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Articles 6001 - 6030 of 36823
Full-Text Articles in Engineering
Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple
Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple
Faculty Publications
Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from …
Encouraging Voluntary Government Action Via A Solar-Friendly Designation Program To Promote Solar Energy In The United States, Xue Gao, Casey I. Canfield, Tian Tang, Hunter Hill, Morgan Higman, John Cornwell
Encouraging Voluntary Government Action Via A Solar-Friendly Designation Program To Promote Solar Energy In The United States, Xue Gao, Casey I. Canfield, Tian Tang, Hunter Hill, Morgan Higman, John Cornwell
Engineering Management and Systems Engineering Faculty Research & Creative Works
Sustainable development requires an accelerated transition toward renewable energy. In particular, substantially scaling up solar photovoltaics (PV) adoption is a crucial component of reducing the impacts of climate change and promoting sustainable development. However, it is challenging to convince local governments to take action. This study uses a combination of propensity score matching (PSM) and difference-in-differences (DID) models to assess the effectiveness of a voluntary environmental program (VEP) called SolSmart that targets local governments to engage in solar-friendly practices to promote the local solar PV market in the United States. Via specific designation requirements and technical assistance, SolSmart simplifies the …
Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison
Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison
Engineering Faculty Articles and Research
Vast improvements in communications technology are possible if the conversion of digital information from optical to electric and back can be removed. Plasmonic devices offer one solution due to optical computing’s potential for increased bandwidth, which would enable increased throughput and enhanced security. Plasmonic devices have small footprints and interface with electronics easily, but these potential improvements are offset by the large device footprints of conventional signal regeneration schemes, since surface plasmon polaritons (SPPs) are incredibly lossy. As such, there is a need for novel regeneration schemes. The continuous, uniform, and unambiguous digital information encoding method is phase-shift-keying (PSK), so …
Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor
Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor
Electrical and Computer Engineering: Faculty Scholarship
Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …
Deep Learning-Based Low Complexity And High Efficiency Moving Object Detection Methods, Bingxin Hou
Deep Learning-Based Low Complexity And High Efficiency Moving Object Detection Methods, Bingxin Hou
Engineering Ph.D. Theses
Moving object detection (MOD) is the process of extracting dynamic foreground content from the video frames, such as moving vehicles or pedestrians, while discarding the nonmoving background. It plays an essential role in computer vision field. The traditional methods meet difficulties when applied in complex scenarios, such as videos with illumination changes, shadows, night scenes,and dynamic backgrounds. Deep learning methods have been actively applied to moving object detection in recent years and demonstrated impressive results. However, many existing models render superior detection accuracy at the cost of high computational complexity and slow inference speed. This fact has hindered the development …
Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari
Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari
College of Science & Mathematics Departmental Research
Ransomware is a developing menace that encrypts users’ files and holds the decryption key hostage until the victim pays a ransom. This particular class of malware has been in charge of extortion hundreds of millions of dollars every year. Adding to the problem, generating new variations is cheap. Therefore, new malware can detect antivirus and intrusion detection systems and evade them or manifest in ways to make themselves undetectable. We must first understand the characteristics and behavior of various varieties of ransomware to create and construct effective security mechanisms to combat them. This research presents a novel dynamic and behavioral …
Malware Binary Image Classification Using Convolutional Neural Networks, John Kiger, Shen-Shyang Ho, Vahid Heydari
Malware Binary Image Classification Using Convolutional Neural Networks, John Kiger, Shen-Shyang Ho, Vahid Heydari
College of Science & Mathematics Departmental Research
