Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- TÜBİTAK (3106)
- Missouri University of Science and Technology (1815)
- Chinese Chemical Society | Xiamen University (1278)
- Old Dominion University (899)
- Air Force Institute of Technology (887)
-
- University of Central Florida (581)
- New Jersey Institute of Technology (544)
- Embry-Riddle Aeronautical University (472)
- Portland State University (391)
- University of Nebraska - Lincoln (373)
- Technological University Dublin (340)
- California Polytechnic State University, San Luis Obispo (337)
- University of Kentucky (263)
- University of New Mexico (260)
- Tashkent State Technical University (259)
- University of Nevada, Las Vegas (250)
- University of Dayton (246)
- University of Arkansas, Fayetteville (244)
- Brigham Young University (222)
- Louisiana State University (199)
- Marquette University (199)
- Purdue University (177)
- Michigan Technological University (171)
- Wright State University (167)
- Clemson University (166)
- Utah State University (160)
- University of Texas at El Paso (158)
- University of South Carolina (154)
- University of South Florida (152)
- University of Dar es Salaam (139)
- Keyword
-
- Machine learning (282)
- Optimization (219)
- Deep learning (205)
- Classification (127)
- Department of Electrical Engineering (127)
-
- Image processing (120)
- Machine Learning (117)
- Applied sciences (110)
- Algorithms (97)
- Signal processing (96)
- Simulation (95)
- Daniel Felix Ritchie School of Engineering and Computer Science (92)
- Neural networks (92)
- #antcenter (89)
- Computer vision (88)
- Modeling (85)
- Engineering (84)
- Artificial intelligence (82)
- Genetic algorithm (81)
- Electrical Engineering (80)
- Security (77)
- Deep Learning (74)
- Renewable energy (72)
- FPGA (70)
- Electrical and Computer Engineering (68)
- Control (67)
- Microgrid (66)
- Smart grid (66)
- Particle swarm optimization (65)
- Reinforcement learning (64)
- Publication Year
- Publication
-
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Journal of Electrochemistry (1278)
- Theses and Dissertations (1204)
- Electrical and Computer Engineering Faculty Research & Creative Works (1191)
- Electronic Theses and Dissertations (701)
-
- Theses (422)
- Masters Theses (407)
- Electrical & Computer Engineering Theses & Dissertations (349)
- Electrical and Computer Engineering Faculty Publications (348)
- Electrical & Computer Engineering Faculty Publications (300)
- Journal of Digital Forensics, Security and Law (290)
- Dissertations (261)
- Electrical and Computer Engineering Faculty Publications and Presentations (244)
- Faculty Publications (241)
- Electrical and Computer Engineering ETDs (223)
- Department of Electrical and Computer Engineering: Faculty Publications (199)
- Doctoral Dissertations (189)
- Dissertations and Theses (185)
- Chemical Technology, Control and Management (175)
- Graduate Theses and Dissertations (169)
- Master's Theses (166)
- Electrical Engineering (164)
- Articles (162)
- Browse all Theses and Dissertations (156)
- Open Access Theses & Dissertations (154)
- USF Tampa Graduate Theses and Dissertations (146)
- Electrical and Computer Engineering Faculty Research and Publications (141)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (128)
- Electrical Engineering Faculty Publications (118)
- Tanzania Journal of Engineering and Technology (TJET) (111)
- Publication Type
- File Type
Articles 2341 - 2370 of 18150
Full-Text Articles in Entire DC Network
Optical Design Study Of A High-Resolution Spectrograph Utilizing Photonic Lanterns For A Large Fiber Array Telescope, Richard D'Alo
Optical Design Study Of A High-Resolution Spectrograph Utilizing Photonic Lanterns For A Large Fiber Array Telescope, Richard D'Alo
Graduate Thesis and Dissertation 2023-2024
Large area fiber array telescopes are a relatively modern development in the long history of telescope design and effectively create a single large equivalent aperture by combining many smaller unit telescopes at a fraction of the cost. In this study a spectrograph optical design is demonstrated that utilizes photonic lanterns in the input fiber feed for the Large Fiber Array Spectroscopic Telescope (LFAST) design concept, where photonic lanterns provide a simplified approach to the fiber feed originally proposed for LFAST. Conservation of etendue is applied to derive the relationship between slit size and photonic lantern ratio, and classical echelle spectrograph …
