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Articles 1 - 9 of 9
Full-Text Articles in Business
Enhanced Breast Cancer Tumor Classification Using Mobilenetv2: A Detailed Exploration On Image Intensity, Error Mitigation, And Streamlit-Driven Real-Time Deployment, Aaditya Surya, Aditya Keshary Shah, Subash Tarun Sasikumar, Jarnell Kabore
Enhanced Breast Cancer Tumor Classification Using Mobilenetv2: A Detailed Exploration On Image Intensity, Error Mitigation, And Streamlit-Driven Real-Time Deployment, Aaditya Surya, Aditya Keshary Shah, Subash Tarun Sasikumar, Jarnell Kabore
Butler Journal of Undergraduate Research
This research introduces a sophisticated transfer learning model based on Google’s MobileNetV2 for breast cancer tumor classification into normal, benign, and malignant categories, utilizing a dataset of 1576 ultrasound images (265 normal, 891 benign, 420 malignant). The model achieves an accuracy of 0.82, precision of 0.83, recall of 0.81, ROC-AUC of 0.94, PR-AUC of 0.88, and MCC of 0.74. It examines image intensity distributions and misclassification errors, offering improvements for future applications. Addressing dataset imbalances, the study ensures a generalizable model. This work, using a dataset from Baheya Hospital, Cairo, Egypt, compiled by Walid Al- Dhabyani and colleagues (2020), emphasizes …
Obat Aborsi Cytotec Asli Wa 085875427775, Nia Diana
Obat Aborsi Cytotec Asli Wa 085875427775, Nia Diana
nia diana
Cloud Trader Simulator Overview
Cloud Trader Simulator Overview
Stephen M. Watt
This video presentation complements the article "An Agent-Based Financial Market Simulator for Evaluation of Algorithmic Trading Strategies" by Rui Hu and Stephen Watt.
Natural Disasters And Early Warning Systems In Australia, Emma Papaemanuel, Katina Michael, Peter Johnston
Natural Disasters And Early Warning Systems In Australia, Emma Papaemanuel, Katina Michael, Peter Johnston
Professor Katina Michael
Australia's national emergency warning system alerts. Radio program in Greek.
Are Disaster Early Warnings Effective?, Kerri Worthington, Katina Michael, Peter Johnson, Paul Barnes
Are Disaster Early Warnings Effective?, Kerri Worthington, Katina Michael, Peter Johnson, Paul Barnes
Professor Katina Michael
Australia's summer is traditionally a time of heightened preparation for natural disasters, with cyclones and floods menacing the north and bushfires a constant threat in the south. And the prospect of more frequent, and more intense, disasters thanks to climate change has brought the need for an effective early warning system to the forefront of policy-making. Technological advances and improved telecommunication systems have raised expectations that warning of disasters will come early enough to keep people safe. But are those expectations too high? Kerri Worthington reports. Increasingly, the world's governments -- and their citizens -- rely on technology-based early warning …
Concern People Without Latest Technology Will Miss Fire Warnings, Sally Sara, Ashley Hall, Peter Johnson, Katina Michael
Concern People Without Latest Technology Will Miss Fire Warnings, Sally Sara, Ashley Hall, Peter Johnson, Katina Michael
Professor Katina Michael
But what if the website goes down in the way Victoria's Country Fire Authority website crashed as fires raged a few weeks ago? What about those people who don't own the latest technology? And what happens when the power goes out?
KATINA MICHAEL: Well there's no television, there isn't ability to access the internet potentially.
ASHLEY HALL: Professor Katina Michael is Associate Professor at the School of Information Systems and Technology at the University of Wollongong.
KATINA MICHAEL: I would suggest a long lasting powered radio because we don't want is we don't want when the lights go out, or …
Delayed Observation Planning In Partially Observable Domains, Pradeep Reddy Varakantham, Janusz Marecki
Delayed Observation Planning In Partially Observable Domains, Pradeep Reddy Varakantham, Janusz Marecki
Research Collection School Of Computing and Information Systems
Traditional models for planning under uncertainty such as Markov Decision Processes (MDPs) or Partially Observable MDPs (POMDPs) assume that the observations about the results of agent actions are instantly available to the agent. In so doing, they are no longer applicable to domains where observations are received with delays caused by temporary unavailability of information (e.g. delayed response of the market to a new product). To that end, we make the following key contributions towards solving Delayed observation POMDPs (D-POMDPs): (i) We first provide an parameterized approximate algorithm for solving D-POMDPs efficiently, with desired accuracy; and (ii) We then propose …
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Michael Stanley Smith
This is an example Windows 32bit program to estimate a Gaussian copula model with NBD margins. The margins are estimated first using MLE, and the copula second using Bayesian MCMC. The model was discussed in Danaher & Smith (2011; Marketing Science) as example 4 (section 4.2).
Panel I: Earning More By Using Less: Businesses, Efficiency, And Renewable Energy, Janet Napolitano, Jim Murren, Jon Creyts, Michael Yackira, Rhone Resch
Panel I: Earning More By Using Less: Businesses, Efficiency, And Renewable Energy, Janet Napolitano, Jim Murren, Jon Creyts, Michael Yackira, Rhone Resch
National Clean Energy Summit
Panel discussion Moderator: Randolph Townsend, Nevada State Senator