Electrical and Electronics Commons^™

Calibration To Mitigate Near-Field Antennas Effects For A Mimo Radar Imaging System, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann

Articles

A calibration method for a high-resolution hybrid MIMO turntable radar imaging system is presented. A line of small metal spheres is employed as a test pattern in the calibration process to measure the position shift caused by undesired antenna effects. The unwanted effects in the antenna near-field responses are analysed, modelled and significantly mitigated based on the symmetry and differences in the responses of the MIMO configuration.

Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

In the above article [1], Figure 2 was incorrect. Unfortunately, we mixed the color label of "CONV $\to $ BN $\to $ ReLu" and "Unpooling" in the CNN structure section of Figure 2. The color label of "CONV $\to $ BN $\to $ ReLu" should be orange while the color label of "Unpooling" should be green. Also, the word "Decoder" is misspelled. That same figure with the same error is also used for the graphic abstract. The corrected figure is given here. None of the sections in the figure is modified. The only change is in the color label of …

Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch

Electrical and Computer Engineering Faculty Publications

With the development of the Internet of Things (IoT) and the widespread use of electric vehicles (EV), vehicle-to-grid (V2G) has sparked considerable discussion as an energy-management technology. Due to the inherently high maneuverability of EVs, V2G systems must provide on-demand service for EVs. Therefore, in this work, we propose a hybrid computing architecture based on fog and cloud with applications in 5G-based V2G networks. This architecture allows the bi-directional flow of power and information between schedulable EVs and smart grids (SGs) to improve the quality of service and cost-effectiveness of energy service providers. However, it is very important to select …

Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

Rising global temperatures over the past decades is directly affecting glacier dynamics. To understand glacier fluctuations and document regional glacier-state trends, glacier-boundary detection is necessary. Debris-covered glacier (DCG) mapping, however, is notoriously difficult using conventional geospatial technology methods. Therefore, in this research for automated DCG mapping, we evaluate the utility of a convolutional neural network (CNN), which is a deep learning feed-forward neural network. The CNN inputs include Landsat satellite images, an Advanced Land Observation Satellite (ALOS) digital elevation model (DEM) and DEM-derived land-surface parameters. Our CNN based deep-learning approach named GlacierNet was designed by appropriately choosing the type, number …

Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Mitotic cell detection is one of the challenging problems in the field of computational pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic markers for breast cancer diagnosis. The clinical visual inspection on histology slides is tedious, error prone, and time consuming for the pathologist. Thus, automatic mitotic cell detection approaches are highly demanded in clinical practice. In this paper, we propose an end-to-end multi-task learning system for mitosis detection from pathological images which is named"MitosisNet". MitosisNet consist of segmentation, detection, and classification models where the segmentation, and detection models are used for mitosis reference region …

Kettlebell Ultra, Elissa Peters, Kathryn Wegman, Daniel Basch, Mason Pastorius

Williams Honors College, Honors Research Projects

This project will consist of an attachment to an average kettlebell that will track the number of repetitions that the user has performed. The device will send this data over Bluetooth to a smart phone application so the user can track their workout accurately.

Rapid Prototyping Of Nanostructures With Electron Beam Induced Processing, Samaneh Esfandiarpour

Theses and Dissertations--Electrical and Computer Engineering

Focused electron beam induced processing (FEBIP) is a nano-scale fabrication technique that allows the direct deposition of functional materials. However, it suffers from significant drawbacks, such as high cost, low speed, unavailable precursors for many materials and low purity of deposits. Liquid-phase focused electron beam induced processes (LP-FEBIP) are being investigated due to the potential benefits over the gas phase technique. In this method, deposition or etching occurs at the interface between a substrate and a bulk liquid. In this work, electron beam induced deposition of copper nanostructures from aqueous solutions of copper sulfate is demonstrated. The addition of sulfuric …

Performance Enhancement And Characterization Of An Electromagnetic Railgun, Paul M. Gilles

Master's Theses

Collision with orbital debris poses a serious threat to spacecraft and astronauts. Hypervelocity impacts resulting from collisions mean that objects with a mass less than 1g can cause mission-ending damage to spacecraft. A means of shielding spacecraft against collisions is necessary. A means of testing candidate shielding methods for their efficacy in mitigating hypervelocity impacts is therefore also necessary. Cal Poly’s Electromagnetic Railgun was designed with the goal of creating a laboratory system capable of simulating hypervelocity (≥ 3 km/s) impacts. Due to several factors, the system was not previously capable of high-velocity (≥ 1 km/s) tests. A deficient projectile …

