Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Machine learning (11)
- Classification (7)
- Convolutional neural networks (6)
- Deep learning (6)
- Genetic algorithm (6)
-
- Optimization (6)
- Artificial neural networks (4)
- Adaptive control (3)
- Feature extraction (3)
- Feature selection (3)
- Genetic algorithms (3)
- Security (3)
- Support vector machine (3)
- Synthetic aperture radar (3)
- Wideband (3)
- Wireless sensor network (3)
- Wireless sensor networks (3)
- 5G (2)
- Artificial bee colony (2)
- Artificial neural network (2)
- CAD (2)
- Clustering (2)
- Conic functions (2)
- Convolutional neural network (2)
- Decision tree (2)
- Detection (2)
- Diversity (2)
- Efficiency (2)
- Energy efficiency (2)
- Energy harvesting (2)
Articles 1 - 30 of 230
Full-Text Articles in Physical Sciences and Mathematics
A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai
A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai
Turkish Journal of Electrical Engineering and Computer Sciences
The compute-intensive multimedia applications on portable devices require power and area efficient arithmetic units. The adder is a prime building block of these arithmetic units and limits the overall performance. Therefore, this paper analyzes the logic operations of the state-of-the-art adders and presents a novel low complexity adder segment with new carry prediction logic by removing the redundant logic and sharing the common operations. Further, a new power and area efficient approximate carry skip (PAEA-CSK) adder is proposed using the novel adder segment. The effectiveness of the proposed PAEA-CSK adder is evaluated and compared over the existing adders by implementing …
Performance Improvement Of Induction Motor Drives With Model-Based Predictive Torque Control, Fati̇h Korkmaz
Performance Improvement Of Induction Motor Drives With Model-Based Predictive Torque Control, Fati̇h Korkmaz
Turkish Journal of Electrical Engineering and Computer Sciences
One of the most important advantages of using modeling and simulation software in design and control engineering is the ability to predict system behavior within specified conditions. This paper presents a novel error vector-based control algorithm that aims to reduce torque ripples predicting flux and torque errors in a conventional vector-controlled induction motor. For this purpose, a new control model has been developed that envisages flux change by applying probabilistic space vectors' torque and flux control. In the proposed predictive control algorithm, flux and torque errors are calculated for each candidate voltage vector. Thus, the optimal output voltage vector that …
Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan
Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan
Turkish Journal of Electrical Engineering and Computer Sciences
In simultaneous multithreaded (SMT) processors, various data path resources are concurrently shared by many threads. A few heuristic approaches that explicitly distribute those resources among threads with the goal of improved overall performance have already been proposed. A selection hyperheuristic is a high-level search methodology that mixes a predetermined set of heuristics in an iterative framework to utilize their strengths for solving a given problem instance. In this study, we propose a set of selection hyperheuristics for selecting and executing the heuristic with the best performance at a given stage. To the best of our knowledge, this is one of …
Piezoresistive Disposable Weight Sensor With Increased Sensitivity, Kuter Erdi̇l, Tuğçe Ayraç, Ömer Gökalp Akcan, Yi̇ği̇t Dağhan Gökdel
Piezoresistive Disposable Weight Sensor With Increased Sensitivity, Kuter Erdi̇l, Tuğçe Ayraç, Ömer Gökalp Akcan, Yi̇ği̇t Dağhan Gökdel
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents the design, simulation, implementation, and experimental characterization of a paperbased perforated disposable weight sensor system with a double piezoresistive layer. The demonstrated system is designed to achieve highly sensitive weight sensing operations with low-cost materials. For that purpose, the main fabrication material of the proposed disposable sensor is selected as a 289 $\mu$m thick Strathmore 400 series Bristol paper. Approximately 48 $\mu$m thick piezoresistive graphite paste is coated onto both sides of the paper-based cantilever beam with the aim of acquiring more sensitive weight-sensing capability. Additionally, the proposed paper-based structure has rows of closely spaced perforations at …
