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Articles 1 - 30 of 182
Full-Text Articles in Computer Engineering
Design And Prototyping Of A Low-Cost High Frequency Antenna For Vicinity Coupling Devices, Benjamin Kommey, Ernest Ofosu Addo, Elvis Tamakloe
Design And Prototyping Of A Low-Cost High Frequency Antenna For Vicinity Coupling Devices, Benjamin Kommey, Ernest Ofosu Addo, Elvis Tamakloe
Makara Journal of Technology
This paper describes the development of a high frequency (HF) antenna for high output power vicinity coupling devices (VCDs) operating at 13.56 MHz. Key design parameters, such as RF power level, antenna size, and communication protocol, and their link to the antenna features and requirements, have been discussed. For efficient reader interrogation, detection, and recovery of transponder responses, a tuning circuit necessary to adjust the antenna power matching and resonance characteristics was designed and prototyped. The antenna was fed to an industry standard reader and evaluated for read range performance with vicinity cards. The designed antenna on the reader achieved …
Damage Stability Study Of A 500 Dw Ro-Ro Ferry Vessel, Zulfaidah Ariany, Budhi Santoso, Sarwoko Sarwoko, Nauval Abdurrahman Prasetyo
Damage Stability Study Of A 500 Dw Ro-Ro Ferry Vessel, Zulfaidah Ariany, Budhi Santoso, Sarwoko Sarwoko, Nauval Abdurrahman Prasetyo
Makara Journal of Technology
The development of the crossing transportation industry is currently increasing in the island areas. The use of Ro-Ro type ferry boats is extremely efficient in moving people, goods, and vehicles. The current research focuses on the damage stability of the 500 DWT Ro-Ro ferry, which aims to meet the needs of the Ro-Ro ferry in the archipelago area. The previously existing initial design of a barge hull with a main size Lpp = 40.15 m, B = 12 m, H = 3.2 m, and T = 2.15 m was used to analyze the damage stability condition further. First, the drawings …
Performance Comparison Of Several Control Algorithms For Tracking Control Of Pantograph Mechanism, Laylaa Mahmoud Eng, Mohamed Shamseldin Dr, Mohamed Sallam Dr, Abdelghany Mohamed Prof
Performance Comparison Of Several Control Algorithms For Tracking Control Of Pantograph Mechanism, Laylaa Mahmoud Eng, Mohamed Shamseldin Dr, Mohamed Sallam Dr, Abdelghany Mohamed Prof
Future Engineering Journal
A sort of parallel manipulator known as a pantograph robot mechanism was created primarily for industrial requests that required high precision and satisfied speed. While tracking a chosen trajectory profile requires a powerful controller. Because it has four active robot links and one robot passive link in place of just two links like the open chain does, it can carry more loads than the open chain robot mechanism while maintaining accuracy and stability. The calculated model for a closed chain pantograph robot mechanism presented in this paper takes into account the boundary conditions. For the purpose of simulating the dynamics …
Relative Rate Observer Self-Tuning Of Fuzzy Pid Virtual Inertia Control For An Islanded Microgrid, Ahmed H. Mohamed, Helmy M. El Zoghby, Mohiy Bahgat, A. M. Abdel Ghany
Relative Rate Observer Self-Tuning Of Fuzzy Pid Virtual Inertia Control For An Islanded Microgrid, Ahmed H. Mohamed, Helmy M. El Zoghby, Mohiy Bahgat, A. M. Abdel Ghany
Future Engineering Journal
Expanding the usage of renewable energy in islanded microgrids leads to a reduction in its total inertia. Low inertia microgrids have difficulties in voltage and frequency control. That affected saving its stability and preventing a blackout. To improve low inertia islanded microgrids' dynamic response and save their stability, this paper presented relative rate observer self-tuning fuzzy PID (RROSTF-PID) based on virtual inertia control (VIC) for an islanded microgrid with a high renewable energy sources (RESs) contribution. RROSTF-PID based on VIC's success in showing remarkable improvement in the microgrid's dynamic response and enhancement of its stability. Moreover, it handles different contingency …
Rdlnn-Based Image Forgery Detection And Forged Region Detection Using Mot, Akram Hatem Saber, Mohd Ayyub Khan, Basim Galeb Mejbel
Rdlnn-Based Image Forgery Detection And Forged Region Detection Using Mot, Akram Hatem Saber, Mohd Ayyub Khan, Basim Galeb Mejbel