High Frequency Ltcc Based Planar Transformer, Adithya Venkatanarayanan

Graduate Theses and Dissertations

As we move towards high power and higher frequency related technology, conventional wire-wound magnetics have their own limitations which has led path to the development of planar based magnetic materials. Nowadays more planar magnetic technology has been employed because it is easier to fabricate them. The planar magnetic is a transformer or an inductor that replaces the wire-wound transformer or inductors which generally uses copper wires. One of the main reasons why we move to planar magnetic technology is its operation at higher frequency which provides higher power density. This study explains in detail about the design and fabrication of …

Design And Analysis Of Modular Axial Flux Switched Reluctance Motor, Rochak Shiwakoti

LSU New Orleans Theses and Dissertations

This thesis presents a new modular structure of the axial flux Switched Reluctance Motor (SRM). The design consists of four stator disks with each adjacent disk rotated 30 degrees apart and four rotor disks connected to a common shaft. The proposed design aims to reduce the unwanted radial force, mitigate the torque ripple, and improve the efficiency. The modular structure distributes the radial force and torque strokes along the axial length of the motor, potentially damping the torque pulsation. In addition, the modular structure would deliver the rating power at a lower current level, reducing the overall ohmic loss. Moreover, …

Designing A Simulator For An Electrically-Pumped Organic Laser Diode, Robert Hulbert

Master's Theses

Organic semiconductors provide an alternative set of basis materials to fabricate electronic devices like PN Junctions, LEDs, and FETs. These materials have several benefits over traditional inorganic semiconductors including their mechanical flexibility, reliance on renewable resources, and inexpensive large-scale manufacturability. Despite the contemporary device implementations with organic semiconductors, a solid-state electrically-pumped organic laser diode does not exist. However, organically-based lasers do exist by utilizing the organic material strictly for optical gain. The challenge occurs when charge carriers appear in the organic material. The charge carriers must reach a concentration such that population inversion occurs producing optical gain. However, between the …

Dc-Dc Converter For Electric Vehicle, Jason Y. Zhou, Nicholas James Mah

Electrical Engineering

In this work, a DC-DC converter is designed for an electric vehicle. The DC-DC converter is designed to provide 500W with a 200-400V input and a 12-15V adjustable output. Electric vehicle sales are beginning to increase in popularity and the need for DC-DC converters to siphon power from the tractive system is not yet fully satisfied, especially for single-seater class vehicles. Additionally, improving performance in efficiency without sacrificing wide input voltage range can benefit future DC-DC converter designs. In the end, a forward active clamp DC-DC converter is designed and tested. Additionally, spreadsheet calculators, LTSpice simulations, and Matlab scripts were …

Research Of Electro-Optical Effect In Metal Halide Perovskites By Fabry-Perot Interometer Method, Hanxiang Yin

McKelvey School of Engineering Graduate Student Theses & Dissertations

Perovskites have been investigated a lot by present and reported with outstanding optoelectronic properties. However, so far there is no publications about another important property, the electro-optical (EO) effect which is related to important applications in photolithography. This thesis is mainly mean to calculate the EO constants of one kind of organic perovskite material, CH₃NH₃PbI₃, which has been reported to have good capability of forming film by spin-coating, through the way of putting the film of CH₃NH₃PbI₃ between two layers of metal mirrors to build a Fabry-Perot interferometer and …

A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …

Experimental Optical Pulse Picker For Lawrence Livermore National Lab, Alexander Thomas Wargo

Master's Theses

Proprietary.