The persistent shortage of cybersecurity professionals combined with enterprise networks tasked with processing more data than ever before has led many cybersecurity experts to consider automating some of the most common and time-consuming security tasks using machine learning. One of these cybersecurity tasks where machine learning may prove advantageous is malware analysis and classification. To evade traditional detection techniques, malware developers are creating more complex malware. This is achieved through more advanced methods of code obfuscation and conducting more sophisticated attacks. This can make the manual process of analyzing malware an infinitely more complex task. Furthermore, the proliferation of malicious …
The Greenest Solar Power? Life Cycle Assessment Of Foam-Based Flexible Floatovoltaics, Koami Soulemane Hayibo, Pierce Mayville, Joshua M. Pearce
The Greenest Solar Power? Life Cycle Assessment Of Foam-Based Flexible Floatovoltaics, Koami Soulemane Hayibo, Pierce Mayville, Joshua M. Pearce
Electrical and Computer Engineering Publications
This study presents a life cycle analysis (LCA) of a 10 MW foam-based floatovoltaics (FPV) plant installed on Lake Mead, Nevada, U.S. A material inventory of the flexible crystalline silicon (c-Si)-based module involved massing and determination of material composition of the module's encapsulation layers with ATR/FTR spectroscopy and electron microscopy. The LCA was performed using SimaPro and the results were interpreted in terms of cumulative energy demands, energy payback time, global warming potential, GHG emissions, and water footprint including negative values for reduced evaporation. A sensitivity analysis was performed on the lifetime of the modules and the foam-based racking. The …
Adaptive Output Tracking Of Distributed Parameter Systems, İhsan Berk Altiner, Mustafa Doğan, Janset Daşdemi̇r
Adaptive Output Tracking Of Distributed Parameter Systems, İhsan Berk Altiner, Mustafa Doğan, Janset Daşdemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we consider the unknown trajectory tracking problem for stable distributed parameter systems. The main assumptions are that trajectory signals are generated by an unknown finite-dimensional exosystem that is a marginally stable system and the tracking error is available for measurement. In order to achieve perfect error regulation, a frequency estimator scheme is proposed to estimate unknown exosystem parameters, and the control law that is designed based on geometric output regulation theory is revisited. The success of the proposed method is demonstrated on a parabolic heat equation and a first-order hyperbolic partial differential equation.
Kemar Hats Head Orientation Directivity, Samuel D. Bellows, Timothy W. Leishman
Kemar Hats Head Orientation Directivity, Samuel D. Bellows, Timothy W. Leishman
Directivity
This directivity data set for a KEMAR head head-and-torso simulator (HATS) includes head orientations in 14 directions in 5° steps starting from 0° to 40° and then in 10° steps from 40° to 90°. The full spherical measurements followed at an a = 0.97 m radius with the mouth aperture at the spherical center. The sampling density and distribution followed the AES 5° dual-equiangular sampling standard, omitting the south pole (θ = 180°). Thus, each spherical directivity assessment included 36 polar-angle θ samples and 72 azimuthal-angle ϕ samples. The presented data include 22 1/3-octave bands, ranging from 80 Hz …
Hsp90 Inhibitors Modulate Sars-Cov-2 Spike Protein Subunit 1-Induced Human Pulmonary Microvascular Endothelial Activation And Barrier Dysfunction, Ruben Manuel Luciano Colunga Biancatelli, Pavel Solopov, Betsy W. Gregory, Yara Khodour, John D. Catravas
Hsp90 Inhibitors Modulate Sars-Cov-2 Spike Protein Subunit 1-Induced Human Pulmonary Microvascular Endothelial Activation And Barrier Dysfunction, Ruben Manuel Luciano Colunga Biancatelli, Pavel Solopov, Betsy W. Gregory, Yara Khodour, John D. Catravas
Bioelectrics Publications
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused more than 5 million deaths worldwide. Multiple reports indicate that the endothelium is involved during SARS-Cov-2-related disease (COVID-19). Indeed, COVID-19 patients display increased thrombophilia with arterial and venous embolism and lung microcapillary thrombotic disease as major determinants of deaths. The pathophysiology of endothelial dysfunction in COVID-19 is not completely understood. We have investigated the role of subunit 1 of the SARS-CoV-2 spike protein (S1SP) in eliciting endothelial barrier dysfunction, characterized dose and time relationships, and tested the hypothesis that heat shock protein 90 (HSP90) inhibitors would prevent and repair such injury. S1SP …
