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Personalized Mobile Targeting with User Engagement Stages: Combining a ...

https://www.fox.temple.edu/sites/fox/files/SHMM_isre.2018.0831.pdf

Abstract. Low engagement rates and high attrition rates have been formidable challenges to mobile apps and their long-term success, especially for those whose revenues derive mainly from in-app purchases. To date, little is known about how companies can sci-entifically detect user engagement stages and optimize corresponding personalized-targeting promotion strategies to improve business ...

Pei Wang Publications - Temple University

https://cis.temple.edu/~pwang/papers.html

On the identity and methodology of AI On the Working Definition of Intelligence [Technical Report No. 94 of CRCC, 1994. The on-line version is a revision finished in 1995.] The general philosophical issues of artificial intelligence

教育博士学位论文 - sites.temple.edu

https://sites.temple.edu/nsfcareerakt/files/2019/06/140601033-%E5%8D%9A%E5%A3%AB%E6%AF%95%E4%B8%9A%E8%AE%BA%E6%96%87.pdf

4.5.4 课堂教学的支持: 技术进阶..................................................................94 第5 章新手教师的专业发展路径探究..................................................................98 5.1 课堂教学结构..................................................................................................98

The Effects of a Language and Literacy Intervention on Head Start ...

https://sites.temple.edu/texttotalk/files/2016/02/Wasik-Bond-Hindman-2006.pdf

A language and literacy intervention was implemented in 10 Head Start classrooms. Teachers were trained in specific book reading and conversation strategies. The focus of the intervention was to train teachers how to increase opportunities for language and vocabulary development in young children. At the end of the year, children in the intervention classrooms performed significantly better ...

How to Correct Your I-94 Card | International Student and Scholar ...

https://global.temple.edu/isss/students/future-students/how-correct-your-i-94-card

The feature provides a more convenient way for travelers to apply for an I-94, review their past travel history, check their I-94 expiration date and obtain proof of their electronic I-94 from their mobile device.

Cost of a Data Breach Report 2022 - Temple University

https://community.mis.temple.edu/mis5206sec951summer2023/files/2023/06/Cost-of-a-Data-Breach-Full-Report-2022.pdf

Executive summary The Cost of a Data Breach Report offers IT, risk management and security leaders a lens into factors that can increase or help mitigate the rising cost of data breaches.

ECAI 2024 73 U. Endriss et al. (Eds.) © 2024 The Authors. of the ...

https://cis.temple.edu/~latecki/Papers/JoPanECAI2024.pdf

This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).

FedHAN: A Cache-Based Semi-Asynchronous Federated Learning Framework ...

https://cis.temple.edu/~jiewu/research/publications/Publication_files/Paper%206750%20Camera%20Ready%20Version.pdf

41.04 33.72 25.32 45.16 37.89 25.05 36.02 28.16 27.63 45.87 37.98 27.76 33.02 23.46 21.63 43.94 34.49 21.94 Table 1: Prediction accuracy of FedHAN under varying levels of staleness, model heterogeneity, and Non-IID degree. its stability.

Microsoft Word - Article B Bricker.doc

https://sites.temple.edu/ticlj/files/2017/02/27.1.Bricker-TICLJ.pdf

American homicide statutes had their antecedents in early English common law.90 At common law, murder was defined as “the unlawful killing of another with malice aforethought.”91 Jurisdictions routinely executed offenders found guilty of murder92 as well as for a host of other offenses.93 Further, the scope of felonious homicide was broad ...

Young Children’s Motivational Frameworks and Math Achievement ... - Sites

https://sites.temple.edu/cognitionlearning/files/2016/10/Park-et-al-2016_JEP.pdf

All predictors were grand-mean centered. The results are reported in Table 3 (Model 2). Neither grade, 10 0.08, t 0.72, p .40, nor gender, 20 0.04, t .46, p .60, was a significant predictor of spring framework, whereas fall framework was a significant pos-itive predictor of spring framework, 30 0.53, t 9.94, p .001.