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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Conference Object Differential and Linear Analyses of DIZY Through MILP Modeling(Springer Science and Business Media Deutschland GmbH, 2026) İlter, M.B.; Koçak, O.; Kara, O.; Sulak, F.In this work, we present the first independent security analysis of DIZY, a recently proposed ultra-lightweight stream cipher with two variants: DIZY-80 and DIZY-128. Our analysis focuses on DIZY’s resistance to linear and differential cryptanalysis. We employ a formal technique known as Mixed Integer Linear Programming (MILP), which enables us to model the internal structure of DIZY and search for characteristics that describe how XOR differences or linear masks propagate through the cipher. Specifically, we construct such characteristics to evaluate how many S-boxes become “active” during keystream generation, as this number directly affects the cipher’s resistance to these attacks. Contrary to the designers’ claim that any linear or differential characteristic over 8 rounds must involve at least 20 active S-boxes in DIZY-80 and 22 in DIZY-128, we identify characteristics with only 18 differentially or linearly active S-boxes and 20 linearly active S-boxes, respectively. We mount two distinguishing attacks on each cipher. Our 3-round linear distinguishing attack requires 223 bits of keystream, while the 4-round version requires 235 bits for DIZY-128 and DIZY-80, respectively. Our 2-round differential resynchronization attacks succeed using only the first four bytes of keystream data from approximately 230 and 226 different initializations with chosen initialization vectors (IVs) for DIZY-128 and DIZY-80, respectively. While these attacks do not compromise the full 15-round version of the cipher, they provide valuable insights into the design of DIZY and contribute to a deeper understanding of the security requirements of its diffusion layer. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.Article Performance Assessment of a Solar-Geothermal Based Organic Rankine Cycle System Producing Green Hydrogen(Pergamon-Elsevier Science Ltd, 2026-02) Atak, Yagmur Nalbant; Nalbant Atak, YagmurThis study presents a comprehensive thermodynamic (energy and exergy) analysis of a solar-geothermal-based Organic Rankine Cycle (ORC) system integrated with a proton exchange membrane (PEM) electrolyzer for green hydrogen production. The system simultaneously harnesses the continuous heat of a geothermal source and the intermittent solar thermal input to ensure stable hydrogen generation. The effects of key operating parameters (solar radiation intensity, production well temperature, inlet temperature of the PTSC fluid, and ORC and PTSC working fluid types were investigated. The results reveal that higher solar radiation intensities significantly enhance both power generation and hydrogen yield, increasing the hydrogen production rate from 22.9 to 24.3 kg/h and the net electrical output from 4.17 to 4.41 MW. Similarly, increasing the geothermal well temperature from 400 K to 600 K significantly enhances hydrogen production, rising from 15.9 to 45.5 kg/h, and increases the net power output by approximately 185 %. However, the exergy efficiency decreases slightly from 0.26 to 0.17 due to increased irreversibilities at higher temperatures. The optimal working pair was determined to be R134a for the ORC and Therminol VP1 for the PTSC, achieving an electrical efficiency of 9.27 %, exergy efficiency of 25.13 %, and hydrogen production rate of 29.02 kg/h. In addition, the exergy analysis showed that the PTSC (similar to 35 %) and condenser (similar to 24.6 %) are the dominant sources of irreversibility. Finally, the Taguchi optimization identified the optimal configuration (Gb = 3.50 x 10(-4) MW/m(2), T-a = 500 K, T-11 = 600 K, and ORC fluid = R134a) yielding the highest overall efficiency and robust performance under variable operating conditions.Article The Purpose and Legal Nature of the Condition of `Prohibition of Use` in Mesne Profit Claims Between Joint Owners(Istanbul Univ, Fac Law, 2025-01-02) Goka, Ekin KorkmazThe Court of Cassation, through its established case law, has delineated the condition of "prohibition of use" ("in tifadan men") in instances where other joint owners initiate a claim for mesne profits ("ecrimisil") against a joint owner who is in actual use of property subject to joint ownership. Nevertheless, the definition and legal function of this condition remain ambiguous, both in doctrine and in practice. Some scholars perceive it as an unjustified limitation on property rights and criticize the case law. However, the study reveals that the condition required by the Court of Cassation is a legal construct inherently rooted in the structural logic of joint ownership particularly the scope of use and utilization rights. This is because, in order for one joint owner to file a claim for compensation against another, it is first necessary to determine the limits of the latter's right of use and whether these limits have been exceeded. In this context, the term "prohibition of use" functions as a practical criterion for determining whether the actual use of the property by a joint owner is justified. In this study, the condition of "prohibition of use" is first defined in light of the decisions ofthe Court of Cassation; then, the purpose of this condition is revealed within the framework ofthe 'use' and "utilization" rights of the co owners in jointly owned properties. Subsequently, the cases recognized as exceptions bythe Court ofCassation are evaluated in line with the purpose ofthe condition, and finally, the legal nature of "prohibition of use" is determined.Article Univariate Deep Learning Models for Short-Term Electricity Load Forecasting from Renewables(Ankara Univ, Fac Sci, 2025-12-24) Kabran, Fatma Basoglu; Unlu, Kamil Demirberk; Başoğlu Kabran, FatmaRenewable energy offers a cost-effective, carbon-free solution for energy needs, while protecting the environment. Accurate forecasting of electricity generation from renewable sources is crucial for the efficiency of modern power grids. This study employs a univariate deep learning approach to predict daily renewable energy generation, evaluating Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) as candidate models. Five performance metrics-mean absolute error, root mean squared error, mean absolute percentage error, mean absolute scaled error and the coefficient of determination-are employed to assess the forecasting power of the algorithms. The empirical results show that CNN outperforms other models, achieving an R2 of almost 94%. This research shows that the univariate model based on historical data of electricity load generated from renewables can accurately predict day-ahead electricity load, even without meteorological data.Article Legalizing Anti-Gender Ideology and Civil Society Resistance in Turkey(Pergamon-Elsevier Science Ltd, 2026-05) Keysan, Asuman Ozgur; Özgür Keysan, AsumanThis study investigates how feminist, LGBTQI+, labour, and human rights organisations in Turkey frame and negotiate the legal institutionalisation of anti-gender ideology and how these processes generate strategic yet fragile cross-movement alliances. Drawing on Benford and Snow's framing theory and Yuval-Davis's transversal politics, the analysis is based on semi-structured interviews conducted with activists from ten organisations between April and June 2025 and organisational documents. The study conceptualises anti-gender politics in Turkey not as a societal backlash but as a state-driven, multi-layered project of "masculinist entrenchment (Yetis, & O<spacing diaeresis>zd & uuml;zen, 2024)" that restructures legal, ideological, and affective arenas. The findings demonstrate that activists increasingly reframe anti-gender assaults as systemic attacks on democracy, rights, and equality, producing a shift from issue-based coordination to what this article terms "strategic coexistence", a hybrid alliance formed across previously distant ideological and organisational positions. Diagnostic framing identifies anti-gender reforms as an existential threat, prognostic framing centres on alliance-building, movement memory, and inclusive organisational practices and motivational framing foregrounds shared destiny, solidarity, and the symbolic significance of LGBTQI+ rights. The analysis reveals that while this recontextualisation widens the basis for coalition, the resulting alliance remains structurally unbalanced and fragile. Hierarchical power relations, uneven exposure to political risk, and selective silence, particularly regarding LGBTQI+ concerns, limit the depth and durability of alliances. In this context, LGBTQI+ rights serve both as a catalyst for broad-based mobilisation and as a litmus test for democratic commitment, disclosing the limitations of transversal solidarity under authoritarian regimes.Article Citation - Scopus: 1Robust Divergence-Based Tests of Hypotheses for Simple Step-Stress Accelerated Life-Testing Under Gamma Lifetime Distributions(Elsevier, 2026-09) Balakrishnan, Narayanaswamy; Jaenada, Maria; Pardo, LeandroMany modern devices are highly reliable, with long lifetimes before their failure. Conducting reliability tests under actual use conditions may require therefore impractically long experimental times to gather sufficient data for developing accurate inference. To address this, Accelerated Life Tests (ALTs) are often used in industrial experiments to induce product degradation and eventual failure more quickly by increasing certain environmental stress factors. Data collected under such increased stress conditions are analyzed, and results are then extrapolated to normal operating conditions. These tests typically involve a small number of devices and so pose significant challenges, such as interval-censoring. As a result, the outcomes are particularly sensitive to outliers in the data. Additionally, a comprehensive analysis requires more than just point estimation; inferential methods such as confidence intervals and hypothesis testing are essential to fully assess the reliability behaviour of the product. This paper presents robust statistical methods based on minimum divergence estimators for analyzing ALT data of highly reliable devices under step-stress conditions and Gamma lifetime distributions. Robust test statistics generalizing the Rao test and divergence-based tests for testing linear null hypothesis are then developed. These hypotheses include in particular tests for the significance of the identified stress factors and for the validity of the assumption of exponential lifetimes.Article Fröbenius Expansions for Second-Order Random Differential Equations: Stochastic Analysis and Applications to Lindley-Type Damping Models(Elsevier, 2026-09) Zeghdoudi, Halim; Kerker, Mohamed Amine; Boduroglu, ElifThis paper develops a Frobenius series framework for the stochastic analysis of second-order random differential equations of the form Y(t) + A(t)Y(t) = 0, where the damping coefficient A(t) is a