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Articles 3781 - 3810 of 17330

Full-Text Articles in Engineering

Performance Analysis And Feature Selection For Network-Based Intrusion Detectionwith Deep Learning, Serhat Caner, Nesli̇ Erdoğmuş, Yusuf Murat Erten Mar 2022

Performance Analysis And Feature Selection For Network-Based Intrusion Detectionwith Deep Learning, Serhat Caner, Nesli̇ Erdoğmuş, Yusuf Murat Erten

Turkish Journal of Electrical Engineering and Computer Sciences

An intrusion detection system is an automated monitoring tool that analyzes network traffic and detects malicious activities by looking out either for known patterns of attacks or for an anomaly. In this study, intrusion detection and classification performances of different deep learning based systems are examined. For this purpose, 24 deep neural networks with four different architectures are trained and evaluated on CICIDS2017 dataset. Furthermore, the best performing model is utilized to inspect raw network traffic features and rank them with respect to their contributions to success rates. By selecting features with respect to their ranks, sets of varying size …

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Modeling And Evaluation Of Soc-Based Coordinated Ev Charging For Powermanagement In A Distribution System, Murat Akil, Emrah Dokur, Ramazan Bayindir Mar 2022

Modeling And Evaluation Of Soc-Based Coordinated Ev Charging For Powermanagement In A Distribution System, Murat Akil, Emrah Dokur, Ramazan Bayindir

Turkish Journal of Electrical Engineering and Computer Sciences

The importance of using clean energy in electrical energy generation and transportation network planning has recently increased due to carbon footprint rising. In this direction, the use of electric vehicles (EV), known as ultra-low carbon emission vehicles, has become widespread in addition to renewable energy sources (RES) such as wind and photovoltaic (PV) power generations. The trend of EVs to be preferred the primary means of transport has revealed the effects of charging an additional load on the grid. There is a need to create coordinated charging methods by considering the approaches for real-time charging models of EVs. In this …

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Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz Mar 2022

Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

TV rating is a numeric estimate of the popularity of television programs. Forecasting TV ratings is considered an important asset for investment planning of media due to its potential of reducing the risks of future ventures. The aim of this study is to develop a machine learning model capable of efficiently forecasting the TV ratings of Turkish TV series in a practical manner. To this end, two prediction models were proposed for forecasting the TV ratings of television series, facilitating an extensive set of features. A contribution of this study is the inclusion of social media-based features using search trends …

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Predictive Optimization Of Sliding Mode Control Using Recurrent Neural Paradigmfor Nonlinear Dfig-Wpgs During Distorted Voltage, Omar Busati, Xiangjie Liu Mar 2022

Predictive Optimization Of Sliding Mode Control Using Recurrent Neural Paradigmfor Nonlinear Dfig-Wpgs During Distorted Voltage, Omar Busati, Xiangjie Liu

Turkish Journal of Electrical Engineering and Computer Sciences

Dynamic characteristics of the doubly-fed induction generator (DFIG)-based wind power generation (WPGS) are fully nonlinear. Therefore, issues such as stability and achieving high efficiency, especially under harmonics behavior, are challenges that assess the control strategy reliability to find the perfect dynamic solution. This discussion offers a control strategy for the separated stator-port power using a predictive sliding mode strategy with a resonant function (PSMC-R) based on a deep recurrent neural network (DRNN). DRNN is formed as a low-order Taylor series formula. PSMC-R predicts the perfect switching surface path and regulates the distorted nonlinear DFIG with several dynamic aims. This approach …

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Scattering Analyses Of Arbitrary Roughness From 2-D Perfectly Conductiveperiodic Surfaces With Moments Method, Yunus Emre Yamaç, Ahmet Kizilay Mar 2022

Scattering Analyses Of Arbitrary Roughness From 2-D Perfectly Conductiveperiodic Surfaces With Moments Method, Yunus Emre Yamaç, Ahmet Kizilay

