COVID-19 and its latest omicron strains continue to cause infections across the country as well as globally. Serology (blood) and molecular tests are the two most commonly used methods for rapid COVID-19 testing. Because COVID-19 tests use different mechanisms, they vary significantly. Molecular tests measure the presence of viral SARS-CoV-2 RNA while serology tests detect the presence of antibodies triggered by the SARS-CoV-2 virus. Currently, there is no existing study on the correlation between serology and molecular tests and which COVID-19 symptoms play a key role in producing a positive test result.

Using a method that models drug and target protein interactions using natural language processing techniques, the researchers achieved up to 97% accuracy in identifying promising drug candidates. The results were published recently in the journal Briefings in Bioinformatics. The technique represents drug-protein interactions through words for each protein binding site and uses deep learning to extract the features that govern the complex interactions between the two. "With AI becoming more available, this has become something that AI can tackle," says study co-author Ozlem Garibay, an assistant professor in UCF's Department of Industrial Engineering and Management Systems. "You can try out so many variations of proteins and drug interactions and find out which are more likely to bind or not."

Boca Raton, FL – Florida Atlantic University is launching four new master's degree programs for working professionals, including an expansion of the state's first Master of Science with Major in Artificial Intelligence (AI). The FAU Board of Trustees recently approved the programs in information technology management, supply chain management and business analytics, in addition to AI. The four degree programs, already offered to full-time students, will be available online and in-person to working professionals and are expected to begin in the fall. The master's in AI degree, first announced in 2019 for full-time students, is part of an innovative program that covers AI foundations and technologies. Students will develop new skills for jobs not yet defined, allowing them to join a first-generation workforce with significant earning potential.

A first-of-its-kind study using haptic/touch sensation feedback, electromyogram (EMG) control and an innovative wearable soft robotic armband could just be a game changer for users of prosthetic hands who have long awaited advances in dexterity. Findings from the study could catalyze a paradigm shift in the way current and future artificial hands are controlled by limb-absent people. Researchers from Florida Atlantic University's College of Engineering and Computer Science in collaboration with FAU's Charles E. Schmidt College of Science investigated whether people could precisely control the grip forces applied to two different objects grasped simultaneously with a dexterous artificial hand. For the study, they also explored the role that visual feedback played in this complex multitasking model by systematically blocking visual and haptic feedback in the experimental design. In addition, they studied the potential for time saving in a simultaneous object transportation experiment compared to a one-at-a-time approach.

Persistent observations of large underwater animals are difficult to achieve without the help of electronic, multi-sensor tags. Data obtained from these sensors provide important insight into the biomechanics, activity patterns, energy expenditure, diving and mating behaviors of these animals, which are otherwise "foreign" to the scientists who study them. In particular, there has been little work done on large reef fish such as the Atlantic goliath grouper (Epinephelus itajara), whose behaviors have been poorly described despite being a common inhabitant of many of Florida's offshore reefs and wrecks. Researchers from Florida Atlantic University's Harbor Branch Oceanographic Institute and College of Engineering and Computer Science are the first to reveal detailed behavior of this grouper species, which can reach lengths of 8 feet and weigh more than 800 pounds. To accomplish this task, they developed a novel multi-sensor tag that includes a three axis accelerometer, gyroscope and magnetometer (collectively referred to as an inertial measurement unit or IMU) as well as a temperature, pressure and light sensor, a video camera and a hydrophone for monitoring underwater sound.

Each fingertip has more than 3,000 touch receptors, which largely respond to pressure. Humans rely heavily on sensation in their fingertips when manipulating an object. The lack of this sensation presents a unique challenge for individuals with upper limb amputations. While there are several high-tech, dexterous prosthetics available today--they all lack the sensation of'touch'. The absence of this sensory feedback results in objects inadvertently being dropped or crushed by a prosthetic hand.

Americans have one of the highest levels of fear in the world when it comes to technology related to robotic systems and self-driving cars. Addressing these concerns is paramount if the technology hopes to move forward. A researcher from Florida Atlantic University's College of Engineering and Computer Science has developed new technology for autonomous systems that is responsive to human emotions based on machine-learned human moods. His solution, "Adaptive Mood Control in Semi or Fully Autonomous Vehicles," has earned a very competitive utility patent from the United States Patent and Trademark Office for FAU. Adaptive Mood Control provides a convenient, pleasant, and more importantly, trustworthy experience for humans who interact with autonomous vehicles.

The Center for Connected Autonomy and Artificial Intelligence is housed in the state-of-the-art Engineering East building on the Boca Raton campus. Artificial intelligence technologies are quickly evolving and changing every aspect of industry in the United States and globally. Artificial intelligence enables autonomy by robotic mobility and control learned through examples and computational decision-making and estimation from data using past training data experience. It has the ability to process large amounts of data much faster and make predictions more accurately than humanly possible. To rapidly advance the field of artificial intelligence and autonomy, Florida Atlantic University's College of Engineering and Computer Science recently unveiled its "Center for Connected Autonomy and Artificial Intelligence" (CCA-AI), a cutting-edge center designed to accelerate the development of innovative artificial intelligence and autonomy solutions.

Dimitris A. Pados, Ph.D., principal investigator, a professor in the Department of Computer and Electrical Engineering and Computer Science, a fellow of FAU's Institute for Sensing and Embedded Network Systems Engineering (I-SENSE), the Charles E. Schmidt Eminent Scholar in Engineering and Computer Science, and director of the Center for Connected Autonomy and Artificial Intelligence. Ensuring data quality is critical for artificial intelligence (AI) machines to learn effectively and operate efficiently and safely. Researchers from Florida Atlantic University's College of Engineering and Computer Science have received a three-year, $653,393 grant from the United States Air Force Office of Scientific Research (AFOSR) for a project titled, "Data Analytics and Data Conformity Evaluation with L1-norm Principal Components." For the project, researchers will develop new theory and methods to curate training data sets for AI learning and screen real-time operational data for AI field deployment. The project team is spearheaded by Dimitris A. Pados, Ph.D., principal investigator, a professor in the Department of Computer and Electrical Engineering and Computer Science, a fellow of FAU's Institute for Sensing and Embedded Network Systems Engineering (I-SENSE), the Charles E. Schmidt Eminent Scholar in Engineering and Computer Science, and director of the Center for Connected Autonomy and Artificial Intelligence (ca-ai.fau.edu)

Researchers from Florida Atlantic University's College of Engineering and Computer Science have received a four-year, $1 million grant from the National Science Foundation for a project to make the master's degree in artificial intelligence (AI) accessible to high-achieving, low-income students. The accelerated five-year bachelor's degree in science and master's degree in AI program is designed to adapt curricular and co-curricular support to enable students to complete their degrees in AI, autonomous systems or machine learning, which are critically important areas needed to advance America's global competitiveness and national security. "Artificial intelligence is transforming every walk of life from business to healthcare and enabling us to rethink how we analyze data, integrate massive amounts of information and make informed decisions that impact society, the economy and governance," said Stella Batalama, Ph.D., dean of FAU's College of Engineering and Computer Science and a co-principal investigator of the grant. "This important grant from the National Science Foundation will allow us to recruit and train talented and diverse students who are economically disadvantaged and provide them with a unique opportunity to pursue graduate education in an exciting and burgeoning field." By preparing increased numbers of high-achieving, low-income students to become engineers in these fields, this project addresses the need for growing a more diverse STEM (science, technology, engineering and mathematics) research population.