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How does prohibition stop working? The visibility and legitimacy of Mevlevi ceremonies in modern Turkey
Get PDFSufism has been officially banned in the Turkish Republic since 1925, which includes
all Sufi orders, their lodges and rituals, and naturally, the Mevlevi order is no
exception. Interestingly, however, the semâ ceremony of the Mevlevi order has
turned out to be a cultural and touristic show that supposedly represents Turkish
culture. The “whirling dervish” has become an iconic figure, frequently used in
national touristic advertisements. Moreover, annual commemorations in honor of
Mevlânâ Celaleddin Rumi, the founder of Mevlevi Sufi order, are attended by the
highest state authorities every year. The research question of my thesis is how
legitimacy and visibility of Mevlevi semâ ceremonies have been changed after the
ban in 1925. I limited my work to the ceremonies in Konya performed in every
December since the 1940s, the most popular and central celebration event on Rumi’s
death anniversary called “Şeb-i Arus” (means “wedding night”). Effective actors in this
field are; the Turkish Republic’s apparatuses including relevant statesmen and
institutions, members of the Mevlevî order, performers of the ceremonies, people
interested in Rumi and Mevlevîlik for scientific, intellectual and touristic reasons,
especially from the US and Europe, mass media and non-governmental organizations.
I explored and discussed both tensions and accommodation between these actors
throughout the history of Turkish Republic.Abstract ....................................................................................................................... iv
Öz ................................................................................................................................. v
Acknowledgements ..................................................................................................... vi
Table of Contents ........................................................................................................vii
List of Figures ............................................................................................................... x
List of Abbreviations ....................................................................................................xi
CHAPTERS
1. INTRODUCTION ........................................................................................................ 1
1.1. The Problem and Rationale ............................................................................... 1
1.2. The Literature and Methodology ...................................................................... 4
1.3. Organization ...................................................................................................... 9
2. EVOLUTION OF MEVLEVILIK AND SEMÂ ................................................................ 11
2.1. Mevlânâ Celâleddîn Rûmî and the Mevlevî Order .......................................... 11
2.1.1. Traditional Transmission and Legitimacy ................................................. 12
2.1.2. Rumi Commemorations: Şeb-i Arûs ......................................................... 14
2.2. Turkish Modernization and Sufism .................................................................. 15
2.2.1. Sufis and the Ottoman Modernization ..................................................... 15
2.2.2. Sufis and the New Regime ........................................................................ 17
3. NEGOTIATION AND INSTITUTIONALIZATION OF SEMÂ ......................................... 20
3.1. Actors Negotiating the Sema: the State, NGOs and Mevlevis ........................ 20
3.1.1. Examining the Turkish State as an Actor .................................................. 20
3.1.2. Actors of the Ceremonies ......................................................................... 22
3.1.2.1. Organization ...................................................................................... 22
3.1.2.1.1. Statesmen and State Institutions ............................................... 22
3.1.2.1.2. NGOs and Organizers ................................................................. 25
3.1.2.2. Performers: Semâzens and Musicians .............................................. 26
3.1.2.3. The Audience..................................................................................... 28
3.1.2.3.1. Media ......................................................................................... 28
3.1.2.3.2. Tourism ...................................................................................... 29
