Study of Periodic and Quasi-Periodic Structures in Silicon-on-Insulator

In this thesis, a numerical design approach has been proposed and developed based on the transmission matrix method in order to characterize periodic and quasi-periodic photonic structures in silicon-on-insulator. The approach and its performance have been extensively tested with specific structures in 2D and its validity has been verified in 3D

Privacy risks in trajectory data publishing: reconstructing private trajectories from continuous properties

Location and time information about individuals can be captured through GPS devices, GSM phones, RFID tag readers, and by other similar means. Such data can be pre-processed to obtain trajectories which are sequences of spatio-temporal data points belonging to a moving object. Recently, advanced data mining techniques have been developed for extracting patterns from moving object trajectories to enable applications such as city traffic planning, identification of evacuation routes, trend detection, and many more. However, when special care is not taken, trajectories of individuals may also pose serious privacy risks even after they are de-identified or mapped into other forms. In this paper, we show that an unknown private trajectory can be reconstructed from knowledge of its properties released for data mining, which at first glance may not seem to pose any privacy threats. In particular, we propose a technique to demonstrate how private trajectories can be re-constructed from knowledge of their distances to a bounded set of known trajectories. Experiments performed on real data sets show that the number of known samples is surprisingly smaller than the actual theoretical bounds

Discovering private trajectories using background information

Trajectories are spatio-temporal traces of moving objects which contain valuable information to be harvested by spatio-temporal data mining techniques. Applications like city traffic planning, identification of evacuation routes, trend detection, and many more can benefit from trajectory mining. However, the trajectories of individuals often contain private and sensitive information, so anyone who possess trajectory data must take special care when disclosing this data. Removing identifiers from trajectories before the release is not effective against linkage type attacks, and rich sources of background information make it even worse. An alternative is to apply transformation techniques to map the given set of trajectories into another set where the distances are preserved. This way, the actual trajectories are not released, but the distance information can still be used for data mining techniques such as clustering. In this paper, we show that an unknown private trajectory can be reconstructed using the available background information together with the mutual distances released for data mining purposes. The background knowledge is in the form of known trajectories and extra information such as the speed limit. We provide analytical results which bound the number of the known trajectories needed to reconstruct private trajectories. Experiments performed on real trajectory data sets show that the number of known samples is surprisingly smaller than the actual theoretical bounds

Privacy risks of spatio-temporal data transformations

In recent years, we witness a great leap in data collection thanks to increasing number of mobile devices. Millions of mobile devices including smart phones, tablets and even wearable gadgets embedded with GPS hardware enable tagging data with location. New generation applications rely heavily on location information for innovative business intelligence which may require data to be shared with third parties for analytics. However, location data is considered to be highly sensitive and its processing is regulated especially in Europe where strong data protection practices are enforced. To preserve privacy of individuals, first precaution is to remove personal identifiers such as name and social security number which was shown to be problematic due to possible linking with public data sources. In fact, location itself may be an identifier, for example the locations in the evening may hint the home address which may be linked to the individual. Since location cannot be shared as it is, data transformation techniques have been developed with the aim of preventing user re-identification. Data transformation techniques transform data points from their initial domain into a new domain while preserving certain statistical properties of data. In this thesis, we show that distance-preserving data transformations may not fully preserve privacy in the sense that location information may be estimated from the transformed data when the attacker utilizes information such as public domain knowledge and known samples. We present attack techniques based on adversaries with various background information. We first focus on spatio-temporal trajectories and propose an attack that can reconstruct a target trajectory using a few known samples from the dataset. We show that it is possible to create many similar trajectories that mimic the target trajectory according to the knowledge (i.e. number of known samples). The attack can identify locations visited or not visited by the trajectory with high confidence. Next, we consider relation-preserving transformations and develop a novel attack technique on transformation of sole location points even when only approximate or noisy distances are present. We experimentally demonstrate that an attacker with a limited background information from the dataset is still able to identify small regions that include the target location points

Privacy leaks in spatio-temporal trajectory publishing

Trajectories are spatio-temporal traces of moving objects which contain valuable information to be harvested by spatio-temporal data mining techniques. Applications like city traffic planning, identification of evacuation routes, trend detection, and many more can benefit from trajectory mining. However, the trajectories of individuals often contain private and sensitive information, so anyone who possess trajectory data must take special care when disclosing this data. Removing identifiers from trajectories before the release is not effective against linkage type attacks, and rich sources of background information make it even worse. An alternative is to apply transformation techniques to map the given set of trajectories into another set where the distances are preserved. This way, the actual trajectories are not released, but the distance information can still be used for data mining techniques such as clustering. In this thesis, we show that an unknown private trajectory can be reconstructed using the available background information together with the mutual distances released for data mining purposes. The background knowledge is in the form of known trajectories and extra information such as the speed limit. We provide analytical results which bound the number of the known trajectories needed to reconstruct private trajectories. Experiments performed on real trajectory data sets show that the number of known samples is surprisingly smaller than the actual theoretical bounds

