Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.13091/1624

Browse

Now showing 1 - 20 of 316

3d Printed Horn Antenna for Near Field Isar Imaging Applications
(ICAENS, 2021) Dursak, Hüseyin; Yiğit, Enes; Seyfi, Levent
In this study, low-cost horn antenna for Ka frequency band is fabricated help of 3-dimensional (3D) printer. Produced antennas are used in near-field ISAR imaging. The performance of the antennas is evaluated with Vector Network Analyzer (VNA). In the constructed ISAR imaging system with these antennas, the backscattering signals reflected from the target are collected. Targets are scanned 360and backscattering signals are recorded for 26.5 to 40 GHz frequencies with 974 sampling points. In the first experiment, a metal box is placed in the experimental setup. Then, back-projection algorithm is applied to the raw data to obtain the ISAR image of the target. In the second experiment, the metal box is covered with a textile. The backscattering signals reflected from the covered target are gathered. The image of the second target is created by applying the back-projection algorithm to the ISAR raw data. The experimentalresults show that the antennas are suitable for ISAR imaging applications.
Access Control and Recording System Using Sqlite and Rfid
(2019) Ezginci, Yalçın; Karadaş, Meryem
Accurate Edge Detection With Support of Reflectance Transformation Imaging
(Institute of Electrical and Electronics Engineers Inc., 2022) Kaya, Burhan; Durdu, Akif
Reflectance Transformation Imaging (RTI) is a method of photographing an object that reveals details that are invisible to the naked eye. The input of RTI consists of a series of images captured by a fixed positioned camera and each illuminated from a known and different direction by lights. Reflection Transform Imaging is widely used to produce quality models from multi-light image data. It is frequently preferred for various studies in the field of cultural heritage. For the first time in this paper, the RTI photographing method has been used outside of its traditional using way. It is used to solve the well-known problem of edge detection. Reflection transform cannot be used actively, because it is difficult to create an RTI experimental environment in daily life. However, under certain conditions, the approaches mentioned in this paper will be used in daily life, from the analysis of images in every field. In this paper, the ideas that it can be applied in every partially controlled area that needs high resolution object detection are discussed. With the method mentioned in this statement, a new approach has been proposed and proven based on RTI basics for edge and corner detections. © 2022 IEEE.
Citation - WoS: 3
Citation - Scopus: 4
Achievable Rate Analysis for Two-Way Relay Non-Orthogonal Multiple Access Systems
(IEEE, 2021) Özdemir, Özgür
This paper investigates the performance of a non-orthogonal multiple access (NOMA) based two-way relaying system where the users want to exchange independent messages with the help of a decode-and-forward relay. We consider transmission over three phases where the first and second phases are allocated to the transmissions of the users and after detection the relay applies superposition coding and transmits the network encoded symbol to the users in the third phase. Exact analytical expressions are derived to characterize the achievable average rate of the system over independent Rayleigh fading channels. Computer simulations are also presented to confirm the theoretical analysis. Analytical and simulation results show that the proposed three-phase two-way relaying scheme with NOMA outperforms the two-phase and four-phase NOMA-based two-way relaying scenarios in terms of achievable average rate.
Citation - Scopus: 1
Achievable Rate of Noma-Based Cooperative Communication Systems With Best Relay Selection Over Cascaded Rayleigh Fading Channels
(IEEE, 2020) Özdemir, Özgür
In this paper, the achievable rate analysis of NOMA-based cooperative communication systems with best relay selection is studied. The cascaded Rayleigh fading channels are considered since investigations have shown that cascaded channel structure agree better with mobile network models such as inter-vehicular communication systems. A cooperative network where a source terminal communicates with a destination directly and through a selected relay among K relays is considered and the achievable average rate of this system using NOMA is found by computer simulations. The obtained results for cascaded Rayleigh fading channels in case of decode and forward protocol have shown that the average rate is decreased as the cascading degree increases. It has been also seen that for a given cascading degree the average rate performance of the system is increased when the number of total relays is increased.
