https://cis.temple.edu/~latecki/Papers/GIFT-IEEEMM2017.pdf
In summary, we call the feature in (12) Aggregated Contextual Activation (ACA). Next, we will introduce some improvements of (12) concerning its retrieval accuracy and computational ef-ficiency. 1) Improving Accuracy: Similar to diffusion process, the proposed ACA requires an accurate estimation of the context in the data manifold.
https://cis.temple.edu/~jiewu/research/publications/Publication_files/FedCPD.pdf
Despite partially mitigating historical information forgetting, this strategy’s ef-ficacy in extracting local features declines when client data exhibits substantial heterogeneity.
https://www.fox.temple.edu/sites/fox/files/SHMM_isre.2018.0831.pdf
Indeed, the structural model helps decom-pose heterogeneous treatment effects by engagement segment, which, in turns, empowers businesses to target the most ef cient users to effectively meet the fi challenge of low engagement with mobile apps.
https://cph.temple.edu/marketing/lp/MSHI
Designed for All Backgrounds – Ideal for professionals with or without prior health informatics experience. Exclusive Industry Access – Full-time students receive free Healthcare Information and Management Systems Society (HIMSS) membership.
https://cis.temple.edu/~jiewu/research/publications/Publication_files/FedHAN.pdf
Federaser: Enabling ef-ficient client-level data removal from federated learning models. In 2021 IEEE/ACM 29th International Sympo-sium on Quality of Service (IWQOS), pages 1–10, 2021.
https://www.cis.temple.edu/~jiewu/research/publications/Publication_files/INS-Time-Based%20Proxy%20Re-encryption%20Scheme%20for%20Secure%20Data%20Sharing%20in%20a%20Cloud%20Environment.pdf
If a user is identified by n attributes and his ef-fective time periods correspond to m nodes in the time tree, the GenKey algorithm requires the data owner to execute O(mn) point multiplications to generate secret keys of O(mn) length.
https://scholarshare.temple.edu/bitstreams/b1ecc345-7a7c-4776-a366-9b5585e714d6/download
London: J. Murray; 1859. Vaughan TG. IcyTree: rapid browser-based visualization for phylogenetic trees and networks. Bioinformatics. 2017;33:btx155. Kreft Ł, Botzki A, Coppens F, Vandepoele K, Van Bel M. PhyD3: a phylogenetic tree viewer with extended phyloXML support for functional genomics data visualization. Bioinformatics. 2017;33(18):2946 ...
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Human Subjects Research Training The Temple University IRB utilizes The Collaborative Institutional Training Initiative (CITI) Program to provide research ethics education to the research community. The CITI program offers both initial and refresher courses covering human subjects research. Collaborative Institutional Training Initiative (CITI) Program All key research personnel engaged in ...
https://www.fox.temple.edu/sites/fox/files/Frontiers-Machines-versus-Humans-The-Impact-of-Artificial-Intelligence-Chatbot-Disclosure-on-Customer-Purchases.pdf
Our data suggest that undisclosed chatbots are as effective as procient workers and four times more ef- fi fective than inexperienced workers in engendering customer purchases. However, the disclosure of chatbot machine identity before conversation reduces purchase rates by more than 79.7%.
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Distributed_Deep_Multi-Agent_Reinforcement_Learning_for_Cooperative_Edge_Caching_in_Internet-of-Vehicles.pdf
Therefore, these ef-forts are insuficient to cope with these grant challenges. A fundamental innovation that breaks through the bottleneck of massive content delivery in IoVs there is urgently required.