3.2. Bureaucratization and “Co-optation” of the Sema ......................................... 30
3.2.1. The Inclusion Process: Adoption of Mevlevi Semâ by the State............... 30
3.2.2. Mevlevi Approaches to the State and the Ban ......................................... 35
3.2.3. The State’s Perception of the Commemoration Ceremonies .................. 45
3.2.3.1. Politics and Sufism in Turkey: Nonpolitical or Political, Moderate or Radical ............................................................................................................ 45
3.2.3.2. The Legalization of Semâ Ceremonies .............................................. 51
3.2.3.3. The Privatization Policies, Commodification and Semâ .................... 52
3.2.3.4. Rumi Commemorations Today: Power and Legitimacy .................... 55
4. THE VISIBILITY AND AUTHENTICITY OF SEMA ........................................................ 59
4.1. Public Visibility of Rumî’s Image and Semâ Ceremonies................................. 59
4.1.1. (Di)vision, Orientalism, and Hybridity in Turkey’s “Belated Modernity” . 61
4.1.2. Three Discourses on Rumi ........................................................................ 65
4.1.2.1. The Humanist Discourse ................................................................... 65
4.1.2.2. The Nationalist Discourse ................................................................. 69
4.1.2.3. The Traditionalist Discourse .............................................................. 72
4.1.3. “Postmodern” Justification: The Effect of New Age, Publications and International Interaction .................................................................................... 76
4.1.4. Popularization: Tourism and the Media Representations ........................ 79
4.1.4.1. Touristic value ................................................................................... 80
4.1.4.2. Media ................................................................................................ 84
4.1.4.2.1. Mevlevi ayins as part of Turkish Music corpus .......................... 84
4.1.4.2.2. Mevlana Commemoration Ceremonies in visual media ........... 85
4.2. Production of Authenticity: The Real and the Artificial .................................. 87
4.2.1. Understanding the Mevlevi Ceremony: Theoretical Framework ............. 87
4.2.1.1. Meaning, Action and Performance ................................................... 87
4.2.1.2. Self and Frame .................................................................................. 89
4.2.1.3. Cultural Pragmatics ........................................................................... 91
4.2.2. Analyzing the elements of contemporary semâ performances ............... 93
4.2.2.1. Systems of collective representation ................................................ 93
4.2.2.2. Actors ................................................................................................ 94
4.2.2.3. Audience/Observers ......................................................................... 95
4.2.2.4. Means of symbolic production ......................................................... 97
4.2.2.5. Mise-en-scéne ................................................................................... 98
4.2.2.6. Social Power .................................................................................... 100
4.2.3. Fusion and De-fusion .............................................................................. 101
4.2.4. Authenticity of Semâ Performances: Revivalist and Mimesis Frames ... 103
4.2.4.1. Revivalist Frame .............................................................................. 104
4.2.4.2. Mimesis Frame ................................................................................ 108
5. CONCLUSION ........................................................................................................ 111
BIBLIOGRAPHY.......................................................................................................... 11
Biometric identification and authentication using time series classification for mouse and eye movements
No full textTezin basılısı İstanbul Şehir Üniversitesi Kütüphanesi'ndedir.Security plays a very important role in modern world where almost everything is done with the computer. It is agreed that biometric recognition systems require the combined analysis of multiple behavioral traits or physiological characteristics. In addition, those systems are considered to be the most flexible and effective mode of identifying and authenticating individuals as the person does not need to remember any password, or carry smart cards.
The human body can remember the movement of mouse and the gaze if that action is practiced a lot, which mean when the user want to be authenticated in to computer so he will not forget the mouse and eye actions. So, this actions can be utilized in way of password authentication system, in which if the user implement the right movements can be considered as an authenticated user. Otherwise the system will reject the user. So for experimenting the authentication system, Different time series datasets consisting of mouse movements and gaze positions were analyzed and an authentication model was developed. It is shown that the users can be authenticated by proving their claimed identities using the developed model. This thesis investigates mouse and eye coordinates for user recognition scheme that introduce a random forest classification model for Mouse and eye movements to recognize these movements. The focus of this thesis is on the classification methods of time series, including similarity measures and random forest . Features are extracted from the mouse and eye movements raw data and implementing 1.Nearest Neighbor and Random forest to classify users. The accuracy of the identification varies with the variety of features used The experimental results were competing with our proposed biometric authentication model. The accuracy achieved by 1.Nearest neighbor was not sufficient in predicting users identities by mouse and eye tracking . On the other hand the maximum accuracy from implementing random forest model was 60 % which quietly good in terms of biometric but it is still need development to have perfect biometric model with higher accuracy.Abstract v
Öz vi
Acknowledgments viii
List of Figures xi
List of Tables xii
Abbreviations xiii
1 Introduction 1
2 Background 8
2.1 Biometric Authentication Applications . . . . . . . . . . . . . . . . . . . . 8
2.2 Eye Movement and Mouse Biometrics . . . . . . . . . . . . . . . . . . . . 9
2.3 Time Series Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.3.1 Time Series Data Mining (TSDM) . . . . . . . . . . . . . . . . . . 12
2.3.2 Time series Data Mining Tasks . . . . . . . . . . . . . . . . . . . . 13
2.4 Time Series Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.5 Time Series Classification Algorithms . . . . . . . . . . . . . . . . . . . . 15
2.6 Time-Series Similarity Measures . . . . . . . . . . . . . . . . . . . . . . . . 15
2.6.1 Euclidean and Dynamic Time Warping Distance . . . . . . . . . . 16
2.7 Nearest Neighbor Classification . . . . . . . . . . . . . . . . . . . . . . . 16
2.8 Support Vector Macnes . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.8.0.1 Tree-Based Approaches . . . . . . . . . . . . . . . . . . . 18
2.9 Feature Extraction and Selection . . . . . . . . . . . . . . . . . . . . . . . 19
2.9.1 Importance of Feature Extraction . . . . . . . . . . . . . . . . . . . 19
2.10 Time Series Data Mining Applications . . . . . . . . . . . . . . . . . . . . 20
3 Literature Survey 22
4 Data and Analysis 26
4.1 Data Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.1.1 Data Variables (Input Features) . . . . . . . . . . . . . . . . . . . 27
4.1.2 Datasets and the System Used in Experiments . . . . . . . . . . . 28
4.2 Data Interpolation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.3 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.3.1 Similarity Measures . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.3.2 Nearest Neighbor . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.3.2.1 Data preprocessing . . . . . . . . . . . . . . . . . . . . . 30
4.4 Feature extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.4.2 Constructing the Dataset (Data Processing) . . . . . . . . . . . . . 32
4.5 Data Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.5.1 Mouse Positions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.5.2 Gaze Positions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4.5.3 Normalized X Coordinates . . . . . . . . . . . . . . . . . . . . . . . 36
4.5.4 Normalized Y Coordinates . . . . . . . . . . . . . . . . . . . . . . . 37
4.5.5 Length of the Curve . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.5.6 Speed of Mouse and Eye Movements . . . . . . . . . . . . . . . . . 38
4.5.7 Acceleration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.5.8 Average Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.5.9 Euclidean Distance . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.5.10 DifferenceXCoordinates YCoordinatesforEyeandMouseMovements ( ∆x,∆y) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
5 Experimental results 43
5.1 Nearest Neighbor Classification Results . . . . . . . . . . . . . . . . . . . . 43
5.1.1 Measurements and Performance Metrics . . . . . . . . . . . . . . . 43
5.2 Random forest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
5.2.1 Data Partitioning . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
5.2.2 Design and Performance Improvements for Random Forest . . . . . 45
5.2.3 Random Forest Features . . . . . . . . . . . . . . . . . . . . . . . . 45
5.2.4 Random Forest for Data A . . . . . . . . . . . . . . . . . . . . . . 46
5.2.4.1 Constructing the Model . . . . . . . . . . . . . . . . . . 46
5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
6 Conclusion 52
6.1 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
A Tables 55
Bibliography 5
Evaluation of the impacts of plug-in hybrid electric vehicles on electricity load curve for Istanbul
Get PDFThe greenhouse gas emissions, depletion of fossil fuels and high petroleum prices are major concerns of the world in the recent years. Plug-in Hybrid Electric Vehicles (PHEVs) are emerging as an alternative solution in the transportation sector due to their economic and environmental advantages. PHEVs have a grid connection capability to charge their batteries. Therefore, it is crucial to investigate the impacts of PHEVs on the electricity grid when the PHEVs penetrate into the system.
