WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/4465

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Citation - WoS: 1
Citation - Scopus: 1
Accelerated Trends in Tourism Marketing and Tourist Behaviour
(Routledge, 2023) Kozak, Metin; Kozak, Metin
[No Abstract Available]
Acoustic Assessment of Shared Office Spaces: A Case Based Study
(Society of Acoustics, 2025) Kelle, D.; Şaher, K.; Ustundag Ganic, O.
This study investigates the acoustic conditions in shared flex-desk office spaces, where user requirements differ from those in traditional permanent open-plan offices. Unlike conventional office environments, shared workspaces accommodate a diverse and dynamic user base, necessitating greater flexibility in acoustic and spatial design. To assess the acoustic environment and user preferences, both subjective and objective data were collected. Subjective data was obtained through questionnaire, capturing occupants’ perceptions of noise levels, and overall comfort. Objective measurements were conducted to show activity noise levels during a typical workday. The data collected was then compared with assessment parameters defined in standard ISO 22955:2021, to identify discrepancies in user needs and expectations. The findings indicate that shared desk open-plan offices exhibit higher ambient noise levels than traditional open-plan offices, with intelligible speech being the most dominant source of disturbance. While perceived noise levels strongly correlated with disturbance, noise disturbance was not significantly linked to work load related factors, suggesting user adaptation or task-specific resilience. These results highlight the need to reassess conventional acoustic standards, such as ISO 22955:2021, to better accommodate the unique dynamics of shared workspaces. Specifically, shared workspace users show greater flexibility in noise levels and demands in spatial configurations, promoting the networking and transition of knowledge and collaborative nature of these environments. This study underscores the limitations of applying traditional office acoustic standards to shared environments and suggests the necessity for revised criteria that better reflect the unique demands of these spaces. © Copyright 2012 - 2025 IIAV - All Rights Reserved.
Citation - WoS: 3
Citation - Scopus: 3
Adaptive Sampling Noise Mitigation Technique for Feedback-Based Quantum Algorithms
(Springer international Publishing Ag, 2024) Rahman, Salahuddin Abdul; Clausen, Henrik Glavind; Karabacak, Ozkan; Wisniewski, Rafal; Abdul Rahman, Salahuddin
Inspired by Lyapunov control techniques for quantum systems, feedback-based quantum algorithms have recently been proposed as alternatives to variational quantum algorithms for solving quadratic unconstrained binary optimization problems. These algorithms update the circuit parameters layer-wise through feedback from measuring the qubits in the previous layer to estimate expectations of certain observables. Therefore, the number of samples directly affects the algorithm's performance and may even cause divergence. In this work, we propose an adaptive technique to mitigate the sampling noise by adopting a switching control law in the design of the feedback-based algorithm. The proposed technique can lead to better performance and convergence properties. We show the robustness of our technique against sampling noise through an application for the maximum clique problem.
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: 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.
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 - 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: 2
Attentional Control Scale-Turkish Version: Psychometric Qualities, Factor Structure and Its Comparison with Behavioral Measures of Executive Attention
(ODTU-AYNA Klinik Psikoloji Destek Unitesi, 2024) Altan-Atalay, Ayse; Cinli, Dilem; Aksungur, Sebla Umay; Turkakin, Esin; Aksungur, Umay
Attentional control refers to the capacity to voluntarily control attentional resources in a flexible manner. Attentional control was reported to play a fundamental role in self-regulation, emotion regulation, delay of gratification, and psychological distress. The Attentional Control Scale (ACS) was developed to measure perceived attentional control based on shifting and focusing dimensions. The present studies aimed to adapt the Turkish version of ACS and asses its psychometric characteristics. Study 1 aimed to explore the psychometric qualities of the Turkish version with a group of Turkish individuals (N = 428, 306 women) between the ages of 18 and 68 and supported the two-factor model of ACS consisting of 17 items in total. The results supported that shifting, focusing, and total ACS showed adequate internal consistency, test-retest reliability, and convergent validity evidence based on its significant correlations with measures of anxiety, depression, and repetitive negative thinking, signifying its proper psychometric characteristics. In Study 2 (N = 97, 65 women), the association of ACS with behavioral attentional control measures was examined, and non-significant associations between self-report and behavioral measures of attentional control were denoted. These findings signified that rather than indicating the individual's actual attentional control capacity, ACS assessed how the individual perceives their own attention control capacities. Taken together, the results suggest that the Turkish form of ACS is a valid and reliable scale that can be used to assess perceived attentional control capacity based on shifting and focusing domains, particularly in the research setting.
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.
BERT for Harmonic Time Series Modeling: A Multi-Stage Fine-Tuning Approach
(IEEE, 2025) Hekimoglu, Nevin Sehbal; Tileylioglu, Salih; Akagunduz, Erdem
This study demonstrates the potential of a BERT-based transformer model in harmonic signal modeling using synthetic sinusoidal data. The model was trained through a three-stage fine-tuning process (reconstruction, linear analysis, full tuning) with a masked language modeling approach. In the first stage, the model successfully filled in missing data and learned the basic features, while in subsequent stages, its ability to capture temporal dependencies and sequential patterns was enhanced. Additionally, patch, time, and station embedding strategies effectively represented the harmonic structure of the signal. The results indicate that pre-training with synthetic data can overcome the limited access to real-world data, allowing transformer models to be efficiently used in these types of problems.
Citation - WoS: 1
Beyond the Disaster: Vulnerability of Governance in the Turkey-Syria Earthquake
(Palgrave Macmillan, 2024) Yilmaz, Elif Ebru; Tomaka, Deniz Halman
Çağının Mimarlık Ortamına Katkılarıyla Diyarbakır Artuklu Sultanı Nâsırüddin Melik Salih Mahmud (1200-1222)
(Istanbul Univ, Research Inst. Turkology, Dept Art History, 2025) Alper, Mehmet
Nâsırüddin Melik Salih Mahmud (M 1200-1222), Diyarbakır ve Mardin Bölgesinde 1102-1409 yılları arasında üç kol hâlinde hüküm sürmüş Artuklu Beyliği'nin Hasankeyf ve Diyarbakır kolunun sultanıdır. Hükümdarlığı süresince imar faaliyetlerine önem veren Nâsırüddin Melik Salih Mahmud’un siyasi kimliğinin ötesinde çağının önemli yapılarının hem banisi hem de mimarı olduğu yapıların inşa kitabelerinden açıkça anlaşılmaktadır. Yedi Kardeş Burcu (M 1208-1209) ve Devegeçidi Köprüsü, Nâsırüddin Melik Salih Mahmud’un planları doğrultusunda inşa edildikleri kitabelerindeki tersim (tasarımı yapan) ifadeleriyle belirtilen iki mimari eseridir. Her ne kadar inşa kitabelerinde belirtilmemiş olsa da Ulu Beden Burcu ve Artuklu Sarayı’nın mimari özellikleri ile Nâsırüddin Melik Salih Mahmud’u simgelediği düşünülen çift başlı kartal armalı süslemeleri göz önünde bulundurulduğunda yine onun tasarımıyla inşa edildiği kabul edilmektedir. 1200 – 1222 yılları arasında hüküm sürmüş Artuklu Sultanı Nâsırüddin Melik Salih Mahmud dönemi imar faaliyetle- rinin ele alındığı bu çalışmada, bu dönemde Diyarbakır’da inşa edilen yapılar incelenmiştir. Literatür çalışmalarıyla edinilen bilgiler, “Diyarbakır Surları Koruma Projesi” kapsamında gerçekleştirilen restorasyon çalışmaları sırasında elde edilen bulgularla birlikte değerlendirilerek, Nâsırüddin Melik Salih Mahmud dönemi çok yönlü olarak irdele- nerek bani-mimar ilişkisi ve yöneticinin tasarım sürecine katkısı ortaya konulmaya çalışılmıştır. Ayrıca, Diyarbakır’ın en eski kilisesi olduğu kabul edilen ve MS 3 yüzyıla tarihlendirilen St. George Kilisesi’nin Artuklu Dönemi eki olan avlu bölümünü tarihlendirmeye ve inşa edildiği dönemdeki işlevi konusuna açıklık getirmesi amaçlanmıştır.
Citation - WoS: 1
Citation - Scopus: 1
Channel Estimation and Physical Layer Security in Optical MIMO-OFDM based LED Index Modulation
(IEEE, 2023) Okumus, F. Batuhan; Panayırcı, Erdal; Khalighi, Mohammad Ali
In this paper, we propose a new and low-complexity channel estimation algorithm for the generalized LED index modulation (GLIM), recently proposed for visible-light communication systems based on multi-input multi-output (MIMO) and orthogonal frequency-division multiplexing (OFDM). For this scheme, denoted by GLIM-OFDM, we investigate the bit-error rate (BER), the mean-square error (MSE) of channel estimation, as well as the Cramer-Rao bound on the latter. Furthermore, we present a novel physical layer security (PLS) technique for the GLIM-OFDM scheme using precoding at the transmitter assuming it has the channel state information (CSI) between the LEDs and a legitimate user, but no knowledge of the CSI corresponding to eavesdroppers. The efficiency of the proposed PLS technique is demonstrated through numerical results.
Citation - WoS: 2
Citation - Scopus: 3
Channel Estimation Using Optical MIMO OFDM Based LED Index Modulation
(IEEE, 2021) Okumus, Furkan Batuhan; Panayırcı, Erdal
In this paper, a new MIMO channel estimation technique is proposed for generalized LED index modulation (GLIM-OFDM) developed for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) based VLC systems. The mean square error (MSE) of the channel estimation algorithm, the bit error rate (BER) and the Cramer-Rao (CR) lower-bound of the system were obtained analytically and the performance of the algorithm according to the signal-to-noise ratio was investigated by computer simulations. From the obtained MSE, BER and CR curves it is concluded that the MSE performance of the proposed channel estimation algorithm is very high and the BER performance of the system obtained with the estimated channel information is very close to the BER performance in the case of perfect knowledge of the channel.
Citizenship, Media and Activism in Turkey during Gezi Park Protests1
(Taylor and Francis, 2023) Yanardağoğlu, E.
In the decade that followed the Arab Spring, hopes for greater democratization in the Arabic speaking countries and their neighbours have waned. The political activism in Turkey has grown in the immediate years after the Gezi Park protests especially due to the increasing role of social media as an alternative venue for information exchange for citizens. However, the media freedom began to decline especially after the failed coup in 2016 onward and democratic backsliding have been more prominent. This chapter examines the use of Twitter during the Gezi Park protests and explores the ways in which it motivated or facilitated democratic participation. The data presented here are drawn from independent research efforts of a number of academics who collaborated in data collection, which combines a quantitatively driven social network analysis of approximately one million archived tweets, followed by in-depth interviews in order to collect personal accounts of motivations for online participation of protestors during the Gezi Protests. © 2024 selection and editorial matter, Nael Jebril and Mohammed-Ali Abunajela; individual chapters, the contributors.
Co-Insurance and Rights of Subrogation Post-Gard Marine and Energy V China National Chartering Company Ltd
(Edward Elgar Publishing Ltd., 2024) Noussia, K.; Aslan, Y.C.
Citation - WoS: 108
Citation - Scopus: 128
Cognitive impairment in amyotrophic lateral sclerosis: evidence from neuropsychological investigation and event-related potentials
(Elsevier Science Bv, 2002) Hanagasi, Hasmet A.; Gurvit, I. Hakan; Ermutlu, Numan; Kaptanoğlu, Gulustu; Karamürsel, Sacit; Idrisoğlu, Halil A.; Emre, Murat; Demiralp, Tamer
The presence of subclinical cognitive impairment in patients with amyotrophic lateral sclerosis (ALS) is investigated using neuropsychological assessment and event-related potential recordings (ERP). An extensive battery of neuropsychological tests assessing the domains of attention memory language visuo-spatial and executive functions were administered to 20 non-demented patients with sporadic ALS and 13 age- and education-matched healthy control subjects. Mismatch negativity (MMN) P3b P3a (novelty P300) and contingent negative variation (CNV) were recorded. ALS patients were significantly impaired in tests of working memory sustained attention response inhibition naming verbal fluency and complex visuo-spatial processing. The memory impairment seemed to be secondary to deficits in forming learning strategies and retrieval. In ERP recordings P3a and P3b amplitudes of ALS patients were lower compared with the controls P3a latencies were significantly longer and mean CNV amplitudes were higher. These results indicate subclinical impairment of cognitive functions in patients with ALS. The pattern of cognitive impairment suggests the dysfunction of the frontal network. (C) 2002 Elsevier Science B.V. All rights reserved.
Commentary: Shifting Standards? The ECtHR’s Evolving Approach to Minority Rights
(European Centre Minority Issues -ECMI, 2025) Akbulut, Olgun
This commentary critically examines the European Court of Human Rights' (ECtHR) approach to minority rights within the broader human rights framework. The analysis assesses how the Court's reasoning has reinforced or, recently, deviated from established principles. Through a doctrinal and critical analysis of key judgments, the commentary identifies trends in the Court's reliance on pluralism, non-discrimination, and democratic participation as guiding principles. While earlier rulings underscored the necessity of protecting cultural, linguistic, and religious identities, recent decisions - particularly regarding Russian-speaking minorities in Latvia - signal a shift, raising concerns on judicial reasoning. The findings highlight inconsistencies in the Court's application of international minority rights instruments and question the broader implications for legal certainty in minority rights protection.

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