Digital Commons Network^™

Investigation Of Green Strawberry Detection Using R-Cnn With Various Architectures, Daniel W. Rivers

Master's Theses

Traditional image processing solutions have been applied in the past to detect and count strawberries. These methods typically involve feature extraction followed by object detection using one or more features. Some object detection problems can be ambiguous as to what features are relevant and the solutions to many problems are only fully realized when the modern approach has been applied and tested, such as deep learning.

In this work, we investigate the use of R-CNN for green strawberry detection. The object detection involves finding regions of interest (ROIs) in field images using the selective segmentation algorithm and inputting these regions …

Impact Of Teaching Practices And Communication Climates On Participation In Computer Science Education, Jackie Krone

Master's Theses

One way to understand teaching is to view it as a people process rather than a presentation of knowledge. It follows that the role of an educator often extends beyond the primary subject matter and into the realm of classroom management. With this in mind, our research aimed to capture the various teaching practices, participation patterns, and communication climates that occur in virtual computer science classrooms. We sought to answer the following research questions related to virtual computer science classrooms at our institution: Who participates in virtual computer science classrooms, and is participation proportional to student demographics? Is there any …

Long-Term Traffic Flow Estimation: A Hybrid Approach Using Location-Basedtraffic Characteristic, Tuğberk Ayar, Ferhat Atli̇nar, Mehmet Amaç Güvensan, Hafi̇za İrem Türkmen

Turkish Journal of Electrical Engineering and Computer Sciences

Traffic speed estimation plays a key role in various situations, ranging from individual's trip planning to urban traffic management. Despite many studies on short-term prediction, there is only a limited number of studies focusing on long-term prediction and only a couple of them does go beyond 24 h. On the contrary, this study presents a novel hybrid architecture using location-based traffic characteristic for traffic speed estimation up to 7 days. In this architecture, the introduced mean filtering estimation (MFE) model and long short-term memory (LSTM) neural network are jointly utilized for minimizing the error for traffic flow estimation. Both MFE …

Privacy Preserving Scheme For Document Similarity Detection, Ayad Abdulsada, Salah Al-Darraji, Dhafer Honi

Turkish Journal of Electrical Engineering and Computer Sciences

The problem of detecting similar documents plays an essential role for many real-world applications, such as copyright protection and plagiarism detection. To protect data privacy, the new version of such a problem becomes more challenging, where the matched documents are distributed among two or more parties and their privacy should be preserved. In this paper, we propose new privacy-preserving document similarity detection schemes by utilizing the locality-sensitive hashing technique, which can handle the misspelled mistakes. Furthermore, the keywords' occurrences of a given document are integrated into its underlying representation to support a better ranking for the returned results. We introduced …

A New Classification Method Using Soft Decision-Making Based On An Aggregation Operator Of Fuzzy Parameterized Fuzzy Soft Matrices, Samet Memi̇ş, Serdar Engi̇noğlu, Uğur Erkan

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, a precise and stable machine learning algorithm, i.e. eigenvalue classification method (EigenClass), has been developed by using the concept of generalised eigenvalues in contrast to common approaches, such as k-nearest neighbours, support vector machines, and decision trees. In this paper, we offer a new classification algorithm called fuzzy parameterized fuzzy soft aggregation classifier (FPFS-AC) to combine the modelling ability of soft decision-making (SDM) and classification success of generalised eigenvalues. FPFS-AC constructs a decision matrix by employing the similarity measures of fuzzy parameterized fuzzy soft matrices fpfs -matrices) and a generalised eigenvalue-based similarity measure. Then, it applies an SDM method …

Defect Classification Of Railway Fasteners Using Image Preprocessing And Alightweight Convolutional Neural Network, İlhan Aydin, Mehmet Sevi̇, Mehmet Umut Salur, Erhan Akin

