http://smartech.gatech.edu/handle/1853/5988 The School of Electrical and Computer Engineering (ECE) is the largest of the nine Schools within the College of Engineering , with over 110 faculty members and over 2,300 undergraduate and graduate students. Search the Channel search http://smartech.gatech.edu/simple-search http://smartech.gatech.edu/handle/1853/24073 Title: Vee dipole antennas for use in short-pulse ground-penetrating radars <br/> <br/>Authors: Montoya, Thomas P. http://smartech.gatech.edu/handle/1853/24061 Title: Characterizing Single Ventricle Patient-Specific Anatomy Using Segmentation of MRI and 3D Reconstruction to Aid Surgical Planning <br/> <br/>Authors: Jayaprakash, Gopinath <br/> <br/>Abstract: Single ventricle congenital heart defects occur 2 per every 1000 live births in the USA. In these cases, cyanosis occurs due to the mixing of venous deoxygenated blood and oxygenated blood from the lungs. These defects are surgically treated by the total cavo-pulmonary connection (TCPC), where the superior and inferior vena cavae are connected to the pulmonary arteries routing the systemic venous return directly to the lungs. However, this Fontan repair results in high energy losses and therefore the optimization of this connection prior to the surgery could significantly improve post-operative performance. In this paper, the in-house segmentation and 3D reconstruction scheme is used in the following studies. First, 3D geometrical analysis of the TCPCs is used to determine the advantages and disadvantages of two commonly performed TCPC palliations intra-atrial and extra-cardiac configurations. Then, a surgical planning outline is proposed with segmentation of pre and post surgical Magnetic Resonance Imaging (MRI) data followed by the 3D reconstruction with emphasis on extracting surrounding vessels and structures. A pediatric surgeon performs a virtual surgery on the reconstruction of the patient s pre-Fontan anatomy prior to the actual surgery. A segmentation of the heart, aorta and surrounding vessels superimposed with the Glenn, when used with the SURGEM® tool, simulates the actual Fontan operation. This outline allows the surgeon to envision numerous scenarios of possible surgical options, and accordingly to predict the post operative procedures. The segmentation tool is improved upon to increase the accuracy and efficiency of the process and enhance the quality of the anatomical reconstructions. http://smartech.gatech.edu/handle/1853/23215 Title: System and Method for Determining Harmonic Contributions from Nonlinear Loads in Power Systems <br/> <br/>Authors: Mazumdar, Joy <br/> <br/>Abstract: The objective of this research is to introduce a neural network based solution for the problem of measuring the actual amount of harmonic current injected into a power network by an individual nonlinear load. Harmonic currents from nonlinear loads propagate through the system and cause harmonic pollution. As a result, voltage at the point of common coupling (PCC) is rarely sinusoidal. The IEEE 519 harmonic standard provides customer and utility harmonic limits and many utilities are now requiring their customers to comply with IEEE 519. Measurements of the customer’s current at the PCC are expected to determine the customer’s compliance with IEEE 519. However, results in this research show that the current measurements at the PCC are not always reliable in that determination. In such a case, it may be necessary to determine what the customer’s true current harmonic distortions would be if the PCC voltage could be a pure sinusoidal voltage. However, establishing a pure sinusoidal voltage at the PCC may not be feasible since that would mean performing utility switching to reduce the system impedance. An alternative approach is to use a neural network that is able to learn the customer’s load admittance. Then, it is possible to predict the customer’s true current harmonic distortions based on mathematically applying a pure sinusoidal voltage to the learned load admittance. The proposed method is called load modeling. Load modeling predicts the true harmonic current that can be attributed to a customer regardless of whether a resonant condition exists on the utility power system. If a corrective action is taken by the customer, another important parameter of interest is the change in the voltage distortion level at the PCC due to the corrective action of the customer. This issue is also addressed by using the dual of the load modeling method. Topologies of the neural networks used in this research include multilayer perceptron neural networks and recurrent neural networks. The theory and implementation of a new neural network topology known as an Echo State Networks is also introduced. The proposed methods are verified on a number of different power electronic test circuits as well as field data. The main advantages of the proposed methods are that only waveforms of voltages and currents are required for their operation and they are applicable to both single and three phase systems. The proposed methods can be integrated into any existing power quality instrument or can be fabricated into a commercial standalone instrument that could be installed in substations of large customer loads, or used as a hand-held clip on instrument. http://smartech.gatech.edu/handle/1853/23039 Title: Career: an integrated research, education and technology transfer proposal <br/> <br/>Authors: Zhou, G. Tong <br/> <br/>Description: Issued as final report