05. Fakülteler

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17th International Conference on Mechatronics Technology, October 15-18, 2013, Jeju Island, Korea
(Elsevier, 2015) Hwang, Sung Ho; Kim, Joon-wan; Dorantes-Gonzalez, Dante Jorge
In recent years, Mechatronics has gained a lot of interest as more applications have been introduced to industry and society. The need for new mechatronic technologies in the form of advanced production systems, mechatronic devices, control systems, robotics, biomedical applications, MEMS, and measurement systems, among others, is very much required in improving productivity and competitiveness in many industries. Thus, this conference was organized to address the state-of-the-art technology for the benefit of researchers and users, and this time the conference made a special focus on the topic: Sustainable Mechatronics Technology.
Citation - WoS: 6
Citation - Scopus: 6
A 32-Society Investigation of the Influence of Perceived Economic Inequality on Social Class Stereotyping
(Wiley, 2022) Ashokkumar, Ashwini; Billet, Matthew; Becker, Maja; Peters, Kim; Jetten, Joland; Barry, Oumar; Tanjitpiyanond, Porntida; Peker, Müjde
There is a growing body of work suggesting that social class stereotypes are amplified when people perceive higher levels of economic inequality—that is, the wealthy are perceived as more competent and assertive and the poor as more incompetent and unassertive. The present study tested this prediction in 32 societies and also examines the role of wealth-based categorization in explaining this relationship. We found that people who perceived higher economic inequality were indeed more likely to consider wealth as a meaningful basis for categorization. Unexpectedly, however, higher levels of perceived inequality were associated with perceiving the wealthy as less competent and assertive and the poor as more competent and assertive. Unpacking this further, exploratory analyses showed that the observed tendency to stereotype the wealthy negatively only emerged in societies with lower social mobility and democracy and higher corruption. This points to the importance of understanding how socio-structural features that co-occur with economic inequality may shape perceptions of the wealthy and the poor. © 2022 The Authors. European Journal of Social Psychology published by John Wiley & Sons Ltd.
A Bayesian Allocation Model Based Approach To Mixed Membership Stochastic Blockmodels
(Taylor and Francis Ltd., 2022) Kırbız, Serap; Hızlı, Çağlar
Although detecting communities in networks has attracted considerable recent attention, estimating the number of communities is still an open problem. In this paper, we propose a model, which replicates the generative process of the mixed-membership stochastic block model (MMSB) within the generic allocation framework of Bayesian allocation model (BAM) and BAM-MMSB. In contrast to traditional blockmodels, BAM-MMSB considers the observations as Poisson counts generated by a base Poisson process and marks according to the generative process of MMSB. Moreover, the optimal number of communities for BAM-MMSB is estimated by computing the variational approximations of the marginal likelihood for each model order. Experiments on synthetic and real data sets show that the proposed approach promises a generalized model selection solution that can choose not only the model size but also the most appropriate decomposition.
Citation - WoS: 2
Citation - Scopus: 1
A Benchmark Dataset for Turkish Data-To Generation
(Elsevier, 2022) Demir, Şeniz; Öktem, Seza
In the last decades, data-to-text (D2T) systems that directly learn from data have gained a lot of attention in natural language generation. These systems need data with high quality and large volume, but unfortunately some natural languages suffer from the lack of readily available generation datasets. This article describes our efforts to create a new Turkish dataset (Tr-D2T) that consists of meaning representation and reference sentence pairs without fine-grained word alignments. We utilize Turkish web resources and existing datasets in other languages for producing meaning representations and collect reference sentences by crowdsourcing native speakers. We particularly focus on the generation of single-sentence biographies and dining venue descriptions. In order to motivate future Turkish D2T studies, we present detailed benchmarking results of different sequence-to-sequence neural models trained on this dataset. To the best of our knowledge, this work is the first of its kind that provides preliminary findings and lessons learned from the creation of a new Turkish D2T dataset. Moreover, our work is the first extensive study that presents generation performances of transformer and recurrent neural network models from meaning representations in this morphologically-rich language.
