https://community.mis.temple.edu/mis5121beaver/files/2015/02/Ex-2-Order-to-Cash-Guide.pdf
SAP ERP The previous assignment dealt with the purchase-to-pay cycle. This assignment deals with the mirror image of that business cycle, the order-to-cash cycle.
https://www.fox.temple.edu/sites/fox/files/ISR-delayed-effects.pdf
Can location-based mobile promotion (LMP) trigger contemporaneous and delayed sales purchases? As mobile technologies can reach users anywhere and anytime, LMP becomes a promising new channel. We unravel the dynamic sales impact of LMP on the basis of a randomized field experiment with 22,000 mobile users sponsored by one of the largest mobile service providers in the world. Our identification ...
https://cis.temple.edu/~wu/teaching/Spring%202015/EGWY04.pdf
Abstract—In this paper we provide a theoretical foundation for the problem of network localization in which some nodes know their locations and other nodes determine their locations by measuring the distances to their neighbors. We construct grounded graphs to model network localization and apply graph rigidity theory to test the conditions for unique localizability and to construct uniquely ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Privacy-Preserving_Federated_Neural_Architecture_Search_With_Enhanced_Robustness_for_Edge_Computing.pdf
Abstract—With the development of large-scale artificial intelli-gence services, edge devices are becoming essential providers of data and computing power. However, these edge devices are not immune to malicious attacks. Federated learning (FL), while pro-tecting privacy of decentralized data through secure aggregation, struggles to trace adversaries and lacks optimization for hetero-geneity ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Reinforcement_Learning-based_Dual-Identity_Double_Auction_in_Personalized_Federated_Learning.pdf
Reinforcement Learning-based Dual-Identity Auction in Personalized Federated Juan Li, Member, IEEE, Zishang Chen, Tianzi Wu, Fellow, IEEE, Yanmin