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Parabolik oluklu kolektör alıcıları için nanotekslenmiş güneş seçici metalik yüzeyler
No full textThis thesis investigates the potential of replacing commercial solar selective coated receivers in PTC receivers with nanotextured metallic surfaces to reduce the complexity of the fabrication and enhance the feasibility of these receivers. Chromium and stainless steel are selected for their corrosion resistance and thermal stability. Optical parameters of these materials are obtained using Lorentz-Drude Theory, while Gaussian Random Surfaces (GRS) are used to generate nanotextured surfaces. Spectral reflectance spectra over UV-VIS-NIR and IR regions are modeled using the FDTD method to solve Maxwell’s Equations. The opto-thermal properties are derived from spectral reflectance data for each material-surface configuration and applied to a thermal model of the PTC receiver. Nanotextured Cr surfaces demonstrate high solar selectivity with solar absorptance (α_s) of 0.90 and thermal emittance (ε_th) of 0.12 at 400 °C. However, maximum thermal conversion efficiency (η_(th,c)) of 0.69 is achieved at α_s/ε_th = 0.94/0.18, only 2.8% lower than the commercial PTC receiver (0.71). In contrast, AISI 304 achieves similar absorptance (α_s = 0.94) but lower selectivity (ε_th = 0.29), resulting in η_(th,c) = 0.65.Bu tez, parabolik oluklu kolektörlerde (PTC) kullanılan güneş seçici kaplamalı alıcıların, imalat sürecini basitleştirerek ve teknolojinin uygulanabilirliğini artırarak nano dokulu metalik yüzeylerle değiştirilme potansiyelini araştırmaktadır. Bu amaçla, korozyona karşı dirençleri ve termal kararlılıkları nedeniyle Cr ve AISI 304 tercih edilmiştir. Bu malzemelerin optik parametreleri Lorentz-Drude Teorisi kullanılarak belirlenmiş, nano dokulu yüzeyler ise Gauss Rastgele Yüzeyler (GRS) yöntemiyle oluşturulmuştur. UV-VIS-NIR ve IR bölgelerindeki spektral yansıma spektrumları, Maxwell Denklemlerini çözmek için FDTD yöntemi kullanılarak modellenmiştir. Her bir malzeme-yüzey konfigürasyonu için opto-termal özellikler, spektral yansıma verilerinden türetilmiş ve PTC alıcısının termal modeline uygulanmıştır. Nanodokunmuş Cr yüzeyler arasında, 400°C sıcaklıkta 0,90 güneş soğurganlığı (α_s) ve 0,12 ısıl yayıcılık (ε_th) değerleri ile yüksek güneş seçiciliği elde edilmiştir. Bununla birlikte, 0,69'luk maksimum ısıl dönüşüm verimliliği (η_(th,c)) α_s/ε_th = 0,94/0,18 durumunda elde edilmiştir ve bu değer ticari PTC alıcısınınkinden (η_(th,c) = 0,71) sadece %2,8 daha düşüktür. Buna karşılık, AISI 304 benzer soğurganlığa (α_s = 0,94) ancak daha düşük seçiciliğe yani daha yüksek ısıl yayıcılığa (ε_th = 0,29) sahiptir ki bu da η_(th,c) = 0,65 ile ticari alıcının ısıl dönüşüm veriminin %8,5 daha altında kalmaktadır.M.S. - Master of Scienc
COMPARATIVE STUDY BY ADDING BOOTSTRAPPING STAGE IN CONSTRUCTION OF BIOLOGICAL NETWORKS
No full textModel selection methods are very popular in high-dimensional settings in recent years due to the availability of massive amounts of data, specifically from genetical, image progressing, and financial sources. Therefore, the selection of the best estimated model becomes crucial. There are a number of model selection approaches in order to choose the optimal one among alternatives. Among them are the Akaike information criterion, Bayesian information criterion, Consistent Akaike information criterion with Fisher information matrix (CAICF), and Information and COMPlexity (ICOMP), which are very successful in lasso regression when constructing biological networks. In this study, we have proposed these criteria by inserting both non-parametric and Bayesian bootstrap approaches to optimize CAICF and ICOMP selection criteria when the sample size is smaller than the number of genes in the system. We evaluate the performance of the bootstrapping strategy with distinct Monte Carlo scenarios. From the majority of results it is shown that the model selection with bootstraps has higher accuracy than the model selection without bootstraps
From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction
No full textPancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therapeutic options. Risk stratification has traditionally been performed using epidemiological studies and genetic analyses, through which key risk factors, including smoking, diabetes, chronic pancreatitis, and inherited predispositions, have been identified. However, the multifactorial nature of PDAC has often been insufficiently addressed by these methods, leading to limited precision in individualized risk assessments. Advances in artificial intelligence (AI) have been proposed as a transformative approach, allowing the integration of diverse datasets—spanning genetic, clinical, lifestyle, and imaging data into dynamic models capable of uncovering novel interactions and risk profiles. In this review, the evolution of PDAC risk stratification is explored, with classical epidemiological frameworks compared to AI-driven methodologies. Genetic insights, including genome-wide association studies and polygenic risk scores, are discussed, alongside AI models such as machine learning, radiomics, and deep learning. Strengths and limitations of these approaches are evaluated, with challenges in clinical translation, such as data scarcity, model interpretability, and external validation, addressed. Finally, future directions are proposed for combining classical and AI-driven methodologies to develop scalable, personalized predictive tools for PDAC, with the goal of improving early detection and patient outcomes
Stokastik rezerv tahmini ve UFRS 17 altında risk düzeltmeleri
No full textClaim reserving is always a critical concept in the insurance sector. Various approaches, both stochastic and deterministic, are developed and extensively discussed in the literature; deterministic approaches, such as the Chain Ladder (CL) model, are preferred by many practitioners because of their straightforward application. It uses the run-off triangle of paid (or incurred) claims and development factors to predict future reserves. However, they might yield a risk of underestimating or overestimating the reserve estimation due to their lack of ability to capture the randomness in the claims amounts, occurrence, and reported time. Therefore, various techniques are developed to overcome or improve these obstacles in deterministic ones. In this thesis, we apply a time-varying Geometric Brownian Motion (GBM) model to annual development factors to estimate ultimate reserves. We propose the Modified Brownian Bridge (BB) as a non-decreasing stochastic process to increase the time interval while maintaining the structure of claim data. By transforming annual data into monthly intervals, this method reduces over-fitting and makes it possible to model claims behavior more precisely. Furthermore, the thesis also incorporates the International Financial Reporting Standards (IFRS 17) risk adjustment (RA) technique into the reserve estimation framework. In the direction of IFRS 17 regulations, a quantile approach is used to calculate the corresponding RA values under the heavy-tailed distributional assumption such as Log-normal, Gamma and Weibull. Unlike most studies in the literature and educational notes in the sector, we utilize the stochastic discount rate, assumed to follow Cox-Ingersol-Ross (CIR) model, to evaluate discounted ultimate reserves required in RA calculation. The Expectation-Maximization (EM) approach is used for parameter estimation in light of the computational difficulties posed by the complex likelihood function of the CIR model. It is supported by the pseudo-log-likelihood technique and normal approximation. The study explores the sensitivity and robustness of both models, GBM and CL, based on the simulations having the recommended risk measures, VaR and TVaR, and percentiles by IRFS 17. The outputs of RA calculation and the behavior of both models to extremely shocked events are presented.Hasar rezervi, sigortacılık sektöründe her zaman kritik bir kavram olmuştur. Literatürde, hem deterministik hem de stokastik yaklaşımlar geliştirilmiş ve geniş çapta tartışılmıştır. Chain Ladder (CL) modeli gibi deterministik yaklaşımlar, uygulama kolaylığı nedeniyle birçok uzman tarafından tercih edilmektedir. Bu yöntem, ödenmiş (veya tahakkuk eden) hasarların üçgen verilerini ve gelişim faktörlerini kullanarak gelecekteki rezervleri tahmin eder. Ancak bu modeller, hasar tutarlarını, gerçekleşme ve ihbar zamanlarındaki rastgeleliği yakalama yeteneği olmadığından, rezerv tahmininde eksik ya da fazla değerlendirme riski taşıyabilirler. Bu nedenle, deterministik yaklaşımların bu eksikliklerini gidermek veya iyileştirmek için çeşitli teknikler geliştirilmiştir. Bu tezde, yıllık gelişim faktörlerine zamanla değişen Geometrik Brownian Hareketi (GBM) modeli uygulanarak nihai rezerv tahminleri yapılmaktadır. Hasar verilerinin yapısını korurken, zaman aralığını artırmak amacıyla, artmayan stokastik bir süreç olarak Değiştirilmiş Brown Köprüsü (BB) sürecini sunuyoruz. Bu yöntem, yıllık verileri aylık aralıklara