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ÖgeCharacterization of different shape objects using EM pulse for several different scenarios(Graduate School, 2024-10-07)This thesis presents a thorough investigation into the interaction of electromagnetic pulses (EMP) with various shaped objects, with a particular focus on computational method for characterization. The comprehensive dissertation is anchored in the principles of electromagnetics, with Maxwell's equations serving as the foundation for formulating the theoretical framework essential for analyzing radiation and diffraction phenomena. Initially, the study delves into Maxwell's equations within the context of a uniform dielectric medium characterized by permittivity and permeability. These equations are crucial for describing the behavior of electric and magnetic fields in various media and are presented in their frequency domain forms. The main framework of the thesis revolves around the formulation of problems related to EM radiation and diffraction. By applying the curl operator to Maxwell's equations, the study derives expressions that elucidate how electromagnetic fields propagate and interact with different objects. The thesis meticulously examines the boundary conditions at the surfaces of different objects, essential for deriving the integral equations governing radiation and scattering phenomena. A significant portion of the thesis is devoted to the derivation of functions, which are indispensable for solving the integral equations related to EM problems. These functions assist in characterizing the fields generated by sources in different configurations. The thesis also details the computation of electric and magnetic vector potentials, which are pivotal in understanding how EM fields can be represented and manipulated mathematically. The integral equations, which form the basis for many of the computational methods used in the study, are carefully derived and explained. These foundational steps are critical as they set the stage for the complex simulations and analyses that follow, ensuring that the theoretical underpinnings are robust and reliable. In examining the scattering of EM pulses, the thesis employs various boundary conditions to ensure accurate simulation of the scenarios. These conditions include the continuity of tangential components of electric and magnetic fields across interfaces, which is critical for solving the resulting linear algebraic equations. The inversion of these equations provides the amplitudes of the unknown fields, facilitating the calculation of fields both inside and outside the objects. The handling of boundary conditions is crucial for ensuring the physical accuracy of the simulations, and the thesis provides a detailed account of how these conditions are implemented. This meticulous approach ensures that the simulations reflect realistic physical behaviors, which is paramount for the reliability of the results. The thesis progresses to apply these theoretical constructs to practical problems involving different shapes of objects. The Method of Auxiliary Sources (MAS) is extensively utilized for this purpose. MAS is an efficient computational technique that approximates the scattered fields by placing hypothetical sources around the object. This method's efficacy is particularly highlighted in its application to scenarios where objects need to be rendered invisible over a broad frequency range—a novel extension of MAS within this thesis. Numerical research explores the potential of time domain analysis in addition to frequency domain methods. Moreover, the research extends to shape reconstruction of objects using EM pulses. By analyzing the frequency response of the dielectric objects to EM pulses, the thesis provides a comprehensive characterization of their scattering properties. This dual approach allows for a more detailed understanding of the interactions between EM pulses and objects, offering insights that are not readily apparent from time-domain analysis alone. The frequency-domain analysis also helps identify resonant frequencies at which the scattering characteristics are particularly pronounced, valuable for applications in sensing and detection technologies. In practical applications, the thesis demonstrates the feasibility of using the MAS method for real-time object characterization. The research includes developing algorithm that can quickly process Gaussian EMP signal to reconstruct object shapes and determine