Citation - WoS: 9
Citation - Scopus: 8
A Longitudinal Assessment of Variability in Covid-19 Vaccine Hesitancy and Psychosocial Correlates in a National United States Sample
(Elsevier Sci Ltd, 2023) Shook, Natalie J.; Oosterhoff, Benjamin; Sevi, Barış
Recent evidence suggests that COVID-19 vaccine hesitancy is not static. In order to develop effective vaccine uptake interventions, we need to understand the extent to which vaccine hesitancy fluctuates and identify factors associated with both between- and within-person differences in vaccine hesitancy. The goals of the current study were to assess the extent to which COVID-19 vaccine hesitancy varied at an individual level across time and to determine whether disgust sensitivity and germ aversion were associated with between- and within-person differences in COVID-19 vaccine hesitancy. A national sample of U.S. adults (N = 1025; 516 woman; M-age = 46.34 years, SDage = 16.56, range: 18 to 85 years; 72.6 % White) completed six weekly online surveys (March 20 - May 3, 2020). Between-person mean COVID-19 vaccine hesitancy rates were relatively stable across the six-week period (range: 38-42 %). However, there was considerable within-person variability in COVID-19 vaccine hesitancy. Approximately, 40 % of the sample changed their vaccine hesitancy at least once during the six weeks. There was a significant between-person effect for disgust sensitivity, such that greater disgust sensitivity was associated with a lower likelihood of COVID-19 vaccine hesitance. There was also a significant within-person effect for germ aversion. Participants who experienced greater germ aversion for a given week relative to their own six week average were less likely to be COVID-19 vaccine hesitant that week relative to their own six-week average. This study provides important information on rapidly changing individual variability in COVID-19 vaccine hesitancy on a weekly basis, which should be taken into consideration with any efforts to decrease vaccine hesitancy and increase vaccine uptake. Further, these findings identify-two psychological factors (disgust sensitivity and germ aversion) with malleable components that could be leveraged in developing vaccine uptake interventions.
A Lot-Sizing Problem in Deliberated and Controlled Co-Production Systems
(Taylor and Francis, 2021) Kabakulak, Banu; Ağralı, Semra; Taşkın, Z. Caner; Pamuk, Bahadır
We consider an uncapacitated lot sizing problem in co-production systems, in which it is possible to produce multiple items simultaneously in a single production run. Each product has a deterministic demand to be satisfied on time. The decision is to choose which items to co-produce and the amount of production throughout a predetermined planning horizon. We show that the lot sizing problem with co-production is strongly NP-Hard. Then, we develop various mixed-integer linear programming (MILP) formulation of the problem and show that LP relaxations of all MILPs are equal. We develop a separation algorithm based on a set of valid inequalities, lower bounds based on a dynamic lot-sizing relaxation of our problem and a constructive heuristic that is used to obtain an initial solution for the solver, which form the basis of our proposed Branch & Cut algorithm for the problem. We test our models and algorithms on different data sets and provide the results.
Citation - WoS: 5
Citation - Scopus: 6
A New Approach for Measuring Viscoelastic Properties of Soft Materials Using the Dynamic Response of a Spherical Object Placed at the Sample Interface
(Springer, 2023) Besli, Ayça; Koç,Ömer Hayati; Körük,Hasan; Yurdaer, Berk Salih
Background: There are several techniques to characterize the mechanical properties of soft materials, such as the indentation method and the method based on the application of a spherical object placed inside the sample. The indentation systems usually yield the elastic properties of materials and their mathematical models do not consider the inertia of the sample involved in motion and radiation damping, while placing an object inside the sample is not practical and this procedure can alter the mechanical properties of the sample for the method based on the application of a bubble/sphere placed inside the sample. Objective: A new approach for the identification of the viscoelastic properties of soft materials using the dynamic response of a spherical object placed at the sample interface was proposed. Methods: The spherical object placed at the sample interface was pressed using an electromagnet and the dynamic response of the spherical object was tracked using a high-speed camera, while the dynamic response of the spherical object placed at the sample interface was estimated using a comprehensive analytical model. The effects of the shear modulus, viscosity, Poisson’s ratio and density of the soft sample, the radius and density of the spherical object and the damping due to radiation were considered in this mathematical model. The shear modulus and viscosity of the soft sample were determined by matching the experimentally identified and theoretically estimated responses of the spherical object. Results: The shear moduli and viscosities of the three phantoms with the gelatin mass ratios of 0.20, 0.25 and 0.29 were measured to be 3450, 4300 and 4950 Pa and 12.5, 14.0 and 15.0 Pa⋅s, respectively. The shear modulus and viscosity of the phantom increases as the gelatin mass ratio increases. The frequency of oscillations of the hemisphere placed at the phantom interface increases as the gelatin mass ratio increases due to stiffness increase. Conclusions: After matching the experimental and theoretical steady-state displacements and amplitudes of oscillations of the hemisphere at the sample interface, the comparison of the experimentally identified and theoretically predicted frequency of oscillations further confirmed the identified material properties of the samples. The approach presented here is expected to provide valuable information on material properties in biomedical and industrial applications.