dönüştürerek aşırı uyumu azaltır ve hasar davranışını daha hassas şekilde modellemeyi mümkün kılar. Ayrıca, tezde Uluslararası Finansal Raporlama Standartları (IFRS 17) risk ayarlaması (RA) tekniği de rezerv tahmin çerçevesine dahil edilmiştir. IFRS 17 düzenlemeleri doğrultusunda, kalın kuyruklu dağılım varsayımları (örneğin Log-normal, Gamma ve Weibull) altında ilgili RA değerlerini hesaplamak için bir yüzdelik yaklaşımı kullanılmıştır. Sektördeki çoğu çalışma ve eğitim notlarından farklı olarak, RA hesaplamasında gerekli olan iskonto edilmiş nihai rezervleri hesaplamak için Cox-Ingersoll-Ross (CIR) modelini takip eden stokastik bir iskonto oranı kullanılmıştır. CIR modelinin karmaşık olabilirlik fonksiyonunun hesaplanmma zorlukları göz önüne alındığında, parametre tahmini için Beklenti-Maksimizasyon (EM) yaklaşımı kullanılmıştır. Bu süreç, sözde-olabilirlik tekniği ve normal yaklaşımı ile desteklenmiştir. Çalışmada, GBM ve CL modellerinin, IFRS 17’ye göre önerilen risk ölçümleri (Riske Maruz Değer ve Kuyruk-Risk Değeri) ve yüzdelik dilimleri kullanılarak simülasyonlar temelinde duyarlılığı ve dayanıklılığı incelenmiştir. RA hesaplama çıktıları ve her iki modelin aşırı şok içeren olaylara karşı davranışları sunulmuştur.Ph.D. - Doctoral Progra
Application of Artificial Neural Network based Surrogate Models for Parameterized Flow to a Sweptback Wing: An Outlook for Wind Turbine Blades
No full textThe dynamics of blunt-body reentry vehicles are crucial, as they must withstand the intense aerodynamic forces and extreme heat generated during atmospheric reentry. Despite thermal protection benefits, the blunt body shape can cause dynamic instabilities, especially at transonic and low-supersonic speeds, which are crucial during parachute deployment and scientific measurements. Ensuring robust stability requires precise optimization of system parameters and initial conditions. Markov chain Monte Carlo (MCMC) framework, widely used for nonlinear parameter estimation for these systems, is highly sensitive to initial conditions. However, traditional gradient-based methods are prone to getting stuck in local minima, whereas neural network-based approaches often face challenges such as overfitting, hyperparameter sensitivity, and the curse of dimensionality in navigating complex loss landscapes. This study employs Differential Evolution (DE), an evolutionary algorithm, to optimize initial conditions for MCMC parameter estimation. We present a case study on 1-DoF planar motion blunt body vehicle dynamics, demonstrating that DE improves computational efficiency and solution quality. Using DE, the pitch-damping sum coefficients (a = 1.49, b =-0.78, c =-0.37, d =-0.31, and e =-1.01) were optimized to capture nonlinear aerodynamic behavior through a cubic spline model. The reconstructed angle-of-attack (a) trajectories closely matched high-fidelity CFD data, with a sum of squared errors of 700, validating the accuracy of approach. Additionally, DE reduced computational time significantly, achieving a 30.0% reduction when using 10 CPU cores and a 43.6% reduction with 15 CPU cores compared to 5 CPU cores computation. This research advances our understanding of blunt body dynamics and underscores the value of evolutionary algorithms in complex aerospace applications
Interactive biobjective optimization algorithms and an application to UAV routing in continuous space
No full textWe develop interactive optimization algorithms for biobjective problems with continuous nondominated frontiers to search for the most preferred solution of a decision maker who is assumed to have an underlying linear or quasiconvex preference function. We progressively acquire preference information from the decision maker through pairwise comparisons of efficient solutions. We keep reducing the search space based on the obtained preference information and the properties of the form of the preference function. Our algorithms provide a performance guarantee on the final solution's distance from the most preferred solution in the objective function space. We demonstrate the algorithms on complex Unmanned Air Vehicle routing problems in continuous space with nonconvex and continuous nondominated frontiers. We consider the objectives of minimizing the total distance traveled and minimizing the total radar detection threat. We simulate the preference function of the decision maker using several underlying preference functions. The interactive algorithms for all preference functions converge to solutions within the desired accuracies after a few pairwise comparisons