A High-Level And Adaptive Metaheuristic Selection Algorithm For Solving Highdimensional Bound-Constrained Continuous Optimization Problems, Osman Gökalp, Aybars Uğur
A High-Level And Adaptive Metaheuristic Selection Algorithm For Solving Highdimensional Bound-Constrained Continuous Optimization Problems, Osman Gökalp, Aybars Uğur
Turkish Journal of Electrical Engineering and Computer Sciences
Metaheuristic algorithms are used to find sufficiently good solutions for the optimization problems that are not solvable in a polynomial time. Although metaheuristics offer a general problem-solving framework and can be applied to various types of optimization problems, their performances depend heavily on the problem to be solved. Thus, hybrid metaheuristics are used to combine strong parts of different algorithms. In this study, a novel adaptive metaheuristic selection algorithm is proposed for solving bound-constrained continuous optimization problems. The developed method hybridizes artificial bee colony, differential evolution, and particle swarm optimization at a high level where each algorithm works independently from …
User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç
User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an earlier method proposed by the authors to make smart recommendations utilizing artificial intelligence and the latest technologies developed for the television area is expanded further using controlled clustering with genetic algorithms (CCGA). For this purpose, genetic algorithms (GAs), artificial neural networks (ANNs), and hybrid broadcast broadband television (HbbTV) are combined to get the users' television viewing habits and to create profiles. Then television programs are recommended to the users based on that profiling. The data gathered by the developed HbbTV application for previous studies are reused in this study. These data are employed to cluster users. …
Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache
Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache
Turkish Journal of Electrical Engineering and Computer Sciences
In the context of noncoherent detection and high-resolution maritime radar system with low grazing angle, new Constant False Alarm Rate (CFAR) decision rules are suggested for two Compound Gaussian (CG) clutters namely: The K distribution and the Compound Inverse Gaussian (CIG) distribution, which are considered among the most appropriate models for sea clutter. The proposed decision rules are then modified to deal with the presence of thermal noise and interfering targets. The proposed detectors are investigated on the basis of synthetic data as well as real data of the IPIX radar database. The obtained results exhibit a high probability of …
Formation Of A Wireless Sensor Network Using Custom-Designed Sensors Having Lowpower And Low Cost Components, Veysel Yaman Akgün, Engi̇n Maşazade
Formation Of A Wireless Sensor Network Using Custom-Designed Sensors Having Lowpower And Low Cost Components, Veysel Yaman Akgün, Engi̇n Maşazade
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we first design a sensor with low power and low cost components, namely an MSP430G2553 microcontroller (MCU), nRF24L01+ communication unit, and a light-dependent resistor (LDR). Then, connecting these custom-designed sensors with a central node, a fusion center (FC), we form a wireless sensor network (WSN) in which sensors measure light intensities and send their measurements to the FC for final inference. Since the default addressing structure of nRF24L01+ can simultaneously connect up to 6 devices, in order to have more connections, we define a new addressing scheme for the transmissions between sensors and the FC. Finally, as …
A Detailed Survey Of Turkish Automatic Speech Recognition, Recep Si̇nan Arslan, Necaatti̇n Barişçi
A Detailed Survey Of Turkish Automatic Speech Recognition, Recep Si̇nan Arslan, Necaatti̇n Barişçi
Turkish Journal of Electrical Engineering and Computer Sciences