Microwave Hyperthermia Application With Bioimplant Single Slot Coaxial Antennadesign For Mouse Breast Cancer Treatment, Ahmet Ri̇fat Görgün, Cem Baytöre, Selçuk Çömlekçi̇, Mehmet İbrahi̇m Tuğlu, Adnan Kaya
Microwave Hyperthermia Application With Bioimplant Single Slot Coaxial Antennadesign For Mouse Breast Cancer Treatment, Ahmet Ri̇fat Görgün, Cem Baytöre, Selçuk Çömlekçi̇, Mehmet İbrahi̇m Tuğlu, Adnan Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a novel animal model for the breast cancer treatment which contains hyperthermia is proposed. For this main purpose a low cost, interstitial, bioimplant antenna by short ended single slot design is proposed to heat the cancerous tissues. Both the theoretical background of the proposed system and the simulation and measurement results of antenna design are presented. An artificial tissue phantom model has been created under laboratory conditions and then the utility of the proposed antenna has been tested on this model. Artificial tissues have been heated by 25W to (41-44 ? C) in a short time like …
Identification And Mitigation Of Non-Line-Of-Sight Path Effect Using Repeater Forhybrid Ultra-Wideband Positioning And Networking System, Gwo Chin Chung, Mohd. Aqmal Syafiq Kamarudin, It Ee Lee, Soo Fun Tan
Identification And Mitigation Of Non-Line-Of-Sight Path Effect Using Repeater Forhybrid Ultra-Wideband Positioning And Networking System, Gwo Chin Chung, Mohd. Aqmal Syafiq Kamarudin, It Ee Lee, Soo Fun Tan
Turkish Journal of Electrical Engineering and Computer Sciences
At least two decades ago, various applications have been proposed for the implementation of ultra-wideband (UWB) technology, but only a few of them are being realised such as radar detection, home networking, and indoor positioning. Although UWB positioning offers precise locality tracking, the accuracy of the estimation is greatly affected by the non-line-of-sight (NLOS) path effect. In this paper, we propose a hybrid indoor UWB positioning and networking system that utilises the existing repeater of the data network to eliminate the NLOS paths. A switching algorithm is written to identify the existence of NLOS paths based on received signal strength …
A Factor Graph Optimization Mapping Based On Normaldistributions Transform, Kedi Zhong, Yuansheng Liu, Jiansuo Yang, Ming Lu, Jun Zhang
A Factor Graph Optimization Mapping Based On Normaldistributions Transform, Kedi Zhong, Yuansheng Liu, Jiansuo Yang, Ming Lu, Jun Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
This paper aims to achieve highly accurate mapping results and real time pose estimation of autonomous vehicle by using the normal distribution transform (NDT) algoritm. A factor graph optimization algorithm (FGO-NDT) is proposed to address the poor real-time performance and pose drift errors of the NDT algorithm. Smooth point cloud data are obtained by multisensor calibration and data preprocessing. NDT registration is then used for lidar odometry and feature matching. The global navigation satellite system (GNSS) data and loop detection results are added to the factor graph framework as the pose constraint factors to optimize the pose trajectory and eliminate …
Independent Closed Loop Control Of Di/Dt And Dv/Dt For High Power Igbts, Osman Tanriverdi̇, Deni̇z Yildirim
Independent Closed Loop Control Of Di/Dt And Dv/Dt For High Power Igbts, Osman Tanriverdi̇, Deni̇z Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
As the insulated gate bipolar transistor (IGBT) modules have their own specific characteristic switching forms, their turn-on and turn-off times are changed according to practical applications. For the conventional gate drives, gate resistors are used to adjust the turn-on and turn-off times which change switching losses that have a significant amount in total losses. Collector current rate of change, $di_{C}/ dt$ and collector-emitter rate of change, $dv_{CE}/ dt$ are dependent on each other and they affect operating parameters in high power converters. Relations between current and voltages during the switching transitions are given and effects of the changes in electrical …
Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu
Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Centroid based clustering approaches, such as k-means, are relatively fast but inaccurate for arbitrary shape clusters. Fuzzy c-means with Mahalanobis distance can accurately identify clusters if data set can be modelled by a mixture of Gaussian distributions. However, they require number of clusters apriori and a bad initialization can cause poor results. Density based clustering methods, such as DBSCAN, overcome these disadvantages. However, they may perform poorly when the dataset is imbalanced. This paper proposes a clustering method, named clustering with density initialization and Bhattacharyya based merging based on the fuzzy clustering. The initialization is carried out by density estimation …
