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Full-Text Articles in Engineering

Study Of Spatial Reuse In Ieee 802.11ax Networks Over Propagation Models, Jun Peng, Paola Miller Jan 2023

Study Of Spatial Reuse In Ieee 802.11ax Networks Over Propagation Models, Jun Peng, Paola Miller

Electrical and Computer Engineering Faculty Publications

The paper studies the spatial reuse in IEEE 802.11ax networks over propagation models in ns3. The propagation models used in the study include the Friis model, the Nakagami model, and the combination of the two models. The results show that not all access points in an area benefit from the spatial reuse, and some even lose throughput. These results introduce the question of how to justify the spatial reuse for those access points who lose throughput, although the total throughput of the access points in the area benefits from the spatial reuse in general. The results also show that the …

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Improving The Flexibility And Robustness Of Machine Tending Mobile Robots, Richard Ethan Hollingsworth Jan 2023

Improving The Flexibility And Robustness Of Machine Tending Mobile Robots, Richard Ethan Hollingsworth

Theses and Dissertations

While traditional manufacturing production cells consist of a fixed base robot repetitively performing tasks, the Industry 5.0 flexible manufacturing cell (FMC) aims to bring Autonomous Industrial Mobile Manipulators (AIMMs) to the factory floor. Composed of a wheeled base and a robot arm, these collaborative robots (cobots) operate alongside people while autonomously performing tasks at different workstations. AIMMs have been tested in real production systems, but the development of the control algorithms necessary for automating a robot that is a combination of two cobots remains an open challenge before the large scale adoption of this technology occurs in industry. Currently popular …

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A Strong Scattering Solution With Applications To Remote Sensing Systems Modelling, Jonathan Blackledge Jan 2023

A Strong Scattering Solution With Applications To Remote Sensing Systems Modelling, Jonathan Blackledge

Conference papers

Although not always fully appreciated as such, the linear stationary convolution model for a signal and/or image, generated by the interaction of an incident wave field with an inhomogeneous medium, is based on the ‘weak scattering condition’, commonly referred to as the ‘Born approximation’. This approximation forms the basis for signal processing and analysis associated with applications over a broad range of frequencies. The Born approximation assumes that a scattering interaction is based on single scattering events alone and that the scattered field is therefore a weak field in comparison to the incident field. The physical limitations of such a …

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Printed-Dipole End-Fire Array For Mm-Wave Applications, Neeraj Kumar Maurya, Max Ammann Jan 2023

Printed-Dipole End-Fire Array For Mm-Wave Applications, Neeraj Kumar Maurya, Max Ammann

Conference papers

A novel curved printed-dipole element in an end-fire array for mmWave communication is presented. The curved dipole element is printed on both sides of a RO5880 substrate of 0.5mm thickness. The proposed antenna operates in the frequency bands n257, n258, and n261 (22.79 GHz - 29.7 GHz) and the 4-element array has a peak gain of 8.85 dBi.

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Fully 3d-Printed Hemispherical Dielectric Resonator Antenna For C-Band Applications, Jakub Przepiorowski, Irina Munina, Max Ammann, Daniel Trimble Jan 2023

Fully 3d-Printed Hemispherical Dielectric Resonator Antenna For C-Band Applications, Jakub Przepiorowski, Irina Munina, Max Ammann, Daniel Trimble

Conference papers

This paper investigates the 3D printing of a hemispherical dielectric resonator antenna (DRA) on a ground plane made from a 3D printed conductive material. The DRA is designed to operate in the C-band (3700 – 4200 MHz) and is intended for satellite communication (SATCOM) applications. The proposed antenna prototype achieved a -10 dB bandwidth of 12.2% with an average and peak gain of 4.69 dBi and peak gain of 5.39 dBi respectively.

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H2020 Auto-Dan Project: Enhance The Participation Of The Community To Demand Response By Providing The State-Of-The-Art Technological And Policy Solution, Rene Peeren, Dharmesh Dabhi, John Dalton Jan 2023

H2020 Auto-Dan Project: Enhance The Participation Of The Community To Demand Response By Providing The State-Of-The-Art Technological And Policy Solution, Rene Peeren, Dharmesh Dabhi, John Dalton

Conference papers

The growing demand for electricity in Europe has increased the need for a more flexible and sustainable power system. In recent years, Demand Response (DR) has emerged as a promising solution to meet this need, by providing an opportunity for residential and smaller commercial consumers to actively participate in the electricity market. This research paper investigates the potential for DR among the residential community and small commercial electricity consumers in Europe and identifies the technological barriers and drivers that impact consumer engagement with DR programs in Europe. The different DR opportunities are identified and validated at the six different demo …

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Quantum Classifiers For Video Quality Delivery, Tautvydas Lisas, Ruairí De Fréin Jan 2023