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a periodic-MoM-based code with high accuracy performance is developed to calculate electromagnetic scattering from a periodic conductive surface in two dimensions with any degree of roughness. Firstly, the existing separate methods in the literature are reviewed step by step to compose a periodic-MoM solution for 2-D periodic surfaces. Then, the dynamic selection of optimal formulation of the periodic-MoM solutions created using these existing methods is evaluated to reduce solution time and obtain high accuracy. In this study, the performance parameters of the existing methods are investigated in solving a real 3-D scattering problem by a periodic-MoM for …

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Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş Mar 2022

Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş

Turkish Journal of Electrical Engineering and Computer Sciences

The aerodynamic design and analysis of an Unmanned Air Vehicle, capable of vertical take-off and landing by employing fixed four rotors on the tilt-wing and two rotors on the tilt-tail, will be presented in this study. Both main wing and the horizontal tail can be tilted 90°. During VTOL, transition and forward flight, aerodynamic and thrust forces have been employed. Different flight conditions, including the effects of angle of attack, side slip, wing tilt angle and control surfaces deflection angle changes, have been studied with CFD analysis. For a Tilt-Wing UAV, there are challenges like high non-linearity, vulnerability to disturbances …

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Reactive Power Sharing And Voltage Restoration In Islanded Ac Microgrids, Khurram Hashmi, Rizwan Ali, Muhammad Hanan, Waseem Aslam, Abubakar Siddique, Muhammad Mansoor Khan Mar 2022

Reactive Power Sharing And Voltage Restoration In Islanded Ac Microgrids, Khurram Hashmi, Rizwan Ali, Muhammad Hanan, Waseem Aslam, Abubakar Siddique, Muhammad Mansoor Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Microgrids (MG) are a new and innovative concept in modern distribution networks. Several challenges are associated with the operation and control of MG networks. Active and reactive power sharing among energy resources interfaced through power electronic conversion stages is a major challenge. Although active power sharing can be achieved under varying scenarios, sharing of reactive power between distributed generation units is difficult to achieve. This paper presents a novel and innovative control scheme to ensure sharing of reactive power between Distributed generation units within an autonomous, islanded AC microgrid. A framework composed of novel multiagent moving average estimators is proposed …

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Robust Position/Force Control Of Nonholonomic Mobile Manipulator Forconstrained Motion On Surface In Task Space, Güli̇n Eli̇bol Seçi̇l, Serhat Obuz, Osman Parlaktuna Mar 2022

Robust Position/Force Control Of Nonholonomic Mobile Manipulator Forconstrained Motion On Surface In Task Space, Güli̇n Eli̇bol Seçi̇l, Serhat Obuz, Osman Parlaktuna

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a robust controller is developed for a mobile manipulator (MM) to track reference position/force trajectories. Nonholonomic and holonomic constraints are considered for the mobile platform and manipulator, respectively. Additionally, the control design considers the uncertainties in parameters of the dynamics of the mobile manipulator with a bounded time varying additive disturbance (unmodelled effects, external disturbances). A Lyapunov-based stability analysis is used to prove semiglobal uniform ultimate boundedness of the tracking error signals and the position/force of the system track to an arbitrarily small neighborhood of the reference trajectories. Numerical results for a mobile manipulator, which is formed …

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Design And Manufacture Of Electromagnetic Absorber Composed Of Boricacid-Incorporated Wastepaper Composites, Ali̇ İhsan Kaya, Ahmet Çi̇fci̇, Fi̇li̇z Kirdioğullari, Mesud Kahri̇man, Osman Çerezci̇ Mar 2022

Design And Manufacture Of Electromagnetic Absorber Composed Of Boricacid-Incorporated Wastepaper Composites, Ali̇ İhsan Kaya, Ahmet Çi̇fci̇, Fi̇li̇z Kirdioğullari, Mesud Kahri̇man, Osman Çerezci̇

