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Gövde alan ağlarının güvenliği için fizyolojik sinyaller kullanılarak sözde rasgele anahtarlar oluşturulması
With the help of recent technological advancements especially in the last decade, it has become much easier to extensively and remotely observe medical conditions of the patients. This observation is done through wearable devices named "biosensors" that act as connected nodes on the Body Area Network (BAN). The main goal of these biosensors is to collect and provide critical and sensitive health data concerning the host individual, communicate with each other in order to make decisions based on what has been captured and relay the collected data to remote healthcare professionals. The sensitive nature of this critical data makes it extremely important to process it as securely as possible. Biosensors communicate with each other through wireless medium that is vulnerable to potential security attacks. Therefore, secure mechanisms for both data protection and intra-BAN communication are needed. Moreover, these mechanisms should be lightweight in order to overcome the hardware resource restrictions of biosensors. Random and secure cryptographic key generation and agreement among the biosensors take place at the core of these security mechanisms. In this thesis, we propose SKA-PSAR (Secure Key Agreement Using Physiological Signals with Augmented Randomness) system. The main goal of this system is to produce highly random cryptographic keys for the biosensors for secure communication in a BAN. Similar to its predecessor SKA-PS protocol by Karaoğlan Altop et al., SKA-PSAR also employs physiological signals, such as heart rate and blood pressure, as inputs for the keys and utilizes the set reconciliation mechanism as basic building block. Novel quantization and binarization methods of the Secure Key Agreement Protocol of the proposed SKA-PSAR system distinguish it from SKA-PS in a way that the former has increased the randomness of the generated keys. In addition, the generated cryptographic keys in our proposed SKA-PSAR system have distinctive and time variant characteristics as well as long enough bit sizes that can be considered resistant against a cryptographic attack. Moreover, correct key generation rate of 100% and false key generation rate of 0% have been obtained. Last but not least, results of the computational complexity, communication complexity and memory requirements of our proposed system are quite higher as compared to SKA-PS, but this is a cost that needs to be paid for achieving high randomness level.
Farklı çinko ve azot uygulamaları altında yetişen buğday ve mısırda çinkonun alımı, taşınması ve tanede birikimi
Chronic zinc (Zn) deficiency is a major health issue affecting over two billion people, caused by heavy reliance on staple crops (i.e. wheat, rice and maize) which are inherently low in Zn. This project was devoted to reveal the individual and combined effects of genetic and agronomic Zn biofortification in wheat and maize. The first part focused on understanding the mechanisms involved in differences in uptake and translocation of foliar-applied Zn among wheat and maize species. It was shown that wheat has a greater capacity of leaf uptake and translocation of foliar-applied Zn compared to maize. The second part investigated the effect of nitrogen (N) supply on uptake and accumulation of Zn in maize and wheat. Improving N supply significantly enhanced the shoot accumulation as well as leaf uptake of Zn from foliar Zn sprays in wheat and maize. The third part studied the effectiveness of Zn fertilizers in the form of soil, foliar and soil + foliar for improving growth, grain yield and nutrients uptake by genetically biofortified HarvestPlus wheat genotypes. It was demonstrated that the genetically biofortified genotypes have higher capacity to uptake, utilize and translocate Zn from soil and/or foliar applications as compared to conventional cultivars. These results conclude that the most sustainable way of tackling human Zn deficiency would be to improve grain Zn concentration of cereal crops by unifying genetic and agronomic biofortification strategies.
