Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article A Multi-Scenario Evaluation of Adaptive Fuzzy Logic Algorithms for Intelligent Traffic Signal Management in Urban Intersections(Nature Portfolio, 2026) Dvorsky, Jiri; Martinovic, Jan; Shaheen, Sumaira; Riaz, Muhammad Bilal; Qadri, Syed Shah Sultan Mohiuddin; Slaninova, KaterinaThe article presents a performance analysis of the advanced adaptive control systems of traffic lights that are based on the advanced fuzzy logic. They include Modified Intuitionistic Fuzzy Logic Algorithm (MIFLA) and the Modified Interval Type-2 fuzzy logic (MIT2FL) at a four-leg intersection. In this article, there is an integration of these fuzzy models with the SUMO platform with respect to the weaknesses of the traditional fixed-time traffic lights, particularly in rapidly urbanizing areas. This will be to achieve a real-time dynamic control system. The simulation matrix was a grid of the nine scenarios in which the performance of the controllers was assessed to some extent, depending on the traffic and directional imbalances. The results reveal that the MIT2FL is more effective than the MIFLA and the Modified Webster benchmark. MIT2FL is less divergent, has shorter queuing times, and is more flexible. This occurs when the demand is high, and the traffic conditions are not proportional. This work is significant because it provides fuzzy logic controllers that can deal with uncertainty. It also creates a benchmarking model of a typical multi-scenario. Moreover, it gives the opportunity for reproducibility of the findings in real traffic implementation. The innovations will assist in making the city smarter and easier to move around. They manage congestion, delays, and improve the sustainability of smart traffic control.Article Citation - WoS: 11Citation - Scopus: 17Convolutional Neural Network-Based Deep Learning for Landslide Susceptibility Mapping in the Bakhtegan Watershed(Nature Portfolio, 2025) Feng, Li; Zhang, Maosheng; Mao, Yimin; Liu, Hao; Yang, Chuanbo; Dong, Ying; Nanehkaran, Yaser A.Landslides pose a significant threat to infrastructure, ecosystems, and human safety, necessitating accurate and efficient susceptibility assessment methods. Traditional models often struggle to capture the complex spatial dependencies and interactions between geological and environmental factors. To address this gap, this study employs a deep learning approach, utilizing a convolutional neural network (CNN) for high-precision landslide susceptibility mapping in the Bakhtegan watershed, southwestern Iran. A comprehensive landslide inventory was compiled using 235 documented landslide locations, validated through remote sensing and field surveys. An equal number of non-landslide locations were systematically selected to ensure balanced model training. Fifteen key conditioning factors-including topographical, geological, hydrological, and climatological variables-were incorporated into the model. While traditional statistical methods often fail to extract spatial hierarchies, the CNN model effectively processes multi-dimensional geospatial data, learning intricate patterns influencing slope instability. The CNN model outperformed other classification approaches, achieving an accuracy of 95.76% and a precision of 95.11%. Additionally, error metrics confirmed its reliability, with a mean absolute error (MAE) of 0.11864, mean squared error (MSE) of 0.18796, and root mean squared error (RMSE) of 0.18632. The results indicate that the northern and northeastern regions of the Bakhtegan watershed are highly susceptible to landslides, highlighting areas where proactive mitigation strategies are crucial. This study demonstrates that deep learning, particularly CNNs, offers a powerful and scalable solution for landslide susceptibility assessment. The findings provide valuable insights for urban planners, engineers, and policymakers to implement effective risk reduction strategies and enhance resilience in landslide-prone regions.Article Citation - WoS: 41Citation - Scopus: 44Psychological Well-Being in Europe After the Outbreak of War in Ukraine(Nature Portfolio, 2024) Scharbert, Julian; Humberg, Sarah; Kroencke, Lara; Reiter, Thomas; Sakel, Sophia; ter Horst, Julian; Back, Mitja D.The Russian invasion of Ukraine on February 24, 2022, has had devastating effects on the Ukrainian population and the global economy, environment, and political order. However, little is known about the psychological states surrounding the outbreak of war, particularly the mental well-being of individuals outside Ukraine. Here, we present a longitudinal experience-sampling study of a convenience sample from 17 European countries (total participants = 1,341, total assessments = 44,894, countries with >100 participants = 5) that allows us to track well-being levels across countries during the weeks surrounding the outbreak of war. Our data show a significant decline in well-being on the day of the Russian invasion. Recovery over the following weeks was associated with an individual's personality but was not statistically significantly associated with their age, gender, subjective social status, and political orientation. In general, well-being was lower on days when the war was more salient on social media. Our results demonstrate the need to consider the psychological implications of the Russo-Ukrainian war next to its humanitarian, economic, and ecological consequences.Correction Magnetic Dipole Effects on Unsteady Flow of Casson-Williamson Nanofluid Propelled by Stretching Slippery Curved Melting Sheet With Buoyancy Force (Vol 13, 12770, 2023)(Nature Portfolio, 2023) Kumar, Pradeep; Nagaraja, Basavarajappa; Almeida, Felicita; AjayKumar, Abbani Ramakrishnappa; Al-Mdallal, Qasem; Jarad, Fahd; Al‑Mdallal, QasemArticle Citation - WoS: 5Citation - Scopus: 5Significance of Nanoparticles Aggregation on the Dynamics of Rotating Nanofluid Subject To Gyrotactic Microorganisms, and Lorentz Force(Nature Portfolio, 2022) Siddique, Imran; Ali, Rifaqat; Awrejcewicze, Jan; Jarad, Fahd; Khalifa, Hamiden Abd El-Wahed; Ali, BaghThe significance of nanoparticle aggregation, Lorentz and Coriolis forces on the dynamics of spinning silver nanofluid flow past a continuously stretched surface is prime significance in modern technology, material sciences, electronics, and heat exchangers. To improve nanoparticles stability, the gyrotactic microorganisms is consider to maintain the stability and avoid possible sedimentation. The goal of this report is to propose a model of nanoparticles aggregation characteristics, which is responsible to effectively state the nanofluid viscosity and thermal conductivity. The implementation of the similarity transforQ1m to a mathematical model relying on normal conservation principles yields a related set of partial differential equations. A well-known computational scheme the FEM is employed to resolve the partial equations implemented in MATLAB. It is seen that when the effect of nanoparticles aggregation is considered, the temperature distribution is enhanced because of aggregation, but the magnitude of velocities is lower. Thus, showing the significance impact of aggregates as well as demonstrating themselves as helpful theoretical tool in future bioengineering and industrial applications.Article Citation - WoS: 27Citation - Scopus: 31The Improved Thermal Efficiency of Prandtl-Eyring Hybrid Nanofluid Via Classical Keller Box Technique(Nature Portfolio, 2021) Baleanu, Dumitru; Nasir, Nor Ain Azeany Moh; Shahzad, Faisal; Nisar, Kottakkaran Sooppy; Shoaib, Muhammad; Ismail, Khadiga Ahmed; Jamshed, WasimPrandtl-Eyring hybrid nanofluid (P-EHNF) heat transfer and entropy generation were studied in this article. A slippery heated surface is used to test the flow and thermal transport properties of P-EHNF nanofluid. This investigation will also examine the effects of nano solid tubes morphologies, porosity materials, Cattaneo-Christov heat flow, and radiative flux. Predominant flow equations are written as partial differential equations (PDE). To find the solution, the PDEs were transformed into ordinary differential equations (ODEs), then the Keller box numerical approach was used to solve the ODEs. Single-walled carbon nanotubes (SWCNT) and multi-walled carbon nanotubes (MWCNT) using Engine Oil (EO) as a base fluid are studied in this work. The flow, temperature, drag force, Nusselt amount, and entropy measurement visually show significant findings for various variables. Notably, the comparison of P-EHNF's (MWCNT-SWCNT/EO) heat transfer rate with conventional nanofluid (SWCNT-EO) results in ever more significant upsurges. Spherical-shaped nano solid particles have the highest heat transport, whereas lamina-shaped nano solid particles exhibit the lowest heat transport. The model's entropy increases as the size of the nanoparticles get larger. A similar effect is seen when the radiative flow and the Prandtl-Eyring variable-II are improved.Article Citation - WoS: 20Citation - Scopus: 21Entropy Generation and Induced Magnetic Field in Pseudoplastic Nanofluid Flow Near a Stagnant Point(Nature Portfolio, 2021) Nadeem, Sohail; Matoog, R. T.; Hussain, Azad; Rehman, Aysha; Baleanu, Dumitru; Sherif, El-Sayed M.; Hou, EnranIn this present article the entropy generation, induced magnetic field, and mixed convection stagnant point flow of pseudoplastic nano liquid over an elastic surface is investigated. The Buongiorno model is employed in modeling. Through the use of the boundary layer idea, flow equations are transformed from compact to component form. The system of equations is solved numerically. The Induced magnetic spectrum falls near the boundary and grows further away as the reciprocal of the magnetic Prandtl number improves. The fluctuation of induced magnetic rises while expanding the values of mixed convection, thermophoresis, and magnetic parameters, whereas it declines for increment in the Brownian and stretching parameters. The velocity amplitude ascends and temperature descends for the rise in magnetic parameter. The mass transfer patterns degrade for the higher amount of buoyancy ratio while it boosts by the magnification of mixed convection and stretching parameters. Streamlines behavior is also taken into account against the different amounts of mixed convection and magnetic parameters. The pseudoplastic nanofluids are applicable in all electronic devices for increasing