https://hdl.handle.net/20.500.12440/5668 Sun, 12 Apr 2026 19:25:32 GMT 2026-04-12T19:25:32Z https://hdl.handle.net/20.500.12440/5970 The impact of blockchain technology on accounting, auditing, and assurance practices: Turkey case Selimoglu, Seval; Yesilcelebi, Gul; Altunel, Mehtap The purpose of this study is to examine the impact of blockchain technology on accounting, auditing, and assurance practices. For this purpose, the relevant national and international literature on the accounting, auditing, and assurance practices of blockchain technology has been reviewed. As a result of the research, the advantages and disadvantages of blockchain technology were evaluated and categorized. As a result of the study, it has been determined that the blockchain technology has a great effect on accounting, auditing, and assurance. Sun, 01 Jan 2023 00:00:00 GMT https://hdl.handle.net/20.500.12440/5970 2023-01-01T00:00:00Z https://hdl.handle.net/20.500.12440/5858 Simultaneous design of morphing hexarotor and autopilot system by using deep neural network and SPSA Kose, Oguz; Oktay, Tugrul Purpose: The purpose of this paper is to optimize the simultaneous flight performance of a hexarotor unmanned aerial vehicle (UAV) by using simultaneous perturbation stochastic approximation (i.e. SPSA), deep neural network and proportional integral derivative (i.e. PID) according to varying arm length (i.e. morphing). Design/methodology/approach: In this paper, proper PID gain coefficients and morphing ratio were obtained using the stochastic optimization method, also known as SPSA to maximize flight efficiency. Because it is difficult to establish an analytical connection between the morphing ratio and hexarotor moments of inertia, the deep neural network was used to obtain the moments of inertia according to the morphing ratio. By using SPSA and deep neural network, the best performance indexes were obtained and both longitudinal and lateral flight simulations were performed with the obtained data. Findings: With SPSA, the best PID coefficients and morphing ratio are obtained for both longitudinal and lateral flight. Because the hexarotor solid body model changes according to the morphing ratio, the moment of inertia values used in the simulations also change. According to the morphing ratio, the moment of inertia values was obtained with the deep neural network over a created data set. Research limitations/implications: It takes a long time to obtain the morphing ratio suitable for the hexarotor model and the PID gain coefficients suitable for this morphing ratio. However, this situation can be overcome with the proposed SPSA. In addition, it takes a long time to obtain the appropriate moments of inertia according to the morphing ratio. However, in this case, it was overcome using the deep neural network. Practical implications: Determining the morphing ratio and PID gain coefficients using the optimization method, as well as determining the moments of inertia using the deep neural network, is very useful as it can increase the efficiency of hexarotor flight and flight efficiently with different arm lengths. With the proposed method, the hexarotor design performance criteria (i.e. rise time, settling time and overshoot) values were significantly improved compared to similar studies. Social implications: Determining the hexarotor flight parameters using SPSA and deep neural network provides advantages in terms of time, cost and applicability. Originality/value: The hexarotor flight efficiency is improved with the proposed SPSA and deep neural network approaches. In addition, the desired flight parameters can be obtained more quickly and reliably with the proposed approaches. The design performance criteria were also improved, enabling the hexarotor UAV to follow the given trajectory in the best way and providing convenience for end users. SPSA was preferred because it converged faster than other methods. While other methods perform 2n operations per iteration, SPSA only performs two operations. To obtain the moment of inertia, many physical parameter values of the UAV are required in the existing methods. In the proposed method, by creating a date set, only arm length and moment of inertia were estimated without the need to obtain physical parameters with the deep neural network structure. © 2023, Emerald Publishing Limited. Sun, 01 Jan 2023 00:00:00 GMT https://hdl.handle.net/20.500.12440/5858 2023-01-01T00:00:00Z https://hdl.handle.net/20.500.12440/5851 SPSA, PID Algoritması ve Morphing ile Hexarotor Yaw Uçuş Kontrolü Köse, Oğuz; Oktay, Tuğrul In recent years, the interest in unmanned aerial vehicles (UAV) has increased. They have penetrated into all areas of life. However, studies on UAV control have been a frequently discussed topic by researchers. In this study, a hexarotor in which yaw flight is tried to be controlled by changing the arm lengths during flight (morphing) is discussed. The hexarotor mathematical model is linearly derived using Newton's equations of motion. The equations of motion are modeled using the state space model approach. Hexarotor has been drawn in Solidworks program in accordance with the reality of all morphing states. Morphing estimation and accordingly proportional-integral-derivative (PID) coefficients were estimated using Simultaneous Perturbation Stochastic Approximation (SPSA). SPSA was preferred because it converged to the optimum result faster than similar algorithms. Hexarotor simulations were performed in Matlab/Simulink environment. Hexarotor yaw flight stability was achieved by minimizing the SPSA generated cost function based on design performance criteria. The cost function converged in 3-4 iterations and approached the optimum result. Accordingly, the design performance criteria have also improved and successfully followed the given trajectory. © 2022, Ismail Saritas. All rights reserved. Sat, 01 Jan 2022 00:00:00 GMT https://hdl.handle.net/20.500.12440/5851 2022-01-01T00:00:00Z https://hdl.handle.net/20.500.12440/5807 Impact of Covid-19 Pandemic on Cryptocurrency Prices Karaaslan, İbrahim This book consists of several theoretical and empirical papers. It is written by distinguished authors working in social and engineering sciences at different universities. Studies show the developments that may occur regarding the new normal life with the effect of Covid-19. The book aims to present a different perspective to researchers, readers and interested people regarding the Covid-19 process. © Peter Lang GmbH. Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/20.500.12440/5807 2021-01-01T00:00:00Z