Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Keyword
-
- Neural networks (Computer science) (2)
- Robotics (2)
- Adaptive control systems (1)
- Androids (1)
- Asynchronous circuits -- Design (1)
-
- Biomimetics (1)
- Entertainment computing (1)
- Integrated circuits (1)
- Machine learning (1)
- Memory management (Computer science) (1)
- Neural networks (Neurobiology) (1)
- Neurons -- Mathematical models (1)
- Parallel processing (Electronic computers) (1)
- Prolog (Computer program language) (1)
- Robots -- Design and construction (1)
- Robots -- Motion (1)
- Rootkits (Computer software) (1)
- Three-dimensional printing -- Applications to robotics (1)
- Virtual computer systems -- Security measures (1)
- Publication
- Publication Type
Articles 1 - 7 of 7
Full-Text Articles in Computer Engineering
Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt
Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt
Mechanical and Materials Engineering Faculty Publications and Presentations
Engineering neural networks to perform specific tasks often represents a monumental challenge in determining network architecture and parameter values. In this work, we extend our previously-developed method for tuning networks of non-spiking neurons, the “Functional subnetwork approach” (FSA), to the tuning of networks composed of spiking neurons. This extension enables the direct assembly and tuning of networks of spiking neurons and synapses based on the network’s intended function, without the use of global optimization ormachine learning. To extend the FSA, we show that the dynamics of a generalized linear integrate and fire (GLIF) neuronmodel have fundamental similarities to those of …
Flight Simulator Modeling Using Recurrent Neural Networks, Nickolas Sabatini, Andreas Natsis
Flight Simulator Modeling Using Recurrent Neural Networks, Nickolas Sabatini, Andreas Natsis
Undergraduate Research & Mentoring Program
Recurrent neural networks (RNNs) are a form of machine learning used to predict future values. This project uses RNNs tor predict future values for a flight simulator. Coded in Python using the Keras library, the model demonstrates training loss and validation loss, referring to the error when training the model.
From Inductive To Deductive Learning, Mikhail Mayers, Brian Henson
From Inductive To Deductive Learning, Mikhail Mayers, Brian Henson
Undergraduate Research & Mentoring Program
Using Machine Vision as a way to give information to Prolog. Using Prolog to solve deductive problems and analogical problems without having to manually enter all facts and information.
Applying The Principle Of Least Privilege To System Management Interrupt Handlers With The Intel Smi Transfer Monitor, Brian Delgado, Tejaswini Vibhute, Karen L. Karavanic
Applying The Principle Of Least Privilege To System Management Interrupt Handlers With The Intel Smi Transfer Monitor, Brian Delgado, Tejaswini Vibhute, Karen L. Karavanic
Computer Science Faculty Publications and Presentations
Recent years have seen a growing concern over System Management Mode (SMM) and its broad access to platform resources. The SMI Transfer Monitor (STM) is Intel’s most powerful executing CPU context. The STM is a firmware-based hypervisor that applies the principle of least privilege to powerful System Management Interrupt (SMI) handlers that control runtime firmware. These handlers have traditionally had full access to memory as well as the register state of applications and kernel code even when their functionality did not require it. The STM has been been enabled for UEFI and, most recently, coreboot firmware, adding protection against runtime …
3d-Printed Leg Design And Modification For Improved Support On A Quadruped Robot, Jasmin S. Collins
3d-Printed Leg Design And Modification For Improved Support On A Quadruped Robot, Jasmin S. Collins
Undergraduate Research & Mentoring Program
The Agile and Adaptive Robotics Lab aims to uncover the biological and physiological complexities in animal agility and adaptive control, which can be replicated through robotics and provide further applications in biology and medicine. One project within the lab focuses on understanding structure, actuation, and control through the modeling of a canine quadruped robot.
The AARL has developed a full-body quadruped robot with artificial muscles that control limb movement and a body that is built from 3D-printed parts. This specific project involved modification of these existing parts to (a) minimize deflections in the front legs, causing unwanted lateral and abduction/adduction …
Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi
Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi
Dissertations and Theses
Humanoid robots are expected to be able to communicate with expressive gestures at the same level of proficiency as humans. However, creating expressive gestures for humanoid robots is difficult and time consuming due to the high number of degrees of freedom (DOF) and the iterations needed to get the desired expressiveness.
Current robot motion editing software has varying levels of sophistication of motion editing tools ranging from basic ones that are text-only, to ones that provide graphical user interfaces (GUIs) which incorporate advanced features, such as curve editors and inverse kinematics. These tools enable users to create simple motions; but …
Facilitating Mixed Self-Timed Circuits, Alexandra R. Hanson
Facilitating Mixed Self-Timed Circuits, Alexandra R. Hanson
University Honors Theses
Designers constrain the ordering of computation events in self-timed circuits to ensure the correct behavior of the circuits. Different circuit families utilize different constraints that, when families are combined, may be more difficult to guarantee in combination without inserting delay to postpone necessary events. By analyzing established constraints of different circuit families like Click and GasP, we are able to identify the small changes necessary to either 1) avoid constraints entirely; or 2) decrease the likelihood of necessary delay insertion. Because delay insertion can be tricky for novice designers and because the likelihood of its requirement increases when mixing different …