Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- TÜBİTAK (3106)
- Embry-Riddle Aeronautical University (409)
- Missouri University of Science and Technology (335)
- Old Dominion University (319)
- Air Force Institute of Technology (129)
-
- University of New Haven (74)
- University of Nebraska - Lincoln (63)
- University of Nevada, Las Vegas (62)
- University of Dar es Salaam (55)
- Western University (36)
- University of Arkansas, Fayetteville (35)
- Chapman University (34)
- Portland State University (31)
- Loyola University Chicago (27)
- University of Kentucky (27)
- Purdue University (26)
- Wayne State University (24)
- New Jersey Institute of Technology (23)
- University of Texas at El Paso (23)
- University of Malaya (21)
- University of South Florida (21)
- California Polytechnic State University, San Luis Obispo (18)
- Michigan Technological University (18)
- South Dakota State University (15)
- Technological University Dublin (15)
- Munster Technological University (14)
- University of Denver (14)
- University of South Carolina (14)
- University of New Mexico (13)
- Washington University in St. Louis (13)
- Keyword
-
- Machine learning (152)
- Deep learning (128)
- Classification (87)
- Optimization (85)
- Genetic algorithm (61)
-
- Neural networks (54)
- Particle swarm optimization (53)
- Security (53)
- Digital forensics (48)
- Image processing (48)
- Artificial intelligence (47)
- Feature extraction (46)
- Clustering (43)
- Computer vision (42)
- Machine Learning (42)
- Wireless sensor networks (41)
- Artificial neural networks (40)
- Algorithms (37)
- Feature selection (37)
- Support vector machine (37)
- Artificial neural network (35)
- Deep Learning (34)
- Fuzzy logic (34)
- Convolutional neural network (30)
- Convolutional neural networks (30)
- Cybersecurity (30)
- Reinforcement learning (29)
- Natural language processing (28)
- Neural network (28)
- Power quality (28)
- Publication Year
- Publication
-
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Journal of Digital Forensics, Security and Law (290)
- Electrical and Computer Engineering Faculty Research & Creative Works (282)
- Theses and Dissertations (127)
- Electrical & Computer Engineering Theses & Dissertations (120)
-
- Electrical & Computer Engineering Faculty Publications (109)
- Annual ADFSL Conference on Digital Forensics, Security and Law (100)
- Electrical & Computer Engineering and Computer Science Faculty Publications (71)
- Tanzania Journal of Engineering and Technology (TJET) (50)
- School of Computing: Conference and Workshop Papers (44)
- Electrical and Computer Engineering Publications (36)
- Electronic Theses and Dissertations (34)
- Computer Science: Faculty Publications and Other Works (27)
- Faculty Publications (27)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (26)
- Dissertations (25)
- Engineering Faculty Articles and Research (25)
- Open Access Theses & Dissertations (23)
- USF Tampa Graduate Theses and Dissertations (20)
- Chemical Engineering and Materials Science Faculty Research Publications (19)
- Computer Science Faculty Research & Creative Works (19)
- Graduate Theses and Dissertations (19)
- Computer Science Faculty Publications (18)
- Dissertations and Theses (18)
- Publications (18)
- Doctoral Dissertations (17)
- Engineering Technology Faculty Publications (16)
- Fred and Harriet Cox Senior Design Competition Projects (16)
- VMASC Publications (15)
- Electrical & Computer Engineering Faculty Research (14)
- Publication Type
- File Type
Articles 1411 - 1440 of 5273
Full-Text Articles in Computer Sciences
Mutant Selection By Using Fourier Expansion, Savaş Takan, Tolga Ayav
Mutant Selection By Using Fourier Expansion, Savaş Takan, Tolga Ayav
Turkish Journal of Electrical Engineering and Computer Sciences
Mutation analysis is a widely used technique to evaluate the effectiveness of test cases in both hardware and software testing. The original model is mutated systematically under certain fault assumptions and test cases are checked against the mutants created to see whether the test cases can detect the faults or not. Mutation analysis is usually a computationally intensive task, particularly in finite state machine (FSM) testing due to a possibly huge amount of mutants. Random selection could be a practical reduction method under the assumption that each mutant is identical in terms of the probability of occurrence of its associating …
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Turkish Journal of Electrical Engineering and Computer Sciences
A transmission line is the main commodity of power transmission network through which power is transmitted to the utility. These lines are often swayed by accidental breakdowns owing to different random origins. Hence, researchers try to detect and track down these failures at the earliest to avoid financial prejudice. This paper offers a new realtime mathematical morphology based approach for fault feature extraction. The morphological open-close-median filter is exploited to wrest unique fault features which are then fed as an input to support vector machine to detect and classify the short circuit faults. The acquired graphical and numerical results of …
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
Turkish Journal of Electrical Engineering and Computer Sciences