Turkish Journal of Electrical Engineering and Computer Sciences

Railway fasteners are used to securely fix rails to sleeper blocks. Partial wear or complete loss of these components can lead to serious accidents and cause train derailments. To ensure the safety of railway transportation, computer vision and pattern recognition-based methods are increasingly used to inspect railway infrastructure. In particular, it has become an important task to detect defects in railway tracks. This is challenging since rail track images are acquired using a measuring train in varying environmental conditions, at different times of day and in poor lighting conditions, and the resulting images often have low contrast. In this study, …

Magnetic Flux Channel Antenna Design In Conformal Applications, William J. Tremblay

Theses and Dissertations

Magnetic Flux Channels (MFC) and Magneto-Dielectric Wire Antennas (MDWA) are effective, and in some cases, superior alternatives to traditional metallic antennas, in conformal and electrically small applications at the cost of fabrication and feed complexity. The frequency dispersive nature of magnetic material constituent parameters imposes constraints on the antenna design process, which were not fully developed in prior art. This research quantifies the key differences between the operating regions of magneto-dielectric materials for antenna applications and demonstrates the effectiveness of numerical method augmented modal analysis in the design process, regardless of operating region. Modeling challenges associated with MDWAs are addressed …

Considering Dds In The Domain Of Dis - Pros And Cons, Nathaniel R. Peck

Theses and Dissertations

DIS is a legacy IEEE standard for defining and structuring PDUs in large scale distributed wargames. Although the standard specifies various QoS appropriate for certain PDUs, a one-size-fits-all transport strategy is traditionally employed via UDP. Since the inception of DIS, the OMG has produced a standard for a DDS which has been implemented by several middleware vendors. DDS middleware offers an abstraction for network communications that allows applications and developers to easily employ configurable QoS by topic. Adoption and use of these QoS in DIS applications may introduce greater compliance with the IEEE standard and enrich the service features available …

Relative Magnetic Position And Rotation Sensor Assisted Dual-Foot Pedestrian Dead Reckoning, Jenario Y. Johnson

Theses and Dissertations

The use of wearable foot-based inertial measurement units (IMUs) incorporated in a navigation system can address the problem of single-person location tracking in situations and environments where GPS signals may be unavailable or inconsistent. This Pedestrian Dead Reckoning (PDR) approach enables standalone personal tracking. A notable solution involves using inertial measurement units (IMUs) in a filter to apply zero-velocity updates to a Kalman filter to get a position solution. This paper continues on the path of the former method by investigating the feasibility of PDR using a pair of low cost IMUs along with a pair of relative position and …

Performance Assessment Of Navigation Using Carrier Doppler Measurements From Multiple Leo Constellations, Michael J. Hartnett

Theses and Dissertations

The goal of this work is to characterize a novel navigation method which uses carrier Doppler shift measurements from LEO satellites. An ever-growing reliance on the GNSS has coincided with an increase in ways it can be degraded or denied, whether naturally occurring or man-made. These potentially disastrous threats to traditional navigation and timing have necessitated new technologies to augment GNSS in the case of an outage. LEO constellations, whose size and higher signal power make them potentially useful for navigation, are one technology that has been explored. The navigation algorithms detailed in this research use Doppler measurements from 8 …

Design Study For An Antenna Radar Cross Section Measurement Test Fixture, Wayne C. Kreimeyer

Theses and Dissertations

Military technology requires equipment to be undetected by adversaries. Stealth aircraft are designed to be undetected through electromagnetic means by minimizing a return signature called the RCS. Therefore, it is essential to understand how antennas, which are necessary for communication, affect the overall RCS of the aircraft. The antenna is measured in a compact RADAR range. The antenna needs a structure to support it, also referred to as a test fixture, that does not interfere with the measuring process of the antenna’s RCS. This thesis set out to get the lowest RCS possible of a test fixture by evaluating different …

Magnetic Anomaly Absolute Positioning For Hypersonic Aircraft, Alexander J. Mcneil

Theses and Dissertations

GPS has proven to be an extremely valuable asset for navigation, and timing. GPS has become the standard navigation system for all applications, but GPS has limitations. GPS is susceptible to jamming, spoofing, and in the case of hypersonic aircraft, is likely unavailable. When an aircraft is traveling at hypersonic speeds, there is a plasma sheath that surrounds the aircraft. This plasma sheath blocks electromagnetic waves, and is therefore responsible for a GPS blackout. GPS unavailability for hypersonic aircraft has prompted the research into the viability of alternate navigation systems for these aircraft. This paper seeks to explore the viability …

