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RedirectToGroupHome_ - TUportal6 - TUportal6

https://tuportal5.temple.edu/

Id Name Url Category TUportal My Schools & Colleges Information Technology Services TUportal6 RedirectToGroupHome_ Hidden

Find a Database - Temple University

https://guides.temple.edu/az/databases

Case Files Collection offers the best-selling Case Files content in an interactive format. This collection features: the complete collection of basic science, clinical medicine, and post-graduate level cases from 23 Case Files series books; an interactive format; and personalized functionality to let users mark their progress through completed and unseen cases.

Topology-Aware Scheduling Framework for Microservice Applications in Cloud

https://cis.temple.edu/~wu/research/publications/Publication_files/Topology-Aware_Scheduling_Framework_for_Microservice_Applications_in_Cloud.pdf

Abstract—Loosely coupled and highly cohesived microservices running in containers are becoming the new paradigm for application development. Compared with monolithic applications, applications built on microservices architecture can be deployed and scaled independently, which promises to simplify software development and operation. However, the dramatic increase in the scale of microservices ...

1 QoS-aware Online Service Provisioning and Updating in Cost-efficient ...

https://cis.temple.edu/~wu/research/publications/Publication_files/10_bare_jrnl_compsoc.pdf

6.1 Basic Setting at runs a Linux operating system with E5-2620 CPU, NVIDIA RTX5000 GPU, 128Gb memory, and a 2Tb hard disk. We choose the Social LSTM model to predict the future trajectories of users which can achieve an average accuracy of over 70%. We used

TEMPLE UNIVERSITY

https://www.temple.edu/sites/www/files/uploads/232_1718_ENR_ADM_CampusMap.pdf

38. Mitchell and Hilarie Morgan Hall (student housing/food court) E5, F5–6 39. Newman Center (Catholic center) B1–2 40. O’Connor Plaza/Founder’s Garden D4–5

Distributed Deep Multi-Agent Reinforcement Learning for Cooperative ...

https://cis.temple.edu/~jiewu/research/publications/Publication_files/Distributed_Deep_Multi-Agent_Reinforcement_Learning_for_Cooperative_Edge_Caching_in_Internet-of-Vehicles.pdf

2 Power of background noise -95 Bm Size of requested contents [0.5, 1.5] MB 2.4GHz Intel Xeon E5-2650 processor and 256GB RAM. The main parameters are listed in Table II. For performance comparison, the following four bench-mark caching methods are introduced: