Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 5 of 5
Full-Text Articles in Engineering
Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth
Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth
Publications
The COVID-19 pandemic has forced public health experts to develop contingent policies to stem the spread of infection, including measures such as partial/complete lockdowns. The effectiveness of these policies has varied with geography, population distribution, and effectiveness in implementation. Consequently, some nations (e.g., Taiwan, Haiti) have been more successful than others (e.g., United States) in curbing the outbreak. A data-driven investigation into effective public health policies of a country would allow public health experts in other nations to decide future courses of action to control the outbreaks of disease and epidemics. We chose Spain and India to present our analysis …
Challenges And Opportunities In Near-Threshold Dnn Accelerators Around Timing Errors, Pramesh Pandey, Noel Daniel Gundi, Prabal Basu, Tahmoures Shabanian, Mitchell Craig Patrick, Koushik Chakraborty, Sanghamitra Roy
Challenges And Opportunities In Near-Threshold Dnn Accelerators Around Timing Errors, Pramesh Pandey, Noel Daniel Gundi, Prabal Basu, Tahmoures Shabanian, Mitchell Craig Patrick, Koushik Chakraborty, Sanghamitra Roy
Electrical and Computer Engineering Faculty Publications
AI evolution is accelerating and Deep Neural Network (DNN) inference accelerators are at the forefront of ad hoc architectures that are evolving to support the immense throughput required for AI computation. However, much more energy efficient design paradigms are inevitable to realize the complete potential of AI evolution and curtail energy consumption. The Near-Threshold Computing (NTC) design paradigm can serve as the best candidate for providing the required energy efficiency. However, NTC operation is plagued with ample performance and reliability concerns arising from the timing errors. In this paper, we dive deep into DNN architecture to uncover some unique challenges …
Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner
Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner
Publications and Research
Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself …
Deep Learning Towards Intelligent Vehicle Fault Diagnosis, Mohammed Al-Zeyadi, Javier Andreu-Perez, Hani Hagras, Chris Royce, Darren Smith, Piotr Rzonsowski, Ali Malik
Deep Learning Towards Intelligent Vehicle Fault Diagnosis, Mohammed Al-Zeyadi, Javier Andreu-Perez, Hani Hagras, Chris Royce, Darren Smith, Piotr Rzonsowski, Ali Malik
Conference papers
Recently, the rapid development of automotive industries has given rise to large multidimensional datasets both in the production sites and after-sale services. Fault diagnostic systems are one of the services that the automotive industries provide. As a consequence of the rapid development of cars features, traditional rule-based diagnostic systems became very limited. Therefore, more sophisticated AI approaches need to be investigated towards more efficient solutions. In this paper, we focus on utilising deep learning so as to build a diagnostic system that is able to estimate the required services in an efficient and effective way. We propose a new model, …
Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur
Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur
Publications
Humans are able to provide symbolic knowledge in structured form for potential use by an AI system in learning human-desirable concepts. In clinical settings, for instance, prediction of patient outcomes by an AI can be guided by knowledge from patient history. This history contains concepts such as treatment information, observational and drug-related information, mental health conditions, and severity of disease/disorder. Additionally, there is also often a certain graphical structure to the knowledge among the concepts, for example, ”patient symptoms cause certain tests to be taken”, which in turn affects the prescription of medication. This type of structure between human interpretable …