Visualizing multidimensional data has been a crucial task in recent years regarding the growing amount of data from various sources. To achieve this, dimensionality reduction algorithms have been used to reduce the number of dimensions for visualization of the data on a screen. However, these algorithms may fail to faithfully represent high dimensional data in lower dimensions and eventually lead to erroneous visualizations. In this work, we propose an error detection algorithm for dimensionality reduction algorithms based on recently developed error prediction algorithms for medical image registration. The proposed algorithm matches the neighborhoods of high and low dimensional data with …
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a power-speed (P-V) model of the wind turbine by assuming three different functions for the first performance region; cubic, quadratic and uncorrected cubic. These three functions have been compared with the manufacturer models of five different wind turbines which were installed in five different locations in Jordan; Tafila, Hofa, Fujeij, Al Rajef, and Deahan. The wind turbine of these wind farms are considered as large scale HAWT in the range of Mw. The generated P-V models are developed by applying a new method described in this paper which is basically based on generating a multiplier factor x. …
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Turkish Journal of Electrical Engineering and Computer Sciences
Network reconfiguration is a process to change the open-switches in distribution system for a minimum power loss. In the past, metaheuristic techniques were applied widely for network reconfiguration with consideration of a fixed loading profile. When the loading changes, the current configuration may not be the optimal one. Thus, the technique needs to be executed to find a new optimal configuration based on the latest loading. The process is time-consuming since metaheuristic techniques commonly require high computational times and produces inconsistent results. Therefore, this paper proposes a network reconfiguration technique based on artificial neural network (ANN) for variable loading conditions. …
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
Turkish Journal of Electrical Engineering and Computer Sciences
Radio frequency identification (RFID) tags that meet EPC Gen2 standards are used in many fields such as supply chain operations. The number of the RFID tags, smart cards, wireless sensor nodes, and Internet of things devices is increasing day by day and the areas where they are used are expanding. These devices are very limited in terms of the resources they have. For this reason, many security mechanisms developed for existing computer systems cannot be used for these devices. In order to ensure secure communication, it is necessary to provide authentication process between these lightweight devices and the devices they …
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Turkish Journal of Electrical Engineering and Computer Sciences
Person reidentification (Re-ID) is an important task in computer vision and has many applications in videobased surveillance. Recently, the triplet loss has been popular in the deep learning framework for person Re-ID. It is particularly important to note that the selection of hard triplets has significant influence on the performance of the learned deep model. However, the existing triplet losses only focus on some specific forms of hard triplets, thus leading to weaker generalization capability. To address this issue, we propose a novel variant of the triplet loss, named exhaustive hard triplet mining loss (EHTM), which is able to deal …
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Turkish Journal of Electrical Engineering and Computer Sciences
Motion sensors available on smart phones make it possible to recognize human activities. Accelerometer, gyroscope, magnetometer, and their various combinations are used to classify, particularly, locomotion activities, ranging from walking to biking. In most of the studies, the focus is on the collection of data and on the analysis of the impact of different parameters on the recognition performance. The parameter space includes the types of sensors used, features, classification algorithms, and position/orientation of the mobile device. In most of the studies, the impact of some of these parameters is partially analyzed; however, in this work, we investigate the parameter …
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Turkish Journal of Electrical Engineering and Computer Sciences
Internet usage has increased rapidly with the development of information communication technologies. The increase in internet usage led to the growth of data volumes on the internet and the emergence of the big data concept. Therefore, it has become even more important to analyze the data and make it meaningful. In this study, 690 million queries and approximately 5.9 quadrillion data collected daily from different servers were recorded on the Redis servers by using real-time big data analysis method and load balance structure for a company operating in the tourism sector. Here, wireless networks were used as a triggering factor …