Nanokompozit yakıt hücreleri
The interactions between the components of the nanocomposite fuel cell electrolyte were investigated. Surface charges were thought to be responsible for the differences in the ionic conductivity. The literature claims that ionic transport in hybrid electrolytes does not happen primarily in the solid oxide or the matrix phase but at the interface between them. The surface charges of oxide particles are dissociating the matrix salt molecules into positive and negative ion complexes. The complex with the opposite charge sticks to the surface of the particles. The counter-ion moves freely under the influence of the electrical field, thus causing fast ionic current. Therefore, it is postulated that by modifying the surface charges one can affect the ionic conductivity. The strength of surface acidity was manipulated by reduction without significantly changing the chemistry of the oxide material. TiO2 (Rutile) was selected as the material whose surface charge was altered by reduction. Ionic conductivities were measured by impedance spectrometry. Surface charges were obtained by isoelectric point measurements. The amounts of reduction were measured by thermogravimetric analysis. Oxides with different surface charges resulted in different ionic conductivities. Sub-stoichiometric oxides had different strength of surface charges that resulted in correlated ionic conductivities. These interactions of surface charges and the ionic conductivities are explained with the help of a developed model for the composite electrolyte.
Metal-organik kafes/grafen oksit türevli gözenekli karbonların platin bazlı oksijen indirgenme reaksiyonu elektrokatalizörlerinde kullanımı
Fossil fuel-based energy economy is bound to change at some point within the 21st century as fossil fuels are inherently limited sources. Energy conversion and storage devices such as batteries, fuel cells, solar cells and supercapacitors need to advance in terms of efficiency for the fruition of a renewable energy ecosystem. Hierarchically porous materials are utilized as catalyst supports in polymer electrolyte membrane fuel cells (PEMFCs) and batteries to increase mass transfer and active site density in the catalyst. Metal-organic frameworks (MOFs) are tailorable crystalline solids where organic linker units are connected to metal centers. They may form molecular gates, channels and pores within the framework in angstrom to nanometer scale. Porous carbons derived from metal-organic frameworks are promising catalyst supports owing to their high surface area and 3-D network structure. In this thesis, a porous carbon has been produced from pyrolysis of a hybrid material based on Zn based MOF called zeolitic imidazolate framework-8 (ZIF-8) and graphene oxide (GO). As observed by physical and chemical characterization, ZIF-8 were coordinated to GO during the synthesis conditions of ZIF-8 and formed a hybrid structure in contrast with simple mixing. Evolution of macro/mesoporosity have been observed when the hybrid was exposed to pyrolyzing temperatures owing to the exfoliating effect of GO on ZIF-8. Pt nanoparticle (Pt NP) deposition on this porous carbon has resulted in catalyst Cat-1, which has been tested via voltammetric experiments against two reference materials; Pt decorated on pyrolyzed ZIF-8 (Cat-0) and Pt decorated on reduced GO (Pt/rGO). Cat-1 exhibits increased mass and specific activity against Pt/rGO at 0.8 V for oxygen reduction reaction (ORR). The nature of increased activity is proposed to be increased mass transport properties of Cat-1 sample that originates from its hierarchical porosity.
Topolojik meta-materyallerde topolojik geçişlerin teşviki ve kuvantum taşınımı
In this Thesis, we propose a novel method that changes the topological order in superconductor wires. We first consider the case of disorder in one dimensional topological superconductors and show how disorder can destroy or create topological order leading to reentrant topological phases. We then consider the effects of a superlattice potential, a zero-average piecewise continuous weak electrostatic potential, on p-wave and s-wave topological superconductor wires. We call such stacked wires leading to weak periodic potential modulation, meta-topological superconductor wires. Topological superconducting wires in their non-trivial phases exhibit Majorana modes as their edge states. We show that by stacking topologically trivial pieces of superconductors, it is possible to induce a topological phase which feature Majorana states at the edges of the superlattice: the meta-topological superconductor. The presence of an electrostatic superlattice allows us to control the topological phase space via the geometry of the electrostatic superlattice. We consider strictly one dimensional meta-topological superconductor wires as well as their quasi-one dimensional multichannel counterparts and show that reentrant topological phases in multichannel meta-topological superconductors occur. Finally, we consider the analogous case of a meta-topological insulator, a quantum anomalous Hall insulator featuring a weak superlattice of magnetic modulation, and show that the transmission can be topologically controlled as a function of energy. The topological protection leads to binary transmission (either transmit or reflect) through the metatopological quantum anomalous Hall insulator, details of which can be controlled by tuning the properties of the weak superlattice.
Genetik algoritması kullanarak serbestleşmiş elektrik piyasalarında gizli anlaşmaları tespit etme
Deregulated electricity markets allow competition over the electricity price among the power companies. However, in an oligopolistic environment, the strategic behavior of the power companies in the electricity market may lead to collusive opportunities. The independent system operator (ISO) is an authorized entity which is responsible for administrating the electricity market. Therefore, ISO shall be able to detect and avoid collusive opportunities among generators. In this study, we propose a metaheuristics approach to assist ISO in the decision-making process to prevent collusions. We develop a method, based on principles of genetic algorithm to detect the collusive opportunities in deregulated electricity markets. We test our algorithm on three problems of varying size. Our results are promising in terms of both speed and accuracy. For the large-scale problem, our algorithm works much faster than the existing alternatives in the literature.
Grafen büyütmede bakırdaki içsel karbonun ve hidrojen yardımıyla tüketilmesinin rolü
Growth of graphene on Cu by chemical vapor deposition (CVD) method is a multidimensional process. Therefore, a comprehensive understanding of the parameters involved in this process is essential to achieve a reproducible and optimized growth recipe. In this work, the role of intrinsic carbon in the bulk of Cu on nucleation of graphene is revealed and it is disclosed that CVD growth of graphene on Cu foil is not a pure surface process. We uncovered that hydrogen-assisted carbon depletion (HACD) effect causes carbon content within Cu bulk to diffuse out during annealing under hydrogen atmosphere and is a critical mechanism in the nucleation of graphene crystals. Additionally, we investigated the role of hydrogen on the diffusion of carbon toward the Cu surface during annealing. We showed that this interplay is not a linear mechanism, but depending on its concentration hydrogen either can boost or diminish the surface density of segregated carbon atoms from bulk. From that, we managed not only to grow a graphitic film on Cu foil but also and more importantly, illustrate spontaneous nucleation of graphene crystals during hydrogen annealing in the absence of external carbon precursor. To our knowledge, this is the first time such a growth has been realized. This finding can clarify the role of intrinsic carbon on the nucleation mechanism of graphene in the CVD process. We also showed that intrinsic carbon in Cu can effect the formation of ad-layers under as-grown graphene layer.
Mikrobolometreler için iki aşamalı zamandan sayısala dönüştürücü içeren ve asenkron çalışan yeni bir sayısal tümleşik okuma devresi
Soğutmasız kızılötesi görüntüleme sistemleri, soğutmalı emsallerine göre hafif ve düşük maliyetli bir alternatiftir. Soğutmasız kızılötesi görüntüleme sistemlerinin en bilinenlerinden biri olan mikrobolometreler tıbbi görüntüleme, termografi, gece görüşü, gözetleme ve endüstriyel proses kontrolü gibi uygulamalar için son yıllarda artarak devam eden araştırmalara konu olmuştur. Bu sistemlerin küçük piksel aralıklarına (< 25 um) sahip olması, enerji verimliliklerinin yüksek olması, gürültü performansının yüksek olması (NETD) (< 50 mK) ve yüksek dinamik aralığa (> 250 K) sahip olması gerekmektedir. Düşük NETD mükemmel mikrobolometre ve okuma gürültüsü performansı gerektirir. Eğer hassas analog sinyaller uzun metal bağlantılarla bağlanmışsa, bu durum genellikle gürültü performansını iyileştirmek için yüksek güç tüketen ve fazla alan kaplayan tampon devreler gerektirir. Bu nedenle hem yüksek gürültü performansına ulaşan hem de düşük güç tüketip az alan kaplayan okuma devrelerinin geliştirilmesi için mimari düzeyde yenilikler gerekmektedir. Buna bağlı olarak, bu tezde zaman uyumlu bir sayısallaştırıcı kullanarak düşük gürültülü çalışmayı mümkün kılan mikrobolometre okuma devreleri için sütun-paralel bir okuma mimarisi önerilmiştir. Önerilen okuma devresi, aktif ve referans mikrobolometrelere sahip olan köprü tipi bir dedektör ağına dayanmaktadır ve yeni bir iki aşamalı entegrasyon mekanizmasını içeren kapasitif bir transpedans yükseltecini (CTIA) kullanmaktadır. CTIA'da modifiye edilmiş bir sıfırlama şeması kullanılarak, giriş tarafında ileri bir rampa ve ardından çıkışta geleneksel geriye entegre eden rampa kullanılır. Bu metod, ölçüm aralığını uzatır ve sinyal-gürültü oranını (SNR) iyileştirir. Senkron bir sayaç tabanlı zamandan sayısala çevirici (TDC), bu aralığı ölçerek sağlam dijitalleştirme sağlar. Dahası, bu teknik aynı zamanda kendi kendine ısınma etkilerini telafi etmenin bir yolunu sağlar. Yüksek dijitalliğe sahip olan önerilen mimari, güçlü ön uç işleme sunuyor ve en son bildirilen tasarımlardan oldukça düşük olan, kanal başına 66 uW güç tüketiyor. Bununla beraber 10 mK NETD değeri ile oldukça iyi bir gürültü performansı sunuyor.
