WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/4465
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Article Citation Count: 0Two Balloons Can Fly a Minaret: Parody and Fabricated Reality as Integral Qualities of Mock-Documentary in aya Seyahat(Routledge Journals, Taylor & Francis Ltd, 2025) Tuzun, Defne; Akcali, Elif; Cengiz, Esin Paca; Behlil, MelisThis paper takes a close look at the critically acclaimed artist and filmmaker Kutlu & gbreve; Ataman's mockumentary Aya Seyahat (Journey to the Moon, 2009). We discuss the potentials and possibilities that the mockumentary mode brings to the film in detail, and address this mode as an aesthetic and critical manner that Ataman employs in his artistic practice. Through this discussion, we evaluate the ways in which the film is informed by and can be interpreted as a parodic observation of recurrent patterns in Turkish politics and representations of the national pasts. We argue that it exemplifies and endorses mockumentary's politically reflexive capacity to rethink history and the process of historiography in which historical truths are constructed. Mockumentary mode offers layers of meanings, exceeding the obvious narrative of historical parody, and invites the viewers to notice and problematize conventional narrational and stylistic methods of documenting a historical event. Thus, the film provides a criticism and comparison of the public opinion towards politics within two distinct periods in Turkey's history, namely the 1950s and the 2000s. It also opens up a space for a critical engagement with Turkey's troubled pasts and their construction as historical narratives in both cinematic and other representations.Article Citation Count: 0Secure Quantum-Based Adder Design for Protecting Machine Learning Systems Against Side-Channel Attacks(Elsevier, 2025) Ul Ain, Noor; Ahmadpour, Seyed-Sajad; Navimipour, Nima Jafari; Diakina, E.; Kassa, Sankit R.Machine learning (ML) has recently been adopted in various application domains. Usually, a well-performing ML model relies on a large volume of training data and powerful computational resources. Recently, hardware accelerators utilizing field programmable gate arrays (FPGAs) have been developed to provide high-performance hardware while maintaining the required accuracy for ML tools. However, one of the main challenges hindering the FPGA-based ML models is their susceptibility to adversarial attacks, such as physical side-channel attacks. In this study, various kinds of countermeasures, including masking and hiding techniques, are examined to mitigate the aforementioned shortcomings and enhance the security of FPGA-based ML systems. In addition to FPGA-based defenses, the advantages of quantum computing for designing circuits to enhance data protection are also elaborated. However, concerning FPGA-based ML models, which are used to defend against physical side-channel attacks, quantum dot cellular automata (QCA) offers a more promising option. Its inherent security, lower power consumption, higher speed, and reduced vulnerability to side-channel leakage make it the best alternative. Therefore, this study emphasizes the implementation of the quantum nature of QCA to protect valuable information against physical side-channel attacks. It also offers quantum masking circuits for protecting sensitive information in machine learning systems, including XOR, adder, and RCA. Furthermore, the presented work advocates for leveraging QCA technology to augment the security of machine learning systems by mitigating the disclosure of sensitive data. The proposed QCA-based masked designs, which include an adder and a ripple carry adder (RCA), pose some qualities, which include a single-layer structure, minimal cell count, and low latency. When compared with the best counterparts among the recommended designs, these designs exhibit significant improvements regarding cell consumption and occupied area, with improvements of 33.3% and 36.6% respectively.Article Citation Count: 0A Motion Planner for Growing Reconfigurable Inflated Beam Manipulators in Static Environments(Ieee-inst Electrical Electronics Engineers inc, 2025) Altagiuri, Rawad E. H.; Zaghloul, Omar H. A.; Do, Brian H.; Stroppa, FabioSoft growing robots have the potential to be useful for complex manipulation tasks and navigation for inspection or search and rescue. They are designed with plant-like properties, allowing them to evert and steer multiple links and explore cluttered environments. However, this variety of operations results in multiple paths, which is one of the biggest challenges faced by classic pathfinders. In this letter, we propose a motion planner based on A$<^>*$ search specifically designed for soft growing manipulators operating on predetermined static tasks. Furthermore, we implemented a stochastic data structure to reduce the algorithm's complexity as it explores alternative paths. This allows the planner to retrieve optimal solutions over different tasks. We ran demonstrations on a set of three tasks, observing that this stochastic process does not compromise path optimality.Article Citation Count: 0Resource Allocation for Discrete Rate Multi-Cell Energy Constrained Communication Networks(Springer, 2024) Iqbal, Muhammad Shahid; Salik, Elif Dilek; Sadi, Yalcin; Coleri, SinemRadio frequency energy harvesting is a promising technique to extend the lifetime of wireless powered communication networks (WPCNs) due to its controllability. In this paper, we consider a novel discrete rate based multi-cell WPCN, where multiple hybrid access points (HAPs) transmit energy to the users and users harvest this energy for the information transmission by using a transmission rate selected from a finite set of discrete rate levels. We formulate an optimization problem to minimize the schedule length through optimal rate allocation and scheduling of the users while considering the traffic demand, energy causality and interference constraints. The problem is mixed integer non-linear programming problem. Initially, we investigate the problem for non-simultaneous and simultaneous transmission considering both predetermined and variable transmission rates. We propose optimal and heuristic algorithms for all these categories by using optimality analysis, Perron-Frobenius conditions and iterative improvement of the total schedule length. Then, for the general problem, we propose heuristic algorithm based on the maximization of the number of concurrently transmitting users within each time slot by considering the maximum allowed interference level of the users. Via extensive simulations, we demonstrate significant improvement in schedule length through rate selection and proper scheduling of concurrently transmitting users.Article Citation Count: 0Explaining Mortgage Defaults Using Shap and Lasso(Springer, 2024) Ozturkkal, Belma; Wahlstrom, Ranik RaaenWe utilize machine learning methods to model the credit risk of mortgages in a significant emerging market. For this purpose, we investigate a multitude of variables that explain the characteristics of the loans, the demographics of the borrowers, and macroeconomic factors. We employ SHapley Additive exPlanations (SHAP) values in conjunction with five different tree-based machine learning methods, as well as the least absolute shrinkage and selection operator (LASSO) in conjunction with logistic regressions. Our findings, which are robust across two sampling schemes, reveal that while demographic variables are significant and important, loan-specific and macroeconomic variables are the most crucial in explaining mortgage defaults. As existing literature on mortgage default has primarily focused on advanced markets, we aim to bridge this gap by concentrating on emerging market data. We also share our code, which we hope will encourage others to utilize the methods we have applied.Article Citation Count: 0Resource Allocation for Multi-Cell Full-Duplex Wireless Powered Communication Networks(Springer, 2024) Iqbal, Muhammad Shahid; Sadi, Yalcin; Kazmi, Syed Adil Abbas; Coleri, SinemWireless powered communication networks (WPCNs) are crucial in achieving perpetual lifetime for the machine-type communication (MTC) and Internet of things (IoT) in fifth-generation (5G) communication and beyond networks. Practical WPCNs cover a broad region and have a significant number of sensors, requiring multi-cell deployment. We investigate the minimum length scheduling problem for a multi-cell full-duplex WPCNs to find the optimal power and schedule by considering the simultaneous transmission, maximum transmit power and energy causality constraints for the users. The optimization problem to minimize the schedule length is combinatorial, thus, difficult to find the global optimum solution. To overcome this, we divide the problem into two subproblems, i.e., power control problem (PCP) and the scheduling problem. Then, we present the optimal polynomial time algorithm for the PCP based on the use of the bisection method and evaluation of the Perron-Frobenius criteria. Then, by using the PCP solution, we calculate the optimal transmission time for the users that are scheduled by the scheduling algorithm. For the scheduling problem, we define a penalty function that represents the gain of simultaneous transmission over the individual transmission of the users and we show that the minimization of schedule length is similar to the minimization of sum of penalties. Following the optimum analysis of the proposed penalty metric, we present a heuristic algorithm that tries to minimize the sum penalties of the simultaneously transmitting users over the schedule. Through extensive simulations, we show significant gains of scheduling for concurrent transmissions over individual transmissions.Article Citation Count: 0Applications of Deep Learning in Alzheimer's Disease: a Systematic Literature Review of Current Trends, Methodologies, Challenges, Innovations, and Future Directions(Springer, 2024) Toumaj, Shiva; Heidari, Arash; Shahhosseini, Reza; Navimipour, Nima JafariAlzheimer's Disease (AD) constitutes a significant global health issue. In the next 40 years, it is expected to affect 106 million people. Although more and more people are getting AD, there are still no effective drugs to treat it. Insightful information about how important it is to find and treat AD quickly. Recently, Deep Learning (DL) techniques have been used more and more to diagnose AD. They claim better accuracy in drug