A New Benchmark Dataset for P300 Erp-Based Bci Applications
(Academic Press Inc Elsevier Science, 2023) Çakar, Tuna; Özkan, Hüseyin; Musellim, Serkan; Arslan, Suayb S.; Yağan, Mehmet; Çakar, Tuna; Alp, Nihan
Because of its non-invasive nature, one of the most commonly used event-related potentials in brain -computer interface (BCI) system designs is the P300 electroencephalogram (EEG) signal. The fact that the P300 response can easily be stimulated and measured is particularly important for participants with severe motor disabilities. In order to train and test P300-based BCI speller systems in more realistic high-speed settings, there is a pressing need for a large and challenging benchmark dataset. Various datasets already exist in the literature but most of them are not publicly available, and they either have a limited number of participants or utilize relatively long stimulus duration (SD) and inter-stimulus intervals (ISI). They are also typically based on a 36 target (6 x 6) character matrix. The use of long ISI, in particular, not only reduces the speed and the information transfer rates (ITRs) but also oversimplifies the P300 detection. This leaves a limited challenge to state-of-the-art machine learning and signal processing algorithms. In fact, near-perfect P300 classification accuracies are reported with the existing datasets. Therefore, one certainly needs a large-scale dataset with challenging settings to fully exploit the recent advancements in algorithm design (machine learning and signal processing) and achieve high-performance speller results. To this end, in this article we introduce a new freely-and publicly-accessible P300 dataset obtained using 32-channel EEG, in the hope that it will lead to new research findings and eventually more efficient BCI designs. The introduced dataset comprises 18 participants performing a 40 -target (5 x 8) cued-spelling task, with reduced SD (66.6 ms) and ISI (33.3 ms) for fast spelling. We have also processed, analyzed, and character-classified the introduced dataset and we presented the accuracy and ITR results as a benchmark. The introduced dataset and the codes of our experiments are publicly accessible at https://data .mendeley.com /datasets /vyczny2r4w.(c) 2023 Elsevier Inc. All rights reserved.
Citation - WoS: 6
Citation - Scopus: 6
A Strong Integer Programming Formulation for Hybrid Flowshop Scheduling
(Taylor & Francis, 2019) Ağralı, Semra; Ünal, A. Tamer; Taşkın, Z. Caner
We consider a hybrid flowshop scheduling problem that includes parallel unrelated discrete machines or batch processing machines in different stages of a production system. The problem is motivated by a bottleneck process within the production system of a transformer producer located in the Netherlands. We develop an integer programming model that minimises the total tardiness of jobs over a finite planning horizon. Our model is applicable to a wide range of production systems organised as hybrid flowshops. We strengthen our integer program by exploiting the special properties of some constraints in our formulation. We develop a decision support system (DSS) based on our proposed optimisation model. We compare the results of our initial optimisation model with an improved formulation as well as with a heuristic that was in use at the company before the implementation of our DSS. Our results show that the improved optimisation model significantly outperforms the heuristic and the initial optimisation model in terms of both the solution time and the strength of its linear programming relaxation.
Citation - WoS: 23
Citation - Scopus: 25
Acoustic Particle Palpation for Measuring Tissue Elasticity
(American Institute of Physics, 2015) El Ghamrawy, Ahmed; Körük, Hasan; Choi, James J; Pouliopoulos, Antonios N
We propose acoustic particle palpation—the use of sound to press a population of acoustic particles against an interface—as a method for measuring the qualitative and quantitative mechanical properties of materials. We tested the feasibility of this method by emitting ultrasound pulses across a tunnel of an elastic material filled with microbubbles. Ultrasound stimulated the microbubble cloud to move in the direction of wave propagation, press against the distal surface, and cause deformations relevant for elasticity measurements. Shear waves propagated away from the palpation site with a velocity that was used to estimate the material’s Young’s modulus.
Citation - WoS: 12
Citation - Scopus: 15
Acoustic Streaming in a Soft Tissue Microenvironment
(Elsevier, 2019) El Ghamrawy, Ahmed; Mohammed, Ali; Jones, Julian R; Körük, Hasan; Choi, James J; de Comtes, Florentina
We demonstrated that sound can push fluid through a tissue-mimicking material. Although acousticstreaming in tissue has been proposed as a mechanism for biomedical ultrasound applications, such as neuromodu-lation and enhanced drug penetration, streaming in tissue or acoustic phantoms has not been directly observed. Wedeveloped a material that mimics the porous structure of tissue and used a dye and a video camera to track fluidmovement. When applied above an acoustic intensity threshold, a continuous focused ultrasound beam (spatialpeak time average intensity: 238 W/cm2, centre frequency: 5 MHz) was found to push the dye axially, that is, in thedirection of wave propagation and in the radial direction. Dye clearance increased with ultrasound intensity andwas modelled using an adapted version of Eckart’s acoustic streaming velocity equation. No microstructuralchanges were observed in the sonicated region when assessed using scanning electron microscopy. Our study indi-cates that acoustic streaming can occur in soft porous materials and provides a mechanistic basis for future use ofstreaming for therapeutic or diagnostic purposes.
Citation - WoS: 18
Citation - Scopus: 18
Adding Rapid-Acting Insulin or Glp-1 Receptor Agonist To Basal Insulin: Outcomes in a Community Setting
(2015) Dalal, Mehul R; DiGenio, Andres; Xie, Lin; Başer, Onur
To evaluate real-world outcomes in patients with type 2 diabetes mellitus (T2DM)receiving basal insulin, who initiate add-on therapy with a rapid-acting insulin (RAI) or aglucagon-like peptide 1 (GLP-1) receptor agonist.Data were extracted retrospectively from a U.S. health claims database. Adults withT2DM on basal insulin who added an RAI (basal+RAI) or GLP-1 receptor agonist (basal+GLP-1) were included. Propensity score matching (1 up to 3 ratio) was used to control for differencesin baseline demographics, clinical characteristics, and health resource utilization. Endpointsincluded prevalence of hypoglycemia, pancreatic events, all-cause and diabetes-relatedresource utilization, and costs at 1 year follow-up. Overall, 6,718 matched patients were included: 5,013 basal+RAI and 1,705basal+GLP1. Patients in both groups experienced a similar proportion of any hypoglycemicevent (P = .4079). Hypoglycemic events leading to hospitalization were higher in the basal+RAIcohort (2.7% vs. 1.8%; P = .0444). The basal+GLP-1 cohort experienced fewer all-cause(13.55% vs. 18.61%; P<.0001) and diabetes-related hospitalizations (11.79% vs. 15.68%;P<.0001). The basal+GLP-1 cohort had lower total all-cause health care costs ($18,413 vs.$20,821; P = .0002), but similar diabetes-related costs ($9,134 vs. $8,985; P<.0001) comparedwith the basal+RAI cohort. Add-on therapy with a GLP-1 receptor agonist in T2DM patients receiving basalinsulin was associated with fewer hospitalizations and lower total all-cause costs compared withadd-on therapy using a RAI, and could be considered an alternative to a RAI in certain patientswith T2DM, who do not achieve effective glycemic control with basal insulin.
Citation - WoS: 44
Citation - Scopus: 67
Adoption and Use of Learning Management Systems in Education: the Role of Playfulness and Self-Management
(MDPI [Commercial Publisher], 2021) Akküçük, Ulaş; Balkaya, Selen
This article investigates the factors affecting primary and secondary education teachers' behavioral intention to adopt learning management systems (LMSs). Information technology (IT) innovations have the power to change the way we work, educate, learn, and basically the way we live. The effect of IT innovations on education makes it critical to understand the current usage situation of LMSs and the factors affecting their adoption by teachers. The unified theory of acceptance and use of technology (UTAUT) was extended with factors from education and game-based learning literature. In order to see the effect of individual- and organizational-level characteristics, multi-group structural equation modeling (SEM) analysis was conducted and discrepancies in relationships were reported. Evaluation of users and non-users and teachers of different fields were also compared to each other. The findings of this study not only contribute to theory through the development and testing of a thorough model relating technology features and individual characteristics to behavioral intention to use, but also offer strong implications for practitioners who would like to increase LMS usage and create a more effective learning environment.
Citation - WoS: 19
Citation - Scopus: 21
An Adaptive Admittance Controller for Collaborative Drilling With a Robot Based on Subtask Classification Via Deep Learning
(Elsevier, 2022) Başdoğan, Çağatay; Niaz, P. Pouya; Aydın, Yusuf; Güler, Berk; Madani, Alireza
In this paper, we propose a supervised learning approach based on an Artificial Neural Network (ANN) model for real-time classification of subtasks in a physical human–robot interaction (pHRI) task involving contact with a stiff environment. In this regard, we consider three subtasks for a given pHRI task: Idle, Driving, and Contact. Based on this classification, the parameters of an admittance controller that regulates the interaction between human and robot are adjusted adaptively in real time to make the robot more transparent to the operator (i.e. less resistant) during the Driving phase and more stable during the Contact phase. The Idle phase is primarily used to detect the initiation of task. Experimental results have shown that the ANN model can learn to detect the subtasks under different admittance controller conditions with an accuracy of 98% for 12 participants. Finally, we show that the admittance adaptation based on the proposed subtask classifier leads to 20% lower human effort (i.e. higher transparency) in the Driving phase and 25% lower oscillation amplitude (i.e. higher stability) during drilling in the Contact phase compared to an admittance controller with fixed parameters.
Citation - WoS: 28
Citation - Scopus: 41
An Analysis of Elementary School Children's Fractional Knowledge Depicted With Circle, Rectangle, and Number Line Representations
(Springer, 2015) Tunç-Pekkan, Zelha
It is now well known that fractions are difficult concepts to learn as well as to teach. Teachers usually use circular pies, rectangular shapes and number lines on the paper as teaching tools for fraction instruction. This article contributes to the field by investigating how the widely used three external graphical representations (i.e., circle, rectangle, number line) relate to students' fractional knowledge and vice versa. For understanding this situation, a test using three representations with the same fractional knowledge framed within Fractional Scheme Theory was developed. Six-hundred and fifty-six 4th and 5th grade US students took the test. A statistical analysis of six fractional Problem Types, each with three external graphical representations (a total of 18 problems) was conducted. The findings indicate that students showed similar performance in circle and rectangle items that required using part-whole fractional reasoning, but students' performance was significantly lower on the items with number line graphical representation across the Problem Types. In addition, regardless of the representation, their performance was lower on items requiring more advanced fractional thinking compared to part-whole reasoning. Possible reasons are discussed and suggestions for teaching fractions with graphical representations are presented. Copyright of Educational Studies in Mathematics is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.
Citation - WoS: 15
Citation - Scopus: 15
An Analysis of Turkey’s Water Diplomacy and Its Evolving Position Vis-À International Water Law
(Taylor & Francis, 2014) Kibaroğlu, Ayşegül
This article analyzes Turkey’s transboundary water policy by examining its institutional framework and basic principles. It explores the reasons why Turkey voted against the UN Watercourses Convention. Turkey’s harmonization with the water law of the European Union is also scrutinized with an aim to assess its implications for transboundary water policy making. Turkish water diplomacy faces new challenges, such as the devastating impacts of prolonged droughts as well as ongoing instability and conflicts in Syria and Iraq. Hence, it is imperative for Turkey to systematically reconcile its water policy objectives in accordance with the global norms that are adopted in this field
Citation - WoS: 29
Citation - Scopus: 38
An Efficient Framework for Visible-Infrared Cross Modality Person Re-Identification
(Elsevier, 2020) Gökmen, Muhittin; Başaran, Emrah; Kamasak, Mustafa E.
Visible-infrared cross-modality person re-identification (VI-ReId) is an essential task for video surveillance in poorly illuminated or dark environments. Despite many recent studies on person re-identification in the visible domain (ReId), there are few studies dealing specifically with VI-ReId. Besides challenges that are common for both ReId and VI-ReId such as pose/illumination variations, background clutter and occlusion, VI-ReId has additional challenges as color information is not available in infrared images. As a result, the performance of VI-ReId systems is typically lower than that of ReId systems. In this work, we propose a four-stream framework to improve VI-ReId performance. We train a separate deep convolutional neural network in each stream using different representations of input images. We expect that different and complementary features can be learned from each stream. In our framework, grayscale and infrared input images are used to train the ResNet in the first stream. In the second stream, RGB and three-channel infrared images (created by repeating the infrared channel) are used. In the remaining two streams, we use local pattern maps as input images. These maps are generated utilizing local Zernike moments transformation. Local pattern maps are obtained from grayscale and infrared images in the third stream and from RGB and three-channel infrared images in the last stream. We improve the performance of the proposed framework by employing a re-ranking algorithm for post-processing. Our results indicate that the proposed framework outperforms current state-of-the-art with a large margin by improving Rank-1/mAP by 29.79%/30.91% on SYSU-MM01 dataset, and by 9.73%/16.36% on RegDB dataset.
Citation - WoS: 21
Audio Source Separation Using Variational Autoencoders and Weak Class Supervision
(Institute of Electrical and Electronics Engineers (IEEE), 2019) Kırbız, Serap; Karamatlı, Ertuğ; Cemgil, Ali Taylan
In this letter, we propose a source separation method that is trained by observing the mixtures and the class labels of the sources present in the mixture without any access to isolated sources. Since our method does not require source class labels for every time-frequency bin but only a single label for each source constituting the mixture signal, we call this scenario as weak class supervision. We associate a variational autoencoder (VAE) with each source class within a non negative (compositional) model. Each VAE provides a prior model to identify the signal from its associated class in a sound mixture. After training the model on mixtures, we obtain a generative model for each source class and demonstrate our method on one-second mixtures of utterances of digits from 0 to 9. We show that the separation performance obtained by source class supervision is as good as the performance obtained by source signal supervision.
Citation - WoS: 30
Citation - Scopus: 41
Barriers in Participative Water Governance: a Critical Analysis of Community Development Approaches
(MDPI, 2022) Shunglu, Raghav; Withanachchi, Chandana Rohana; Kibaroǧlu, Ayşegül; Köpke, Sören; Kanoi, Lav; Nissanka, Thushantha S.; Gamage, Deepika U.
Participatory approaches within development programs involving common-pool resources are intended to revive a community’s role in managing these resources. Certainly, to ensure the successful and equitable use of such resources, community participation is essential. However, in many cases, attempts at applying a participatory approach often fail to genuinely engage all subgroups within a community due to assumptions of homogeneity and a lack of understanding of the deep socio-political divisions between people. As a result, development programs can be plagued by these pre-existing power relations, potentially resulting in tokenistic community participation and the continuation of elite capture of natural resources to the same extent or worse than before a development program has begun. This in turn can negatively impact good governance and the fair distribution of a common pool resource. This paper explores the use of participatory approaches in water projects, assessing to what degree power relationships impact water management programs. Using a qualitative approach, the paper identifies key challenges of participatory water governance through case studies from Turkey, India, and Sri Lanka, exploring: lack of social trust, elite capture of participatory processes, power heterogeneity and imbalances at the micro-level, and a lack of inclusive participation in decision-making. Based on the analysis of these case studies, this paper argues that it is essential for participatory development interventions to understand socio-political power relations within a community—an inherently complex and contested space. The so-called “exit strategy” of a community project play a key role to decide the project sustainability that grants the “community ownership” of the project. Such an understanding can bring about greater success in development interventions attempting to address water-related issues.
Citation - WoS: 2
Citation - Scopus: 2
Bedouins and In-Between Border Space in the Northern Sinai
(Taylor & Francis, 2019) Görmüş, Evrim
The northern Sinai as interstice space of contestation offers useful insights concerning the relation between the dynamics of power and resistance. This article aims to analyse the complex relationship between the local inhabitants’ belonging and spatial practices by referring to the idea of in-betweenness. The article uses the notion of in-between border space to understand the Bedouins’ changing identity formations within a given spatial situation, as well as to trace the Egyptian State’s spatial variations in achieving social control within its territory. It is argued that the decades-long marginalization and oppression of the Bedouins by the Egyptian State turned their borderland region into a space of resistance and leaded to the forming of spatio-temporal identities in-between border space in the northern Sinai.

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