Engineering Commons^™

Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

This study performed a deep learning-based classification of chaotic systems over their phase portraits. To the best of the authors' knowledge, such classification studies over phase portraits have not been conducted in the literature. To that end, a dataset consisting of the phase portraits of the most known two chaotic systems, namely Lorenz and Chen, is generated for different values of the parameters, initial conditions, step size, and time length. Then, a classification with high accuracy is carried out employing transfer learning methods. The transfer learning methods used in the study are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet, and …

Transmission Network Planning For Realistic Egyptian Systems Via Encircling Prey Based Algorithms, Abdullah M. Shaheen, Ragab Elsehiemy, Mohammed Kharrich, Salah Kamel

Turkish Journal of Electrical Engineering and Computer Sciences

Transmission network planning problem (TNPP) is one of the pertinent issues of the planning activities in power systems. It aims to optimally pick out the routs, types, and number of the new installed lines to confront the expected future loading conditions. In this line, this study proposes a new economic model to the TNPP. The aim of the model is to find the optimal transmission routes at least investment and operating costs. Three recent algorithms called grey wolf optimization algorithm (GWOA), spotted hyena optimization algorithm (SHOA) and whale optimization algorithm (WOA) are developed to solve the TNPP. The concept of …

Basismap: Sequence-Based Similarity Search For Geomagnetic Positioning, Tevfi̇k Kadioğlu, Burcu Erkmen

Turkish Journal of Electrical Engineering and Computer Sciences

Indoor localization has become a popular topic with the development of location-based services (LBS) and indoor navigation systems. Beside these circumstances indoor positioning has been the focus of attention for researchers as the most important component of these applications. Many signals are used as distinguishable features for indoor positioning. RF-based Wi-Fi and BLE systems are the most popular ones and these have been preferred because of their high distinguishable feature. The use of geomagnetism, a natural signal found all over the world, has also been of interest to many researchers. Geomagnetic signals being distorted in the indoor area due to …

The Effects Of The Dielectric Substrate Thickness And The Loss Tangent On The Absorption Spectrum: A Comprehensive Study Considering The Resonance Type, The Ground Plane Coupling, And The Characterization Setup, Umut Köse, Evren Ekmekçi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the effects of dielectric substrate thickness and the dielectric loss tangent on the absorption spectrum are investigated parametrically in S-band. The study has been conducted on two different absorber topologies, one is closed ring resonator (CRR) and the other is composed of a split ring resonator (SRR), to observe the effects on both LC - and dipole-type resonances. The studies on the substrate thickness have been performed both numerically and experimentally, whereas the studies on the dielectric loss tangent have been performed numerically. The results agree with the literature such that the substrate thickness has significant effects …

Variational Autoencoder-Based Anomaly Detection In Time Series Data For Inventory Record Inaccuracy, Hali̇l Arğun, Sadetti̇n Emre Alpteki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Retail companies monitor inventory stock levels regularly and manage them based on forecasted sales to sustain their market position. Inventory accuracy, defined as the difference between the warehouse stock records and the actual inventory, is critical for preventing stockouts and shortages. The root causes of inventory inaccuracy are the employee or customer theft, product damage or spoilage, and wrong shipments. In this paper, we aim at detecting inaccurate stocks of one of Turkey's largest supermarket chain using the variational autoencoder (VAE), which is an unsupervised learning method. Based on the findings, we showed that VAE is able to model the …

Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler

Turkish Journal of Electrical Engineering and Computer Sciences

It is well known that classifiers trained using imbalanced datasets usually have a bias toward the majority class. In this context, classification models can present a high classification performance overall and for the majority class, even when the performance for the minority class is significantly lower. This paper presents a genetic programming (GP) model with a crossover-based oversampling technique for oversampling the imbalanced dataset for binary text classification. The aim of this study is to apply an oversampling technique to solve the imbalanced issue and improve the performance of the GP model that employed the proposed technique. The proposed technique …

A Robust Model For Spot Virtual Machine Bidding In The Cloud Market Using Information Gap Decision Theory (Igdt), Mona Naghdehforoushha, Mehdi Dehghan Takht Fooladi, Mohammed Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi

Turkish Journal of Electrical Engineering and Computer Sciences

The spot market is one of the most common cloud markets where cloud providers, such as Amazon EC2, rent their surplus computing resources at lower prices in the form of spot virtual machines (SVMs). In this market, which is often managed through an auction mechanism, users seek optimal bidding strategies for renting SVMs to minimize cost and risk. Uncertainty in the price of SVMs and their low availability/reliability is a challenging issue to bid on the user side. In this paper, we present a robust model for minimizing the cost of executing tasks by considering the uncertainty of the price …

Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically attempts to learn a mapping from the (visual) feature space to the semantic space in which the classes are represented by a list of semantically meaningful attributes. However, the fact that this mapping is learned without using instances of the test classes affects the performance of ZSL, which is known as the domain shift problem. In this study, we propose to apply the learning vector quantization (LVQ) algorithm …

An Xai Approach For Covid-19 Detection Using Transfer Learning With X-Ray Images, Salih Sarp, Ferhat Ozgur Catak, Murat Kuzlu, Umit Cali, Huseyin Kusetogullari, Yanxiao Zhao, Gungor Ates, Ozgur Guler

Engineering Technology Faculty Publications

The coronavirus disease (COVID-19) has continued to cause severe challenges during this unprecedented time, affecting every part of daily life in terms of health, economics, and social development. There is an increasing demand for chest X-ray (CXR) scans, as pneumonia is the primary and vital complication of COVID-19. CXR is widely used as a screening tool for lung-related diseases due to its simple and relatively inexpensive application. However, these scans require expert radiologists to interpret the results for clinical decisions, i.e., diagnosis, treatment, and prognosis. The digitalization of various sectors, including healthcare, has accelerated during the pandemic, with the use …

Defending Ai-Based Automatic Modulation Recognition Models Against Adversarial Attacks, Haolin Tang, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Yanxiao Zhao

Engineering Technology Faculty Publications

Automatic Modulation Recognition (AMR) is one of the critical steps in the signal processing chain of wireless networks, which can significantly improve communication performance. AMR detects the modulation scheme of the received signal without any prior information. Recently, many Artificial Intelligence (AI) based AMR methods have been proposed, inspired by the considerable progress of AI methods in various fields. On the one hand, AI-based AMR methods can outperform traditional methods in terms of accuracy and efficiency. On the other hand, they are susceptible to new types of cyberattacks, such as model poisoning or adversarial attacks. This paper explores the vulnerabilities …

Editorial: Internet Of Energy For Renewable Energy-Based Decarbonized Electrical Energy Systems, Onur Elma, Murat Kuzlu, Nasibeh Zohrabi

Engineering Technology Faculty Publications

[Introduction] This research topic aims to highlight the current state-of-the art technologies in digitalized smart grids, including renewable energy and others with the Internet of Energy (IoE) under the decarbonized electrical energy systems. These approaches will increase the overall efficiency of electrical power systems, along with emerging technologies and applications in the current system. IoE covers all digitalization processes with mobility, electronic devices, and energy network as seen in Figure 1.

Coordinating Multi-Party Vehicle Routing With Location Congestion Via Iterative Best Response, Waldy Joe, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This work is motivated by a real-world problem of coordinating B2B pickup-delivery operations to shopping malls involving multiple non-collaborative logistics service providers (LSPs) in a congested city where space is scarce. This problem can be categorized as a vehicle routing problem with pickup and delivery, time windows and location congestion with multiple LSPs (or ML-VRPLC in short), and we propose a scalable, decentralized, coordinated planning approach via iterative best response. We formulate the problem as a strategic game where each LSP is a self-interested agent but is willing to participate in a coordinated planning as long as there are sufficient …

The Wound Healing And Antibacterial Properties Of Mesenchymal Stromal Cell Extracellular Matrix Nanoparticles, Emily N. Wandling

Theses and Dissertations

Treatments for acute respiratory distress syndrome (ARDS) are still unavailable and the prevalence of the disease has only increased due to the Covid-19 pandemic. Mechanical ventilation regiments are still utilized to support declining lung function, but they also contribute to lung damage and increase the risk of bacterial infection. The anti-inflammatory and pro-regenerative abilities of mesenchymal stromal cells (MSCs) have shown to be a promising therapy for ARDS. We propose to utilize the regenerative effects of MSC secretome and the extracellular matrix (ECM) into a nanoparticle. Our mouse MSC (MMSC) ECM nanoparticles were characterized using size, zeta-potential, and mass spectrometry …

