Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/1248

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18 - Turkey
(Cambridge University Press, 2020) Diner,C.
Each of these chapters contains a case study of a couple from the relevant country. Each includes a description of the everyday life of the couple with respect to the division of housework and childcare, a recounting of the history of their relationship and how it became equal, a discussion of how they balance paid work and family, and an analysis of the factors that facilitate their equality. Those factors include their conviction in gender equality, their rejection of essentialist beliefs, their familism, and their socialization in their families of origin. By showing how and why they undo gender, these couples provide lessons on how equality at home can be achieved. © Cambridge University Press 2020
Academic Freedom in the Tourism and Hospitality Literature: A Review and Call for Action
(Taylor and Francis, 2026) Wen, J.; Kozak, M.; Hu, F.
Academic freedom, the cornerstone of intellectual inquiry, has been a subject of reflection and debate. Whereas it is a fairly common topic in disciplines such as higher education, relevant discussion in tourism and hospitality is limited: a systematic review, described in this chapter, revealed a mere five articles within the literature in this field. The chapter highlights the need to focus on academic freedom from an interdisciplinary perspective in order to further develop tourism and hospitality's reputation. A call for action is made by underlining potential constraints to academic freedom in this context and how removing these barriers can promote innovation and nurture a new generation of professionals. Overall, more voices and joint efforts are needed to foster academic freedom. © 2026 selection and editorial matter, Jun Wen, Metin Kozak, Joshua Aston and Wei Wang; individual chapters, the contributors.
Citation - WoS: 1
Citation - Scopus: 1
Accelerated Trends in Tourism Marketing and Tourist Behaviour
(Routledge, 2023) Kozak, Metin; Kozak, Metin
[No Abstract Available]
Citation - Scopus: 18
Actively open- minded thinking and the political effects of its absence
(Oxford University Press, 2023) Baron, J.; Isler, O.; Yilmaz, O.
[No abstract available]
Adoption of Design Thinking in Industry 4.0 Project Management
(IGI Global, 2021) Dilan, Ebru; Aydin, Mehmet Nafiz
Management of Industry 4.0 projects needs to have a distinct discourse, be flexible, iterative and creative. These projects are tightly linked with the way people work which is directly related to both their capabilities and their ways of thinking. Challenging Industry 4.0 projects entail out-of-the-box thinking. The basic premise of this research is that the complex transformation accompanying Industry 4.0, which involves various dimensions, requires extensive and effective project management that can leverage novel approaches and techniques such as design thinking. This new approach may overcome the limitations of the dominant model of standard project management and has the potential to bridge the gap between a refreshed project management perspective and the tools/techniques in practical use. Deciding whether, and to what extent, design thinking needs to be adopted in practice in Industry 4.0 project management is a challenge. However, it is time to start exploring the challenges governing the interface between agile approaches such as design thinking and Industry 4.0 project management. © 2025 Elsevier B.V., All rights reserved.
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(Springer Nature, 2025) Kurultay, A.B.
Citation - WoS: 1
Citation - Scopus: 1
Age Classification by WGAN Brain MR Image Augmentation
(IEEE, 2024) Yaman, Batuhan; Yilmaz, Ozge Zeynep; Darici, Muazzez Buket; Ozmen, Atilla
Medical image augmentation plays a crucial role in enhancing the performance of Artificial Intelligence (AI) applications in medical sciences. Augmenting medical images is important for solving data scarcity, increasing data diversity, enhancing robustness and reliability of model and improving training and test results that can be done in medical sciences. In this work we show that Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) can be used for increasing the performance of data classification. To achieve that, we have augmented healthy brain MR images by using WGAN and updated the dataset. The results give that when dataset augmented by WGAN-GP is used as input for CNN-based model to solve age classification problem, accuracy of this model increases to 98,37% from 95,14%. It can be concluded that the purposed WGAN-based brain MR image augmentation method enhances the performance of image classification.
Citation - WoS: 6
Citation - Scopus: 7
Alternative Credit Scoring and Classification Employing Machine Learning Techniques on a Big Data Platform
(Institute of Electrical and Electronics Engineers Inc., 2019) Hindistan, Yavuz Selim; Kiyakoğlu, Burhan Yasin; Rezaeinazhad, Arash Mohammadian; Korkmaz, Halil Ergun; Dağ, Hasan
With the bloom of financial technology and innovations aiming to deliver a high standard of financial services, banks and credit service companies, along with other financial institutions, use the most recent technologies available in a variety of ways from addressing the information asymmetry, matching the needs of borrowers and lenders, to facilitating transactions using payment services. In the long list of FinTechs, one of the most attractive platforms is the Peer-to-Peer (P2P) lending which aims to bring the investors and borrowers hand in hand, leaving out the traditional intermediaries like banks. The main purpose of a financial institution as an intermediary is of controlling risk and P2P lending platforms innovate and use new ways of risk assessment. In the era of Big Data, using a diverse source of information from spending behaviors of customers, social media behavior, and geographic information along with traditional methods for credit scoring prove to have new insights for the proper and more accurate credit scoring. In this study, we investigate the machine learning techniques on big data platforms, analyzing the credit scoring methods. It has been concluded that on a HDFS (Hadoop Distributed File System) environment, Logistic Regression performs better than Decision Tree and Random Forest for credit scoring and classification considering performance metrics such as accuracy, precision and recall, and the overall run time of algorithms. Logistic Regression also performs better in time in a single node HDFS configuration compared to a non-HDFS configuration.
