2-D iteratively reweighted least squares lattice algorithm and its application to defect detection in textured images

In this paper, a 2-D iteratively reweighted least squares lattice algorithm, which is robust to the outliers, is introduced and is applied to defect detection problem in textured images. First, the philosophy of using different optimization functions that results in weighted least squares solution in the theory of 1-D robust regression is extended to 2-D. Then a new algorithm is derived which combines 2-D robust regression concepts with the 2-D recursive least squares lattice algorithm. With this approach, whatever the probability distribution of the prediction error may be, small weights are assigned to the outliers so that the least squares algorithm will be less sensitive to the outliers. Implementation of the proposed iteratively reweighted least squares lattice algorithm to the problem of defect detection in textured images is then considered. The performance evaluation, in terms of defect detection rate, demonstrates the importance of the proposed algorithm in reducing the effect of the outliers that generally correspond to false alarms in classification of textures as defective or nondefective

Markiz Pastanesi açıldı

Taha Toros Arşivi, Dosya No: 112-Lokantalarİstanbul Kalkınma Ajansı (TR10/14/YEN/0033) İstanbul Development Agency (TR10/14/YEN/0033

The Study of ZnSnN2 for possible Thermoelectric and Photovoltaic Applications

In order to replace semiconductors that rely on rare Earth and costly elements, the search for analogous semiconductors formed by plentiful elements began. A recently developed material, ZnSnN2, is the analog to InN. In this project, the Seebeck and Hall effects are measured along with the electrical conductivity. The carrier concentration can then be determined from the Hall coefficient. Using the method of four coefficients and a general theory of these properties, the bounds on effective mass are determined corresponding to the different possible scattering parameters. The results show that samples with carrier concentrations around 6-9Å~10 19 cm-3 exhibit properties consistent with the model, but not samples with a higher concentration of 1.02Å~10 21 cm-3

The Thermoelectric and Transport Properties of ZnSnN2

Zinc Tin Nitride (ZnSnN2) is the II-IV-V2 semiconductor analog to the III-V Indium Nitride (InN), and the two are predicted to have similar properties that make them attractive for thermoelectric and photovoltaic applications. Replacing the costly and rare indium with more Earth-abundant and inexpensive zinc and tin makes ZnSnN2 a potentially valuable alternative to InN. In this work, the temperature dependence of the Seebeck coefficient, Hall coefficient, and electrical resistivity were measured in a range of 7-300K. The Hall and resistivity measurements enabled the determination of Hall mobility and carrier concentration. Using the solutions to the Boltzmann transport equations in the relaxation time approximation and assuming a parabolic band, bounds on density of states effective mass are determined corresponding to different possible electron scattering mechanisms. The results show that samples with carrier concentrations around 6-9×10 19 cm-3 exhibit properties consistent with the model, but not samples with a higher concentration of 1.02×10 21 cm-3

Discussion networks in Turkey: a social capital approach to informal social relations

The present study inquires into the informal social network underpinnings of generalized trust in Turkey. For this purpose, it utilizes survey data on Turkish discussion networks. The findings show that informal social relations in Turkey are mostly composed of nonkinship relations, which serve as an important bridge across diverse social groups. The socio-economic cleavages of age and education, however, are found to be important filters through which both kinship and non-kinship relations influence generalized trust. Overall, the analysis affirms the relationship between individuals’ socialization experiences and generalized trust. However, the influence of diverse social relations is not uniform and is much more complicated than is hypothesized in the social capital literature.No sponso

Civic space in Turkey: a social capital approach to civil society

The present study explores civil society organizations’ (CSOs) civic and political potential in Turkey. For this purpose, it generates original data from Antalya and utilizes social network analysis to analyze the CSOs’ cooperation structure. The analysis points out certain levels of dynamism and diversity in terms of the CSOs’ cooperative connections. Yet it also shows variance between the publicgoods oriented Putnam-type CSOs and the special-interest oriented Olsontype CSOs in terms of their civic and political potential. This observed variance, in turn, is likely to influence their respective potential to articulate common interests on the one hand, to affect politics on the other hand.No sponso

Beyond the institutional logics: international level systemic analysis of EU-Turkish relations

This article aims to explain the slowing down of European Union (EU)–Turkish relations since the start of the accession negotiations in 2005 with international level systemic analysis. For this purpose, it examines the current challenges the new rising powers pose to the US-led unipolar international order and it shows how both the EU’s and Turkey’s responses to these challenges influence their relative powers as well as the negotiation process. By focusing on international level systemic dynamics, the article differs from the institutional explanations that explain EU–Turkish relations either with the utility-based logic of consequentialism or the norms-based logic of appropriateness.No sponso

Imaging measurements of soot particle size and soot volume fraction with laser-induced incandescence at Diesel engine conditions