Wifi Sensing At The Edge Towards Scalable On-Device Wireless Sensing Systems, Steven M. Hernandez

Theses and Dissertations

WiFi sensing offers a powerful method for tracking physical activities using the radio-frequency signals already found throughout our homes and offices. This novel sensing modality offers continuous and non-intrusive activity tracking since sensing can be performed (i) without requiring wearable sensors, (ii) outside the line-of-sight, and even (iii) through the wall. Furthermore, WiFi has become a ubiquitous technology in our computers, our smartphones, and even in low-cost Internet of Things devices. In this work, we consider how the ubiquity of these low-cost WiFi devices offer an unparalleled opportunity for improving the scalability of wireless sensing systems. Thus far, WiFi sensing …

Pms And Gas Pollutants Removal By Electret Filter Media And Metal-Organic Frameworks (Mofs), Yu Zhang

Theses and Dissertations

Indoor air quality (IAQ) has been becoming a major concern worldwide because statistical data showed that the indoor concentrations of gas pollutants, e.g., volatile organic compounds (VOCs) and particulate matters (PMs) are often 2–5 times higher than that of outdoors. Especially, people spend 87% of their time indoors and increasing to more than 90% during COVID-19 pandemic. The high concentration of these indoor air pollutants is mainly due to the reduced air exchange rate for the design of energy-efficient building construction and the increased usage of furnishings, glues, paints, furnaces, etc., leading to VOC outgassing and particle emission. Evidence has …

A Sustainable Ultrafiltration Of Sub-20 Nm Nanoparticles In Water And Isopropanol: Experiments, Theory And Machine Learning, Jie Mcatee

Theses and Dissertations

This research focused on ultrafiltration (UF) for particles down to 2 nm against membranes with larger pore size in water and IPA, which has the potential to save up to 90% of energy. This study developed electrospray (ES) - scanning mobility particle sizer (SMPS) method to fast and effective measure retention efficiencies for small particles (ZnS, Au and PSL) on polytetrafluoroethylene (PTFE), polyvinylidene fluoride (PVDF) and polycarbonate (PCTE) in different liquids. Theoretical models that could quantitatively explain the experimental results for small particles in medium-polarity organic solvents were also developed. Results showed that the highest efficiency was up to ~80% …

Synthesis And Application Of Redox-Active Covalent Organic Frameworks In Rechargeable Batteries, Mohammad K. Shehab

Theses and Dissertations

Synthesis and Application of Redox-Active Covalent Organic Frameworks in Rechargeable Batteries

Mohammad K. Shehab

Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States

Abstract

In recent years, lithium-ion batteries (LIBs) have been considered the dominant energy storage devices for portable electronics and electric vehicles due to their high energy density, low self-discharge rate, and long cycle life. In LIBs, the traditional positive electrodes employed are mainly derived from metal-containing inorganic compounds composed of cobalt, iron, nickel, or manganese (LiCoO₂, LiMn₂O₄, and LiFePO₄) coupled with graphite as the negative electrode. Despite …

Model Based Systems Engineering Approaches To Chemicals And Materials Manufacturing, Quang Le

Theses and Dissertations

Model-based systems engineering (MBSE) is part of a long-term trend toward model-centric approaches adopted by many engineering disciplines. This work establishes the need for an MBSE approach by reviewing the importance, complexity, and vulnerability of the U.S. chemical supply chains. The origins, work processes, modeling approaches, and supporting tools of the systems engineering discipline (SE) are discussed, along with the limitations of the current Process Systems Engineering (PSE) framework. The case is made for MBSE as a more generalizable and robust approach. Systems modeling strategies for MBSE are introduced, as well as a novel MBSE method that supports the automation …

Mechanisms Of Emulsion Destabilization: An Investigation Of Surfactant, Stabilizer, And Detergent Based Formulations Using Diffusing Wave Spectroscopy, Jordan N. Nowaczyk

Theses and Dissertations

Conventional approaches for studying emulsions, such as microscopy and macroscopic phase tracking, present challenges when it comes to establishing detailed mechanistic descriptions of the impact of emulsifier and stabilizer additives. Additionally, while a combination of sizing methods and macroscopic phase tracking can provide insights into droplet size changes and concentration, the use of multiple measurements can be cumbersome and error-prone. It is the focus of this work, to present a new method for studying water in oil (W/O) emulsions that involves using diffusing wave spectroscopy (DWS) to examine the impact of three different surface stabilizing additives at varying concentrations. By …