material properties. This algorithm is tested using results generated from numerical simulations. The results show that the MAS-based algorithms can accurately and efficiently characterize objects in real-time, making them suitable for deployment in field applications where rapid assessment is required. The thesis delves into shape reconstruction using time-domain analysis, which involves measuring the time delay between the first and second echoes of an incident EMP to determine the object's dimensions. This method proves particularly accurate for objects with low ellipticity. When the object's permittivity is known, both the shape and dimensions can be accurately reconstructed; otherwise, only the shape can be inferred. This technique is vital for non-invasive applications such as medical imaging, where precision and safety are crucial. The research demonstrates how time-domain analysis can significantly enhance shape reconstruction accuracy, offering a promising avenue for further research and practical applications. The thesis also explores the practical implications of its findings, particularly in the field of radar and stealth technology. By optimizing the parameters of objects such as elliptical cylinders and dielectric ellipsoids with high ellipticity, the MAS method effectively minimizes the scattering echoes, making the object less detectable by radar. This has significant implications for military and defense applications, where reducing the radar cross-section of objects is of paramount importance. The thesis provides detailed case studies of how these principles can be applied to real-world scenarios, enhancing the understanding of EMP interactions with various materials and shapes. The case studies are comprehensive, covering different dielectric properties and configurations, and provide valuable insights into the practical applications of the MAS method. One of the other significant applications of the MAS method in this research is the reduction of front echo in Gaussian EMP scattering from 3D dielectric ellipsoids with high ellipticity. By optimizing the parameters of the ellipsoids, such as size and dielectric permittivity, the MAS method effectively minimizes the scattering echoes, making the object less detectable by radar. This has important implications for military and defense applications, particularly in stealth technology and missile design. The thesis presents detailed numerical results to demonstrate the efficacy of the MAS method. Simulations were performed using a specially designed software suite, and the results were visualized to show the electric field amplitudes for dielectric ellipsoids. These results highlight significant reductions in front echo, validating the proposed method's practical utility. Numerical results form a substantial part of the thesis, showcasing the practical applications of the derived formulations. These results not only validate the theoretical models but also demonstrate the capability of the computational method to handle complex scattering problems. The numerical results are presented in a series of detailed graphs and tables, illustrating the effectiveness of the MAS method in reducing computational complexity while maintaining high accuracy. The results highlight the precision with which the MAS method can model the scattering behavior, making it a powerful tool for various applications. Also, the advantages of MAS are demonstrated through a variety of numerical experiments and comparisons with other methods, such as the Method of Moments (MoM) and the Finite-Difference Time- Domain (FDTD) method. These comparisons are essential as they validate the MAS method against established techniques, showcasing its advantages in terms of computational efficiency and accuracy. In summary, this thesis offers a comprehensive analysis of EMP interactions with different shaped objects. It combines rigorous theoretical formulations with advanced computational method, providing significant contributions to the field of electromagnetic research. The methods developed and the numerical results obtained have potential applications in areas such as radar detection, stealth technology, telecommunications, medical imaging, geoscience and material science. The study not only advances technological capabilities but also enriches scientific understanding of electromagnetic interactions with complex objects. The detailed explanations, extensive numerical simulations, and practical applications presented in the thesis make it a valuable resource for researchers and practitioners in the field of electromagnetics. The findings and methodologies presented in this thesis have the potential to influence future research and development in the field, offering new insights and tools for tackling complex electromagnetic problems.