Turkish Journal of Electrical Engineering and Computer Sciences

With the effect of technological advances, the use of electrical and electronic devices has increased dramatically in recent years. Wireless technologies and related applications are mostly preferred for the communication of these devices with each other. Thus, people are easily exposed to electromagnetic waves in daily life. The extensive global use of these devices raises the question of their possible biological effects on human health. Also, electromagnetic waves influence the functioning of a nearby device. In this study, an electromagnetic absorber based on boric acid (5, 10, 20, and 30 wt%) added wastepaper was developed. Copper (Cu) and aluminum (Al) …

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A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇ Mar 2022

A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems provide their users an efficient way to handle information overload problem by offering personalized suggestions. Traditional recommender systems are based on two-dimensional user-item preference matrix constructed depending on the users' overall evaluations over items. However, they have begun to present their preferences under various circumstances. Thus, traditional recommendation techniques fail to process multicriteria ratings during the recommendation process. Multicriteria recommender systems are an extension of traditional recommender systems that utilize multicriteria-based user preferences. Multicriteria recommender systems provide more personalized and accurate predictions compared to traditional recommender systems. However, the increased amount of data dimension causes sparsity to be …

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Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan Mar 2022

Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan

Turkish Journal of Electrical Engineering and Computer Sciences

Electric vehicles (EVs) exhibit several benefits over combustion engine vehicles, making them an attractive mode of mobility for the future. However, supplying the electrical energy required to recharge their batteries could adversely affect the power system infrastructure. The most severe impact of EV integration is expected to be on the distribution transformers, which are among the costliest equipment in the distribution network. Sustained overloads on the transformer could lead to accelerated aging and early retirement. As the rate of EV deployment rises, so does the probability of transformer overloads and the subsequent loss of life. There is a need for …

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The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan Mar 2022

The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan

Turkish Journal of Electrical Engineering and Computer Sciences

The meaningful performance of convolutional neural network (CNN) has enabled the solution of various state-of-the-art problems. Although CNNs achieve satisfactory results in computer-vision problems, they still have some difficulties. As the designed CNN models are deepened to achieve much better accuracy, computational cost and complexity increase. It is significant to train CNNs with suitable topology and training hyperparameters that include initial learning rate, minibatch size, epoch number, filter size, number of filters, etc. because the initialization of hyperparameters affects classification results. On the other hand, it is not possible to make a definite inference for the hyperparameter initialization and there …

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A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani Mar 2022

A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani

Turkish Journal of Electrical Engineering and Computer Sciences

A new design of current mode instrumentation amplifier (CMIA) with tunable gain and low voltage operation capability is proposed in this paper, which is suitable for biomedical signals processing, especially in electrocardiogram (ECG). It consists of a new design of current differencing transconductance amplifier (CDTA) and dual z copy CDTA (DZC-CDTA). The gain of the proposed CMIA is controlled by a MOS-based tunable resistor. The main advantage of the proposed CMIA is its high gain that can be tuned over a significant range with the help of two resistances. The performance of the proposed instrumentation amplifier is evaluated through simulation …

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45-Nm Cds Qds Photoluminescent Filter For Photovoltaic Conversionefficiency Recovery, Victor Juárez-Luna, Daniel Sauceda-Carvajal, Ivett Zavala-Guillen, Enrique Rodarte-Guajardo, Francisco Carranza-Chávez, Carlos Villa Angulo Mar 2022

45-Nm Cds Qds Photoluminescent Filter For Photovoltaic Conversionefficiency Recovery, Victor Juárez-Luna, Daniel Sauceda-Carvajal, Ivett Zavala-Guillen, Enrique Rodarte-Guajardo, Francisco Carranza-Chávez, Carlos Villa Angulo