Citation - Scopus: 25
Analog VLSI Design Automation
(CRC Press, 2003) Balkir,S.; Dündar,G.; Öğrenci,A.S.
The explosive growth and development of the integrated circuit market over the last few years have been mostly limited to the digital VLSI domain. The difficulty of automating the design process in the analog domain, the fact that a general analog design methodology remained undefined, and the poor performance of earlier tools have left the analog. © 2003 by CRC Press LLC.
Citation - Scopus: 1
Analysis and Optimization of the Network Throughput in IEEE 802.15.13 based Visible Light Communication Networks
(IEEE, 2021) Bulbul, Yusuf; Elamassie, Mohammed; Baykas, Tuncer; Uysal, Murat
In line with the growing interest on visible light communication (VLC), IEEE has initiated standardization efforts on this emerging technology. In this work, we consider IEEE 802.15.13 Optical Wireless Personal Area Networks (OWPAN) standard draft. The underlying MAC protocol uses contention free and contention access periods. For a standard-compliant VLC network, we analyze the network load and propose an algorithm to improve the network throughput by proper selection of period lengths. Our suggested algorithm improves the network performance by at least 5% in the case of variable network traffic up to 15 active users.
Citation - WoS: 2
Citation - Scopus: 6
Analysis of deep learning based path loss prediction from satellite images
(IEEE, 2021) Alam, Muhammad Z.; Ates, Hasan F.; Baykas, Tuncer; Gunturk, Bahadir K.
Determining the channel model parameters of a wireless communication system, either by measurements or by running electromagnetic propagation simulations, is a time-consuming process. Any rapid deployment of network demands faster determination of at least major channel parameters. In this paper, we investigate the idea of using deep convolutional neural networks and satellite images for channel parameters (i.e., path loss exponent n and shadowing factor sigma) prediction in a cellular network with aerial base stations. Specifically, we investigate the performance dependency of the method on three different factors: height of the transmitter antenna, quantization levels of the channel parameters and architectural design of CNN. The results presented in this paper show a high prediction accuracy of the channel parameters in real-time.
Citation - Scopus: 2
Analytical approaches for the amplitude and frequency computations in the astable cellular neural networks with opposite sign templates
(2007) Tander, B.; Özmen, A.
In this paper, by using surface fitting methods, analytical approaches for amplitudes and frequencies of the x1,2(t) "States" in a simple dynamical neural network called "Cellular Neural Network with Opposite Sign Templates" which was proposed by Zou and Nossek [1], are obtained under oscillation conditions. The mentioned explicit expressions are employed in a cellular neural network based, amplitude and frequency tuneable oscillator design.
An Ant-Lion Optimization Based Approach to Solve Phase Balancing Problem in Distribution Networks
(IEEE, 2024) Yesilyurt, Gunnur; Ceylan, Oguzhan
Phase unbalance is a significant issue for power distribution networks. It can lead to increased energy losses and voltage instability, undermining the electrical grid's reliability and efficiency. We propose an approach to minimize voltage unbalance through reactive power management from PV installations and the optimization of charging/discharging of energy storage devices utilizing a control algorithm based on Ant-Lion Optimizer. We tested the approach on the IEEE 123-Bus Test System, incorporating PV generations by daily simulations. From the results, the combined operation of reactive power support from PVs and Storage Units with the help of the ALO algorithm offers a promising solution to the phase unbalance problem.
Citation - Scopus: 1
Application of fluorescence technique for understanding film formation from polymer latexes and composites
(Elsevier, 2021) Uğur, Ş.; Pekcan, Önder
This chapter summarizes the application of fluorescence technique to understand all aspects of film formation using both pure polymer latexes and polymer nanocomposites. Transient fluorescence, steady state fluorescence, and photon transmission techniques were used in conjunction with scanning electron microscopy/atomic force microscopy to learn this process with different latex coatings. Polystyrene latexes and poly(methyl methacrylate) latexes labeled with fluorescence probes (such as pyrene, fluorescein, and naphthalene) were used as the model polymer matrixes. We also introduced theoretical models to describe film formation stage by stage including void closure, healing, and interdiffusion and produced the activation energies related to the process. Furthermore the contributing parameters to the film formation process are identified including annealing time-temperature, solvent vapor, film thickness, particle size, and different filler materials and ratios (clay, TiO2, carbon nanotube, etc.) in both pure latex and composite systems. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 79
Citation - Scopus: 95
The association of the severity of obstructive sleep apnea with plasma leptin levels
(Amer Medical Assoc., 2003) Öztürk, Levent; Ünal, Murat; Tamer, Lülüfer; Çelikoğlu, Firuz
Objective: To examine whether circulating leptin levels correlate with the severity of disease in patients with obstructive sleep apnea. Design: Prospective nonrandomized study. Setting: Referral sleep laboratory for patients with sleep-disordered breathing and biochemistry laboratory. Patients: Thirty-two subjects (mean+/-SD age 47+/-12 years) who were referred for suspected sleep apnea underwent an overnight sleep study and fasting morning venous blood sampling. Patients were divided into 3 groups with respect to apnea-hypopnea index: (1) severe sleep apnea (n=8) apnea-hypopnea index greater than 20
Citation - WoS: 10
Citation - Scopus: 11
Automatic Adaptation of Hypermutation Rates for Multimodal Optimisation
(Assoc Computing Machinery, 2021) Corus, Dogan; Oliveto, Pietro S.; Yazdani, Donya
Previous work has shown that in Artificial Immune Systems (AIS) the best static mutation rates to escape local optima with the ageing operator are far from the optimal ones to do so via large hypermutations and vice-versa. In this paper we propose an AIS that automatically adapts the mutation rate during the run to make good use of both operators. We perform rigorous time complexity analyses for standard multimodal benchmark functions with significant characteristics and prove that our proposed algorithm can learn to adapt the mutation rate appropriately such that both ageing and hypermutation are effective when they are most useful for escaping local optima. In particular, the algorithm provably adapts the mutation rate such that it is efficient for the problems where either operator has been proven to be effective in the literature.
Citation - Scopus: 3
Automatic Segmentation of Time Series Data With Pelt Algorithm for Predictive Maintenance in the Flat Steel Industry
(Institute of Electrical and Electronics Engineers Inc., 2024) Kaçar, S.; Balli, T.; Yetkin, E.F.
In this study, we aim to test the usability of Change Point Detection (CPD) algorithms (specifically the Pruned Exact Linear Time-PELT) to facilitate the utilization of large volumes of data within predictive mechanisms in the industry. We proposed an efficient CPD parameter selection mechanism for defect diagnosis using time-series vibration data from critical assets. We emphasized the practical algorithm PELT to ensure broad industrial applicability. Our experimental analysis, using synthetic and actual vibration data, demonstrated the practical applicability and effectiveness of PELT algorithm for automatic segmentation. The numerical results show the potential of CPD methodologies for improving predictive maintenance operations by providing an automatic segmentation mechanism. This pipeline proposes a way to increase the operational efficiency and scalability of predictive maintenance approaches, enhancing maintenance procedures and ensuring the long-term reliability of industrial systems. © 2024 IEEE.
Barbieist vs. Oppenheimerist: A Gender-Based Reception Study of Barbie in Turkey
(Bloomsbury Publishing Plc., 2026) Behlil, M.; Erdede, R.D.
Barriers To Gender-Based Pro-Environmental Travel Behavior
(Edward Elgar Publishing Ltd., 2024) Chalermchaikit, V.; Kozak, M.
This chapter aims to rationally analyze responsible travel behavior from the sustainability and development perspective, indicating barriers and implications toward tourists’ pro-environmental behavior. Based on sustainability, the triple bottom line shows possible ways to move from the previous travel behavior via sustainable behavior, highlighting the ‘Go Green’ concept influencing marketing, communication, and policies. Gender implications become important keys to sustainable behavior patterns via marketing, communication, and policies. Also, the chapter integrates the current practice of the United Nations via sustainable development goals with implementation as a part of travel behavior. Thus, the viewpoints analyze the different marketing, communication, and policy approaches via different dimensions; values, social norms, and travel constraints through sustainable travel behavior. Furthermore, the scope of different gender perceptions is from the lens of tourists via attitudes, behavior, and characteristics. Hence, the chapter conceptualizes gender-based pro-environment and concludes with coherent predictions of pro-environment behavior. © The Editors and Contributors Severally 2024.
Battery Capacity Determination Of Electric Vehicle Under Variable Temperature Conditions
(Institute of Electrical and Electronics Engineers Inc., 2024) Yavuz, H.; Saygili, T.; Gulisli, A.; Tavakol, V.B.
This paper presents an innovative test method for evaluating the effects of sudden temperature changes on battery capacity. Unlike existing test methods, this method aims to measure the discharge capacity of the battery during abrupt temperature variations using a single test approach. In the test conducted in this study, a fully charged battery was subjected to partial discharge after sudden temperature changes, and then the temperature was returned to the reference value, allowing the discharge to continue until the minimum voltage was reached. In this way, the effect of temperature fluctuations on the usable capacity was observed. Using the same test method, the battery was discharged to the minimum voltage at low temperatures. After the temperature was returned to the reference value, the discharge process continued, and as a result, it was observed that sudden changes in temperature had no effect on capacity. These findings provide a new methodological contribution that can be applied in the battery industry and battery modeling techniques. © 2024 IEEE.

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