Portable Robotic Navigation Aid For The Visually Impaired, Lingqiu Jin

Theses and Dissertations

This dissertation aims to address the limitations of existing visual-inertial (VI) SLAM methods - lack of needed robustness and accuracy - for assistive navigation in a large indoor space. Several improvements are made to existing SLAM technology, and the improved methods are used to enable two robotic assistive devices, a robot cane, and a robotic object manipulation aid, for the visually impaired for assistive wayfinding and object detection/grasping. First, depth measurements are incorporated into the optimization process for device pose estimation to improve the success rate of VI SLAM's initialization and reduce scale drift. The improved method, called depth-enhanced visual-inertial …

Investigating Tgf-Β1 And Fibronectin Signaling In Low Oxygen Environments, Caitlin E. Williams

Theses and Dissertations

Breast cancer is the second leading cause of death in women, second to lung cancer. It’s one of the most well-known cancers, with almost 300,000 new cases estimated to be diagnosed in 2023. Breast cancer often begins in ductal epithelial cells, and these cells will typically undergo a cellular transformation process known as epithelial-mesenchymal transition (EMT) in early stages. Breast cancer becomes deadly when it reaches a metastatic stage. As a part of the metastatic process, transformed cells will conduct remodeling of the extracellular matrix (ECM) to allow for migration of an otherwise non-migratory cell type.

As dense tumors form, …

Real-Time Motion Controller For Human-Robot Teams Utilizing Artificial Potential Fields, Gabriella Graziani

Theses and Dissertations

This thesis presents a real-time robotic motion control system for human-robot teams. The framework utilizes artificial potential fields (APFs) to guide robotic agents towards a “goal” agent while navigating around “obstacle” agents; these goals and obstacles are also dynamic agents with their own set of tasks. This system is also developed for a live-programming environment, where a controlling agent updates the tasks of all agents within the system at any time during the system’s runtime. This motion controller was created and tested for a human-robot choreographic team. After the controller was fully integrated on a Trossen Robotic LoCobot Wx200 robotic …

Numerical Study Of Sediment Suspension Affected By Rigid Cylinders Under Unidirectional And Combined Wave-Current Flows, Sha Lou, Xiaolan Chen, Shengyu Zhou, Gangfeng Ma, Shuguang Liu, Larisa Dorzhievna Radnaeva, Elena Nikitina, Irina Viktorovna Fedorova

Civil & Environmental Engineering Faculty Publications

Sediment transport modeling for flows with cylinders is very challenging owing to the complicated flow–cylinder–sediment interactions, especially under the combined wave-current flows. In this paper, an improved formulation for incipient sediment suspension considering the effect of cylinder density (i.e., solid volume fraction) is employed to simulate the bottom sediment flux in the flow with cylinders. The proposed model is calibrated and validated using laboratory measurements under unidirectional and combined wave-current flows in previous studies. It is proved that the effects of cylinders on sediment suspension can be accounted for through a modified critical Shields number, and the proposed model is …

Are Ride-Hailing Services Safer Than Taxis? A Multivariate Spatial Approach With Accomodation Of Exposure Uncertainty, Guocong Zhai, Kun Xie, Hong Yang, Di Yang

Civil & Environmental Engineering Faculty Publications

Despite many research efforts on ride-hailing services and taxis, limited studies have compared the safety performance of the two modes. A major challenge is the need for reliable mode-specific exposure data to model their safety outcomes. Moreover, crash frequencies of the two modes by injury severities tend to be spatially and inherently correlated. To fully address these issues, this study proposes a novel multivariate conditional autoregressive model considering measurement errors in mode-specific exposures (MVCARME). More specially, a classical measurement error structure is used to accommodate the uncertainty of mode-specific exposures estimated, and a multivariate spatial specification is adopted to capture …

Data-Integrity Aware Stochastic Model For Cascading Failures In Power Grids, Rezoan Ahmed Shuvro, Pankaz Das, Jamir Shariar Jyoti, Joana M. Abreu, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