Turkish Journal of Electrical Engineering and Computer Sciences

Different energy loss mechanisms have restricted the breakthroughs in concentrated photovoltaic/thermal (CPVT) hybrid solar systems that use photoluminescent filters. Re?ected and transmitted light, emission spectrum, nonideal absorption, Stokes shift (proportional to $f_1 f_2$), overlapping absorption, and scattering of light are mechanisms in photoluminescent filters that restrict optical efficiency to below theoretical limits. In addition, increases in temperature by light concentration affect the operation of photovoltaic cells and photoluminescent filters because of an increase in molecular motion and collisions that consequently lead to energy loss. Meanwhile, nanocrystals or quantum dots (QDs) from groups II VI hold electrical, optical, chemical, and physical …

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Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao Mar 2022

Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao

Turkish Journal of Electrical Engineering and Computer Sciences

This paper is devoted to revealing some properties of the probabilistic optimal power flow (POPF) problem. In conjunction with Hermite polynomial model, Nataf transformation is introduced to map POPF problem to the independent standard normal space. Firstly, a multivariate polynomial model is employed to represent the function relationship between POPF inputs and outputs. Then, moment matching equations are derived to characterize the uncertainty effects of POPF inputs on outputs; three cubature rules are derived to calculate statistical moments of POPF outputs. Finally, along with Monte Carlo simulation method, the proposed methods are tested on IEEE 57-bus system and IEEE 118-bus …

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A Bi-Level Charging Management Approach For Electric Truck Charging Stationconsidering Power Losses, Tayfur Gökçek, Mehmet Tan Turan, Yavuz Ateş, Ahmet Yi̇ği̇t Arabul Mar 2022

A Bi-Level Charging Management Approach For Electric Truck Charging Stationconsidering Power Losses, Tayfur Gökçek, Mehmet Tan Turan, Yavuz Ateş, Ahmet Yi̇ği̇t Arabul

Turkish Journal of Electrical Engineering and Computer Sciences

This article presents an optimized heavy duty electric truck charging station (ETCS) design based on bi-level mixed integer linear programming. Electric truck parameters are integrated with the grid model and charging sequences are firstly formulated to optimize charging stages. As the second level of the optimization stage, line losses are aimed to be minimized for the charging station. ETCS model is obtained from actual parameters of the Istanbul Muratbey Customs zone which is one of the busiest customs zone in Europe and an ideal location for ETCS application in the future. The ETCS is equipped with roof type photovoltaic (PV) …

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Tara: Temperature Aware Online Dynamic Resource Allocation Scheme For Energyoptimization In Cloud Data Centres, Narayanamoorthi Thilagavathi, Arockiasamy John Prakash, Sridhar Sridevi, Vaidyanathan Rhymend Uthariaraj Mar 2022

Tara: Temperature Aware Online Dynamic Resource Allocation Scheme For Energyoptimization In Cloud Data Centres, Narayanamoorthi Thilagavathi, Arockiasamy John Prakash, Sridhar Sridevi, Vaidyanathan Rhymend Uthariaraj

Turkish Journal of Electrical Engineering and Computer Sciences

Cloud data centres, which are characteristic of dynamic workloads, if not optimized for energy consumption, may lead to increased heat dissipation and eventually impact the environment adversely. Consequently, optimizing the usage of energy has become a hard requirement in today's cloud data centres wherein the major part of energy consumption is mostly attributed to computing and cooling systems. Motivated by which this paper proposes an online algorithm for dynamic resource allocation, namely, temperature aware online dynamic resource allocation algorithm (TARA). TARA demonstrates a novel algorithm design to adapt dynamic resource allocation based on the temperature of a data centre using …

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Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah Mar 2022

Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning (DL) models are currently not widely deployed for critical tasks such as in health. This is attributable to the "black box", making it difficult to gain the trust of practitioners. This paper proposes the use of visualizations to enhance performance verification, improve monitoring, ensure understandability, and improve interpretability needed to gain practitioners' confidence. These are demonstrated through the development of a CapsNet model for the recognition of gastrointestinal tract infection. The gastrointestinal tract comprises several organs joined in a long tube from the mouth to the anus. It is susceptive to diseases that are difficult for medics to …

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Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu Mar 2022

Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Determining identity is a crucial task especially in the cases of mass disasters such as tsunamis, earthquakes, fires, epidemics, and in forensics. Although there are various studies in the literature on biometric identification from radiographic dental images, more research is still required. In this study, a panoramic dental radiographic (PDR) imagebased human identification system was developed using a customized deep convolutional neural network model in a few-shot learning scheme. The proposed model (PDR-net) was trained on 600 PDR images obtained from a total of 300 patients. As the PDR images of the patients were very different in terms of pose …

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Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu Mar 2022

Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu

Research Collection School Of Computing and Information Systems

This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processed on a specific machine, defined as: R|rj,eij,STsd|Cmax. The objective is first to maximize the number of processed jobs, then minimize the maximum completion time (makespan), and finally minimize the maximum completion times of the non-bottleneck machines. A mixed-integer programming (MIP) model is proposed as a solution approach …

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Efficient Certificateless Multi-Copy Integrity Auditing Scheme Supporting Data Dynamics, Lei Zhou, Anmin Fu, Guomin Yang, Huaqun Wang, Yuqing Zhang Mar 2022

Efficient Certificateless Multi-Copy Integrity Auditing Scheme Supporting Data Dynamics, Lei Zhou, Anmin Fu, Guomin Yang, Huaqun Wang, Yuqing Zhang

Research Collection School Of Computing and Information Systems

To improve data availability and durability, cloud users would like to store multiple copies of their original files at servers. The multi-copy auditing technique is proposed to provide users with the assurance that multiple copies are actually stored in the cloud. However, most multi-replica solutions rely on Public Key Infrastructure (PKI), which entails massive overhead of certificate computation and management. In this article, we propose an efficient multi-copy dynamic integrity auditing scheme by employing certificateless signatures (named MDSS), which gets rid of expensive certificate management overhead and avoids the key escrow problem in identity-based signatures. Specifically, we improve the classic …

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Improving Utilization Rate Of Semi-Parallel Successive Cancellation Architecture For Polar Codes Using 2-Bit Decoding, Dinesh Kumar Devadoss, Shantha Selva Kumari Rama Packiam Mar 2022

Improving Utilization Rate Of Semi-Parallel Successive Cancellation Architecture For Polar Codes Using 2-Bit Decoding, Dinesh Kumar Devadoss, Shantha Selva Kumari Rama Packiam

Turkish Journal of Electrical Engineering and Computer Sciences

Polar codes are the capacity-achieving error-correcting code proved to be a significant invention in coding theory. It can achieve channel capacity at infinite code length N due to its explicit code construction. However, the processing complexity along with the higher latency due to successive cancellation (SC) decoding is being a major design issue, which reduces the utilization rate in the decoder architectures. This paper presents a modified semi-parallel architecture for decoding polar code with a better decoding latency. Precomputation and look-ahead techniques are used to generate two bits in the final stage. Pipelined partial-sum unit with a less critical path …

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Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft Mar 2022

Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft

Turkish Journal of Electrical Engineering and Computer Sciences

The massive use of social media causes rapid information dissemination that amplifies harmful messages such as fake news. Fake-news is misleading information presented as factual news that is generally used to manipulate public opinion. In particular, fake news related to COVID-19 is defined as 'infodemic' by World Health Organization. An infodemic is a misleading information that causes confusion which may harm health. There is a high volume of misinformation about COVID-19 that causes panic and high stress. Therefore, the importance of development of COVID-19 related fake news identification model is clear and it is particularly important for Turkish language from …

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Event-Related Microblog Retrieval In Turkish, Çağri Toraman Mar 2022

