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Full-Text Articles in Engineering

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly Dec 2016

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly

Dissertations and Theses

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat.

An implantable cardiac …


Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi Jul 2016

Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi

Dissertations and Theses

The overall objective of this thesis is to build an integrated, inexpensive, human-sized humanoid robot from scratch that looks and behaves like a human. More specifically, my goal is to build an android robot called Marie Curie robot that can act like a human actor in the Portland Cyber Theater in the play Quantum Debate with a known script of every robot behavior. In order to achieve this goal, the humanoid robot need to has degrees of freedom (DOF) similar to human DOFs. Each part of the Curie robot was built to achieve the goal of building a complete humanoid …


Incorporating Priors For Medical Image Segmentation Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung Feb 2016

Incorporating Priors For Medical Image Segmentation Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung

Computer Science Faculty Publications and Presentations

Medical image segmentation is typically performed manually by a physician to delineate gross tumor volumes for treatment planning and diagnosis. Manual segmentation is performed by medical experts using prior knowledge of organ shapes and locations but is prone to reader subjectivity and inconsistency. Automating the process is challenging due to poor tissue contrast and ill-defined organ/tissue boundaries in medical images. This paper presents a genetic algorithm for combining representations of learned information such as known shapes, regional properties and relative position of objects into a single framework to perform automated three-dimensional segmentation. The algorithm has been tested for prostate segmentation …


3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall Jan 2016

3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall

Undergraduate Research & Mentoring Program

Physical size limitations in miniaturizing two-dimensional (2D) transistors are becoming more difficult to overcome. In order to continue increasing the processing power of electronic circuits, new design paradigms are needed. Three-dimensional (3D) architectures provide a solution to this issue and are currently being implemented via wafer stacking. However, more significant gains in terms of packing and speed can be achieved by CMOS components with truly integrated 3D cellular architectures. One of these is the Cell Matrix, a self-configurable defect- and fault-tolerant architecture, which is ideally suited for ultra large-scale integration. For this project, we worked to expand the Cell Matrix …


Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood Jan 2016

Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood

Undergraduate Research & Mentoring Program

The goal of this work is to explore applications of reservoir computing in biomolecular computation. Reservoir computing is a unique model for representing a mapping from one instance in time to a specific output. A neural network of randomly connected neurons is linked with a single output neuron or multiple output neurons. The output neurons are capable of mapping inputs to desired outputs using adaptable algorithms. This framework is investigated by using the Python programming language and object oriented design and programming. Neurons are created in programs by bundling information like input data and attributes of the network, which utilize …