Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Khamfroush, Hana"'
Autor:
Mahanipour, Afsaneh, Khamfroush, Hana
In certain emerging applications such as health monitoring wearable and traffic monitoring systems, Internet-of-Things (IoT) devices generate or collect a huge amount of multi-label datasets. Within these datasets, each instance is linked to a set of
Externí odkaz:
http://arxiv.org/abs/2405.00524
Autor:
Mahanipour, Afsaneh, Khamfroush, Hana
The integration of Internet of Things (IoT) applications in our daily lives has led to a surge in data traffic, posing significant security challenges. IoT applications using cloud and edge computing are at higher risk of cyberattacks because of the
Externí odkaz:
http://arxiv.org/abs/2404.19114
Autor:
Mahanipour, Afsaneh, Khamfroush, Hana
The fast development of Internet-of-Things (IoT) devices and applications has led to vast data collection, potentially containing irrelevant, noisy, or redundant features that degrade learning model performance. These collected data can be processed
Externí odkaz:
http://arxiv.org/abs/2308.07131
Autor:
Hudson, Nathaniel, Khamfroush, Hana, Baughman, Matt, Lucani, Daniel E., Chard, Kyle, Foster, Ian
Publikováno v:
In Future Generation Computer Systems August 2024 157:250-263
The COVID-19 pandemic has influenced the lives of people globally. In the past year many researchers have proposed different models and approaches to explore in what ways the spread of the disease could be mitigated. One of the models that have been
Externí odkaz:
http://arxiv.org/abs/2106.08820
Mobile edge computing pushes computationally-intensive services closer to the user to provide reduced delay due to physical proximity. This has led many to consider deploying deep learning models on the edge -- commonly known as edge intelligence (EI
Externí odkaz:
http://arxiv.org/abs/2104.15094
With the increasing demand for computationally intensive services like deep learning tasks, emerging distributed computing platforms such as edge computing (EC) systems are becoming more popular. Edge computing systems have shown promising results in
Externí odkaz:
http://arxiv.org/abs/2011.08381
Autor:
Hufbauer, Emory, Khamfroush, Hana
Twitter, like many social media and data brokering companies, makes their data available through a search API (application programming interface). In addition to filtering results by date and location, researchers can search for tweets with specific
Externí odkaz:
http://arxiv.org/abs/2006.11887
Click-through rate (CTR) prediction of advertisements on online social network platforms to optimize advertising is of much interest. Prior works build machine learning models that take a user-centric approach in terms of training -- using predominan
Externí odkaz:
http://arxiv.org/abs/1911.02061
Meeting QoS of Users in a Edge to Cloud Platform via Optimally Placing Services and Scheduling Tasks
Autor:
Turner, Matthew, Khamfroush, Hana
This paper considers the problem of service placement and task scheduling on a three-tiered edge-to-cloud platform when user requests must be met by a certain deadline. Time-sensitive applications (e.g., augmented reality, gaming, real-time video ana
Externí odkaz:
http://arxiv.org/abs/1908.04824