From Which Aspects Do Differentiated Tasks Nurture Mathematically Gifted Students?
No full textMathematically gifted students need differentiated tasks in mixed-ability classrooms, and studies evaluating the use of these tasks in classrooms are of crucial importance. Thus, the present study examines how the use of differentiated tasks nurtures mathematically gifted students from the perspectives of mathematics teachers and their gifted students. Nineteen mathematically gifted students and five mathematics teachers from public and private schools in Turkey constituted the study sample. The data obtained through qualitative methods point out three categories: contributions of differentiated tasks to mathematically gifted students' cognitive, emotional, and social needs. Study findings reflected the importance of differentiated tasks in classrooms from the perspective of the mathematically gifted students, and their teachers
Microplastics from industrial sources: A known but overlooked problem
No full textCurrent studies suggest that industrial wastewaters can be major sources of microplastics (MPs), but specific studies are rare in regard to specific industries and organized industrial zones (OIZs). This study addresses this gap by analyzing two different OIZs and two selected industries from each in terms of their MPs concentrations, characteristics, their diurnal variation and the effect of pretreatments employed by the industries. One OIZ contains an industrial WWTP (IWWTP) so the effect of this plant by the analysis of wastewater from inlet, outlet as well as wastewater and sludge from specific units are evaluated. MPs encountered had a variety of sizes, but the smallest size (38 μm to 425 μm) dominated almost all the samples analyzed. Variety of plastics have been observed including the most common types as well as rare ones. MPs' relative abundances changed and diversity decreased after treatment. It is shown that IWWTPs can reduce MP concentrations up to 95 %, and results in the capture of 127 million particles each day. However, the results also show that industrial wastewaters can still emit 7.6 million particles, which indicates both the magnitude of the problem and the effectiveness of WWTPs, considering that the other OIZ without a WWTP discharges 384 million MPs daily
Erken cumhuriyet dönemi spor politikalarının politik temelleri: türkiye idman cemiyetleri ittifakı dönemi
No full textThis thesis aims to analyze the sports and physical training policies of early
republican Turkey during Turkey Training Community Alliance (TICI) era. In this
context, the political and ideological factors which shaped these policies during the
early years of the Republic will be analyzed through practices and policies in this
field. The ideological significance of sports and physical training for the government
of Turkey will be interpreted, with a focus on factors such as biopolitics, physical
culture, nation-building, and nationalism. In this regard, this study aims to analyze
how the single-party regime of this period ideologically utilized sports and physical
training policies in the nation-building process. The influence and control of the
regime over TICI will be explored, emphasizing the political developments in the
interwar period. Additionally, the background of modern sports in Turkey will be
analyzed, considering the continuity between the early years of the Republic and the
Ottoman Empire.Bu tez genel hatlarıyla Türkiye Cumhuriyeti‘nin ilk yıllarında beden terbiyesi ve spor
politiklarını Türkiye İdman Cemiyetleri İttifakı dönemine odaklanarak politik ve
ideolojik yönleriyle incelemeyi amaçlamaktadır. Bu bağlamda dönemin beden
terbiyesi ve spor politiklarını şekillendiren etkenler bu alandaki uygulamalar
üzerinden analiz edilecektir. Biyopolitika, fiziksel kültür ve ulus inşası gibi ana
faktörlere odaklanarak, beden terbiyesi ve sporun devlet tarafından verilen ideolojik
önemi irdelenecektir. Devletin TİCİ üzerinde artan kontrolü ve etkisi
örneklendirilerek incelenecek, iki savaş arasındaki bu dönemde bu alanın politik
önemi analiz edilecektir. Bu noktada Osmanlı Devleti‘nin son yılları ile Türkiye
Cumhuriyeti‘nin ilk yılları arasındaki devamlılık göz önünde bulundurularak modern
sporların Türkiye‘deki geçmişi de ele alınacaktır.M.A. - Master of Art
How do seasonal changes affect university students’ helpfulness? The Mediating Role of Psychological Well-Being and Anxiety
No full textMevsimsellik, değişen mevsim koşullarından etkilenme düzeyi olarak ifade edilmektedir.