Event-Related Microblog Retrieval In Turkish, Çağri Toraman

Turkish Journal of Electrical Engineering and Computer Sciences

Microblogs, such as tweets, are short messages in which users are able to share any opinion and information. Microblogs are mostly related to real-life events reported in news articles. Finding event-related microblogs is important to analyze online social networks and understand public opinion on events. However, finding such microblogs is a challenging task due to the dynamic nature of microblogs and their limited length. In this study, assuming that news articles are given as queries and microblogs as documents, we find event-related microblogs in Turkish. In order to represent news articles and microblogs, we examine encoding methods, namely traditional bag-of-words …

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Identification Of Gain And Phase Margins Based Robust Stability Regions For Atime-Delayed Micro-Grid System Including Fractional-Order Controller In Presenceof Renewable Power Generation, Hakan Gündüz, Şahi̇n Sönmez, Saffet Ayasun Mar 2022

Identification Of Gain And Phase Margins Based Robust Stability Regions For Atime-Delayed Micro-Grid System Including Fractional-Order Controller In Presenceof Renewable Power Generation, Hakan Gündüz, Şahi̇n Sönmez, Saffet Ayasun

Turkish Journal of Electrical Engineering and Computer Sciences

This study examines the gain and phase margins (GPMs) based robust stability margins in the parameter space of fractional order proportional-integral (FOPI) controller for a micro-grid (MG) system with communication time delays. Fluctuations in renewable energy sources (RESs), uncertainties in parameters of system components and communication delays could adversely affect the dynamical analysis and frequency stability of the MG system. Such a MG system has an interval characteristic due to the parametric variations and the interval transfer functions defined by Kharitonov's theorem, which presents a solution for checking of robust stability. Therefore, this study addresses the robust stability regions containing …

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Removing The Veil: Shining Light On The Lack Of Inclusivity In Cybersecurity Education For Students With Disabilities, Felicia Hellems, Sajal Bhatia Mar 2022

Removing The Veil: Shining Light On The Lack Of Inclusivity In Cybersecurity Education For Students With Disabilities, Felicia Hellems, Sajal Bhatia

School of Computer Science & Engineering Faculty Publications

There are currently over one billion people living with some form of disability worldwide. The continuous increase in new technologies in today's society comes with an increased risk in security. A fundamental knowledge of cybersecurity should be a basic right available to all users of technology. A review of literature in the fields of cybersecurity, STEM, and computer science (CS) has revealed existent gaps regarding educational methods for teaching cybersecurity to students with disabilities (SWD's). To date, SWD's are largely left without equitable access to cybersecurity education. Our goal is to identify current educational methods being used to teach SWD's …

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Monocular Pose Estimation For Automated Aerial Refueling Via Perspective-N-Point, James C. Lynch Mar 2022

Monocular Pose Estimation For Automated Aerial Refueling Via Perspective-N-Point, James C. Lynch

Theses and Dissertations

Any Automated Aerial Refueling (AAR) solution requires the quick and precise estimation of the relative position and rotation of the two aircraft involved. This is currently accomplished using stereo vision techniques augmented by Iterative Closest Point (ICP), but requires post-processing to account for environmental factors such as boom occlusion. This paper proposes a monocular solution, combining a custom-trained single-shot object detection Convolutional Neural Network (CNN) and Perspective-n-Point (PnP) estimation to calculate a pose estimate with a single image. This solution is capable of pose estimation at contact point (22m) within 7cm of error and a rate of 10Hz, regardless of …

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Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller Mar 2022

Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller

Theses and Dissertations

Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …

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Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice Mar 2022

Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice

Theses and Dissertations

We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …

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The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold Mar 2022

The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold

Theses and Dissertations

Traditional control mechanisms restrict human input on the displays in 5th generation aircraft. This research explored methods for enhancing pilot interaction with large, information dense cockpit displays; specifically, the effects of visual feedback and control button configuration when augmenting cursor control with head tracking technology. Previous studies demonstrated that head tracking can be combined with traditional cursor control to decrease selection times but can increase pilot mental and physical workload. A human subject experiment was performed to evaluate two control button configurations and three visual feedback conditions. A Fitts Law analysis was performed to create predictive models of selection time …

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