Calculating Influence Based On The Fusion Of Interest Similarity And Informationdissemination Ability, Shulin Cheng, Ziming Wang, Meng Qian, Shan Yang, Xin Zheng
Calculating Influence Based On The Fusion Of Interest Similarity And Informationdissemination Ability, Shulin Cheng, Ziming Wang, Meng Qian, Shan Yang, Xin Zheng
Turkish Journal of Electrical Engineering and Computer Sciences
With the popularization, in-depth development and application of the Internet, microblogs have become a mainstream social network platform. Several studies on social networks have conducted researches, and user influence evaluation is an important research hotspot. Most of the existing studies calculate user influence by improving PageRank and have achieved certain results. However, these studies ignored the fusion of users' interest theme similarity and information dissemination ability, and the analysis of interaction behaviors among users is not comprehensive. To address these issues, we propose a new microblog user influence algorithm called microblog user influence based on interest similarity and information dissemination …
Photonic Integrated Circuit-Assisted Optical Time-Domainreflectometer System, Mehmet Cengi̇z Onbaşli
Photonic Integrated Circuit-Assisted Optical Time-Domainreflectometer System, Mehmet Cengi̇z Onbaşli
Turkish Journal of Electrical Engineering and Computer Sciences
Optical time-domain reflectometers (OTDR) are photonic systems that consist of an interrogator, a receiver and a fiber optical cable and have applications in telecommunications, security, environmental monitoring, distributed temperature and strain sensing. Since OTDR systems are bulk optical setups that consume multiple Watts of power, have large mass and volume footprint and are vulnerable to thermal drift, deployment of OTDR systems in the field is expensive, complicated and may not necessarily yield accurate sensing results. Thus, a compact, low-power, inexpensive and thermal drift-free OTDR system needs to be developed for improving the accuracy and the viability of OTDR in the …
Critical Speed Calculation Of A Refurbishment Of 11mw Hydro Power Plant Unit, Ahmet Seli̇m Pehli̇van, Dario Kraljevic, Ivan Triplat, Beste Bahçeci̇
Critical Speed Calculation Of A Refurbishment Of 11mw Hydro Power Plant Unit, Ahmet Seli̇m Pehli̇van, Dario Kraljevic, Ivan Triplat, Beste Bahçeci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Hydro generator design is a significant issue in terms of safety, efficiency, and energy production sustainability. One of the most crucial issues about design criteria is to satisfy the needs of the project?s critical speed. In this work, the critical speed calculation of an 11 MW hydro power plant was investigated with several design steps. Numerical solution methodologies were implemented using ARMD?. A generator design was developed, and the implementation of the rotor was carried out in Antalya, Turkey. Vibration and displacements of the hydro generator are adequate. The generator unit is active for 3 years and have never encountered …
Determining Allowable Parametric Uncertainty In An Uncommon Quadrotormodel For Closed Loop Stability, Mehmet Baskin, Mehmet Kemal Leblebi̇ci̇oğlu
Determining Allowable Parametric Uncertainty In An Uncommon Quadrotormodel For Closed Loop Stability, Mehmet Baskin, Mehmet Kemal Leblebi̇ci̇oğlu
Turkish Journal of Electrical Engineering and Computer Sciences
In this article, control oriented uncertainty modeling of an uncommon quadrotor in hover is discussed. This quadrotor consists of two counter-rotating big rotors on longitudinal axis and two counter-rotating small tilt rotors on lateral axis. Firstly, approximate linear model of this vehicle around hover is obtained by using Newton--Euler formulation. Secondly, specific uncertainty is assigned to each parameter. Resulting uncertain model is converted into a linear fractional transformation framework for robustness analysis. Next, the most critical uncertain parameters in terms of robust stability in a proposed quadrotor model are investigated using $ \mu $ sensitivities. Finally, skewed-$ \mu $ analysis …
Performance Analysis And Feature Selection For Network-Based Intrusion Detectionwith Deep Learning, Serhat Caner, Nesli̇ Erdoğmuş, Yusuf Murat Erten
Performance Analysis And Feature Selection For Network-Based Intrusion Detectionwith Deep Learning, Serhat Caner, Nesli̇ Erdoğmuş, Yusuf Murat Erten
Turkish Journal of Electrical Engineering and Computer Sciences