Utilizing Machine Learning Algorithm In Predicting The Power Conversion Efficiency Limit Of A Monolithically Perovskites/Silicon Tandem Structure, Moustafa Ganoub, Omar Elsaban, Sameh O. Abdellatif Dr, Khaled Kirah, Hani Ghali
Utilizing Machine Learning Algorithm In Predicting The Power Conversion Efficiency Limit Of A Monolithically Perovskites/Silicon Tandem Structure, Moustafa Ganoub, Omar Elsaban, Sameh O. Abdellatif Dr, Khaled Kirah, Hani Ghali
Electrical Engineering
Tandem structures have been introduced to the photovoltaics (PV) market to boost power conversion efficiency (PCE). Single-junction cells’ PCE, either in a homojunction or heterojunction format, are clipped to a theoretical limit associated with the absorbing material bandgap. Scaling up the single-junction cells to a multi-junction tandem structure penetrates such limits. One of the promising tandem structures is the perovskite over silicon topology. Si junction is utilized as a counter bare cell with perovskites layer above, under applying the bandgap engineering aspects. Herein, we adopt BaTiO3/CsPbCl3/MAPbBr3/CH3NH3PbI3/c-Si tandem structure to be investigated. In tandem PVs, various input parameters can be tuned …
Decarbonization Analysis For Thermal Generation And Regionally Integrated Large-Scale Renewables Based On Minutely Optimal Dispatch With A Kentucky Case Study, Donovin Lewis, Aron Patrick, Evan S. Jones, Rosemary E. Alden, Abdullah Al Hadi, Malcolm D. Mcculloch, Dan Ionel
Decarbonization Analysis For Thermal Generation And Regionally Integrated Large-Scale Renewables Based On Minutely Optimal Dispatch With A Kentucky Case Study, Donovin Lewis, Aron Patrick, Evan S. Jones, Rosemary E. Alden, Abdullah Al Hadi, Malcolm D. Mcculloch, Dan Ionel
Power and Energy Institute of Kentucky Faculty Publications
Decarbonization of existing electricity generation portfolios with large-scale renewable resources, such as wind and solar photo-voltaic (PV) facilities, is important for a transition to a sustainable energy future. This paper proposes an ultra-fast optimization method for economic dispatch of firm thermal generation using high granularity, one minute resolution load, wind, and solar PV data to more accurately capture the effects of variable renewable energy (VRE). Load-generation imbalance and operational cost are minimized in a multi-objective clustered economic dispatch problem with various generation portfolios, realistic generator flexibility, and increasing levels of VRE integration. The economic feasibility of thermal dispatch scenarios is …
Structural Transformations In Photo-Thermo-Refractive Glass For Hologram Recording, Roberto Alejandro Alvarez Aguirre
Structural Transformations In Photo-Thermo-Refractive Glass For Hologram Recording, Roberto Alejandro Alvarez Aguirre
Electronic Theses and Dissertations, 2020-2023
This dissertation focuses on the structural transformations in photo-thermo-refractive (PTR) glass that enable recording phase holograms for efficient transformation of optical beams and high resolution spectroscopy. PTR glass is a multicomponent silicate matrix doped with Ce, Ag, Sn and Sb. It is a holographic phase medium with the ability of permanent refractive index change after UV exposure and thermal development above 500°C due to the precipitation of a NaF crystalline phase. Electronic processes are studied by analyzing the structure of absorption and luminescence bands of PTR glass matrix and its dopants. We analyze the structural transformations in PTR glass from …
Active Photonic Integrated Devices And Circuits On Thin-Film Lithium Niobate Platform, Ehsan Ordouie
Active Photonic Integrated Devices And Circuits On Thin-Film Lithium Niobate Platform, Ehsan Ordouie
Electronic Theses and Dissertations, 2020-2023
This thesis delves into innovative active photonic integrated devices and circuits on the thin-film lithium niobate (TFLN) platform, focusing on their applications and potential future advancements. We introduce a new family of electrooptic modulators (EOMs), the Four-Phase Electrooptic Modulators (FEOMs), which are fabricated using the TFLN platform. These devices effectively mitigate bandwidth and dynamic-range constraints in optical communication systems by reducing dispersion penalties and common-mode noises. Their functionality is demonstrated in a photonic time-stretch system. A dual-polarization variant further exemplifies the mitigation of both dispersion penalties and common-mode noises in long-haul communication links, marking significant strides towards the practical implementation …
