Digital Commons Network^™

Membership Application Subscription Based, Vlera Zhubi, Medina Shamolli

UBT International Conference

I

t's no secret: Units wanting from small businesses, both public and private, to large businesses, are facing new challenges in hiring and managing members and payments. The membership application is an application that provides businesses, associations, clubs and functional organizations looking to manage their members. A membership application is an online subscription-based business where people pay for regular access to exclusive content. Online memberships and courses have continued to grow as people are willing to pay for convenience, exclusivity, knowledge and community. They are structured in such a way as to meet the special needs of the members at …

Public Interest Technology – Exploring Covid-19 Health Data, Sarah Zelikovitz

Open Educational Resources

This module is part of a Introduction to Data Science course that covers the different parts of the data science process: data acquisition, cleaning, exploratory data analysis, and modeling. The COVID-19 pandemic has created much interest in public health data, as well as interest in visualization of all types of data. Public health data has a set of challenges that is unique to health data, with HIPAA laws, and real time collection of data. With COVID-19, the challenges are particularly amplified, as data collection and statistics collected are constantly changing in response to feedback from labs, hospitals, drug companies, and …

Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Security Against Data Falsification Attacks In Smart City Applications, Venkata Praveen Kumar Madhavarapu

Doctoral Dissertations

Smart city applications like smart grid, smart transportation, healthcare deal with very important data collected from IoT devices. False reporting of data consumption from device failures or by organized adversaries may have drastic consequences on the quality of operations. To deal with this, we propose a coarse grained and a fine grained anomaly based security event detection technique that uses indicators such as deviation and directional change in the time series of the proposed anomaly detection metrics to detect different attacks. We also built a trust scoring metric to filter out the malicious devices. Another challenging problem is injection of …

A Data-Based Guiding Framework For Digital Transformation, Zakaria Maamar, Saoussen Cheikhrouhou, Said Elnaffar

All Works

This paper presents a framework for guiding organizations initiate and sustain digital transformation initiatives. Digital transformation is a long-term journey that an organization embarks on when it decides to question its practices in light of management, operation, and technology challenges. The guiding framework stresses out the importance of data in any digital transformation initiative by suggesting 4 stages referred to as collection, processing, storage, and dissemination. Because digital transformation could impact different areas of an organization for instance, business processes and business models, each stage suggests techniques to expose data. 2 case studies are adopted in the paper to illustrate …