Citation - WoS: 24
Citation - Scopus: 40
An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using Sumo Traffic Simulator
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021) Ali, Muzamil Eltejani Mohammed; Durdu, Akif; Çeltek, Seyit Alperen; Yılmaz, Alper
In the past, the Webster optimal cycle time formula was limited to calculate the optimal cycle from historical data for fixed-time traffic signal control. This paper focuses on the design of an adaptive traffic signal control based on fuzzy logic with Webster and modified Webster's formula. These formulas are used to calculate the optimal cycle time depending on the current traffic situation which applying in the next cycle. The alternation of the traffic condition between two successive cycles is monitored and handled through the fuzzy logic system to compensate the fluctuation. The obtained optimal cycle time is used to determine adaptively the effective phase green times i.e. is used to determine adaptively the maximum allowable extension limit of the green phase in the next cycle. The SUMO traffic simulator is used to compare the results of the proposed adaptive control methods with fuzzy logic-based traffic control, and fixed-time Webster and modified Webster-based traffic control methods. The proposed methods are tested on an isolated intersection. In this study, real field-collected data obtained from three, four, and five approaches intersections in Kilis/Turkey are used to test the performance of the proposed methods. In addition, to examine the efficiency of the proposed techniques at heavy demands, the arbitrary demands are generated by SUMO for a four approaches intersection. The obtained simulation results indicate that the proposed methods overperform the fixed time and fuzzy logic-based traffic control methods in terms of average vehicular delay, speed, and travel time.
Citation - WoS: 1
Citation - Scopus: 2
Adaptive State Feedback Control Method Based on Recursive Least Squares
(Kauno Technologijos Universitetas, 2022) Levent, Mehmet Latif; Aydoğdu, Ömer
This study revealed an adaptive state feedback control method based on recursive least squares (RLS) that is introduced for a time-varying system to work with high efficiency. Firstly, a system identification block was created that gives the mathematical model of the time-varying system using the input/output data packets of the controller system. Thanks to this block, the system is constantly monitored to update the parameters of the system, which change over time. Linear quadratic regulator (LQR) is renewed according to these updated parameters, and self-adjustment of the system is provided according to the changed system parameters. The Matlab/Simulink state-space model of the variable loaded servo (VLS) system module was obtained for the simulation experiments in this study; then the system was controlled. Moreover, experiments were carried out on the servo control experimental equipment of the virtual simulation laboratories (VSIMLABS). The effectiveness of the proposed new method was observed taking the performance indexes as a reference to obtain the results of the practical application of the proposed method. Regarding the analysis of simulation and experimental results, the proposed approach minimizes the load effect and noise and the system works at high efficiency. © 2022 Kauno Technologijos Universitetas. All rights reserved.
Adrenal Lesion Classification on T1-Weighted Abdomen Images With Convolutional Neural Networks
(2022) Solak, Ahmet; Ceylan, Rahime; Bozkurt, Mustafa Alper; Cebeci, Hakan; Koplay, Mustafa
Adrenal lesions are usually discovered incidentally during other health screenings and are usually benign. However, it is vital to take precautions when a malignant adrenal lesion is detected. Especially deep learning models developed in the last ten years give successful results on medical images. In this paper, adrenal lesion characterization on T1-weighted magnetic resonance abdomen images was aimed using convolutional neural network (CNN) which is one of the deep learning methods. Firstly, effects of important model parameters are assessed on performance of CNN, so optimum CNN model is obtained for classification of adrenal lesions. For a fixed number of convolution filters determined in the first stage of the study, CNN model implemented by different kernel sizes were trained. According to the best result obtained, this time the kernel size was kept constant, and experiments were made for different filter numbers. Finally, studies were carried out with CNN structures of different depths and the results were compared. As a result of the studies, when filter is selected as [5 20], the best results in the trainings conducted with a single-block CNN structure are obtained 0.97, 0.90, 0.98, 0.90, 0.90, and 0.94, for accuracy, sensitivity, specificity, precision, F1-score, and AUC score, respectively. The study was compared with the studies in the literature, and it was seen that it was superior to them.