THE INVESTIGATION OF QUALITY INDICATORS OF INDIVIDUALIZED EDUCATION PLAN PREPARED IN PUBLIC SCHOOLS

Individualized Education Program (IEP) is an important element in the Turkish Education system since it aims students with disabilities to get a systematic, measurable and on point education. Thus, preparation, implementation, and evaluation of the IEP play a critical role for students with disabilities, their parents, and professionals. Researchers conducted studies and provided suggestions to improve the quality of IEPs. However, in the literature, there was not any evaluation tool for the IEP. The purpose of this study is to create an evaluation tool for IEPs, and based on this tool, to measure the quality of prepared IEPs in Turkey. In this study, descriptive analysis was used. The findings demonstrated serious deficiencies in the components of IEPs. Based on that, the researchers provided suggestions to enhance the quality of IEPs.  Article visualizations

Efficacy of the greater occipital nerve block in recurrent migraine type headaches

Aims We aimed to evaluate six months of results following repeated GON blocks. Methods We evaluated the results from GON block performed on 60 patients. Briefly, we applied a standard 2mL of 0.5% Bupivacaine GON blockage once a week for 4 weeks. We recorded the Visual Analog Scale (VAS) scores, the number of migraine attacks and the Migraine Disability Assessment Questionnaire (MIDAS) scores. The study subjects were not allowed to use medication for prophylaxis, and Ibuprofen (400mg, 1200mg at maximum) was prescribed for any migraine attacks. Results The initial mean number of attacks per month before starting treatment was 8.33+2.31. After treatment, the initial MIDAS mean was found to be 2.82 per month; this declined to 1.47 in 3rd, and was 1.50 in the 6th month. The individual month values were found to be significant, and were listed respectively as, 1st month: 3.95+2.52, 2nd month: 3.23+1.82, 3rd month: 2.60+1.90, 4th month: 2.68+2.10, 5th month: 2.58+1.90 and 6th month: 2.58+1.90. The mean VAS scores were recorded as follows for each month: 6.28±1.24, 3.13±0.97, 2.55±1.19, 2.35±1.26, 2.38±1.20 and 2.48±1.30, respectively. This difference was noted to be statistically significant. No difference regarding the efficacy of the treatment was determined when the results were compared across age groups. Conclusion We assume that GON blockage with 2mL of 0.5% Bupivacaine can be a supportive treatment in migraine treatment, with no serious adverse effects reported

High performance electrocatalysts supported on graphene based hybrids for polymer electrolyte membrane fuel cells

In this study, new electrocatalysts for PEM fuel cells, based on Pt nanoparticles supported on hybrid carbon support networks comprising reduced graphene oxide (rGO) and carbon black (CB) at varying ratios, were designed and prepared by means of a rapid and efficient microwave-assisted synthesis method. Resultant catalysts were characterized ex-situ for their structure, morphology, electrocatalytic activity. In addition, membrane-electrode assemblies (MEAs) fabricated using resultant electrocatalysts and evaluated in-situ for their fuel cell performance and impedance characteristics. TEM studies showed that Pt nanoparticles were homogeneously decorated on rGO and rGO-CB hybrids while they had bigger size and partially agglomerated distribution on CB. The electrocatalyst, supported on GO-CB hybrid containing 75% GO (HE75), possessed very encouraging results in terms of Pt particle size and dispersion, catalytic activity towards HOR and ORR, and fuel cell performance. The maximum power density of 1090 mW cm(-2) was achieved with MEA (Pt loading of 0.4 mg cm(-2)) based on electrocatalyst, HE75. Therefore, the resultant hybrid demonstrated higher Pt utilization with enhanced FC performance output. Our results, revealing excellent attributes of hybrid supported electrocatalysts, can be ascribed to the role of CB preventing rGO sheets from restacking, effectively modifying the array of graphene and providing more available active catalyst sites in the electrocatalyst material.(C) 2018 The Authors

Diversity and ethics in trauma and acute care surgery teams: results from an international survey

Background Investigating the context of trauma and acute care surgery, the article aims at understanding the factors that can enhance some ethical aspects, namely the importance of patient consent, the perceptiveness of the ethical role of the trauma leader, and the perceived importance of ethics as an educational subject. Methods The article employs an international questionnaire promoted by the World Society of Emergency Surgery. Results Through the analysis of 402 fully filled questionnaires by surgeons from 72 different countries, the three main ethical topics are investigated through the lens of gender, membership of an academic or non-academic institution, an official trauma team, and a diverse group. In general terms, results highlight greater attention paid by surgeons belonging to academic institutions, official trauma teams, and diverse groups. Conclusions Our results underline that some organizational factors (e.g., the fact that the team belongs to a university context or is more diverse) might lead to the development of a higher sensibility on ethical matters. Embracing cultural diversity forces trauma teams to deal with different mindsets. Organizations should, therefore, consider those elements in defining their organizational procedures. Level of evidence Trauma and acute care teams work under tremendous pressure and complex circumstances, with their members needing to make ethical decisions quickly. The international survey allowed to shed light on how team assembly decisions might represent an opportunity to coordinate team member actions and increase performance

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements