Investigation of the Relationships and Effects of Urban Transformation Parameters for Risky Structures: A Rapid Assessment Model

Most of the works on the literature on urban transformation focus on the outcomes of transformation in legal, psychosocial, socioeconomic, and geographical aspects; and employ rapid screening models to assess the areas and multiple structures subject to urban transformation. Aiming the contribute to the literature, this study investigates the causal relationships between the parameters used in risk assessment of the individual masonry structures undergoing transformation. The causal relationship, which expresses the cause-effect relationship between two variables, shows that the independent variable has a direct or indirect effect on the dependent variable. The results of statistical analysis and theory should be considered concurrently in building a causal relationship model. The structural assessment reports for risky structures of 183 individual masonry buildings were examined and the relationships between the dependent and independent variables were assessed using path analysis. In order to establish a rapid assessment technique for risk assessment, the variables were chosen by binary logistic regression analysis due to the discrete nature of the dependent variable, and the final model was built accordingly. According to the model analysed by binary logistic regression, direct and indirect effects between the variables were determined using path analysis. While path analysis is applied to continuous data and evaluates linear regression results, an evaluation was performed based on logistic regression with discrete data results in this study. According to the path model analysis, the city where the building was located had the largest direct effect (path coefficient). It was concluded that the model, built with 6 effective variables selected among 25 independent variables generating the risk result, was acceptable in terms of engineering, and the proposed rapid assessment model could be used for risk assessment because of its high correct classification rate

Türkçe Haber Metinlerinin Makine Öğrenmesi Yöntemleri Kullanılarak Sınıflandırılması

En büyük bilgi kaynağının internet olarak kabul edildiği günümüz bilgi çağında, elektronik ortamda yer alan metinlerin gün geçtikçe artması sonucunda metin madenciliği ve makine öğrenimi konusu önem kazanmıştır. Teknolojinin gelişmesine paralel olarak bu alanlarda da yenilikler geliştirilmektedir. Yapılan yenilikler ile herhangi bir platformda düzensiz olarak bulunan metinlerin, anlamlı bir bütün haline getirilerek sınıflandırılması ihtiyacı doğmaktadır. Bu çalışmada; farklı makine öğrenmesi yöntemleri kullanılarak Türkçe haber metinlerinin sınıflandırması yapılmaktadır. Haber içerikleri olarak birçok haber metninin ve haber kategorisinin yer aldığı bir veri seti kullanılmıştır. Çalışmada, Destek Vektör Sınıflandırıcısı, Rastgele Orman ve Naive Bayes Sınıflandırıcına göre gerçekleştirilen analiz sonuçları karşılaştırılarak, en başarılı performansa sahip yöntemin 91% doğruluk oranı ile Naive Bayes Sınıflandırıcısı olduğu görülmüştür.In today's information age, where the largest source of information is accepted as the internet, the issue of text mining and machine learning has become important as a result of the increasing amount of texts in the electronic environment. In parallel with the advancement of technology, innovations are being developed in these areas. Due to the innovations, the need arises to classify the texts found irregularly on any platform into a meaningful whole. In this study; Turkish news texts are classified using different machine learning methods. A data set containing many news texts and news categories was used as news content. In the study, comparing the analysis results performed according to the Support Vector Classifier, Random Forest and Naive Bayes Classifier, it was seen that the method with the most successful performance was the Naive Bayes Classifier with 91% accuracy.</p

Analysis the Path of the Light in the Optical Waveguide withQuadratic Graded Index by Using Simple ApproximationMethod

Optical waveguides are photonic circuit elements where the light is guided inside. These photonic elements require a transparent medium that the refractive index of the layer is higher than that of the surrounding material. Optical waveguides usually consist of two parts. The inside part is called as core has high refractive index The second part is called as cladding with lower refractive index surrounded the core. Guiding property of optical waveguides are based on the principle of total reflection of light from planar dielectric interfaces. This property of optical waveguides is defined by some structure parameters. Since the refractive index of optical waveguides decreases from the core center to cladding gradually, the refractive index changing of optical waveguides with graded index should be taken into consideration. In this study, behavior of light is analyzed by the parameter changing of optical waveguides. Eikonal equation is used to determine the trajectory of the light. Determination of the trajectory of the light is useful for the explanation of guiding in these waveguides.

MULTI-CRITERIA DECISION MAKING FOR CEMENT MORTAR MIXTURE SELECTION BY FUZZY TOPSIS

Cement mortar mixture consists of different materials as the content. The materials which make up this mixture and the selection of this mixture have a vital proposition for the constructions in which this mixture is used. In this selection process, it is very complicated to decide which one material and how to use in the selection. Fuzzy decisionmaking theory is a very useful method that can be used in such decision-making problems. In this study, it was preferred to use the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method to find the best cement mortar mixture. For this purpose, the optimum sorting was done for 40 alternatives using five criteria. These five criteria used are; The age of the samples (days), fly ash (FA), silica fume (SF), compressive strength (MPa) and ration of FA+SF mixtures. As a result, this study shows that the presented fuzzy TOPSIS model is able to effectively evaluate fuzziness in the multi-criteria decision process.Çimento harcı karışımı, içerik olarak farklı malzemelerden oluşmaktadır. Bu karışımı oluşturan malzemeler ve bu karışımın seçimi, bu karışımın kullanıldığı yapılar için hayati öneme sahiptir. Bu seçim sürecinde hangi malzemenin seçileceğine ve nasıl kullanılacağına karar vermek çok karmaşıktır. Bulanık karar verme teorisi, bu tür karar verme problemlerinde kullanılabilecek çok kullanışlı bir yöntemdir. Bu araştırmada, en iyi çimento harcı karışımını bulmak için bulanık TOPSIS yönteminin kullanılması tercih edilmiştir. Bu amaçla, beş kriter kullanılarak 40 adet alternatif için ideal sıralama yapılmıştır. Kullanılan bu beş kriter; numunelerin yaşı (gün), uçucu kül (FA), silis dumanı (SF), basınç dayanımı (MPa) ve FA + SF karışımları oranıdır. Sonuç olarak, bu çalışma sunulan bulanık TOPSIS modelinin çok kriterli karar sürecinde belirsizliği etkili bir şekilde değerlendirebildiğini göstermektedir