reuse, medication recognition, and labeling. This essay meticulously examines the works that have talked about using DL with Alzheimer's disease. Some of the methods are Natural Language Processing (NLP), drug reuse, classification, and identification. Concerning these methods, we examine their pros and cons, paying special attention to how easily they can be explained, how safe they are, and how they can be used in medical situations. One important finding is that Convolutional Neural Networks (CNNs) are most often used for AD research and Python is most often used for DL issues. Some security problems, like data protection and model stability, are not looked at enough in the present research, according to us. This study thoroughly examines present methods and also points out areas that need more work, like better data integration and AI systems that can be explained. The findings should help guide more research and speed up the creation of DL-based AD identification tools in the future.Article Citation Count: 0Cultural Context Shapes the Selection and Adaptiveness of Interpersonal Emotion Regulation Strategies(Amer Psychological Assoc, 2024) Pruessner, Luise; Altan-Atalay, AyseIn everyday life, we commonly experience, express, and regulate our emotions in interpersonal contexts. However, much of the existing research on utilizing others for modulating one's emotions has focused on Western, individualistic cultures, leaving a significant gap in understanding how the selection and adaptiveness of interpersonal emotion regulation (IER) strategies vary across cultural contexts. This cross-national comparison study aims to bridge this gap by examining intrinsic IER in 1,187 participants from Turkey and Germany, which are characterized by different cultural norms, values, and socialization practices regarding emotional experience and expression. All participants completed measures of intrinsic IER strategies alongside measures of adaptive outcomes, including depression, anxiety, negative affect, and positive affect. The results revealed cross-national differences between Turkish and German individuals in terms of the intrinsic IER strategies most frequently selected and their associations with depression, anxiety, negative affect, and positive affect. These findings emphasize the significance of cultural context in intrinsic IER and offer insights into the conditions under which these strategies are linked to adaptive outcomes. By recognizing the cultural nuances in how people navigate their emotions via social interactions, clinicians and researchers can develop more culturally sensitive interventions tailored to the specific needs of individuals in diverse cultural contexts.Article Citation Count: 0The Floor Is (y)ours: Auxiliary Staff Voices Their Persona(Wiley, 2024) Caner, Mustafa; Karatas, Suleyman; Karadag, Engin; Sertel, GulsumThe current study investigated the perspectives of auxiliary staff regarding their profession. This study used a holistic multiple-case study design and a qualitative research method. The sample consisted of 45 auxiliary staff who worked in various K12 public schools in the central districts of a city in Turkey and voluntarily participated in the study. The study's participants, which was designed using a case study design, consisted of 45 auxiliary staff working in 11 K12 public schools in the central districts of a province in Turkey who voluntarily participated in the study. A maximum variation sampling strategy, a purposeful sampling technique, was employed for sample selection. Semi-structured interviews were conducted with each participant to gather data for this study. An inductive content analysis method was used to analyze the collected data, and the findings were interpreted accordingly. The results revealed that auxiliary staff perform multiple roles, such as sanitation, kitchen duties, environmental monitoring, administrative tasks, and technical work. Moreover, the auxiliary staff perceived that their various roles contributed to the overall well-being of the school community in schools.Article Citation Count: 0When Neighbors Become Aggressors: the Local Tensions Behind the Expulsion of Jews From Eastern Thrace in 1934(Cambridge Univ Press, 2024) Basaranlar, BurakThis article examines the local context that led to the expulsion of Jews from Eastern Thrace in 1934. Going beyond the conventional state-centric narratives, it unearths the local socio-economic tensions that triggered the locals to target their Jewish neighbors. It highlights three major factors that fueled already-existing nationalist sentiments in the region: some Jewish merchants' involvement in usury, Turkish-Muslim agricultural producers' growing indebtedness due to the devastating impact of the Great Depression, and the government's failure to support producers with appropriate credit policies. Faced with the danger of indebtedness and dispossession, the locals in this context deemed the small Jewish community as "the easy target," scapegoating it for their ongoing problems amid Turkey's nationalist political climate in the 1930s.Article Citation Count: 0Maternal Underestimations and Overestimations of Their Infants' Word Comprehension: Effects on Mothers' Verbal Input and Infants' Receptive Vocabulary(Cambridge Univ Press, 2024) Ertas, Sura; Kuntay, Aylin C.; Aktan-Erciyes, AsliInfants' language is often measured indirectly via parent reports, but mothers may underestimate or overestimate their infants' word comprehension. The current study examined estimations of mothers from diverse educational backgrounds regarding their infants' word comprehension and how these estimations are associated with their verbal input and infants' receptive vocabulary at 14 months. We compared 34 infants' looking-while- listening (LWL) performances with the mothers' Turkish Communicative Development Inventory (TCDI) reports to calculate the mothers' overestimation and underestimation. During free-play sessions, we assessed the mothers' number of words, number of clauses, lexical diversity, and linguistic complexity. We found that mothers have overestimations and underestimations regardless of their educational background. Crucially, mothers' only overestimations were positively associated with their number of words and lexical diversity. Mothers' verbal input was not related to infants' receptive vocabulary scores. The findings suggest that mothers' input might be aligned with their estimations of their infants' language capabilities, which might not reflect the infants' true performance.Article Citation Count: 0Change of the Built Environment in Jerusalem During the Late Ottoman Period (1840-1917)(Routledge Journals, Taylor & Francis Ltd, 2024) Alioglu, E. FusunThe establishment of Jerusalem, the holy city of three monotheistic religions on a global scale, dates to 4000 BCE. The city has been settled by various civilizations and has had walls protecting its borders since ancient times. Throughout history, Jerusalem has been influenced by Assyrian, Babylonian, Persian, Hellenic, Roman, Byzantine, Islamic States, and Ottoman periods. The Ottoman Empire first took control of the city in 1517 and then again in 1840, when they regained dominance in Syria and Palestine. In 1841, Jerusalem was separated from the Damascus Province and directly linked to Istanbul. This marked a period of modernization for the Ottoman Empire, following the Tanzimat Edict of 1839. This led to significant changes in legal, administrative, social, economic, political, and zoning fields, transforming the appearance of Ottoman cities. This article will discuss how existing structures were managed in Jerusalem during the final period of Ottoman rule, the regulations for constructing new buildings, the preservation of ancient monuments, and the enforcement of new laws.Article Citation Count: 0X-Ray Spectroscopy of the Dwarf Nova Z Chamaeleontis in Quiescence and Outburst Using the Xmm-Newton Observatory(Iop Publishing Ltd, 2024) Balman, Solen; Schlegel, Eric M.; Godon, Patrick; Drake, Jeremy J.We present X-ray spectroscopy of the SU UMa-type dwarf nova Z Chamaeleontis using the European Photon Imaging Camera and reflection grating spectrometer (RGS) instruments on board the XMM-Newton observatory. The quiescent system can be modeled by collisional equilibrium (CIE) or nonequilibrium plasma models, yielding a kT of 8.2-13.0 keV at a luminosity of (5.0-6.0) x 10(30) erg s(-1). The spectra yield better chi(nu)2 using partially covering absorbers of cold and/or photoionized nature. The ionized absorber has an equivalent N-H = (3.4-5.9) x 10(22) cm(-2) and a log(xi) = 3.5-3.7 with a (50-60)% covering fraction when the VNEI model (XSPEC) is used. The line diagnosis in quiescence shows no resonance lines, with only the forbidden lines of Ne, Mg, and Si detected. The H-like C, O, Ne, and Mg are detected. The strongest line is O viii, with (2.7-4.6) x 10(-14) erg s(-1) cm(-2). The quiescent X-ray-emitting plasma is not collisional and not in ionization equilibrium, which is consistent with hot ADAF-like accretion flows. The line diagnosis in the outburst shows He-like O and Ne, with intercombination lines being the strongest, along with weaker resonance lines. This indicates the plasma is more collisional and denser, but not yet in CIE, revealing ionization timescales of (0.97-1.4) x 10(11) s cm(-3). The R ratios in the outburst yield electron densities of (7-90) x 10(11) cm(-3) and the G ratios yield electron temperatures of (2-3) x 10(6) K. The outburst luminosity is (1.4-2.5) x 10(30) erg s(-1). The flow is inhomogeneous in density. All detected lines are narrow, with widths limited by the resolution of RGS, yielding Keplerian rotational velocities <1000 km s(-1). This is too low for boundary layers, consistent with the nature of ADAF-like hot flows.Article Citation Count: 0The Role of Hydrogen in the Energy Mix: a Scenario Analysis for Turkey Using Osemosys(Mdpi, 2024) Tetik, Hepnur; Kirkil, GokhanThe urgent need to tackle climate change drives the research on new technologies to help the transition of energy systems. Hydrogen is under significant consideration by many countries as a means to reach zero-carbon goals. Turkey has also started to develop hydrogen projects. In this study, the role of hydrogen in Turkey's energy system is assessed through energy modeling using the cost optimization analytical tool, Open Source Energy Modelling System (OSeMOSYS). The potential effects of hydrogen blending into the natural gas network in the Turkish energy system have been displayed by scenario development. The hydrogen is produced via electrolysis using renewable electricity. As a result, by using hydrogen, a significant reduction in carbon dioxide emissions was observed; however, the accumulated capital investment value increased. Furthermore, it was shown that hydrogen has the potential to reduce Turkey's energy import dependency by decreasing natural gas demand.Article Citation Count: 0Regime Switching in Coupled Nonlinear Systems: Sources, Prediction, and Control-Minireview and Perspective on the Focus Issue(Aip Publishing, 2024) Franovic, Igor; Eydam, Sebastian; Eroglu, DenizRegime switching, the process where complex systems undergo transitions between qualitatively different dynamical states due to changes in their conditions, is a widespread phenomenon, from climate and ocean circulation, to ecosystems, power grids, and the brain. Capturing the mechanisms that give rise to isolated or sequential switching dynamics, as well as developing generic and robust methods for forecasting, detecting, and controlling them is essential for maintaining optimal performance and preventing dysfunctions or even collapses in complex systems. This Focus Issue provides new insights into regime switching, covering the recent advances in theoretical analysis harnessing the reduction approaches, as well as data-driven detection methods and non-feedback control strategies. Some of the key challenges addressed include the development of reduction techniques for coupled stochastic and adaptive systems, the influence of multiple timescale dynamics on chaotic structures and cyclic patterns in forced systems, and the role of chaotic saddles and heteroclinic cycles in pattern switching in coupled oscillators. The contributions further highlight deep learning applications for predicting power grid failures, the use of blinking networks to enhance synchronization, creating adaptive strategies to control epidemic spreading, and non-feedback control strategies to suppress epileptic seizures. These developments are intended to catalyze further dialog between the different branches of complexity.Article Citation Count: 0Simultaneous Impacts of Correlated Photovoltaic Systems and Fast Electric Vehicle Charging Stations on the Operation of Active Distribution Grids(Elsevier, 2024) Kenari, Meghdad Tourandaz; Ozdemir, AydoganThis paper presents two novel probabilistic models developed to account for the uncertainties of aggregated fast electric vehicle charging stations (FEVCSs) demand and correlated photovoltaic (PV) injections in active distribution network (ADN) analysis. Both models are more precise than the available ones. A probabilistic model based on the Beta distribution is used for solar radiance, while the shared random variables technique is proposed considering correlated solar radiation random variables. Furthermore, a probabilistic negative exponential load model is extended for modeling the FEVCSs based on the Weibull probability density function. Moreover, the proposed probabilistic load flow (PLF) model is solved using the combined cumulants and saddle-point approximation method. Numerical tests are provided and discussed by applying the IEEE 69-bus distribution system for different PV correlation coefficients and FEVCS load models. The results demonstrate how the uncertainty of PLF outputs is increased by integrating FEVCSs and correlated PV resources into the distribution network. In addition, simulation results validate that the cumulants-based methodology provides satisfactory accuracy with a low computational cost.Article Citation Count: 0Finding Leadership in Media Education(Univ Pittsburgh, Univ Library System, 2024) Baybars, Banu; Akser, MuratThis article is an exploration of leadership in media education and some of its identifying features. As lecturers in media studies and production, our teaching philosophy weaves through these themes: active learning (Budhai 2021), learning by doing (Schank et al 2013), peer and self-assessment (Iglesias P & eacute;rez, Vidal-Puga, and Pino Juste 2022) and constructive alignment (Loughlin, Lygo-Baker and Lindberg-Sand 2021).Article Citation Count: 0Multimodal Communication in Virtual and Face-To Gesture Production and Speech Disfluency(Istanbul Univ, Fac Letters, dept Psychology, 2024) Arslan, Burcu; Avci, Can; Ozer, DemetThe COVID-19 pandemic has made online data collection a popular choice. It is important to evaluate howcomparable online studies are to face-to-face studies, particularly in multimodal language research wheremodes of communication significantly impact the results. In this study, we examined individuals' rates andpatterns of speech disfluency and gesture use across face-to-face and online videoconferencing settings asthey described their daily routines (N= 64). We asked whether and how multimodal language is affected acrossdifferent communication settings and gesture use, particularly iconic gestures, is associated with speech fluencyregardless of the context. Our results have showed that the participants' overall disfluency rate was higherfor the speech communicated via videoconferencing than the speech communicated face-to-face. However,the type of disfluencies changed across contexts, such that filled pauses and repairs were more commonin online communication, whereas silent pauses were more common in face-to-face communication. Thesefindings signal an interplay between the cognitive functions of different disfluency types and communicativestrategies. Results indicate that the overall gesture frequency and iconic gesture use were similar in bothsettings. Furthermore, the use of iconic gestures was found to negatively predict the overall disfluency rate,regardless of the setting. This finding suggests that using iconic gestures might facilitate cognitive processes,paving the way for a more fluent speech. This study demonstrates that multimodal language and communicationstrategies may vary across different communication settings and nuanced understanding of the differences inmultimodal language between online and face-to-face communication can be gained using different contexts.The findings contribute to understanding the impact of increasingly widespread online communication onmultimodal language production processes and provide foundation for future research.Article Citation Count: 0The Impact of the Characteristics of Self-Service Technologies on Customer Experience Quality: Insights for Airline Companies(Vysoka Skola Obchodni & Praze, 2024) Duran, Cem; Uray, Nimet; Alkilani, ShaymaaResearch on self-service technologies (SSTs) has not been fully developed, and it is still open to debate with many aspects concerning its effect on customer experience and potential outcomes empirically, especially in the airline industry. Studies regarding these technologies and their potential impact are needed in the airline industry as they represent an integral part of the tourism industry. Previous studies on the airline industry have merely focused on SSTs and their impact on customer adoption, tendency to use, and satisfaction. The SSTs have the capacity to influence how customers perceive their experience in the overall process of getting a service. Thus, customer experience quality (CXQ) is influenced by the perceived characteristics of SSTs. The literature on the impact of SSTs on CXQ is considerably limited in general, particularly in the airline industry. More research on this issue is needed, especially following the outbreak of COVID-19; thus, this study aims to investigate a model that integrates the impact of the perceived characteristics of SSTs as antecedents and outcomes of CXQ. The research design of this study is based on a mixed-method approach: a preliminary study consisting of two qualitative investigations and a main study through face-to-face questionnaires with airline passengers. Structural equation modeling (SEM) is applied to the data collected from passengers traveling with the airline company in Turkey (N=501) through questionnaires applied as mall intercepts. The results of this study include extending the CXQ dimensions to add consistency and institutionalism, hence contributing to the service and tourism literature. Furthermore, this research provides actionable insights for managers in airline businesses to invest more in SSTs to improve their CXQ, customer satisfaction, and positive word-ofmouth communication (WOM).Article Citation Count: 0Sustainable Aviation Fuel Supplier Evaluation for Airlines Through Lopcow and Marcos Approaches With Interval-Valued Fuzzy Neutrosophic Information(Elsevier Sci Ltd, 2025) Ecer, Fatih; Tanriverdi, Gokhan; Yasar, Mehmet; Gorcun, Omer FarukIn line with the 2050 net zero emission target, sustainable aviation fuel (SAF) is recognized as one of the most effective decarbonization solutions for the aviation industry, which has been identified among the critical areas for mitigating climate change. However, although sustainability issues and decarbonization have attracted scholars' attention in various terms for the airline industry, we identified some significant theoretical and managerial gaps as follows: (i) the number of studies evaluating sustainable suppliers by airlines via multicriteria decision-making (MCDM) approaches are very few, (ii) the extant literature has no paper addressing airlines' SAF supplier selection process, and (iii) no widely established criteria set in the literature to evaluate the SAF suppliers for airlines. We propose a novel model for the decision-making process of airlines' sustainable SAF supplier selection, including 39 criteria from 5 aspects considering the triple bottom of sustainability. The proposed model involves the combination of the logarithmic percentage change-driven objective weighting (LOPCOW) and measurement alternatives and ranking according to the compromise solution (MARCOS) approaches' extended forms based on the interval-valued fuzzy neutrosophic numbers (IVFNN). A comprehensive sensitivity and comparison control is further exploited to display the developed framework's robustness and practicality. Our results suggest that airlines prioritize the green initiatives of SAF suppliers over the economic aspect in the process of sustainable SAF supplier selection. We provide some managerial and policy insights for practitioners and policy-makers in the airline industry and some directions for further research.
