ...
https://sites.temple.edu/ticlj/files/2017/02/30.1.Scharre-TICLJ.pdf
Paul Scharre* Much of the debate on autonomous weapons presumes a choice between human versus autonomous decision-making over targeting and engagement decisions. In fact, in many situations, human-machine teaming in engagement decisions will not only be possible but preferable. Hybrid human-machine cognitive architectures will be able to leverage the precision and reliability of automation ...
https://scholarshare.temple.edu/bitstreams/1c1f1a6d-0f34-4234-8b39-41d9eeb397f0/download
of machine learning (ML) versus a traditional statistical model in predicting dental caries in
https://www.fox.temple.edu/sites/fox/files/documents/Cummins%20Conference%202022/XiangHuBao-main-2022-03-23.pdf
The significant progress in information technologies promotes new venues in risk sharing and risk management practices (OECD, 2017). Just as peer-to-peer (P2P) lending platforms connected un-or under-financed borrowers to lenders, emerging fintech platforms can also be leveraged to reach traditionally un-insured or under-insured customers.2 This is exemplified by Xiang Hu Bao (XHB, meaning ...
https://cis.temple.edu/tagit/presentations/Neural-Symbolic%20Computing%20An%20Effective%20Methodology%20for%20Principled%20Integration%20of%20Machine%20Learning%20and%20Reasoning.pdf
“Neural-symbolic computing aims at reconciling the dominating symbolic and connectionist paradigms of AI under a principled foundation. In neural-symbolic computing, knowledge is represented in symbolic form, whereas learning and reasoning are computed by a neural network.”