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a convolutional neural networks Turkish tweet classification system for crisis response. This system has the ability to classify the present information before or during any crisis. In addition, a preprocessing model was also implemented and integrated as a part of the developed system. This paper presents the first ever Turkish tweet dataset for crisis response, which can be widely used and improve similar studies. This dataset has been carefully preprocessed, annotated, and well organized. It is suitable to be used by all the well-known natural language processing tools. Extensive experimental work, using our produced Turkish tweet dataset …
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Turkish Journal of Electrical Engineering and Computer Sciences
Robotic manipulators are open to external disturbances and actuation failures during performing a task such as trajectory tracking. In this paper, we present a modifed controller consisting of a global fast sliding surface combined with an adaptive neural network which is called adaptive fast sliding neural control (AFSNC) for a robotic manipulator to precise stable trajectory tracking performance under the external disturbances. The adaptive term is employedtoreduce uncertainties due to unmodeled dynamics. Trackingerror asymptoticallyconvergesto zero according to the Lyapunov stability theorem. Numerical examples have been carried on a planar two-links manipulator to verify the control approach efficiency. The experimental results …
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Turkish Journal of Electrical Engineering and Computer Sciences
Thispaperpresentstheapplicationofanewlydeveloped21-levelhybridmultilevelinverter. Ahighfrequency modulation technique known as sinusoidal pulse width modulation (SPWM) is applied to the hybrid inverter. This modulation methodology operates the switching sequences of the multilevel inverter to produce the desired 21-level output voltage. To validate the proper application of this inverter, it is further utilized to maintain the speed of a single phase induction motor. The velocity control of the motor is established on the principle of V/f control technique. The speed control strategy along with the compatibility of the SPWM modulation technique were verified by means of simulation and experimental results.
Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r
Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Minimization or elimination of cogging torque is a significant issue in permanent magnet (PM) motor design process. There are some design techniques to reduce or eliminate this unwanted torque components in PM motors. This paper focuses on two different design techniques, varying magnet pole-arc and step-skew, to reduce cogging torque component in radial flux PM synchronous motors. Different design points which consider pulsating torque components and back-EMF harmonics are obtained via finite element analysis (FEA) for a low power industrial PM motor. A prototype motor is manufactured for one of the desired designs and is tested experimentally. Good agreement is …
Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu
Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents the application of deep learning algorithms towards demand response management. Demand limit violation and voltage stability are the major problems associated with a secondary distribution system. These problems are solved using demand response models by day ahead scheduling loads at every 15 min interval through linear integer programming and based on short term forecasting of load (kW). A new architecture for short term load forecasting is presented namely gated recurrent unit in which statistical analysis is carried out to get the optimal architecture of the neural network model. Reliability indices such as loss of load probability (LOLP) …
A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük
A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük
Turkish Journal of Electrical Engineering and Computer Sciences
5G slices have challenging application demands from a wide variety of fields including high bandwidth, low latency and reliability. The requirements of the container network functions which are used in telecommunications are different from any other cloud native IT applications as they are used for data plane packet processing functions, together with control, signalling and media processing which have critical processing requirements. This study aims to discover high performing container networking solution by considering traffic loads and application types. The behaviour of several container cluster networking solutions -- Flannel, Weave, Libnetwork, Open Virtual Networking for Open vSwitch and Calico -- …
Optimizing Cluster Sets For The Scan Statistic Using Local Search, James Shulgan
Optimizing Cluster Sets For The Scan Statistic Using Local Search, James Shulgan
Graduate Research Theses & Dissertations
In recent years, scattering sensors to produce wireless sensor networks (WSN) has been proposed for detecting localized events in large areas. Because sensor measurements are noisy, the WSN needs to use statistical methods such as the scan statistic. The scan statistic groups measurements into various clusters, computes a cluster statistic for each cluster, and decides that an event has happened if any of the statistics exceeds a threshold. Previous researchers have investigated the performance of the scan statistic to detect events; however, little attention was given to the optimization of which clusters the scan statistic should use. Using the scan …
