Engineering Commons^™

Transition-Metal Ions In Β-Ga2O3 Crystals: Identification Of Ni Acceptors, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway, J. Jesenovec, B. L. Dutton, M. D. Mccluskey, Larry E. Halliburton

Faculty Publications

Excerpt: Transition-metal ions (Ni, Cu, and Zn) in β-Ga₂O₃ crystals form deep acceptor levels in the lower half of the bandgap. In the present study, we characterize the Ni acceptors in a Czochralski-grown crystal and find that their (0/−) level is approximately 1.40 eV above the maximum of the valence band.

Material Characterization And Comparison Of Sol-Gel Deposited And Rf Magnetron Deposited Lead Zirconate Titanate Thin Films, Katherine Lynne Miles

Mechanical Engineering ETDs

Lead zirconate titanate (PZT) has been a material of interest for sensor, actuator, and transducer applications in microelectromechanical systems (MEMS). This is due to their favorable piezoelectric, pyroelectric and ferroelectric properties. While various methods are available to deposit PZT thin films, radio frequency (RF) magnetron sputtering was selected to provide high quality PZT films with the added capability of batch processing. These sputter deposited PZT films were characterized to determine their internal film stress, Young’s modulus, composition, and structure. After characterization, the sputtered PZT samples were poled using corona poling and direct poling methods. As a means of comparison, commercially …

Rdlnn-Based Image Forgery Detection And Forged Region Detection Using Mot, Akram Hatem Saber, Mohd Ayyub Khan, Basim Galeb Mejbel

Karbala International Journal of Modern Science

Image forgery detection TEMPhas become an emerging research area due to the increasing number of forged images circulating on the internet and other social media, which leads to legal and social issues. Image forgery detection includes the classification of an image as forged or authentic and as well as localizing the forgery wifin the image. In this paper, we propose a Regression Deep Learning Neural Network (RDLNN) based image forgery detection followed by Modified Otsu Thresholding (MOT) algorithm to detect the forged region. The proposed model comprises five steps that are preprocessing, image decomposition, feature extraction, classification and block matching. …

Submillimeter-Wave Cornea Phantom Sensing Over An Extended Depth Of Field With An Axicon-Generated Bessel Beam, Mariangela Baggio, Aleksi Tamminen, Joel Lamberg, Roman Grigorev, Samu-Ville Pälli, Juha Ala-Laurinaho, Irina Nefedova, Jean-Louis Bourges, Sophie X. Deng, Elliott R. Brown, Vincent P. Wallace, Zachary D. Taylor

Electrical Engineering Faculty Publications

The feasibility of a 220 - 330 GHz zero order axicon generated Bessel beam for corneal water content was explored. Simulation and experimental data from the 25-degree cone angle hyperbolic-axicon lens illuminating metallic spherical targets demonstrate a monotonically decreasing, band integrated, backscatter intensity for increasing radius of curvature from 7 - 11 mm, when lens reflector and optical axis are aligned. Further, for radii >= 9.5 mm, maximum signal was obtained with a 1 mm transverse displacement between lens and reflector optical axes arising from spatial correlation between main lobe and out of phase side lobes. Thickness and permittivity parameter …

Development Of An Automated Platform For Sensing And Differentiating Vapor-Phase Btex Constituents, Jonathan Samuelson

USF Tampa Graduate Theses and Dissertations

Light aromatic hydrocarbons are an inevitable byproduct of fossil fuel extraction, refinement, distribution, and use. The four lightest and most prevalent of these are benzene, toluene, ethylbenzene, and xylene, which are known collectively as BTEX. In spite of their chemical similarity these species have markedly different effects on human health and substantially different concentrations are permitted by OSHA in workplaces and by the EPA in ambient air and groundwater. Real-time detection, identification, and quantification of these species is therefore of great importance wherever they see industrial use.This work represents the continuation and advancement of a line of research in which …

Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons

Faculty Publications

This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.

Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte

LSU Doctoral Dissertations

Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …

Deepdemod: Bpsk Demodulation Using Deep Learning Over Software-Defined Radio, Arhum Ahmad, Satyam Agarwal, Sam Darshi, Sumit Chakravarty

Open Access Publishing Fund Collection

In wireless communication, signal demodulation under non-ideal conditions is one of the important research topic. In this paper, a novel non-coherent binary phase shift keying demodulator based on deep neural network, namely DeepDeMod, is proposed. The proposed scheme makes use of neural network to decode the symbols from the received sampled signal. The proposed scheme is developed to demodulate signal under fading channel with additive white Gaussian noise along with hardware imperfections, such as phase and frequency offset. The time varying nature of hardware imperfections and channel poses a additional challenge in signal demodulation. In order to address this issue, …

Spam Detection Using Machine Learning And Deep Learning, Olubodunde Agboola

LSU Doctoral Dissertations

Text messages are essential these days; however, spam texts have contributed negatively to the success of this communication mode. The compromised authenticity of such messages has given rise to several security breaches. Using spam messages, malicious links have been sent to either harm the system or obtain information detrimental to the user. Spam SMS messages as well as emails have been used as media for attacks such as masquerading and smishing ( a phishing attack through text messaging), and this has threatened both the user and service providers. Therefore, given the waves of attacks, the need to identify and remove …

Sers Platform For Single Fiber Endoscopic Probes, Debsmita Biswas

LSU Doctoral Dissertations

Molecular detection techniques have huge potential in clinical environments. In addition to many other molecular detection techniques, endoscopic Raman spectroscopy has great ability in terms of minimal invasiveness and real-time spectra acquisition. However, Raman Effect is low in sensitivity, limiting the application. Surface-Enhanced Raman Scattering (SERS), addresses this limitation. SERS brings rough nano-metallic surfaces in contact with specimen molecules which enormously enhances Raman signals. This provides Raman spectroscopy with immense capabilities for diverse fields of applications.

Generally, in clinical probe applications, the spectrometer is brought near the target molecules for detection. Typically, optical fibers are used to couple spectrometers to …

A Field-Deployable Quartz Crystal Microbalance System For Gas Detection, Jongyoon Park

LSU Doctoral Dissertations

Quartz crystal microbalance (QCM) has been widely studied as a mass sensing technique in laboratory environments and has shown a wide range of industrial applications such as food quality control, various forms of chemical detection, and biomolecular recognition under gas phase as well as liquid phase media. The construction of multi-sensor arrays combined with special sensor coatings enables multiple analyte detections and discrimination of multi-analyte along with statistical analysis. Despite the great sensing capabilities of QCM and growing interest in practical applications beyond the laboratory setup, most QCM studies are still performed in laboratory settings with benchtop QCM instruments. Therefore, …

Redefining Research In Nanotechnology Simulations: A New Approach To Data Caching And Analysis, Darin Tsai, Alan Zhang, Aloysius Rebeiro

The Journal of Purdue Undergraduate Research

No abstract provided.

Ethics In Engineering Education: Is Abet Enough?, Alyssa Delouise

The Journal of Purdue Undergraduate Research

No abstract provided.

Hypoxic Incubation Chamber, Simone Lisette Helfrich, Makenzie Nicole Jones

Biomedical Engineering: Graduate Reports and Projects

This paper describes the design, manufacturing, and testing of a novel controllable hypoxic incubator with fully functional oxygen gas control and temperature control in a humid environment. On the current market, a majority of the few hypoxic incubators use pre-mixed gas that does not offer precise control over gas concentration. The objective for this project was to create a chamber that allows the user to set the O2 concentration to varying set points of % O2 while maintaining the chamber at a constant body temperature, CO2 level, humidity, and sterility. To start the project, multiple concepts were developed for the …

Hypoxic Incubation Chamber, Simone Lisette Helfrich, Makenzie Nicole Jones

Master's Theses

This paper describes the design, manufacturing, and testing of a novel controllable hypoxic incubator with fully functional oxygen gas control and temperature control in a humid environment. On the current market, a majority of the few hypoxic incubators use pre-mixed gas that does not offer precise control over gas concentration. The objective for this project was to create a chamber that allows the user to set the O2 concentration to varying set points of % O2 while maintaining the chamber at a constant body temperature, CO2 level, humidity, and sterility. To start the project, multiple concepts were developed for the …

Solid State Lighting/Led Lighting, With Reliability Analysis And Smart Sustainable Energy Solutions, Anjan N. Padmasali Dr.

Technical Collection

Reliability analysis of LED based lighting solutions used in general applications. Daily use LED luminaire performance analysis at different accelerated conditions and prediction of performance for any other conditions. System and component level reliability study and analysis. Develop LED based solutions for any specific application requirements. Currently working on developing measurements, data analysis and solutions in lines with providing smart and sustainable solution applicable to lighting and also energy usage optimizations in any system.

1. https://ieeexplore.ieee.org/document/9537294
2. https://journals.sagepub.com/doi/10.1177/1477153520976936
3. https://ieeexplore.ieee.org/document/9559924
4. https://ieeexplore.ieee.org/document/9108554
5. https://ieeexplore.ieee.org/document/8930628

Application Of Machine Learning And Cyber Security In Smart Grid, Soham Dutta Dr.

Technical Collection

Unplanned islanding of microgrids is a major hindrance in providing continuous power supply to the critical loads. The detection of these islanding instants needs to be very fast so that the distributed generators (DG) are able to take control actions in minimum time. Due to high quality data at a rapid rate, micro phasor measurement unit (μ-PMU) are becoming widely popular in distribution system and micro grids. These μ-PMUs can be leveraged for island detection. However, the working of μ-PMU is hugely dependent on communication network for data transmission which is prone to cyber-attacks. In view of the above facts, …

Energy Efficient Routing Technique In Underwater Wireless Sensor Networks, Yashwanth N Dr.

Technical Collection

Wireless sensor networks can improve the efficiency for collecting information in underwater environments. In the past, researchers collected data under the sea by the way of both sending oceanographic equipments into water and recovering it at the end of mission. The whole process often took long time so real-time services cannot be supported. Wireless sensor networks can detect events and transmit the collected data to a data center immediately. However, current terrestrial routing protocols are not suitable in the underwater sensor networks. Due to unique characteristics in the water, the transmission performance and energy of the routing protocols are inefficient. …

Multi-Terminal Smart Transformer For Data Centre Applications, Anandh N

Technical Collection

With the increasing digitalization in recent times, cloud servers and data centres have gained significant attention. Renewable energy sources (RES) and battery energy storage systems (BESS) are inherent components of green data centres. This has led to an increasing need to develop efficient power electronic solutions. A multi-terminal smart transformer (MTST) is proposed for green data centre applications. The proposed system has the capacity to provide quality power both in the form of ac and dc at various required voltage levels. Moreover, the ac and dc terminals also offer the possibility of connecting alternative power sources such as RES or …

Development Of Analytical Models For Photovoltaic Systems, Arjun M

Interdisciplinary Collection

One of the frequent circumstances in photovoltaic (PV) systems is partial shading, often characterized by multiple peaks in its characteristics. As a result, modelling and delivering peak power is strenuous. Analytical techniques are well-known effective instruments to overcome such challenges by establishing

correlations between variables with the help of non-linear implicit mathematical equations. With an aim to simplify these models, earlier research has focussed on formulating explicit equations by making assumptions/approximations, leading to less accurate results. With today’s fast processing computers, solving nonlinear equations is no longer a problem. Moreover, the application of analytical techniques has only been limited to …

Effects Of Position And Gap Orientation Of The Split Ring Resonator Structure Excited By Microstrip Transmission Line On The Transmission Characteristics, Nezi̇he Karacan, Nesli̇han Kader Bulut, Evren Ekmekçi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the effects of the position and the gap orientation of the split ring resonator (SRR) structure, which is applied as a superstrate, on transmission characteristics (i.e. S21 ) are investigated numerically and experimentally. For that purpose, the left edge of the transmission line has been designated as the reference line and the SRR structure is shifted towards both left and right for three different gap orientations. Subsequently, S21 characteristics of the SRR structure having several substrate thicknesses and several substrate dielectric constants are investigated parametrically for three different gap orientations. The results reveal that the position and …

Blockchain And Federated Learning-Based Security Solutions For Telesurgery System: A Comprehensive Review, Sachi Chaudjary, Riya Kakkar, Rajesh Gupta, Sudeep Tanwar, Smita Agrawal, Ravi Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

The advent of telemedicine with its remote surgical procedures has effectively transformed the working of healthcare professionals. The evolution of telemedicine facilitates the remote monitoring of patients that lead to the advent of telesurgery systems, i.e. one of the most critical applications in telemedicine systems. Apart from gaining popularity, the telesurgery system may encounter security and trust issues of patients? data while communicating with the surgeon for their remote treatment. Motivated by this, we have presented a comprehensive survey on secure telesurgery systems comprising healthcare, surgical robots, traditional telesurgery systems, and the role of artificial intelligence to deal with the …

Skin Lesion Segmentation By Using Object Detection Networks, Deeplab3+, And Active Contours, Fatemeh Bagheri, Mohammad Jafar Tarokh, Majid Ziaratban

Turkish Journal of Electrical Engineering and Computer Sciences

Developing an automatic system for detection, segmentation, and classification of skin lesions is very useful to aid well-timed diagnosis of skin diseases. Lesion segmentation is a crucial task for automated diagnosis of skin cancers, as it affects significantly the accuracy of the subsequent steps. Varieties in sizes and locations of lesions, and the lesions with low-contrast boundaries make this task very challenging. In this paper, a three-stage CNN-based method is presented for accurate segmentation of lesions from dermoscopic images. At the first step, normalization, approximate locations and sizes of lesions are estimated. Due to the importance of the normalization stage, …

Computationally Efficient Predictive Torque Control Strategies Without Weighting Factors, Emrah Zerdali̇, Mert Altintaş, Ali̇ Bakbak, Erkan Meşe

Turkish Journal of Electrical Engineering and Computer Sciences

Predictive torque control (PTC) is a promising control method for electric machines due to its simplicity, fast dynamics, ability to handle nonlinearities, and easy inclusion of additional control objectives. The main challenge in conventional PTC design is to determine the weighting factors in the cost function. These weighting factors are generally chosen by the trial-and-error method or metaheuristic optimization algorithms, but these methods may not apply the optimum voltage vectors according to changing operating conditions. There are also several studies on the elimination of the weighting factors. This paper proposes two weighting factorless PTC strategies with lower computational complexities than …

Utilizing Motion And Spatial Features For Sign Language Gesture Recognition Using Cascaded Cnn And Lstm Models, Hamzah Luqman, Elsayed Elalfy

Turkish Journal of Electrical Engineering and Computer Sciences

Sign language is a language produced by body parts gestures and facial expressions. The aim of an automatic sign language recognition system is to assign meaning to each sign gesture. Recently, several computer vision systems have been proposed for sign language recognition using a variety of recognition techniques, sign languages, and gesture modalities. However, one of the challenging problems involves image preprocessing, segmentation, extraction and tracking of relevant static and dynamic features related to manual and nonmanual gestures from different images in sequence. In this paper, we studied the efficiency, scalability, and computation time of three cascaded architectures of convolutional …

Mocmin: Convex Inferring Of Modular Low-Rank Contact Networks Over Covid Diffusion Data, Emre Sefer

Turkish Journal of Electrical Engineering and Computer Sciences

SEIR (which consists of susceptible, exposed, infected, and recovered states) is a common diffusion model which could model different disease propagation dynamics across various domains such as influenza and COVID diffusion. As a motivation, across these domains, observing the node states is relatively easier than observing the network edges over which the diffusion is taking place, or it may not even be possible to observe the underlying network. This paper focuses on the problem of predicting modular low-rank human contact network edges only if a SEIR diffusion dynamics spreading among the human on their contact network can be observed. Such …

Compact Dual-Band Rectangular T E10 Mode To Circular Tm01 Mode Converter For Telemetry/Telecommand Applications In Satellite Communication: Design, Equivalent Circuit Modeling, Mode Level Measurement Technique And 3d Printed Manufacturing, Esra Alkin, Ceyhan Türkmen, Mustafa Seçmen

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the design of a dual-band mode converter, which provides transition from rectangular waveguide T E10 mode to circular waveguide TM01 mode and operates simultaneously in telemetry/telecommand (TT&C) frequencies, is presented along with its equivalent circuit and a mode level measurement technique. This dual-band converter is designed to uniformly excite TT&C slot antennas used in satellite communication with symmetric circular TM01 mode. The structure can work as a transceiver due to having one common rectangular waveguide feed. As a Ku-band application, a converter giving high purity TM01 mode at circular waveguide at 11.75 GHz/TX …

Load2load: Day-Ahead Load Forecasting At Aggregated Level, Mustafa Berkay Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

A reliable and accurate short-term load forecasting (STLF) helps utilities and energy providers deal with the challenges posed by supply and demand balance, higher penetration of renewable energies and the development of electricity markets with increasingly complex pricing strategies in future smart grids. Recent advances in deep learning have been successively utilized to STLF. However, there is no certain study that evaluates the performances of different STLF methods at an aggregated level on different datasets with different numbers of daily measurements.In this study, a deep learning STLF architecture called Load2Load is proposed for day-ahead forecasting. Different forecasting methods have been …

Monte-Carlo Method Based Simulations For Photothermal Mucosa Coagulation With Accurate Depth Limits, Merve Türker Burhan, Serhat Tozburun

Turkish Journal of Electrical Engineering and Computer Sciences

The mucosa layer, the innermost layer of the gastrointestinal (GI) system, is of great importance in carcinogenesis since most cancerous tissues occur as superficial lesions. Although various treatment strategies exist, the main difficulty in eradicating lesions is unintentional damage to healthy tissues with the uncontrolled depth of treatment. This study proposes a computer modeling approach for simulating depth-resolved photothermal (laser) mucosal coagulation therapy. Computer modeling mimics the thermal dynamics of mucosal tissue to characterize the total heat energy required for successful superficial coagulation, which can be controlled by the scan rate, scan time, output power, and beam diameter of the …

Identification Of Initial Events Of Cascading Failures Using Graph Theory Methods, Mojtaba Fekri, Javad Nikoukar, Gevork Babamalek Gharehpetian

Turkish Journal of Electrical Engineering and Computer Sciences

In power systems, the unintentional outage of a grid element can lead to overload and outage of other equipment and, through a domino effect, all or a large part of a power system may collapse. The resulting events are called cascading, consecutive, or sequential failures. So far, various methods have been proposed to identify the initial events of cascading failures with different levels of accuracy and computational load. In this paper, an effective approach is employed which, by calculating the maximum flow of independent paths between generators and loads in the network graph, identifies the critical lines and transformers of …