Deep Learning Techniques To Estimate 3d Position In Stereoscopic Imagery, Jonathan I. Nicholson

Theses and Dissertations

Current AAR efforts utilize machine vision algorithms to estimate the pose of a receiver aircraft. However, these algorithms are dependent on several conditions such as the availability of precise 3D aircraft models; the accuracy of the pipeline significantly degrades in the absence of high-quality information given beforehand. We propose a deep learning architecture that estimates the 3D position of an object based on stereoscopic imagery. We investigate the use of both machine learning techniques and neural networks to directly regress the 3D position of the receiver aircraft. We present a new position estimation framework that is based on the differences …

Global Sporadic-E Climatological Analysis Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos

Theses and Dissertations

A climatology of sporadic-E (Es) derived from a combined data set of GPS radio occultation (GPS-RO) and ground-based ionosonde soundings is presented for the period from September 2006 to February 2019. The ionosonde soundings were measured using the Lowell Digisonde International (LDI) Global Ionosphere Radio Observatory (GIRO) network consisting of 65 sites and 13,141,060 total soundings. The GPS-RO observations were taken aboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites and processed using two binary Es detection algorithms, totaling 9,072,922 occultations. The first algorithm is an S4 amplitude threshold calibrated to the occurrence of any blanketing Es …

Recent Advances In Electrochemical Kinetics Simulations And Their Applications In Pt-Based Fuel Cells, Ji-Li Li, Ye-Fei Li, Zhi-Pan Liu

Journal of Electrochemistry

Theoretical simulations of electrocatalysis are vital for understanding the mechanism of the electrochemical process at the atomic level. It can help to reveal the in-situ structures of electrode surfaces and establish the microscopic mechanism of electrocatalysis, thereby solving the problems such as electrode oxidation and corrosion. However, there are still many problems in the theoretical electrochemical simulations, including the solvation effects, the electric double layer, and the structural transformation of electrodes. Here we review recent advances of theoretical methods in electrochemical modeling, in particular, the double reference approach, the periodic continuum solvation model based on the modified Poisson-Boltzmann …

Facet Dependent Oxygen Evolution Activity Of Spinel Cobalt Oxides, Li-Hua Zhang, Hong-Yuan Chuai, Hai Liu, Qun Fan, Si-Yu Kuang, Sheng Zhang, Xin-Bin Ma

Journal of Electrochemistry

Water splitting is a promising technology to produce clean hydrogen if powered by renewable energies, where oxygen evolution is the rate determining step at an anode. Here we adjust the different crystal planes of the cobalt oxides catalyst to expose more effective active sites through a hydrothermal process, so as to improve the reaction activity for oxygen evolution. The samples were well characterized by TEM, SEM and XRD. Among the three synthetic crystal planes (100), (111) and (110) of spinel cobalt oxides, the (100) crystal plane has the highest intrinsic activity. Combining in-situ infrared and DFT calculations, we …

Real-Time Complex Hand Gestures Recognition Based On Multi- Dimensional Features, Isack Bulugu

Tanzania Journal of Engineering and Technology (TJET)

Gesture recognition is broadly utilized within the field of sensing. There are basically three gesture recognition methods based on computer vision, depth sensor and motion sensor. Motion sensor-based gesture recognition has few input data, fast speed, and direct access to three- dimensional information of the hand. The advantages of traditional motion sensor-based gesture recognition have gradually become a current research hotspot. The essence of traditional motion sensor-based gesture recognition is a pattern recognition problem, and its accuracy depends heavily on the feature dataset extracted from prior experience. Unlike traditional pattern recognition methods, deep learning can be used to a large …

A Precise Dispenser Design For Canine Cognition Research, Walker Arce, Jeffrey R. Stevens