Karbala International Journal of Modern Science
Image forgery detection TEMPhas become an emerging research area due to the increasing number of forged images circulating on the internet and other social media, which leads to legal and social issues. Image forgery detection includes the classification of an image as forged or authentic and as well as localizing the forgery wifin the image. In this paper, we propose a Regression Deep Learning Neural Network (RDLNN) based image forgery detection followed by Modified Otsu Thresholding (MOT) algorithm to detect the forged region. The proposed model comprises five steps that are preprocessing, image decomposition, feature extraction, classification and block matching. …
Redefining Research In Nanotechnology Simulations: A New Approach To Data Caching And Analysis, Darin Tsai, Alan Zhang, Aloysius Rebeiro
Redefining Research In Nanotechnology Simulations: A New Approach To Data Caching And Analysis, Darin Tsai, Alan Zhang, Aloysius Rebeiro
The Journal of Purdue Undergraduate Research
No abstract provided.
Identification Of Initial Events Of Cascading Failures Using Graph Theory Methods, Mojtaba Fekri, Javad Nikoukar, Gevork Babamalek Gharehpetian
Identification Of Initial Events Of Cascading Failures Using Graph Theory Methods, Mojtaba Fekri, Javad Nikoukar, Gevork Babamalek Gharehpetian
Turkish Journal of Electrical Engineering and Computer Sciences
In power systems, the unintentional outage of a grid element can lead to overload and outage of other equipment and, through a domino effect, all or a large part of a power system may collapse. The resulting events are called cascading, consecutive, or sequential failures. So far, various methods have been proposed to identify the initial events of cascading failures with different levels of accuracy and computational load. In this paper, an effective approach is employed which, by calculating the maximum flow of independent paths between generators and loads in the network graph, identifies the critical lines and transformers of …
Effects Of Position And Gap Orientation Of The Split Ring Resonator Structure Excited By Microstrip Transmission Line On The Transmission Characteristics, Nezi̇he Karacan, Nesli̇han Kader Bulut, Evren Ekmekçi̇
Effects Of Position And Gap Orientation Of The Split Ring Resonator Structure Excited By Microstrip Transmission Line On The Transmission Characteristics, Nezi̇he Karacan, Nesli̇han Kader Bulut, Evren Ekmekçi̇
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, the effects of the position and the gap orientation of the split ring resonator (SRR) structure, which is applied as a superstrate, on transmission characteristics (i.e. S21 ) are investigated numerically and experimentally. For that purpose, the left edge of the transmission line has been designated as the reference line and the SRR structure is shifted towards both left and right for three different gap orientations. Subsequently, S21 characteristics of the SRR structure having several substrate thicknesses and several substrate dielectric constants are investigated parametrically for three different gap orientations. The results reveal that the position and …
Utilizing Motion And Spatial Features For Sign Language Gesture Recognition Using Cascaded Cnn And Lstm Models, Hamzah Luqman, Elsayed Elalfy
Utilizing Motion And Spatial Features For Sign Language Gesture Recognition Using Cascaded Cnn And Lstm Models, Hamzah Luqman, Elsayed Elalfy
Turkish Journal of Electrical Engineering and Computer Sciences
Sign language is a language produced by body parts gestures and facial expressions. The aim of an automatic sign language recognition system is to assign meaning to each sign gesture. Recently, several computer vision systems have been proposed for sign language recognition using a variety of recognition techniques, sign languages, and gesture modalities. However, one of the challenging problems involves image preprocessing, segmentation, extraction and tracking of relevant static and dynamic features related to manual and nonmanual gestures from different images in sequence. In this paper, we studied the efficiency, scalability, and computation time of three cascaded architectures of convolutional …