A Dlt Based Trust Framework For Iot Ecosystems, Tharindu Ranathunga
A Dlt Based Trust Framework For Iot Ecosystems, Tharindu Ranathunga
Theses
In the last ten years, the Internet of Things (IoT) has experienced significant growth and has become a critical aspect of digital transformation across various industries such as healthcare, manufacturing, energy and society more broadly. IoT systems are now integrated across these verticals, creating ecosystems supporting data-driven decision-making and autonomous processes. These ecosystems consist of IoT network components, network services, and network participants such as organisations, consumers, governments, and businesses. They need to be built on the principles of the next-generation internet, which is viewed as being highly adaptive and resilient, trustworthy, sustainable, open and human-centric. The provision of Trust …
Design, Modeling And Analysis Of An Ac-Ac Dual Active Bridge Converter, Kartikeya Jayadurga Prasad Veeramraju
Design, Modeling And Analysis Of An Ac-Ac Dual Active Bridge Converter, Kartikeya Jayadurga Prasad Veeramraju
Doctoral Dissertations
"The Solid-State Transformer (SST) is gaining attention as an alternative to conventional iron-core transformers in the power electronic community. The power industry's increasing demands for smaller size, higher efficiency, and greater energy density have made the SST an attractive option. Among various power electronic converter topologies, the Dual Active Bridge (DAB) has become popular for its bidirectional power flow capability and galvanic isolation, primarily in the DC application space. Advancements in semiconductor technologies have introduced new bidirectional switches, opening avenues for novel SST topologies. This research investigates the application of the DAB as a single-stage SST and focuses on advancements …
Introduction Of A Variable Inductance Transformer For The Design Of Resonant Power Converters, Angshuman Sharma
Introduction Of A Variable Inductance Transformer For The Design Of Resonant Power Converters, Angshuman Sharma
Doctoral Dissertations
"Magnetic integration is a hot topic in power electronics that concerns the use of a transformer's leakage and magnetizing inductances purposefully in isolated power electronic converters, thereby giving the opportunity to save the cost and footprint of any additional inductor. This is of prime interest, especially in CLLLC resonant converters which require up to three inductors. For a complete integration of these inductances, the concept of a variable inductance transformer (VIT) is introduced in this thesis. A VIT is an adaptive magnetic structure that facilitates an easy adjustment of both magnetizing and leakage inductances to meet their desired values. However, …
Physical Layer Authenticated Image Encryption For Iot Network Based On Biometric Chaotic Signature For Mpfrft Ofdm System, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek Hassan
Physical Layer Authenticated Image Encryption For Iot Network Based On Biometric Chaotic Signature For Mpfrft Ofdm System, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek Hassan
Research outputs 2022 to 2026
In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the multi-parameter fractional Fourier transform–Orthogonal frequency division multiplexing (MP-FrFT-OFDM) is suggested for secure image transmission over the IoT network. In addition, a new robust multi-cascaded chaotic modular fractional sine map (MCC-MF sine map) is designed and analyzed. Also, a new dynamic chaotic biometric signature (DCBS) generator based on combining the biometric signature and the proposed MCC-MF sine map random chaotic sequence output is also designed. The final output of the proposed DCBS generator is used as a dynamic secret key for the MPFrFT OFDM system in which …
Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch
Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch
Faculty Publications
Excerpt: Satnav SDRs present many benefits in terms of flexibility and configurability. However, due to the high bandwidth signals involved in satnav SDR processing, the software must be highly optimized for the host platform in order to achieve acceptable runtimes. Modules such as sample decoding, carrier replica generation, carrier wipeoff, and correlation are computationally intensive components that benefit from accelerations.
