Papers by Muzaffer Ege Alper
Folksonomies constitute an important type of Web 2.0 services, where users collectively annotate ... more Folksonomies constitute an important type of Web 2.0 services, where users collectively annotate (or "tag") resources to create custom categories. Semantic relation of these categories hint at the possibility of another categorization at a higher level. Discovering these more general categories, called "topics", is an important task. One problem is to discover these semantically coherent topics and the accompanying small sets of tags that cover these topics in order to facilitate more detailed item search. Another important problem is to find words/phrases that describe these topics, i.e. labels or "meta-tag"s. These labeled topics can immensely increase the item search efficiency of users in a folksonomy service. However, this possibility has not been sufficiently exploited to date. In this paper, a probabilistic model is used to identify topics in a folksonomy, which are then associated with relevant, descriptive meta-tags. In addition, a small set of diverse and relevant tags are found which cover the semantics of the topic well. The resulting topics form a personalized categorization of folksonomy data due to the personalized nature of the model employed. The results show that the proposed method is successful at discovering important topics and the corresponding identifying meta-tags.
Atmospheric Chemistry and Physics, Apr 7, 2022
The number of cloud droplets formed at the cloud base depends on both the properties of aerosol p... more The number of cloud droplets formed at the cloud base depends on both the properties of aerosol particles and the updraft velocity of an air parcel at the cloud base. As the spatial scale of updrafts is too small to be resolved in global atmospheric models, the updraft velocity is commonly parameterised based on the available turbulent kinetic energy. Here we present alternative methods through parameterising updraft velocity based on high-resolution large-eddy simulation (LES) runs in the case of marine stratocumulus clouds. First we use our simulations to assess the accuracy of a simple linear parameterisation where the updraft velocity depends only on cloud top radiative cooling. In addition, we present two different machine learning methods (Gaussian process emulation and random forest) that account for different boundary layer conditions and cloud properties. We conclude that both machine learning parameterisations reproduce the LES-based updraft velocities at about the same accuracy, while the simple approach employing radiative cooling only produces on average lower coefficient of determination and higher root mean square error values. Finally, we apply these machine learning methods to find the key parameters affecting cloud base updraft velocities.
Technical note: Emulation of a large-eddy simulator for stratocumulus clouds in a general circulation model
. Here we present for the first time a proof of concept for an emulation-based method that uses a... more . Here we present for the first time a proof of concept for an emulation-based method that uses a large-eddy simulations (LES) to present sub-grid cloud processes in a general circulation model (GCM). We focus on two key variables affecting the properties of shallow marine clouds: updraft velocity and precipitation formation. The LES is able to describe these processes with high resolution accounting for the realistic variability in cloud properties. We show that the selected emulation method is 5 able to represent the LES outcome with relatively good accuracy and that the updraft velocity and precipitation emulators can be coupled with the GCM practically without increasing the computational costs. We also show that the emulators influence the climate simulated by the GCM, but do not consistently improve or worsen the agreement with observations on cloud related properties. Although especially the updraft velocity at cloud base is better captured. A more quantitative evaluation of the emulator impacts against observations would, however, have required model re-tuning, which is a significant task and thus could 10 not be included in this proof-of-concept study. All in all, the approach introduced here is a promising candidate for representing detailed cloud and aerosol related sub-grid processes in GCMs. Further development work together with increasing computing capacity can be expected to improve the accuracy and the applicability of the approach in climate simulations.