Compact Dual-Band Rectangular T E10 Mode To Circular Tm01 Mode Converter For Telemetry/Telecommand Applications In Satellite Communication: Design, Equivalent Circuit Modeling, Mode Level Measurement Technique And 3d Printed Manufacturing, Esra Alkin, Ceyhan Türkmen, Mustafa Seçmen
Compact Dual-Band Rectangular T E10 Mode To Circular Tm01 Mode Converter For Telemetry/Telecommand Applications In Satellite Communication: Design, Equivalent Circuit Modeling, Mode Level Measurement Technique And 3d Printed Manufacturing, Esra Alkin, Ceyhan Türkmen, Mustafa Seçmen
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, the design of a dual-band mode converter, which provides transition from rectangular waveguide T E10 mode to circular waveguide TM01 mode and operates simultaneously in telemetry/telecommand (TT&C) frequencies, is presented along with its equivalent circuit and a mode level measurement technique. This dual-band converter is designed to uniformly excite TT&C slot antennas used in satellite communication with symmetric circular TM01 mode. The structure can work as a transceiver due to having one common rectangular waveguide feed. As a Ku-band application, a converter giving high purity TM01 mode at circular waveguide at 11.75 GHz/TX …
Skin Lesion Segmentation By Using Object Detection Networks, Deeplab3+, And Active Contours, Fatemeh Bagheri, Mohammad Jafar Tarokh, Majid Ziaratban
Skin Lesion Segmentation By Using Object Detection Networks, Deeplab3+, And Active Contours, Fatemeh Bagheri, Mohammad Jafar Tarokh, Majid Ziaratban
Turkish Journal of Electrical Engineering and Computer Sciences
Developing an automatic system for detection, segmentation, and classification of skin lesions is very useful to aid well-timed diagnosis of skin diseases. Lesion segmentation is a crucial task for automated diagnosis of skin cancers, as it affects significantly the accuracy of the subsequent steps. Varieties in sizes and locations of lesions, and the lesions with low-contrast boundaries make this task very challenging. In this paper, a three-stage CNN-based method is presented for accurate segmentation of lesions from dermoscopic images. At the first step, normalization, approximate locations and sizes of lesions are estimated. Due to the importance of the normalization stage, …
Computationally Efficient Predictive Torque Control Strategies Without Weighting Factors, Emrah Zerdali̇, Mert Altintaş, Ali̇ Bakbak, Erkan Meşe
Computationally Efficient Predictive Torque Control Strategies Without Weighting Factors, Emrah Zerdali̇, Mert Altintaş, Ali̇ Bakbak, Erkan Meşe
Turkish Journal of Electrical Engineering and Computer Sciences
Predictive torque control (PTC) is a promising control method for electric machines due to its simplicity, fast dynamics, ability to handle nonlinearities, and easy inclusion of additional control objectives. The main challenge in conventional PTC design is to determine the weighting factors in the cost function. These weighting factors are generally chosen by the trial-and-error method or metaheuristic optimization algorithms, but these methods may not apply the optimum voltage vectors according to changing operating conditions. There are also several studies on the elimination of the weighting factors. This paper proposes two weighting factorless PTC strategies with lower computational complexities than …
A Rule-Based/Bpso Approach To Produce Low-Dimensional Semantic Basis Vectors Set, Atefe Pakzad, Morteza Analoui
A Rule-Based/Bpso Approach To Produce Low-Dimensional Semantic Basis Vectors Set, Atefe Pakzad, Morteza Analoui
Turkish Journal of Electrical Engineering and Computer Sciences
The present study aims to generate low-dimensional explicit distributional semantic vectors. In explicit semantic vectors, each dimension corresponds to a word, which makes word vectors interpretable. In this study, a new approach is proposed to obtain low-dimensional explicit semantic vectors. Firstly, the suggested approach considers three criteria, namely, word similarity, number of zeros, and word frequency as features for words in a corpus. Next, some rules are extracted to obtain the initial basis words using a decision tree which is drawn based on the three features. Secondly, a binary weighting method is proposed based on the binary particle swarm optimization …
Monte-Carlo Method Based Simulations For Photothermal Mucosa Coagulation With Accurate Depth Limits, Merve Türker Burhan, Serhat Tozburun