Citation - WoS: 5
Citation - Scopus: 6
Adrenal Tumor Characterization on Magnetic Resonance Images
(WILEY, 2020) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Adrenal tumors occur on adrenal glands and are generally detected on abdominal area scans. Adrenal tumors, which are incidentally detected, release vital hormones. These types of tumors that can be malignant affect body metabolism. Both of benign and malign adrenal tumors can have a similar size, intensity, and shape, this situation may lead to wrong decision during diagnosis and characterization of tumors. Thus, biopsy is done to confirm diagnosis of tumor types. In this study, adrenal tumor characterization is handled by using magnetic resonance images. In this way, it is wanted that patient can be disentangled from one or more imaging modalities (some of them can includes X-ray) and biopsy. An adrenal tumor image set, which includes five types of adrenal tumors and has 112 benign tumors and 10 malign tumors, was used in this study. Two data sets were created from the adrenal tumor image set by manually/semiautomatically segmented adrenal tumors and feature sets of these data sets are constituted by different methods. Two-dimensional gray-level co-occurrence matrix (2D-GLCM), gray-level run-length matrix (GLRLM), and two-dimensional discrete wavelet transform (2D-DWT) methods were analyzed to reveal the most effective features on adrenal tumor characterization. Feature sets were classified in two ways: benign/malign (binary classification) and type characterization (multiclass classification). Support vector machine and artificial neural network classified feature sets. The best performance on benign/malign classification was obtained by the 2D-GLCM feature set. The best results were assessed with sensitivity, specificity, accuracy, precision, and F-score metrics and they were 99.17%, 90%, 98.4%, 99.17%, and 99.13%, respectively. The highest classification performance on type characterization was obtained by the 2D-DWT feature set as 59.62%, 96.17%, 93.19%, 54.69%, and 54.94% for sensitivity, specificity, accuracy, precision, and F-score metrics, respectively.
Adrenal Tumor Classification on T1 and T2-Weighted Abdominal Mr Images
(Institute of Electrical and Electronics Engineers Inc., 2019) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Adrenal tumors occur on adrenal glands and can be malignant. Adrenal glands consist of cortex and medulla. If cortex or medulla produce hormones extremely, the hormonal unbalance situation arises. This situation causes adrenal tumor occurrence on adrenal glands. In this study, adrenal tumors on T1 and T2-weighted MR images were classified by the SVM algorithm. Before the classification stage, different feature extraction algorithms and filtering methods were used for preprocessing. The classification results that were obtained by four different methods were evaluated on five different evaluation metrics as sensitivity, specificity, accuracy, precision, and F-score. The best classification performance was obtained with Method 2 on T1-weighted MR (Magnetic Resonance) images where the sensitivity, specificity, accuracy, precision, and F-score metrics were obtained as 99.17%, 90%, 98.4%, 99.17%, and 99.13%, respectively. © 2019 IEEE.
Citation - WoS: 9
Citation - Scopus: 11
Adrenal Tumor Segmentation Method for Mr Images
(ELSEVIER IRELAND LTD, 2018) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Background and objective: Adrenal tumors, which occur on adrenal glands, are incidentally determined. The liver, spleen, spinal cord, and kidney surround the adrenal glands. Therefore, tumors on the adrenal glands can be adherent to other organs. This is a problem in adrenal tumor segmentation. In addition, low contrast, non-standardized shape and size, homogeneity, and heterogeneity of the tumors are considered as problems in segmentation. Methods: This study proposes a computer-aided diagnosis (CAD) system to segment adrenal tumors by eliminating the above problems. The proposed hybrid method incorporates many image processing methods, which include active contour, adaptive thresholding, contrast limited adaptive histogram equalization (CLAHE), image erosion, and region growing. Results: The performance of the proposed method was assessed on 113 Magnetic Resonance (MR) images using seven metrics: sensitivity, specificity, accuracy, precision, Dice Coefficient, Jaccard Rate, and structural similarity index (SSIM). The proposed method eliminates some of the discussed problems with success rates of 74.84%, 99.99%, 99.84%, 93.49%, 82.09%, 71.24%, 99.48% for the metrics, respectively. Conclusions: This study presents a new method for adrenal tumor segmentation, and avoids some of the problems preventing accurate segmentation, especially for cyst-based tumors. (C) 2018 Elsevier B.V. All rights reserved.
Afyon Bölgesinde Yer Alan Doğalgaz Boru Hattı Üzerindeki Ac Enterferans Sevilerinin Ölçülmesi ve Ac Korozyon İhtimalinin Değerlendirilmesi
(SETSCI, 2018) Karataş, Emre; Seyfi, Levent
Bu çalışmada, Afyon Bölgesindeki 8” çapındaki bir doğalgaz boru hattının yüksek gerilim enerji iletim hattı ile yakın güzergahı kullanması, kesişim ve paralellik arz etmesi nedeniyle önceden hazırlanan rapora göre alınan tedbirler neticesinde boru hattının bir kısmı üzerindeki alternatif akım yoğunluğu seviyesinin ölçülmesi, ulusal ve uluslararası kuruluşların belirlediği sınır değerlerle karşılaştırılması ve boru hattı üzerindeki farklı noktalardaki AC akım yoğunluğu ile kıyaslanması amaçlanmıştır. Ölçümler boru hattı üzerinde 2 ayrı noktada uzun dönemli olarak gerçekleştirilmiştir. Bu çalışmada Z- Log 44 veri kayıt cihazı kullanılmıştır. Çalışma sonunda elde edilen ölçüm değerleri EkoLog 4100 arayüzü kullanılarak grafiklere dönüştürülmüştür. Ayrıca boru hattı üzerinde ilave tedbirler alınması gerektiği tespit edilmiştir.
