https://sites.temple.edu/newcombe/files/2025/07/Nguyenetal.2025.JEPG_.pdf
Navigation and episodic memory are foundational cognitive processes that guide future decisions and are often linked to one another due to their behavioral and neural similarities. However, the extent and nature of their interdependence is unclear. We investigated this question using a real-world encoding experience with 8- to 13-year-old children and young adults. Participants were guided on ...
https://bulletin.temple.edu/courses/mis/
The MIS department prioritizes the professional development of its students as high as the domain specific knowledge and skills students develop in many of its classes. This zero-credit, credit/no-credit, self-directed course challenges students to complete a portfolio of professional development activities which prepare students to be valued contributors and leaders in industry after they ...
https://cis.temple.edu/~qzeng/cis3207-spring18/
Below is a schedule for this course, which will be updated as the course progresses. Students are thus required to frequently check this webpage for schedule, reading materials, and assignment updates.
https://sites.temple.edu/rtassessment/files/2018/10/MoCA-Instructions-English_7.2.pdf
Administration and Scoring Instructions The Montreal Cognitive Assessment (MoCA) was designed as a rapid screening instrument for mild cognitive dysfunction. It assesses different cognitive domains: attention and concentration, executive functions, memory, language, visuoconstructional skills, conceptual thinking, calculations, and orientation. Time to administer the MoCA is approximately 10 ...
https://cphapps.temple.edu/wiki/it/student/bootcamp
Windows 10 is available for free to all Temple University students. In order for Mac users (with the exception of the M1 Mac) to run Windows 10 on their computers, they must run a program called Boot Camp, which is also free to Temple students, or a similar program. Windows 10 is available via the OnTheHub website. Before beginning this installation, it is highly recommended that you make a ...
https://cis.temple.edu/~pwang/demos.html
The file contains three tables showing the relations among uncertainty measurements, the truth-value functions of the one-premise rules, and the truth-value functions of the two-premise rules, respectively. In each table, the input values can be modified, and the outputs of the functions change accordingly. The system parameters used in the functions can also be adjusted.
https://research.temple.edu/sites/research/files/NSF-CAREER-Overview-and-Planning-Guide.pdf
INTRODUCTION Securing funding from the National Science Foundation (NSF) is highly competitive and requires the development and submission of substantially rigorous and merited proposals. As with all NSF proposals, the key elements of successful CAREER requests is that they contain sufficiently technical descriptions of innovative science that shows promise for advancing your field(s), are ...
https://guides.temple.edu/qda/choosing
This workshop is the second of the two-part workshop on five different Qualitative Data Analysis (QDA) tools – ATLAS.ti, NVivo, Dedoose, Taguette, and QualCoder. The workshop recaps essential and distinctive features demonstrated in the Part 1 recorded workshop and answered questions about the tools. The workshop discusses considerations for choosing among the five tools and provides ...
https://cis.temple.edu/~yu/research/PPGSpotter-info24.pdf
Abstract—Free weight training (FWT) is of utmost importance for physical well-being. However, the success of FWT depends heavily on choosing the suitable workload, as improper selections can lead to suboptimal outcomes or injury. Current workload estimation approaches rely on manual recording and special-ized equipment with limited feedback. Therefore, we introduce PPGSpotter, a novel PPG ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Paper%206750%20Camera%20Ready%20Version.pdf
1 Introduction Federated learning (FL) [Koneˇcn ́y et al., 2017], a widely-used framework for distributed machine learning, is a signif-icant research focus. Most FL algorithms, such as the clas-sic FedAvg, fall into Synchronous Federated Learning (SFL). They require the server to wait for all selected clients’ lo-cal training and uploads before aggregating updates, and as-sume uniform ...