Sensing Of Multiple Parameters With Whispering Gallery Mode Optical Fiber Micro-Resonators, Arun Kumar Mallik Dr, Vishnan Kavungal, Gerald Farrell, Yuliya Semenova

Conference Papers

Monitoring of multiple physical parameters, such as humidity, temperature, strain, concentrations of certain chemicals or gases in various environments is of great importance in many industrial applications both for minimizing adverse effects on human health as well as for maintaining production levels and quality of products. In this paper we demonstrate two different approaches to the design of multi-parametric sensors using coupled whispering gallery mode (WGM) optical fiber micro-resonators. In the first approach, a small array of micro-resonators is coupled to a single fiber taper, while in the second approach each of the micro-resonators within an array is coupled to …

Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …

Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai

Electrical and Computer Engineering Faculty Publications

To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …

Dual Graphene Patch Antenna For Ka Band Satellite Applications, Mohammed Amin Rabah, Mohammed Bekhti

International Journal of Aviation, Aeronautics, and Aerospace

Currently; grapheme offers a new opportunity to use in space technology and this is due to its amazing properties like conductivity, strength, flexibility and transparency which allows us to exploit new generation of ultra-fast nanoscale components; Since future wireless communication techniques are geared towards the use of the high frequency spectrum and many recent research prove this trend. This letter presents a proposal for design of a dual graphene-based antenna to use in new communication techniques in Ka band, where the proposed antenna can work for uplink and dowlink frequencies at same time since it has return loss less then …

Compact -300 Kv Dc Inverted Insulator Photogun With Biased Anode And Alkali-Antimonide Photocathode, C. Hernandez-Garcia, P. Adderley, B. Bullard, J. Benesch, J. Grames, J. Gubeli, F. Hannon, J. Hansknecht, J. Jordan, R. Kazimi, G. A. Krafft, M. A. Mamun, M. Poelker, M. L. Stutzman, R. Suleiman, M. Tiefenback, Y. Wang, S. Zhang, H. Baumgart, G. Palacios-Serrano, S. Wijethunga, J. Yoskowitz, C. A. Valerio Lizarraga, R. Montoya Soto, A. Canales Ramos

Electrical & Computer Engineering Faculty Publications

This contribution describes the latest milestones of a multiyear program to build and operate a compact −300  kV dc high voltage photogun with inverted insulator geometry and alkali-antimonide photocathodes. Photocathode thermal emittance measurements and quantum efficiency charge lifetime measurements at average current up to 4.5 mA are presented, as well as an innovative implementation of ion generation and tracking simulations to explain the benefits of a biased anode to repel beam line ions from the anode-cathode gap, to dramatically improve the operating lifetime of the photogun and eliminate the occurrence of micro-arc discharges.

Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation, and detection tasks. One DL technique, U-Net, has become one of the most popular for these applications. We propose a recurrent U-Net model and a recurrent residual U-Net model, which are named RU-Net and R2U-Net, respectively. The proposed models utilize the power of U-Net, residual networks, and recurrent convolutional neural networks. There are several advantages to using these proposed architectures for segmentation tasks. First, a residual unit helps when training deep …

A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun

Electrical and Computer Engineering Faculty Publications

The rapid adoption of mobile devices has dramatically changed the access to various net- working services and led to the explosion of mobile service traffic. Mobile service traffic classification has been a crucial task that attracts strong interest in mobile network management and security as well as machine learning communities for past decades. However, with more and more adoptions of encryption over mobile services, it brings a lot of challenges about mobile traffic classification. Although classical machine learning approaches can solve many issues that port and payload-based methods cannot solve, it still has some limitations, such as time-consuming, costly handcrafted …

Optimum Design Of Axial Flux Pm Machines Based On Electromagnetic 3d Fea, Narges Taran

Theses and Dissertations--Electrical and Computer Engineering

Axial flux permanent magnet (AFPM) machines have recently attracted significant attention due to several reasons, such as their specific form factor, potentially higher torque density and lower losses, feasibility of increasing the number of poles, and facilitating innovative machine structures for emerging applications. One such machine design, which has promising, high efficiency particularly at higher speeds, is of the coreless AFPM type and has been studied in the dissertation together with more conventional AFPM topologies that employ a ferromagnetic core.

A challenge in designing coreless AFPM machines is estimating the eddy current losses. This work proposes a new hybrid analytical …

Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh

Purdue Journal of Service-Learning and International Engagement

Deegan Atha, a graduating senior in electrical engineering and a future engineer, is interested in human-centered design and developing technology that helps students engage and be successful in STEM.

