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To conduct a numerical study on two‐dimensional, transient, buoyant flow inside an air‐filled 45°‐inclined enclosure, heated and cooled on adjacent walls.

The governing equations obtained through the stream function‐vorticity formulation are solved using finite differences. Flow characteristics have been investigated for an aspect ratio of 1. Calculations are carried out for the Rayleigh numbers in the range of 10³≤Ra≤5×10⁷.

With the increasing Rayleigh number, four distinct flow regimes were identified based on the time variations of the mid‐point stream function and the mean Nusselt number at the heated wall as well as those of flow and temperature fields: steady flow with symmetric two cells at low Ra; steady flow with asymmetric two cells at lower moderate Ra; oscillatory flow with the periodic nature at upper moderate Ra; and oscillatory flow in chaotic nature at higher Ra range.

The distinct flow regimes are observed only at ϕ=45°; a small deviation of the tilting angle from ϕ=45° results in the disappearance of the distinction.

The purpose of this paper is to investigate cotton fabric behavior that is exposed to radar waves between selected operation frequencies as an alternative radar-absorbing material (RAM) response. Cotton fabric biocomposite materials were compared with carbon fabric composite materials, which are good absorbers, in terms of mechanical and electromagnetic (EM) properties for that purpose.

The laminated composite plates were manufactured by using a vacuum infusion process. The EM tests were experimentally performed with a vector network analyzer to measure reflection, transmission and absorption ability of cotton fabric, carbon fabric and cotton–carbon fabric (side by side) composite plates between 3 and 18 GHz. The tensile and low-velocity impact tests were carried out to compare the mechanical properties of cotton fabric and carbon fabric composite plates. A scanning electron microscope was used for viewing the topographical features of fracture surfaces.

The cotton fabric composite plate exhibits low mechanical values, but it gives higher EM wave absorption values than the carbon fabric composite plate in certain frequency ranges. Comparing the EM absorption properties of the combination of cotton and carbon composites with those of the carbon composite alone, it appears that the cotton–carbon combination can be considered as a better absorber than the carbon composite in a frequency range from 12 to 18 GHz at Ku band.

This paper shows how cotton, which is a natural and easily supplied low-cost raw material, can be evaluated as a RAM.

The primary purpose is to empower financial institutions in AI integration decisions. By combining QSFS and the Golden Cut technique, the study establishes a robust foundation for assessing AI progress effects, aligning implementation with performance goals, and promoting technical innovation. Dimensions explored include AI-related workforce competency, technological adaption, and ethical AI practices, crucial components within the BSC framework for technological innovation.

This study employs a distinctive approach, integrating the Balanced Scorecard (BSC) framework with Quantum Spherical Fuzzy Sets (QSFS) and the Golden Cut approach to explore the dynamic landscape of AI deployment. The integration addresses uncertainties, enhancing impact assessment accuracy amid ambiguity associated with AI outcomes. QSFS and the Golden Cut technique together facilitate precise identification of thresholds and crucial values.

The research delves into the intricate relationship between enduring financial stability and AI progress, recognizing technology's crucial influence on financial decision-making. Findings underscore technology's significant impact on financial institutions' AI integration decisions. This novel approach provides a strong quantitative basis, offering insights into workforce competency, technological adaption, and ethical AI practices.

Despite valuable contributions, the study acknowledges limitations, such as potential biases and generalizability concerns, emphasizing the need for cautious interpretation and suggesting future research directions. Recognizing the research's boundaries and complexities in studying AI deployment in financial institutions underscores the need for ongoing exploration.

The research's originality lies in presenting an innovative methodology, integrating BSC, QSFS, and the Golden Cut, providing a unique perspective for decision-making. Contributions extend beyond academia, offering practical insights to enhance AI strategic implementation in the financial industry. This novel approach enriches the technology and finance discourse, fostering theoretical and practical advancements.

Our perception and analysis gradually grow and mature from subjectivity to objectivity as we investigate different periods of society and widen the temporal and spatial framework. The egocentric viewpoint is responsible for some of humanity's greatest mistakes and social crises throughout history. Without perceiving the ‘other’ and considering individuals who are different from them, societies will not be able to create permanent solutions. Although the answers offered are appropriate for one's own civilisation, when looking at the problem from a global perspective, it is extremely likely that there will be a significant incompatibility with other nations and societies. In this context, while our study advises a method of approaching social arrangements regardless of location, particularly time period, it also provides analysis. So much so that today's analysis differs from yesterday's, and tomorrow's will differ even more from today's. Today, more than 80% of the population lives in cities, and this trend is expected to continue. We find that the perceptions of the demands of generations x, y, z and alpha, living today in the same time period, for public goods and/or services, and the value they place on them, are considerably different in the demographic segment, which continues to develop and grow.

Our study intends to explain, on a worldwide scale, how the value ascribed to events, objects and phenomena differentiate these perceptions through social observations and bilateral interviews with these people living simultaneously in an urban environment. Despite the fact that our research will define a geographical area as an urban area in terms of scope, it will also present examples of these urban areas from other countries throughout the world, putting the problem in a global context. Our sample comprises the major cities of the countries with the most people on each continent, whereas our study universe spans the entire globe. It is about observing the values given to these generations' perceptions of urban services in these capitals, ensuring that generations better understand each other based on these findings and reforming the production and presentation of urban goods and/or services based on these findings. Developed and emerging countries are the focus of our judgements and observations.

