Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Conference Object Citation - WoS: 5Citation - Scopus: 6Fractional Differentiation and Its Applications (Fda08)(Iop Publishing Ltd, 2009) Baleanu, D.; Tenreiro Machado, J.A.The international workshop, Fractional Differentiation and its Applications (FDA08), held at Cankaya University, Ankara, Turkey on 5-7 November 2008, was the third in an ongoing series of conferences dedicated to exploring applications of fractional calculus in science, engineering, economics and finance. Fractional calculus, which deals with derivatives and integrals of any order, is now recognized as playing an important role in modeling multi-scale problems that span a wide range of time or length scales. Fractional calculus provides a natural link to the intermediate-order dynamics that often reflects the complexity of micro- and nanostructures through fractional-order differential equations. Unlike the more established techniques of mathematical physics, the methods of fractional differentiation are still under development; while it is true that the ideas of fractional calculus are as old as the classical integer-order differential operators, modern work is proceeding by both expanding the capabilities of this mathematical tool and by widening its range of applications. Hence, the interested reader will find papers here that focus on the underlying mathematics of fractional calculus, that extend fractional-order operators into new domains, and that apply well established methods to experimental and theoretical problems. The organizing committee invited presentations from experts representing the international community of scholars in fractional calculus and welcomed contributions from the growing number of researchers who are applying fractional differentiation to complex technical problems. The selection of papers in this topical issue of Physica Scripta reflects the success of the FDA08 workshop, with the emergence of a variety of novel areas of application. With these ideas in mind, the guest editors would like to honor the many distinguished scientists that have promoted the development of fractional calculus and, in particular, Professor George M Zaslavsky who supported this special issue but passed away recently. The organizing committee wishes to thank the sponsors and supporters of FDA08, namely Cankaya University represented by the President of the Board of Trustees Sitki Alp and Rector Professor Ziya B Güvenc, The Scientfic and Technological Research Council of Turkey (TUBITAK) and the IFAC for providing the resources needed to hold the workshop, the invited speakers for sharing their expertise and knowledge of fractional calculus, and the participants for their enthusiastic contributions to the discussions and debates. © 2009 The Royal Swedish Academy of Sciences.Article Citation - Scopus: 1Bit Segmentation of Non-Line of Sight Data in Optical Camera Communication Using U-Net(Iop Publishing Ltd, 2025) Ozkan, Cagla; Inan, Tolga; Baykal, YahyaOptical Camera Communication (OCC) utilizes image sensors to decode modulated light signals from light-emitting diodes (LEDs), offering a cost-effective solution for wireless communication. However, data extraction in non-line-of-sight (NLOS) conditions is challenging due to signal distortions caused by obstacles and reflections. Traditional segmentation techniques, such as Otsu's thresholding and adaptive thresholding, are computationally efficient but struggle with lighting variations, background interference, and high-frequency distortions, limiting their effectiveness in real-world OCC applications. To address these limitations, we propose a U-Net convolutional neural network, trained on a diverse dataset covering various camera distances, lighting conditions, and reflection levels to improve segmentation accuracy. The proposed model achieves up to 25% BER improvement, outperforming traditional thresholding methods and ensuring more reliable bit extraction in challenging OCC environments. These advancements make deep learning a promising approach for improving OCC applications such as indoor positioning, smart transportation, and secure optical wireless communication.Article Citation - WoS: 5Citation - Scopus: 6Bit Error Rate of M-Pulse Position Modulated Laser Beams for Vertical Links Operating in Weak Oceanic Turbulence(Iop Publishing Ltd, 2024) Gercekcioglu, Hamza; Baykal, YahyaThe on-axis scintillation index of laser beams is investigated by employing the Rytov method in a weakly turbulent oceanic medium for up/downlink coupling of laser communication between any underwater vehicles or divers. For vertical links, the formulation of the on-axis scintillation index of laser beams is derived analytically and evaluated for plane, collimated Gaussian and spherical beams in specific mediums, including the Atlantic Ocean at mid and low latitudes associating temperature and salinity changes at low latitudes, at mid latitude-summer and at mid latitude-winter. Using the scintillation index, bit error rate (BER) performance of M-pulse position modulation is investigated for these types of laser beams. The variations of the scintillation index against the uplink/downlink propagation distances, source size and zenith angle are examined, and BER variations versus the Kolmogorov microscale and the symbol orders, and results are compared. It is noted that the behavior of the scintillation index that depends on the relative strength of temperature and salinity fluctuations which changes in depth, is different for uplink/downlink and for each latitude due to its distinct characteristics. The source size that minimizes the scintillation index values is in the range of about 0.1 cm-0.2 cm for all latitudes.Article Citation - WoS: 4Citation - Scopus: 1Degradation of Signal-To Ratio Due To Turbulence in Various Biological Tissues(Iop Publishing Ltd, 2024) Baykal, YahyaWhen a biological tissue is excited by an optical beam, the presence of turbulence in the tissue causes the signal-to-noise ratio (SNR) to degrade. This degradation is in reference to the SNR value in the absence of tissue turbulence. The effect of tissue turbulence in reducing the SNR is examined. SNR reductions are examined for various types of biological tissues such as liver parenchyma (mouse), intestinal epithelium (mouse), upper dermis (human). Also, SNR reductions in the turbulent tissue are evaluated against the changes in the strength coefficient of the refractive-index fluctuations, fractal dimension, characteristic length of heterogeneity, small length-scale factor, tissue length, wavelength and the source size.Article Design, Optimization, Simulation, and Implementation of a 3d Printed Soft Robotic Peristaltic Pump(Iop Publishing Ltd, 2024) Totuk, Onat Halis; Mistikoglu, Selcuk; Guvenc, Mehmet AliThis study presents an innovative approach to fluidic pumping using soft robotics, designed to circulate fluid through soft conduits for delicate environments like blood streams where traditional peristaltic pumps may not be feasible. A novel soft robotic peristaltic pump is optimized and implemented, featuring 3D printed ring-shaped actuators and a PDMS pipe housing a Newtonian fluid. The design includes a three-stage actuator ring structure, actuated sequentially for peristaltic motion. A parametric finite element model predicts the required pressure, and the Mooney-Rivlin 5 Parameters hyper-elastic material model ensures accurate material properties. Optimization uses response surface analysis in Minitab and MATLAB Simulink Simscape simulations to achieve maximum flow rate with minimal power and pressure. Experimental validation confirms the simulations, achieving an optimal flow rate of 0.27 ml s(-1) at a 450 ms cycle, with minor discrepancies due to friction and measurement errors. This study demonstrates the scalability of linearly sequenced soft squeeze actuators into an effective pump, validated by both simulation and experiments. Future applications include medical devices addressing deep venous thrombosis, with further research exploring control theory for optimization and comparing performance with conventional pumps to enhance practical applicability.Article Citation - WoS: 1Citation - Scopus: 2Thermodynamic and Dielectric Properties of Hexagonal Barium Titanate Near the Phase Transitions(Iop Publishing Ltd, 2024) Yurtseven, Hamit; Kiraci, AliThe critical behavior of the thermodynamic quantities is studied for the two phase transitions near the transition temperatures (74 K and 222 K) in the hexagonal (h) BaTiO3. A linear relationship has been established between the variations of the frequency shifts and of the dielectric constant by using the literature data in h-BaTiO3. Temperature and pressure dependence of the mode Gr & uuml;neisen parameters ( gamma p and gamma T ) are also described by a power-law formula as the other thermodynamic parameters near Tpt in h-BaTiO3. Our results show that they explain the observed behavior adequately, in particular soft-mode frequency, dielectric constant, thermal expansion, the excess specific heat and the entropy near Tpt in h-BaTiO3. Temperature dependence of the isobaric mode Gr & uuml;neisen parameter ( gamma p ), enthalpy and the Gibbs free energy, which we have evaluated, can be compared with experiments in h-BaTiO3.Article Citation - WoS: 1Citation - Scopus: 2Scintillation Index and Outage Probability of Vortex Gaussian Beams for Horizontal Links in Weak Atmospheric Turbulence(Iop Publishing Ltd, 2024) Gercekcioglu, Hamza; Baykal, YahyaUsing the Rytov method, the off-axis scintillation index for a Gaussian vortex beam is examined in horizontal laser communication links operating in a weakly turbulent atmosphere. The performance of laser communication systems, defined in this study by the outage probability, is evaluated using the lognormal distributed intensity to find the scintillation index. The off-axis scintillation index of vortex Gaussian beams is analytically derived and evaluated in horizontal atmospheric links. The scintillation index obtained from the figures drawn versus the source size and propagation length is used to calculate the outage probability. It is found that turbulence affects vortex Gaussian beams less than non-vortex Gaussian beams. Our important finding is that the scintillation index is reduced when the topological charge increases.Article Citation - WoS: 3Citation - Scopus: 5Depth Dependence of Oceanic Turbulence Optical Power Spectrum Under Any Temperature and Salinity Concentration(Iop Publishing Ltd, 2024) Gercekcioglu, Hamza; Baykal, YahyaThe Oceanic Turbulence Optical Power Spectrum (OTOPS) with depth variations is acquired under any temperature and salinity concentration. It is supposed that specific medium is the Atlantic Ocean at high latitude and the Pacific Ocean at high, mid and low latitudes. For the OTOPS model, a depth-varying functions that include low-latitude, high- and mid-latitude-summer and mid-latitude-winter salinity and temperature changes are found. With the help of the equations for the temperature and salinity changes, figures are obtained for the eddy diffusivity ratio depth of seawater and OTOPS model against the depth and kappa at these media. In the ocean, downlink (uplink) is defined as the optical wireless communication link where the receiver (transmitter) is located at a deeper point than the transmitter (receiver), i.e., in the downlink, optical signal proceeds from a point close to ocean surface to deeper ocean