Digital Commons Network^™

Efficient Interface Enabled By Nano-Hydroxyapatite@Porous Carbon For Lithium-Sulfur Batteries, Jia-Yu Wang, Xue-Feng Tong, Qi-Fan Peng, Yue-Peng Guan, Wei-Kun Wang, An-Bang Wang, Nai-Qiang Liu, Ya-Qin Huang

Journal of Electrochemistry

The dissolution and “shuttle effect” of lithium polysulfides (LiPSs) hinder the application of lithium-sulfur (Li-S) batteries. To solve those problems, inspired by natural materials, a nano-hydroxyapatite@porous carbon derived from chicken cartilage (nano-HA@CCPC) was fabricated by employing a simple pre-carbonization and carbonization method, and applied in Li-S batteries. The nano-HA@CCPC would provide a reactive interface that allows efficient LiPSs reduction. With a strong affinity for LiPSs and an excellent electronic conductive path for converting LiPSs, the shuttle effect of LiPSs was confined and the redox kinetics of LiPSs was substantially enhanced. Li-S batteries employing nano-HA@CCPC-modified separators exhibited long cycle life and …

Advances And Atomistic Insights Of Electrolytes For Lithium-Ion Batteries And Beyond, Tingzheng Hou, Xiang Chen, Lu Jiang, Cheng Tang

Journal of Electrochemistry

Electrolytes and the associated electrode-electrolyte interfaces are crucial for the development and application of high-capacity energy storage systems. Specifically, a variety of electrolyte properties, ranging from mechanical (compressibility, viscosity), thermal (heat conductivity and capacity), to chemical (solubility, activity, reactivity), transport, and electrochemical (interfacial and interphasial), are correlated to the performance of the resultant full energy storage device. In order to facilitate the operation of novel electrode materials, extensive experimental efforts have been devoted to improving these electrolyte properties by tuning the physical design and/or chemical composition. Meanwhile, the recent development of theoretical modeling methods is providing atomistic understandings of the …

Cocm: Co-Occurrence-Based Consistency Matching In Domain-Adaptive Segmentation, Siyu Zhu, Yingjie Tian, Fenfen Zhou, Kunlong Bai, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

This paper focuses on domain adaptation in a semantic segmentation task. Traditional methods regard the source domain and the target domain as a whole, and the image matching is determined by random seeds, leading to a low degree of consistency matching between domains and interfering with the reduction in the domain gap. Therefore, we designed a two-step, three-level cascaded domain consistency matching strategy—co-occurrence-based consistency matching (COCM)—in which the two steps are: Step 1, in which we design a matching strategy from the perspective of category existence and filter the sub-image set with the highest degree of matching from the image …

A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Lung segmentation plays an important role in computer-aided detection and diagnosis using chest radiographs (CRs). Currently, the U-Net and DeepLabv3+ convolutional neural network architectures are widely used to perform CR lung segmentation. To boost performance, ensemble methods are often used, whereby probability map outputs from several networks operating on the same input image are averaged. However, not all networks perform adequately for any specific patient image, even if the average network performance is good. To address this, we present a novel multi-network ensemble method that employs a selector network. The selector network evaluates the segmentation outputs from several networks; on …

Computer Engineering Education, Marilyn Wolf

School of Computing: Conference and Workshop Papers

Computer engineering is a rapidly evolving discipline. How should we teach it to our students?

This virtual roundtable on computer engineering education was conducted in summer 2022 over a combination of email and virtual meetings. The panel considered what topics are of importance to the computer engineering curriculum, what distinguishes computer engineering from related disciplines, and how computer engineering concepts should be taught.

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.

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.

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, …

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), …

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 …

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.

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 …

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, …

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 …

Gesture Controlled Collaborative Robot Arm And Lab Kit, Abel A. Reyes, Skylar Reinhardt, Tony Wise, Nathir Rawashdeh, Sidike Paheding

Michigan Tech Publications, Part 1

In this paper, a mechatronics system was designed and implemented to include the subjects of artificial intelligence, control algorithms, robot servo motor control, and human-machine interface (HMI). The goal was to create an inexpensive, multi-functional robotics lab kit to promote students’ interest in STEM fields including computing and mechtronics. Industrial robotic systems have become vastly popular in manufacturing and other industries, and the demand for individuals with related skills is rapidly increasing. Robots can complete jobs that are dangerous, dull, or dirty for humans to perform. Recently, more and more collaborative robotic systems have been developed and implemented in the …

Operation Of A Controllable Force-Sensing Industrial Pneumatic Parallel Gripper System, Brian Piechocki, Chelsey Spitzner, Namratha Karanam, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications, Part 1

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project was performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and application of a force-programmable and sensing pneumatic parallel gripper system. Force sensing is a critical part of many systems in modern automation systems. Applications such as prosthetics, robotic surgery, or basic manufacturing systems may rely on the ability to properly read and control forces applied to an object. This work evaluates the basic operation of the pneumatic force-sensing gripper …

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 …