Fault Detection And Classification Of A Single Phase Inverter Using Artificial Neural Networks, Ayomikun Samuel Orukotan
Fault Detection And Classification Of A Single Phase Inverter Using Artificial Neural Networks, Ayomikun Samuel Orukotan
All Graduate Theses, Dissertations, and Other Capstone Projects
The detection of switching faults of power converters or the Circuit Under Test (CUT) is real-time important for safe and efficient usage. The CUT is a single-phase inverter. This thesis presents two unique methods that rely on backpropagation principles to solve classification problems with a two-layer network. These mathematical algorithms or proposed networks are able to diagnose single, double, triple, and multiple switching faults over different iterations representing range of frequencies. First, the fault detection and classification problems are formulated as neural network-based classification problems and the neural network design process is clearly described. Then, neural networks are trained over …
System Efficient Esd Design Concept For Soft Failures, Giorgi Maghlakelidze
System Efficient Esd Design Concept For Soft Failures, Giorgi Maghlakelidze
Doctoral Dissertations
"This research covers the topic of developing a systematic methodology of studying electrostatic discharge (ESD)-induced soft failures. ESD-induced soft failures (SF) are non-destructive disruptions of the functionality of an electronic system. The soft failure robustness of a USB3 Gen 1 interface is investigated, modeled, and improved. The injection is performed directly using transmission line pulser (TLP) with varying: pulse width, amplitude, polarity. Characterization provides data for failure thresholds and a SPICE circuit model that describes the transient voltage and current at the victim. Using the injected current, the likelihood of a SF is predicted. ESD protection by transient voltage suppressor …
Real-Time Urban Weather Observations For Urban Air Mobility, Kevin A. Adkins, Mustafa Akbas, Marc Compere
Real-Time Urban Weather Observations For Urban Air Mobility, Kevin A. Adkins, Mustafa Akbas, Marc Compere
International Journal of Aviation, Aeronautics, and Aerospace
Cities of the future will have to overcome congestion, air pollution and increasing infrastructure cost while moving more people and goods smoothly, efficiently and in an eco-friendly manner. Urban air mobility (UAM) is expected to be an integral component of achieving this new type of city. This is a new environment for sustained aviation operations. The heterogeneity of the urban fabric and the roughness elements within it create a unique environment where flight conditions can change frequently across very short distances. UAM vehicles with their lower mass, more limited thrust and slower speeds are especially sensitive to these conditions. Since …
Distributed Strategy For Power Re-Allocation In High Performance Applications, Vaibhav Sundriyal, Masha Sosonkina
Distributed Strategy For Power Re-Allocation In High Performance Applications, Vaibhav Sundriyal, Masha Sosonkina
Electrical & Computer Engineering Faculty Publications
To improve the power consumption of parallel applications at the runtime, modern processors provide frequency scaling and power limiting capabilities. In this work, a runtime strategy is proposed to distribute a given power allocation among the cluster nodes assigned to the application while balancing their performance change. The strategy operates in a timeslice-based manner to estimate the current application performance and power usage per node followed by power redistribution across the nodes. Experiments, performed on four nodes (112 cores) of a modern computing platform interconnected with Infiniband showed that even a significant power budget reduction of 20% may result in …
Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin
Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin
Electrical & Computer Engineering Faculty Publications
This guest editorial summarizes the Special Section on Machine Learning in Optics.
Priority Based Routing And Link Scheduling For Cognitive Radio Networks, Peng Jiang, Mitchell Zhou, Song Wen
Priority Based Routing And Link Scheduling For Cognitive Radio Networks, Peng Jiang, Mitchell Zhou, Song Wen
Electrical & Computer Engineering Faculty Publications
To address the challenges caused by the time-varying rate requirement for multimedia communication sessions, we propose a Priority Based Routing and link Scheduling (PBRS) scheme for multi-hop cognitive radio networks. The objective is to minimize disruption to communication sessions due to channel switching as well as to minimize network resource consumption for multimedia applications based on a prioritized routing and resource allocation scheme. PBRS includes a priority based optimization formulation and an efficient algorithm to solve the problem. The main idea is to allocate the available resource to different types of services with their Quality of Experience (QoE) expectation as …
Generative Adversarial Networks For Visible To Infrared Video Conversion, Mohammad Shahab Uddin, Jiang Li, Chiman Kwan (Ed.)
Generative Adversarial Networks For Visible To Infrared Video Conversion, Mohammad Shahab Uddin, Jiang Li, Chiman Kwan (Ed.)