Courtney Balogh, a junior in mechanical engineering, is interested in human-centered design and the importance it plays in product development. Deegan and Courtney are members of the Purdue EPICS project, Learning Equations Across Platforms (LEAP). They partnered with the Indiana School for the Blind and Visually Impaired (ISBVI) to develop a braille transcription device and web application that converts braille to print in real time.

Thermal And Mechanical Energy Harvesting Using Lead Sulfide Colloidal Quantum Dots, Taher Ghomian

LSU Doctoral Dissertations

The human body is an abundant source of energy in the form of heat and mechanical movement. The ability to harvest this energy can be useful for supplying low-consumption wearable and implantable devices. Thermoelectric materials are usually used to harvest human body heat for wearable devices; however, thermoelectric generators require temperature gradient across the device to perform appropriately. Since they need to attach to the heat source to absorb the heat, temperature equalization decreases their efficiencies. Moreover, the electrostatic energy harvester, working based on the variable capacitor structure, is the most compatible candidate for harvesting low-frequency-movement of the human body. …

Experimental Evaluation Of A Krypton Propellant Arrangement In A T-100-3 Hall-Effect Thruster, Adam Patel, Javier Cortina Fernandez, Justin Chow, Osvaldo Alejandro Martin, Alexey Shashurin

The Summer Undergraduate Research Fellowship (SURF) Symposium

Stationary Hall thrusters are electric, moderate-specific impulse propulsion systems developed in Russia. These devices manipulate electric and magnetic fields to expel ionized gas (plasma) components, resulting in thrust. The success of Hall-effect engines in USSR satellite-transfer missions quickly sparked western interest in the design. Extensive government and academic study commenced shortly after the dissolution of the Soviet Union, when the technology was made available to the United States. The common SPT-100 model was the primary subject of such studies. Unfortunately, limited literature exists for rare and uncommon Hall thruster models. The T-100-3 stationary plasma thruster suffers from this gap; few …

Spice Based Compact Model For Electrical Switching Of Antiferromagnet, Xe Jin Chan, Jan Kaiser, Pramey Upadhyaya

The Summer Undergraduate Research Fellowship (SURF) Symposium

A simulation framework that can model the behavior of antiferromagnets (AFMs) is essential to building novel high-speed devices. The electrical switching of AFMs allows for high performance memory applications. With new phenomena in spintronics being discovered, there is a need for flexible and expandable models. With that in mind, we developed a model for AFMs which can be used to simulate AFM switching behavior in SPICE. This approach can be modified for adding modules, keeping pace with new developments. The proposed AFM switching model is based on the Landau-Lifshitz-Gilbert equation (LLG). LLG along with an exchange coupling module is implemented …

Hybrid Perovskite Characterization And Device Applications., Kasun Fernando

Electronic Theses and Dissertations

Hybrid perovskites are a group of materials that has shown a great impact in the field of scientific research in the past decade due to the efficiency gain within a short period of time. Hot casting is one technique that has been producing high efficient and stable solar cells. Electrical transportation of lateral device structure by such film is explored to understand basic properties and predict possible device applications using it. Under dark, memristive ability of the film was explored using various experiments. Unique uni-polar memristor ability was observed. Using the experimental results, a model is hypothesized using the concepts …

High Dynamic Range Optical Devices And Applications., Elijah Robert Jensen

Electronic Theses and Dissertations

Much of what we know about fundamental physical law and the universe derives from observations and measurements using optical methods. The passive use of the electromagnetic spectrum can be the best way of studying physical phenomenon in general with minimal disturbance of the system in the process. While for many applications ambient visible light is sufficient, light outside of the visible range may convey more information. The signals of interest are also often a small fraction of the background, and their changes occur on time scales so quickly that they are visually imperceptible. This thesis reports techniques and technologies developed …

Brushless Direct Current Motor Control For Inspired Flight, Aidan James Mccoy

Computer Science and Software Engineering

Brushless direct current motors have become a very common part of many modern electronics. Although they are more expensive and less robust than conventional brushed direct current motors, they provide large advantages in control, power output, longevity as well as efficiency. To make these motors run, they need more than just power. Each motor needs a separate motor controller that is responsible for taking in a signal for what speed/torque to run the motor at, and then managing the current flow to the motor to keep it spinning while fitting within these boundaries. Brushless direct current motors have a set …