Significant improvements have been made in automatic speech recognition(ASR)systems in terms of both the general technology and the software used. Despite these advancements, however, there is still an important difference between the recognition performance of humans and machines. This work focuses on the studies conducted in the field of Turkish speech recognition, the progress made in such studies in recent years, the language-specific constraints, the performance results achieved in the applications developed to date, and the development of a general scheme for researchers wishing to develop an ASR system for the Turkish language. A comprehensive study on the Turkish language, …
A Priority-Based Queuing Model Approach Using Destination Parameters Forreal-Time Applications On Ipv6 Networks, Sadetti̇n Demi̇r, İbrahi̇m Özçeli̇k
A Priority-Based Queuing Model Approach Using Destination Parameters Forreal-Time Applications On Ipv6 Networks, Sadetti̇n Demi̇r, İbrahi̇m Özçeli̇k
Turkish Journal of Electrical Engineering and Computer Sciences
In the early days of the Internet architecture, the most important aim is to transmit data over packet switched networks. The traditional Internet architecture used in these networks lacks quality of service. However, today, as realtime applications increase, it is needed. There are approaches to improving the quality of service using the flow label field in the Internet Protocol version 6 header. In this study, a novel algorithm that uses destination network parameters to reduce queuing and end-to-end delay is created. A round-robin-based time-aware priority queue new model is used within this algorithm. Data packets using this proposed queue are …
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 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 …
Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik
Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik
Turkish Journal of Electrical Engineering and Computer Sciences
Alzheimer's disease is a brain disease that causes impaired cognitive abilities in memory, concentration, planning, and speaking. Alzheimer's disease is defined as the most common cause of dementia and changes different parts of the brain. Neuroimaging, cerebrospinal fluid, and some protein abnormalities are commonly used as clinical diagnostic biomarkers. In this study, neuroimaging biomarkers were applied for the diagnosis of Alzheimer's disease and dementia as a noninvasive method. Structural magnetic resonance (MR) brain images were used as input of the predictive model. T1 weighted volumetric MR images were reduced to two-dimensional space by several preprocessing methods for three different projections. …
Design And Fabrication Of An Eight-Port Binary Wilkinson Power Splitter, Mohammad Amir Ghasemi Shabankareh
Design And Fabrication Of An Eight-Port Binary Wilkinson Power Splitter, Mohammad Amir Ghasemi Shabankareh
Turkish Journal of Electrical Engineering and Computer Sciences
An eight-port X-band power splitter based on binary Wilkinson power splitter topology is presented in this paper. The proposed power splitter consists of three stages, with one, two, and four equal power splitters in the first, second, and third stages, respectively. The input power is divided equally between the eight outputs to provide an equal-split power splitter. Evaluation of the structure is carried out using even- and odd-mode techniques. An epoxy laminate FR4 substrate with thickness of 0.5 mm is chosen, while the designed power splitter is simulated using Keysight Advanced Design System 2019 and ANSYS High Frequency Structure Simulation. …
Design And Implementation Of A Bandpass Wilkinson Power Divider With Wide Bandwidth And Harmonic Suppression, Hojatollah Soleymani, Sobhan Roshani
Design And Implementation Of A Bandpass Wilkinson Power Divider With Wide Bandwidth And Harmonic Suppression, Hojatollah Soleymani, Sobhan Roshani
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a Wilkinson power divider (WPD) is presented with ultrawide-band operation and harmonic suppression. This WPD is designed using coupling lines and meandered open stubs at main branches. The center frequency of the presented WPD is 4.25 GHz, which is fabricated and measured on RT/Duroid substrate with dielectric constant of 2.2. The proposed WPD provides good filtering band with high attenuation level. The 15 dB return loss operational bandwidth (BW) of the WPD is obtained between 3.2 GHz and 5.3 GHz, which shows 50 % operational bandwidth.
Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak
Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak
Turkish Journal of Electrical Engineering and Computer Sciences
Understanding human activities is a newly emerging paradigm that is greatly involved in developing ubiquitous health care (u-Health) systems. The aim of these systems is to seamlessly gather knowledge about the patient?s health and, after collecting knowledge, make suggestions to the patient according to his/her health profile. For this purpose, one of the most important ubiquitous communication trends is the smartphone, which has drawn the attention of both professionals and caregivers for monitoring the aging population, childcare, fall detection, and cognitive impairment. Recognizing human actions in a ubiquitous environment is very challenging and researchers have extensively investigated different methods to …
Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇
Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, railway transport has been preferred intensively in local and intercity freight and passenger transport. For this reason, it is of utmost importance that railway lines are operated in an uninterrupted and safe manner. In order to carry out continuous operation, all systems must continue to operate with maximum availability. In this study, data were collected from switch motors, which are the important equipment of railways, and the related equipment and these data were evaluated with sector experience and the results related to the failure status of the switch points were revealed. The obtained results were processed with …
The Impact Of Text Preprocessing On The Prediction Of Review Ratings, Muhi̇tti̇n Işik, Hasan Dağ
The Impact Of Text Preprocessing On The Prediction Of Review Ratings, Muhi̇tti̇n Işik, Hasan Dağ
Turkish Journal of Electrical Engineering and Computer Sciences
With the increase of e-commerce platforms and online applications, businessmen are looking to have a rating and review system through which they can easily reveal the feelings of customers related to their products and services. It is undeniable from the statistics that online ratings and reviews attract new customers as well as increase sales by means of providing confidence, ratification, opinions, comparisons, merchant credibility, etc. Although considerable research has been devoted to the sentiment analysis for review classification, rather less attention has been paid to the text preprocessing which is a crucial step in opinion mining especially if convenient preprocessing …
Feature Points-Based Image Registration Between Satellite Imagery And Aerialimages Of Agricultural Land, Mohsin Abbas, Sajid Saleem, Fazli Subhan, Abdul Bais
Feature Points-Based Image Registration Between Satellite Imagery And Aerialimages Of Agricultural Land, Mohsin Abbas, Sajid Saleem, Fazli Subhan, Abdul Bais
Turkish Journal of Electrical Engineering and Computer Sciences
Rapid advancement in remote sensing sensors has resulted in an enormous increase in the use of satellite imagery (SI) and images taken from unmanned aerial vehicles (UAVs) in a wide range of remote sensing applications. These applications include urban planning, environment monitoring, map updating, change detection, and precision agriculture. This paper focuses on an agricultural application of SI and UAV images. SI-UAV images possess high temporal, textural, and intensity differences due to rapid changes in agricultural crops with the passage of time. Feature points such as scale invariant feature transform (SIFT), oriented FAST and rotated BRIEF (ORB), and speeded-up robust …
Multiplicative-Additive Despeckling In Sar Images, Gülay Aksoy, Fati̇h Nar
Multiplicative-Additive Despeckling In Sar Images, Gülay Aksoy, Fati̇h Nar
Turkish Journal of Electrical Engineering and Computer Sciences
Visual and automatic analyses using synthetic aperture radar (SAR) images are challenging because of inherently formed speckle noise. Thus, reducing speckle noise in SAR images is an important research area for SAR image analysis. During speckle noise reduction, homogeneous regions should be smoothed while details such as edges and point scatterers need to be preserved. General speckle noise model contains gamma distributed multiplicative part which is dominant and Gaussian distributed additive part which is in low amount and mostly neglected in literature. In this study, a novel sparsity-driven speckle reduction method is proposed that takes both multiplicative noise model and …
Bases Of Polymatroids And Problems On Graphs, Hakan Kutucu
Bases Of Polymatroids And Problems On Graphs, Hakan Kutucu
Turkish Journal of Electrical Engineering and Computer Sciences
In the paper, we present new theorems to show that a Hamiltonian path and circuit on an undirected graph can be formulated in terms of bases of polymatroids or extended polymatroids associated with submodular functions defined on subsets of the node-set of a given graph. In this way, we give a new formulation of the well-known traveling salesman problem including constraints in these terms. The main result in the paper states that using a special base of the polymatroid, a Hamiltonian path on an undirected graph can be solved effectively. Since the determination of a Hamiltonian circuit can be reduced …
Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez
Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez
Turkish Journal of Electrical Engineering and Computer Sciences
