Many industries are incorporating drones into their daily routines as a way to automate tasks. Th... more Many industries are incorporating drones into their daily routines as a way to automate tasks. These tasks range from reconnaissance, search and rescue for disaster response operations to public safety and traffic management. One of the major benefits of drones is the ability to perform tasks and venture into areas which are typically more dangerous for a human beings. In order to take full advantage, drones must be capable to send and receive wireless communication. Communicating over the air has it's challenges. Drones can quickly fly in and out of communication range causing intermittent connectivity, connectivity issues can cause data packets to be lost or transmitted out of order, data transfer size can be limited causing more complex work around architectures for media data types. This document proposes a new solution to utilize multiple drones to intelligently execute, store, carry and forward packets of data using reinforcement learning.
Determining the optimal path by maximizing rewards based on an action state goal rewards set of a... more Determining the optimal path by maximizing rewards based on an action state goal rewards set of attributes is the core of the Markov Decision Process (MDP). It requires there exist rewards, goals, actions and state. However, what happens if you already have the optimal path, or policy and you want to determine what rewards were present which helped determine that optimal path how would that be done? This document provides a quick overview of Andre Ng and Stuart Russell publication [1] on the inverse reinforcement learning methodology.
Generative adversarial networks (GANs) are a machine learning type of algorithm which is designed... more Generative adversarial networks (GANs) are a machine learning type of algorithm which is designed to help generate content based on learning from training examples provided. GANs do this by first determining the probability distribution of data which created the training set of examples and then producing a single example from the learned distribution. In other words GANs can be used to create content similar to what it has learned. In the medical field chest x-ray images of SARS-CoV-2 virus infected patients can be detected using machine learning. Building a GAN with these same trained image can produce a new chest x-ray image infected with the SARS-CoV-2 virus. This new image can then be mutated in a way to provide more insight potential SARS-CoV-2 evolutions.
Generative adversarial networks (GANs) are a machine learning type of algorithm which is designed... more Generative adversarial networks (GANs) are a machine learning type of algorithm which is designed to help generate content based on learning from training examples provided. GANs do this by first determining the probability distribution of data which created the training set of examples and then producing a single example from the learned distribution. In other words GANs can be used to create content similar to what it has learned. In the medical field chest x-ray images of SARS-CoV-2 virus infected patients can be detected using machine learning. Building a GAN with these same trained image can produce a new chest x-ray image infected with the SARS-CoV-2 virus. This new image can then be mutated in a way to provide more insight potential SARS-CoV-2 evolutions.
The Internet of Things (IoT) is a platform of uniquely identifiable connected devices which is ch... more The Internet of Things (IoT) is a platform of uniquely identifiable connected devices which is changing healthcare in a variety of ways. There is much hype and interest in using it to advance medicine, primary care, surgery, medical insurance, and overall healthcare. Much of the interest leads to innovation and implementations which suit to help society. However, not without a warning. There is dangerous potential to cause harm to society. This paper details the benefits, harm, risks, and mitigations to quell the hype, and bring an ounce of reality and awareness to IoT in Healthcare.
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Papers by Dwight Goins