Electrical & Computer Engineering Faculty Publications
Deep learning models are data driven. For example, the most popular convolutional neural network (CNN) model used for image classification or object detection requires large labeled databases for training to achieve competitive performances. This requirement is not difficult to be satisfied in the visible domain since there are lots of labeled video and image databases available nowadays. However, given the less popularity of infrared (IR) camera, the availability of labeled infrared videos or image databases is limited. Therefore, training deep learning models in infrared domain is still challenging. In this chapter, we applied the pix2pix generative adversarial network (Pix2Pix GAN) …
Energy Efficiency In Cmos Power Amplifier Designs For Ultralow Power Mobile Wireless Communication Systems, Selvakumar Mariappan, Jagadheswaran Rajendran, Norlaili Mohd Noh, Harikrishnan Ramiah, Asrulnizam Abd Manaf
Energy Efficiency In Cmos Power Amplifier Designs For Ultralow Power Mobile Wireless Communication Systems, Selvakumar Mariappan, Jagadheswaran Rajendran, Norlaili Mohd Noh, Harikrishnan Ramiah, Asrulnizam Abd Manaf
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless communication standards keep evolving so that the requirement for high data rate operation can be fulfilled. This leads to the efforts in designing high linearity and low power consumption radio frequency power amplifier (RFPA) to support high data rate signal transmission and preserving battery life. The percentage of the DC power of the transceiver utilized by the power amplifier (PA) depends on the efficiency of the PA, user data rate, propagation conditions, signal modulations, and communication protocols. For example, the PA of a WLAN transceiver consumes 49 % of the overall efficiency from the transmitter. Hence, operating the PA …
A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid
A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, systems-on-chip have reached a level where nonrecurring engineering costs have become a great challenge due to the increase of design complexity and postfabrication errors. Embedded field programmable gate arrays (eFPGAs) represent a viable alternative to overcome these issues since they provide postmanufacturing flexibility that can reduce the number of chip redesigns and amortize chip fabrication cost. In this paper, we present an overview on eFPGAs and their architectures, computer aided design (CAD) tools, and design challenges. An eFPGA must be well-designed and accompanied by an optimized CAD tool suite to respond to target application's requirements in terms of power …
Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala
Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala
Turkish Journal of Electrical Engineering and Computer Sciences
Inductors play a crucial role in the design of radio frequency integrated circuits (RFICs) and they typically consume a considerably large area and have a low-quality factor at high frequencies. The employment of fractal structure in on-chip inductors helps in improving the quality factor and also reduces the overall area besides improving the inductance value. In this paper, an orthogonal series stacked differential fractal inductor is proposed and the same is used to design a low noise amplifier (LNA) for 5G band (27--30 GHz) applications. The proposed inductor is fabricated on a multilayer printed circuit board and the measurement results …
A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati
A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati
Turkish Journal of Electrical Engineering and Computer Sciences
In real-world problems, finding sufficient labeled data for defining classification rules is very difficult. This paper suggests a new semisupervised multiclass classification method. In the initialization, new membership functions are defined by utilizing the labeled data?Äôs medoids and means. Then the unlabeled points are labeled with the class of the highest membership value. In the supervised learning phase, separation via the polyhedral conic functions (PCFs) approach is improved by using defined membership values in the linear programming problem. The suggested algorithm is tested on real-world datasets and compared with the state-of-the-art semisupervised methods. The results obtained indicate that the suggested …
Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp
Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp
Turkish Journal of Electrical Engineering and Computer Sciences
Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold …
Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock
Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock
Turkish Journal of Electrical Engineering and Computer Sciences
Recommender systems (RSs) are running behind E-commerce websites to recommend items that are likely to be bought by users. Most of the existing RSs are relying on mere star ratings while making recommendations. However, ratings alone cannot help RSs make accurate recommendations, as they cannot properly capture sentiments expressed towards various aspects of the items. The other rich and expressive source of information available that can help make accurate recommendations is user reviews. Because of their voluminous nature, reviews lead to the information overloading problem. Hence, drawing out the user opinion from reviews is a decisive job. Therefore, this paper …
Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban
Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban
Turkish Journal of Electrical Engineering and Computer Sciences
Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a …