In this study, the effects of PHEVs on electricity network is evaluated for İstanbul. For this purpose, the related data is obtained and the Monte Carlo simulation is applied to generate new daily load curve while considering the charging characteristics, driving characteristics and penetration level of PHEVs. Two different scenarios are defined with regard the time of charging: uncontrolled charging and off-peak charging. For each scenario, various cases are created by considering different percentages of battery sizes, different distribution of charger types, and risk perception of the vehicle owners. The new daily load curve is generated for 10% and 50% penetration levels of PHEVs. The changes in the daily load curve due to the additional demand from PHEV charging is analyzed for each scenario. According to the results, in particular with high penetration level, the electricity consumption increases significantly and new peak loads are created on the daily load profile.CONTENTS:
Declaration of Authorship ii
Abstract iii
Öz iv
Acknowledgments v
List of Figures viii
List of Tables xiii
1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Background and Literature Survey 6 2.1 Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.1 Advantages of Electric Vehicles . . . . . . . . . . . . . . . . . . . . 7 2.1.2 History of Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . 8 2.1.3 Electric Vehicle Market Over the World . . . . . . . . . . . . . . . 9 2.1.4 Electric Vehicle Market in Turkey . . . . . . . . . . . . . . . . . . 11 2.1.5 Charging Stations in Turkey . . . . . . . . . . . . . . . . . . . . . 12 2.2 Impact Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.1 Charging Characteristics . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.1.1 Charging Power Level . . . . . . . . . . . . . . . . . . . . 14 2.2.1.2 Battery Size . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.1.3 State of Charge . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.2 Driving Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.2.2.1 Distribution of Arrival Times . . . . . . . . . . . . . . . . 21 2.2.2.2 Distribution of Daily Driving Distances . . . . . . . . . . 21 2.2.3 Penetration levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2.4 Personel Preferences . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.3 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3 Application of Monte Carlo Simulation On Electricity Network 29 3.1 Related Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.2 Methodology to Generate Daily Load Curve . . . . . . . . . . . . . . . . . 35
3.2.1 Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . . . 37 3.3 Scenario Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.3.1 Uncontrolled Charging . . . . . . . . . . . . . . . . . . . . . . . . . 42 3.3.2 Off-Peak Charging . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 3.4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.4.1 Results of 10% PHEV Penetration Level . . . . . . . . . . . . . . . 43 3.4.1.1 Results for Uncontrolled Charging At Home Only . . . . 43 3.4.1.2 Results for Uncontrolled Charging Everywhere . . . . . . 51 3.4.1.3 Results for Off-Peak Charging At Home Only . . . . . . . 59 3.4.1.4 Results for Off-Peak Charging Everywhere . . . . . . . . 64 3.4.2 Results of 50% PHEV Penetration Level . . . . . . . . . . . . . . . 70 3.4.2.1 Results for Uncontrolled Charging At Home Only . . . . 71 3.4.2.2 Results for Uncontrolled Charging Everywhere . . . . . . 77 3.4.2.3 Results for Off-Peak Charging At Home Only . . . . . . . 83 3.4.2.4 Results for Off-Peak Charging Everywhere . . . . . . . . 90
4 Conclusion and Future Work 97 4.1 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Bibliography 10
Close social ties, socioeconomic diversity and social capital in us congregations
No full textThis paper explores how various types of in-church close social ties of worshipers, socio-economic homogeneity of congregations and sociodemographic characteristics of their geographical locations affect worshipers’ bonding social capital (church-related volunteer participation) and bridging social capital (civic participation outside of church), by using the 2001 USCLS data. Close-social ties index determines various combinations of attending with close friends, children, and/or spouse. Congregational homogeneity levels are measured by looking at the race, income, age and education of churchgoers. Neighborhood-level sociodemographic characteristics include percentages of urban population and the proportion of racial minorities. Findings indicate that each type and composition of close social ties affect bonding and bridging social capital in different ways. Bonding social capital is the highest when worshipers attend together with their spouses, children and close friends. Bridging social capital is the highest when they attend with both spouses and close friends, but it starts to decline after the inclusion of children as the third type of tie. Race and income homogeneity foster church-related participation. Age and education homogeneity negatively affects church-related volunteerism but fosters civic participation outside. Only bonding social capital is affected by neighborhood-level factors. Higher proportions of racial minorities in neighborhoods increase church-related participation
When does globalization lead to local adaptation? the emergence of hybrid Islamic schools in Turkey, 1985-2007
No full textInstitutional perspectives of globalization envision the homogenization of the world through global cultural, economic, and political dynamics, while glocalization theory highlights how local cultures may adapt or resist global forces. On the basis of these theories, the authors analyze when, where, and why local hybrid organizational forms emerge as a reaction to globalization. They suggest that the impact of globalization on the emergence and expansion of hybrid organizational forms, which reflect local adaptations of global forms, depends on three types of moderators: (1) the fit between global and local ideas, values, and practices; (2) the experience of the local community with alternative organizational forms; and (3) the motivation of the local community to adapt. The authors test their hypotheses with data from the high school education system in Turkey from 1985 to 2007, a period in which Turkey experienced the growing impact of globalization
Towards better child protection programmes:a qualitative evaluation of Youth Disseminating Life Skills Programme
Get PDFThe present study aimed to assess the acceptability of a 12-week training programme, Youth Disseminating Life Skills Programme whose aims were to help university students acquire knowledge on and to increase sensitivity towards child abuse and neglect by adopting a qualitative methodology. The sample consisted of 13 university students who took part in the Youth Disseminating Life Skills Programme (10 female, 3 male: mean age 22 years; age range: 20–31). With the help of a general interview guide, the focus group meetings were held. Established conventions guided the analysis. Participants recounted feelings about and benefits of the Programme, and ways to improve the Programme. Feelings about the Programme included both positive (e.g. feeling hopeful) and negative feelings (e.g. feeling traumatised). Participants recounted a variety of benefits of the Programme (e.g. correcting some myths about child abuse). Participants proposed some ways whereby the Programmecouldbeimproved.Some findingscouldbeinterpretedin terms of existing literature/theory. Other findings extended the literature and could be viewed as targets for future child protection programmes
Traffic density estimation via KDE and nonlinear LS
No full textWith increasing population, the determination of traffic density becomes critical in managing urban city roads for safer driving and low carbon emissions. In this study, kernel density estimation is utilized in order to estimate traffic density more accurately when the speeds of vehicles are available for a given region. For the proposed approach, as a first step, the probability density function of the speed data is modeled by kernel density estimation. Then the speed centers from the density function are modeled as clusters. The cumulative distribution function of the speed data is then determined by Kolmogorov{Smirnov test, whose complexity is less when compared to the other techniques and whose robustness is high when outliers exist. Then the mean values of clusters are estimated from the smoothed density function of the distribution function, followed by a peak detection algorithm. The estimates of variance values and kernel weights, on the other hand, are found by a nonlinear least square approach. As the estimation problem has linear and nonlinear components, the nonlinear least square with separation of parameters approach is adopted, instead of dealing with a high complexity nonlinear equation. Simulations are carried out in order to assess the performance of the proposed approach. It is observed that the error between cumulative distribution functions is less than 1%, an indication that the traffic densities are estimated accurately. For an assumed traffic condition that bears five speed clusters, the minimum mean square error of kernel weights is found to be less than 0.00004. The proposed approach was also applied to real data from sample road traffic, and the speed center and the variance were accurately estimated. By using the proposed approach, accurate traffic density estimation is realized, providing extra information to the municipalities for better planning of their cities