Department of Electrical and Computer Engineering: Faculty Publications

Some forms of canine cognition research require a dispenser that can accurately dispense precise quantities of treats. When using off-the-shelf or retrofitted dispensers, there is no guarantee that a precise number of treats will be dispensed. Often, they will over-dispense treats, which may not be acceptable for some tasks. Here we describe a 3D-printed precise treat dispenser with a 59-treat capacity driven by a stepper motor drive and controlled by an integrated Raspberry Pi. The dispenser can be built for less than 200 USD and is fully 3D printable. While off-the-shelf dispensers can result in an error rate of 20–30%, …

A Deep Unsupervised Feature Learning Spiking Neural Network With Binarized Classification Layers For The Emnist Classification, Ruthvik Vaila, John Chiasson, Vishal Saxena

Electrical and Computer Engineering Faculty Publications and Presentations

End user AI is trained on large server farms with data collected from the users. With ever increasing demand for IoT devices, there is a need for deep learning approaches that can be implemented at the Edge in an energy efficient manner. In this work we approach this using spiking neural networks. The unsupervised learning technique of spike timing dependent plasticity (STDP) and binary activations are used to extract features from spiking input data. Gradient descent (backpropagation) is used only on the output layer to perform training for classification. The accuracies obtained for the balanced EMNIST data set compare favorably …

Integration Of Electrical Impedance Spectroscopy For Multichannel Cell Culture Measurement, Conard Chan

Master's Theses

ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY (EIS) has been widely used to study the electrical properties of biological material due to its non-invasive nature and experimental reliability. However, most of the precision impedance analyzers used in EIS only provide single- or two-channel measurements which are inadequate for larger-scale multiplexed measurements, such as those found in modern microfluidic cell culture experiments. The Biomedical Microsystems Laboratory has developed a 16-channel cell culture platform with integrated electrode arrays for monitoring cell growth and electrical properties (i.e., the so-called “electrical phenotype”). In this paper, a system consisting of a 16-channel solid-state analog multiplexer (MUX)paired with a low-cost, …

Tri-Op Redactable Blockchains With Block Modification, Removal, And Insertion, Mohammad Sadeq Dousti, Alpteki̇n Küpçü

Turkish Journal of Electrical Engineering and Computer Sciences

In distributed computations and cryptography, it is desirable to record events on a public ledger, such that later alterations are computationally infeasible. An implementation of this idea is called blockchain, which is a distributed protocol that allows the creation of an immutable ledger. While such an idea is very appealing, the ledger may be contaminated with incorrect, illegal, or even dangerous data, and everyone running the blockchain protocol has no option but to store and propagate the unwanted data. The ledger is bloated over time, and it is not possible to remove redundant information. Finally, missing data cannot be inserted …

Blocksim-Net: A Network-Based Blockchain Simulator, Prashanthi Ramachandran, Nandini Agrawal, Osman Bi̇çer, Alpteki̇n Küpçü

Turkish Journal of Electrical Engineering and Computer Sciences

Since its proposal by Eyal and Sirer (CACM '13), selfish mining attacks on proof-of-work blockchains have been studied extensively. The main body of this research aims at both studying the extent of its impact and defending against it. Yet, before any practical defense is deployed in a real world blockchain system, it needs to be tested for security and dependability. However, real blockchain systems are too complex to conduct any test on or benchmark the developed protocols. Instead, some simulation environments have been proposed recently, such as BlockSim (Maher et al., SIGMETRICS Perform. Eval. Rev. '19), which is a modular …

Estonian Internet Voting With Anonymous Credentials, İsa Sertkaya, Peter Roenne, Peter Y. A. Ryan

Turkish Journal of Electrical Engineering and Computer Sciences

The Estonian Internet voting (EIV) scheme is a unique example of a long-term nation-wide, legally binding electronic voting deployment. The EIV scheme is used in parallel with standard paper-based election day voting, of course invalidating an already cast i-vote. This necessarily requires careful authentication of the eligible voters and makes the Estonian identity card solution a crucial part of the scheme, however, note that Parsovs has recently drawn attention to the security flaws found in Estonian ID-cards. In this study, we propose an e-voting scheme EIV-AC that integrates the EIV scheme with anonymous credentials based on self-sovereign identity. In addition …

Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Currently, renewable energy generation has received more and more attention. This article focuses on wind energy generation, one of the renewable energy sources. Aiming at the intermittent and unpredictable wind power problems, according to the day ahead bidding mechanism in the power market, this paper introduces the energy storage system to maximize wind power merchants profit based on the newsvendor model. First, this paper focuses on the wind farms combined with storage system to put forward the optimal bidding decision of selling or buying electricity to the market one day in advance and the optimal bidding amount. Then, we analyze …

Efficient And Accurate Phase-Measurement Method For Core-Loss Characterization, Anfeng Huang, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate core-loss characterization is essential to push the power density of power converters to their limits. However, existing core-loss measurement methods still have some limitations, such as a slow test speed and a complex probe calibration procedure. In particular, accurate phase-difference measurement is time-consuming because a fast Fourier transform analysis with a kHz-range frequency interval is typically applied to reduce the influence of noise. An automated measurement system for magnetic core-loss characterization is described in this paper. An accurate phase-detection block with programmable attenuators is developed to measure the phase difference between voltage and current waveforms. The proposed system considerably …

A Low-Profile Fabry-Pérot Cavity Antenna Using Anisotropic Metasurface, Muhammad Yasir Jamal, Min Li, Kwan Lawrence Yeung, Xiaoqiang Li, Lijun Jiang, Tatsuo Itoh

Electrical and Computer Engineering Faculty Research & Creative Works

A Fabry-Pérot cavity (FPC) antenna utilizing a new cavity resonance phenomenon based on the polarization standing wave (PSW) is proposed. To produce PSW, two anisotropic metasurfaces acting as the handedness preserving mirror are designed as the two ends of the cavity. Such a cavity possesses a new resonant condition, i.e., the relative rotation angle and distance between two metasurfaces together determine its resonant frequency. Hence, in comparison to conventional FPC antennas, the proposed one possesses a lower profile height of around 0.125 wavelengths. The antenna concept is experimentally demonstrated for the 12 GHz X-band application. Measurement results agree well with …

Privacy In Blockchain Systems, Murat Osmanoğlu, Ali̇ Aydin Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Privacy of blockchains has been a matter of discussion since the inception of Bitcoin. Various techniques with a varying degree of privacy protection and complexity have been proposed over the past decade. In this survey, we present a systematic analysis of these proposals in four categories: (i) identity, (ii) transaction, (iii) consensus, and (iv) smart contract privacy. Each of these categories have privacy requirements of its own, and various solutions have been proposed to meet these requirements. Almost every technique in the literature of privacy enhancing technologies have been applied to blockchains: mix networks, zero-knowledge proofs, blind signatures, ring signatures, …

An Intelligent Distributed Ledger Construction Algorithm For Iot, Charles Rawlins, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed …

Assistive Technologies For Independent Navigation For People With Blindness, Howard Kaplan

USF Tampa Graduate Theses and Dissertations

The necessity for individuals to navigate from location to location is essential to daily life. The majority of humans use sight as the main source for determining how to move through their environment. However, there is a large population of people who are either blind or living with low vision. Based on a 2017 National Health Survey there are around 27 million adult Americans that have experienced vision loss (National Center for Health Statistics, 2017). According to the Eye Diseases Prevalence Research Group there are 3.4 million Americans 40 years and older that are legally blind or visually impaired (EDPRG, …

Development Of A Testing Station For Grid-Interactive Smart Inverter Systems, Yudong Lan

Dissertations and Theses

As renewable energy penetration increases within the electrical power grid, flexible power is required to ensure reliability. Reliability can be jeopardized by the fluctuation and non-dispatch ability of renewable generators. This instability is caused by an imbalance between the amount of power produced and the amount of power consumed. Grid-enabled battery inverter systems are considered a solution to offset voltage and frequency fluctuations, which arise due to this power imbalance.

The objective of this work is to develop a system for testing grid-enabled inverters. These inverters use one or more communication standards to control their interactions with the grid. This …