Quantum Classifiers For Video Quality Delivery, Tautvydas Lisas, Ruairí De Fréin

Conference papers

Classical classifiers such as the Support Vector Classifier (SVC) struggle to accurately classify video Quality of Delivery (QoD) time-series due to the challenge in constructing suitable decision boundaries using small amounts of training data. We develop a technique that takes advantage of a quantum-classical hybrid infrastructure called Quantum-Enhanced Codecs (QEC). We evaluate a (1) purely classical, (2) hybrid kernel, and (3) purely quantum classifier for video QoD congestion classification, where congestion is either low, medium or high, using QoD measurements from a real networking test-bed. Findings show that the SVC performs the classification task 4% better in the low congestion …

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Optimising Electric Vehicle Charging Infrastructure In Dublin Using Geecharge, Alexander Mutua Mutiso, Ruairí De Fréin, Ali Malik, Eliel Kibanza, Marco Sahbane, Maxime Pantel Jan 2023

Optimising Electric Vehicle Charging Infrastructure In Dublin Using Geecharge, Alexander Mutua Mutiso, Ruairí De Fréin, Ali Malik, Eliel Kibanza, Marco Sahbane, Maxime Pantel

Conference papers

Range anxiety poses a hurdle to the adoption of Electric Vehicles (EVs), as drivers worry about running out of charge without timely access to a Charging Point (CP). We present novel methods for optimising the distribution of CPs, namely, EV portacharge and GEECharge. These solutions distribute CPs in Dublin, in this paper, by considering the population density and Points Of Interest (POIs) or road traffic. The object of this paper is to (1) develop and evaluate methods to distribute CPs in Dublin city; (2) optimise CP allocation; (3) visualise paths in the graph network to show the most used roads …

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Architecting Future Multi-Modal Networks Coexistence, Generalization & Testbeds, Maqsood Ahamed Abdul Careem Jan 2023

Architecting Future Multi-Modal Networks Coexistence, Generalization & Testbeds, Maqsood Ahamed Abdul Careem

Legacy Theses & Dissertations (2009 - 2024)

Next Generation (xG) wireless networks are poised to revolutionize the way people, devices, data and processes sense, communicate, interact, and collectively enable a wide range of emerging applications, ranging from smart cities, connected healthcare, and advanced vehicular communication to extended reality. To facilitate this seamless interoperability, these networks need to evolve to accommodate and integrate multiple modalities in communication/ sensing technologies and spectrum, heterogeneous networks, trends in signal-processing (statistical, AI-driven, and distributed systems), centralized and distributed architectures, and device/ network hardware resources. However, to cater to the high-target metrics and wide-range of applications, these multi-modal networks must efficiently address multi-faceted …

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Oxidation Layer Formation On Aluminum Substrates With Surface Defects Using Molecular Dynamics Simulation, Emmanuel Olugbade, Hiep Pham, Yuchu He, Haicheng Zhou, Chulsoon Hwang, Jonghyun Park Jan 2023

Oxidation Layer Formation On Aluminum Substrates With Surface Defects Using Molecular Dynamics Simulation, Emmanuel Olugbade, Hiep Pham, Yuchu He, Haicheng Zhou, Chulsoon Hwang, Jonghyun Park

Electrical and Computer Engineering Faculty Research & Creative Works

Aluminum Oxide Layer Affects the Integrity of Electrical Contact and Can Contribute Adversely to Passive Intermodulation (PIM) Behavior in Radio Frequency (RF) Devices, necessitating a Need for Understanding its Formation Mechanism and Realistic Estimation of its Thickness. using ReaxFF Molecular Dynamics Simulation Technique, This Study Investigated the Impact of Surface Defects on Aluminum Oxide Layer Formation. Results Reveal that Crystallographic Orientation Did Not Affect the Kinetics of Oxidation Process of Aluminum. However, the Reaction Kinetics Increased Significantly with Surface Inhomogeneities Such as Cracks, Scratches, and Grain Boundaries. a Non-Uniform Oxide Layer with Thickness Variation in the Range of 72-77% Was …

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Chemical Classification By Monitoring Liquid Evaporation Using Extrinsic Fabry-Perot Interferometer With Microwave Photonics, Abhishek Prakash Hungund, Bohong Zhang, Anand Nambisan, Wassana Naku, Rex E. Gerald, Jie Huang Jan 2023

Chemical Classification By Monitoring Liquid Evaporation Using Extrinsic Fabry-Perot Interferometer With Microwave Photonics, Abhishek Prakash Hungund, Bohong Zhang, Anand Nambisan, Wassana Naku, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Identification of liquids is essential in chemical analysis, safety, environmental protection, quality control, and research. A novel liquid identification system based on Microwave Photonics (MWP) measured time transient evaporation signals is investigated. An extrinsic Fabry-Perot Interferometer (EFPI) based optical probe using single-mode fiber (SMF) is proposed to monitor evaporation of different liquids. The MWP system is used to measure the optical path changes during liquid evaporation due to its high sensitivity, selectivity, and Signal-to-Noise Ratio (SNR). The measured S21 continuous wave (CW) time Magnitude and Phase signals were processed to extract features such as histogram and Fast Fourier Transform (FFT) …