An intrusion detection system is an automated monitoring tool that analyzes network traffic and detects malicious activities by looking out either for known patterns of attacks or for an anomaly. In this study, intrusion detection and classification performances of different deep learning based systems are examined. For this purpose, 24 deep neural networks with four different architectures are trained and evaluated on CICIDS2017 dataset. Furthermore, the best performing model is utilized to inspect raw network traffic features and rank them with respect to their contributions to success rates. By selecting features with respect to their ranks, sets of varying size …
Modeling And Evaluation Of Soc-Based Coordinated Ev Charging For Powermanagement In A Distribution System, Murat Akil, Emrah Dokur, Ramazan Bayindir
Modeling And Evaluation Of Soc-Based Coordinated Ev Charging For Powermanagement In A Distribution System, Murat Akil, Emrah Dokur, Ramazan Bayindir
Turkish Journal of Electrical Engineering and Computer Sciences
The importance of using clean energy in electrical energy generation and transportation network planning has recently increased due to carbon footprint rising. In this direction, the use of electric vehicles (EV), known as ultra-low carbon emission vehicles, has become widespread in addition to renewable energy sources (RES) such as wind and photovoltaic (PV) power generations. The trend of EVs to be preferred the primary means of transport has revealed the effects of charging an additional load on the grid. There is a need to create coordinated charging methods by considering the approaches for real-time charging models of EVs. In this …
Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz
Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
TV rating is a numeric estimate of the popularity of television programs. Forecasting TV ratings is considered an important asset for investment planning of media due to its potential of reducing the risks of future ventures. The aim of this study is to develop a machine learning model capable of efficiently forecasting the TV ratings of Turkish TV series in a practical manner. To this end, two prediction models were proposed for forecasting the TV ratings of television series, facilitating an extensive set of features. A contribution of this study is the inclusion of social media-based features using search trends …
Predictive Optimization Of Sliding Mode Control Using Recurrent Neural Paradigmfor Nonlinear Dfig-Wpgs During Distorted Voltage, Omar Busati, Xiangjie Liu
Predictive Optimization Of Sliding Mode Control Using Recurrent Neural Paradigmfor Nonlinear Dfig-Wpgs During Distorted Voltage, Omar Busati, Xiangjie Liu
Turkish Journal of Electrical Engineering and Computer Sciences
Dynamic characteristics of the doubly-fed induction generator (DFIG)-based wind power generation (WPGS) are fully nonlinear. Therefore, issues such as stability and achieving high efficiency, especially under harmonics behavior, are challenges that assess the control strategy reliability to find the perfect dynamic solution. This discussion offers a control strategy for the separated stator-port power using a predictive sliding mode strategy with a resonant function (PSMC-R) based on a deep recurrent neural network (DRNN). DRNN is formed as a low-order Taylor series formula. PSMC-R predicts the perfect switching surface path and regulates the distorted nonlinear DFIG with several dynamic aims. This approach …
Scattering Analyses Of Arbitrary Roughness From 2-D Perfectly Conductiveperiodic Surfaces With Moments Method, Yunus Emre Yamaç, Ahmet Kizilay
Scattering Analyses Of Arbitrary Roughness From 2-D Perfectly Conductiveperiodic Surfaces With Moments Method, Yunus Emre Yamaç, Ahmet Kizilay
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a periodic-MoM-based code with high accuracy performance is developed to calculate electromagnetic scattering from a periodic conductive surface in two dimensions with any degree of roughness. Firstly, the existing separate methods in the literature are reviewed step by step to compose a periodic-MoM solution for 2-D periodic surfaces. Then, the dynamic selection of optimal formulation of the periodic-MoM solutions created using these existing methods is evaluated to reduce solution time and obtain high accuracy. In this study, the performance parameters of the existing methods are investigated in solving a real 3-D scattering problem by a periodic-MoM for …
Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş
Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş
Turkish Journal of Electrical Engineering and Computer Sciences
The aerodynamic design and analysis of an Unmanned Air Vehicle, capable of vertical take-off and landing by employing fixed four rotors on the tilt-wing and two rotors on the tilt-tail, will be presented in this study. Both main wing and the horizontal tail can be tilted 90°. During VTOL, transition and forward flight, aerodynamic and thrust forces have been employed. Different flight conditions, including the effects of angle of attack, side slip, wing tilt angle and control surfaces deflection angle changes, have been studied with CFD analysis. For a Tilt-Wing UAV, there are challenges like high non-linearity, vulnerability to disturbances …
Reactive Power Sharing And Voltage Restoration In Islanded Ac Microgrids, Khurram Hashmi, Rizwan Ali, Muhammad Hanan, Waseem Aslam, Abubakar Siddique, Muhammad Mansoor Khan
Reactive Power Sharing And Voltage Restoration In Islanded Ac Microgrids, Khurram Hashmi, Rizwan Ali, Muhammad Hanan, Waseem Aslam, Abubakar Siddique, Muhammad Mansoor Khan
Turkish Journal of Electrical Engineering and Computer Sciences
Microgrids (MG) are a new and innovative concept in modern distribution networks. Several challenges are associated with the operation and control of MG networks. Active and reactive power sharing among energy resources interfaced through power electronic conversion stages is a major challenge. Although active power sharing can be achieved under varying scenarios, sharing of reactive power between distributed generation units is difficult to achieve. This paper presents a novel and innovative control scheme to ensure sharing of reactive power between Distributed generation units within an autonomous, islanded AC microgrid. A framework composed of novel multiagent moving average estimators is proposed …
Robust Position/Force Control Of Nonholonomic Mobile Manipulator Forconstrained Motion On Surface In Task Space, Güli̇n Eli̇bol Seçi̇l, Serhat Obuz, Osman Parlaktuna
Robust Position/Force Control Of Nonholonomic Mobile Manipulator Forconstrained Motion On Surface In Task Space, Güli̇n Eli̇bol Seçi̇l, Serhat Obuz, Osman Parlaktuna
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a robust controller is developed for a mobile manipulator (MM) to track reference position/force trajectories. Nonholonomic and holonomic constraints are considered for the mobile platform and manipulator, respectively. Additionally, the control design considers the uncertainties in parameters of the dynamics of the mobile manipulator with a bounded time varying additive disturbance (unmodelled effects, external disturbances). A Lyapunov-based stability analysis is used to prove semiglobal uniform ultimate boundedness of the tracking error signals and the position/force of the system track to an arbitrarily small neighborhood of the reference trajectories. Numerical results for a mobile manipulator, which is formed …
Design And Manufacture Of Electromagnetic Absorber Composed Of Boricacid-Incorporated Wastepaper Composites, Ali̇ İhsan Kaya, Ahmet Çi̇fci̇, Fi̇li̇z Kirdioğullari, Mesud Kahri̇man, Osman Çerezci̇
Design And Manufacture Of Electromagnetic Absorber Composed Of Boricacid-Incorporated Wastepaper Composites, Ali̇ İhsan Kaya, Ahmet Çi̇fci̇, Fi̇li̇z Kirdioğullari, Mesud Kahri̇man, Osman Çerezci̇
Turkish Journal of Electrical Engineering and Computer Sciences
With the effect of technological advances, the use of electrical and electronic devices has increased dramatically in recent years. Wireless technologies and related applications are mostly preferred for the communication of these devices with each other. Thus, people are easily exposed to electromagnetic waves in daily life. The extensive global use of these devices raises the question of their possible biological effects on human health. Also, electromagnetic waves influence the functioning of a nearby device. In this study, an electromagnetic absorber based on boric acid (5, 10, 20, and 30 wt%) added wastepaper was developed. Copper (Cu) and aluminum (Al) …
A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇
A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇
Turkish Journal of Electrical Engineering and Computer Sciences
Recommender systems provide their users an efficient way to handle information overload problem by offering personalized suggestions. Traditional recommender systems are based on two-dimensional user-item preference matrix constructed depending on the users' overall evaluations over items. However, they have begun to present their preferences under various circumstances. Thus, traditional recommendation techniques fail to process multicriteria ratings during the recommendation process. Multicriteria recommender systems are an extension of traditional recommender systems that utilize multicriteria-based user preferences. Multicriteria recommender systems provide more personalized and accurate predictions compared to traditional recommender systems. However, the increased amount of data dimension causes sparsity to be …