Atmospheric Chemistry and Physics, Aug 9, 2019
Significant discrepancies remain in estimates of climate impacts of anthropogenic aerosols betwee... more Significant discrepancies remain in estimates of climate impacts of anthropogenic aerosols between different general circulation models (GCMs). Here, we demonstrate that eliminating differences in model aerosol or radiative forcing fields results in close agreement in simulated globally averaged temperature and precipitation responses in the studied GCMs. However, it does not erase the differences in regional responses. We carry out experiments of equilibrium climate response to modern day anthropogenic aerosols using an identical representation of anthropogenic aerosol optical properties and aerosol-cloud interactions, MACv2-SP, in two independent climate models (NorESM and ECHAM6). We find consistent global average temperature responses of −0.48(±0.02) K and −0.50(±0.03) K and precipitation responses of −1.69(±0.04)% and −1.79(±0.05)% in NorESM1 and ECHAM6, respectively, compared to modern-day equilibrium climate without anthropogenic aerosols. However, significant differences remain between the two GCMs regional temperature responses around the Arctic circle and the equator and precipitation responses in the tropics. The scatter in the simulated globally averaged responses is small in magnitude when compared against literature data from modern GCMs using model intrinsic aerosols but same aerosol emissions (−(0.5-1.1) K and −(1.5-3.1)% for temperature and precipitation, respectively). The Pearson correlation of regional temperature (precipitation) response in these literature model experiments with intrinsic aerosols is 0.79 (0.34). The corresponding correlation coefficients for NorESM1 and ECHAM6 runs with identical aerosols are 0.78 (0.41). The lack of improvement in correlation coefficients between models with identical aerosols and models with intrinsic aerosols implies that the spatial distribution of regional climate responses is not improved via homogenizing the aerosol descriptions in the models. Rather, differences in the atmospheric dynamic and high latitude cloud and snow/sea ice cover responses dominate the differences in regional climate responses. Hence, further improvements in the model aerosol descriptions can be expected to have a limited value in improving our understanding of regional aerosol climate impacts, unless the dynamical cores of the climate models are improved as well.
The Impact of Meteorological Conditions and Aerosol Concentrations on Shallow Marine Clouds
AGU Fall Meeting Abstracts, Dec 1, 2018
Modeling and prediction of student success is a critical task in education. In this paper, we emp... more Modeling and prediction of student success is a critical task in education. In this paper, we employ machine learning methods to predict course grade performance of Computer Engineering students. As features, in addition to the conventional course grades we use fine grained student performance measurements corresponding to different goals (ABET outcomes) of a course. We observe that, compared to using only previous course grades, addition of outcome grades can significantly improve the prediction results. Using the trained model enables interpretation of how different courses affect performance on a specific course in the future. We think that even more detailed and systematically produced course outcome measurements can be beneficial in modeling students university performance.
Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (M.Sc.) ... more Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2011Günümüzde bilgisayar grafik teknolojileri giderek yaygınlaşmaktadıtır. Bu teknolojiler üretimden, eğlenceye ve sağlığa kadar farklı alanlarda uygulama olanağı bulmuşlardır. Ancak giderek çoğalan veri sayısı, bu verilerin etkin kodlanmasını zorunlu kılmaktadır. Bilgisayar grafiği teknolojileri arasında çokgen tabanlı, 3 boyutlu yüzey modelleri, matematiksel basitlikleri ve temsil kolaylığı gibi nedenlerle en sık kullanılan araçlardandır. 3 Boyutlu bilgisayar grafikleri teknolojileri sayesinde bir nesnenin birden fazla bak{\i}\c{s} a\c{c}{\i}s{\i} alt{\i}nda g\ or\ ulebilmesi m\ umk\ un olmu\c{s}tur. Herhangi bir veri sıkıştırma yöntemi, verideki istatistiksel ilişkileri ve izleyicinin görsel algılama özelliklerini değerlendirmelidir. Günümüzde veri sıkıştırmanın istatistiksel doğası oldukça iyi anlaşılmış durumdadı...
JaakkoAhola/LES-emulator-02postpros: v2.1
The effects of meteorological conditions, aerosol concentrations and microphysics on shallow marine clouds
EGU General Assembly Conference Abstracts, Apr 1, 2019
DESIGN: SALSA daytime 150 simulations
SALSA daytime design with 150 points Originally released Jun 6, 2019
Publication in the conference proceedings of EUSIPCO, Marrakech, Morocco, 2013
3 Boyutlu Sahnelerin Bakış Noktasına Bağımlı Kodlanması
Scientific Reports, 2017
Using reports of forest losses caused directly by large scale windstorms (or primary damage, PD) ... more Using reports of forest losses caused directly by large scale windstorms (or primary damage, PD) from the European forest institute database (comprising 276 PD reports from 1951–2010), total growing stock (TGS) statistics of European forests and the daily North Atlantic Oscillation (NAO) index, we identify a statistically significant change in storm intensity in Western, Central and Northern Europe (17 countries). Using the validated set of storms, we found that the year 1990 represents a change-point at which the average intensity of the most destructive storms indicated by PD/TGS > 0.08% increased by more than a factor of three. A likelihood ratio test provides strong evidence that the change-point represents a real shift in the statistical behaviour of the time series. All but one of the seven catastrophic storms (PD/TGS > 0.2%) occurred since 1990. Additionally, we detected a related decrease in September–November PD/TGS and an increase in December–February PD/TGS. Our ana...
View-dependent 3-D mesh coding by rate allocation with the image rendering-based distortion measures
Signal, Image and Video Processing, 2015
Low-bandwidth transmission of synthetic digital content to the end user device in the form of a s... more Low-bandwidth transmission of synthetic digital content to the end user device in the form of a scene of 3-D meshes requires efficient compression of the mesh geometry. For applications in which the meshes are observed from a single viewpoint, this work explores the use of the image rendering-based distortion measures in rate allocation to their surface regions for view-dependent mesh geometry compression. It is experimentally demonstrated that the image rendering-based distortion measures yield far superior performance (the quality of the rendered image of the reconstructed scene from a viewpoint at a given rate) in optimal rate allocation than other previously proposed distortion measures. A fast rate allocation method is also proposed for use with the image rendering-based measures for real-time or interactive applications. Not only does this method have significantly lower complexity than the optimal rate allocation method due to the rendering of the images of the reconstructed meshes at only judiciously selected rate–distortion operating points, but also its coding performance is just as competitive. Further complexity reduction in rate allocation, through rendering of only the coded regions of the meshes, is also investigated.
Proceedings of the 4th International Conference on Computer Supported Education, 2012
Modeling and prediction of student success is a critical task in education. In this paper, we emp... more Modeling and prediction of student success is a critical task in education. In this paper, we employ machine learning methods to predict course grade performance of Computer Engineering students. As features, in addition to the conventional course grades we use fine grained student performance measurements corresponding to different goals (ABET outcomes) of a course. We observe that, compared to using only previous course grades, addition of outcome grades can significantly improve the prediction results. Using the trained model enables interpretation of how different courses affect performance on a specific course in the future. We think that even more detailed and systematically produced course outcome measurements can be beneficial in modeling students university performance.
This paper presents the results of main part-of-speech tagging of Turkish sentences using Conditi... more This paper presents the results of main part-of-speech tagging of Turkish sentences using Conditional Random Fields (CRFs). Although CRFs are applied to many different languages for part-of-speech (POS) tagging, Turkish poses interesting challenges to be modeled with them. The challenges include issues related to the statistical model of the problem as well as issues related to computational complexity and scaling. In this paper, we propose a novel model for main-POS tagging in Turkish. Furthermore, we propose some approaches to reduce the computational complexity and allow better scaling characteristics or improve the performance without increased complexity. These approaches are discussed with respect to their advantages and disadvantages. We show that the best approach is competitive with the current state of the art in accuracy and also in training and test durations. The good results obtained imply a good first step towards full morphological disambiguation.
This thesis is made up of four main chapters. In the first two chapters, we review the literature... more This thesis is made up of four main chapters. In the first two chapters, we review the literature on inverse problems and Monte Carlo methods. We put special emphasis on the functional space approach, which fits naturally into our programme of working in high dimensional inverse problems. We also attempt to describe alternative methods and, if possible, their relations to our proposed methods. We use the groundwater-flow dynamics as a basis to construct several inverse problems, which are later used as examples for our proposed methods. The third chapter describes our novel adaptive sequential Monte Carlo method and its application to the groundwater-flow problem. Here, we observe significant time-savings compared to previous SMC approaches. We also observe, however, that this method is still too slow to be used in practice. Therefore, in chapter four, we turn our attention to multi-resolution (also known as multi-level) methods. We begin by discussing a classical example in the literature, we clearly demonstrates the (asymptotically) reduced error per unit computation. We then describe our implementation of this idea and show the match of experimental results to the predictions of asymptotic theory. We end the thesis with our conclusions and observations on the practical properties of the discussed methods. This thesis is mainly a practical one and hence does not contain any new theorems. However, it's important to know certain theorems to make sense of the resulting algorithms and get a sense of their behaviour. For that reason, we will state important ones when necessary but avoid giving the proofs. References to the proofs, of course, will be provided. Contents List of Figures viii List of Tables ix
Parameterising cloud base updraft velocity of marine stratocumuli
. The number of cloud droplets formed at the cloud base depends both on the properties of aerosol... more . The number of cloud droplets formed at the cloud base depends both on the properties of aerosol particles and the updraft velocity of an air parcel at the cloud base. As the spatial scale of updrafts is too small to be resolved in global atmospheric models, the updraft velocity is commonly parameterised based on the available turbulent kinetic energy. Here we present alternative methods through parameterising updraft velocity based on high-resolution large eddy simulation (LES) runs in the case of marine stratocumulus clouds. First we use our simulations to assess the accuracy of a simple linear parametrisation where the updraft velocity depends only on cloud top radiative cooling. In addition, we present two different machine learning methods (Gaussian process emulation and random forest) that account for different boundary layer conditions and cloud properties. We conclude that both machine learning parameterisations reproduce the LES-based updraft velocities at about the same accuracy, while the simple approach employing radiative cooling only produce on average lower coefficient of determination and higher root mean square error values. Finally, we apply these machine learning methods to find the key parameters affecting cloud base updraft velocities.
Atmospheric Chemistry and Physics Discussions
Significant discrepancies remain in estimates of climate impacts of anthropogenic aerosols betwee... more Significant discrepancies remain in estimates of climate impacts of anthropogenic aerosols between different general circulation models (GCMs). Here, we demonstrate that eliminating differences in model aerosol or radiative forcing fields results in close agreement in simulated globally averaged temperature and precipitation responses in the studied GCMs. However, it does not erase the differences in regional responses. We carry out experiments of equilibrium climate response to modern day anthropogenic aerosols using an identical representation of anthropogenic aerosol optical properties and aerosol-cloud interactions, MACv2-SP, in two independent climate models (NorESM and ECHAM6). We find consistent global average temperature responses of −0.48(±0.02) K and −0.50(±0.03) K and precipitation responses of −1.69(±0.04)% and −1.79(±0.05)% in NorESM1 and ECHAM6, respectively, compared to modern-day equilibrium climate without anthropogenic aerosols. However, significant differences remain between the two GCMs regional temperature responses around the Arctic circle and the equator and precipitation responses in the tropics. The scatter in the simulated globally averaged responses is small in magnitude when compared against literature data from modern GCMs using model intrinsic aerosols but same aerosol emissions (−(0.5-1.1) K and −(1.5-3.1)% for temperature and precipitation, respectively). The Pearson correlation of regional temperature (precipitation) response in these literature model experiments with intrinsic aerosols is 0.79 (0.34). The corresponding correlation coefficients for NorESM1 and ECHAM6 runs with identical aerosols are 0.78 (0.41). The lack of improvement in correlation coefficients between models with identical aerosols and models with intrinsic aerosols implies that the spatial distribution of regional climate responses is not improved via homogenizing the aerosol descriptions in the models. Rather, differences in the atmospheric dynamic and high latitude cloud and snow/sea ice cover responses dominate the differences in regional climate responses. Hence, further improvements in the model aerosol descriptions can be expected to have a limited value in improving our understanding of regional aerosol climate impacts, unless the dynamical cores of the climate models are improved as well.
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Papers by Muzaffer Ege Alper