Eroğlu, Deniz
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Deniz, Eroglu
Eroglu,D.
Eroğlu, DENIZ
DENIZ EROĞLU
Eroglu, Deniz
Eroglu D.
EROĞLU, DENIZ
Eroğlu,D.
Deniz EROĞLU
Eroğlu, D.
Eroğlu, Deniz
Deniz Eroğlu
E., Deniz
EROĞLU, Deniz
E.,Deniz
D. Eroğlu
Eroglu,Deniz
Eroğlu, Deniz
Eroglu,D.
Eroğlu, DENIZ
DENIZ EROĞLU
Eroglu, Deniz
Eroglu D.
EROĞLU, DENIZ
Eroğlu,D.
Deniz EROĞLU
Eroğlu, D.
Eroğlu, Deniz
Deniz Eroğlu
E., Deniz
EROĞLU, Deniz
E.,Deniz
D. Eroğlu
Eroglu,Deniz
Eroğlu, Deniz
Job Title
Dr. Öğr. Üyesi
Email Address
Main Affiliation
Molecular Biology and Genetics
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
3
GOOD HEALTH AND WELL-BEING
2
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
3
Research Products
13
CLIMATE ACTION
1
Research Products
14
LIFE BELOW WATER
1
Research Products
17
PARTNERSHIPS FOR THE GOALS
1
Research Products
Documents
36
Citations
715
h-index
16
This researcher does not have a WoS ID.
Scholarly Output
26
Articles
20
Views / Downloads
207/1907
Supervised MSc Theses
3
Supervised PhD Theses
3
WoS Citation Count
181
Scopus Citation Count
205
WoS h-index
8
Scopus h-index
8
Patents
0
Projects
0
WoS Citations per Publication
6.96
Scopus Citations per Publication
7.88
Open Access Source
19
Supervised Theses
6
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| Journal | Count |
|---|---|
| Physical Review Research | 2 |
| Physical Review X | 2 |
| Earth Surface Processes and Landforms | 1 |
| Entropy | 1 |
| European Physical Journal-Special Topics | 1 |
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Now showing 1 - 10 of 26
Article Citation - WoS: 26Citation - Scopus: 26Network Structural Origin of Instabilities in Large Complex Systems(Amer Assoc Advancement Science, 2022) Duan, Chao; Nishikawa, Takashi; Eroglu, Deniz; Motter, Adilson E.A central issue in the study of large complex network systems, such as power grids, financial networks, and ecological systems, is to understand their response to dynamical perturbations. Recent studies recognize that many real networks show nonnormality and that nonnormality can give rise to reactivity-the capacity of a linearly stable system to amplify its response to perturbations, oftentimes exciting nonlinear instabilities. Here, we identify network structural properties underlying the pervasiveness of nonnormality and reactivity in real directed networks, which we establish using the most extensive dataset of such networks studied in this context to date. The identified properties are imbalances between incoming and outgoing network links and paths at each node. On the basis of this characterization, we develop a theory that quantitatively predicts nonnormality and reactivity and explains the observed pervasiveness. We suggest that these results can be used to design, upgrade, control, and manage networks to avoid or promote network instabilities.Article Citation - WoS: 4Citation - Scopus: 7Collective dynamics of random Janus oscillator networks(AMER PHYSICAL SOC, 2020) Peron, Thomas; Eroğlu, Deniz; Rodrigues, Francisco A.; Moreno, YamirJanus oscillators have been recently introduced as a remarkably simple phase oscillator model that exhibits nontrivial dynamical patterns-such as chimeras, explosive transitions, and asymmetry-induced synchronization-that were once observed only in specifically tailored models. Here we study ensembles of Janus oscillators coupled on large homogeneous and heterogeneous networks. By virtue of the Ott-Antonsen reduction scheme, we find that the rich dynamics of Janus oscillators persists in the thermodynamic limit of random regular, Erdos-Renyi, and scale-free random networks. We uncover for all these networks the coexistence between partially synchronized states and a multitude of solutions of a collective state we denominate as a breathing standing wave, which displays global oscillations. Furthermore, abrupt transitions of the global and local order parameters are observed for all topologies considered. Interestingly, only for scale-free networks, it is found that states displaying global oscillations vanish in the thermodynamic limit.Article Citation - WoS: 3Citation - Scopus: 4First-Principle Validation of Fourier's Law in D=1, 2, 3 Classical Systems(Elsevier, 2023) Tsallis, Constantino; Lima, Henrique