Monte-Carlo Method Based Simulations For Photothermal Mucosa Coagulation With Accurate Depth Limits, Merve Türker Burhan, Serhat Tozburun
Turkish Journal of Electrical Engineering and Computer Sciences
The mucosa layer, the innermost layer of the gastrointestinal (GI) system, is of great importance in carcinogenesis since most cancerous tissues occur as superficial lesions. Although various treatment strategies exist, the main difficulty in eradicating lesions is unintentional damage to healthy tissues with the uncontrolled depth of treatment. This study proposes a computer modeling approach for simulating depth-resolved photothermal (laser) mucosal coagulation therapy. Computer modeling mimics the thermal dynamics of mucosal tissue to characterize the total heat energy required for successful superficial coagulation, which can be controlled by the scan rate, scan time, output power, and beam diameter of the …
Load2load: Day-Ahead Load Forecasting At Aggregated Level, Mustafa Berkay Yilmaz
Load2load: Day-Ahead Load Forecasting At Aggregated Level, Mustafa Berkay Yilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
A reliable and accurate short-term load forecasting (STLF) helps utilities and energy providers deal with the challenges posed by supply and demand balance, higher penetration of renewable energies and the development of electricity markets with increasingly complex pricing strategies in future smart grids. Recent advances in deep learning have been successively utilized to STLF. However, there is no certain study that evaluates the performances of different STLF methods at an aggregated level on different datasets with different numbers of daily measurements.In this study, a deep learning STLF architecture called Load2Load is proposed for day-ahead forecasting. Different forecasting methods have been …
Application Of Hierarchical Clustering On Electricity Demand Of Electric Vehicles For Gep Problems, Seyedkazem Afghah, Hati̇ce Teki̇ner Moğulkoç, Bi̇jan Bi̇bak
Application Of Hierarchical Clustering On Electricity Demand Of Electric Vehicles For Gep Problems, Seyedkazem Afghah, Hati̇ce Teki̇ner Moğulkoç, Bi̇jan Bi̇bak
Turkish Journal of Electrical Engineering and Computer Sciences
Increasing fossil fuel consumption and consequently the effects of greenhouse gases (GHGs) on the environment and economy are a major concern for all nations and governments. Electric vehicles (EVs) with plug-in capabilities have the potential to ease such problems. However, the extracted power from the grid for charging the EVs' batteries will significantly impact daily power demand. To satisfy the increasing demand and ensure generation capacity adequacy, the generation expansion planning (GEP) problem is solved to determine the investment decisions for electricity generation sources. Even though there are no centralized utilities for generation planning in most markets, there is still …
Asking The Right Questions To Solve Algebraic Word Problems, Ege Yi̇ği̇t Çeli̇k, Zeynel Orulluoğlu, Ridvan Mertoğlu, Selma Teki̇r
Asking The Right Questions To Solve Algebraic Word Problems, Ege Yi̇ği̇t Çeli̇k, Zeynel Orulluoğlu, Ridvan Mertoğlu, Selma Teki̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Word algebra problems are among challenging AI tasks as they combine natural language understanding with a formal equation system. Traditional approaches to the problem work with equation templates and frame the task as a template selection and number assignment to the selected template. The recent deep learning-based solutions exploit contextual language models like BERT and encode the natural language text to decode the corresponding equation system. The proposed approach is similar to the template-based methods as it works with a template and fills in the number slots. Nevertheless, it has contextual understanding because it adopts a question generation and answering …
Affective States Classification Performance Of Audio-Visual Stimuli From Eeg Signals With Multiple-Instance Learning, Yaşar Daşdemi̇r, Rüstem Özakar
Affective States Classification Performance Of Audio-Visual Stimuli From Eeg Signals With Multiple-Instance Learning, Yaşar Daşdemi̇r, Rüstem Özakar
Turkish Journal of Electrical Engineering and Computer Sciences