The purpose of this paper is to present an improved particle filter-based attitude estimator for a quadrotor unmanned aerial vehicle (UAV) that addresses the degeneracy issues.

Control of a quadrotor is not sufficient enough without an estimator to eliminate the noise from low-cost sensors. In this work, particle filter-based attitude estimator is proposed and used for nonlinear quadrotor dynamics. But, since recursive Bayesian estimation steps may rise degeneracy issues, the proposed scheme is improved with four different and widely used resampling algorithms.

Robustness of the proposed schemes is tested under various scenarios that include different levels of uncertainty and different particle sizes. Statistical analyses are conducted to assess the error performance of the schemes. According to the statistical analysis, the proposed estimators are capable of reducing sensor noise up to 5x, increasing signal to noise ratio up to 2.5x and reducing the uncertainty bounds up to 36x with root mean square value of as low as 0.0024, mean absolute error value of 0.036, respectively.

To the best of the authors’ knowledge, the originality of this paper is to propose a robust particle filter-based attitude estimator to eliminate the low-cost sensor errors of quadrotor UAVs.

This paper aims to investigate the environmental impact of various pollutant emissions including carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxide (NO_x) and hydrocarbon (HC) from aircraft exhaust gases during the landing and take-off (LTO) cycles at Eskisehir Hasan Polatkan Airport, Turkey, between 2017 and 2018.

The methodology approach used to calculate the emissions from aircrafts is based on the ICAO databank and the actual data records taken from Presidency of The Republic of Turkey Directorate of Communications (DoC).

The maximum amount of total fuel burnt during the two years is 80.898 and 70.168 tons in 2017 and 2018, respectively, while the average fuel burnt per year from 2017 to 2018 is approximately 369.773 tons. The highest CO, CO₂, NO_x and HC emissions are found to be 248.3 kg in 2017, 261.380 tons, 1.708 tons and 22.15 kg, during the 2018 year, respectively. Average CO, HC, NO_x and CO₂ emissions amount per year are observed to be 1.392 tons, 135 kg, 6.909 tons and 1,143 tons, respectively. Considering the average of total emission amount as an environmental factor, as expected, CO₂ emissions contributed the most to the total emissions while HC emissions contributed the least to the total emissions from the airport.

The study presents the approach in determining the amounts of emissions released into the interannual atmosphere and it explicitly provides researchers and policymakers how to follow emissions from commercial aircraft activities at different airports.

The value of the study lies in the transparent computation of the amounts of pollutants by providing the data directly from the first hand-DoC.

Scientific research and delivering education at undergraduate and graduate levels are the main responsibilities of higher education institutions. Considering these points, we aimed to provide insights into an array of topics pertaining to scientific research and tertiary education in Turkey and the future of Turkish higher education. We focused on research-based education, lifelong learning, research and higher education institutions, research grants and funding in Turkey, performance management in higher education, international collaborations, future of hands-on approaches, and lastly the issue of brain drain in Turkey. In the endeavor to present these issues in detail, we employed sector analysis method. Throughout the chapter, we aimed to provide detailed and comparative evaluations making use of both national and international literature.

This study aims to develop a perception scale of gender role in disaster management and examine related factors.

A total of 1,167 individuals were reached in the main trial. Exploratory and confirmatory factor analyses were applied to test the validity of the final scale form, respectively.

The scale was developed as unidimensional with two positive items and 17 negative items. The mean scores of the participants were in the positive perception group. The 19-item model is a reliable and valid instrument for measuring the perception of gender role specific to disaster management.

Determining the perceptions of the people will guide the policies related to gender equity and equality and activities to be carried out in the disaster management field. This tool can be used to raise awareness related to gender perceptions in the disaster preparedness activities.

The “Perception Scale of Gender Role in Disaster Management” which is a reliable and robust tool to determine the perception of gender role specific to the disaster management was developed in this study. This tool can contribute to address the needs and capacities and provide influencive strategy development through gender analysis.

The purpose of this paper is to investigate the effect of doping element on the microwave absorption performance of hexagonal nano boron nitride (h-nBN)-reinforced basalt fabric (BF)/epoxy composites. A new type of hybrid composite that will be produced by the use of boron nitride as an additive that leads to increased radar absorption capability will be developed and a new material that can be used in aeronautical radar applications.

This study is focused on the microwave absorption properties of h-nBN doped basalt fabric-reinforced epoxy composites. Basalt fabric (BF)/epoxy composites (pure composites) and the BF/h-nBN (1 Wt.% h-nBN doped composites) hybrid composites were fabricated by vacuum infusion method. Phase identification of the composites were performed using X-ray diffraction (XRD), the 2θ scan range was from 10 to 60 with the scanning speed of 3°/min and surface morphologies of the composites were investigated using scanning electron microscopy (SEM). Microwave properties of samples were investigated through transmission/reflection measurements in Agilent brand 2-Port PNA-L Network Analyzer in the frequency range of 3–18 GHz. The prepared sample is positioned between two horn antennas with and without metal plate.

Experimental results show that h-nBN doped composite was synthesized successfully and the produced hexagonal nano boron nitride-added fiber laminated composite material has good absorption behavior when they are used with metallic sheets and good for isolation applications at many points in the 3–18 GHz band.

This paper will contribute to the literature on the use of basalt fabric, which are new types of fibers, and hexagonal nano boron nitride and the effects of boron nitride on radar absorption properties of composite material. It presents detail characterization of each composite by using XRD and scanning electron microscopy.