University of Turkish Aeronautical Association

The services provided by ground handling companies at airports play an important role in ensuring that flight operations are carried out safely and securely on the airside of the airport and supporting airport authorities and airlines with services for passengers on the land side.These services have very effective role in reducing turnaround times of aircraft by ensuring uninterrupted and smooth operations, optimizing aircraft utilization, improving passenger experiences with effective and uninterrupted check-in, boarding and baggage procedures, and also play an active role in the attractiveness by the customers and determining sustainable strategies of the airlines for the future. At the same time, as the effective, efficient, and uninterrupted provision of ground handling services has an impact on the optimum capacity utilization of airport infrastructure elements, the performance of ground handling companies also makes significant contributions to airport infrastructure management. This study aims to develop a model to evaluate the performance of ground handling companies. For the model, MCDM approach was applied in performance evaluation. The model employs a hybrid model composed of Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy TOPSIS Methods in the weighting of the criteria, and ranking of the companies successively. Model application was made at Antalya Airport.

The round sardinella (Sardinella aurita Valenciennes, 1847) is a widely distributed migratory pelagic fish inhabiting the Mediterranean Sea and the eastern Atlantic coasts. The species is heavily exploited and represents a valuable resource for global fisheries. In the Mediterranean area, uptakes of round sardinella are particularly high in the Ionian and Levant regions, where landings have shown fluctuating yet significant peaks in recent decades. Given its migratory nature, understanding the connectivity among populations is crucial for delineating appropriate fishery management units. Previous studies employing morphometric, meristic, and molecular analyses have yielded mixed results regarding population structuring. Here, the genetic differentiation among Eastern Mediterranean S. aurita populations was investigated using a multi-marker approach: the mitochondrial cytochrome c oxidase subunit I (COI), cytochrome b (CytB), control region (CR), and 16S ribosomal RNA (16S rRNA), and seven species-specific nuclear simple sequence repeats (SSRs). Overall, the results indicate high genetic diversity coupled with weak population structuring across the Eastern Mediterranean. These analyses aim at clarifying stock boundaries towards supporting sustainable management strategies at a regional scale for this ecologically and economically important species.

Bu çalışma, havacılık sektörünün operasyonel yoğunluğu en yüksek alanlarından biri olan yer hizmetlerinde görev yapan kadın çalışanların karşılaştıkları zorlukları ve mesleki deneyimlerini toplumsal cinsiyet perspektifinden nitel bir yaklaşımla incelemektedir. Yer hizmetleri faaliyetleri, esnek çalışma düzenleri, zaman baskısı ve fiziksel dayanıklılık gerektiren yüksek stresli operasyonel koşulları barındırır. Bu özellikler, sektörün uzun süre erkek egemen bir alan olarak algılanmasına yol açsa da son yıllarda kadınların bu alandaki görünürlüğü giderek artmaktadır. Ancak cinsiyet temelli mesleki algılar ve yapısal engeller, kadın çalışanların işe alım ve kariyer ilerleme süreçlerinde zorluklarla karşılaşmasına neden olmaktadır. Çalışmada, keşfedici nitel yaklaşım benimsenmiş ve Ankara Esenboğa Havalimanı’nda farklı pozisyonlarda görev yapan sekiz kadın çalışan ile yarı yapılandırılmış derinlemesine görüşmeler gerçekleştirilmiştir. Elde edilen veriler, Braun ve Clarke (2006) tarafından geliştirilen tematik analiz yöntemi kullanılarak incelenmiştir. Analiz sonucunda, fiziksel zorluklar ve iş koşulları, iş dışı sürekli erişebilirlik, kadınlara yönelik sosyal ve yasal haklar, kariyer gelişimi ve kadınların temsili, kurumsal politikalar ve sosyal destek uygulamaları, psikolojik ve duygusal etkiler, toplumsal cinsiyet temelli eşitsizlikler ve baş etme stratejileri olmak üzere sekiz ana tema ortaya çıkmıştır. Bulgular, kadın çalışanların fiziksel ve duygusal açıdan çeşitli zorluklarla karşılaştıklarını ortaya koymaktadır. Ayrıca, iş-yaşam dengesi, kariyer ilerlemesi ve otorite ilişkilerinde toplumsal cinsiyet kaynaklı engellerin varlığı dikkat çekmektedir. Çalışma, sektörde toplumsal cinsiyet eşitliğini teşvik edici politikaların geliştirilmesi, kurumsal destek mekanizmalarının güçlendirilmesi ve eşit kariyer fırsatlarının sağlanmasının stratejik bir gereklilik olduğunu ortaya koymaktadır.