A Study On Peer-To-Peer Energy Trading Market In Low-Voltage Distribution Systems By Considering System Operation Criteria, Pikkanate Angaphiwatchawal
A Study On Peer-To-Peer Energy Trading Market In Low-Voltage Distribution Systems By Considering System Operation Criteria, Pikkanate Angaphiwatchawal
Chulalongkorn University Theses and Dissertations (Chula ETD)
This dissertation investigates the challenges and proposes solutions for enhancing the efficiency and resilience of power systems through peer-to-peer (P2P) energy trading markets, focusing on the context of Thailand. It emphasizes assessing P2P energy transactions to prevent overloading of distribution lines and voltage fluctuations. The study proposes a method to determine the allowable maximum trading power (MTP) for sellers and buyers, considering the operating conditions of the distribution system and forecast error data of photovoltaic (PV) generation and load consumption and leveraging real-time data and algorithms to adjust trading power based on network constraints, ensuring power exchange does not affect …
Small Objects Detection In Aerial Imagery For System-On-Chip Fpgas, Wimonthip Saenprasert
Small Objects Detection In Aerial Imagery For System-On-Chip Fpgas, Wimonthip Saenprasert
Chulalongkorn University Theses and Dissertations (Chula ETD)
Unmanned aerial vehicles (UAVs) offer significant advantages in accessing remote or high-risk locations. Yet, they also present challenges concerning privacy and safety. Effective air traffic management is crucial for ensuring compliance with security regulations. The primary objective is to monitor the flight trajectories of target objects in the airspace, necessitating efficient object detection, especially for distant objects, to facilitate surveillance and preparedness for addressing potential threats. However, the current performance of existing models in detecting small objects is inadequate for real-time surveillance applications. This study advocates prioritizing object detection over precise prediction of object bounding box sizes. We propose a …
Evaluating The Impact Of Increased Cycling On Thermal Power Plants Due To Wind Energy Penetration In The Midwest: A Case Study, Joscelyne Larson
Evaluating The Impact Of Increased Cycling On Thermal Power Plants Due To Wind Energy Penetration In The Midwest: A Case Study, Joscelyne Larson
Electronic Theses and Dissertations
One of the most significant shifts in the mix of U.S. electricity generation over the past few years has been the rapid expansion of renewable energy resources, especially solar and wind. However, fossil fuels are still necessary to fulfill the world’s energy requirements. Despite efforts to increase the use of renewable energy sources, these sources can be at times unreliable, causing countries around the world to continue to rely on base load units such as coal and natural gas. This decrease in fossil fuels and increase in renewable energy sources presents many complex issues in terms of power system planning, …
Evaluation Of Low-Cost Radiometer For Surface Reflectance Re-Trieval And Orbital Sensor’S Validation, Dinithi Siriwardana Pathiranage
Evaluation Of Low-Cost Radiometer For Surface Reflectance Re-Trieval And Orbital Sensor’S Validation, Dinithi Siriwardana Pathiranage
Electronic Theses and Dissertations
This paper evaluates the Arable Mark 2 sensor, an automated and low-cost radiometer, for its potential to retrieve surface reflectance data and validate orbital sensors such as the Landsat-8 (L8) Operational Land Imager (OLI) Level 2 product. While orbital sensors are widely used for monitoring solar radiation changes, managing natural resources, and understanding climatic trends, atmospheric effects can make it challenging to obtain accurate measurements. Equipped with multiple sensors, including long-wave and short-wave radiometers, the Arable Mark 2 sensor can measure upwelling and downwelling irradiance to calculate surface reflectance. To assess the accuracy and consistency of the Arable Mark 2 …
A New Approach To Linear Displacement Measurements Based On Hall Effect Sensors, İsmai̇l Yari̇çi̇, Yavuz Öztürk
A New Approach To Linear Displacement Measurements Based On Hall Effect Sensors, İsmai̇l Yari̇çi̇, Yavuz Öztürk
Turkish Journal of Electrical Engineering and Computer Sciences
Since displacement is a vital variable to be considered in many industrial applications, displacement sensing devices have been extensively studied both theoretically and experimentally. There have been also many studies on Hall effect-based displacement measurement, but for many systems linearity still remains a problem. This paper discusses different approaches to calculate the magnetic field due to a cylindrical permanent magnet and proposes a new setup geometry with 2-Hall effect sensors and a permanent magnet between them to overcome the linearity problems. Furthermore, theoretical and experimental studies of the discussed displacement sensor were presented by focusing on the linear range and …
Architecting Future Multi-Modal Networks Coexistence, Generalization & Testbeds, Maqsood Ahamed Abdul Careem
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 …
Defending Ai-Based Automatic Modulation Recognition Models Against Adversarial Attacks, Haolin Tang, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Yanxiao Zhao
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 …
An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang
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. …
Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu
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 …
A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan
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 …
Transmission Network Planning For Realistic Egyptian Systems Via Encircling Prey Based Algorithms, Abdullah M. Shaheen, Ragab Elsehiemy, Mohammed Kharrich, Salah Kamel
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 …
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
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 …
Early Diagnosis Of Pancreatic Cancer By Machine Learning Methods Using Urine Biomarker Combinations, İrem Acer, Firat Orhan Bulucu, Semra İçer, Fatma Lati̇foğlu
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 …
Two New Mathematical Models For Two Level Electricity Network Design With Distributed Generation, Burçi̇n Çakir Erdener, Berna Dengi̇z, Zülal Güngör, İmdat Kara
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 …
Basismap: Sequence-Based Similarity Search For Geomagnetic Positioning, Tevfi̇k Kadioğlu, Burcu Erkmen
Basismap: Sequence-Based Similarity Search For Geomagnetic Positioning, Tevfi̇k Kadioğlu, Burcu Erkmen
Turkish Journal of Electrical Engineering and Computer Sciences
Indoor localization has become a popular topic with the development of location-based services (LBS) and indoor navigation systems. Beside these circumstances indoor positioning has been the focus of attention for researchers as the most important component of these applications. Many signals are used as distinguishable features for indoor positioning. RF-based Wi-Fi and BLE systems are the most popular ones and these have been preferred because of their high distinguishable feature. The use of geomagnetism, a natural signal found all over the world, has also been of interest to many researchers. Geomagnetic signals being distorted in the indoor area due to …
The Effects Of The Dielectric Substrate Thickness And The Loss Tangent On The Absorption Spectrum: A Comprehensive Study Considering The Resonance Type, The Ground Plane Coupling, And The Characterization Setup, Umut Köse, Evren Ekmekçi̇
The Effects Of The Dielectric Substrate Thickness And The Loss Tangent On The Absorption Spectrum: A Comprehensive Study Considering The Resonance Type, The Ground Plane Coupling, And The Characterization Setup, Umut Köse, Evren Ekmekçi̇
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, the effects of dielectric substrate thickness and the dielectric loss tangent on the absorption spectrum are investigated parametrically in S-band. The study has been conducted on two different absorber topologies, one is closed ring resonator (CRR) and the other is composed of a split ring resonator (SRR), to observe the effects on both LC - and dipole-type resonances. The studies on the substrate thickness have been performed both numerically and experimentally, whereas the studies on the dielectric loss tangent have been performed numerically. The results agree with the literature such that the substrate thickness has significant effects …
Variational Autoencoder-Based Anomaly Detection In Time Series Data For Inventory Record Inaccuracy, Hali̇l Arğun, Sadetti̇n Emre Alpteki̇n
Variational Autoencoder-Based Anomaly Detection In Time Series Data For Inventory Record Inaccuracy, Hali̇l Arğun, Sadetti̇n Emre Alpteki̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Retail companies monitor inventory stock levels regularly and manage them based on forecasted sales to sustain their market position. Inventory accuracy, defined as the difference between the warehouse stock records and the actual inventory, is critical for preventing stockouts and shortages. The root causes of inventory inaccuracy are the employee or customer theft, product damage or spoilage, and wrong shipments. In this paper, we aim at detecting inaccurate stocks of one of Turkey's largest supermarket chain using the variational autoencoder (VAE), which is an unsupervised learning method. Based on the findings, we showed that VAE is able to model the …
Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler
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 …
Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu
Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu
Turkish Journal of Electrical Engineering and Computer Sciences
In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically attempts to learn a mapping from the (visual) feature space to the semantic space in which the classes are represented by a list of semantically meaningful attributes. However, the fact that this mapping is learned without using instances of the test classes affects the performance of ZSL, which is known as the domain shift problem. In this study, we propose to apply the learning vector quantization (LVQ) algorithm …
An Optimized Deep Learning-Based Framework For Predicting Diabetes Mellitus Using Ffnn, Norhan S. Elmongy, Sally M. Elghamrawy, Amr M. T. Ali-Eldin, Ali I. Eldesouky
An Optimized Deep Learning-Based Framework For Predicting Diabetes Mellitus Using Ffnn, Norhan S. Elmongy, Sally M. Elghamrawy, Amr M. T. Ali-Eldin, Ali I. Eldesouky
Mansoura Engineering Journal
Diabetes mellitus (DM) is a major public health problem in Egypt, and the illness is regarded as a contemporary epidemic across the world. Diabetes is becoming more common, which is a cause for serious concern. As a result, precise and timely identification of the illness is critical. Health and research institutions have also recently expressed a serious interest in developing and implementing cutting-edge healthcare systems. Therefore, it is necessary to accurately and quickly identify the condition. To solve this issue, scientific research has been carried out, but the outcomes have fallen short. Four layers make up the proposed Diabetes mellitus …