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Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria Jan 2023

Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria

Electrical and Computer Engineering Faculty Research & Creative Works

Recently, the utilization of Radio Frequency (RF) devices has increased exponentially over numerous vertical platforms. This rise has led to an abundance of Radio Frequency Interference (RFI) continues to plague RF systems today. The continued crowding of the RF spectrum makes RFI efficient and lightweight mitigation critical. Detecting and localizing the interfering signals is the foremost step for mitigating RFI concerns. Addressing these challenges, we propose a novel and lightweight approach, namely RaFID, to detect and locate the RFI by incorporating deep neural networks (DNNs) and statistical analysis via batch-wise mean aggregation and standard deviation (SD) calculations. RaFID investigates the …

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Mode-Decomposition-Based Equivalent Via (Mev) Model And Mev Model Application Range Analysis, Chaofeng Li, Kevin Cai, Muqi Ouyang, Manish Kizhakkeveettil Mathew, Mehdi Mousav, Bidyut Sen, Donghyun Kim Jan 2023

Mode-Decomposition-Based Equivalent Via (Mev) Model And Mev Model Application Range Analysis, Chaofeng Li, Kevin Cai, Muqi Ouyang, Manish Kizhakkeveettil Mathew, Mehdi Mousav, Bidyut Sen, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

The Mode-Decomposition-Based Equivalent Via (MEV) Model is Proposed in This Paper, which is a Physics-Based Equivalent Model for the High-Speed Channel Modeling. the Application Ranges of the MEV Model Are Analyzed by Varying Anti-Pad Radius, Via Radius, and Distance between the Parallel Plates for a Single Via with Multiple Layers. based on the S-Parameter Comparison with Full-Wave Simulations, the MEV Model is Useful for the Insertion Loss Calculation Up to 100 GHz. Meanwhile, the Return Loss from the MEV Model Shows a High Level of Correlation with Full-Wave Simulation Results Up to 70GHz, Even When the Anti-Pad Radius is Larger …

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Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based On Natural Organic Memristor, Jinhui Wang, Feng Zhao, Mohammed Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin Jan 2023

Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based On Natural Organic Memristor, Jinhui Wang, Feng Zhao, Mohammed Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin

Electrical and Computer Engineering Faculty Research & Creative Works

Three-dimensional environmentally sustainable neuromorphic computing system based on natural organic honey-memristor is proposed in this paper. The experimental results indicate the proposed systems have high inference accuracy over 90 % with device variation and nonlinearity. What is more, four conductance drift scenarios, ADC (Analog-to-Digital Converter) quantization effects, and different algorithms (VGG8 and DenseNet-40) are considered to further verify the proposed systems.

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Defending Ai-Based Automatic Modulation Recognition Models Against Adversarial Attacks, Haolin Tang, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Yanxiao Zhao Jan 2023

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 …

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Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp Jan 2023

Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp

Engineering Technology Faculty Publications

The Arduino platform has long been an efficient tool in teaching electrical engineering technology, electrical engineering, and computer science concepts in schools and universities and introducing new learners to programming and microcontrollers. Numerous Arduino projects are widely available through the open-source community, and they can help students to have hands-on experience in building circuits and programming electronics with a wide variety of topics that can make learning electrical prototyping fun. The educational fields of electrical engineering and electrical engineering technology need continuous updating to keep up with the continuous evolution of the computer system. Although the traditional Arduino platform has …

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Editorial: Internet Of Energy For Renewable Energy-Based Decarbonized Electrical Energy Systems, Onur Elma, Murat Kuzlu, Nasibeh Zohrabi Jan 2023

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.

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An Extendable High Step-Up Dc-Dc Converter For Renewable Energy Applications, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi Jan 2023

An Extendable High Step-Up Dc-Dc Converter For Renewable Energy Applications, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a high step-up DC-DC converter based on a switched-inductor-capacitor-diode (SLCD) cell is proposed. the proposed converter provides a high voltage gain, low voltage stress on the power switches and diodes, and a low input current ripple. Moreover, the proposed converter is extendable, meaning that the voltage gain could be further increased by using a higher number of proposed cells in the topology. the steady-state analysis and comparison of the proposed converter to the other existing converters are presented. a 200 W, 40 V to 380 V experimental setup is developed to verify the steady-state analysis of the …

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An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang Jan 2023

An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang

Turkish Journal of Electrical Engineering and Computer Sciences

In imaging systems, the mixed Poisson-Gaussian noise (MPGN) model can accurately describe the noise present. Total variation (TV) regularization-based methods have been widely utilized for Poisson-Gaussian removal with edge-preserving. However, TV regularization sometimes causes staircase artifacts with piecewise constants. To overcome this issue, we propose a new model in which the regularization term is represented by a combination of total variation and high-order total variation. We study the existence and uniqueness of the minimizer for the considered model. Numerically, the minimization problem can be efficiently solved by the alternating minimization method. Furthermore, we give rigorous convergence analyses of our algorithm. …

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Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu Jan 2023

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 …

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A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan Jan 2023

A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a type-2 fuzzy logic-based decision support system comprising clinical examination and blood test results that health professionals can use in addition to existing methods in the diagnosis of COVID-19 has been developed. The developed system consists of three fuzzy units. The first fuzzy unit produces COVID-19 positivity as a percentage according to the respiratory rate, loss of smell, and body temperature values, and the second fuzzy unit according to the C-reactive protein, lymphocyte, and D-dimer values obtained as a result of the blood tests. In the third fuzzy unit, the COVID-19 positivity risks according to the clinical …

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Transmission Network Planning For Realistic Egyptian Systems Via Encircling Prey Based Algorithms, Abdullah M. Shaheen, Ragab Elsehiemy, Mohammed Kharrich, Salah Kamel Jan 2023

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 …

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An Effective Hilbert-Huang Transform-Based Approach For Dynamic Eccentricity Fault Diagnosis In Double-Rotor Double-Sided Stator Structure Axial Flux Permanent Magnet Generator Under Various Load And Speed Conditions, Makan Torabi, Yousef Alinejad Beromi Jan 2023

An Effective Hilbert-Huang Transform-Based Approach For Dynamic Eccentricity Fault Diagnosis In Double-Rotor Double-Sided Stator Structure Axial Flux Permanent Magnet Generator Under Various Load And Speed Conditions, Makan Torabi, Yousef Alinejad Beromi

Turkish Journal of Electrical Engineering and Computer Sciences

Eccentricity fault in double-sided axial flux permanent magnet generator is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic, especially at the initial stages of the fault occurrence. In addition, one of the most important problems in any fault diagnosis approach is the investigation of load and speed variation on the proposed indices. To overcome the aforementioned difficulty and problems, this paper adopts a novelty detection algorithm based on Hilbert-Huang transform (HHT) which is a time-frequency signal analysis approach based on empirical mode decomposition and the Hilbert transform. It is …

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Early Diagnosis Of Pancreatic Cancer By Machine Learning Methods Using Urine Biomarker Combinations, İrem Acer, Firat Orhan Bulucu, Semra İçer, Fatma Lati̇foğlu Jan 2023

Early Diagnosis Of Pancreatic Cancer By Machine Learning Methods Using Urine Biomarker Combinations, İrem Acer, Firat Orhan Bulucu, Semra İçer, Fatma Lati̇foğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The most common type of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC), which accounts for the vast majority of pancreatic cancers. The five-year survival rate for PDAC due to late diagnosis is 9%. Early diagnosed PDAC patients survive longer than patients diagnosed at a more advanced stage. Biomarkers can play an essential role in the early detection of PDAC to assist the health professional. Machine learning and deep learning methods are used with biomarkers obtained in recent studies for diagnostic purposes. In order to increase the survival rates of PDAC patients, early diagnosis of the disease with a noninvasive test …

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Two New Mathematical Models For Two Level Electricity Network Design With Distributed Generation, Burçi̇n Çakir Erdener, Berna Dengi̇z, Zülal Güngör, İmdat Kara Jan 2023

Two New Mathematical Models For Two Level Electricity Network Design With Distributed Generation, Burçi̇n Çakir Erdener, Berna Dengi̇z, Zülal Güngör, İmdat Kara

Turkish Journal of Electrical Engineering and Computer Sciences

In the new millennium, traditional electrical power systems have undergone a significant change driven by a set of requirements arising from evolving and changing technology. Thus, fundamental changes have occurred in the way electrical energy is produced, transmitted, and distributed. This situation has revealed the need to expand existing networks or to establish new networks. The available literature revealed that particular attention to the latter one is still limited due to the complexity of the power system. The purpose of this study is to contribute to the body of literature that tries to address the gap at overall design of …

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Basismap: Sequence-Based Similarity Search For Geomagnetic Positioning, Tevfi̇k Kadioğlu, Burcu Erkmen Jan 2023

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 …

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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 Jan 2023

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 …

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Variational Autoencoder-Based Anomaly Detection In Time Series Data For Inventory Record Inaccuracy, Hali̇l Arğun, Sadetti̇n Emre Alpteki̇n Jan 2023

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 …

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Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler Jan 2023

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 …

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Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu Jan 2023

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 …

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