https://community.mis.temple.edu/mis2402sec004fall2025/
Department of Management Information Systems, Temple University
https://guides.temple.edu/qda/nvivo
NVivo is a commercial qualitative research tool that allows advanced coding, analysis, and visualization for qualitative data. NVivo interface changed in 2020 and the term Code is now used instead of Node, among other changes. Latest version is NVivo 15. View version compatibility and MacOS and Windows differences.
https://medicine.temple.edu/sites/medicine/files/files/research-with-epic-data-2021.pdf
Most straightforward when patients opt-in in response to posted fliers or if the investigator reaches out to his own patients when they are being seen for clinical appointment with that physician Increasing regulatory challenges as recruitment extends to other practices, or if research staff need to recruit via mail, or phone
https://cis.temple.edu/~latecki/Papers/GIFT-IEEEMM2017.pdf
Abstract—Projective analysis is an important solution in three-dimensional (3D) shape retrieval, since human visual perceptions of 3D shapes rely on various 2D observations from different viewpoints. Although multiple informative and discriminative views are utilized, most projection-based retrieval systems suffer from heavy computational cost, and thus cannot satisfy the basic requirement ...
https://cphapps.temple.edu/wiki/it/resources/students
There are several resources available for student consumption. Each page contains more information, click away! Free Boot Camp and Windows 10 Installation Laptop ...
https://cis.temple.edu/tagit/events/workshop2025/NARS_files/docs/GeneticNARSAGI25.pptx
the system’s memory; concepts, beliefs, goals, questions, etc. This level is acquired by the system’s experience, and can change during the system’s lifetime.
https://sites.temple.edu/xifanwu/files/2020/10/PhysRevLett.125.156803.pdf
We report a joint study using surface-specific sum-frequency vibrational spectroscopy and ab initio molecular dynamics simulations, respectively, on a pristine hydrophobic (sub)monolayer hexane-water interface, namely, the hexane/water interface with varied vapor pressures of hexane and different pHs in water. We show clear evidence that hexane on water revises the interfacial water structure ...
https://cis.temple.edu/~latecki/Courses/CIS601-04/Lectures/ImSeg04.ppt
Image Segmentation Segmentation divides an image into its constituent regions or objects. Segmentation of images is a difficult task in image processing. Still under research. Segmentation allows to extract objects in images. Segmentation is unsupervised learning. Model based object extraction, e.g., template matching, is supervised learning. What it is useful for After a successful segmenting ...
https://cis.temple.edu/~wu/research/publications/Publication_files/A_Personalized_Privacy_Preserving_Mechanism_for_Crowdsourced_Federated_Learning.pdf
The first challenge is how to determine the personalized privacy budget for each worker while mitigating the degree of the global model accuracy degradation incurred by injected parameter perturbations. Each worker wants to choose a smaller privacy budget to enhance its PPL as high as possible. However, the smaller privacy budget means a greater extent of parameter perturbations, which leads ...
https://cis.temple.edu/~yu/research/D3Guard-Infocom19.pdf
The percentage maintains relatively high when the frame length is shorter than 0:3s, but decreases rapidly when the frame length is longer than 0:3s. A small frame length which is shorter than 0:2s can bring high computational complexity to smartphones. Thus, we adopt 0:25-second frame length in D3-Guard.