Tütüncü, Gözde Yazgı

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Profile URL
https://hdl.handle.net/20.500.14365/7030
Name Variants
Tütüncü, G.Y.
Tutuncu, G. Yazgi
Aşçı, Gözde Yazgı Tütüncü
Tuetuencue, G. Yazgi
Tütüncü Aşçı, Gözde Yazgı
Tutuncu, Gozde Yazgi
Tutuncu, G.Y.
Job Title
Email Address
yazgi.tutuncu@ieu.edu.tr
Main Affiliation
02.02. Mathematics
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Current Staff
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ORCID ID
0000-0002-9363-6141
Scopus Author ID
26436326500
Turkish CoHE Profile ID
AC323561955AE7AC
Google Scholar ID
1AsbPe4AAAAJ
WoS Researcher ID
AAP-6520-2021
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Gozde_Tutuncu.png (77.47 KB)

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Supervised MSc Theses

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WoS Citation Count

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Scopus Citation Count

314

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JournalCount
Journal of Computatıonal And Applıed Mathematıcs2
4Th Annual Euromed Conference of the Euromed Academy of Busıness: Busıness Research Challenges in A Turbulent Era1
Acta Physiologica1
Advances in Computatıonal Intellıgence, Mıcaı 2016, Pt I1
Advances in Productıon Management Systems: Innovatıve And Knowledge-Based Productıon Management in A Global-Local World, Pt 11
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Now showing 1 - 10 of 37
  • Thumbnail Image
    Master Thesis
    A Cost Effectiveness Analysis To Compare Mastectomy Versus Lumpectomy Using a Fuzzy Approach
    (İzmir Ekonomi Üniversitesi, 2015) Aktaş, Aysun; Tütüncü, Gözde Yazgı
    Meme kanseri çoğu ülkede en yaygın olan kanser türüdür. Meme kanserinin tedavisi birçok faktöre bağlıdır. Erken evre meme kanseri hastaları belirli şartlar altında meme dokusunun çıkarılması (mastektomi) ya da meme koruyucu cerrahi (lumpektomi) yöntemlerinden birini seçebilir. Lumpektomi ve sonrasında uygulanan ışın tedavisi ile mastektominin sağ kalım oranları eşittir fakat hastaların duygusal, sosyal ve fiziksel hallerini etkileyen yaşam kaliteleri arasında önemli bir fark vardır. Bu çalışmanın amacı Mastektomi ve Lumpektomi operasyonlarını hastaların operasyon sonrası tedavilerini, tedavi maliyetlerini ve hastaların memnuniyetini dikkate alarak maliyet etkinlik analizi ile değerlendirmektir. Ameliyat sonrasında hastaların klinik geçmişini özetleyen bir karar ağacı oluşturulmuştur. Modeli tanımlarken geçiş olasılıkları ve yaşam kaliteleri kullanılmıştır. Maliyetlerin ve sağlık durumunun zamana bağlı değişkenliği sebebiyle düzensiz verileri değerlendirmek için güçlü bir karar aracı olan bulanık küme maliyet etkinlik oranı önerilmiştir. Gerekli veriler hastane kayıtlarından, TUIK veri tabanından ve yazılı kaynaklardan elde edilmiştir.
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    Article
    Citation - WoS: 29
    Citation - Scopus: 36
    A Visual Interactive Approach To Classical and Mixed Vehicle Routing Problems With Backhauls
    (Pergamon-Elsevier Science Ltd, 2009) Tütüncü, Gözde Yazgı; Carreto, Carlos A. C.; Baker, Barrie M.
    In this paper a new visual interactive approach for the classical vehicle routing problem with backhauls (VRPB) and its extensions is presented. The classical VRPB is the problem of designing minimum cost routes from a single depot to two type customers that are known as Backhaul (pickup) and Linehaul (delivery) customers where deliveries after pickups are not allowed. The mixed VRPB is an extension of the classical VRPB where deliveries after pickups are allowed. A decision support system (DSS) is developed in order to solve the classical VRPB, mixed VRPB and the restricted VRPB, which is a compromise problem between the classical VRPB, and the mixed VRPB. And a new criterion, which considers the remaining capacity of the vehicles, is proposed for producing solutions for mixed and restricted VRPB. The visual interactive approach that is based on Greedy Randomised Adaptive Memory Programming Search (GRAMPS) is described, and experimental results for the VRPB benchmark test problems are presented and analysed. The computational results on VRPB benchmark test problems indicated that the new criterion and the proposed visual interactive approach are effective towards finding a compromise between the mixed or restricted and the classical VRPB problems. The developed DSS is used by 18 students and reported to be capable of producing high quality solutions for the VRPB. (C) 2006 Elsevier Ltd. All rights reserved.
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    Conference Object
    Citation - Scopus: 1
    Drivers for Rfid Implementations
    (Springer Verlag, 2010) Goethals F.G.; Tütüncü, Gözde Yazgı; Lin C.-Y.
    This workshop paper studies drivers for RFID (Radio Frequency IDentification) adoption. The research in progress reported here puts forward several types of mindless and mindful decision making drivers. Hypotheses are tested using a questionnaire that was answered by 122 Chinese companies. The promise to reach higher efficiency seems to be the most important driver for mindful RFID adoption decisions. The early implementers were more driven to adoption by the promise of higher efficiency, better supply chain monitoring and better collaboration than late implementers. Tests show that mindless decision making shows up in RFID adoption. © 2010 Springer-Verlag Berlin Heidelberg.
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    Article
    High Prevalence of Developmental Coordination Disorder Risk in Childhood Apraxia of Speech
    (Wiley, 2025) Tukel, Sermin; Baker, Emma K.; Tutuncu, G. Yazgi; O'Donnell, Lorraine; Lauretta, Mariana; Brenchley, Celia; Morgan, Angela T.
    Aim To explore motor impairments linked to developmental coordination disorder (DCD) in children with childhood apraxia of speech (CAS).Method This prospective cohort study included 105 children (79 male, aged 5-15 years) with CAS. Assessments included the Developmental Coordination Disorder Questionnaire, Revised, the visuomotor precision subtest of the Neuropsychological Assessment, Second Edition, the motor subtest of the Vineland Adaptive Behaviour Scales, Third Edition (Vineland-3), and Full-scale IQ (FSIQ) scores. Data analysis used multiple imputation for missing data, along with descriptive statistics, repeated-measures analysis of variance, multiple binary logistic regression, and receiver operating characteristic (ROC) analyses.Results Eighty-two per cent of participants showed motor impairments; 63% screened positive for DCD risk; and 71% had visuomotor precision impairments. Fine-motor scores were lower than gross-motor and coordination scores. The logistic regression model accurately predicted DCD risk at 73%, identifying the Vineland-3 (odds ratio [OR] = 7.17) and visuomotor precision subtest (OR = 4.90) as significant predictors, whereas the FSIQ was not. The Vineland-3 showed a high false negative rate (46%) for DCD risk, and the ROC analysis suggested a higher cut-off point for improved prediction accuracy.Interpretation This study highlights a high prevalence of DCD risk and visuomotor precision impairments among children with CAS, independent of FSIQ. The Vineland-3 motor subtest is not recommended for DCD assessment, whereas screening for DCD is essential for targeted interventions in CAS.
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    Conference Object
    An Evolutionary Algorithm Based on Multidimensional Multiple-Choice Knapsack Model for Resource Allocation Problem in a Construction Equipment Manufacturer
    (International Conference on Information Systems, Logistics and Supply Chain, 2020) Duenas A.; Di Martinelly C.; Aguado J.; Tütüncü Y.
    This paper presents an approach to production resource allocation applied to a real-world problem within the construction equipment manufacturing industry. It shows an original way of determining the outcome manufacturing production problems using existing mathematical modeling techniques combined with evolutionary heuristics. A multidimensional knapsack problem was formulated, the proposed model being based on an evolutionary algorithm using a three-dimensional binary-coded chromosome. Three different selection strategies were applied to evaluate the algorithm's performance and tests were carried out to show the appropriateness of the solutions. The results obtained were of a high quality from the company's perspective. © Interconnected Supply Chains in an Era of Innovation - Proceedings of the 8th International Conference on Information Systems, Logistics and Supply Chain, ILS 2020. All rights reserved.
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    Article
    Citation - WoS: 6
    Citation - Scopus: 10
    A New Local Covariance Matrix Estimation for the Classification of Gene Expression Profiles in High Dimensional Rna-Seq Data
    (Pergamon-Elsevier Science Ltd, 2021) Kochan, Necla; Tütüncü, Gözde Yazgı; Giner, Goknur
    Recent developments in the next-generation sequencing based on RNA-sequencing (RNA-Seq) allow researchers to measure the expression levels of thousands of genes for multiple samples simultaneously. In order to analyze these kinds of data sets, many classification models have been proposed in the literature. Most of the existing classifiers assume that genes are independent; however, this is not a realistic approach for real RNA-Seq classification problems. For this reason, some other classification methods, which incorporates the dependence structure between genes into a model, are proposed. Quantile transformed Quadratic Discriminant Analysis (qtQDA) proposed recently is one of those classifiers, which estimates covariance matrix by Maximum Likelihood Estimator. However, MLE may not reflect the real dependence between genes. For this reason, we propose a new approach based on local dependence function to estimate the covariance matrix to be used in the qtQDA classification model. This new approach assumes the dependencies between genes are locally defined rather than complete dependency. The performances of qtQDA classifier based on two different covariance matrix estimates are compared over two real RNA-Seq data sets, in terms of classification error rates. The results show that using local dependence function approach yields a better estimate of covariance matrix and increases the performance of qtQDA classifier.
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    Master Thesis
    Reliability of Weighted K-Out System With M Types of Components
    (İzmir Ekonomi Üniversitesi, 2020) Benek, Seçil Tezel; Aşçı, Gözde Yazgı Tütüncü
    Bu tezde, birden fazla tip bileşenden oluşan ağırlıklı n'den-k'lı sistemler çalışıldı. m tane tip bileşene sahip ağırlıklı n'den-k'lı sistemlerin güvenirlilik analizi için genel bir yöntem önerildi. Farklı yapılara sahip sistemler için güvenirlilik gösterildi. Her gruptaki bileşen sayısının optimum değerleri, toplam edinme maliyetini en aza indirerek gerekli minimum güvenilirlik altında belirlendi. Ayrıca, sayısal örnekler de dahil edilmiştir.
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    Article
    Citation - WoS: 3
    Qtqda: Quantile Transformed Quadratic Discriminant Analysis for High-Dimensional Rna-Seq Data
    (Peerj Inc, 2019) Kochan, Necla; Tütüncü, Gözde Yazgı; Smyth, Gordon K.; Gandoffo, Luke C.; Giner, Goeknur
    Classification on the basis of gene expression data derived from RNA-seq promises to become an important part of modern medicine. We propose a new classification method based on a model where the data is marginally negative binomial but dependent, thereby incorporating the dependence known to be present between measurements from different genes. The method, called qtQDA, works by first performing a quantile transformation (qt) then applying Gaussian quadratic discriminant analysis (QDA) using regularized covariance matrix estimates. We show that qtQDA has excellent performance when applied to real data sets and has advantages over some existing approaches. An R package implementing the method is also available on https://github.com/goknurginer/qtQDA.
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    Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Relative Behavior of a Coherent System With Respect To Another Coherent System
    (Springer, 2015) Eryılmaz, Serkan; Tütüncü, Gözde Yazgı
    In this paper, two independent coherent systems with different structures, and different types of components are considered. The remaining lifetime and the remaining number of working components of system I after the failure of the system II when we know that the system II fails before the system I are studied. In particular, signature-based expressions are obtained for the distribution of these conditional random variables. Illustrative examples are provided.
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    Doctoral Thesis
    A New Rna-Seq Data Classifier Based on Quantile Transformation
    (İzmir Ekonomi Üniversitesi, 2020) Koçhan, Necla; Aşçı, Gözde Yazgı Tütüncü
    Son zamanlarda kanser araştırmalarında, bilinen bir kanser tipi olan bir hastanın o kanserin çeşidine göre doğru sınıflandırılması o hasta için daha iyi tahminlere dayanan ve kişiye özel tedavi sağlamaktadır. Bu nedenle, hastanın kanser çeşidine göre sınıflandırılması çok önemlidir ve bu, genetik bilgi kullanılarak yapılabilinmektedir. Mevcut sınıflandırıcıların çoğu genlerin bağımsız olduğu varsayımına dayanmaktadır; ancak, bu varsayım asıl RNA-Sekans sınıflandırma problemleri için gerçekçi bir yaklaşım değildir. Bu nedenle, bu tezde, genler arasındaki bağımlılık yapısını dikkate alan yeni bir sınıflandırıcı önerilmektedir. Genler arasındaki bağımlılık önce kovaryans matrisi ve daha sonra lokal kovaryans matrisi ile modellenmektedir. Lokal kovaryans matrisi, lokal bağımlılık fonksiyonu kullanılarak tahmin edilmektedir. Sınıflama algoritması R programlama dilinde kodlanmış olup RNA-Sekans verileri için yeni bir sınıflama paketi geliştirilmiştir. Yeni sınıflandırıcının performansı, gerçek RNA-Sekans verileri kullanılarak mevcut sınıflandırıcılar ile sınıflandırma hataları açısından karşılaştırılmıştır.