RNA structure prediction is a challenging problem, especially with pseudoknots. Recently, there has been a shift from the classical minimum free energy-based methods (MFE) to partition function-based ones that assemble structures based on base-pairing probabilities. Two typical examples of the latter group are the popular maximum expected accuracy (MEA) method...
Using robotics in education allows students to become familiar with multiple topics in science, technology, engineering, and mathematics (STEM). With the use of robotic educational tools in the 8th – 12th grade classrooms, such as Sphero, Anki Cozmo, and Lego Mindstorms, few devices allow students to build the robots’ electrical...
Data acquisition (DAQ) systems are a necessary component for products whose outcomes depend on collected information throughout its operation. Current systems are directed towards users utilizing custom hardware, software, and requiring its user to have high-level skills in coding and system setup; but with the increasing interest in renewable energy,...
As the sources of our electricity shift from centralized and carbon emitting, to a portfolio of distributed, clean-energy sources, the wave energy converter (WEC) has become a topic of exploration and development for providing coastal communities electric power. Part of this trend has included an effort to create open source...
Deep Learning methods have been gaining a lot of significance for various Biomedical applications for diagnosing several types of diseases. Two applications considered here are: 1) Diabetic Retinopathy Detection and 2) ECG signal Classification (or Arrhythmia Detection). Diabetic Retinopathy (DR) is a major cause of blindness in Diabetic patients, and...
How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124 participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated...
The rapid population growth in large urban cities has led to an unprecedented increase in both the number and the diversity of wireless devices and applications with varying quality of service requirements in terms of latency and data rates. LinkNYC is an example of an urban communication network infrastructure, which...
Although deep reinforcement learning agents have produced impressive results in many domains, their decision making is difficult to explain to humans. To address this problem, past work has mainly focused on explaining why an action was chosen in a given state. A different type of explanation that is useful is...
Question answering forums like Reddit have been quite effective in improving social interaction and disseminating useful information. Community members ask a variety of questions related to a subject which are answered by other community members. The answers are given ratings by other members. In this thesis we study the problem...
Heatmap regression has became one of the mainstream approaches to localize facial landmarks. As Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are becoming popular in solving computer vision tasks, extensive research has been done on these architectures. However, the loss function for heatmap regression is rarely studied. In...