the heating or cooling rate in them. Further, pseudoplastic nanofluids are also applicable in reducing skin friction coefficient.Article Citation - WoS: 28Citation - Scopus: 33Boger Nanofluid: Significance of Coriolis and Lorentz Forces on Dynamics of Rotating Fluid Subject To Suction/Injection Via Finite Element Simulation(Nature Portfolio, 2022) Siddique, Imran; Hussain, Sajjad; Ali, Liaqat; Baleanu, Dumitru; Ali, BaghThis study briefings the roles of Coriolis, and Lorentz forces on the dynamics of rotating nanofluids flow toward a continuously stretching sheet. The nanoparticles are incorporated because of their unusual qualities like upgrade the thermal transportation, which are very important in heat exchangers, modern nanotechnology, electronics, and material sciences. The primary goal of this study is to improve heat transportation. Appropriate similarity transformations are applied for the principal PDEs to transform into nonlinear dimensionless PDEs. A widely recognized Numerical scheme known as the Finite Element Method is employed to solve the resultant convective boundary layer balances. Higher input in the solvent fraction parameter has a rising effect on the primary velocity and secondary velocity magnitude, and decreasing impact on the distributions of temperature. It is seen that growing contributions of the Coriolis, and Lorentz forces cause to moderate the primary and secondary velocities, but the temperature and concentration functions show opposite trend. The concentration, temperature, and velocities distributions for suction case is prominently than that of injection case, but inverse trend is observed for local Nusselt and Sherwood numbers. These examinations are relevant to the field of plastic films, crystal growing, paper production, heat exchanger, and bio-medicine.Article Citation - WoS: 4Citation - Scopus: 3Quantum Correlation of Microwave Two-Mode Squeezed State Generated by Nonlinearity of Inp Hemt(Nature Portfolio, 2023) Salmanogli, A.This study significantly concentrates on cryogenic InP HEMT high-frequency circuit analysis using quantum theory to find how the transistor nonlinearity can affect the quantum correlation of the modes generated. Firstly, the total Hamiltonian of the circuit is derived, and the dynamic equation of the motion contributed is examined using the Heisenberg-Langevin equation. Using the nonlinear Hamiltonian, some components are attached to the intrinsic internal circuit of InP HEMT to address the circuit characteristics fully. The components attached are arisen due to the nonlinearity effects. As a result, the theoretical calculations show that the states generated in the circuit are mixed, and no pure state is produced. Accordingly, the modified circuit generates the two-mode squeezed thermal state, which means one can focus on calculating the Gaussian quantum discord to evaluate quantum correlation. It is also found that the nonlinearity factors (addressed as the nonlinear components in the circuit) can intensely influence the squeezed thermal state by which the quantum discord is changed. Finally, as the primary point, it is concluded that although it is possible to enhance the quantum correlation between modes by engineering the nonlinear components; however, attaining quantum discord greater than unity, entangled microwave photons, seems a challenging task since InP HEMT operates at 4.2 K.Article Citation - WoS: 27Citation - Scopus: 34Magnetic Dipole Effects on Unsteady Flow of Casson-Williamson Nanofluid Propelled by Stretching Slippery Curved Melting Sheet With Buoyancy Force(Nature Portfolio, 2023) Nagaraja, Basavarajappa; Almeida, Felicita; AjayKumar, Abbani Ramakrishnappa; Al-Mdallal, Qasem; Jarad, Fahd; Kumar, PradeepIn particular, the Cattaneo-Christov heat flux model and buoyancy effect have been taken into account in the numerical simulation of time-based unsteady flow of Casson-Williamson nanofluid carried over a magnetic dipole enabled curved stretching sheet with thermal radiation, Joule heating, an exponential heat source, homo-heterogenic reactions, slip, and melting heat peripheral conditions. The specified flow's partial differential equations are converted to straightforward ordinary differential equations using similarity transformations. The Runge-Kutta-Fehlberg 4-5th order tool has been used to generate solution graphs for the problem under consideration. Other parameters are simultaneously set to their default settings while displaying the solution graphs for all flow defining profiles with the specific parameters. Each produced graph has been the subject of an extensive debate. Here, the analysis shows that the thermal buoyancy component boosts the velocity regime. The investigation also revealed that the melting parameter and radiation parameter had counterintuitive effects on the thermal profile. The velocity distribution of nanofluid flow is also slowed down by the ferrohydrodynamic interaction parameter. The surface drag has decreased as the unsteadiness parameter has increased, while the rate of heat transfer has increased. To further demonstrate the flow and heat distribution, graphical representations of streamlines and isotherms have been offered.