positive stochastic process and the initial conditions are square-integrable random variables. Assuming mean-square analyticity of A(t) in a neighborhood of the initial time, we establish existence and uniqueness of the solution in L2(Omega) and derive exponentially convergent truncation error bounds for the associated Frobenius expansion. The resulting series representation enables the numerical approximation of the probability density function of Y(t) via Monte Carlo simulation. To improve computational efficiency, a control variates strategy is incorporated for variance reduction. A comprehensive numerical study is conducted for a broad family of positive, right-skewed damping distributions, including the Lindley, XLindley, New XLindley (NXLD), Gamma-Lindley, Inverse-Lindley, Truncated-Lindley, Log-Lindley, and a newly proposed Mixed Lindley-Uniform model. The simulations illustrate how different tail behaviors and boundedness properties of the damping coefficient influence the stochastic dynamics and the accuracy of density estimation. Finally, stylized applications to option pricing and Value-at-Risk estimation are presented to illustrate how the Frobenius-based framework and control variates methodology can be embedded within standard uncertainty quantification workflows. Overall, the proposed approach provides a flexible and computationally efficient tool for the analysis of randomly damped dynamical systems.Article Crack Detection on Asphalt Runway Using Unmanned Aerial Vehicle Data with Non-Crack Object Removal and Deep Learning Methods(Pontificia Univ Catolica Chile, Escuela Construccion Civil, 2025-12-30) Tapkin, Serkan; Tercan, Emre; Bostan, Atila; Sengul, GokhanUnmanned aerial vehicles are extensively utilized for image acquisition in a cheap, fast, and effective way. In this study, an automatic crack detection method with non-crack object removal and deep learning-based approaches are developed and tested on images captured by unmanned aerial vehicle. The motivation of this study is to detect either a crack exists or not in the asphalt-runway. The novelty of this study lies in integrating a non-crack artifact removal process with six classical edge detectors and comparing the resulting performance with four lightweight CNN models on the same UAV-acquired runway image dataset, enabling a unified evaluation of classical and learning-based approaches. For deep learning-based approach, four lightweight CNN models, namely GoogleNet, SqueezeNet, MobileNetv2, and ShuffleNet, are trained and the best accuracy of %87.9 is obtained whenever GoogleNet model is used. For the non-crack object removal approach, exclusion of non-crack objects from the images is the first step, where crack-detection which makes use of edge-detection techniques is the latter. In the study, Sobel, Prewitt, Canny, Laplacian of Gaussian, Roberts and Zero Cross edge detection algorithms are examined and their success rates in detecting cracks are comparatively presented. With sensitivity=0.981, specificity=0.744, accuracy=0.917, precision=0.912 and F-score=0.945 values Canny algorithm performs significantly better than others in detecting the cracks. This study provides enough evidence for the practicability of automated crack detection on unprocessed digital photographs by the results of the study conducted on asphalt runway.Article Citation - WoS: 1Citation - Scopus: 1Regular AdS3 Black Holes From a Regularized Gauss-Bonnet Coupling(Elsevier, 2026-01) Alkac, Gokhan; Mesta, Murat; Unal, GonulWe obtain a three-dimensional bi-vector-tensor theory of the generalized Proca class by regularizing the Gauss-Bonnet invariant within the Weyl geometry. We show that the theory admits a regular AdS3 black hole solution with primary hairs. Introducing a deformation in the theory, a different regular AdS3 black hole solution is obtained. Charged generalizations of these solutions are given by coupling to Born-Infeld electrodynamics.Article Citation - Scopus: 1Randomised Comparison Between Navigation and Non-Navigation Camera Control Performance in a Surgical Simulation Task Using a Haptic Device Interface(Wolters Kluwer Medknow Publications, 2025-03-05) Cagiltay, Nergiz Ercil; Topalli, Damla; Tuner, Emre; Berker, MustafaIntroduction:Navigation skills for controlling the camera in the surgical field are critical for many minimally invasive surgery (MIS) procedures. Currently, endoscopes lack integrated navigation aids, making camera control a challenging task. This experimental study aims to investigate the effect of navigation guidance on the performance of beginners.Patients and Methods:A custom computer-based simulation environment was developed for this study, featuring two conditions - one with navigation guidance and one without - focussed on a camera-cleaning task. Participants (64 beginners) were randomly assigned to one of these groups and used two haptic devices to simulate the endoscope and surgical tools.Results:Participants in the guided condition performed significantly better than those in the unguided condition. Notably, female participants completed the task in significantly less time under the guided condition compared to the unguided one.Conclusion:These findings suggest that incorporating navigation aids into endoscope interfaces could improve user performance, especially for beginners. Medical device manufacturers should consider adding navigation features to enhance usability. In addition, simulation-based instructional systems should integrate navigation aids to better support surgical training.