Computer Engineering Commons^™

Consensus-Based Virtual Leader Tracking Algorithm For Flight Formation Control Of Swarm Uavs, Berat Yıldız, Akif Durdu, Ahmet Kayabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

Technological developments in industrial areas also impact unmanned aerial vehicles (UAVs). Recent improvements in both software and hardware have significantly increased the use of many UAVs in social and military fields. In particular, the widespread use of these vehicles in social areas such as entertainment, shipping, transportation, and delivery and military areas such as surveillance, tracking, and offensive measures has accelerated the research on swarm systems. This study examined the previous investigations on swarm UAVs and aimed to create a more efficient algorithm. The effectiveness of the proposed algorithm was compared with other leader-based applications. A swarm consisting of 5 …

Cascade Controller Design Via Controller Synthesis For Load Frequency Control Of Electrical Power Systems, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

The regulation of tie-line electricity flow and frequency of electrical power systems (EPS) is crucial for ensuring their robustness to parameter changes and efficient management of disturbances. To this end, a novel cascade control design approach utilizing a serial Proportional-Integral-Derivative controller with a filter (PIDF) is proposed in this paper. The parameters of the controllers are derived analytically, and it is employed in both loops of the cascade control system to regulate the Load Frequency Control (LFC) of EPS. The implementation of PIDF controllers in both loops is utilized in the cascade control scheme for various power systems featuring different …

Atomic Comagnetometer Gyroscopes For Inertial Navigation Systems: A Review, Murat Salim Karabinaoglu, Bekir Çakir, Mustafa Engin Başoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, developments in quantum sensing, laser, and atomic sensor technologies have also enabled advancement in the field of quantum navigation. Atomic-based gyroscopes have emerged as one of the most critical atomic sensors in this respect. In this review, a brief technology statement of spin exchange relaxation free (SERF) and nuclear magnetic resonance (NMR) type atomic comagnetometer gyroscope (CG) is presented. Related studies in the literature have been gathered, and the fundamental compositions of CGs with technical basics are presented. A comparison of SERF and NMR CGs is provided. A basic simulation of SERF CG was carried out because …

Uncovering And Mitigating Spurious Features In Domain Generalization, Saeed Karimi, Hamdi̇ Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Domain generalization (DG) techniques strive to attain the ability to generalize to an unfamiliar target domain solely based on training data originating from the source domains. Despite the increasing attention given to learning from multiple training domains through the application of various forms of invariance across those domains, the enhancements observed in comparison to ERM are nearly insignificant under specified evaluation rules. In this paper, we demonstrate that the disentanglement of spurious and invariant features is a challenging task in conventional training since ERM simply minimizes the loss and does not exploit invariance among domains. To address this issue, we …

Lower Data Attacks On Advanced Encryption Standard, Orhun Kara

Turkish Journal of Electrical Engineering and Computer Sciences

The Advanced Encryption Standard (AES) is one of the most commonly used and analyzed encryption algorithms. In this work, we present new combinations of some prominent attacks on AES, achieving new records in data requirements among attacks, utilizing only 2 4 and 2 16 chosen plaintexts (CP) for 6-round and 7-round AES 192/256, respectively. One of our attacks is a combination of a meet-in-the-middle (MiTM) attack with a square attack mounted on 6-round AES-192/256 while another attack combines an MiTM attack and an integral attack, utilizing key space partitioning technique, on 7-round AES-192/256. Moreover, we illustrate that impossible differential (ID) …

Spatiotemporal Reaction Dynamics Control In Two-Photon Polymerization For Enhancing Writing Characteristics, Aofei Mao, Sarah Fess, Nada Kraiem, P. Li, Zhipeng P. Wu, Qiuchi Zhu, Xi Huang, Peixun Fan, Bai Cui, Jean-Francois Silvain, Suxing Hu, Mitchell Anthamatten, Sean P. Regan, David Harding, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

Since 2001, 3D microfabrication based on two-photon polymerization (TPP) has drawn extensive attention and interest in biology, optics, photonics, material science, and high-energy physics. The in-volume fabrication capability due to the threshold behavior of two-photon absorption enables TPP higher flexibility compared with other nanofabrication techniques. However, as determined by the in-volume fabrication feature as well as various reaction dynamics, the writing characteristics of TPP, such as throughput, accuracy, surface quality, and fabrication capability, are still limited. Herein, a comprehensive study is performed on the spatiotemporal behavior of reaction dynamics during TPP fabrication, mainly focusing on spatiotemporal characteristics of radical diffusion, …

A Deep Learning Convolutional Neural Network For Antenna Near-Field Prediction And Surrogate Modeling, Md Rayhan Khan, Constantinos L. Zekios, Shubhendu Bhardwaj, Stavros V. Georgakopoulos

Department of Electrical and Computer Engineering: Faculty Publications

This study investigates the use of deep learning techniques for building a generalized surrogate model that can accurately and very efficiently predict antenna performance parameters. Notably, we focus on applications where a substantial amount of simulation time is required and prior data is available for deep learning use. Specifically, for these applications, we introduce deep learning models that efficiently and reliably model the near-field of the antenna. These models, in turn, accurately predict far-field properties and essential antenna metrics, such as the reflection coefficient. To demonstrate the efficiency of our method, the widely used rectangular patch antenna is considered, encompassing …

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …

A Study Of Random Partitions Vs. Patient-Based Partitions In Breast Cancer Tumor Detection Using Convolutional Neural Networks, Joshua N. Ramos

Master's Theses

Breast cancer is one of the deadliest cancers for women. In the US, 1 in 8 women will be diagnosed with breast cancer within their lifetimes. Detection and diagnosis play an important role in saving lives. To this end, many classifiers with varying structures have been designed to classify breast cancer histopathological images. However, randomly partitioning data, like many previous works have done, can lead to artificially inflated accuracies and classifiers that do not generalize. Data leakage occurs when researchers assume that every image in a dataset is independent of each other, which is often not the case for medical …

Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson

Dissertations

Our co-authored research ‘Steminism: Analyzing Factors That Improve Retention for Women as STEM Majors’ analyzed factors that contributed to the retention of women in science, technology, engineering, and mathematics (STEM) programs at Missouri University of Science & Technology (Missouri S&T). Women make up half of the US population, and while careers in (STEM) are an integral part of the US economy, women are underrepresented in these career fields. The purpose of our dissertation is to address the underrepresentation of women in STEM majors. Our methodology included homogeneous sampling to collect qualitative data. More specifically, we consulted with academic advisors and …

A Systematic Survey On 5g And 6g Security Considerations, Challenges, Trends, And Research Areas, Paul Scalise, Matthew Boeding, Hamid Sharif, Joseph Delloiacovo, John Reed

Department of Electrical and Computer Engineering: Faculty Publications

With the rapid rollout and growing adoption of 3GPP 5thGeneration (5G) cellular services, including in critical infrastructure sectors, it is important to review security mechanisms, risks, and potential vulnerabilities within this vital technology. Numerous security capabilities need to work together to ensure and maintain a sufficiently secure 5G environment that places user privacy and security at the forefront. Confidentiality, integrity, and availability are all pillars of a privacy and security framework that define major aspects of 5G operations. They are incorporated and considered in the design of the 5G standard by the 3rd Generation Partnership Project (3GPP) with the goal …

Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley

Dissertations and Theses

This thesis outlines the design of an IQ Test Bench that allows for experimentation of quadrature modulation techniques. Quadrature modulation utilizes two signals I and Q, 90° out of phase from each other, to greatly increase communication data rates. Using Desmos, a thorough mathematical analysis of waveform mixing is presented, and constellation diagrams are plotted from the results. From this an ancient fire signaling technique known as the Polybius Square is encoded into the system. The IQ Test Bench is built from fundamental components that would be contained within an RFFE: a local oscillator and two frequency mixers. The LO …

Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …

Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions were developed with different objective functions, namely a reduction in the total remaining queue and fair distribution of the remaining queue after each signal cycle. Our framework contains two distinct stages. The initial stage applies two distinct MILP methodologies, while the subsequent stage employs a neighborhood search method to further reduce the delays associated with the green signal timings derived from the first stage. Ultimately, to evaluate their effectiveness across various intersections, we …

Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu

Turkish Journal of Electrical Engineering and Computer Sciences

It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …

Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi

Turkish Journal of Electrical Engineering and Computer Sciences

In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown …

Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …

Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a novel online and adaptive truncation method is proposed for differentially private Bayesian online estimation of a static parameter regarding a population. A local differential privacy setting is assumed where sensitive information from individuals is collected on an individual level and sequentially. The inferential aim is to estimate, on the fly, a static parameter regarding the population to which those individuals belong. We propose sequential Monte Carlo to perform online Bayesian estimation. When individuals provide sensitive information in response to a query, it is necessary to corrupt it with privacy-preserving noise to ensure the privacy of those …

Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, subcarrier coordinate interleaving (CI) is implemented to orthogonal frequency division multiplexing (OFDM) systems with the aim of both enhancing the error performance and reducing the implementation complexity. To this end, the modulated symbols are independently chosen from a modified M-ary amplitude-shift keying signal constellation under a specific CI strategy. In addition to doubling the diversity level of the original OFDM scheme, the adopted CI approach also drastically reduces the inverse fast Fourier transform (IFFT) size at the transmit side by guaranteeing the first half of the input vector to be identical with the second half at the …

Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …

Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a fractional delay-dependent load frequency control design approach for a single-area power system with communication delay based on gain and phase margin specifications. In this approach, the closed-loop reference transfer function relies on the delayed Bode’s transfer function. The gain and phase margin specifications are established in order to optimize the reference model based on three time-domain performance indices. Here, a category of fractional-order model is employed to describe the single-area power system incorporating communication delay. The controller parameters are determined using the fractional-order system model and optimal closed-loop reference model. Then, a delay-dependent control mechanism is …

Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in deep learning, increased availability of large-scale datasets, and improvement of accelerated graphics processing units facilitated creation of an unprecedented amount of synthetically generated media content with impressive visual quality. Although such technology is used predominantly for entertainment, there is widespread practice of using deepfake technology for malevolent ends. This potential for malicious use necessitates the creation of detection methods capable of reliably distinguishing manipulated video content. In this work we aim to create a learning-based detection method for synthetically generated videos. To this end, we attempt to detect spatiotemporal inconsistencies by leveraging a learning-based magnification-inspired feature manipulation …

Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …

Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy

Turkish Journal of Electrical Engineering and Computer Sciences

Local differential privacy (LDP) has recently emerged as an accepted standard for privacy-preserving collection of users’ data from smartphones and IoT devices. In many practical scenarios, users’ data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user’s privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: …

A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new extended version of the reaction force observer (RFOB) for high-precision motion control systems. The RFOB has been proven to be useful for many applications in the literature. However, because of the low-pass filter present inside of the RFOB, it has certain limitations. In this study, a new algorithm is proposed to compensate for filtering-based errors in the classical RFOB structure. The algorithm includes the differentiation of the observed force and scaling with a proper value. However, since the force has a noisy nature, differentiation also affects the signal’s stability and performance. To resolve this issue, …

Room Temperature Polaritonic Soft-Spin Xy Hamiltonian In Organic–Inorganic Halide Perovskites, Kai Peng, Wei Li, Natalia G. Berloff, Xiang Zhang, Wei Bao

Department of Electrical and Computer Engineering: Faculty Publications

Exciton–polariton condensates, due to their nonlinear and coherent characteristics, have been employed to construct spin Hamiltonian lattices for potentially studying spin glass, critical dephasing, and even solving optimization problems. Here, we report the room-temperature polariton condensation and polaritonic soft-spin XY Hamiltonian lattices in an organic–inorganic halide perovskite microcavity. This is achieved through the direct integration of highquality single-crystal samples within the cavity. The ferromagnetic and antiferromagnetic couplings in both one- and two-dimensional condensate lattices have been observed clearly. Our work shows a nonlinear organic–inorganic hybrid perovskite platform for future investigations as polariton simulators.

Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish

Theses and Dissertations

Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …

Editorial: Frontiers In Lasers And Applications, John T. Fourkas, Koji Sugioka, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

When the laser was invented in 1960 by Theodore H.Maiman, the potential applications of this apparatus were far from clear. Indeed, even 4 years later, Maiman himself, in an interview with The New York Times, called the laser “a solution seeking a problem.”

Nearly 64 years later, it is safe to say that the laser’s influence on our everyday lives has been nearly beyond measure. Lasers are integral to CD and DVD readers, barcode readers, many computer printers, speed and distance sensors, and in various entertainment systems used in concerts and other events.

Tree Localization In A Plantation Using Ultra Wideband Signals, Akshat Verma

The Journal of Purdue Undergraduate Research

No abstract provided.

High Crystalline Quality Homoepitaxial Si-Doped Β-Ga2O3(010) Layers With Reduced Structural Anisotropy Grown By Hot-Wall Mocvd, D. Gogova, D. Q. Tran, V. Jokubavicius, L. Vines, M. Schubert, R. Yakimova, P. P. Paskov, V. Darakchieva

Department of Electrical and Computer Engineering: Faculty Publications

A new growth approach, based on the hot-wall metalorganic chemical vapor deposition concept, is developed for high-quality homoepitaxial growth of Si-doped single-crystalline β-Ga₂O₃ layers on (010)-oriented native substrates. Substrate annealing in argon atmosphere for 1 min at temperatures below 600 ^oC is proposed for the formation of epi-ready surfaces as a cost-effective alternative to the traditionally employed annealing process in oxygen-containing atmosphere with a time duration of 1 h at about 1000 ^oC. It is shown that the on-axis rocking curve widths exhibit anisotropic dependence on the azimuth angle with minima for in-plane direction …