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ÖgeKesirli kalkülüs ve derin değerlendirme yaklaşımı ile havacılık verilerinin modellenmesi, etki faktörlerinin analizi ve öngörü çalışması(Lisansüstü Eğitim Enstitüsü, 2024-05-21)Bu tez çalışmasında; taşınan hava yolcuları sayısı, hava kargo miktarı, uçuş sayısı, varış noktası sayısı, uluslararası yolcu sayısı, uluslararası varış noktası sayısı, uluslararası uçuş sayısı, arz edilen koltuk kilometre (AKK) bilgisi, AKK uluslararası bilgisi 2011-2019 yılları arasında en yoğun havalimanlarına sahip sekiz ülke olan Almanya, Fransa, İngiltere, Amerika, Hindistan, Singapur, Çin ve Türkiye için seçilmiştir. Seçilen havacılık verileri dikkate alınarak her bir faktörün hesaplanmasında kesirli hesaplama ve derin değerlendirme yöntemlerinden faydalanılacaktır. Çalışmada bildiğimiz kadarıyla türevleri de içeren çok fonksiyonlu olarak henüz ele alınmamış kesirli türevden faydalanılarak; Türevli Çoklu Derin Değerlendirme Metodolojisi (MDAM wd) ile geliştirilen modelleme, öngörü ve etki analizi yapmamıza imkan verecektir. Bu tez çalışmasında yukarıda belirlediğimiz veri seti ile geliştirdiğimiz matematiksel yaklaşımların uygulaması yapılacaktır. İlk olarak modellemek istediğimiz faktörü, etkilendiğini değerlendirdiğimiz kendi ve diğer faktörlerin geçmiş değerleriyle ilişkilendirip böylece her bir faktörün diğer faktörlerin geçmiş değerleriyle etkileşimini ve aynı zamanda geçmiş verilerindeki değişimlerinin ağırlıklı etkisini bulacağız. Sonrasında ise geleceğe ilişkin tahminlerde bulunulacaktır. Bu çalışmada havacılık faktörleri çok az bir sapma ile modellenerek doğru sonuçlar elde edilmiştir, öyle ki modellenen sekiz ülke içinde maksimum hata % 0,015927302 olarak Almanya'nın Hava taşımacılığı, kargo faktörü için bulunmuştur. Faktörlerin öngörülmesi ile ilgili olarak, toplam 72 öngörü için hataların %90.278'i %10'dan küçük olarak bulunmuştur. Önerilen yöntemin sonucu oldukça tatmin edicidir ve kıyaslama yaptığımız önceki türev olmayan yönteme (MDAM) göre daha iyi sonuçlar vermektedir. Ayrıca, 2019 yılı için elde edilen öngörü sonuçları ışığında en öngörülebilir ülkenin İngiltere olduğu tespit edildi; ikinci sırada Almanya, üçüncü sırada ABD, dördüncü sırada Fransa, beşinci sırada Çin, altıncı sırada Singapur, yedinci sırada Türkiye ve sonuncu sırada ise Hindistan oldu. Örneklem için seçilen sekiz ülke içinden en az öngörülebilir faktörler ise Türkiye'nin uluslararası yolcuları ve Singapur'un uçuş sayısı ve uluslararası uçuş sayısı olmuştur. Etki analizi sonuçları verilmiş ve ayrıca ülkeler arasında ortak veya değişken olduğu tespit edilen bazı faktör etkileri çalışmada tartışılmıştır. Faktörlerin diğer faktörler üzerindeki ağırlıklı ortalama etkisi açısından ve geriye dönük olarak 2019 yılı ve 𝑙=2 yıl için önerdiğimiz varsayım çerçevesinde, güçlü pozitif (olumlu) ve güçlü negatif (olumsuz) etkiler değerlendirilmiştir.
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ÖgeDistilling knowledge of neural networks for image analysis, model compression, data protection and minimization(Graduate School, 2024-07-04)Knowledge distillation is an effective tool for model training, which refers to the process of knowledge transfer between models. In the context of knowledge distillation, the model to be trained with the injected knowledge is named student, where the teacher refers to the model whose knowledge is acquired. It can be exploited for various aims including improving model performance, accelerating the model, and reducing model parameters. Further, with the advent of diverse distillation schemes, it can be efficiently applied in various scenarios and problems. Thus, it has a wide range of application fields including computer vision and natural language processing. This thesis comprises the studies conducted on numerous problems of knowledge distillation, as well as the literature review. The first problem we focus on is hint position selection as an essential element in hint distillation, which is transferring features extracted in intermediate layers, namely hints. First, we demonstrate the importance of the determination of the hint positions. Then, we propose an efficient