Throughout various disciplines, emotion recognition continues to be an essential subject of study. With the advancement of machine learning methods, accurate emotion recognition from different data modalities (facial images, brain EEG signals) has become possible. Success of EEG-based emotion recognition systems depends on efficient feature extraction and pre/postprocessing of signals. Main objective of this study is to analyze the efficacy of multiple-instance learning (MIL) on postprocessing features of EEG signals using three different domains (time, frequency, time-frequency) for human emotion classification. Methods and results are presented for single-trial classification of valence (V), arousal (A), and dominance (D) ratings from EEG …
Blockchain And Federated Learning-Based Security Solutions For Telesurgery System: A Comprehensive Review, Sachi Chaudjary, Riya Kakkar, Rajesh Gupta, Sudeep Tanwar, Smita Agrawal, Ravi Sharma
Blockchain And Federated Learning-Based Security Solutions For Telesurgery System: A Comprehensive Review, Sachi Chaudjary, Riya Kakkar, Rajesh Gupta, Sudeep Tanwar, Smita Agrawal, Ravi Sharma
Turkish Journal of Electrical Engineering and Computer Sciences
The advent of telemedicine with its remote surgical procedures has effectively transformed the working of healthcare professionals. The evolution of telemedicine facilitates the remote monitoring of patients that lead to the advent of telesurgery systems, i.e. one of the most critical applications in telemedicine systems. Apart from gaining popularity, the telesurgery system may encounter security and trust issues of patients? data while communicating with the surgeon for their remote treatment. Motivated by this, we have presented a comprehensive survey on secure telesurgery systems comprising healthcare, surgical robots, traditional telesurgery systems, and the role of artificial intelligence to deal with the …
Mocmin: Convex Inferring Of Modular Low-Rank Contact Networks Over Covid Diffusion Data, Emre Sefer
Mocmin: Convex Inferring Of Modular Low-Rank Contact Networks Over Covid Diffusion Data, Emre Sefer
Turkish Journal of Electrical Engineering and Computer Sciences
SEIR (which consists of susceptible, exposed, infected, and recovered states) is a common diffusion model which could model different disease propagation dynamics across various domains such as influenza and COVID diffusion. As a motivation, across these domains, observing the node states is relatively easier than observing the network edges over which the diffusion is taking place, or it may not even be possible to observe the underlying network. This paper focuses on the problem of predicting modular low-rank human contact network edges only if a SEIR diffusion dynamics spreading among the human on their contact network can be observed. Such …
Modeling And Validation Of The Thermoelectric Generator With Considering The Change Of The Seebeck Effect And Internal Resistance, Mehmet Ali̇ Üstüner, Hayati̇ Mamur, Sezai̇ Taşkin
Modeling And Validation Of The Thermoelectric Generator With Considering The Change Of The Seebeck Effect And Internal Resistance, Mehmet Ali̇ Üstüner, Hayati̇ Mamur, Sezai̇ Taşkin
Turkish Journal of Electrical Engineering and Computer Sciences
Thermoelectric generators (TEGs) produce power in direct proportion to the temperature difference between their surfaces. The Seebeck coefficient and internal resistance of the thermoelements (TEs) that make up the TEGs change depending on the temperature change. In simulation studies, it is seen that these two values are kept constant. However, this situation prevents approaching the data of TEG in real applications. In this study, a TEG Simulink/MATLAB ® model has been developed to capture real TEG module data, which considers changing of both the Seebeck coefficient and the internal resistance depending on the temperature difference change. To achieve this aim, …
Detection And Classification Of White Blood Cells With An Improved Deep Learning-Based Approach, Fatma Akalin, Nejat Yumuşak
Detection And Classification Of White Blood Cells With An Improved Deep Learning-Based Approach, Fatma Akalin, Nejat Yumuşak
Turkish Journal of Electrical Engineering and Computer Sciences
The analysis of white blood cells, which defend the body against deadly infections and disease-causing substances, is an important issue in the medical world. The concentrations of these cells in the blood, examined in 5 classes, i.e. monocytes, eosinophils, basophils, lymphocytes, and neutrophils, vary according to the types of diseases in the body. The peripheral blood smear is widely used to analyze blood cells. Manual evaluation of this method is laborious and time-consuming. At the same time, many environmental and humanistic parameters affect the method's performance. Therefore, in the presented study, a real-time detection process is realized. Firstly, YOLOv5s, YOLOv5x, …
Enhancement Of Stability Delay Margins By Virtual Inertia Control For Microgrids With Time Delay, Suud Ademnur Hasen, Şahi̇n Sönmez, Saffet Ayasun
Enhancement Of Stability Delay Margins By Virtual Inertia Control For Microgrids With Time Delay, Suud Ademnur Hasen, Şahi̇n Sönmez, Saffet Ayasun
Turkish Journal of Electrical Engineering and Computer Sciences
Large-scale deployment of renewable energy sources (RESs) contributes to fluctuations in the system frequency due to their inherent reduced inertia feature. Time delays have emerged as a major source of concern in microgrids (MGs) as a result of the broad adoption of open communication networks since significant delays inevitably reduce the controller?s performance and even cause instabilities. In this article, a frequency-domain direct method is used to evaluate the impact of the virtual inertia (VI) control on the stability delay margins of MG with communication delays. By avoiding approximation, the approach first removes transcendental terms from characteristic equations and turns …
A Conical-Beam Dual-Band Double Aperture-Coupled Stacked Elliptical Patch Antenna Design For 5g, Feza Turgay Çeli̇k, Kami̇l Karaçuha
A Conical-Beam Dual-Band Double Aperture-Coupled Stacked Elliptical Patch Antenna Design For 5g, Feza Turgay Çeli̇k, Kami̇l Karaçuha
Turkish Journal of Electrical Engineering and Computer Sciences
This study investigates a dual-band, aperture coupled and stacked elliptical patch antenna with conical radiation. To obtain such characteristics, the TM21 mode of the radiating elliptical patches is excited by utilizing two special apertures and shorting planes. The proposed antenna operates both at 2.45 GHz and 3.5 GHz. The design aims to be used indoor applications of 5G operating in both free and planned 5G bands, respectively. Therefore, the low-profile antenna element that has a monopole-like radiation pattern is a good candidate for two-dimensional arraying. The design steps and the evolution of the proposed antenna are presented in detail. The …
Perceptual Analysis Of Distance Sampling And Transmittance Estimation Techniques In Biomedical Volume Visualization, Raazia Sosan, Muhammad Mobeen Movania, Shama Siddiqui
Perceptual Analysis Of Distance Sampling And Transmittance Estimation Techniques In Biomedical Volume Visualization, Raazia Sosan, Muhammad Mobeen Movania, Shama Siddiqui
Turkish Journal of Electrical Engineering and Computer Sciences
In volumetric path tracer, distance sampling and transmittance estimation techniques play a vital role in producing high-quality final rendered images. Previously, these techniques were implemented for production volume rendering, and were analyzed for faster convergence. In this article, we have augmented additional transmittance estimators including ratio tracking, residual ratio tracking and unbiased ray marcher in a GPU-based volumetric path tracer (Exposure Render) for biomedical datasets. We have also analyzed distance sampling methods and transmittance estimators perceptually using CIEDE2000 and Structural Similarity Index (SSIM). It was found that ratio and residual ratio tracking estimators performed close to each other and were …
Rtpltool: A Software Tool For Path Loss Modeling In 5g Outdoor Systems, Ci̇han Bariş Findik, Özlem Özgün
Rtpltool: A Software Tool For Path Loss Modeling In 5g Outdoor Systems, Ci̇han Bariş Findik, Özlem Özgün
Turkish Journal of Electrical Engineering and Computer Sciences
The increase in the required bandwidth along with the global growth of existing wireless communication systems is one of the major reasons why research and industry communities are exploring 5G and millimeter-wave frequencies. The advantages of millimeter wave frequencies for 5G applications are a wide range of accessible and unlicensed spectrum, the use of small antennas in RF applications with increasing frequency, and low losses due to the interference effects compared to the currently used frequency bands. However, due to some computational challenges especially at millimeter waves (i.e. in FR2 frequency band), it is necessary to develop efficient software tools …