and in the uplink, optical signal proceeds from deeper ocean to a point close to ocean surface. In this paper, the OTOPS model is investigated on how its properties change in the underwater environment in downlink and uplink. Different behavior of the OTOPS model is exhibited.Article Citation - WoS: 37Citation - Scopus: 37Advanced Fractional Calculus, Differential Equations and Neural Networks: Analysis, Modeling and Numerical Computations(Iop Publishing Ltd, 2023) Karaca, Yeliz; Vazquez, Luis; Macias-Diaz, Jorge E.; Baleanu, DumitruMost physical systems in nature display inherently nonlinear and dynamical properties; hence, it would be difficult for nonlinear equations to be solved merely by analytical methods, which has given rise to the emerging of engrossing phenomena such as bifurcation and chaos. Conjointly, due to nonlinear systems' exhibiting more exotic behavior than harmonic distortion, it becomes compelling to test, classify and interpret the results in an accurate way. For this reason, avoiding preconceived ideas of the way the system is likely to respond is of pivotal importance since this facet would have effect on the type of testing run and processing techniques used in nonlinear systems. Paradigms of nonlinear science may suggest that it is 'the study of every single phenomenon' due to its interdisciplinary nature, which is another challenge encountered and needs to be addressed by generating and designing a systematic mathematical framework where the complexity of natural phenomena hints the requirement of identifying their commonalties and classifying their various manifestations in different nonlinear systems. Studying such common properties, concepts or paradigms can enable one to gain insight into nonlinear problems, their essence and consequences in a broad range of disciplines all forthwith. Fractional differential equations associated with non-local phenomena in physics have arisen as a powerful mathematical tool within a multidisciplinary research framework. Fractional differential equations, as one extension of the fractional calculus theory, can yield the evolution of various systems properly, which reinforces its position in mathematics and science while setting stage for the description of dynamic, complicated and nonlinear events. Through the reflection of the systems' actual properties, fractional calculus manifests unforeseeable and hidden variations, and thus, enables integration and differentiation, with the solutions to be approximated by numerical methods along with modeling and predicting the dynamics of multiphysics, multiscale and physical systems. Neural Networks (NNs), consisting of hidden layers with nonlinear functions that have vector inputs and outputs, are also considerably employed owing to their versatile and efficient characteristics in classification problems as well as their sophisticated neural network architectures, which make them capable of tackling complicated governing partial differential equation problems. Furthermore, partial differential equations are used to provide comprehensive and accurate models for many scientific phenomena owing to the advancements of data gathering and machine learning techniques which have raised opportunities for data-driven identification of governing equations derived from experimentally observed data. Given these considerations, while many problems are solvable and have been solved, efforts are still needed to be able to respond to the remaining open questions in the fields that have a broad range of spectrum ranging from mathematics, physics, biology, virology, epidemiology, chemistry, engineering, social sciences to applied sciences. With a view of different aspects of such questions, our special issue provides a collection of recent research focusing on the advances in the foundational theory, methodology and topical applications of fractals, fractional calculus, fractional differential equations, differential equations (PDEs, ODEs, to name some), delay differential equations (DDEs), chaos, bifurcation, stability, sensitivity, machine learning, quantum machine learning, and so forth in order to expound on advanced fractional calculus, differential equations and neural networks with detailed analyses, models, simulations, data-driven approaches as well as numerical computations.Article Citation - WoS: 5Citation - Scopus: 6Underwater Turbulence Effect on Optical Imaging(Iop Publishing Ltd, 2022) Gokce, Muhsin Caner; Baykal, Yahya; Ata, YalcinModulation transfer function (MTF) of oceanic turbulence plays an essential role in the design and quality of underwater image sensing systems capturing optical signals. MTF gives clues about the characteristics of turbulence which can help image reconstruction where the image resolution can be increased in this way. In the paper, under the conditions of weak turbulence and Gaussian beam propagation, we derive the modulation transfer function for short-exposure and long-exposure images based on the recently developed turbulence spectrum model: Oceanic turbulence optical power spectrum (OTOPS). With the aid of the OTOPS model, the effect of measurable turbulence parameters, namely average temperature, average salinity concentration, and temperature-salinity gradient ratios, as well as imaging system parameters, namely receiver aperture radius and wavelength of the laser source on the MTF are reported. Obtained results indicate that MTF rapidly decreases with increasing relative spatial frequency and turbulence strength. Turbulence becomes stronger with the increase in the average temperature, average salinity concentration, energy dissipation rate, temperature-salinity gradient ratio and with the decrease in the temperature dissipation rate, wavelength.