hint point selection methodology based on layer clustering. For this purpose, we exploit the k-means algorithm with specially designed metrics for layer comparison. We validate our approach by conducting comprehensive experiments utilizing various architectures for teacher-student pairs, hint types, and hint distillation methods, on two well-known image classification datasets. The results indicate that the proposed method achieves superior performance compared to the conventional approach. Another problem focused on in this thesis is model stealing, which refers to acquiring knowledge of a model that is desired to be protected due to the privacy concerns or commercial purposes. Since knowledge distillation can be exploited for model stealing, the concept of the undistillable teacher has been introduced recently, which aims to protect the model from stealing its knowledge via distillation. To contribute to this field, we propose an approach called averager student, whose goal is distilling the undistillable teacher, in this thesis. We evaluate the proposed approach for given teachers which are undistillable or normal. The results suggest that the proposed method outperforms the compared methods whose aim is the same as ours. The last problem we addressed is cross distillation, which means the distillation process between teacher and student models that operate on different modalities. In this work, we introduce a cross distillation scheme that transfers the compressed domain knowledge to the pixel domain. Further, we employ hint distillation which utilizes our previously proposed hint selection method. We evaluate our approach on two computer vision tasks, that are object detection and recognition. The results demonstrate that compressed domain knowledge can be efficiently exploited in a task in the pixel domain via the proposed approach. The proposed approaches in the context of the thesis, contribute to studies on image analysis, model compression, data protection, and minimization. First, our study on the selection of efficient hint positions aims to improve model compression performance, although the proposed approach can also be employed for other distillation schemes. The gains of our method in terms of model compression are presented as well as the performance results of the proposed algorithm. Then, our work on model stealing targets to contribute to the literature on model intellectual property (IP) protection and data protection, where we introduce an algorithm to distill a protected model's knowledge. Moreover, our study on cross distillation provides a contribution to data protection and minimization studies, where we propose a distillation methodology that utilizes compressed domain knowledge on pixel domain problems. Our approach demonstrates a technique that expands limited knowledge by employing different modality data instead of more samples. Since we utilize compressed domain images and eliminate the need for more samples to boost performance, we prevent the use of more data that may be personal or sensitive.
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ÖgeNew RF energy harvesting models for next-generation wireless communication systems(Graduate School, 2022-11-09)Deployment of massive sensor and Internet of Things (IoT) devices in next-generation wireless communication systems reveals energy limitations as one of the challenges. Typically, IoT devices are powered by a battery, which restricts their capacity and working time. Energy harvesting (EH) has been regarded as a promising approach which can increase the life-time of a wireless communication system. In EH, energy is obtained by wind, solar, vibration, etc. Thus, the harvested energy is transformed into electricity and can be used by the desired nodes. However, the aforementioned traditional EH methods are not always available. Additionally, radio frequency (RF) EH has emerged as a key promising technique that enables wireless systems to harvest energy from the incoming signals in the environment. This energy is available as dedicated or ambient energy and can be harvested throughout the whole day. Hence, RF EH can be an effective alternative for empowering battery-free IoT devices, resulting in increased operational time. As RF EH methods for power-constrained nodes, simultaneous wireless information and power transfer (SWIPT) and wireless-powered communication (WPC) schemes are studied in the literature. The SWIPT scheme employs two EH receiver structures: power-splitting (PS) and time-switching (TS). The power-constraint node harvests power from the incoming signal energy in PS EH mode, with one portion of the signal power used for harvesting energy and the remainder for information processing. On the other hand, in the TS EH mode, EH and information processing (IP) are allocated to two non-overlapping time intervals, respectively. Furthermore, the amount of harvested energy is regarded as a linear or nonlinear (NL) function of the input power of the energy receiving (ER) node. The input and output powers of the EH circuit are directly proportional in the linear EH model. For the region with low input power, the NL EH model provides the same amount of energy as the linear model. However, the amount of harvested power saturates to a predefined threshold power at the high input power of the EH circuit. In this thesis, three different RF EH system models are investigated and the closed-form analytical expressions for their performances are derived. Moreover, the performance of each considered system is investigated in terms of bit error probability (BEP) and outage probability. Besides, theoretical derivation results are provided for different system parameters and supported by the Monte-Carlo simulation results. Comprehensive insights into the studied systems are provided, which broaden the view of engineers toward the EH system designs. The first section investigates the bit error rate (BER) performance of a full-duplex (FD) overlay cognitive radio (CR) network with linear/NL EH capability. The studied overlay CR network comprises of a primary transmitter/receiver (PT/PR) pair, a secondary transmitter (ST), and a secondary receiver (SR) operating in FD mode, whereby ST harvests energy from both PT and SR during the first communication time slot. In the second time slot, SR receives its signal from ST while PT sends its signal to PR. The BEP expressions for the primary/secondary users (PU/SU) are obtained analytically and verified through Monte-Carlo simulations using both linear and NL EH models at ST. Additionally, to determine the trade-off between EH and IP, corresponding system performances are evaluated with regard to a power allocation coefficient at SR. The results demonstrate that, in contrast to the non-cooperative (direct transmission) case, the proposed FD-CR system with NL EH improves the PU BEP performance. Besides, SU benefits from the licensed spectrum of PU with significant BER performance. In the second part of the thesis, the performance of a wireless-powered, two-hop, amplify-and-forward relaying system is studied when there is no direct link between the source and the destination. The power-constrained source and relay receive energy from a dedicated power beacon (PB) that broadcasts an energy-bearing signal. For both linear and NL energy harvesting models, theoretical derivations of BEP, outage probability, and throughput expressions are performed. Additionally, Monte Carlo simulations are performed to verify the theoretical results that are presented for various system parameters. The results show how the realistic NL EH model is different from the traditional linear EH model, which overestimates the performance of the system when a large amount of energy is harvested. This results in a misunderstanding of the actual performance of EH systems. However, both models operate similarly and provide appropriate results at low levels of harvested energy. In the last part of this dissertation, the performance of the proposed two novel NL EH models is analyzed in terms of average harvested power, throughput, and BEP. The system comprises a single multi-antenna power-constraint source that transmits its signal to a destination with multiple antennas while harvesting power from a dedicated PB. For a comprehensive analysis of the system, closed-form expressions are derived for Nakagami-$m$ fading channels and the special case of Rayleigh channels. In addition, for existing NL EH models, the simulation results are obtained using the Monte-Carlo method. The results provide a broader picture of EH systems and comprehensively compare the proposed NL EH models to linear, piece-wise linear, and NL EH models available in the literature. As a result, these provide better perspectives on the analysis and design of EH systems.