In the literature it is observed that complex image processing operations are used in the classification of Ball Grid Array (BGA) X-ray images, however high classification results were not achieved. In recent years, it has been shown that deep learning methods are very successful especially in classification problems. In this study, a new deep neural network (DNN) model is proposed to classify the BGA X-ray images. The proposed DNN model contains feature extractor layers and a minimum distance classifier. Since the proposed network consists of less number of layers (4 convolution layers and 1 fully connected layer), determination of the …
Field-Of-View Optimization Of Magnetically Actuated 2d Gimballed Scanners, Gökçe Aköz, Yi̇ği̇t Dağhan Gökdel
Field-Of-View Optimization Of Magnetically Actuated 2d Gimballed Scanners, Gökçe Aköz, Yi̇ği̇t Dağhan Gökdel
Turkish Journal of Electrical Engineering and Computer Sciences
This work presents the field of view (FOV) maximization of a magnetically actuated two-dimensional (2D) gimballed scanner. The process of maximization is completed in two steps. (1) Optimization of the electrocoil providing the magnetic force that moves the scanner and (2) precise choice of optimum respective locations of both the scanner and the electrocoil. We first derived a formula relating the generated magnetic flux density, coil design parameters and driving voltage. Subsequently, we discussed the design trade-offs of an actuating electrocoil. We also conducted several experiments on a stainless steel 430 scanner having a footprint of 15 mm × 15 …
Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin
Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Developing software systems to meet user-demanded functionality is critical. Achieving the design goals by providing the needed functionality is a necessary task, and it is about figuring out a proper set of quality attributes and implementing each one by reflecting a complete set of quality attributes. This study presents popular quality attributes of crisis software systems by conducting a literature review. Each crisis software system has been studied by concentrating on crisis management phases where the system is used, design purposes, and the data processing style. The findings of this research shed light on the crisis software development process by …
Mlcocoa: A Machine Learning-Based Congestion Control For Coap, Alper Kami̇l Demi̇r, Fati̇h Abut
Mlcocoa: A Machine Learning-Based Congestion Control For Coap, Alper Kami̇l Demi̇r, Fati̇h Abut
Turkish Journal of Electrical Engineering and Computer Sciences
Internet of Things (IoT) is a technological invention that has the potential to impact on how we live and how we work by connecting any device to the Internet. Consequently, a vast amount of novel applications will enhance our lives. Internet Engineering Task Force (IETF) standardized the Constrained Application Protocol (CoAP) to accommodate the application layer and network congestion needs of such IoT networks. CoAP is designed to be very simple where it employs a genuine congestion control (CC) mechanism, named as default CoAP CC leveraging basic binary exponential backoff. Yet efficient, default CoAP CC does not always utilize the …
Chronic Obstructive Pulmonary Disease Severity Analysis Using Deep Learning Onmulti-Channel Lung Sounds, Gökhan Altan, Yakup Kutlu, Ahmet Gökçen
Chronic Obstructive Pulmonary Disease Severity Analysis Using Deep Learning Onmulti-Channel Lung Sounds, Gökhan Altan, Yakup Kutlu, Ahmet Gökçen
Turkish Journal of Electrical Engineering and Computer Sciences
Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases which cannot be treated but can be kept under control in certain stages. COPD has five severities, including at-risk, mild, moderate, severe, and very severe stages. Diagnosis of COPD at early stages needs additional clinical tests for even experienced specialists. The study aims at detecting the severity of the COPD to start treatment for preventing the progression of the disease to the next levels. We analyzed 12-channel lung sounds with different COPD severities from RespiratoryDatabase@TR. The lung sounds were recorded from the clinical auscultation points from 41 patients on …
Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez
Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez
Turkish Journal of Electrical Engineering and Computer Sciences
Shortening the periods of compaction tests can be possible by analyzing the data obtained from previous laboratory tests with regression methods. The regression analysis applied to current data reduces the cost of experiments, saves time, and gives estimated outputs. In this study, the MLS-SVR, KB-SVR, and DTR algorithms were employed for the first time for the estimation of soil compaction parameters. The performances of these regression algorithms in estimating maximum dry unit weight (MDD) and optimum water content (OMC) were compared. Furthermore, the soil properties (fine-grained soil, sand, gravel, specific gravity, liquid limit, and plastic limit) were employed as inputs …
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.
Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya
Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Lung cancer is one of the deadly cancer types, and almost 85 % of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation of two subtypes of NSCLC, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). The major advances in understanding the effects of therapy agents suggest that future targeted therapies will be increasingly subtype specific. We obtained positron emission tomography (PET) images of 93 patients with NSCLC, 39 of which had ADC while the rest had SqCC. Random walk segmentation was applied to delineate three-dimensional tumor …