Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14365/3

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Now showing 1 - 20 of 227

Citation - WoS: 9
Citation - Scopus: 17
Abnormal Ecg Beat Detection Based on Convolutional Neural Networks
(Institute of Electrical and Electronics Engineers Inc., 2020) Ozdemir M.A.; Guren O.; Cura O.K.; Akan A.; Onan A.
The heart is the most critical organ for the sustainability of life. Arrhythmia is any irregularity of heart rate that causes an abnormality in your heart rhythm. Clinical analysis of Electrocardiogram (ECG) signals is not enough to quickly identify abnormalities in the heart rhythm. This paper proposes a deep learning method for the accurate detection of abnormal and normal heartbeats based on 2-D Convolutional Neural Network (CNN) architecture. Two channels of ECG signals were obtained from the MIT-BIH arrhythmia dataset. Each ECG signal is segmented into heartbeats, and each heartbeat is transformed into a 2-D grayscale heartbeat image as an input for CNN structure. Due to the success of image recognition, CNN architecture is utilized for binary classification of the 2-D image matrix. In this study, the effect of different CNN architectures is compared based on the classification rate. The accuracies of training and test data are found as 100.00% and 99.10%, respectively for the best CNN model. Experimental results demonstrate that CNN with ECG image representation yields the highest success rate for the binary classification of ECG beats compared to the traditional machine learning methods, and one-dimensional deep learning classifiers. © 2020 IEEE.
Accurate Dictionary Matching for Mr Fingerprinting Using Neural Networks and Feature Extraction
(Institute of Electrical and Electronics Engineers Inc., 2020) Soyak R.; Ersoy E.O.; Navruz E.; Fakultesi M.; Unay D.; Oksuz I.
Magnetic Resonance Fingerprinting is a recent technique which aims at providing simultaneous measurements of multiple parameters. MRF works by varying acquisition parameters in a pseudorandom manner so as to get unique, uncorrelated signal evolutions from each tissue. MRF is a dictionary based approach, and thus requires a database. This database can be created by simulating the signal evolutions from first principles using different physical models for a wide variety of tissue parameter combinations. Having this dictionary, a pattern recognition algorithm is used to match the acquired signal evolutions from each voxel with each signal evolution in the dictionary. In this paper, we compare the efficiency of deep learning based feature extraction method and neural network architectures in order to achieve state-of-the-art accuracy in dictionary matching for MRF. Our results showcase successful dictionary matching with high accuracy both quantitatively and qualitatively. © 2020 IEEE.
Addressing Diversity in Language Teacher Education: Perspectives on Practicum
(IGI Global, 2023) Taner, G.; Ataş, U.
This chapter defines diversity with its relation to initial teacher education and discusses its significance for the pre-service teachers’ practicum experience, which, in addition to the theoretical courses that might (and usually might not) address diversity, enables them to conceptualize the term. It also refers to teacher education systems in some European countries to present the ways in which diversity could be addressed in teacher education. The second half of the chapter presents a case study carried out in Turkey to illustrate how diversity is perceived from the views of teacher educators and pre-service teachers in the context of pre-service language teaching practicum. Though the case study is context-specific, the context bears similarities with many other teacher education environments offering suggestions, implications, and conclusions for initial language teacher education, policy development, and research. © 2023 by IGI Global. All rights reserved.
Citation - WoS: 17
Citation - Scopus: 16
Agility and Resource Dependency in Ramp-Up Process of Humanitarian Organizations
(Emerald Group Publishing Ltd, 2019) Qing, Lu; Wu, Jie; Goh, Mark; De Souza, Robert
Purpose The ramp-up in humanitarian logistics operations is a stage when the demand surges, often at the start of an emergency. In response, agility is a key strategy used by the humanitarian organizations (HOs). However, the HOs are constrained by their existing resources and have to respond in the ramp-up process under their resource dependency. The purpose of this paper is to develop a framework on agility-building strategies used by HOs for the ramp-up. Design/methodology/approach This study applies both the dynamic capabilities perspective and resource dependence theory to humanitarian relief operations, and develops four testable propositions to explore the agility-building strategies of the HOs for the ramp-up process. A multiple-case study is conducted on six international HOs operating in Indonesia to verify them, in addition to an extensive literature search. Findings The case study shows that the human resource management, pre-positioning, standardization and supplier management of the HOs are all related to their resources and environment in the ramp-up process. The authors highlight the practical differences between the few super large, resource rich and centralized HOs with the second-tier HOs. Research limitations/implications - Given the small sample size and single country as the site of study, some findings may not be applicable to the other HOs or in other regions. Practical implications - The propositions could be applicable to other HOs operating under similar environments, and potentially to the commercial enterprises operating in a highly volatile environment with severe resource scarcity. Originality/value This study provides new insights into ramp-up operations and into how HOs build their agility and reduce their resource dependencies. Theoretically, the paper applies two established theories in the strategic management literature to a new field.
Citation - WoS: 1
Citation - Scopus: 1
The Alevis and Roma/Gypsy in Turkey: Republican Freedom Revisited
(Routledge journals, taylor & francis ltd, 2024) Tamaç, Burak; Yumlu, Oğan; Boyraz, Cemil
This study examines the prospects and limitations of the republican theory of freedom as an analytical tool for analysing Turkey's state of rights and liberties. Following an outline of the main philosophical arguments of republican freedom, which emphasises the link between freedom and non-domination, the paper focuses on the cases of Alevis and Roma-Gypsy populations in Turkey, as two different minority groups that face a unique set of identity problems. The debate on the nature of the discriminatory treatment of certain ethnoreligious groups in Turkey tries, on the one hand, to demonstrate the republican conception's promise to uncover difficulties relating to the status of freedoms. On the other hand, it seeks to highlight potential constraints, especially when it realises socio-economic rights.
Algorithmic Postmemory in the Age of Digital Hoarding
(Routledge Journals, Taylor & Francis Ltd, 2026) Koseoglu, Gamze
The algorithmic turn in photography has transformed memory into a collaboration between humans and machines, fostering digital hoarding -the compulsive accumulation of personal photographs and data that fuels AI systems and reshapes how we remember, forget, and fabricate the past. This article builds on Marianne Hirsch's postmemory to examine how AI technologies and digital hoarding co-create new forms of memory-making, blurring the boundaries between individual and collective histories. These shifts challenge traditional understandings of authenticity, agency, and representation, while also opening new possibilities for reimagining photographic memory in an AI-driven world. By introducing three original frameworks -algorithmic postmemory, speculative memory landscapes, and curated forgetting; this study critically explores the evolving dynamics of AI-mediated memory. It highlights the cultural, ethical, and theoretical implications of these transformations, emphasizing both their creative potential and risks of distortion and erasure. The study contributes to broader debates on culture, photography, and memory practices, underscoring the need for interdisciplinary and ethical engagement to ensure that algorithmic mediation enhances, rather than diminishes, the richness and complexity of human and collective histories.
Citation - WoS: 1
Citation - Scopus: 2
Alzheimer's Dementia Detection: an Optimized Approach Using Itd of Eeg Signals
(IEEE, 2024) Sen, Sena Yagmur; Akan, Aydin; Cura, Ozlem Karabiber
This paper presents a novel early-stage Alzheimer's dementia (AD) disease detection based on convolutional neural networks (CNNs). As it is widely used in detection and classification of AD disease, a time-frequency (TF) method has been proposed for AD detection. It has been described to address the problem of detecting early-stage AD by combining TF and CNN methods. The method is developed by utilizing the well-known structural similarity index measure (SSIM) to obtain discriminative features in each TF image. Experimental results demonstrate that the proposed method outperforms the early-stage AD detection using advanced signal decomposition algorithm that is intrinsic time-scale decomposition (ITD), and it achieves a notable improvement in terms of the detection success rates compared to AD detection from TF images of raw EEG signals.
Citation - WoS: 2
Citation - Scopus: 2
Analysing Sci Patients' Eeg Signal Using Manifold Learning Methods for Triple Command Bci Design
(Institute of Electrical and Electronics Engineers Inc., 2024) Kucukselbes H.; Sayilgan E.
This study analyzed EEG signals from patients with spinal cord injuries by examining five different hand-wrist movements. The signal processing steps designed for an automatic and robust EEG-based BCI system were applied sequentially. Initially, 37 different features in the time, frequency, and time-frequency domains were extracted from the preprocessed signal. After trying widely used Manifold Learning (ML) methods in the literature, including t-Distributed Stochastic Neighbor Embedding (t-SNE), Local Linear Embedding (LLE), Multi-Dimensional Scaling (MDS), and ISOmetric Mapping (ISOMAP), we attempted the Spectral Embedding method, which has not yet been utilized in EEG signal analysis. The signals were then classified using three different machine-learning algorithms. The study compared classification performance using the accuracy metric. A multi-class classification method was employed specifically the triple classification method. The most successful performance was achieved by using the ISOMAP machine learning method and kNN classifier for the Pronation-Palmar Grasp-Hand Open combination, with an accuracy of 0.993 ± 0.016. Other methods used were t-SNE, MDS, LLE, and Spectral Embedding, respectively. Regarding classifiers, the kNN, SVM, and Naive Bayes algorithms were found to be successful in that order. Based on these results, we propose a suitable methodology for designing a robust BCI system. © 2024 IEEE.
Citation - WoS: 2
Citation - Scopus: 5
Art-House Cinema, Avant-Garde Film, and Dramatic Modernism
(Univ Illinois Press, 2011) Cardullo, Robert
[Abstract Not Available]
Citation - WoS: 2
Asymptotic Constancy for Solutions of Abstract Non-Linear Fractional Equations With Delay and Generalized Hilfer ( A, B, A )- Derivatives
(Pergamon-elsevier Science Ltd, 2025) Kostic, Marko; Koyuncuoglu, Halis Can; Katican, Tugce
In this paper, we investigate the asymptotic constancy for solutions of abstract non-linear fractional differential (difference) equations with delay and generalized Hilfer ( a, b, a )- derivatives. Our results are applicable to the abstract fractional functional equations with the usually considered Riemann-Liouville, Caputo, Hilfer and Prabhakar derivatives.
Citation - Scopus: 1
Attribute Value-Range Detection in Identification of Paraphrase Sentence Pairs
(Institute of Electrical and Electronics Engineers Inc., 2016) Kumova S.; Karaoglan B.; Kisla T.
Identification of paraphrase sentence pairs becomes increasingly prominent in natural language processing area (e.g plagiarism detection, summarization, machine translation). In this study, it is proposed to employ information gain measure in determining the value-ranges of the paraphrase classification features on the renown paraphrase corpus of Microsoft Research (MSRP). The classification performances of value-ranges that are determined by information gain measure and an alternative heuristic method are compared by the use of Bayes classifier. The results show that the proposed method performs better than the heuristic method. © 2016 IEEE.
Citation - WoS: 4
Citation - Scopus: 4
The Battlefields of Leisure: Simple Forms of Labor Control in the Turkish Hospitality Sector
(Cambridge Univ Press, 2020) Erköse, Hüseyin Yener
This article is based on an ethnographic study in the Turkish hospitality sector and examines the employment of simple forms of labor control in hospitality service work from the perspective of labor process analysis. It introduces ethnographic data from two holiday villages on the southern coast of Turkey serving international customers. The two holiday villages were workplaces that employed mostly young workers for low-skill, routine tasks that demanded intense physical and emotional labor, but without due remuneration, career chances, and employment security. Data based on participant observation and in-depth interviews point to an increasing managerial reliance on simple forms of labor control. This happens as a result of intensifying competition among hospitality firms in a market with volatile demand and managerial perceptions regarding employees' lack of customer service skills due to routinization and simplification of tasks after the introduction of the all-inclusive boarding system. Such market-related developments encourage employers to use simple control mechanisms that help in adjusting staffing levels, imposing loyalty, cutting costs, and ensuring efficiency.
Citation - WoS: 2
Citation - Scopus: 3
Bioethanol Production From C1 Gases Using Alternative Media by Syngas Fermentation
(Inderscience Enterprises Ltd, 2022) Gungormusler, Mine; Azbar, Nuri; Keskin, Tugba
The main aim of the present study was to evaluate the effects of the presence or absence of trace elements and yeast extract on growth and ethanol production by Clostridium ragsdalei grown on C1 gas dominated syngas (60% CO, 10% CO2, 10% CH4, 10% H-2, 10% N-2). Comparison of whey powder and glucose syrup as low-cost substitutes helped develop a more cost-effective medium formulation to produce ethanol from syngas with significantly higher yields, achieving up to a 3.8-fold improvement with co-utilisation of syngas and glucose syrup. In addition, the results provided further insights into medium manipulation and possible modifications to decrease total costs for increased ethanol production by solventogenic acetogens via syngas fermentation by achieving a 15.6% reduction in the cost of fermentation medium.
Citation - WoS: 22
Citation - Scopus: 26
Carbon Footprints of Omnivorous, Vegetarian, and Vegan Diets Based on Traditional Turkish Cuisine
(Elsevier, 2021) Uctug, Fehmi Gorkem; Gunaydin, Dorukhan; Hunkar, Beliz; Ongelen, Cansu
Turkish cuisine is one of the most globally wide-spread and also nutritionally diverse diets in the world. Yet, to this day the environmental footprint of Turkish cuisine has not been studied. In this work, the carbon footprints of weekly omnivorous, vegetarian, and vegan diets based on traditional Turkish cuisine were calculated. The functional unit was selected as 20 00 kcal of daily intake per person, CCaLC (TM) was used as software alongside CML2001 methodology, and c cradle-to-grave approach was employed. The following stages were included in the life cycle inventory: raw material supply including packaging, meal preparation (energy required for cooking or baking), and end-of-life treatment. On average, the omnivorous, vegetarian and vegan diets were found to have carbon footprints of 35.22, 27.8 and 18.5 kg CO(2)eq. per functional unit, respectively. The reduced carbon footprint of the vegetarian and vegan diets was mainly attributed to the absence of meat and dairy products. Raw material supply emerged as the main hotspot with an average share of 77.2% in the overall carbon footprint, followed by meal preparation with a share of 21.5%. End-of-life treatment options did not have a significant effect on the carbon footprint. The results were found to be highly consistent with those reported earlier in the literature. Extrapolating the results showed that nutrition is roughly responsible for one third of the total carbon footprint of Turkey. The main conclusion was that Turkish cuisine is comparable with other major cuisines in terms of its environmental impacts, while offering a very diverse and healthy diet. (c) 2020 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 4
The Changing Configurations of Self-(m) Other Dialogue in North Cyprus
(Routledge Journals, Taylor & Francis Ltd, 2010) Ilter, Tugrul; Alankuş, Sevda
This paper deals with issues of identity, nationalism, postcolonialism, and selfother relations with a focus on a period of transformative events in North Cyprus. It notes how nationalism has been the dominant means of identification for Cypriots in their modern history, and argues that unless weakened and supplanted by a radically pluralist democracy, nationalism imagines one's identity as an indivisible unity and has no place for different others within the nation. However, a pressing relationship with others and otherness is no stranger to Cypriots either, which makes it clear that the border that defines the 'we' of such nationalism is, at the same time, the line that divides the self intrinsically, indicating the otherness of the self or its alterity. Subjectivity involves subjection to the other.
Changing Power Perceptions: Public Relations Practitioners and Social Media
(Bloomsbury Publishing Plc., 2015) Uzunoǧlu, E.; Öksüz, B.; Genç, M.
Citation - WoS: 1
Citation - Scopus: 2
Characterizing the Heterogeneity of Neurodegenerative Diseases Through Eeg Normative Modeling
(Nature Portfolio, 2025) Tabbal, Judie; Ebadi, Aida; Mheich, Ahmad; Kabbara, Aya; Guntekin, Bahar; Yener, Gorsev; Hassan, Mahmoud
Neurodegenerative diseases like Parkinson's (PD) and Alzheimer's (AD) exhibit considerable heterogeneity of functional brain features within patients, complicating diagnosis and treatment. Here, we use electroencephalography (EEG) and normative modeling to investigate neurophysiological mechanisms underpinning this heterogeneity. Resting-state EEG data from 14 clinical units included healthy adults (n = 499) and patients with PD (n = 237) and AD (n = 197), aged over 40. Spectral and source connectivity analyses provided features for normative modeling, revealing significant, frequency-dependent EEG deviations with high heterogeneity in PD and AD. Around 30% of patients exhibited spectral deviations, while similar to 80% showed functional source connectivity deviations. Notably, the spatial overlap of deviant features did not exceed 60% for spectral and 25% for connectivity analysis. Furthermore, patient-specific deviations correlated with clinical measures, with greater deviations linked to worse UPDRS for PD (rho = 0.24, p = 0.025) and MMSE for AD (rho = -0.26, p = 0.01). These results suggest that EEG deviations could enrich individualized clinical assessment in Precision Neurology.
Charity in the Audience of John the Baptist
(Brill Academic Publishers, 2018) van Eck, Alexander
This article draws attention to the frequent presence of women with children among the audience of John the Baptist's sermon as it is depicted in sixteenth- and seventeenth century prints and paintings. Rather than as genre-like additions, it is argued that they were included as allegories of Charity. According to the gospel of Luke, John the Baptist advised those who had two coats to give away one, and people who had an abundance of food to share it with others. In other words, he exhorted people to be charitable. A literal visualization of one of the acts of charity in the Baptist's sermon is seen on a print published by Nicholas de Mathonniere, in which a man gives away a coat to another person in the audience (note 6). The allegorical approach was much more common though. Examples come from Germany, Italy and the Netherlands. In a woodcut by Cranach, three women in the audience are suckling babies (fig. 2); in a painting by Bacchiacca, a woman with three young children frollicking on her lap is positioned prominently in the foreground (note 4); similar groups are visible in Bloemaert's version of the subject in the Rijksmuseum (fig. 1), and in Philips Galle's engraving (fig. 3). A special case is Jacob Backer's Family group with John the Baptist preaching, as it includes a portrait of the mater familias with one bare breast (fig. 4). That again points to an allegorical interpretation, because such a display of nudity in a common portrait would have been deemed improper. Since it concerns a Mennonite family - the artist, who was a Mennonite preacher himself, included a self portrait with his finger raised in warning - this picture is also a reminder that the subject of the Sermon of John the Baptist was not a typical Calvinist subject referring to open air sermons ('hagepreken'), as is often assumed (note 16). In a country like the young Republic, the sermon was an important instrument for all denominations and a suitable subject for decoration on any wall.
Çoklu Biyosensör Dizilerinin Nesnelerin İnterneti ile Uzaktan İzlenmesi için Altyapı Oluşturulması
(IEEE, 2024) Topalli, Ayca Kumluca
The number of telemetry applications based on Internet of Things is increasing rapidly. These researches are generally about biosensor design; but seamless data transmission is also important. This study is about to construct a robust infrastructure in case of a busy data transfer traffic simultaneously from many biosensors at many different locations to the same server, to setup a reliable platform for data storing, processing, and presenting with different interfaces. The system where Microsoft Azure infrastructure is used is tested by 100 different data input simultaneously. Proposed system offers a solution for health care services such as incubator monitoring, remote monitoring of elderly, etc.
Citation - Scopus: 4
Commonsense Knowledge Extraction Using Concepts Properties
(2011) Blanco E.; Cankaya H.C.; Moldovan D.
This paper presents a semantically grounded method for extracting commonsense knowledge. First, commonsense rules are identified, e.g., one cannot see imaginary objects. Second, those rules are combined with a basic semantic representation in order to infer commonsense knowledge facts, e.g. one cannot see a flying carpet. Further combinations of semantic relations with inferred commonsense facts are proposed and analyzed. Results show that this novel method is able to extract thousands of commonsense facts with little human interaction and high accuracy. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

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