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ÖgeKesirli kalkülüs ve derin değerlendirme yaklaşımı ile G-8 ülkeleri ve Türkiye için ekonomik verilerin modellenmesi, etki faktörlerinin analizi ve öngörü çalışması(Lisansüstü Eğitim Enstitüsü, 2022-09-21)Temelleri 17. yüzyılda atılmış olan kesirli analiz, türev ve integral operatörlerinin gerçel veya karmaşık sayı kuvvetlerini tanımlayan bir matematiksel analiz dalıdır. Kesirli türevin tanımından kaynaklanan bazı eklemeler sayesinde fiziksel gerçeklere daha uygun olduğu tespit edilmiştir. Kesirli kalkülüsün hafıza özelliği ile ekonomik veriler üzerinde diğer yöntemlere göre daha anlamlı sonuçlar elde edileceği düşünülmektedir. Böylece bu tez çalışmasında, kesirli kalkülüs ve en küçük kareler metodu kullanılarak derin değerlendirme metodolojisi ile geliştirilmiş tek fonksiyon girdili ve çok fonksiyon girdili olmak üzere iki matematiksel yaklaşım önerilmektedir. Bu matematiksel yaklaşımların kodlanması ve uygulaması Matlab üzerinde yapılıp, ülkelerin ekonomik verileri kullanılarak modelleme, etki faktörü analizi ve öngörü çalışması yapılmıştır. Tek fonksiyon girdili derin değerlendirme yaklaşımında girdi faktörünün geçmiş değerleri dikkate alınırken, çok fonksiyon girdili derin değerlendirme metodolojisi ile bir faktörü etkileyen diğer faktörler ve geçmiş verileri de sisteme katılmaktadır. Bu yaklaşımlar ile modelleme, etki analizi ve öngörü metodolojileri geliştirilmiştir. Tek fonksiyon girdili türevli derin değerlendirme yaklaşımı (DAM) ile Amerika, Brezilya, Çin, Hindistan, İtalya, İspanya, İngiltere, Japonya, Türkiye ve Avrupa Birliği için 1960-2018 yıllarına ait Kişi Başına Gayrisafi Yurtiçi Hasıla (GSYİH) verileri ile modelleme ve öngörü çalışması yapılmıştır. Uygulama sonuçlarını inceleyecek olursak en düşük modelleme hatası % 0.81 ile Amerika için elde edilirken, en yüksek modelleme hatası % 7.26 olarak Brezilya'da elde edilmiştir. En düşük test hatası % 0.056 ile İspanya'da görülmüş olup, en yüksek test hatası İngiltere'de %0.91 olarak gerçekleşmiştir. Çizelge 4.3'te ise 2019 için Kişi başına GSYİH değerleri için öngörü yapılmıştır. Çok fonksiyon girdili derin değerlendirme yaklaşımı (M-DAM) ile G-8 ülkeleri ve Türkiye'nin 2000-2019 yıllarına ait ekonomik faktör verileri (Cari Hesap Dengesi (% GSYİH), İhracat (% GSYİH), GSYİH Büyüme Oranı (yıllık %), Tasarruflar (% GSYİH), Yatırımlar (% GSYİH), İthalat (% GSYİH), Enflasyon (% yıllık), Faiz Oranı (Gecelik) ve İşsizlik Oranı) kullanılarak modelleme, etki faktörü analizi ve öngörü çalışması yapılmıştır. İlk olarak modelleme sonuçlarını değerlendirecek olursak, ekonomik faktörlerin modellenmesine yönelik 81 faktör için yapılan modellemede maksimum hata Fransa'nın Enflasyon faktöründe %0.0003112 olarak bulunmuştur. Öngörüye ilişkin olarak da toplam 162 adet öngörü için hatanın %10 dan küçük olduğu oran %75.4 hatanın %10 dan büyük olduğu oran da %24.6 bulunmuştur. Ayrıca 2018 ve 2019 yılları için öngörülebilirlik sınıflamasında, en öngörülebilir ülke 1. sırada Almanya 2. sırada Kanada, Fransa, UK, USA, 3. sırada İtalya ve Japonya, 4. sırada Rusya ve en son sırada (5.) Türkiye'nin olduğu tespit edilmiştir. Faktörlere diğer faktörlerin ağırlıklı ortalama etkisi bakımından 2018-2019 yılları ve geçmişe yönelik 3,5 ve 10 yıl için açıklamış olduğumuz varsayım çerçevesinde güçlü pozitif ve güçlü negatif etkiler değerlendirilmiştir. Ülkelerin ekonomik faktörlerinin etkilerinden bazı öne çıkan ortak veya farklı etki durumlardan bahsedecek olursak; Yatırımların etki ettiği faktörleri incelediğimizde; Kanada, Fransa, Almanya, İtalya, Türkiye ve UK'de ihracatı güçlü pozitif olarak etkilemiştir. Japonya'da orta derecede pozitif, Rusya ve USA'da ise zayıf pozitif olarak etki etmiştir. İthalat; Fransa, Almanya, İtalya, Japonya, Rusya, UK ve USA olmak üzere 7 ülkede ihracata güçlü pozitif, Kanada'da orta derecede pozitif olarak etki etmiştir. Bunun aksine Türkiye'de ihracatı zayıf negatif olarak etkilemiştir. Faiz; Almanya ve Rusya'da ihracatı güçlü pozitif olarak etkilemiştir. Türkiye, UK ve USA'da tasarruflar faizi güçlü pozitif olarak etki etmiştir. Enflasyon ihracat ilişkisi incelendiğinde sadece Türkiye'de enflasyon ihracata güçlü pozitif etki ederken, Rusya'da etkisi görülmemiştir ve diğer yedi ülkede negatif etkilerde bulunmuştur. Tasarruflar Kanada'da faiz oranlarına güçlü negatif olarak etki ederken, Fransa, İtalya, Türkiye, UK ve USA'da güçlü pozitif, Japonya'da orta derecede pozitif, Almanya ve Rusya'da zayıf pozitif olarak etki etmiştir. Gelecek çalışmalarda geliştirdiğimiz çok girişli değerlendirme sistemi (M-DAM) modelimize fonksiyon türevleri de katılarak geliştirilmesi hedeflenmektedir.