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
11
SUSTAINABLE CITIES AND COMMUNITIES
3
Research Products
17
PARTNERSHIPS FOR THE GOALS
1
Research Products
14
LIFE BELOW WATER
1
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
15
LIFE ON LAND
0
Research Products
1
NO POVERTY
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
3
GOOD HEALTH AND WELL-BEING
2
Research Products
2
ZERO HUNGER
0
Research Products
4
QUALITY EDUCATION
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
13
CLIMATE ACTION
1
Research Products
5
GENDER EQUALITY
0
Research Products
Documents
36
Citations
731
h-index
16
This researcher does not have a WoS ID.
Scholarly Output
27
Articles
21
Views / Downloads
262/2283
Supervised MSc Theses
3
Supervised PhD Theses
3
WoS Citation Count
201
Scopus Citation Count
219
WoS h-index
8
Scopus h-index
8
Patents
0
Projects
0
WoS Citations per Publication
7.44
Scopus Citations per Publication
8.11
Open Access Source
20
Supervised Theses
6
| Journal | Count |
|---|---|
| Physical Review Research | 2 |
| Physical Review X | 2 |
| Earth Surface Processes and Landforms | 1 |
| Entropy | 1 |
| European Physical Journal-Special Topics | 1 |
Current Page: 1 / 4
Scopus Quartile Distribution
Competency Cloud
27 results
Scholarly Output Search Results
Now showing 1 - 10 of 27
Article Citation - WoS: 1Citation - Scopus: 1Cycle-Star Motifs: Network Response To Link Modifications(Springer, 2024) Bakrani, Sajjad; Kiran, Narcicegi; Eroglu, Deniz; Pereira, TiagoUnderstanding efficient modifications to improve network functionality is a fundamental problem of scientific and industrial interest. We study the response of network dynamics against link modifications on a weakly connected directed graph consisting of two strongly connected components: an undirected star and an undirected cycle. We assume that there are directed edges starting from the cycle and ending at the star (master-slave formalism). We modify the graph by adding directed edges of arbitrarily large weights starting from the star and ending at the cycle (opposite direction of the cutset). We provide criteria (based on the sizes of the star and cycle, the coupling structure, and the weights of cutset and modification edges) that determine how the modification affects the spectral gap of the Laplacian matrix. We apply our approach to understand the modifications that either enhance or hinder synchronization in networks of chaotic Lorenz systems as well as R & ouml;ssler. Our results show that the hindrance of collective dynamics due to link additions is not atypical as previously anticipated by modification analysis and thus allows for better control of collective properties.Article Citation - WoS: 19Citation - 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 Citation - WoS: 11Citation - Scopus: 13Holocene Climate Forcings and Lacustrine Regime Shifts in the Indian Summer Monsoon Realm(Wıley, 2020) Prasad, Sushma; Marwan, Norbert; Eroğlu, Deniz; Goswami, Bedartha; Mishra, Praveen Kuma; Gaye, Birgit; Anoop, Akhil; Stebich, Martina; Jehangir, Arshid; Basavaiah, NathaniExtreme climate events have been identified both in meteorological and long-term proxy records from the Indian summer monsoon (ISM) realm. However, the potential of palaeoclimate data for understanding mechanisms triggering climate extremes over long time scales has not been fully exploited. A distinction between proxies indicating climate change, environment, and ecosystem shift is crucial for enabling a comparison with forcing mechanisms (e.g. El-Nino Southern Oscillation). In this study we decouple these factors using data analysis techniques [multiplex recurrence network (MRN) and principal component analyses (PCA)] on multiproxy data from two lakes located in different climate regions - Lonar Lake (ISM dominated) and the high-altitude Tso Moriri Lake (ISM and westerlies influenced). Our results indicate that (i) MRN analysis, an indicator of changing environmental conditions, is associated with droughts in regions with a single climate driver but provides ambiguous results in regions with multiple climate/environmental drivers; (ii) the lacustrine ecosystem was 'less sensitive' to forcings during the early Holocene wetter periods; (iii) archives in climate zones with a single climate driver were most sensitive to regime shifts; (iv) data analyses are successful in identifying the timing of onset of climate change, and distinguishing between extrinsic and intrinsic (lacustrine) regime shifts by comparison with forcing mechanisms. Our results enable development of conceptual models to explain links between forcings and regional climate change that can be tested in climate models to provide an improved understanding of the ISM dynamics and their impact on ecosystems. (c) 2020 John Wiley & Sons, Ltd.Master Thesis Generalized Synchronization: Master-Slave Relationship in Three Coupled Systems(Kadir Has Üniversitesi, 2022) Doğan, Gizem; Eroglu, DenizSynchronization is an important phenomenon for complex, biological, and physical systems such as the brain, i.e., Parkinson’s disease, heart beating, hand-clapping, power grids, lasers, and many others. Intuitively, we can express synchronization as strong correlations between coupled systems. We can state two scenarios in this manner. One is synchronization between identical systems, which is called complete synchronization; the other is the synchronization between the non-identical systems, called generalized synchronization. In this thesis, initially, we considered the two coupled systems and calculated the critical coupling value for the generalized synchronization analytically. More precisely, the Lorenz system drives two R¨ossler systems. We investigated the critical coupling value for synchronization numerically. However, real-world examples are much more complex. The most straightforward case was the two coupled systems for the generalized synchronization, and next, we focus on three coupled systems. In particular, suppose that we have three coupled one Lorenz and two R¨ossler systems. In our example, the Lorenz system drives the first R¨ossler system, and first R¨ossler system drives the second R¨ossler system, and finally, the second R¨ossler system also drives the Lorenz system. We calculated the critical coupling of the whole system for generalized synchronization and analyzed the time series for each system.Article Citation - WoS: 27Citation - Scopus: 26Emergent hypernetworks in weakly coupled oscillators(Nature Portfolio, 2022) Nijholt, Eddie; Ocampo-Espindola, Jorge Luis; Eroglu, Deniz; Kiss, Istvan Z.; Pereira, TiagoNetworks of weakly coupled oscillators had a profound impact on our understanding of complex systems. Studies on model reconstruction from data have shown prevalent contributions from hypernetworks with triplet and higher interactions among oscillators, in spite that such models were originally defined as oscillator networks with pairwise interactions. Here, we show that hypernetworks can spontaneously emerge even in the presence of pairwise albeit nonlinear coupling given certain triplet frequency resonance conditions. The results are demonstrated in experiments with electrochemical oscillators and in simulations with integrate-and-fire neurons. By developing a comprehensive theory, we uncover the mechanism for emergent hypernetworks by identifying appearing and forbidden frequency resonant conditions. Furthermore, it is shown that microscopic linear (difference) coupling among units results in coupled mean fields, which have sufficient nonlinearity to facilitate hypernetworks. Our findings shed light on the apparent abundance of hypernetworks and provide a constructive way to predict and engineer their emergence.Master Thesis Makroskopik Ağ Sistemlerinde Veri Odaklı Trafik Akışı Modellemesi(2025) Fırat, Toprak; Eroğlu, DenizKentsel trafik sıkışıklığı, günümüz şehirleri için süregelen, karmaşık ve yüksek maliyetli bir problemdir. Artan seyahat süreleri, çevresel bozulma, enerji israfı ve ekonomik kayıplar bu problemin doğrudan sonuçları arasında yer almaktadır. Bu sorunlarla etkili şekilde başa çıkabilmek yalnızca altyapı yatırımlarıyla değil; aynı zamanda ulaşım politikaları, trafik yönetimi ve kontrol sistemlerinin bilimsel temellerle tasarlanmasıyla mümkündür. Bu kapsamda, trafiğin zaman ve mekân içinde nasıl evrildiğine dair sistematik ve ölçeklenebilir bir anlayış geliştirmek kritik önem taşır. Gerçek dünyada yapılacak deneyler genellikle maliyetli, zaman alıcı ve bozucudur. Bu nedenle, kentsel trafik sistemlerinin modellenmesi; alternatif senaryoların test edilmesi, politika etkilerinin değerlendirilmesi ve uzun vadeli sonuçların öngörülebilmesi açısından vazgeçilmez bir araçtır. Bununla birlikte, mevcut trafik modelleme yaklaşımları önemli sınırlılıklar taşır. Mikroskobik modeller bireysel araç davranışlarını yüksek ayrıntıyla temsil etse de, büyük ağlarda hesaplama açısından verimsizdir ve yoğun kalibrasyon verisi gerektirir. Makroskobik modeller ise daha hesaplıdır; ancak sabit başlangıç-varış (OD) akışları, homojen yol davranışları ve sürekli akış varsayımları gibi sadeleştirici kabuller içerir. Bu da onları karmaşık ve heterojen şehir yapıları için yetersiz kılar. Bu tez, trafik akışını yönlü bir ağda ayrık zamanlı yük alışverişiyle temsil eden veri odaklı bir makroskobik model önermektedir. Yol türlerine özgü akış dinamikleri, ağ topolojisi ve gözlemlenen trafik yoğunlukları modele entegre edilerek darboğazlar, geri tepme ve yük yeniden dağılımı gibi olgular temsil edilmektedir. Model parametreleri, evrimsel optimizasyon yoluyla, örtük talep varsayımı olmadan veriden öğrenilmektedir. Model, klasik Hücresel İletim Modeli (CTM) ile karşılaştırılmış; SUMO simülasyonları ve İstanbul, Londra ile New York verileri üzerinde üstünlük göstermiştir.Article Citation - WoS: 8Citation - Scopus: 8Sampling Rate-Corrected Analysis of Irregularly Sampled Time Series(Amer Physical Soc, 2022) Braun, Tobias; Fernandez, Cinthya N.; Eroglu, Deniz; Hartland, Adam; Breitenbach, Sebastian F. M.; Marwan, NorbertThe analysis of irregularly sampled time series remains a challenging task requiring methods that account for continuous and abrupt changes of sampling resolution without introducing additional biases. The edit distance is an effective metric to quantitatively compare time series segments of unequal length by computing the cost of transforming one segment into the other. We show that transformation costs generally exhibit a nontrivial relationship with local sampling rate. If the sampling resolution undergoes strong variations, this effect impedes unbiased comparison between different time episodes. We study the impact of this effect on recurrence quantification analysis, a framework that is well suited for identifying regime shifts in nonlinear time series. A constrained randomization approach is put forward to correct for the biased recurrence quantification measures. This strategy involves the generation of a type of time series and time axis surrogates which we call sampling-rate-constrained (SRC) surrogates. We demonstrate the effectiveness of the proposed approach with a synthetic example and an irregularly sampled speleothem proxy record from Niue island in the central tropical Pacific. Application of the proposed correction scheme identifies a spurious transition that is solely imposed by an abrupt shift in sampling rate and uncovers periods of reduced seasonal rainfall predictability associated with enhanced El Nino-Southern Oscillation and tropical cyclone activity.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 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.
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