An Algorithm To Detect the Vital Signs of Multiple Humans in the Presence of High Static Clutters
(SN Bilgi Teknolojileri, 2019) Acar, Yunus Emre; Sarıtaş, İsmail
Human-targeted radar applications have become an important issue in which interest has increased in recent years. In this study, vital signs which are the basis of many human-targeted applications are discussed. In the case of high clutter, which is one of the most important problems of vital sign detection, it is aimed to detect the vital signs of single and multiple human targets. A two-stage algorithm is proposed to detect the single and multiple targets under high static Rayleigh distributed clutter. The ranges of the targets are determined in the first stage of the algorithm while the vital signs are detected in the second stage. The algorithm is developed for Step Frequency Continuous Wave (SFCW) radar structure with I/Q demodulation and tested for different scenarios. The results confirm that the algorithm detects the vital signs accurately.
Citation - WoS: 8
Citation - Scopus: 10
Analysis and Design of a Transimpedance Amplifier Based Front-End Circuit for Capacitance Measurements
(SPRINGER INTERNATIONAL PUBLISHING AG, 2020) Demirtaş, Mehmet; Erişmiş, Mehmet Akif; Güneş, Salih
In this study, transimpedance amplifier based front-end circuits which can be employed to measure small capacitances were designed, analyzed and simulated using analog electronic circuit simulator. The front-end circuit converts the current flowing through the measured capacitance into a modulated voltage value which contains information regarding the desired capacitance. The frequency-domain, time-domain, stability and noise analyzes were carried out numerically and in simulation environment using a circuit simulator. The analytical, numerical and simulation results can be used to design optimized, precise and stable transimpedance amplifiers with low-noise value. The measured capacitance value was 10 pF which is low enough to simulate various real-world applications. Three commercially available, off-the-shelf operational amplifiers with different peripheral passive components were employed for computer based analysis. The designed transimpedance amplifiers are suitable to connect with capacitance extraction circuits which use analog or digital demodulation techniques.
Citation - Scopus: 20
Analysis and Investigation of Different Advanced Control Strategies for High-Performance Induction Motor Drives
(Universitas Ahmad Dahlan, 2020) Farah, Nabil; Talib, Hairul Nizam; Ibrahim, Z.B.; Abdullah, Q.; Aydoğdu, Ömer; Rasin, Z.; Lazi, J.M.
Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing (DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; the model predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared in term of operation in different operating conditions. Moreover, a comparison of these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions. © (2020). All rights reserved.
Citation - Scopus: 7
Analysis of Average Bit Error Rate for Ofdm-Im Systems With Hardware Impairments Over Nakagami-M and Weibull Fading Channels
(Institute of Electrical and Electronics Engineers Inc., 2022) Ceniklioğlu, Büşra; Develi, I.; Canbilen, Ayşe Elif; Lafcı, Mustafa
Orthogonal frequency division multiplexing together with index modulation (OFDM-IM) is a brilliant key alternative to the traditional orthogonal frequency division multiplexing (OFDM) schemes for future communication technologies whereby it has high spectral and energy efficiency. However, there are still key issues that need to be adressed to evaluate possible applications in practical systems. Accordingly, we investigate the performance of OFDM-IM systems over Nakagami-m and Weibull fading channels that suffer from transceiver hardware impairments (HWIs) in this paper. Specifically, a maximum likelihood (ML) detector is applied for OFDM-IM-based transmission and the system performance is analyzed under the effect of HWIs considering average bit error rate (ABER) by utilizing computer simulations. The obtained results show that the HWIs have serious destructive effects on the overall system performance. © 2022 IEEE.