Santos; Tirnakli, Ugur; Eroglu, DenizWe numerically study the thermal transport in the classical inertial nearest-neighbor XY ferromagnet in d = 1, 2, 3, the total number of sites being given by N = Ld, where L is the linear size of the system. For the thermal conductance sigma, we obtain sigma(T, L)L delta(d)= A(d) e-B(d) [L gamma (d)T ]eta(d) (with ez q(d) q equivalent to [1+(1-q)z]1/(1-q); ez1 = ez; A(d) > 0; B(d) > 0; q(d) > 1; eta(d) > 2; delta >= 0; gamma(d) > 0), for all values of L gamma(d)T for d = 1, 2, 3. In the L -> infinity limit, we have sigma proportional to 1/L rho sigma(d) with rho sigma(d) = delta(d)+gamma(d)eta(d)/[q(d)-1]. The material conductivity is given by kappa = sigma Ld proportional to 1/L rho kappa(d) (L -> infinity) with rho kappa(d) = rho sigma(d) - d. Our numerical results are consistent with 'conspiratory' d-dependences of (q, eta, delta, gamma), which comply with normal thermal conductivity (Fourier law) for all dimensions.(c) 2023 Published by Elsevier B.V.Article Citation - Scopus: 7Collective Dynamics of Random Janus Oscillator Networks(American Physical Society, 2020) Peron,T.; Eroglu,D.; Rodrigues,F.A.; Moreno,Y.Janus oscillators have been recently introduced as a remarkably simple phase oscillator model that exhibits nontrivial dynamical patterns-such as chimeras, explosive transitions, and asymmetry-induced synchronization-that were once observed only in specifically tailored models. Here we study ensembles of Janus oscillators coupled on large homogeneous and heterogeneous networks. By virtue of the Ott-Antonsen reduction scheme, we find that the rich dynamics of Janus oscillators persists in the thermodynamic limit of random regular, Erdos-Rényi, and scale-free random networks. We uncover for all these networks the coexistence between partially synchronized states and a multitude of solutions of a collective state we denominate as a breathing standing wave, which displays global oscillations. Furthermore, abrupt transitions of the global and local order parameters are observed for all topologies considered. Interestingly, only for scale-free networks, it is found that states displaying global oscillations vanish in the thermodynamic limit. © 2020 authors. Published by the American Physical Society.Article Citation - WoS: 18Citation - Scopus: 20Recurrence analysis of extreme event-like data(COPERNICUS GESELLSCHAFT MBH, 2021) Banerjee, Abhirup; Goswami, Bedartha; Hirata, Yoshito; Eroğlu, Deniz; Merz, Bruno; Kurths, Juergen; Marwan, NorbertThe identification of recurrences at various time-scales in extreme event-like time series is challenging because of the rare occurrence of events which are separated by large temporal gaps. Most of the existing time series analysis techniques cannot be used to analyze an extreme event-like time series in its unaltered form. The study of the system dynamics by reconstruction of the phase space using the standard delay embedding method is not directly applicable to event-like time series as it assumes a Euclidean notion of distance between states in the phase space. The edit distance method is a novel approach that uses the point-process nature of events. We propose a modification of edit distance to analyze the dynamics of extreme event-like time series by incorporating a nonlinear function which takes into account the sparse distribution of extreme events and utilizes the physical significance of their temporal pattern. We apply the modified edit distance method to event-like data generated from point process as well as flood event series constructed from discharge data of the Mississippi River in the USA and compute their recurrence plots. From the recurrence analysis, we are able to quantify the deterministic properties of extreme event-like data. We also show that there is a significant serial dependency in the flood time series by using the random shuffle surrogate method.Article Citation - WoS: 6Citation - Scopus: 6Transformation Cost Spectrum for Irregularly Sampled Time Series(Springer Heidelberg, 2023) Ozdes, Celik; Eroglu, DenizIrregularly sampled time series analysis is a common problem in various disciplines. Since conventional methods are not directly applicable to irregularly sampled time series, a common interpolation approach is used; however, this causes data distortion and consequently biases further analyses. We propose a method that yields a regularly sampled time series spectrum of costs with minimum information loss. Each time series in this spectrum is a stationary series and acts as a difference filter. The transformation costs approach derives the differences between consecutive and arbitrarily sized segments. After obtaining regular sampling, recurrence plot analysis is performed to distinguish regime transitions. The approach is applied to a prototypical model to validate its performance and to different palaeoclimate proxy data sets located around Africa to identify critical climate transition periods during the last 5 million years and their characteristic properties.Article Data-Driven Modeling of Traffic Flow in Macroscopic Network Systems(AIP Publishing, 2025) Firat, Toprak; Eroglu, DenizUrban traffic modeling is essential for understanding and mitigating congestion, yet existing approaches face a trade-off between realism and scalability. Microscopic agent-based simulators capture individual vehicle behavior but are computationally intensive and hard to calibrate at scale. Macroscopic models, while more efficient, often rely on strong assumptions, such as fixed origin-destination flows, or oversimplify network dynamics. In this work, we propose a data-driven macroscopic model that simulates traffic as a discrete-time load-exchange process over flow networks. The model captures key phenomena such as bottlenecks, spillbacks, and adaptive load redistribution using only road-type attributes, network structure, and observed traffic density. Parameter learning is performed via evolutionary optimization, allowing the model to adapt to both synthetic and real-world conditions without assuming latent travel demand. We evaluate the framework on synthetic grid-like networks and on real traffic data from London, Istanbul, and New York. The resulting framework provides a scalable and interpretable alternative for urban traffic forecasting, balancing predictive accuracy with computational efficiency across diverse network conditions.Doctoral Thesis Paleoiklim Ağları: Oluşturulma ve Analiz(2025) Özdeş, Mehmet Çelik; Eroğlu, DenizDünya'nın iklimi, farklı ölçeklerde ve doğrusal olmayan etkileşimlerle karakterize edilen, karmaşık bir sistemdir ve küçük değişikliklerin ani rejim değişiklikleri veya dönüm noktaları gibi orantısız ve öngörülemez sonuçlara yol açabilmesi nedeniyle uzun vadeli tahmini zordur. İklimin geçmişindeki kritik geçişleri araştırmak son derece önemlidir çünkü bu tür ani, büyük ölçekli değişiklikler toplumlar ve doğal ekosistemler için derin ve geri döndürülemez sonuçlara sebep olabilir. Bu durum, olası felaket etkilerini hafifletmek için erken uyarı göstergelerinin ve adaptasyon stratejilerin geliştirilmesini gerekli kılar. Paleoiklim çalışmaları, ölçüm olarak düzen- siz aralıklı zaman serileri üreten, çeşitli fiziksel biçimlerde korunan vekil kayıtları kullanmaktadır. Bu tezde, düzensiz seriler için düzenli aralıklı temsilci serilerinden oluşan ve bir baz olarak işlev görecek, genişletilmiş bir analitik araç (Dönüşüm Maliyeti Spektrumu) geliştiril- miştir. Bu yaklaşım, birden fazla vekil ölçümünden gelen bilgiyi değerlendirmek için ortak bir zaman çizelgesinin oluşturulmasına olanak tanır ve verilerde gizli dinamik desenler hakkında spektral bilgi sağlar. Ardından, uzamsal vekil bilgileri aracılığıyla iklim rejimi değişikliklerini araştırmak için yöntem- sel bir çerçeve öneriyorum. İklim sistemindeki uzak-bağlantıları taklit eden veri odaklı kavramsal birimler (İşlevsel Etkileşim Ağları) kullanılarak çevre dinamiklerinin kaba bir tarifi yapılabilir. Bunların çevresel dinamik koşulları için yorumlanabilir ve temsili vekiller olduğunu ve geçiş yapılarının da sistemin davranışını karakterize edebilecek, sistemin yapısal kısıt- larının doğasını ortaya çıkarabilecek olduğunu gösteriyorum. Yöntemlerimi sentetik ve gerçek sistemlerde doğruladıktan sonra, önemli geçişlerin karakteristik özelliklerini ortaya çıkarmak için iklim tarihindeki iki dönemi analiz ediyorum. Bu bulgular, iklim sisteminin durumunu yorumlama ve kritik geçişlerini tahmin etme becerimize katkıda bulunmaktadır.Doctoral Thesis Fizik Tabanlı Elektrik Şebekesi Yeniden İnşası: Karmaşık Sistemler Perspektifi(2025) Rezaeinazhad, Arash Mohammadian; Eroğlu, DenizEnerji, modern yas¸amın tum y ¨ onlerini beslerken, elektrik s¸ebekesi bu sistemin temel ¨ altyapısını olus¸turur. Ancak bu s¸ebeke, buy¨ uk¨ olc¸ekli, do ¨ grusal olmayan ve mek ˘ ana ˆ gom¨ ul¨ u yapısıyla insan eliyle yapılmıs¸ en karmas¸ık sistemlerden biridir. K ¨ uc¸¨ uk bir bozul- ¨ ma bile ardıs¸ık arızaları tetikleyerek genis¸ c¸aplı elektrik kesintilerine ve toplumsal etkilere yol ac¸abilir. Gunes¸ ve r ¨ uzg ¨ ar gibi yenilenebilir kaynaklara gec¸is¸in hızlanmasıyla birlikte, ˆ s¸ebeke degis¸kenlik ve merkezsiz ˘ uretim gibi yeni zorluklarla kars¸ı kars¸ıyadır. Bu nedenle, ¨ s¸ebekenin kararlılıgını ve dayanıklılı ˘ gını sa ˘ glamak hem bilimsel bir zorunluluk hem de ˘ pratik bir ihtiyac¸ haline gelmis¸tir. ˆ Bu tez, karmas¸ık sistemler bakıs¸ ac¸ısıyla tasarlanmıs¸ ac¸ık kaynaklı bir yazılım hattı sunar. Bu hat, ac¸ık eris¸imli cografi verileri kullanarak y ˘ uksek gerilimli iletim a ¨ gı modelleri ˘ olus¸turmayı mumk ¨ un kılar. Y ¨ ontem genel olarak uygulanabilir olsa da, detaylı bir ¨ ornek ¨ c¸alıs¸ma olarak Turkiye elektrik iletim s¸ebekesi ele alınmıs¸tır. Ac¸ık eris¸imli, fiziksel olarak ¨ detaylı s¸ebeke modellerinin azlıgını gidermek amacıyla, OpenStreetMap verileri is¸lenerek ˘ MATLAB MATPOWER ile uyumlu modeller uretilmis¸tir. Ortaya c¸ıkan veri seti; hat ¨ empedansları, termal sınırlar ve yuk da ¨ gılımları gibi temel elektriksel parametreleri ic¸erir. ˘ Bu parametreler muhendislik tahminleriyle elde edilip g ¨ uc¸ akıs¸ı ac¸ısından do ¨ grulanmıs¸tır. ˘ ˙Iki ornek c¸alıs¸ma, yazılım aracının ve olus¸turulan veri setinin yararlılı ¨ gını g ˘ ostermektedir. ¨ ˙Ilk c¸alıs¸ma, senkronizasyon kararlılıgını, kararsızlı ˘ gın erken uyarı sinyallerini tespit et- ˘ mek ic¸in stokastik perturbasyon analizi kullanarak incelemektedir. ¨ ˙Ikinci c¸alıs¸ma ise termal as¸ırı yuklenmelere ba ¨ glı ardıs¸ık arızaları aras¸tırmakta, kırılgan iletim hatlarını belir- ˘ lemekte ve dayanıklılıgı artırmak ic¸in hedefe y ˘ onelik g ¨ uc¸lendirme ¨ onerileri sunmaktadır. ¨ Bu ornekler, elektrik s¸ebekesi dinamiklerini modellemede fiziksel ve yapısal gerc¸ekc¸ili ¨ gin ˘ onemini vurgulamaktadır. ¨ Bu c¸alıs¸maların otesinde, veri seti ve yazılım aracı, g ¨ uc¸ sistemi modellemesi ic¸in ¨ olc¸ekle- ¨ nebilir ve tekrarlanabilir bir c¸erc¸eve sunmaktadır. Yenilenebilir entegrasyonu, genis¸leme planlaması, dayanıklılık analizi ve gerc¸ek zamanlı izleme gibi uygulamaları desteklemektedir. Hem arac¸ların hem de verilerin kamuya ac¸ık hale getirilmesiyle, bu tez modern enerji altyapısının kararlılıgı ve s ˘ urd ¨ ur¨ ulebilirli ¨ gi˘ uzerine veri odaklı, disiplinlerarası ¨ aras¸tırmalara katkı saglamaktadır. ˘ Anahtar Sozcükler: Elektrik S¸ ebekesi Altyapısı, OpenStreetMap Veri Entegrasyonu, Karmas¸ık Sistemler Analizi, Senkronizasyon, KararlılıkArticle Forecasting Critical Economic & Political Events Via Electricity Consumption Patterns in the United States of America and Turkey(Springernature, 2025) Ozdes, Celik; Ediger, Volkan S.; Eroglu, DenizImpacts from natural disasters, government decisions and public's reactions can significantly alter societal daily routines. These effects resonate in systems where individual contributions, such as energy consumption, serve as indirect indicators of societal welfare and living standards. Preparedness for unforeseen events is crucial to enhancing societal well-being. Thus, analysing historical data for unexpected critical transitions and forecasting future occurrences is paramount. Recurrence properties of gross monthly electricity consumption in the United States of America and Turkey are examined, revealing coinciding critical periods with extreme regimes identified by a determinism time series. An ensemble of neural network proxies is then employed to forecast critical periods within a limited time frame, enabling the anticipation of similar occurrences. Validation of this approach demonstrates high predictive performance when measured quantities adequately reflect underlying system dynamics. Predictions based on electricity consumption data suggest potential systemic and socioeconomic crises for both nations within one year, with probabilities, 85% for the US and 32% for Turkey.
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