A Quantitative Evaluation Of Explainable Ai Methods Using The Depth Of Decision Tree, Nizar Abdulaziz Mahyoub Ahmed, Adi̇l Alpkoçak
A Quantitative Evaluation Of Explainable Ai Methods Using The Depth Of Decision Tree, Nizar Abdulaziz Mahyoub Ahmed, Adi̇l Alpkoçak
Turkish Journal of Electrical Engineering and Computer Sciences
It is necessary to develop an explainable model to clarify how and why a medical model makes a particular decision. Local posthoc explainable AI (XAI) techniques, such as SHAP and LIME, interpret classification system predictions by displaying the most important features and rules underlying any prediction locally. Therefore, in order to compare two or more XAI methods, they must first be evaluated qualitatively or quantitatively. This paper proposes quantitative XAI evaluation metrics that are not based on biased and subjective human judgment. On the other hand, it is dependent on the depth of the decision tree (DT) to automatically and …
Track Density Imaging Using Diffusion Tensor Imaging Data From 1.5 T Mri Scanner, Fatma Betül Köşker, Kazim Zi̇ya Gümüş, Mahmut Tokmakçi, Ni̇yazi̇ Acer, Serkan Şenol, Mehmet Bi̇lgen
Track Density Imaging Using Diffusion Tensor Imaging Data From 1.5 T Mri Scanner, Fatma Betül Köşker, Kazim Zi̇ya Gümüş, Mahmut Tokmakçi, Ni̇yazi̇ Acer, Serkan Şenol, Mehmet Bi̇lgen
Turkish Journal of Electrical Engineering and Computer Sciences
Superresolution track density imaging (TDI) has recently been developed for achieving high resolution track density maps from low-resolution diffusion images acquired at 3 T. But, the utility of the approach is still unclear when applied to diffusion tensor imaging (DTI) data acquired at lower 1.5 T magnetic field strength and thus its advantages or disadvantages awaits for exploration. We implemented an algorithm to generate track density maps of human white matter using streamline tracking and tested its performance with data acquired from two healthy volunteers at 1.5 Tesla. The effects of number of diffusion directions and seed selections on the …
A Compact Pattern Reconfigurable Antenna Employing Shorted Quarterwave Patch Antennas, Feza Turgay Çeli̇k, Lale Alatan, Hati̇ce Özlem Aydin Çi̇vi̇
A Compact Pattern Reconfigurable Antenna Employing Shorted Quarterwave Patch Antennas, Feza Turgay Çeli̇k, Lale Alatan, Hati̇ce Özlem Aydin Çi̇vi̇
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a compact pattern reconfigurable antenna structure is proposed. The proposed antenna is a half-wave square microstrip patch antenna divided into two quarter-wave antenna portions by a conducting wall. This wall forces potential zero at the connection point; therefore, it separates the antenna into two independent quarter-wave portions. Pattern reconfiguration is achieved by separate feeding of the quarter-wave portions. Phase difference between excitations of antenna ports result in variation at the maximum beam direction. Hence, pattern reconfiguration is achieved. Within such a compact antenna, beam steering up to 400 is achieved
Error Analysis Of Siso And Dual-Branch Communications With Generalized Gaussian Noise Over Ftr Fading Channels, Mehmet Bi̇li̇m
Error Analysis Of Siso And Dual-Branch Communications With Generalized Gaussian Noise Over Ftr Fading Channels, Mehmet Bi̇li̇m
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we present error probability analysis for single-input single-output (SISO) and asymmetric dual-branch networks with additive white generalized Gaussian noise (AWGGN) over millimeter-wave (mmW) fluctuating two-ray (FTR) fading channels. Then, we examine the error probability evaluation of a SISO system with imperfect phase errors over mmW FTR fading channels. The probability density function (PDF) approach is employed for the error probability performance evaluation and the novel PDF of the asymmetric dual-branch system over Nakagami-m/mmW FTR fading channels is obtained. Specifically, closed-form expressions are derived for the error probability of the SISO and asymmetric dual-branch networks. The derived error …