The reliable operation of power grids during cascading failures is heavily dependent on the interdependencies between the power grid components and the supporting communications and control networks. Moreover, the system operators' expertise in dealing with cascading failures can play a pivotal role during contingencies. In this paper, a dynamical probabilistic model is developed based on Markov-chains, which captures the dynamics of cascading failures in the power grid. Specifically, a previously developed Markov-chain based model is extended to capture the trade-off between the benefits of having a robust communication infrastructure and its vulnerability from data integrity (e.g., cyber-attacks). State-space reduction of …

Winter Dynamics Of Storm Water Management Ponds And Winter Tolerance In Three Aquatic Plant Species, Patrick Strzalkowski

Theses and Dissertations (Comprehensive)

The vast majority of the research into the performance of stormwater management ponds (SWMPs) has been performed in warm regions or during the warmer seasons in temperate regions. It is presumed that SWMPs are inactive in the winter as any potential stormwater is trapped in snow and ice. The main goal of this thesis was to test this presumption and to study the dynamics and performance of three SWMPs during the winter. Remote water level loggers were installed into the three SWMPs and daily grab samples from the influents and effluents were taken and analyzed for total phosphorus (TP), chloride, …

Phosphorus Release And Recovery From Simulated Ferric Wastewater Sludge, Aseel Alnimer

Theses and Dissertations (Comprehensive)

Phosphorus (P) is a fundamental element necessary for all life forms and a key component in the fertilizer industry. Meanwhile, the excessive load of P to water bodies due to human activities has the potential to promote eutrophication. Wastewater treatment plants remove P either biologically or chemically and produce P rich sludge which could be a potential renewable source for P. At present, commercial technologies exist for P recovery from biological wastewater sludge. However, P recovery from chemical sludge particularly iron(III)-phosphate (Fe-P) sludge generated in chemical P removal plants that use iron(III) salts remains a challenge.

This study explored, in …

Aortic Remodeling Kinetics In Response To Coarctation-Induced Mechanical Perturbations, Arash Ghorbannia, Mehdi Maadooliat, Ronald K. Woods, Said H. Audi, Brandon J. Tefft, Claudio Chiastra, El Sayed H. Ibrahim, John F. Ladisa Jr.

Biomedical Engineering Faculty Research and Publications

Background: Coarctation of the aorta (CoA; constriction of the proximal descending thoracic aorta) is among the most common congenital cardiovascular defects. Coarctation-induced mechanical perturbations trigger a cycle of mechano-transduction events leading to irreversible precursors of hypertension including arterial thickening, stiffening, and vasoactive dysfunction in proximal conduit arteries. This study sought to identify kinetics of the stress-mediated compensatory response leading to these alterations using a preclinical rabbit model of CoA.

Methods: A prior growth and remodeling (G&R) framework was reformulated and fit to empirical measurements from CoA rabbits classified into one control and nine CoA groups of various severities …

The Suitability Of Demand-Controlled Sensor Based Ventilation Systems In Retrofit Dwellings - A Longitudinal Study., Seamus Harrington, Mark Mulville

Conference papers

A fabric-first approach to dwelling retrofit results in increased airtightness, therefore there is an obligation to ensure that the upgrades do not lead to poor indoor air quality (IAQ) resulting from inadequate ventilation. The sensor-based demand-controlled ventilation (SBDCV) under review seeks to provide fresh air for breathing and to dilute and exhaust pollutants and odours. This system modulates the ventilation rate over time based on relative humidity levels and/or presence detection and considers that the level of ventilation provided is sufficient to control the concentration of all other indoor air pollutants, including those that are not a result of human …

Towards A Prototype Paleo-Detector For Supernova Neutrino And Dark Matter Detection, Emilie Marie Lavoie-Ingram

UNF Graduate Theses and Dissertations

Using ancient minerals as paleo-detectors is a proposed experimental technique expected to transform supernova neutrino and dark matter detection. In this technique, minerals are processed and closely analyzed for nanometer scale damage track remnants from nuclear recoils caused by supernova neutrinos and possibly dark matter. These damage tracks present the opportunity to directly detect and characterize the core-collapse supernova rate of the Milky Way Galaxy as well as the presence of dark matter. Current literature presents theoretical estimates for these potential tracks, however, there is little research investigating the experimental feasibility of this technique. At the University of North Florida, …