This study explored the key standards and sub-standards for constructing learner-centered education in higher education in Türkiye. Using a qualitative multimethod design, data were collected through individual interviews, focus group discussions, and document analysis. Participants included 12 administrators (7 male, 5 female) and 12 faculty members (4 male, 8 female) from accredited science and social science programs at six public and six private universities in Ankara. Focus group interviews involved 101 third- and fourth-year students across 12 groups from the same institutions. Document analysis encompassed 57 national and international sources, including articles, books, project reports, quality assurance standards, and policy documents, dated between 1979 and 2023. Interviews were conducted from September 2021 to February 2022, while document analysis occurred from February 2021 to June 2023. Inductive data analysis involved coding, identifying patterns, and developing categories and themes. The findings highlight the need for comprehensive academic, social-emotional, motivational, financial, and procedural support systems to foster active learning, collaboration, and autonomy in higher education. The key results include integrating experiential and problem-based learning, enhancing the professional development program for faculty members, and creating adaptive institutional structures balancing theory and practice. Lastly, emphasis on participatory governance and ethical practices underscores the significance of aligning educational strategies with student needs, sectoral expectations, and global orientations.

The main advantage of the proposed knuckle joint press mechanism over traditional crank presses is the extended dwell time, which enables better control over the stamping process. This allows for precise deformation, improving product quality. Additionally, the optimized force transmission in the proposed design reduces mechanical losses, leading to improved energy efficiency. These improvements make the press more suitable for high-demand applications where precision and durability are essential, thus providing a significant advantage over existing crank presses. This study focuses on the synthesis of a knuckle joint press utilizing mechanisms with unevenly distributed rods, which belong to the category of variable contour mechanisms. The objective is to develop a systematic method for synthesizing such a mechanism, specifically targeting the task of maintaining the stability of the working link with predetermined parameters. The synthesis approach involves reducing the mechanism’s class and implementing a step-by-step kinematic synthesis method. The reduction in class is based on the original double-rod mechanism of the fourth class, while the kinematic synthesis of the third-class mechanism is performed in two stages: optimal synthesis of the closed kinematic chain and interpolative synthesis of the kinematic linkage. By following this methodology, a third-class mechanism with a prolonged dwell time is successfully synthesized, and a two-rod crank press with similar kinematic characteristics is designed based on its scheme. Additionally, algorithms and programs for kinematic analysis of the synthesized mechanisms are developed, demonstrating the reliability of the results in achieving the desired kinematic characteristics for the crank press. The obtained results have practical significance and can be applied in the development of high-precision presses for metal forming, ensuring improved product quality and energy efficiency in industrial applications.

Artificial intelligence (AI), machine learning (ML) and decision-support (DS) are gaining increasing interest with widening adoption. This article investigates the enabler role of AI and ML for providing decision-support in procurement&purchasing domain. The study follows a systematic review approach via taxonomic analysis. Comprehensive analysis and discussions are provided for: (a) the relevance and applicability of AI and ML in procurement&purchasing decision-support; (b) functionalities/processes for which they are utilized; (c) related methodologies; and (d) implementation benefits as well as challenges. Findings reveal that procurement&purchasing area holds significant potential in terms of AI-ML applications for decision-support almost every related sub-process. This study is original by offering a process-oriented approach to the research domain; providing unique clustering and classification; and presenting detailed analyses via unique taxonomy tables with respect to approach, topic, focus, context and methodologies of the literature items reviewed. The study offers further research opportunities and has significant potential to provide managerial insights by the identified sectoral applications, benefits and challenges.

Abstract This study investigates the phenomenon of fog clearing in the lee of Sable Island, Nova Scotia, termed a “fog shadow”, using observations from the 2022 Fog And Turbulence Interactions in the Marine Atmosphere field experiment and Coupled Ocean–Atmosphere Mesoscale Prediction System numerical weather prediction model. The fog shadow occurs when a shallow layer of marine fog dissipates downstream of this low‐elevation island due to surface heating and turbulent mixing. Analysis focuses on two cases: July 24, 2022, when a fog shadow was both predicted and observed through multiple platforms, including satellite imagery, and July 26, 2022, when the model erroneously forecast a fog shadow. Though the model successfully predicted some fog shadow events, it consistently overestimated surface heat fluxes over the island, leading to excessive fog dissipation in forecasts. The study reveals that fog shadows can form when sufficient surface heating combines with turbulent mixing to erode shallow fog layers, though the precise mechanisms and conditions required remain to be fully understood. These findings highlight the challenges in accurately modeling air–sea interactions and fog evolution around small islands, suggesting several areas for model improvement, including enhanced resolution, better surface flux parameterizations, and more sophisticated turbulence schemes.

This study explores the potential of artificial intelligence-based methods for route planning in unmanned aerial vehicle (UAV) swarm systems, with a particular focus on the advantages of the Q-learning algorithm in dynamic and uncertain environments, where traditional methods often fall short. A review of the literature reveals that swarm UAV mission planning typically relies on fixed-rule or predefined models, which impose significant limitations in real-time decision-making and adaptability to changing conditions. Q-learning’s ability to balance exploration and exploitation provides a flexible, adaptive structure for route optimization. Future work will focus on implementing this approach and examining its practical applications and operational impact in more detail.