Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/1248

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Citation - Scopus: 0
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
Citation - WoS: 1
Citation - Scopus: 1
Accelerated Trends in Tourism Marketing and Tourist Behaviour
(Routledge, 2023) Kozak, Metin; Kozak, Metin; Kozak, Metin
[No Abstract Available]
Citation - Scopus: 0
ACOUSTIC TRANSFORMATION OF ROCK-CUT CAVES INTO PERFORMANCE SPACES
(European Acoustics Association, EAA, 2023) Şaher, Konca; Saher,K.; Tozoglu,A.E.
Cappadocia Region in Turkey is a center of attention as a tourism destination with its rock-cut caves, some of which are being used as performance spaces for concerts, festivals and local entertainment activities. However, these spaces are not fully investigated for their acoustic performance before being transformed into performance venues. This paper reports on the findings of an initial survey which presents a systematic mapping of the rock-cut caves used as performance spaces to locate, explore and document a sample of structures scattered in this historic district. A typological classification based on volume, size, type of tuff rock material and historical original use has been proposed and an acoustic analysis of some selected rock-cut caves has been carried out. The acoustic analysis included reverberation time calculations and simulations based on apparent volume, and tuff stone absorption characteristics, which were studied by other researchers in the area. © 2023 Aslan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation - WoS: 6
Citation - Scopus: 5
The acquisition and use of relative clauses in Turkish-learning children's conversational interactions: a cross-linguistic approach
(Cambridge University Press, 2019) Arslan Uzundağ, Berna; Küntay, Aylin C.
Using a cross-linguistic approach, we investigated Turkish-speaking children's acquisition and use of relative clauses (RCs) by examining longitudinal child-caregiver interactions and cross-sectional peer conversations. Longitudinal data were collected from 8 children between the ages of 8 and 36 months. Peer conversational corpus came from 78 children aged between 43 and 64 months. Children produced RCs later than in English (Diessel, 2004) and Mandarin (Chen & Shirai, 2015), and demonstrated increasing semantic and structural complexity with age. Despite the morphosyntactic difficulty of object RCs, and prior experimental findings showing a subject RC advantage, preschool-aged children produced object RCs, which were highly frequent in child-directed speech, as frequently as subject RCs. Object RCs in spontaneous speech were semantically less demanding (with pronominal subjects and inanimate head nouns) than the stimuli used in prior experiments. Results suggest that multiple factors such as input frequency and morphosyntactic and semantic difficulty affect the acquisition patterns.
Citation - Scopus: 10
Actively open- minded thinking and the political effects of its absence
(Oxford University Press, 2023) Baron, J.; Isler, O.; Yilmaz, O.
[No abstract available]
Citation - Scopus: 0
Age Classification by Wgan Brain Mr Image Augmentation
(Institute of Electrical and Electronics Engineers Inc., 2024) Özmen, Atilla; Yilmaz, O.Z.; Darici, M.B.; Ozmen, A.
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. © 2024 IEEE.
Citation - WoS: 4
Citation - Scopus: 4
Alternative Credit Scoring and Classification Employing Machine Learning Techniques on a Big Data Platform
(Institute of Electrical and Electronics Engineers Inc., 2019) Dağ, Hasan; 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: 23
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 - WoS: 0
Citation - Scopus: 1
Analysis and Optimization of the Network Throughput in IEEE 802.15.13 based Visible Light Communication Networks
(IEEE, 2021) Baykaş, Tunçer; 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: 1
Citation - Scopus: 5
Analysis of deep learning based path loss prediction from satellite images
(IEEE, 2021) Baykaş, Tunçer; 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) Özmen, Atilla; 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.
Citation - Scopus: 0
Application of fluorescence technique for understanding film formation from polymer latexes and composites
(Elsevier, 2021) Pekcan, Mehmet Önder; 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 - Scopus: 0
Apprenticeship-Type Learning in the Local: Insights from a Cooperative Weaving Practice for Design Education
(Springer Nature, 2023) Öz, Gizem; Timur, Ş.
A growing area in design research concerns learning from local practices and diversifying design’s knowledge space. By understanding and documenting how women in a village in Turkey learn the craft of weaving, this paper reformulates the relationship between the design field and the local context as learning from the local and aims to contributes to the design education field. During the summers of 2017, 2018, and 2019, fieldwork using the participant observation method was conducted in the village. The detailed account of the learning process in this local weaving practice allows us to define this learning as “apprenticeship type learning in the local.” The practice consists of a process in which the forms of learning and teaching are inseparably interwoven with socio-spatial elements. It draws together flexible learning processes where the teaching moments blur and students learn in action in a dialogical exchange through observing and making. During these interactions, the importance of considering the cooperative and social aspects of the learning arises: not only technical knowledge, but also social values and beliefs are transferred in an interdependent process. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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) Çörüş, Doğan; 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: 0
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.
Citation - WoS: 4
Citation - Scopus: 4
Balance sheet effects of foreign currency debt and real exchange rate on corporate investment: evidence from Turkey
(Elsevier B.V., 2021) Demirkılıç, Serkan
I analyze the balance sheet channels of depreciation of the Turkish non-financial corporations for 2003–2015. Having constructed a novel, hand-collected firm-level dataset on the composition and term structure of foreign currency assets and liabilities, I show that foreign currency debt and mismatch has a significant negative balance sheet effect on capital investment following a depreciation. The results remain same even after controlling for foreign currency assets and exports. This implies that the contractionary net worth effect of depreciation dominates its expansionary competitiveness effect. The result is more pronounced for the firms with short-term foreign currency exposures.
Citation - Scopus: 0
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.
Citation - Scopus: 0
Big data analytics and models
(IGI Global, 2019) Sönmez, F.; Perdahçi, Z.N.; Aydin, M.N.
When uncertainty is regarded as a surprise and an event in the minds, it can be said that individuals can change the future view. Market, financial, operational, social, environmental, institutional and humanitarian risks and uncertainties are the inherent realities of the modern world. Life is suffused with randomness and volatility; everything momentous that occurs in the illustrious sweep of history, or in our individual lives, is an outcome of uncertainty. An important implication of such uncertainty is the financial instability engendered to the victims of different sorts of perils. This chapter is intended to explore big data analytics as a comprehensive technique for processing large amounts of data to uncover insights. Several techniques before big data analytics like financial econometrics and optimization models have been used. Therefore, initially these techniques are mentioned. Then, how big data analytics has altered the methods of analysis is mentioned. Lastly, cases promoting big data analytics are mentioned. © 2020, IGI Global.

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