Analysis of Electromagmetic Radiation in Daily Life
(2018) Özkaya, Umut; Seyfi, Levent; Yaldız, Ercan
Along with development of electronics and software technology, amount of electromagnetic (EM) radiation, which expose to people, has significantly risen. For people who uses or do not use technology, it is of great importance that they should have enough information about EM radiation exposing them. So, not only EM radiation is described, but also effects of EM radiation sources are researched in this study. EM radiation is mainly divided into two parts as ionizing and non-ionizing radiation. Technologies which we mostly use in daily life and whose radiation we are exposed to are chiefly telecommunication systems. EM radiation emitted by these systems is non-ionizing type due to their low energy levels. However, exposure of ionizing EM radiation is almost not present and its exposure is personally arisen at only special situations. As examples for this type of EM radiation, medical radiography and security screening systems using x-ray may be said. In this context, each person needs to be informed about these topics and cautious for human health. In respect of health of next generation, definition, types and sources of EM radiation have great importance to be learnt.
Application Example of Deep Echo State Neural Networks Case Study: Prediction of Mobile Hydraulic Crane’s Pressure and Ecu Temperatures
(2021) Karagözler, Kerim; Canan, Süleyman; Ceylan, Murat
Real data taken from the field can be used as design parameters in engineering studies. Alternatively, the calculated and analyzed values should be verified by field tests. However, waiting for data from the field for design parameters can sometimes take a very long time. This makes engineering solutions too long or impossible. In the same way, there may be tests that are difficult to test in design verifications, require cost, and create security problems. This study sought solutions to the problems described using the DESN model in two different data sets. In the study, deep Echo State neural network analysis was performed on two different data sets. As data, the pressures formed in the cylinder during the lifting and lowering of 6 different loads by a truck-mounted mobile crane and the 4- month device temperature of the electronic control unit in an overhead crane were recorded. Echo State Network application was made on these records with deep learning. After training with 80% of the data, the DeepESN model was tested with 20%, and these results were evaluated.
Citation - WoS: 13
Citation - Scopus: 18
Application of the Maturity Model in Industrial Corporations
(Mdpi, 2022) Ünal, Cihan; Sungur, Cemil; Yıldırım, Hakan
Enterprises need to evaluate for themselves whether they are ready for Industry 4.0 to survive and develop in the era of the Fourth Industrial Revolution. Therefore, it is necessary to conceptualize or develop an Industry 4.0 readiness and maturity model with basic model dimensions. The present study aimed to review the maturity models available in the literature and to develop and implement a comprehensive maturity model that would eliminate the problems in the existing models. Most maturity models developed lack vital dimensions such as laws, incentives, and corporate culture. While developing the model, AHP and expert opinions were used to determine the dimension weights. The model was applied to 87 businesses in various industries at the Ankara Chamber of Industry Industrial Park in Turkey. The developed model calculates the maturity level of the enterprise for six dimensions. The data on 61 corporations where Industry 4.0 technologies were adopted were analyzed based on demographic variables such as the year of establishment, industry, size, capital, and turnover. These findings demonstrated that Industry 4.0 was introduced recently in Turkey and businesses are required to take further steps to keep up with the global digital transformation. Since the number of industries and corporations that are aware of the Industry 4.0 technologies is limited in Ankara, Turkey, only a few businesses adopted the Industry 4.0 technologies. This developed model will make an important contribution to the literature with its unique dimensions. It would pave the way for further research in various industries in Turkey and other nations where Industry 4.0 investments are new.
Citation - WoS: 1
Citation - Scopus: 3
An Approach for Learning From Robots Using Formal Languages and Automata
(EMERALD GROUP PUBLISHING LTD, 2019) Aslan, Muhammet Fatih; Durdu, Akif; Sabancı, Kadir; Erdogan, Kemal
Purpose In this study, human activity with finite and specific ranking is modeled with finite state machine, and an application for human-robot interaction was realized. A robot arm was designed that makes specific movements. The purpose of this paper is to create a language associated to a complex task, which was then used to teach individuals by the robot that knows the language. Design/methodology/approach Although the complex task is known by the robot, it is not known by the human. When the application is started, the robot continuously checks the specific task performed by the human. To carry out the control, the human hand is tracked. For this, the image processing techniques and the particle filter (PF) based on the Bayesian tracking method are used. To determine the complex task performed by the human, the task is divided into a series of sub-tasks. To identify the sequence of the sub-tasks, a push-down automata that uses a context-free grammar language structure is developed. Depending on the correctness of the sequence of the sub-tasks performed by humans, the robot produces different outputs. Findings This application was carried out for 15 individuals. In total, 11 out of the 15 individuals completed the complex task correctly by following the different outputs. Originality/value This type of study is suitable for applications to improve human intelligence and to enable people to learn quickly. Also, the risky tasks of a person working in a production or assembly line can be controlled with such applications by the robots.

Browse

Browsing Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu by Department "Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü"