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Article Citation - WoS: 3Citation - Scopus: 4Robust Backstepping Control of a Quadrotor Unmanned Aerial Vehicle Under Colored Noises(Tech Science Press, 2025) Karahan, MehmetAdvances in software and hardware technologies have facilitated the production of quadrotor unmanned aerial vehicles (UAVs). Nowadays, people actively use quadrotor UAVs in essential missions such as search and rescue, counter-terrorism, firefighting, surveillance, and cargo transportation. While performing these tasks, quadrotors must operate in noisy environments. Therefore, a robust controller design that can control the altitude and attitude of the quadrotor in noisy environments is of great importance. Many researchers have focused only on white Gaussian noise in their studies, whereas researchers need to consider the effects of all colored noises during the operation of the quadrotor. This study aims to design a robust controller that is resistant to all colored noises. Firstly, a nonlinear quadrotor model was created with MATLAB. Then, a backstepping controller resistant to colored noises was designed. The designed backstepping controller was tested under Gaussian white, pink, brown, blue, and purple noises. PID and Lyapunov-based controller designs were also carried out, and their time responses (rise time, overshoot, settling time) were compared with those of the backstepping controller. In the simulations, time was in seconds, altitude was in meters, and roll, pitch, and yaw references were in radians. Rise and settling time values were in seconds, and overshoot value was in percent. When the obtained values are examined, simulations prove that the proposed backstepping controller has the least overshoot and the shortest settling time under all noise types.Article Citation - WoS: 1Citation - Scopus: 1Fair-News: Digital Journalism Model To Prevent Information Pollution and Manipulation(Tech Science Press, 2023) Takan, Savas; Ergun, Duygu; Katipoglu, GokmenAs digital data circulation increases, information pollution and manipulation in journalism have become more prevalent. In this study, a new digital journalism model is designed to contribute to the solution of the main current problems, such as information pollution, manipulation, and account-ability in digital journalism. The model uses blockchain technology due to its transparency, immutability, and traceability. However, it is tough to provide the mechanisms necessary for journalism, such as updating one piece of information, instantly updating all other information affected by the updated information, establishing logical relationships between news, making quick comparisons, sorting and indexing news, and keeping the changing informa-tion about the news in the system, with the blockchain data structure. For this reason, in our study, we have developed a new data structure that provides both the immutability, transparency and traceability properties of the blockchain and can support the communication mechanisms necessary for journalism. The functionality of our proposed data structure is demonstrated in terms of communication mechanisms such as mutability, context, consistency, and reliability through example scenarios. Additionally, our data structure is compared with the data structure of blockchain technology in terms of time, space, and maintenance costs. Accordingly, while the model size increases linearly in blockchain, the model's size remains approximately constant since the structure we developed is data-independent. In this way, maintenance costs are reduced. Since our model also has an indexing mechanism, it reduces the linear time search complexity to logarithmic time. As a result, the data structure we developed is found to have higher performance than blockchain in the journalism concept. In future studies, it is planned to test all aspects of the model with a pilot application, eliminate its shortcomings, and develop a holistic approach to the root causes of the problems in the journalism focus.Article Citation - WoS: 7Citation - Scopus: 12Genetic Algorithm and Tabu Search Memory With Course Sandwiching (gats_cs) for University Examination Timetabling(Tech Science Press, 2020) Abayomi-Alli, A.; Misra, S.; Fernandez-Sanz, L.; Abayomi-Alli, O.; Edun, A. R.University timetable scheduling is a complicated constraint problem because educational institutions use timetables to maximize and optimize scarce resources, such as tine and space. In this paper, an examination timetable system using Genetic Algorithm and Tabu Search memory with course sandwiching (GAT_CS), was developed fora lame public University. The concept of Genetic Algorithm with Selection and Evaluation was implemented while the memory properties of Tabu Search and course sandwiching replaced Crossover and Mutation. The result showed that GAT_CS had hall allocation accuracies of 96.07% and 99.02%, unallocated score of 3.93% and 0.98% for first and second semesters, respectively. It also automatically sandwiched (scheduled) multiple examinations into single halls with a simulation time in the range of 20-29.5 seconds. The GAT_CS outperformed previous related works on the same timetable dataset. It could, however, be improved to reduce clashes, duplications, multiple examinations and to accommodate more system-defined constraints.