Dikey eksenli rüzgar türbininin enerji çıktısını büyütmek için MZMC ile Bayesçi pekiştirmeli öğrenme
Optimization of energy output of small scale wind turbines requires a controller which keeps the wind speed to rotor tip speed ratio at the optimum value. An analytic solution can be obtained if the dynamic model of the complete system is known and wind speed can be anticipated. However, not only aging but also errors in modeling and wind speed prediction prevent a straightforward solution. This thesis proposes to apply a reinforcement learning approach designed to optimize dynamic systems with continuous state and action spaces, to the energy output optimization of Vertical Axis Wind Turbines (VAWT). The dynamic modeling and load control of the wind turbine are accomplished in the same process. The proposed algorithm is a model-free Bayesian Reinforcement Learning using Markov Chain Monte Carlo method (MCMC) to obtain the parameters of an optimal policy. The proposed method learns wind speed profiles and system model, therefore, can utilize all system states and observed wind speed profiles to calculate an optimal control signal by using a Radial Basis Function Neural Network (RBFNN). The proposed method is validated by performing simulation studies on a permanent magnet synchronous generator-based VAWT Simulink model to compare with the classical Maximum Power Point Tracking (MPPT). The results show significant improvement over the classical method, especially during the wind speed transients, promising a superior energy output in turbulent settings; which coincide with the expected application areas of VAWTs.
Küçük hücreli dışı akciğer kanserinde p53 tarafından regule edilen hk1b metabolic tedavi için yeni bir hedeftir
Deregulation of glycolysis is common in non-small cell lung cancer (NSCLC). p53 controls the cellular metabolism pathway by activating hexokinases (HKs) to increase glycolysis. HK enzymes catalyze the phosphoryl-group-transfer in glucose metabolism. Unlike HK2, HK1 has several transcript variants. However, the functional differential roles of HK1 isoforms in glucose metabolism and the malignant tumor progression are still elusive. Here, we show that primary NSCLC patient tumor cells metabolically differ from the normal lung epithelium in that they display predominant expression of one of the HK1 isoforms, hexokinase1b (HK1b). Interestingly, we show that p53 positively regulates HK1b expression using CRISPR-Cas9 system. We utilized CRISPR-Cas9 system to selectively target specific HK1b isoform in NSCLC and show that silencing HK1b in NSCLC cells inhibits tumorigenesis through diminishing glycolysis and proliferation. Finally, HK1b deletion sensitizes NCLC cells to cisplatin treatment and the combination therapy synergistically increases both the p53- mediated apoptotic cell death by cisplatin and autophagic cell death by increased formation of LC3-II associated autophagic vesicles and myelinoid bodies in an AMPK-independent manner. Our findings reveal that targeting HK1b isoform alone or in combination with cisplatin may represent a novel strategy for NSCLC patients.