Cotutelle de thèse This work focuses on measurements of soot particle size and volume fraction at Diesel engine conditions. A combination of laser-induced incandescence (LII) imaging, line-of-sight laser extinction, soot pyrometry, and transmission electron microscopy (TEM) measurements of thermophoretically-sampled soot was used. Particle sizing strategies were developed with LII model for the analysis of particlesize poly-dispersity with time-resolved LII signal that is suitable for point-wise measurements at atmospheric pressure, and for spatially-resolved characterization with two-time-step LII imaging. Measurements were performed with these strategies in a flame at atmospheric pressure and in Diesel engine combustion to investigate their applicability. Additional measurements were performed for temperature and soot volume fraction. A novel method, called two-exponential reverse fitting (TERF), is introduced to extract information about the size distribution. The method is based on mono-exponential fits to the LII signal decay at a delayed time. It approximates the particle-size distribution as a combination of one large and one small mono-disperse equivalent mean particle size and does not require a distribution assumption. It also provides a ratio of the contribution of both size classes. The systematic error caused by describing LII signals by mono-exponential decays was calculated as less than 2% for LII signals simulated for mono-disperse aggregated soot with heat-up temperatures for which evaporation is negligible. The method was applied to LII data acquired in a laminar non-premixed ethylene/air flame at various heights above the burner. The particle size of the large particle-size class evaluated with the method showed good consistency with TEM results, however the size of the small particle-size class and its relative contribution could not be compared due to insufficient information in the TEM results for small particles. Simultaneous line-of-sight laser extinction measurements and LII imaging were performed to derive the soot volume fraction in a high-temperature high-pressure constant-volume pre-combustion vessel under the Engine Combustion Network’s (ECN) "Spray A" conditions with parametric variations of gas temperature and composition. Extinction measurements were used to calibrate LII images for quantitative soot distribution measurements. OH-chemiluminescence imaging was used to determine the lift-off length, and used to interpret the soot measurements. Maximum soot volume fractions around 2–3 ppm were obtained at the nominal ambient temperature defined for Spray A (i.e. 900 K) that rise to 12 ppm at elevated temperature (1030 K). Variations of ambient temperature and oxygen concentration were carried out showing effects on soot formation and oxidation that are consistent with the literature. The method for particle-size imaging is based on evaluating gated LII signals acquired with two cameras consecutively after the laser pulse and using LII modeling to deduce particle size from the ratio of local signals. A strategy was developed with a model-based analysis: the dependence of LII particlesize imaging on the assumed boundary conditions was identified such as bathgas temperature, pressure, particle heat-up temperature, thermal accommodation coefficients, and soot morphology. Various laser-fluence regimes and gas pressures were considered. Effects of laser attenuation were evaluated. A combination of one detection gate starting with the particle-heating and the other starting with 11 ns delay with twice as long gate width was found to provide the highest sensitivity for particle sizing at 60 bar. The optimum gate delays for different pressures were calculated. The effects of timing jitter for laser pulse and poly-dispersity were investigated. Systematic errors in pyrometry imaging at 60 bar was evaluated. Parallel to the model-based analysis, experiments were conducted in near Spray A conditions with parametric variations of injection pressure, gas temperature and composition. The results were compared to particle-size measurements from TEM of soot sampled at multiple axial distances from the injector. The discrepancies between the two measurement techniques are discussed to analyze uncertainties and related error sources of the two diagnostics methodologies. It is found that in such an environment where particles are small and pressure is high, LII signal decay times are such that LII suffers from a strong bias towards large particles

Development Education in Theory and Practice: An Educator's Resource

Over the course of three years, the UNIDEV project sought to promote youth awareness and engagement with the MDG (Millennium Development Goals) and post-2015 frameworks in universities in Cyprus, Slovakia and Ireland. The partners undertook a range of activities as part of the programme. The idea for this resource arose out of a desire to develop specific development education materials that would target the new EU member state sector, and which would bring something new to the significant stock of development education resources already available. To this end, instead of providing just another book on general development education topics, the aim was to address contemporary development issues with a focus on the needs of educators in the new EU member states, as well as drawing material from contributors in those countries. The hope is that this book will be used by academics, researchers, NGO practitioners and students as part of development education work to further their understanding of key development issues facing the global community, and more so, to encourage citizen action to bring about a fairer more equitable world. The book covers twelve themes, each chapter includes both a conceptual overview and a teaching methodology section. The conceptual overview introduces the topic, explores the key concepts, theories and current debates. The teaching methodology section offers educators a set of tools that could help them introduce the topic in both formal and non-formal settings

A Granular-based Approach for Semisupervised Web Information Labeling

A key issue when mining web information is the labeling problem: data is abundant on the web but is unlabelled. In this thesis, we address this problem by proposing i) a novel theoretical granular model that structures categorical noun phrase instances as well as semantically related noun phrase pairs from a given corpus representing unstructured web pages with a variant of Tolerance Rough Sets Model (TRSM), ii) a semi-supervised learning algorithm called Tolerant Pattern Learner (TPL) that labels categorical instances as well as relations. TRSM has so far been successfully employed for document retrieval and classification, but not for learning categorical and relational phrases. We use the ontological information from the Never Ending Language Learner (Nell) system. We compared the performance of our algorithm with Coupled Bayesian Sets (CBS) and Coupled Pattern Learner (CPL) algorithms for categorical and relational labeling, respectively. Experimental results suggest that TPL can achieve comparable performance with CBS and CPL in terms of precision.Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant 194376.Master of Science in Applied Computer Scienc