Scopus İndeksli Yayınlar Koleksiyonu
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Book Part 18 - Turkey(Cambridge University Press, 2020) Diner,C.; 01. Kadir Has UniversityEach 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 2020Book Part Citation - WoS: 1Citation - Scopus: 1Accelerated Trends in Tourism Marketing and Tourist Behaviour(Routledge, 2023) Kozak, Metin; Kozak, Metin; Advertising; 04. Faculty of Communication; 01. Kadir Has University[No Abstract Available]Conference Object ACOUSTIC TRANSFORMATION OF ROCK-CUT CAVES INTO PERFORMANCE SPACES(European Acoustics Association, EAA, 2023) Aslan,A.; Saher,K.; Tozoglu,A.E.; Interior Architecture and Environmental Design; 06. Faculty of Art and Design; 01. Kadir Has UniversityCappadocia 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.Article Citation - WoS: 7Citation - Scopus: 6The acquisition and use of relative clauses in Turkish-learning children's conversational interactions: a cross-linguistic approach(Cambridge University Press, 2019) Uzundağ, Berna A.; Küntay, Aylin C.; Psychology; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has UniversityUsing 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.Book Part Citation - Scopus: 15Actively open- minded thinking and the political effects of its absence(Oxford University Press, 2023) Baron, J.; Isler, O.; Yilmaz, O.; 01. Kadir Has University[No abstract available]Book Part Adoption of Design Thinking in Industry 4.0 Project Management(IGI Global, 2021) Dilan, Ebru; Aydin, Mehmet Nafiz; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has UniversityManagement 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.Book Part Advertisements(Springer Nature, 2025) Kurultay, A.B.; 01. Kadir Has University; Advertising; 04. Faculty of CommunicationConference Object Citation - WoS: 1Citation - Scopus: 1Age Classification by WGAN Brain MR Image Augmentation(IEEE, 2024) Yaman, Batuhan; Yilmaz, Ozge Zeynep; Darici, Muazzez Buket; Ozmen, Atilla; Electrical-Electronics Engineering; 05. Faculty of Engineering and Natural Sciences; 01. Kadir Has UniversityMedical 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.Book Part Citation - WoS: 5Citation - Scopus: 7Alternative 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; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has UniversityWith 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.Book Citation - Scopus: 25Analog VLSI Design Automation(CRC Press, 2003) Balkir,S.; Dündar,G.; Öğrenci,A.S.; 01. Kadir Has UniversityThe 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.Conference Object Citation - Scopus: 1Analysis 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; Electrical-Electronics Engineering; 05. Faculty of Engineering and Natural Sciences; 01. Kadir Has UniversityIn 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.Conference Object Citation - WoS: 2Citation - Scopus: 5Analysis of deep learning based path loss prediction from satellite images(IEEE, 2021) Alam, Muhammad Z.; Ates, Hasan F.; Baykas, Tuncer; Gunturk, Bahadir K.; Electrical-Electronics Engineering; 05. Faculty of Engineering and Natural Sciences; 01. Kadir Has UniversityDetermining 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.Conference Object Citation - Scopus: 2Analytical approaches for the amplitude and frequency computations in the astable cellular neural networks with opposite sign templates(2007) Tander, B.; Özmen, A.; Electrical-Electronics Engineering; 05. Faculty of Engineering and Natural Sciences; 01. Kadir Has UniversityIn 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.Conference Object An Ant-Lion Optimization Based Approach to Solve Phase Balancing Problem in Distribution Networks(IEEE, 2024) Yesilyurt, Gunnur; Ceylan, Oguzhan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has UniversityPhase 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.Book Part Application of fluorescence technique for understanding film formation from polymer latexes and composites(Elsevier, 2021) Uğur, Ş.; Pekcan, Önder; Molecular Biology and Genetics; 05. Faculty of Engineering and Natural Sciences; 01. Kadir Has UniversityThis 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.Book Part Apprenticeship-Type Learning in the Local: Insights from a Cooperative Weaving Practice for Design Education(Springer Nature, 2023) Öz, G.; Timur, Ş.; Industrial Design; 06. Faculty of Art and Design; 01. Kadir Has UniversityA 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.Article Citation - WoS: 79Citation - Scopus: 95The association of the severity of obstructive sleep apnea with plasma leptin levels(Amer Medical Assoc., 2003) Öztürk, Levent; Ünal, Murat; Tamer, Lülüfer; Çelikoğlu, Firuz; 01. Kadir Has UniversityObjective: 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 20Conference Object Citation - WoS: 10Citation - Scopus: 11Automatic Adaptation of Hypermutation Rates for Multimodal Optimisation(Assoc Computing Machinery, 2021) Corus, Dogan; Oliveto, Pietro S.; Yazdani, Donya; Computer Engineering; 05. Faculty of Engineering and Natural Sciences; 01. Kadir Has UniversityPrevious 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.Conference Object Citation - Scopus: 1Automatic 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.; 01. Kadir Has UniversityIn 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.Article Citation - WoS: 4Citation - Scopus: 5Balance sheet effects of foreign currency debt and real exchange rate on corporate investment: evidence from Turkey(Elsevier B.V., 2021) Demirkılıç, Serkan; International Trade and Finance; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has UniversityI 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.