Mevsim geçişlerine bağlı olarak görülen hava sıcaklığı ve gün ışığından yararlanma
süresindeki değişimler, psikolojik sağlık üzerinde etkilidir. Bireylerin mevsimsellik
düzeyleri, psikolojik iyi oluşları, kaygı düzeyleri ve yardımseverliği incelendiğinde, bu
değişkenlerin bir arada incelendiği bir çalışmaya literatürde rastlanmamıştır.
Mevsimsellik ile yardımseverlik ilişkisi ve bu ilişkide psikolojik iyi oluş ile kaygının aracı
rolleri bu çalışmada incelenmiştir. Araştırmaya toplam 296 üniversite öğrencisi (220
kadın ve 76 erkek) katılmıştır. Katılımcılardan Demografik Bilgi Formu, Mevsimsel Gidiş
Değerlendirme Formu, Psikolojik İyi Oluş Ölçeği ve Yardımseverlik Ölçeği’ ni
doldurmaları istenmiştir. Öğrenciler bu araştırmaya çevrim içi form aracılığı ile
katılmıştır. Elde edilen veriler SPSS 22.0 analiz programı ve Hayes Process Makro
eklentisinde bulunan Model 4 aracılığı ile incelenmiştir. Bulgulara göre, mevsimsellik ile
yardımseverlik arasında anlamlı ilişki bulunduğu, ek olarak psikolojik iyi oluş ve
kaygının bu ilişkide aracı rolleri olduğu görülmüştür. Literatür incelendiğinde,
değişkenleri aynı araştırma kapsamında inceleyen araştırma bulgusuna rastlanmaması
ve Türk örneklem grubunun katılımcı olduğu benzer bir çalışmanın yapılmaması
açısından, elde edilen sonuçlar alanyazına önemli bilgiler sunmaktadır.Seasonality is defined as the level of being affected by changing seasonal conditions.
Changes in air temperature and daylight hours due to seasonal transitions impact
psychological health. There are no studies in the literature that examine the levels of
individuals affected by seasonality, psychological well-being, anxiety levels, and
helpfulness together. The relationship between seasonality and helpfulness and the
mediating roles of psychological well-being and anxiety in this relationship was
examined in this study. A total of 296 university students (220 females and 76 males)
participated in this study. The participants were asked to fill out the Demographic
Information Form, the Seasonal Pattern Questionary, the Psychological Well-Being
Scale, and the Helpfulness Scale. Students participated in this study through an online
form. The data obtained were analyzed through the SPSS 22.0 analysis program and
Model 4 in Hayes Process Macro. According to the findings, there was a significant
relationship between seasonality and helpfulness; psychological well-being and anxiety
mediated this relationship. A review of the literature reveals significant gaps in research
findings, particularly regarding the variables addressed in this study. Additionally, there
is a notable lack of similar studies involving a Turkish sample group.Publisher's Versio